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harpagornis · 1 year
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Enantiornithean Earth
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Yungavolucris and Halimornis by midiaou and xenopleurodon respectively. Both are real life Cretaceous taxa, showing that these birds were already diversifying into aquatic ecologies.
Enantiornithes are a group of extinct flying theropod dinosaurs that you could reasonably call birds, being the sister group of Euornithes (the group that includes modern birds). However, they differ from our birds in a variety of ways (their name literally means “opposite birds” for a reason):
Several skeletal details, including a tarsometatarsus that is either unfused or half-fused (beginning at the top rather than at the bottom, the opposite than in modern birds), an articulation of the scapula and coracoid that is oppositely shaped (hence the name; the coracoid joint is convex and the scapula joint is concave shaped in enantiornitheans, while the opposite happens in modern birds), a shallower sternum keel with bizarre antler-like projections (which, combined with large crests in their humerus, suggests the muscles lifting the wing were attached to the back as in bats and pterosaurs, rather than all flight muscles being attached to the keel as in modern birds), and a large, rod-shaped pygostyle (which will be relevant later).
Usually toothed jaws instead of beaks, though some taxa did become toothless. Even then, these weren’t capable of cranial kinesis like modern birds (i.e. watch a duck or your pet parrot yawn and you can see them moving their upper jaw; enantiornitheanss are many things but they’re not that abominatory).
All known taxa thus far seem to have been superprecocial: ample sites show buried eggs like those of megapodes, and the hatchlings were already fully flight capable soon after birth.
Unlike modern birds, enantiornitheans lacked a tail fan. They either had contour feathers on their butt like in the rest of the body or had long, streamer-like display feathers, also found in other Cretaceous bird groups but not in modern birds. Some species did have retrices, but they were arranged along the rod-like pygostyle and were not a movable fan, so essentially they were a variation of the tail fronds seen in Archaeopteryx and kin. Note that this did not make flight harder; even modern birds can fly reasonably well without a tail.
Why the opposite birds died out at the end of the Mesozoic while ours survived is unclear. Often, a bias towards arboreal niches is cited, as many enantiornitheans were in fact arboreal, but as the examples above show they also occured in marine and terrestrial niches alongside the ancestors of modern birds. Another possibility is their supreprecocial habits, meaning a more complex ecology as the birds matured since they were already functionally independent since birth, and this did hinder reptiles like lizards so the answer might lay there.
Or, most likely, it was just dumb luck.
Anyways:
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Senmuruy hvare by Dave García. A four meter wingspan predator vaguely analogous to the golden eagle and cinnereous vulture, soaring across the northern hemisphere for corpses to dig its long snout into or live mammals and birds to sink its talons into.
Many Cretaceous enantiornitheans were already suspected of being raptorial, so it is only natural that, once pterosaurs were gone, they’d increase in size. Some reach wingspans of fiver meters, but most are more moderately sized at 1.5-3 meter adult wingspans. Smaller sizes are handled by the young, which like all enantiornithes can already fly since birth and occupy distinct ecological niches. Most species protect the nest and moderate its temperature like our megapodes, and a few even display mild parental care, allowing the young to remain in the vicinity until they’re large enough to be competition.
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Euodontopteryx anatosuchus, a six-meter wingspan pelagic soarer that occurs in tropical and temperate waters, using its massive wings to ride on thermals like frigatebirds while landing to feed like albatrosses. Males sport streamer-like display feathers. By Dave García.
As noted above, some Cretaceous enantiornitheans were already aquatic, so this trend continued. Some species became divers, mostly wing propelled and some even flightless like our penguins, while others inversely invested in supreme gliding abilities, able to either ride thermals like frigatebirds or wave winds like albatrosses.
The most impressive species are reccord beaters. Divers can be as tall as a man when on land, while soarers can reach wingspans of over 7 meters, competing with flying multituberculates for largest living flying animals. Both groups tend to have long, toothy maws, the teeth alloted into a single row rather than individual sockets; this condition is known in both extinct sea birds and reptiles as well as some living cetaceans, and is known as aulacodonty.
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Ghaltavis rex, a three meter tall predator that stalks African and Asian savannas. An apex predator of its own right, an echo of the distant unrelated tyrannosaurs in the form of a bird. By Dave García.
At least one real life enantiornithean, Elsornis, appears to have been flightless. It’s descendents were quick to occupy roles previously taken by non-avian theropods, from ratite-like herbivores to formidable predators that look like the fusion of a terror bird and a tyrannosaur, using their powerful jaws to crush bone.
The relatively long enantiornithean pygostyle allowed them to balance their pelvis/femur joints (a known size inhibittor in our birds) and grow to sizes larger than our timeline’s birds, though species above a ton are fairly rare seeing as mammals got their footing as well.
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Bennu seti, a filter-feeding bird from Africa, Eurasia and Australia. Like flamingos it metabolizes carotenoids, giving it an orange colouration. By Dave García.
The Cretaceous Lectavis had long legs in some aspects convergent with those of flamingos. Thus, several enantiornitheans developed wading ecologies, ironically more associated with their euornithean competitors. Some became probers, dipping their maws (or toothless beaks) into the subtrate, while others became piscivores like herons or aquatic plant specialists like some cranes and magpie geese.
Most spectacular is a filter-feeding clade, Bennuidae. These birds modified their teeth into thin, delicate strands like some Cretaceous pterosaurs, and feed by swallowing water and expelling it, trapping prey in the teeth and keratinous spikes in the tongue. Having the nostrils still at the end of the snout, these birds usually feed in a different position from flamingos: rather than upside down, the lower jaw is submerged, in a manner similar to avocets.
Like most opposite birds the young are superprecocial, starting as plover-like birds before transitioning into a filter feeding lifestyle months later. Though some taxa form protective creches like flamingos, though unlike them they do not feed the young.
Like many of our shorebirds, these are continuous flappers, displaying remarkable endurance as they fly non-top for days in their migrations.
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knithappens05 · 1 year
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FAQ / Cheat Sheet
Name: Moira Mercia-Ward (AKA: Mo-Mo, Sweater Girl)
Species: Human (w/ Alpha Gene)
Playbook: Scion
Alpha Ability: Thread-Kinesis
Pronouns: She/Her
Age: 15 (Currently 2021 in-game)
DOB: June 24, 2005 (Cancer Sun, Pisces Moon, Virgo Rising)
Height: 5'4"
Hair: Brown
Eyes: Brown / Black and gold on power-activation
Sexuality: Pansexual
Mother: Malena Mercia (Greek)
Father: Winston Ward (Black)
Other Relatives: Melita Mercia (Aunt)
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In-Character Playlist
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Who is this character? This is Moira Mercia-Ward, a first year (sophomore) at Alpha King Academy! She was part of an accidental late admission group with her four best friends, Achara Singhaboon, Colt Arvidsson, Diarmuid O'Ceallaigh, and Will Smalls. Later they met Kid Condor, and the six of them were dragged into an intensely dangerous mystery revolving around a fellow student murdered in his dorm room.
FASCINATING, I WISH TO KNOW EVERYTHING! Oof. That's a tall ask. This game spanned nearly 2 years and a lot happened, most of our sessions were 12+ hours, weekend-long affairs. I'm happy to share specifics via the ask function, but I'm afraid a novelization is out of the question. |D
What is Moira's Alpha ability (power)? Mastermind and I call it "Thread Kinesis"--basically thread-movement. Moira often wears sweaters or clothing with laces, she can unravel/unlace these things and use them to constrict opponents, cushion blows, rappel and swing, grab objects, etc. as long as she's in physical contact with what she's controlling. More recently Will Smalls developed a set of twelve magnetic metal plates with holes, to allow Moira to weave her own shields and plate metal. Or create pretty vicious swinging-mace weaponry. Robots beware......
Dang that sounds wild. Can she only control yarn and laces? For the moment, that's what she can control most easily. During the endgame, she was able to control wires for a moment but it created great physical strain. Someday she may be on the same level as her mother (she's able to control wires as well as clothing without being in physical contact, making it unsettlingly easy for her to restrain and constrict anyone who happens to be, you know, dressed).
Why the hyphenated last name? I'm so glad you asked... Moira is the only daughter of Winston Ward and Malena Mercia. Malena happens to have the same power as Moira, in fact this power has passed itself along the female offspring for generations (Malena will say that they're descended from the Moirae, the Fates, themselves, though Moira is extremely skeptical for obvious reasons). Both of her parents being progressive, Moira's last name was hyphenated to "preserve" the Mercia name.
Moira's mom sounds a little intense... Is she okay? Absolutely not. Malena Mercia was an activist for a time, but her methods became more and more extreme until she was classified as a villain. She called herself "Filanesse" as a kind of bitter joke-- if she was going to be villainized for simply doing what had to be done to hold bad people responsible, she would gladly take up the mantle of a 'villainess' (Fil, filament, look I'm very symmetrical it's fine). Eventually when Moira was 10, Malena was defeated by Thunder Solomon (leader of The Vanguard, a prominent superhero team) and arrested for various vigilante-villain activity and killing a security guard. Malena was sent to Alpha Max-- maximum security for people with Alpha abilities-- for a long time. Moira visited for a few years when she still didn't quite understand the extent of what had happened, but eventually asked Winston if she could stay home when he visited Malena. Moira's confusion and grief turned into anger over being essentially abandoned because her mother killed someone using their power. Teenagers, right?
Dang! So has Moira seen her since she stopped visiting the prison? You think she managed to keep that bit of her traumatic history private for two years of gameplay? HA! The trail of the dead student led back to Malena, so Moira had to visit her in Alpha Max. The first time was an emotional disaster, Moira running out of the prison after the visit having a full-blown panic attack. The second time she went, there was a prison break and Malena escaped to join the Big Bad Evil Guy in their plot. Malena kept reappearing and trying to get Moira to come to her side, but Moira was still simultaneously furious and pleading with her mother to just take responsibility for what she'd done and go back to prison. It didn't go over well. At the end of the season, Malena nearly killed Moira and her sister Melita in a blind rage and disappeared when she realized how far she'd gone.
...She has a sister? A twin sister in fact! Melita Mercia, who helped raise Moira. Melita is the youngest and participated in the Filanesse-identity, using her power in tandem with Malena's to make the villain seem even more formidable and powerful. It also helped them evade capture by authorities for a time, Filanesse always seemed to be able to outmaneuver whoever was chasing her, be wherever she needed to be in a moment. The three of them, Melita, Malena, and Moira, spent most of Moira's childhood together, raising her to feel strong and proud in her femininity. They were their own 'coven', for lack of a better word, and when Malena was arrested Melita disappeared, leaving Moira without her support network.
What about Winston though? Winston is a great dad! He's a public defender and works hard to support Moira with his single income. Which means often he wasn't around when Moira got home from school and often came home to eat, sleep, and change his clothes. He's a very supportive parent and wants to protect Moira from everything-- sometimes even from her own and his own feelings. They didn't really discuss Malena's arrest, and so their house was fairly quiet, dark, and sad from the tension and forced-cheerleading on Winston's part. He absolutely did his best, but Moira's life had a huge crater in it where her support network used to be. It's a tall task to fill it when you're already burning the candle at both ends and in the middle to make ends meet.
What's Moira like at school? In the beginning, Moira was very guarded and reserved. The Alpha Identity Protection Act (AIPA) is supposed to seal names and records of active superheroes and villains so their families don't get caught up in their personas, however many heroes still have access to that information. Moira spent the first few months guarding the fact that her mother is a convicted villain with everything she had in her, and it made her seem quiet, awkward, constantly nervous, and blank. In reality so much of her was caught up in her parentage, in the fear that she would someday lose her sanity and kill someone with her power like her mother did, that she stopped moving forward and growing. Pain was comfortable and familiar, building a new self that was separate from Malena and Melita was new and scary--so she didn't do it until the events of the game more or less forced her to confront the realities of her situation and start developing again. She's highly artistically-minded (she has a tree on campus that she regularly yarn-bombs to work out her feelings), she's practical while still being subject to emotional swings and panic attacks, she's highly protective to the point where she's thrown herself in front of real physical harm to protect her friends thinking 'I guess I'm just going to get hurt, this is how it goes'. She gets a little sarcastic if she feels unheard, inconvenienced, or taken advantage of, lightly gives her friends shit when she senses buffoonery, is highly sensitive to how people might be feeling even if she doesn't always know what to say, and is absolutely not above tying the school bully's shoelaces together under the lunch table if he's picking on her friend. As a random, non-specific example......... 8D
(I'm sorry you guys, if you're here, you're going to have to deal with my dumb shipping-- Moira tied Hunter Solomon's shoelaces together when he started picking on Will. Yes, Hunter, the son of Thunder Solomon, the woman who brought Malena down. This shit just writes itself, it's not my fault.)
How does she feel about her friends? Well she very nearly died fighting alongside them, they've absolutely become her new support network. Not the same as what she had with Malena and Melita, but enough for her to feel loved and free to explore the person she's becoming. She's probably closest with Will and Diarmuid, who both really supported her through her identity and mental health journeys. She has great admiration for Kid Condor, and a massive crush on him (he was the first who found out who her mother was and opened up to her about his own less-than-stellar childhood parentage). Achara is her roommate, and while Moira is organizing her scrapbooking supplies Achara is staying up all night playing video games. They couldn't be more different and that initially gave Moira serious pause, but their relationship is growing. Moira and Colt still don't see eye-to-eye, the two of them seem to keep missing each other. However Moira would absolutely have his back in any situation, just because they aren't best buddies doesn't mean she doesn't want what's fair and good for him.
What about a special someone, eh ehhhh?? Currently Moira is building a potential relationship with a second year named Xiomara. She was asked to the Winter Formal by Xiomara and spent most of her time worrying and feeling like she was leading her on by not telling Xiomara who her mother was. She sees what her mother did to Winston's life and doesn't want to do that to a partner. Feelings that are actually reciprocated have been on a very far back burner while dealing with everything else in her life, but she's starting to unclench and give things an honest chance.
So Moira likes boys AND girls? She likes everybody if given half an excuse. She's a little stunted now, but I imagine when she gets to college she goes pretty partner-wild.
OTP? Moira's got two hands and a lot of thread she can use to hold onto many things. I'm just saying.
What are her major themes in-game? Mental health, the power in what's traditionally thought of as 'feminine', moving past childhood trauma, finding the artist in the pragmatist, embracing parts of yourself you initially want to reject, finding greater purpose and courage when it's easier to just hide, finding your own definition of heroism, nobody is inherently "good" or "bad"-- they make choices that shape them.
Can I draw her?? I would LOVE IT. I wouldn't like anything with any intense depictions of violence/torture/sex, she's a kid after all, but I'm guilty of aging her up to write post-AKA fics so just use some good judgment I guess? She's my precious baby after all, handle with care. <3 (I say, as someone who gave her villainous heritage, mental health issues, and an unstable power...)
I really wish this was a TV show! Hey same! But it's great that our anonymous animator is making our kids move and we've gotta be happy with that! <3 Especially since adapting a 2-year-long tabletop game that means so much to us personally into some 10-episode studio-sterilized thing would be stomach-turning. Maybe one of us should work on marrying a billionaire who mysteriously falls down the stairs.
I have a question that's not here and I'm absolutely dying to know-- You can totally hit the asks! I love chattering away about this to anybody who will listen~
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spines-tvo · 10 months
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Meet Spines, the Vengeful one! (Also, Henrique.)
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This one's going to involve a lot of world building, so if you want to just skip all of the information and read the story first, scroll down until the words turn blue. This'll be a long one with a lot of words.
The world: The world is filled with magic, which people use to do essentially whatever they want. While the landmasses look the same as ours, technologies are comparable to the dark ages, and the names for places are different. Life is generally pretty good, however, it's not so when people die. There are three layers of reality; the underworld, where demons rule supreme, the midrealm, where the living are, and heaven, where the light spirits stay.
The afterlife: Back when time began, the demons had the underworld to themselves, however, the mortals eventually began to die. Now, like energy, a soul can never be destroyed, so they had to go somewhere, since the midrealm could no longer hold them. And so the souls began their pilgrimage to heaven. The light spirits knew this would happen, and they were more than happy to accommodate the mortals. Right up until they got bored. You see, the light spirits hadn't fully grasped the concept of eternity, so they saw the mortals as more of a temporary guest, eventually, they got bored and used their vast magical power to reshape the laws of death so that the mortals would be sent to the underworld instead, forcing them to the demons.
Now, demons are very territorial, and they got extremely angry at the mortals for invading their home, but most of all, at the light spirits for forcing the mortals on them. But demons are nowhere near as powerful as light spirits, so there was nothing they could do. Now they take their anger out on the mortals for all of eternity.
Lost souls: Souls that have died and then returned to life solely because they can't take the afterlife anymore. Due to their mission of "Only getting out of the afterlife" they end up losing all memory and personality.
Found souls: Found souls are very similar to lost souls. However, they return to life in order to complete a mission of some sort. They're able to retain their memories, but like lost souls, they're unable to interact with objects in ways other than indirectly.
Magic: The most used form of magic is extremely versatile. It uses the body as a sort of funnel. You can use your body to direct and channel the magic to do any one spell, such as telekinesis, pyrokinesis, basically any kind of kinesis. If you can imagine it, it's been done. However, there's another, ancient form of magic that was abandoned long ago. This magic forgoes the whole "Using your body as a funnel" part and just gathers the surrounding magic in the user's general area and launches it out at once. It was abandoned because it can be chaotic and is near impossible to control, however, it does have the advantage of being able to siphon the magic power from curses, hexes, and basically any and all forms of magic.
Spines died after accidentally getting knocked out and falling underwater. They felt no pain, but nonetheless, they died. After finding their way to the underworld, they were caught by a group of demons who planned on tormenting Spines for eternity. However, under pressure, Spines tends to make jokes, which the group of demons hadn't seen before. They misinterpreted it as finding torment hilarious which the demons related to. Spines ended up becoming almost a pet for the group of demons. Now, when demons want to protect something, they have a bit of an odd way of doing so. They like to take it apart and give it a way to protect itself. So, the demons strengthened spines with new claws, a bloodthirsty (looking) tail named Henrique (Henrique has their own mind that actually seems to want to protect Spines), and front-facing horns for easier headbutting (Which is ironic, seeing as Spines is immune to all forms of harm. Still, it's made them surprisingly attractive to the lesser demons.) In their time in the underworld, Spines learned many things, including ancient magic, which Spines could use even without a body. Spines grew to hate and despise the light spirits for what they'd done to all the mortals of the past (and to a lesser extent, what they'd done to the demons.) That desire to make the light spirits pay brought Spines back to life, and now they're trying to gather enough magic to get rid of the light spirits entirely. Watch out, though. If you get in their way, they won't hesitate to end you, too. After all, they've seen the afterlife, and spending a few years less than eternity in the midrealm seems not that big of a sacrifice.
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@tangledstrings
Kyle was a supe. He manifested quite young. And all he wanted to do was save people. Especially because no one was there to save him when he was young. And lately superheroes have seemed so corrupt despite how they tried to hide it. So many had fallen from grace. Take The Deep for example. Now it was his turn among the seven and he pledged to do everything in his power to change the corrupt system from within. The very first person he was supposed to meet was Homelander himself. So he when he was introduced in his costume which was a mix of black and purple that gave him a bit of a Shinobi look considering his abilities dealt with shadow manipulation or umbra kinesis. He could teleport between shadows and form tangible objects from them too such as weapons and constructs. He was essentially the green lantern but with shadows.
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dreams-of-cerulean · 2 years
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ANYWAY, that wasn’t what I’m trying to decide on. 
I have a skill point and five stat points. My skill tree’s been revealed, and it’s not what I expected. I’m guessing my potential’s been hampered without the Dream, since the System is only offering me three skills: Kinesis, Smite, and Blink. What’s also problematic is that they all seem to be fueled by Faith instead of Mana, thus resource management is gonna be a problem. 
The System was generous enough to let me experience each power once. 
Kinesis is a short-medium ranged telekinetic power - essentially moving things with my mind. At baseline, I can fling things as hard as a bat swing. And I can probably train it up to higher levels to improve its power and range. Problem is that leveling it up also increases its Faith cost. 
Blink is a short-ranged dash in any direction. It’s...strange. It feels like the movement part was sorta tacked on and not its intended purpose. During the dash, I temporarily turn insubstantial for a moment- I can’t be hit. But at the end, I return to normal. It also resets my momentum too. Problem is that with the max Faith I have, I can use it three times a day at best - and it’s very short-ranged like half a room’s size, around 10 feet. It does both cover more distance and get more efficient when leveled up. 
Smite, I’m not as concerned about. It allows me to imbue Faith into my blows, and before the Dream decided to be an asshat, I got very experienced at doing that with Mana. I have a pretty good feeling I could brute-force this one without that skill point, but we’ll see. 
--
So the skills to choose from are either Kinesis or Blink. I doubt I could brute-force these, given my lack of experience with either. Both are pretty versatile skills, and they each can improve my survivability in their own way. 
Decisions decisions. 
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sigmasolveinc · 8 days
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Data Engineering Trends for Maximizing Data Potential
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In today’s data-driven world, businesses are constantly seeking ways to stay ahead of the competition, make informed decisions, and create value from their data assets. Data engineering plays a pivotal role in this journey, as it involves the collection, transformation, and delivery of data to make it accessible and actionable for various stakeholders. To excel in this dynamic landscape, organizations must adopt a proactive approach to data engineering, embracing emerging trends and technologies that enable them to not just keep up but lead the way. In this article, we will explore some of the key data engineering trends that empower organizations to take a proactive stance towards their data initiatives. 
DataOps: Streamlined Data Operations 
DataOps is a methodology that aligns data engineering, data integration, and data quality practices with DevOps principles. This trend emphasizes automation, collaboration, and continuous integration and delivery (CI/CD) processes for data pipelines. By implementing DataOps, organizations can reduce development cycle times, enhance data quality, and ensure that data pipelines are robust and scalable. This proactive approach enables teams to respond rapidly to changing data requirements and deliver high-quality data products to end-users. 
Cloud-Native Data Engineering 
Cloud computing has revolutionized data engineering by providing scalable, flexible, and cost-effective infrastructure for data storage and processing. Cloud-native data engineering leverages cloud services and platforms like AWS, Azure, and Google Cloud to build and operate data pipelines. This trend enables organizations to scale their data infrastructure as needed, reduce maintenance overhead, and focus on data engineering tasks rather than infrastructure management. 
Serverless Computing 
Serverless computing is gaining momentum in the data engineering space. It allows organizations to run code in response to events without managing servers. This trend simplifies data engineering by eliminating the need to provision, scale, or maintain servers, enabling teams to focus solely on writing code and developing data pipelines. Serverless architectures also offer cost advantages as organizations only pay for the computing resources used during execution. 
Data Governance and Privacy 
Data governance and privacy are critical concerns for organizations in the age of data regulations such as GDPR and CCPA. Proactive data engineering includes implementing robust data governance practices and ensuring data privacy compliance throughout the data lifecycle. This involves data cataloging, access control, encryption, and auditing to protect sensitive information while making data accessible to authorized users. 
Real-time Data Processing 
Real-time data processing is becoming increasingly essential for organizations to make instant decisions, detect anomalies, and respond to events as they happen. Data engineering trends like stream processing frameworks (e.g., Apache Kafka, Apache Flink) and real-time data analytics platforms (e.g., Apache Spark Streaming, AWS Kinesis) enable organizations to ingest, process, and analyze data in real time, providing valuable insights and actionable information promptly. 
Data Mesh Architecture 
The Data Mesh concept is gaining traction as a way to decentralize data ownership and improve data discoverability and access. It involves breaking down data silos and treating data as a product. Proponents of Data Mesh advocate for cross-functional, autonomous data teams responsible for data domains, making data engineering more proactive by distributing responsibilities and promoting data democratization. 
Machine Learning Integration 
Machine learning (ML) and artificial intelligence (AI) are reshaping the data landscape. Integrating data engineering with ML pipelines enables organizations to leverage predictive analytics and automation for data cleansing, transformation, and anomaly detection. A proactive approach to data engineering involves harnessing Machine Learning to optimize data processes and deliver data-driven insights more effectively. 
Low-Code/No-Code Data Engineering 
Low-code and no-code platforms are simplifying data engineering tasks by allowing non-technical users to design and execute data pipelines. These platforms empower business analysts and domain experts to be more involved in the data engineering process, accelerating the development of data solutions. This trend promotes a proactive approach by reducing bottlenecks and increasing collaboration between technical and non-technical teams. 
Data Quality and Monitoring 
Proactive data engineering requires robust data quality and monitoring practices. Organizations must implement data profiling, validation, and cleansing processes to ensure the accuracy and reliability of data. Additionally, proactive monitoring and alerting systems can detect data issues in real time, enabling swift resolution and minimizing data-related disruptions. 
Automated Data Documentation 
Documenting data pipelines and datasets is essential for maintaining transparency and ensuring data lineage. Automated data documentation tools are emerging to streamline this process, making it easier for data engineers to keep track of changes, dependencies, and lineage. This proactive approach enhances data governance and facilitates compliance with regulatory requirements. 
In conclusion, a proactive approach to data engineering is essential for organizations looking to harness the full potential of their data assets. Embracing these data engineering trends enables businesses to stay ahead of the curve, respond to changing data needs, and drive innovation. By adopting DataOps methodologies, leveraging cloud-native solutions, and integrating emerging technologies, organizations can build a data engineering foundation that not only meets current demands but also positions them for future success in the ever-evolving data landscape.
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kinesisbiocare12 · 3 months
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Explore the Future of Antibiotic Medicine PCD Company in India
The future of antibiotic medicine for pharmaceutical companies in India is both promising and challenging. Antibiotic resistance, driven by overuse and misuse of antibiotics, remains a global concern. For companies specializing in antibiotic medications (PCD stands for Propaganda Cum Distribution, referring to a distribution system in the Indian pharmaceutical industry), several key aspects will shape their path:
1. Research and Development: Investment in R&D is crucial to develop new antibiotics that can combat evolving resistant strains of bacteria. Companies will need to focus on innovative drug discovery, potentially exploring new mechanisms of action or combination therapies to overcome resistance.
2. Regulatory Environment: Adherence to stringent regulations concerning antibiotic usage and production will become more critical. Stricter guidelines may impact production processes and necessitate compliance with international standards to ensure the quality and efficacy of antibiotics.
3. Public Health Awareness: Efforts to educate healthcare professionals and the public on the responsible use of antibiotics will likely intensify. This could involve campaigns promoting judicious use, emphasizing the importance of completing prescribed courses, and discouraging self-medication.
4. Technological Advancements: Incorporating advanced technologies like artificial intelligence, machine learning, and genetic engineering may aid in the discovery and development of novel antibiotics. These technologies could streamline R&D processes and enhance drug efficacy.
5. Global Collaborations: Collaborations with international organizations, research institutions, and pharmaceutical companies might facilitate the exchange of knowledge, resources, and expertise to address antibiotic resistance on a global scale.
6. Market Dynamics: The market for antibiotics may witness shifts due to the rise of alternative treatments, such as phage therapy or immunotherapy’s. Companies will need to adapt their strategies to meet evolving market demands and explore diversified portfolios beyond traditional antibiotics.
7. Environmental Impact: Efforts to reduce the environmental impact of antibiotic manufacturing processes will likely gain traction. Companies may need to adopt more eco-friendly practices to minimize the release of antibiotics into the environment, which can contribute to resistance.
Final Words
For an Indian PCD company specializing in antibiotics, navigating these challenges while capitalizing on opportunities will be essential. Diversification into research on novel antibiotics, focusing on responsible production and distribution, and aligning with global health initiatives could contribute to their success in the evolving landscape of antibiotic medicine.
If you want to start your own Antibiotic Medicine PCD Company in India with the right company, get in touch with Kinesis Biocare. We are the top antibiotic medicine PCD pharma company in India, provides top quality antibiotic medicines in the market at an affordable price.
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ryanwilliamsonstuff · 4 months
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Essential Components of a Data Pipeline
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Modern businesses utilize multiple platforms to manage their routine operations. It results in the generation and collection of large volumes of data. With ever-increasing growth and the use of data-driven applications, consolidating data from multiple sources has become a complex process. It is a crucial challenge to use data to make informed decisions effectively.
Data is the foundation for analytics and operational efficiency, but processing this big data requires comprehensive data-driven strategies to enable real-time processing. The variety and velocity of this big data can be overwhelming, and a robust mechanism is needed to merge these data streams. This is where data pipelines come into the picture.
In this blog post, we will define a data pipeline and its key components.
What is a Data Pipeline?
Data can be sourced from databases, files, APIs, SQL, etc. However, this data is often unstructured and not ready for immediate use, and the responsibility of transforming the data into a structured format that can be sent to data pipelines falls on data engineers or data scientists.
A data pipeline is a technique or method of collecting raw, unstructured data from multiple sources and then transferring it to data stores or depositories such as data lakes or data warehouses. But before this data is transferred to a data depository, it usually has to undergo some form of data processing. Data pipelines consist of various interrelated steps that enable data movement from its origin to the destination for storage and analysis. An efficient data pipeline facilitates the management of volume, variety and velocity of data in these applications.
Components Of A Scalable Data Pipeline
Data Sources: Considered as the origins of data. It could be databases, web services, files, sensors, or other systems that generate or store data.
Data Ingestion: Data must be collected and ingested into the pipeline from various sources. It would involve batch processing (periodic updates) or real-time streaming (continuous data flow). The most common tools for ingestion include Apache Kafka, Apache Flume, or cloud-based services like AWS Kinesis or Azure Event Hubs.
Data Transformation: As this data moves through the pipeline, it often needs to be transformed, cleaned, and enriched. Further, it would involve data parsing, filtering, aggregating, joining, and other operations. Tools like Apache Spark and Apache Flink or stream processing frameworks like Kafka Streams or Apache Beam are used.
Data Storage: Data is typically stored in a scalable and durable storage system after transformation. Common choices include data lakes (like Amazon S3 or Hadoop HDFS), relational databases, NoSQL databases (e.g., Cassandra, MongoDB), or cloud-based storage solutions.
Data Processing: This component involves performing specific computations or analytics on the data. It can include batch processing using tools like Hadoop MapReduce or Apache Spark or real-time processing using stream processing engines like Apache Flink or Apache Kafka Streams.
Data Orchestration: Managing data flow through the pipeline often requires orchestration to ensure that various components work together harmoniously. Workflow management tools like Apache Airflow or cloud-based orchestration services like AWS Step Functions can be used.
Data Monitoring and Logging: It's essential to monitor the health and performance of your data pipeline. Logging, metrics, and monitoring solutions like ELK Stack (Elasticsearch, Logstash, Kibana), Prometheus, or cloud-based monitoring services (e.g., AWS CloudWatch) help track and troubleshoot issues.
Data Security: Ensuring data security and compliance with regulations is crucial. Encryption, access controls, and auditing mechanisms are essential to protect sensitive data.
Scalability and Load Balancing: The pipeline should be designed to handle increasing data volumes and traffic. Horizontal scaling, load balancing, and auto-scaling configurations are essential to accommodate growth.
Fault Tolerance and Reliability: Building fault-tolerant components and incorporating redundancy is critical to ensure the pipeline continues to operate in the event of failures.
Data Quality and Validation: Implement data validation checks and quality assurance measures to detect and correct errors in the data as it flows through the pipeline.
Metadata Management: Managing metadata about the data, such as data lineage, schema evolution, and versioning, is essential for data governance and maintaining data integrity.
Data Delivery: After processing, data may need to be delivered to downstream systems, data warehouses, reporting tools, or other consumers. This can involve APIs, message queues, or direct database writes.
Data Retention and Archiving: Define policies for data retention and archiving to ensure data is stored appropriately and complies with data retention requirements and regulations.
Scaling and Optimization: Continuously monitor and optimize the pipeline's performance, cost, and resource utilization as data volumes and requirements change.
Documentation and Collaboration: Maintain documentation that outlines the pipeline's architecture, components, and data flow. Collaboration tools help teams work together on pipeline development and maintenance.
Conclusion
These components of a data pipeline are essential for working with big data. Understanding these components and their role in the data pipeline makes it possible to design and build efficient, scalable, and adaptable systems to the changing needs. You can get the help of a specialist company that offers services for data engineering to help design and build systems for data collection, storage and analysis.
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feyariel · 4 months
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Fey's Pokémon Rue-minations: Bottom 10 Gen 1 Moves
I warned you, didn't I?
I'm not going to include obvious ones, like Splash. These are a special flavor of Hell, not just ones that are glitchy or intentionally non-functional. These are moves which either fail to understand how the game is played or moves which force the game into directions it didn't need to go.
#10: Moves Which Require (Re-)Charging
Dig · Fly · Hyper Beam · Razor Wind · Skull Bash · Sky Attack · Solar Beam
These moves are all cool, but they run into a problem with the mechanics of the games: you can switch out a Pokémon instead of having it perform a move. Almost no NPC trainers do this, so these moves are fine to use. The so-called "semi-invulnerable" turn in this generation is closer to true invulnerability, as the only move that can hit a Pokémon during such turns is Swift. Thus, against NPCs, Dig and Fly have some tactical use. However, because switching out when faced with a bad matchup is how competitive play works, most of these moves are actually useless. In Gen I, Hyper Beam doesn't need a recharge if it KOs a target, so it also has tactical uses.
Razor Wind would get remade as Air Slash and a few similar moves later on. Skull Bash is a duplicate of Headbutt. Solar Beam loses its charging turn in harsh sunlight. There not really any replacements for the rest; Game Freak never stopped using this mechanic, even though it sucks.
#9: OHKO Moves
Fissure · Guillotine · Horn Drill
I'm not sure if these are banned in competitive play or not. They should be, as they take the fun out of the prediction and counter gameplay essential to the game. They also rely too heavily on luck, with their abysmal Accuracy. If you're using these moves, you are saying that you have nothing better to do.
#8: Low Accuracy Attacks
[insert ridiculously long list here]
In a game where accuracy is literally everything, to the point that raising evasion is banned, when there is always a move with a decent accuracy that you can use, the existence of these is infuriating.
It's one thing when the accuracy check is for a status move so that the game can give a poor equivalent of a saving throw (resisting an effect). That's annoying, but a worthwhile mechanic. This is just wasting your turn.
#7a: Moves that Raise Evasion
Double Team · Minimize
I like these moves, but they're banned. Accuracy and Evasion are annoying mechanics, ergo no one likes to play with them. As they are separate mechanics, there really isn't a way to lower Evasion in Gen I, so you render yourself nigh-invincible. (I'm unsure if the presence of such in Gens II onward changed the ban, sadly.)
#7b: Moves that Lower Accuracy
Flash · Kinesis · Sand Attack
For some reason, even though the logic is identical (there is no way to raise accuracy in Gen I through a move), these weren't banned. This probably has to do with the fact that 1.) you can switch out of it and 2.) since it impacts the opponent and not the user, the opponent is more likely to get lucky and hit than if the user had used Double Team. Even so, these are really fucking annoying.
#6: Moves that Deal a Fixed Amount of Damage
Dragon Rage · Night Shade · Seismic Toss · Sonic Boom
I'm honestly not sure why these moves exist. I have theorized that this was a means of giving Ghost a special and a physical move in the same generation, but that was the extent of my reasoning. It doesn't make sense with Dragon Rage, since it negates the fact that Dragon is weak to itself; it especially doesn't make sense with Seismic Toss, since Fighting has no good moves, or Sonic Boom, since Normal has too many moves as it is.
#5: Moves that Lock You into Repeating the Move for Multiple Rounds
Petal Dance · Rage · Thrash · etc.
If there's one thing that's more annoying than not being able to hit, it's being locked out of the UI. "Partial" trapping moves are one thing; they work for however long and aren't worse for it each turn they go on. However, because of opponent switching, these moves are terrible.
#4: Moves with Recoil/Crash Damage
Double-Edge · High Jump Kick · Jump Kick · Submission · Take Down
Why are we hurting ourselves just to land an attack? Also, notice how all of these are either Fighting or Normal. Fighting doesn't have a good high-power move, while Normal has a bunch of duplicates of Body Slam that don't need to exist. What was the point of making these?
#3: Crabhammer
Crabhammer could have been great. But it's not a Bug-type move.
There's really no reason why Krabby and Kingler -- for whom this move was signature until Gen III -- are not Bug-types; Game Freak has a mysterious habit of making crustaceans anything besides Bug (all while making non-arthropods like Shuckle Bug-types), but Anorith/Armaldo and Dwebble/Crustle are both crustaceous Bug-types. But they weren't; they were mono-Water. As such, they couldn't receive adequate STAB until Gen IV, by which point the game is almost fundamentally different.
Had Crabhammer been a Bug-type move -- or, even better, had it been a Bug-type move that could also be treated as a Water-type move (depending on circumstances) and was still physical -- then Psychics would largely get checked. Or maybe they wouldn't, since they usually carry Electric-type moves, but they'd have a theoretical counter at the very least, especially if Kingler found a means of not dying immediately.
#2: Lick
In Gen I, there were three Ghost-type moves: Confuse Ray, Lick, and Night Shade. One of these things is not like the other one.
In theory, all three of these should have been signature moves of the Gastly line, given that they were the only Ghost-types in the generation. Confuse Ray (thankfully) had much broader representation, so wasn't. Night Shade was. Was Lick? No.
...Jynx also learned it.
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You would think that Lick would be a Normal-type move and the signature move of Lickitung, the Licking Pokémon, whose entire, unwanted gimmick is licking things with its tongue (not even swallowing them, just licking them). Lickitung appears in Period 1 of the internal index; it's several spots ahead of Gengar and two rows (nearly three) before Gastly, neither of which were related to each other that early in development. If it's not solely based on a lizard of some sort, Lickitung is likely based on the akaname, a yokai with a gigantic tongue that licks grime out of bathhouses.
It doesn't learn Lick until Gen II.
The idea of ghosts licking things is a trope that spans East Asia and even appears occasionally in Western cinema and such, but the former is a relatively obscure trope and the latter is done for comic relief and grossness more than anything. Ghosts, both in other narratives and in Pokémon, first and foremost rely on scaring the shit out of their targets. But Astonish wouldn't be a Ghost-type move until Gen III.
Lick itself doesn't even make sense -- 30% paralysis chance? If anything, it should be a Normal-type move with very low or even no damage and a close to automatic chance to cause the target to flinch. It's a stupid move.
But beyond being stupid, it locked the Ghost type into being a physical type even though all Ghost-types were specially oriented (and so couldn't use physical moves that well) up until Gen III, when we got several new Ghosts with lackluster stats: Shedinja and Banette are both physical attackers with no other good stats, Dusclops is highly defensive with poor stats otherwise, and Sableye's stats are relatively well-rounded for something not fully evolved (when it doesn't evolve at all). The good Ghost-types were specially focused and, especially given move pools, may as well have been Psychic-types.
The thing is, Ghost could have been a physical type from the get-go anyway: Golbat (bat, vampire, vampire bat) and Marowak (spooky scary skeleton, warrior channeling ancestors) could have been Ghost-types, as could have been Leech Life (which should have had a higher power anyway or had an improved equivalent) and Bone Club/Bonemerang. If these were the case, Lick wouldn't matter.
But it does. Because it screwed over a type.
#1: Self-Destruct/Explosion
Self-Destruct and Explosion are moves which annoy the Hell out of me for several reasons.
First, they're not uncommon. Lots of Pokémon which have no logical explanation for blowing up do so. Explosion isn't limited to things which are or could easily become bombs -- Voltorb/Electrode, Exeggcute, and Koffing/Weezing. Rock-types have a habit of exploding despite being made out of rocks, which by and large do not. Lots of lines get the move when only one member (Exeggcute, Seedot) make sense as having it. Shellder can learn it. If we expand our search to include Self-Destruct, we get still more users -- like Snorlax or Mewtwo, neither of which should have a self-destruct mechanism. Vanilluxe can learn it; it's freaking ice-cream.
Second, they're absurdly powerful. They're so powerful that making sure you have a Pokémon that can handle explosions somehow becomes a major component in team building, at least early on. After all, some Pokémon exist solely to give the user the chance to have them explode. Others aren't especially great attackers, but hey, they can at least take down one opponent. This is something I really hate, as it forces me to pick from a subset of Pokémon I may or may not want to use just to avoid having the Pokémon that otherwise would have a good type matchup not die because my opponent went kamikaze on me.
Third, they're redundant. Pokémon is no stranger to creating upgraded versions of the same moves, but Self-Destruct didn't need an upgrade. Since both halve the targets' Defense stats, they both are guilty of having the effectively highest Powers in the game -- and they were already contenders for that without the Defense bypass.
Fourth, they'd make sense as Fire-type moves, but aren't. They deal Normal (neutral) damage. This means Ghosts are immune to them (fine), but Rocks resist. I mean, sure Rock would still resist it if if were a Fire-type move, but Game Freak is aware that we use explosions quite effectively to break apart rock, right?
I don't find the prospect of being very close to a KO only for my opponent to randomly become powerful enough to KO my Pokémon in addition to itself. Either you let your opponent kill you or you take them out first, not both.
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ailtrahq · 6 months
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The value of a silver bar is determined by the spot price of silver. With an ounce of silver trading at $22.12 as of October 11, 2023, a common type of silver bar weighing 10 oz is worth $221.20. Silver is the second most widely traded precious metal in the world, behind gold. The value of a silver bar depends on the spot price of silver, the weight of the bar itself, the silver content, and the potential premium charged for the bar. In this article, we will explore the various aspects that contribute to the worth of a silver bar and provide you with valuable insights into the world of silver investments. What is a silver bar? A silver bar is a rectangular-shaped piece of silver that is typically produced in a standardized weight and purity. It is a form of bullion (which is why it’s commonly referred to as silver bullion), which means it is valued primarily for its precious metal content.  A silver bar is essentially a solid block made out of nearly pure silver.  Silver bars are usually made by private mints or government mints and can vary in size and weight, ranging from small bars of a few grams to large bars weighing several kilograms. They are commonly traded and collected as an investment or store of value, as well as for industrial purposes such as manufacturing silverware, jewelry, and electronic components. How much is a silver bar worth? Factors that determine a silver bar’s worth The value of a silver bar is derived primarily from its size. The most common type of silver bar, the one troy ounce bar, is changing hands at $22.12 per unit as of October 11, 2023. How much is a bar of silver worth is also determined by the potential premium, which is included in the price of a bar, and other factors. With that said, let’s examine the main factors that contribute to the price of silver bars: Silver content: The primary determinant of a silver bar's value is its silver content. Silver bars are typically made of .999 fine silver, meaning they contain 99.9% pure silver. The weight of the bar, usually measured in troy ounces, determines the total amount of silver it holds.  Spot price of silver: The spot price of silver refers to the current market price at which silver is bought and sold for immediate delivery. It fluctuates based on supply and demand dynamics, economic factors, geopolitical events, and market speculation. Premium: The premium represents the additional cost above the spot price that buyers pay to acquire the bar. The premium covers the expenses incurred during the production, distribution, and marketing of the silver bar. It varies depending on factors such as the brand, design, weight, and market conditions – it can range anywhere from 1% to as much as 20%. Brand and design: Well-known brands with a strong reputation for producing high-quality bars often command higher premiums. Additionally, limited edition or commemorative bars may have a higher collectible value, attracting collectors and enthusiasts. Market conditions: Economic factors, such as inflation, interest rates, and currency fluctuations, can influence the demand for precious metals. During times of economic uncertainty, investors often turn to silver as a safe haven, driving up demand and increasing the value of silver. How much is a 10 oz bar of silver worth? A 10 oz silver bar can fetch a price of more than $221.20 at current market prices.  It is worth noting that you can gain exposure to silver without necessarily buying the physical asset itself. For example, you can buy silver-backed cryptocurrency like Kinesis Silver (KAG), which is pegged to the value of 1 oz of silver at a 1:1 ratio.  How much is a 100 oz silver bar worth? At the time of writing the article, a silver bar weighing 100 oz sells for approximately $2,212. Interestingly, the same-sized gold bar is worth over $192,000, over 80 times more.  How much is a 1-pound silver bar worth? A 1-pound (lb.) silver bar costs $322.58, given silver’s current spot price of $22.12. It is
worth noting that silver is currently trading more than 50% removed from its all-time high of $49.45, the precious metal reached in January 1980. Still, silver showed impressive performance over the past couple of years, having gained over +40% in the past five years. The price of silver has increased by more than +40% since 2018. Source: TradingView How much does a silver bar weigh? The most common type of silver bar weighs 1 troy ounce (31.1 grams). Other common types of silver bars include 5 oz, 10 oz, and 100 oz.  The table below lists the most common sizes of silver bars, their weights in different weight units, and prices at current rates. Weight in troy ounces Weight in grams Weight in pounds Price* 1 oz 31.1 g 0.068 lbs $22.12 5 oz 155.5 g 0.342 lbs $110.60 10 oz  311 g 0.686 lbs $221.20 100 oz 3,110 g 6.857 lbs $2,212 *Based on the spot price of silver of $22.12 (collected on October 11, 2023) Who makes silver bars? Silver bars are manufactured by a variety of entities, including government mints, private mints, and precious metals refineries. These organizations specialize in producing silver bars of different sizes and designs to meet the demands of investors and collectors.  Silver bar producers can be roughly divided into three categories, including government mints, private mints, and precious metal refineries. We’ll examine each of these in more detail below:  Government mints: Government-minted silver bars typically feature iconic national symbols, historical figures, or commemorative designs. Some of the most well-known government mints include the Royal Canadian Mint, the United States Mint, and the Perth Mint. Private mints: Private mints are independent companies that produce silver bars for investment and collectible purposes. Some prominent examples of private mints include Swiss-based PAMP Suisse and the US-based Sunshine Minting. Precious metals refineries: Refineries source raw silver material, such as silver ore, scrap silver, or silver bullion, and refine it to meet the required purity standards. While they may not directly produce finished silver bars, refineries supply refined silver to mints for further processing. The UK-based Johnson Matthey and Germany-based Heraeus are two of the most prominent silver refining companies. How to buy a silver bar?  When considering purchasing a silver bar, there are several steps to guide you through the process. First, determine your budget and how much you are willing to invest. This will help narrow down your options as silver bars come in various sizes and weights, each with a different price point. Next, research reputable dealers who specialize in selling silver bars. It is important to conduct thorough research to ensure the dealer has a track record of customer satisfaction, offers competitive prices, and provides genuine and authenticated products.  Furthermore, make sure to verify the authenticity of silver bars. Genuine silver bars should have a hallmark or stamp indicating their weight, purity, and the mint or refinery that produced them. Reputable dealers will provide authentic products and provide proof of authenticity. Comparing prices from different dealers is also important to ensure you are getting a fair deal. Keep in mind that prices can vary based on factors such as weight, brand, design, and current market conditions.  Before finalizing the purchase, consider how you plan to store your silver bar. It is important to think about purchasing a secure storage option such as a safe, safety deposit box, or specialized storage facility. Proper storage helps protect your investment and ensures the longevity of the silver bar. The bottom line: A silver bar’s value depends on its weight, purity, and the spot price of silver The most common type of silver bar, a 10-troy-ounce silver bar, is currently available for a little more than $221. However, there are quite significant discrepancies in the value of different gold bars, depending on their weight, purity, and premium.
If you are considering gaining exposure to precious metals but don’t want to pay maintenance and storage fees, you can consider investing in gold-backed cryptocurrencies. In addition, if you want to expand your portfolio to other metals with real-world utility, you can consider investing in nickel stocks.
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omninossolutio · 6 months
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Building a Netflix Clone: A Deep Dive into the Streaming Service Industry
The global streaming service industry has witnessed exponential growth over the past decade, with platforms like Netflix leading the way. As the demand for on-demand content continues to surge, entrepreneurs and developers are increasingly looking to create their own streaming platforms. In this comprehensive guide, we will explore the concept of a Netflix clone, the key features required to replicate Netflix's success, and the technical aspects involved in building such a platform.
Understanding the Netflix Phenomenon (150 words)
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Netflix, founded in 1997 as a DVD rental service, has evolved into a global streaming giant with millions of subscribers worldwide. Its success can be attributed to its vast content library, user-friendly interface, and personalized recommendations. A Netflix clone aims to replicate these elements to offer a similar streaming experience to its users.
Key Features of a Netflix Clone (200 words)
Content Library: A Netflix clone must have a vast and diverse content library. This includes a wide range of movies, TV shows, documentaries, and original content. Licensing agreements and partnerships with content providers are essential to ensure a continuous flow of fresh content.
User Profiles and Personalization: Like Netflix, a clone should allow users to create individual profiles. Personalization algorithms should then analyze user behavior and preferences to offer tailored content recommendations. This enhances user engagement and retention.
Cross-Platform Compatibility: A Netflix clone should be accessible on multiple devices, including smartphones, tablets, smart TVs, and desktops. Developing responsive web and mobile applications is crucial to reach a broader audience.
Subscription Management: Implementing subscription plans and payment gateways is essential for monetizing the platform. Users should have the flexibility to choose from different subscription tiers, each offering various features and pricing options.
Offline Viewing: Providing the option to download content for offline viewing is a popular feature that enhances user convenience. It's crucial to implement secure DRM (Digital Rights Management) mechanisms to protect downloaded content.
Seamless Streaming Experience: A Netflix clone must ensure smooth and uninterrupted streaming. This includes adaptive streaming technology that adjusts video quality based on the user's internet connection speed.
Search and Navigation: Robust search and navigation functionalities help users discover content easily. Implementing filters, categories, and advanced search options can improve the overall user experience.
Content Recommendations: Machine learning algorithms analyze user preferences and viewing history to suggest relevant content. This keeps users engaged and encourages them to explore more content on the platform.
Technical Aspects of Building a Netflix Clone (200 words)
Content Delivery Network (CDN): To ensure fast and reliable streaming, leverage a CDN to distribute content to users globally. CDNs reduce latency and ensure content is delivered from the nearest server.
Video Encoding and Streaming Servers: Implement video encoding to support various formats and resolutions. Use streaming servers like Wowza, Apache Kafka, or Amazon Kinesis to deliver content efficiently.
Database Management: A robust database system is essential to store and manage vast amounts of user data, content metadata, and streaming logs. Consider using NoSQL databases like MongoDB for scalability.
Security and DRM: Protecting copyrighted content is crucial. Implement Digital Rights Management (DRM) solutions to secure content and user information. SSL encryption should also be employed for secure data transmission.
Scalability: As your user base grows, ensure your infrastructure can scale accordingly. Cloud-based solutions like AWS, Azure, or Google Cloud can provide the scalability needed to handle increased traffic.
Mobile and Web Development: Develop responsive web and mobile applications using technologies like React, Angular, or Vue.js for front-end development. For back-end development, Node.js, Ruby on Rails, or Python can be used.
Payment Integration: Integrate payment gateways like Stripe, PayPal, or Braintree to handle subscription payments securely.
Content Management System (CMS): Implement a CMS to efficiently organize and manage your content library. Tools like WordPress or custom-built CMS systems can be used.
Challenges in Building a Netflix Clone (100 words)
While creating a Netflix clone can be a lucrative endeavor, it comes with its own set of challenges. Securing content licenses, maintaining a vast content library, and competing with established giants are significant hurdles. Additionally, ensuring a seamless streaming experience across various devices and handling user data securely are ongoing challenges that require continuous attention and resources.
Monetization Strategies (100 words)
To sustain a Netflix clone, it's essential to implement effective monetization strategies. Subscription-based models, where users pay for access to premium content, are the most common. You can offer tiered pricing plans with varying features to cater to a broader audience. Alternatively, you can generate revenue through ads, although this may affect the user experience. Partnerships, merchandise sales, and exclusive content deals are other avenues to explore for revenue generation.
Conclusion (50 words)
Creating a Netflix clone is a complex yet promising venture. Success in this competitive industry requires a deep understanding of user preferences, robust technical infrastructure, and a commitment to providing a superior streaming experience. By focusing on key features and overcoming challenges, entrepreneurs and developers can embark on the journey to build their own successful streaming platform.
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datavalleyai · 7 months
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The Role of a Senior Data Engineer: Key Responsibilities and Skills
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Data Engineers play a crucial role in today's data-driven world. They collect, process, and store data, enabling data scientists and analysts to utilize it effectively. As the data landscape evolves, the demand for Senior Data Engineers continues to rise. In this article, we will explore the evolving role of a Senior Data Engineer, essential skills required to excel in this role and how a course at Datavalley can help you acquire and hone these skills.
The Evolving Role of a Data Engineer
Senior data engineers are accountable for building and upkeeping data collection systems, pipelines, and management tools. They oversee the activities of junior data engineers and the architectures themselves. While this role has always been essential, it has evolved significantly in recent years due to the proliferation of big data and cloud technologies. Here are some key aspects of a Senior Data Engineer's responsibilities:
1. Data Ingestion:
One of the primary tasks of a Data Engineer is to design systems that can efficiently ingest data from various sources, such as databases, APIs, and streaming platforms. This requires expertise in tools like Apache Kafka, Apache Nifi, or cloud-based solutions like AWS Kinesis.
2. Data Modeling and Transformation:
Data engineers play a critical role in creating data models that enhance data accessibility and comprehension for non-technical stakeholders, including analysts and data scientists.
Data Engineers need to create and manage data pipelines that transform raw data into a format suitable for analysis. Proficiency in SQL is crucial for data modeling, and ETL (Extract, Transform, Load) tools like Apache Spark or Talend are commonly used for data transformation.
3. Collaborative Engagement
Daily meetings are a fundamental aspect of a data engineer's routine. These meetings often include the daily scrum, where team members discuss recent achievements, ongoing tasks, and potential obstacles.
Additionally, data engineers actively participate in cross-functional meetings, collaborating with data scientists, data analysts, product managers, and application developers.
4. Data Storage and Data Query Optimization:
Selecting the right data storage solution is critical for performance and scalability. Data Engineers should be well-versed in traditional databases (e.g., PostgreSQL, MySQL) as well as NoSQL databases (e.g., MongoDB, Cassandra) and cloud-based storage options (e.g., Amazon S3, Azure Data Lake Storage).
As data volumes continue to grow, data engineers are tasked with optimizing data queries to ensure efficient data retrieval. This optimization process may involve the creation of indexes, data restructuring, or data aggregation to facilitate quicker queries.
5. Data Quality and Governance:
Ensuring data accuracy and compliance with regulations is vital. Data Engineers must implement data quality checks, data lineage tracking, and access controls to maintain data integrity.
6. Cloud Computing:
The cloud has revolutionized data engineering. Familiarity with cloud platforms like AWS, Azure, or Google Cloud is essential, as many organizations are migrating their data infrastructure to the cloud.
7. DevOps and Automation:
Data Engineers often collaborate closely with DevOps teams to automate deployment, scaling, and monitoring of data pipelines. Proficiency in tools like Docker and Kubernetes is increasingly valuable.
Data engineers are instrumental in managing the data infrastructure that underpins data processing and storage. This aspect of their role often encompasses a combination of development and operational tasks, particularly in larger teams.
8. Facilitating Data Flow
In essence, data engineers serve as intermediaries between data sources, storage systems, and end-users. Their role is to ensure the smooth flow of data within an organization, making certain that data is readily available and accessible to those who require it.
By bridging the gap between technology and business, data engineers empower analysts and data scientists to focus on deriving insights rather than grappling with data retrieval and manipulation.
9. Data Security:
Protecting sensitive data is a top priority. Knowledge of encryption techniques, IAM (Identity and Access Management), and security best practices is crucial.
Essential Skills for a Senior Data Engineer
Now that we've outlined the evolving role of a Senior Data Engineer, let's delve into the essential skills needed to excel in this field.
1. Strong Programming Skills:
A Senior Data Engineer should be proficient in at least one programming language commonly used in data engineering, such as Python, Java, or Scala. These languages are essential for building data pipelines and working with big data frameworks.
2. Proficiency in SQL:
SQL is the backbone of data manipulation and querying. A Senior Data Engineer should have a deep understanding of SQL to design efficient database schemas and perform complex data transformations.
3. Data Modeling:
Creating effective data models is crucial for organizing data and ensuring its accessibility and usability. Skills in data modeling techniques like entity-relationship diagrams and star schemas are invaluable. Getting advanced data engineering certifications with Snowflake’s cloud-based platform would be beneficial.
4. Big Data Technologies:
Familiarity with big data technologies such as Apache Hadoop, Spark, and Flink is essential. These tools are used for processing and analyzing massive datasets efficiently.
5. Cloud Platforms:
As mentioned earlier, cloud platforms like AWS, Azure Cloud Services, and Google Cloud Platform are increasingly central to data engineering. Knowledge of these platforms, including services like AWS Lambda and Azure Data Factory, is a must.
6. ETL Tools:
Data Engineers need expertise in ETL tools like Apache NiFi, Talend, or cloud-based alternatives to streamline data integration and transformation processes.
7. Database Management:
A deep understanding of both SQL and NoSQL databases is essential. Data Engineers should be able to design, optimize, and manage databases effectively.
8. Data Pipeline Orchestration:
Tools like Apache Airflow or cloud-native solutions like AWS Step Functions are essential for orchestrating complex data pipelines.
9. Version Control:
Proficiency with version control systems like Git is essential for collaboration and code management in data engineering projects.
10. Interpersonal Skills:
Communication, problem-solving, and teamwork are equally important for a Senior Data Engineer. They often collaborate with data scientists, analysts, and business stakeholders, so effective communication is vital.
Why Datavalley for Data Engineer?
To acquire and master these essential skills for a Senior Data Engineer, consider enrolling in a course at Datavalley. Datavalley offers a comprehensive Data Engineer program designed to provide hands-on experience and in-depth knowledge in all the areas mentioned above. Here's why Datavalley is the right choice:
Comprehensive Curriculum: Our courses cover Python, SQL fundamentals, Snowflake advanced data engineering, cloud computing, Azure cloud services, ETL, Big Data foundations, DevOps, Data lake, AWS data analytics.
1. Expert Instructors: Datavalley's courses are led by experienced data engineers who have worked in the industry for years. Experts teach modules to broaden your understanding and provide industrial insights.
2. Hands-on Projects: The best way to learn is by doing. Datavalley's curriculum includes hands-on projects that allow you to apply your skills in real-world scenarios.
3. Cutting-edge Tools and Technologies: Datavalley stays up-to-date with the latest tools and technologies used in the field of data engineering. You'll learn the most relevant and in-demand skills.
4. Industry Networking: We provide opportunities to connect with industry professionals, helping you build a network that can be invaluable in your career.
5. Career Support: Datavalley goes beyond teaching technical skills. They offer career support services, including resume reviews and interview coaching, to help you land your dream job.
6. Project-Ready, Not Just Job-Ready: Our program prepares you to start working and carry out projects with confidence.
7. On-call Project Assistance After Landing Your Dream Job: Our experts will help you excel in your new role with 3 months of on-call project assistance.
Conclusion
Becoming a Senior Data Engineer requires a diverse set of technical skills and a deep understanding of data infrastructure. As data continues to grow in importance, so does the demand for skilled data engineers.
Datavalley's Big Data Engineer Masters Program can provide you with the knowledge and practical experience you need to excel in this role. Whether you're looking to advance your career or enter the field of data engineering, Datavalley is the right choice to help you achieve your goals. Invest in your future as a Senior Data Engineer and unlock the potential of data on your journey.
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aisoftwareinstitute · 7 months
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AWS Syllabus: A Roadmap to Mastering Amazon Web Services
Introduction
Amazon Web Services (AWS) has established itself as a dominant player in the world of cloud computing, offering a vast array of services and solutions that power businesses and organizations across the globe. AWS certifications are highly regarded in the IT industry and are a testament to one's expertise in cloud computing. To navigate the complexities of AWS and prepare for these certifications, having a well-structured AWS syllabus is essential. In this article, we will explore the significance of an AWS syllabus, its components, and how it can serve as your roadmap to mastering Amazon Web Services.
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The Significance of an AWS Syllabus
Structured Learning: An AWS syllabus provides a structured framework for learning. It breaks down the vast and complex AWS ecosystem into manageable topics and modules, guiding learners step by step through the learning process.
Comprehensive Coverage: AWS is a multifaceted cloud platform with numerous services and concepts. An AWS syllabus ensures comprehensive coverage of these services, ensuring that learners gain a holistic understanding of AWS.
Learning Objectives: Each module or topic in an AWS syllabus typically includes clear learning objectives. These objectives help learners understand what they need to achieve, ensuring focused and goal-oriented learning.
Progress Tracking: A syllabus allows learners to track their progress systematically. They can mark off completed topics and ensure they are on the right path toward their AWS certification or skill development goals.
Resource Guidance: Many AWS syllabi include recommendations for study materials, books, online courses, and hands-on labs. This guidance helps learners choose the most suitable resources to complement their learning.
Key Components of an AWS Syllabus
An AWS syllabus typically comprises a range of topics and components, depending on the specific certification or learning path. Here are some common components found in an AWS syllabus:
Introduction to AWS: This section provides an overview of AWS, its history, and its significance in the cloud computing industry.
AWS Core Services: In-depth coverage of foundational AWS services such as Amazon EC2 (Elastic Compute Cloud), Amazon S3 (Simple Storage Service), Amazon RDS (Relational Database Service), and Amazon VPC (Virtual Private Cloud).
Security and Identity Management: Topics related to AWS Identity and Access Management (IAM), encryption, security groups, and best practices for securing AWS resources.
Compute Services: Detailed explanations of AWS compute services including EC2 instances, AWS Lambda, Elastic Beanstalk, Auto Scaling, and EC2 Container Service.
Storage Services: Coverage of various storage services like Amazon S3, Amazon EBS (Elastic Block Store), Amazon Glacier, and Amazon Storage Gateway.
Databases: In-depth exploration of Amazon RDS, Amazon DynamoDB, Amazon Redshift, and other database services.
Networking: Topics related to Amazon VPC, Amazon Route 53, CloudFront, Direct Connect, and network architecture best practices.
Monitoring and Management Tools: Discussions on AWS CloudWatch, AWS CloudTrail, AWS Systems Manager, AWS Config, and other monitoring and management services.
Application Services: Coverage of services like AWS Elastic Beanstalk, AWS Lambda, Amazon API Gateway, AWS Step Functions, and AWS Elastic Transcoder.
Security, Compliance, and Governance: Detailed insights into AWS security measures, compliance frameworks, and best practices.
DevOps and CI/CD: Guidance on implementing DevOps practices using AWS services such as AWS CodePipeline, AWS CodeBuild, AWS CodeDeploy, and AWS Elastic Beanstalk.
Big Data and Analytics: An introduction to AWS Big Data services including Amazon EMR (Elastic MapReduce), Amazon Redshift, Amazon Athena, and Amazon Kinesis.
Conclusion
An AWS syllabus serves as a valuable roadmap for anyone looking to excel in Amazon Web Services. Whether you are preparing for an AWS certification exam or aiming to deepen your AWS knowledge for professional growth, a well-structured syllabus can be your guiding light. These syllabi offer structured learning paths, comprehensive coverage, clear learning objectives, and resource recommendations, allowing you to progress systematically and efficiently.
In the dynamic and ever-evolving field of cloud computing, staying informed and proficient with AWS is essential. AWS syllabi empower you to set clear learning goals, track your progress, and ultimately become a skilled AWS professional. So, whether you are pursuing an AWS certification or simply striving to enhance your cloud computing skills, make sure to leverage the power of a well-structured AWS syllabus as your companion on your journey to mastering Amazon Web Services.
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dog-food420 · 11 months
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Dr. Tim's Dog Food Review (Dry): Ingredients, Analysis, and Nutrient Profile
If you're looking for high-quality dog food that supports your dog's health, Dr. Tim's product line is worth considering. In this review, we'll take a closer look at Dr. Tim's Kinesis All Life Stages Formula, which represents the other products in the line.
Ingredients:
The first ingredient in this dog food is chicken meal, a concentrated source of protein that contains almost 300% more protein than fresh chicken. The second and third ingredients are brown rice and barley, respectively. While these ingredients provide energy, they are only of modest nutritional value to a dog. The next ingredient, oat groats, is a minimally processed form of oats, which is average in nutritional value.
The fifth ingredient is chicken fat, a high-quality source of linoleic acid, an essential omega-6 fatty acid for your dog's health. The sixth ingredient is beet pulp, a high fiber by-product of sugar beet processing. While there is controversy surrounding beet pulp, reasonable amounts of this ingredient in dog food are considered acceptable.
The seventh ingredient is dried egg product, a dehydrated form of shell-free eggs. Eggs are an easily digestible source of protein and have an exceptionally high biological value. The eighth ingredient is rice bran, a fiber-rich by-product of milling whole grain rice that contains starch, protein, fat, vitamins, and minerals.
The ninth ingredient is herring meal, another protein-rich meat concentrate. This dog food also contains catfish, salmon, and chicken liver meals, which are all high-quality meat concentrates. Flaxseed meal, a plant-based source of healthy omega-3 fatty acids and soluble fiber, is also included.
Additionally, pork plasma, chicory root, and taurine are added to this dog food. Plasma is a nutritious addition to dog food, while chicory root is a natural source of soluble dietary fiber and a prebiotic that promotes healthy bacteria growth in the digestive tract. Taurine is an important amino acid that supports the healthy function of heart muscle.
Analysis:
The nutrient data for Dr. Tim's Kinesis All Life Stages Formula, calculated using a dry matter basis, reveals that this dog food provides a balanced and complete diet for all life stages, according to AAFCO nutrient profiles. The guaranteed analysis indicates a minimum protein content of 26%, a minimum fat content of 16%, and a maximum fiber content of 4%.
Notable Exceptions:
While most ingredients located towards the bottom of the list are unlikely to affect the overall rating of this dog food, there are a few exceptions worth noting. This dog food contains chelated minerals, which are minerals chemically attached to protein, making them easier to absorb. Additionally, it contains sodium selenite, a controversial form of selenium, and it's worth noting that selenium yeast is a more natural source of this mineral.
Conclusion:
Dr. Tim's Kinesis All Life Stages Formula is a high-quality dog food that provides a balanced and complete diet for all life stages. It contains a variety of high-quality meat concentrates, healthy sources of fat and fiber, and other beneficial ingredients like chicory root and taurine. While there is some controversy surrounding certain ingredients, Dr. Tim's dog food is generally well-received by dog owners and recommended by veterinarians.
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bdccglobal · 1 year
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AWS and machine learning
AWS (Amazon Web Services) is a collection of remote computing services (also called web services) that make up a cloud computing platform, offered by Amazon.com. These services operate from 12 geographical regions across the world.
AWS provides a variety of services for machine learning, including:
Amazon SageMaker is a fully-managed platform for building, training, and deploying machine learning models.
Amazon Machine Learning is a service that makes it easy for developers of all skill levels to use machine learning.
AWS Deep Learning AMIs, pre-built Amazon Machine Images (AMIs) that make it easy to get started with deep learning on Amazon EC2.
AWS Deep Learning Containers, Docker images pre-installed with deep learning frameworks to make it easy to run distributed training on Amazon ECS.
Additionally, AWS also provides services for data storage, data processing, and data analysis which are essential for machine learning workloads. These services include Amazon S3, Amazon Kinesis, Amazon Redshift, and Amazon QuickSight.
In summary, AWS provides a comprehensive set of services that allow developers and data scientists to build, train, and deploy machine learning models easily and at scale.
AWS also provides several other services that can be used in conjunction with machine learning. These include:
Amazon Comprehend is a natural language processing service that uses machine learning to extract insights from text.
Amazon Transcribe is a service that uses machine learning to transcribe speech to text.
Amazon Translate is a service that uses machine learning to translate text from one language to another.
Amazon Rekognition is a service that uses machine learning to analyze images and videos, detect objects, scenes, and activities, and recognise faces, text, and other content.
AWS also provides a number of tools and frameworks that can be used to build and deploy machine learning models, such as:
TensorFlow is an open-source machine learning framework that is widely used for building and deploying neural networks.
Apache MXNet, a deep learning framework that is fully supported on AWS.
PyTorch is an open-source machine-learning
 library for Python that is also fully supported on AWS.
AWS SDKs for several programming languages, including Python, Java, and .NET, which make it easy to interact with AWS services from your application.
AWS also offers a number of programs and resources to help developers and data scientists learn about machine learning, including the Machine Learning University, which provides a variety of courses, labs, and tutorials on machine learning topics, and the AWS Machine Learning Blog, which features articles and case studies on the latest developments in machine learning and how to use AWS services for machine learning workloads.
In summary, AWS provides a wide range of services, tools, and resources for building and deploying machine learning models, making it a powerful platform for machine learning workloads at any scale.
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The physiotherapist what he does and when to contact him
Physiotherapy is a branch of medicine that deals with the prevention or treatment of problems related to the musculoskeletal, neurological or visceral system.Doctors often refer to physical therapy as physical therapy or FKT for short. Physiotherapy is nothing but exercise rehabilitation physiotherapy. If the Greek word physio means nature, then kinesi means movement. From the start of their professional life, it is essential to know that physiotherapists choose to focus on the treatment of orthopedic diseases of the musculoskeletal system or the nervous system. It is rare for a physical therapist to deal with both during their career.
Why physiotherapists?
Physiotherapists' primary aim is to prevent and treat movement disorders as a result of trauma and other causes (physiological and postural).Preventive work can be done when inappropriate habits, often postural habits, are identified. This may become obsessive in the future. For athletes, however, prevention consists of body stimulation training and muscle strengthening to prevent injuries.In practice, very few people go to a physioburleigh for prevention. Unfortunately, many people resort to it (or to it) after the onset of acute or prolonged pain and, therefore, after the onset of the disease. To treat medical conditions, physiotherapist gold coast practices various techniques (manual or instrumental) or works in rehabilitation rooms to reduce pain and help patients regain their motor skills. The physical therapist will determine the most appropriate treatment based on the cause of the limitation and follow the patient throughout the recovery process.
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 What the physiotherapist treats?
The first distinction must be made between the musculoskeletal system's orthopaedic pathologies and those of neurological origin. There are traumas and injuries, chronic and degenerative diseases, and posture defects within the first area. All these pathologies have in common is the occurrence of pain with a consequent limitation in performing daily activities.
 Here is what the physiotherapist treats and when to contact him:
Back pain or low back pain ;
Sciatica or lumbosciatica;
neck pain;
Cervicobrachialgia;
bone fractures;
Contusions, sprains or dislocations;
Joint inflammation;
Scoliosis, curved back, hyperlordosis;
Injuries of the ligaments;
Carpal Tunnel Syndrome ;
Arthrosis;
Arthritis;
Muscle strengthening.
The physiotherapist specializes in neurological rehabilitation and instead follows patients with mobility problems related to the nervous system.
 The therapies performed by the physiotherapist
Of all physiotherapy therapies, the best known (and perhaps appreciated) is manual therapy. It is often defined (improperly) as massage therapy or massage, even if technically massage has no curative but aesthetic or wellness purposes.There are a great many techniques and schools of manual therapy. They all have in common that the physiotherapist performs the therapy without tools other than his own hands. The goal of manual treatment is typically to reduce pain and increase the range of motion. The technique used naturally varies according to the pathology.These physical therapies from medical clinic gold coast help reduce pain and inflammation and speed tissue healing. Each therapy is more or less indicated according to the pathology and the phase (acute or sub-acute). However, not all physical therapy machines are the same: the more sophisticated and avant-garde they are, the more effective the therapy will be, and it will take just a few sessions.
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