Search Results (94,614)

Equine-assisted services (EAS) is a relatively new area of study within higher education requiring the development of a curriculum that best prepares the undergraduate student for the demands of the industry. Further, coursework targeting the specific management challenges for ensuring the welfare of horses utilized within EAS is limited. Therefore, the objective of this study was to apply an industry-based survey assessment utilizing EAS professionals within the United States to document management practices associated with healthcare and pain management challenges in the EAS horse. Suggested curriculum for undergraduate students targeting a career in EAS is given, utilizing data collected from the survey. Participant responses (n = 30) indicated that all of the surveyed facilities cared for more than three geriatric horses within their program, with the majority (60% responding “definitely yes”) utilizing regularly functionally lame horses, although the prevalence of lameness was not correlated with number of geriatric horses within a program (0.20, p = 0.22). While lameness is a common healthcare challenge within EAS, gastrointestinal conditions (73%) were one of the other leading health concerns for these facilities. The most common equine pain detection method for EAS facilities was behavior assessment (93%), in which this method was positively correlated with years of horse experience (0.51, p = 0.01). Horse pain was primarily managed through annual alternative therapeutic interventions (76%), daily prescriptions (73%), and nutritional supplements (73%). As such, the curriculum for undergraduate EAS degree programs should cover healthcare practices targeting geriatric horse management and associated health issues such as gastrointestinal conditions and lameness, including early detection and pharmaceutical, nutritional, and alternative therapeutic treatments. Full article

This review explores significant advancements in polymer science and fabrication processes that have enhanced the performance and broadened the application scope of microfluidic devices. Microfluidics, essential in biotechnology, medicine, and chemical engineering, relies on precise fluid manipulation in micrometer-sized channels. Recent innovations in polymer materials, such as flexible, biocompatible, and structurally robust polymers, have been pivotal in developing advanced microfluidic systems. Techniques like replica molding, microcontact printing, solvent-assisted molding, injection molding, and 3D printing are examined, highlighting their advantages and recent developments. Additionally, the review discusses the diverse applications of polymer-based microfluidic devices in biomedical diagnostics, drug delivery, organ-on-chip models, environmental monitoring, and industrial processes. This paper also addresses future challenges, including enhancing chemical resistance, achieving multifunctionality, ensuring biocompatibility, and scaling up production. By overcoming these challenges, the potential for widespread adoption and impactful use of polymer-based microfluidic technologies can be realized. Full article

To improve the resource utilization of dredged silt and industrial waste, this study explores the efficacy of using ground granulated blast furnace slag (GGBS), active calcium oxide (CaO), and sodium silicate (Na₂O·nSiO₂) as alkali activators for silt stabilization. Through a combination of addition tests, response surface method experiments, and microscopic analyses, we identified key factors influencing the unconfined compressive strength (UCS) of stabilized silt, optimized material ratios, and elucidated stabilization mechanisms. The results revealed the following: (1) CaO exhibited the most pronounced stabilization effect, succeeded by Na₂O·nSiO₂, whereas GGBS alone displayed marginal efficacy. CaO-stabilized silt demonstrated rapid strength augmentation within the initial 7 d, while Na₂O·nSiO₂-stabilized silt demonstrated a more gradual strength enhancement over time, attributable to the delayed hydration of GGBS in non-alkaline conditions, with strength increments noticeably during later curing phases. (2) Response surface analysis demonstrated substantial interactions among GGBS-CaO and GGBS-Na₂O·nSiO₂, with the optimal dosages identified as 11.5% for GGBS, 4.1% for CaO, and 5.9% for Na₂O·nSiO₂. (3) X-ray diffraction (XRD) and scanning electron microscopy (SEM) analyses clarified that the hydration reactions within the GGBS-Na₂O·nSiO₂ composite cementitious system synergistically enhanced one another, with hydration products wrapping, filling, and binding the silt particles, thereby rendering the microstructure denser and more stable. Based on these experimental outcomes, we propose a microstructural mechanism model for the stabilization of dredged silt employing GGBS-CaO-Na₂O·nSiO₂. Full article

The application of terahertz (THz) science in industrial technology and scientific research requires efficient THz detectors. Such detectors should be able to operate under various external conditions and conform to existing geometric constraints in the required application. Pyroelectric THz detectors are among the best candidates. This is due to their versatility, outstanding performance, ease of fabrication, and robustness. In this paper, we propose a compact pyroelectric detector based on a bioriented poled polyvinylidene difluoride film coated with sputtered metal electrodes for in situ absorption measurement at cryogenic temperature. The detector design was optimized for the registration system of the electron paramagnetic resonance (EPR) endstation of the Novosibirsk Free Electron Laser facility. Measurements of the detector response to pulsed THz radiation at different temperatures and electrode materials showed that the response varies with both the temperature and the type of electrode material used. The maximum signal level corresponds to the temperature range of 10–40 K, in which the pyroelectric coefficient of the PVDF film also has a maximum value. Among the three coatings studied, namely indium tin oxide (ITO), Au, and Cu/Ni, the latter has the highest increase in sensitivity at low temperature. The possibility of using the detectors for in situ absorption measurement was exemplified using two typical molecular spin systems, which exhibited a transparency of 20–30% at 76.9 cm⁻¹ and 5 K. Such measurements, carried out directly in the cryostat with the main recording system and sample fully configured, allow precise control of the THz radiation parameters at the EPR endstation. Full article

Systematic management of corporate safety risks in industrial parks has become a hot topic. And risk prevention and control mutual aid is a brand-new model in the risk and emergency management of the park. In the context of blockchain, how to incentivize enterprises to actively invest in safety risk prevention and control mutual aid has become a series of key issues facing government regulators. This paper innovatively combines Prospect Theory, Mental Accounting, and Evolutionary Game Theory to create a hypothetical model of limited rationality for the behavior of key stakeholders (core enterprises, supporting enterprises, and government regulatory departments) in mutual aid for safety risk prevention and control. Under the static prize punishment mechanism and dynamic punishment mechanism, the evolutionary stabilization strategy of stakeholders was analyzed, and numerical simulation analysis was performed through examples. The results show: (1) Mutual aid for risk prevention and control among park enterprises is influenced by various factors, including external and subjective elements, and evolves through complex evolutionary paths (e.g., reference points, value perception). (2) Government departments are increasingly implementing dynamic reward and punishment measures to address the shortcomings of static mechanisms. Government departments should dynamically adjust reward and punishment strategies, determine clearly the highest standards for rewards and punishments, and the combination of various incentives and penalties can significantly improve the effectiveness of investment decisions in mutual aid for safety risk prevention and control. (3) Continuously optimizing the design of reward and punishment mechanisms, integrating blockchain technology with management strategies to motivate enterprise participation, and leveraging participant feedback are strategies and recommendations that provide new insights for promoting active enterprise investment in mutual aid for safety risk prevention and control. The marginal contribution of this paper is to reveal the evolutionary pattern of mutual safety risk prevention and control behaviors of enterprises in chemical parks in the context of blockchain. Full article

This article presents the design and implementation of an innovative human–machine interface (HMI) in mixed reality for a robot model operating within Robot Operating System 2 (ROS 2). The interface is specifically developed for compatibility with Microsoft HoloLens 2 hardware and leverages the Unity game engine alongside the Mixed Reality Toolkit (MRTK) to create an immersive mixed reality application. The project uses the Turtlebot 3 Burger model robot, simulated within the Gazebo virtual environment, as a representative mechatronic system for demonstration purposes. Communication between the mixed reality application and ROS 2 is facilitated through a publish–subscribe mechanism, utilizing ROS TCP Connector for message serialization between nodes. This interface not only enhances the user experience by allowing for the real-time monitoring and control of the robotic system but also aligns with the principles of Industry 5.0, emphasizing human-centric and inclusive technological advancements. The practical outcomes of this research include a fully functional mixed reality application that integrates seamlessly with ROS 2, showcasing the potential of mixed reality technologies in advancing the field of industrial automation and human–machine interaction. Full article

The Internet of Things (IoT) presents immense opportunities for driving Industry 4.0 forward. However, in scenarios involving networked control automation, ensuring high reliability and predictable latency is vital for timely responses. To meet these demands, the contemporary wireless protocol time-slotted channel hopping (TSCH), also referred to as IEEE 802.15.4-2015, relies on precise transmission schedules to prevent collisions and achieve consistent end-to-end traffic flow. In the realm of diverse IoT applications, this study introduces a new traffic-aware autonomous multi-objective scheduling function called OPTIMAOrchestra. This function integrates slotframe and channel management, adapts to varying network sizes, supports mobility, and reduces collision risks. The effectiveness of two versions of OPTIMAOrchestra is extensively evaluated through multi-run experiments, each spanning up to 3600 s. It involves networks ranging from small-scale setups to large-scale deployments with 111 nodes. Homogeneous and heterogeneous network topologies are considered in static and mobile environments, where the nodes within a network send packets to the server with the same and different application packet intervals. The results demonstrate that OPTIMAOrchestra_ch4 achieves a current consumption of 0.72 mA while maintaining 100% reliability and 0.86 mA with a 100% packet delivery ratio in static networks. Both proposed Orchestra variants in mobile networks achieve 100% reliability, with current consumption recorded at 6.36 mA. Minimum latencies of 0.073 and 0.02 s are observed in static and mobile environments, respectively. On average, a collision rate of 5% is recorded for TSCH and RPL communication, with a minimum of 0% collision rate observed in the TSCH broadcast in mobile networks. Overall, the proposed OPTIMAOrchestra scheduler outperforms existing schedulers regarding network efficiency, time, and usability, significantly improving reliability while maintaining a balanced latency–energy trade-off. Full article

In today’s competitive and environmentally conscious industries, the ability of organizations to adapt and respond is more important than ever. This study focuses on overcoming the obstacles faced by the Iranian automobile sector by highlighting the significance of incorporating green supply chain techniques. The research intends to integrate organizational operations with environmental sustainability goals by utilizing a MULTIMOORA strategy for supplier selection. The Iranian automobile sector, facing substantial environmental challenges, requires a strategy framework for selecting environmentally friendly suppliers in order to sustain competitiveness and fulfill ecological obligations. The study develops a supplier selection model based on extensive research and expert knowledge. The Delphi and MULTIMOORA techniques are employed to assess and prioritize suppliers according to green criteria, assuring conformity with environmental goals. Data are collected by conducting a comprehensive analysis of the existing literature and engaging in conversations with industry experts in order to acquire information for the construction of the model. The results emphasize the crucial significance of trust-based relationships with suppliers, rigorous compliance with quality standards in new product development, and substantial investment in employee training and development. Sector analysts view these characteristics as crucial for promoting sustainability and gaining a competitive advantage in the Iranian vehicle sector. This study provides firms with strategic instruments to effectively negotiate the intricacies of green supply chain management, with a particular focus on the need for adopting sustainable practices while selecting suppliers in the dynamic and competitive context of the Iranian automobile industry. Full article

Tractors are the most important agricultural power machinery. With the development of tractors toward large-scale and electrification, the design of modern tractor transmission systems increasingly relies on computer simulation technology. However, tractor transmission systems, especially power-shift transmissions and CVTs, are highly complex industrial products that involve specialized knowledge from multiple disciplines. Engineers and researchers find it difficult to choose the correct mathematical model and grasp the trend of technological development when applying simulation technology. To address this issue, we conducted a systematic review of the field and carried out the following work: First, the types and basic principles of tractor transmission systems were introduced; Second, the modeling methods and applications of computer simulation technology in the structural optimization, power-shift control, and energy saving of tractor transmission systems were reviewed; Finally, the method of obtaining simulation parameters through system identification was introduced. Although computer simulation technology has been applied in the development of all tractor transmission systems, there are still some issues that need attention, such as the lack of established shift quality evaluation indicators and driving cycles suitable for tractors, which are crucial for the reliability of simulation results but are rarely studied. These issues need to be addressed in future work. Full article

Jingdezhen, renowned as the cradle of Chinese ceramic art, has embraced new opportunities in the realm of art tourism amidst the global tourism boom. Nonetheless, this growth trajectory is fraught with challenges. This study aims to delve into the obstacles encountered in the development of art tourism in Jingdezhen and to identify the critical influencing factors through qualitative research methods, particularly grounded theory. By conducting in-depth interviews with ‘Jingpiao’ artists who have worked in the art industry in Jingdezhen for three years or more and have interacted with tourists, this research reveals that economic, infrastructure, human resources, government attitude, policy and regulation, promotion, and transportation are significant factors affecting the development of art tourism in Jingdezhen. These factors intertwine to form a complex system that impacts the sustainable development of art tourism in the region. The findings underscore the need for concerted efforts among government, businesses, and artists to optimise these key factors, thereby creating a more conducive environment for the development of art tourism in Jingdezhen. Moreover, this study offers valuable insights and lessons for the development of art tourism in other regions. Full article

This article implements a hybrid Machine Learning (ML) model to classify stoppage events in a copper-crushing equipment, more specifically, a conveyor belt. The model combines Artificial Neural Networks (ANNs) and Support Vector Machines (SVMs) with Principal Component Analysis (PCA) to identify the type of stoppage event when they occur in an industrial sector that is significant for the Chilean economy. This research addresses the critical need to optimise maintenance management in the mining industry, highlighting the technological relevance and motivation for using advanced ML techniques. This study focusses on combining and implementing three ML models trained with historical data composed of information from various sensors, real and virtual, as well from maintenance reports that report operational conditions and equipment failure characteristics. The main objective of this study is to improve the efficiency when identifying the nature of a stoppage serving as a basis for the subsequent development of a reliable failure prediction system. The results indicate that this approach significantly increases information reliability, addressing the persistent challenges in data management within the maintenance area. With a classification accuracy of 96.2% and a recall of 96.3%, the model validates and automates the classification of stoppage events, significantly reducing dependency on interdepartmental interactions. This advancement eliminates the need for reliance on external databases, which have previously been prone to errors, missing critical data, or containing outdated information. By implementing this methodology, a robust and reliable foundation is established for developing a failure prediction model, fostering both efficiency and reliability in the maintenance process. The application of ML in this context produces demonstrably positive outcomes in the classification of stoppage events, underscoring its significant impact on industry operations. Full article

This paper compares concentrated and distributed reactive power compensation to improve the power factor at the point of common connection (PCC) of an industrial electrical system (IES) with harmonics. The electrical system under study has a low power factor, voltage variation, and harmonics caused by motors operating at low loads and powered by variable-speed drives. The designed compensation system mitigates harmonics and reduces electrical losses with the shortest payback period. Four solutions were compared, considering concentrated and distributed compensation with capacitor banks and harmonic filters. Although the cost of investment in concentrated compensation is lower than that of distributed compensation, a higher reduction in electrical losses and a lower payback period are obtained with distributed compensation. Although the lowest payback period was obtained with distributed compensation with capacitor banks (0.4 years), it is not recommended in the presence of harmonics because the effects of current harmonics significantly reduce the useful life of these elements. For this reason, distributed compensation with harmonic filters obtained a payback period of 0.6 years, and it was proposed as the best solution. These results should be considered in projects aimed at power factor compensation in IESs with harmonics. The concentrated compensation of the capacitor bank at the PCC is proposed because of the lower investment cost and ease of installation. However, the advantages of distributed compensation with harmonic filters have not been evaluated. An energy efficiency approach is used to analyze the impact of the location methods of the power factor compensation equipment on the electrical losses of the IES. Full article

The continued evolution of H3 subtype avian influenza virus (AIV)—which crosses the interspecific barrier to infect humans—and the potential risk of genetic recombination with other subtypes pose serious threats to the poultry industry and human health. Therefore, rapid and accurate detection of H3 virus is highly important for preventing its spread. In this study, a method based on real-time reverse transcription recombinase-aided isothermal amplification (RT–RAA) was successfully developed for the rapid detection of H3 AIV. Specific primers and probes were designed to target the hemagglutinin (HA) gene of H3 AIV, ensuring highly specific detection of H3 AIV without cross-reactivity with other important avian respiratory viruses. The results showed that the detection limit of the RT–RAA fluorescence reading method was 224 copies/response within the 95% confidence interval, while the detection limit of the RT–RAA visualization method was 1527 copies/response within the same confidence interval. In addition, 68 clinical samples were examined and the results were compared with those of real-time quantitative PCR (RT–qPCR). The results showed that the real-time fluorescence RT–RAA and RT–qPCR results were completely consistent, and the kappa value reached 1, indicating excellent correlation. For visual detection, the sensitivity was 91.43%, the specificity was 100%, and the kappa value was 0.91, which also indicated good correlation. In addition, the amplified products of RT–RAA can be visualized with a portable blue light instrument, which enables rapid detection of H3 AIV even in resource-constrained environments. The H3 AIV RT-RAA rapid detection method established in this study can meet the requirements of basic laboratories and provide a valuable reference for the early diagnosis of H3 AIV. Full article

This research investigates the relationship between stablecoin usage and tax evasion. We present a model that includes variables related to transactions such as intensity, frequency, environment on-chain (P2P) vs. off-chain (IntraVasp), and company characteristics such as age, sector, and size. Our model was empirically tested using a logistic regression based on data from the Brazilian Federal Revenue Service (Receita Federal do Brasil (RFB)) in 2021. This novel approach aims to understand the tax behaviours associated with stablecoin use in corporate financial practices. Our results indicate that the intensity, frequency, environment of transactions (specifically IntraVasp and P2P transactions), age, sector, and size are factors significantly associated with tax evasion behaviour. However, we found no evidence to suggest that firms engaging in only P2P transactions have a higher propensity for tax evasion than those engaging only in IntraVasp transactions. Our findings reveal that younger and medium-sized companies with intensive use of stablecoin, with high stablecoin transaction frequency, engaging in IntraVasp and P2P transactions, and belonging to the service sector are more likely to evade tax. Therefore, our research provides a detailed understanding of how digital financial practices with crypto assets (blockchain-based technology) intersect with corporate tax strategies, which can offer valuable insights for regulators, industry practitioners, and policymakers. Full article

P91 steel (X10CrMoVNb9-1) is widely used in the energy industry. It is characterized by good mechanical properties, creep resistance, corrosion resistance, impact toughness, and resistance to thermal fatigue. Due to their operating conditions and martensitic structure, components made from P91 steel are often subject to damage related to the presence of hydrogen. This article compares the results of the mechanical properties evaluation for P91 steel in an aggressive solution charged under load and without load. Based on the research, it was found that the hydrogen environment significantly affects the mechanical properties of P91 steel, reducing strength and yield strength, and decreasing ductility. It was revealed that in samples tested after 72 h without preloading, the tensile strength decreased by 1.5%, and the elongation decreased by about 29% for the sample, compared to the delivered condition sample. Under loaded conditions, the difference in tensile strength increased by approximately 8%, while elongation increased by nearly 50% Full article