Introduction – Company Background

GuangXin Industrial Co., Ltd. is a specialized manufacturer dedicated to the development and production of high-quality insoles.

With a strong foundation in material science and footwear ergonomics, we serve as a trusted partner for global brands seeking reliable insole solutions that combine comfort, functionality, and design.

With years of experience in insole production and OEM/ODM services, GuangXin has successfully supported a wide range of clients across various industries—including sportswear, health & wellness, orthopedic care, and daily footwear.

From initial prototyping to mass production, we provide comprehensive support tailored to each client’s market and application needs.

At GuangXin, we are committed to quality, innovation, and sustainable development. Every insole we produce reflects our dedication to precision craftsmanship, forward-thinking design, and ESG-driven practices.

By integrating eco-friendly materials, clean production processes, and responsible sourcing, we help our partners meet both market demand and environmental goals.

Core Strengths in Insole Manufacturing

At GuangXin Industrial, our core strength lies in our deep expertise and versatility in insole and pillow manufacturing. We specialize in working with a wide range of materials, including PU (polyurethane), natural latex, and advanced graphene composites, to develop insoles and pillows that meet diverse performance, comfort, and health-support needs.

Whether it's cushioning, support, breathability, or antibacterial function, we tailor material selection to the exact requirements of each project-whether for foot wellness or ergonomic sleep products.

We provide end-to-end manufacturing capabilities under one roof—covering every stage from material sourcing and foaming, to precision molding, lamination, cutting, sewing, and strict quality control. This full-process control not only ensures product consistency and durability, but also allows for faster lead times and better customization flexibility.

With our flexible production capacity, we accommodate both small batch custom orders and high-volume mass production with equal efficiency. Whether you're a startup launching your first insole or pillow line, or a global brand scaling up to meet market demand, GuangXin is equipped to deliver reliable OEM/ODM solutions that grow with your business.

Customization & OEM/ODM Flexibility

GuangXin offers exceptional flexibility in customization and OEM/ODM services, empowering our partners to create insole products that truly align with their brand identity and target market. We develop insoles tailored to specific foot shapes, end-user needs, and regional market preferences, ensuring optimal fit and functionality.

Our team supports comprehensive branding solutions, including logo printing, custom packaging, and product integration support for marketing campaigns. Whether you're launching a new product line or upgrading an existing one, we help your vision come to life with attention to detail and consistent brand presentation.

With fast prototyping services and efficient lead times, GuangXin helps reduce your time-to-market and respond quickly to evolving trends or seasonal demands. From concept to final production, we offer agile support that keeps you ahead of the competition.

Quality Assurance & Certifications

Quality is at the heart of everything we do. GuangXin implements a rigorous quality control system at every stage of production—ensuring that each insole meets the highest standards of consistency, comfort, and durability.

We provide a variety of in-house and third-party testing options, including antibacterial performance, odor control, durability testing, and eco-safety verification, to meet the specific needs of our clients and markets.

Our products are fully compliant with international safety and environmental standards, such as REACH, RoHS, and other applicable export regulations. This ensures seamless entry into global markets while supporting your ESG and product safety commitments.

ESG-Oriented Sustainable Production

At GuangXin Industrial, we are committed to integrating ESG (Environmental, Social, and Governance) values into every step of our manufacturing process. We actively pursue eco-conscious practices by utilizing eco-friendly materials and adopting low-carbon production methods to reduce environmental impact.

To support circular economy goals, we offer recycled and upcycled material options, including innovative applications such as recycled glass and repurposed LCD panel glass. These materials are processed using advanced techniques to retain performance while reducing waste—contributing to a more sustainable supply chain.

We also work closely with our partners to support their ESG compliance and sustainability reporting needs, providing documentation, traceability, and material data upon request. Whether you're aiming to meet corporate sustainability targets or align with global green regulations, GuangXin is your trusted manufacturing ally in building a better, greener future.

Let’s Build Your Next Insole Success Together

Looking for a reliable insole manufacturing partner that understands customization, quality, and flexibility? GuangXin Industrial Co., Ltd. specializes in high-performance insole production, offering tailored solutions for brands across the globe. Whether you're launching a new insole collection or expanding your existing product line, we provide OEM/ODM services built around your unique design and performance goals.

From small-batch custom orders to full-scale mass production, our flexible insole manufacturing capabilities adapt to your business needs. With expertise in PU, latex, and graphene insole materials, we turn ideas into functional, comfortable, and market-ready insoles that deliver value.

Contact us today to discuss your next insole project. Let GuangXin help you create custom insoles that stand out, perform better, and reflect your brand’s commitment to comfort, quality, and sustainability.

🔗 Learn more or get in touch:
🌐 Website: https://www.deryou-tw.com/
📧 Email: shela.a9119@msa.hinet.net
📘 Facebook: facebook.com/deryou.tw
📷 Instagram: instagram.com/deryou.tw

Indonesia custom insole OEM supplier

Are you looking for a trusted and experienced manufacturing partner that can bring your comfort-focused product ideas to life? GuangXin Industrial Co., Ltd. is your ideal OEM/ODM supplier, specializing in insole production, pillow manufacturing, and advanced graphene product design.

With decades of experience in insole OEM/ODM, we provide full-service manufacturing—from PU and latex to cutting-edge graphene-infused insoles—customized to meet your performance, support, and breathability requirements. Our production process is vertically integrated, covering everything from material sourcing and foaming to molding, cutting, and strict quality control.Taiwan graphene sports insole ODM factory

Beyond insoles, GuangXin also offers pillow OEM/ODM services with a focus on ergonomic comfort and functional innovation. Whether you need memory foam, latex, or smart material integration for neck and sleep support, we deliver tailor-made solutions that reflect your brand’s values.

We are especially proud to lead the way in ESG-driven insole development. Through the use of recycled materials—such as repurposed LCD glass—and low-carbon production processes, we help our partners meet sustainability goals without compromising product quality. Our ESG insole solutions are designed not only for comfort but also for compliance with global environmental standards.Ergonomic insole ODM support Vietnam

At GuangXin, we don’t just manufacture products—we create long-term value for your brand. Whether you're developing your first product line or scaling up globally, our flexible production capabilities and collaborative approach will help you go further, faster.Pillow ODM design company in Vietnam

📩 Contact us today to learn how our insole OEM, pillow ODM, and graphene product design services can elevate your product offering—while aligning with the sustainability expectations of modern consumers.Indonesia OEM factory for footwear and bedding

Recent research uncovers how dopamine in the brain guides animals to identify and refine behaviors leading to rewards. This study, linking specific actions to dopamine release, has implications for improving learning processes in education and AI. Credit: SciTechDaily.com Rewards don’t just reinforce a specific action—they quickly change the whole pattern of how we behave. Imagine you’re teaching a dog to play fetch. You throw a ball, and your dog sprints after it, picks it up, and runs back. You then reward your panting pup with a treat. But now comes the real trick for your dog: figuring out which part of that sequence earned the treat. Scientists call this the ‘credit assignment problem’ in the brain. It’s a fundamental question about understanding which actions are responsible for the positive outcomes we experience. Dopamine, a key chemical messenger in the brain, is known to play a crucial role in this process. But exactly how the brain links specific actions to dopamine’s release has remained unclear. New Insights From a Comprehensive Study A study published on December 13 in Nature by scientists at the Allen Institute, Columbia University’s Zuckerman Mind Brain Behavior Institute, the Champalimaud Centre for the Unknown, and Seattle Children’s Research Institute sheds new light on this mystery. It reveals how dopamine not only signals a reward but also guides animals to home in on the specific behaviors that lead to these rewards through trial and error. Intriguingly, the research also shows that the brain’s reward system can swiftly and dynamically alter the full range of an animal’s movements and behaviors. This highlights a sophisticated learning strategy where behaviors are not just reinforced, but actively shaped and fine-tuned through experience, said Rui Costa, D.V.M, Ph.D., the study’s senior author. “When you reinforce behavior, we often think it’s just that action,” said Costa, the president and CEO of the Allen Institute. “But no: you’re changing the entire behavioral structure. And what was really surprising was how rapid it was.” Decoding How Dopamine Shapes Learning To uncover those insights, the team collaborated with engineers and neuroscientists at the Champalimaud Centre for the Unknown to develop a novel “closed loop” system that could link specific actions by mice to real-time dopamine release. The researchers outfitted mice with wireless sensors to track their movements within a simple controlled space. They then fed this data into a machine learning algorithm, which categorized these actions into distinct groups. The researchers then used optogenetics, a method for controlling neurons with light, to stimulate dopamine neurons once the mice performed predefined “target actions.” They found that mice swiftly changed their behavior in response to dopamine release. Initially, they not only increased the frequency of the target action, but also of similar actions and those that occurred a few seconds before the dopamine release. Meanwhile, actions dissimilar to the target rapidly decreased. Over time, this refinement became more precise, with the mice increasingly focusing on the exact action that led to dopamine release. The study also examined how mice learn a series of actions, unveiling a key process similar to rewinding time to understand what leads to a reward. When actions triggering dopamine occurred further apart, the mice learned more slowly. This shows that longer waits between actions make it harder for mice to connect the sequence with the reward. In essence, actions right before the reward are quickly grasped and improved upon, while earlier actions are refined more gradually. This ‘rewinding’ process strengthens the behavior and helps the mice progressively identify which precise actions and sequences yield the reward. Broader Implications for Education and AI The findings could impact diverse fields like education and artificial intelligence (AI), said lead author Jonathan Tang, Ph.D. , an assistant professor at University of Washington Medicine – Pediatrics, Seattle Children’s Research Institute. For example, allowing for exploration, mistakes, and gradual refinement in the classroom may be more in line with our brain’s innate learning processes. In AI, the insights could lead to more sophisticated and efficient learning systems. By better replicating biological learning processes, we could create AI that is better at adapting to new data and situations. This study offers deeper insight into how our brains learn and adapt through trial and error—whether you’re a scientist or a pup. “We take a lot of stuff for granted about how things work, including credit assignment,” said Tang, who started the research with Costa while at Columbia University. “But it’s when you really start diving in that you realize the complexity. This is why people do science: to home in on the truth of the matter.” Reference: “Dynamic behaviour restructuring mediates dopamine-dependent credit assignment” by Jonathan C. Y. Tang, Vitor Paixao, Filipe Carvalho, Artur Silva, Andreas Klaus, Joaquim Alves da Silva and Rui M. Costa, 13 December 2023, Nature. DOI: 10.1038/s41586-023-06941-5

An innovative AI method developed by University of Konstanz researchers accurately tracks embryonic development stages across species. Initially tested on zebrafish, the method shows promise in studying diverse animal species, enhancing our understanding of evolution. How can we reliably and objectively characterize the speed and various stages of embryonic development? With the help of artificial intelligence! Researchers at the University of Konstanz present an automated method. Animal embryos go through a series of characteristic developmental stages on their journey from a fertilized egg cell to a functional organism. This biological process is largely genetically controlled and follows a similar pattern across different animal species. Yet, there are differences in the details – between individual species and even among embryos of the same species. For example, the tempo at which individual embryonic stages are passed through can vary. Such variations in embryonic development are considered an important driver of evolution, as they can lead to new characteristics, thus promoting evolutionary adaptations and biodiversity. AI in Embryonic Research: Breaking New Ground Studying the embryonic development of animals is therefore of great importance to better understand evolutionary mechanisms. But how can differences in embryonic development, such as the timing of developmental stages, be recorded objectively and efficiently? Researchers at the University of Konstanz led by systems biologist Patrick Müller are developing and using methods based on artificial intelligence (AI). Zebrafish embryos go through characteristic developmental stages, but even sibling embryos differ in the speed of these stages. Artificial intelligence can be used to calculate differences between embryos in terms of development tempo, characteristic developmental stages, and structural differences. Credit: © Patrick Müller, Nikan Toulany In their current article in Nature Methods, they describe a novel approach that automatically captures the tempo of development processes and recognizes characteristic stages without human input – standardized and across species boundaries. Every Embryo Is a Little Different Our current knowledge of animal embryogenesis and individual developmental stages is based on studies in which embryos of different ages were observed under the microscope and described in detail. Thanks to this painstaking manual work, reference books with idealized depictions of individual embryonic stages are available for many animal species today. “However, embryos often do not look exactly the same under the microscope as they do in the schematic drawings. And the transitions between individual stages are not abrupt, but more gradual,” explains Müller. Manually assigning an embryo to the various stages of development is therefore not trivial even for experts and a bit subjective. What makes it even more difficult is that embryonic development does not always follow the expected timetable. “Various factors can influence the timing of embryonic development, such as temperature,” explains Müller. The AI-supported method he and his colleagues developed is a substantial step forward. For a first application example, the researchers trained their Twin Network with more than 3 million images of zebrafish embryos that were developing healthily. They then used the resulting AI model to automatically determine the developmental age of other zebrafish embryos. Objective, Accurate, and Generalizable The researchers were able to demonstrate that the AI is capable of identifying key steps in zebrafish embryogenesis and detecting individual stages of development fully automatically and without human input. In their study, the researchers used the AI system to compare the developmental stage of embryos and describe the temperature dependence of embryonic development in zebrafish. Although the AI was trained with images of normally developing embryos, it was also able to identify malformations that can occur spontaneously in a certain percentage of embryos or that may be triggered by environmental toxins. In a final step, the researchers transferred the method to other animal species, such as sticklebacks or the worm Caenorhabditis elegans, which is evolutionarily quite distant from zebrafish. “Once the necessary image material is available, our Twin Network-based method can be used to analyze the embryonic development of various animal species in terms of time and stages. Even if no comparative data for the animal species exists, our system works in an objective, standardized way,” Müller explains. The method therefore holds great potential for studying the development and evolution of previously uncharacterized animal species. Reference: “Uncovering developmental time and tempo using deep learning” by Nikan Toulany, Hernán Morales-Navarrete, Daniel Čapek, Jannis Grathwohl, Murat Ünalan and Patrick Müller, 23 November 2023, Nature Methods. DOI: 10.1038/s41592-023-02083-8 Open science: The authors have made the Twin-Network open-source code and their research data available for free on GitHub and KonDATA. Funding: European Research Council (ERC), German Research Foundation (DFG), Max Planck Society (MPG), European Molecular Biology Organization (EMBO), Interdisciplinary Graduate School of Medicine (IZKF) University of Tübingen, Blue Sky funding program of the University of Konstanz

Shoreline habitats that are most affected by artificial light at night are vitally important to many aquatic species. Credit: Alex Jordan / Max Planck Institute of Animal Behavior Exposure to artificial light at night led to anxiety-like behaviors in fish, with these effects being inherited by their offspring. Researchers have demonstrated that light pollution, particularly blue light, can change fish behavior in just a few nights, with potential consequences for their descendants. The study focused on female zebrafish to observe their reactions to artificial light at night (ALAN), a major contributor to global light pollution. Fish were exposed to varying wavelengths of ALAN over nine nights, which caused them to swim less, stick closer together, and spend more time near the wall of the aquarium. These anxiety-like behaviors were seen in fish under all wavelengths of light, but short-wavelength light in the blue spectrum caused the fastest and strongest changes. The results further reveal that light pollution can have long-lasting effects: offspring born from light-exposed mothers swam less despite never being exposed themselves. The study was led by scientists from the Institute of Hydrobiology Chinese Academy of Sciences and the Max Planck Institute of Animal Behavior (MPI-AB). Artificial light at night (ALAN) pollutes the environment by adding luminescence to places that would otherwise be dark at nighttime. ALAN exists outdoors through the lights that brighten streets, buildings, and industrial areas all night; and ALAN exists indoors through the devices that hold our attention into the evening. ALAN is known to impact most organisms by disrupting the natural rhythms of biological processes, which are coordinated by cycles of light and dark. “Sleep is one of the main processes of animals that is disrupted by ALAN, so we were curious to know what that means for their ability to navigate their lives. In other words, what does it mean for their behavior?” says Wei Wei Li, the study’s first author who did the work as a doctoral student in MPI-AB. “The light levels that we used in our study matched what is already shining into the homes of animals at night through the many sources we place outdoors. And we found extremely strong and clear negative effects on the behavior of fish and their offspring after only a few bright nights.” The dangers of blue light Because the negative effects of ALAN are known to occur in humans from exposure to light in the blue spectrum, the team wanted to know if different wavelengths also affected the behavior of fish differently. They exposed female zebrafish to all-night light at 10 light regimes: nine separate wavelengths across the visible spectrum as well as white light. Lights were set at 20 lux, approximately the intensity of streetlights seen at a distance, and what animals would be exposed to in outdoor environments. They found that after eight nights of exposure, all wavelengths caused fish to swim less, stick closer together, and spend more time near the wall of the aquarium, a behavior known as “thigmotaxis” or wall-hugging, which is an indicator of animal anxiety. However, the effect of blue light could be seen sooner, after only five days of ALAN exposure, with light at 470 nm having the strongest effect of all. “This is consistent with what is known in humans, that exposure to the blue light of our electronic displays has the biggest effect on our sleep and possibly other physiological cycles,” says co-author Aneesh Bose, who did the work while at MPI-AB. The study did not set out to uncover a mechanism, but the authors speculate that sleep deprivation could be what underlies the patterns in their data. Their finding that behavioral changes revealed themselves after five or eight nights of ALAN exposure, rather than immediately, could be explained by lack of sleep. “The fish could pull a few all-nighters, but after too many nights of disrupted sleep it eventually caught up to them,” explains Bose, who is now a researcher at Swedish University of Agricultural Sciences. Long-lasting changes The study also revealed that the impacts of light pollution did not end in the individual, but were passed down to offspring. After exposure to ALAN, the study’s female zebrafish were allowed to breed and the team raised their offspring under natural light conditions. After 15 days the researchers tested the swimming behaviors of larvae using specialized automated tracking software designed to quantify activity levels of the tiny fish. Offspring of exposed mothers showed decreased daytime movement despite themselves never being exposed to lights at night. “We found that light pollution disrupted the natural behavior of fish, and this disruption may have fitness and performance consequences,” says Ming Duan, the study’s final author from the Institute of Hydrobiology Chinese Academy of Sciences. To mitigate these consequences of ALAN on wild animals, the authors say that special attention needs to be paid to what light is emitted by human sources. Adds Duan: “Many of the places we light up at night are close to animal habitats. The best thing we can do is to minimize the use of blue wavelength light sources where animals are trying to sleep.” Reference: “Behavioural and transgenerational effects of artificial light at night (ALAN) of varying spectral compositions in zebrafish (Danio rerio)” by Weiwei Li, Dongxu Zhang, Qingqing Zou, Aneesh P.H. Bose, Alex Jordan, Erin S. McCallum, Jianghui Bao and Ming Duan, 18 September 2024, Science of The Total Environment. DOI: 10.1016/j.scitotenv.2024.176336

DVDV1551RTWW78V