Research on the Vision-Based Dairy Cow Ear Tag Recognition Method.

With the increase in the scale of breeding at modern pastures, the management of dairy cows has become much more challenging, and individual recognition is the key to the implementation of precision farming. Based on the need for low-cost and accurate herd management and for non-stressful and non-invasive individual recognition, we propose a vision-based automatic recognition method for dairy cow ear tags. Firstly, for the detection of cow ear tags, the lightweight Small-YOLOV5s is proposed, and then a differentiable binarization network (DBNet) combined with a convolutional recurrent neural network (CRNN) is used to achieve the recognition of the numbers on ear tags. The experimental results demonstrated notable improvements: Compared to those of YOLOV5s, Small-YOLOV5s enhanced recall by 1.5%, increased the mean average precision by 0.9%, reduced the number of model parameters by 5,447,802, and enhanced the average prediction speed for a single image by 0.5 ms. The final accuracy of the ear tag number recognition was an impressive 92.1%. Moreover, this study introduces two standardized experimental datasets specifically designed for the ear tag detection and recognition of dairy cows. These datasets will be made freely available to researchers in the global dairy cattle community with the intention of fostering intelligent advancements in the breeding industry.

Towards a Human-Centric Digital Twin for Human-Machine Collaboration: A Review on Enabling Technologies and Methods.

With the intent to further increase production efficiency while making human the centre of the processes, human-centric manufacturing focuses on concepts such as digital twins and human-machine collaboration. This paper presents enabling technologies and methods to facilitate the creation of human-centric applications powered by digital twins, also from the perspective of Industry 5.0. It analyses and reviews the state of relevant information resources about digital twins for human-machine applications with an emphasis on the human perspective, but also on their collaborated relationship and the possibilities of their applications. Finally, it presents the results of the review and expected future works of research in this area.

Improving new energy subsidy efficiency considering learning effect: A case study on wind power.

Subsidy policies are instrumental in driving the development of new energy. However, the effective allocation of new energy subsidies over time is challenging given fiscal constraints. This study addresses this challenge by considering the learning effect associated with the new energy industry. A two-stage dynamic programming model is proposed to capture the investment decision-making process of companies under new energy subsidy policies and government subsidy setups. Theoretical findings suggest that company investment decisions in new energy are influenced by a guiding principle: The subsidy rate should be negatively correlated with the variation rate of production scale increment (VRPSI). We calibrate this investment decision principle using wind power data from 14 countries. According to this principle, excessive subsidy rates may result in a low VRPSI, thereby diminishing future investment profitability in the new energy industry and leading to subsidy inefficiency. Upon investigating the efficiency of annual subsidy allocation, we find that the subsidy rates were potentially set too high in 2014, 2016, and 2017. Furthermore, the government should exercise caution regarding an inefficient subsidy pattern whereby companies invest in new energy only when the subsidy rate exceeds a certain threshold, neglecting traditional power sources. It is crucial to note that although this study uses wind power industry data for calibration and simulation, the theoretical model can be broadly applied to other new energy industries and emerging industries with increasing marginal net profit.

Performance and robustness of small molecule retention time prediction with molecular graph neural networks in industrial drug discovery campaigns.

This study explores how machine-learning can be used to predict chromatographic retention times (RT) for the analysis of small molecules, with the objective of identifying a machine-learning framework with the robustness required to support a chemical synthesis production platform. We used internally generated data from high-throughput parallel synthesis in context of pharmaceutical drug discovery projects. We tested machine-learning models from the following frameworks: XGBoost, ChemProp, and DeepChem, using a dataset of 7552 small molecules. Our findings show that two specific models, AttentiveFP and ChemProp, performed better than XGBoost and a regular neural network in predicting RT accurately. We also assessed how well these models performed over time and found that molecular graph neural networks consistently gave accurate predictions for new chemical series. In addition, when we applied ChemProp on the publicly available METLIN SMRT dataset, it performed impressively with an average error of 38.70 s. These results highlight the efficacy of molecular graph neural networks, especially ChemProp, in diverse RT prediction scenarios, thereby enhancing the efficiency of chromatographic analysis.

60 Years of the 3Rs symposium: Lessons learned and the road ahead.

When The Principles of Humane Experimental Technique was published in 1959, authors William Russell and Rex Burch had a modest goal: to make researchers think about what they were doing in the laboratory - and to do it more humanely. Sixty years later, their groundbreaking book was celebrated for inspiring a revolution in science and launching a new field: The 3Rs of alternatives to animal experimentation. On November 22, 2019, some pioneering and leading scientists and researchers in the field gathered at the Johns Hopkins Bloomberg School of Public Health in Bal-timore for the 60 Years of the 3Rs Symposium: Lessons Learned and the Road Ahead. The event was sponsored by the Johns Hopkins Center for Alternatives to Animal Testing (CAAT), the Foundation for Chemistry Research and Initiatives, the Alternative Research & Development Foundation (ARDF), the American Cleaning Institute (ACI), the International Fragrance Association (IFRA), the Institute for In Vitro Sciences (IIVS), John "Jack" R. Fowle III, and the Society of Toxicology (SoT). Fourteen pres-entations shared the history behind the groundbreaking publication, international efforts to achieve its aims, stumbling blocks to progress, as well as remarkable achievements. The day was a tribute to Russell and Burch, and a testament to what is possible when people from many walks of life - science, government, and industry - work toward a common goal.

William Russell and Rex Burch published their book The Principles of Humane Experimental Technique in 1959. The book encouraged researchers to replace animal experiments where it was possible, to refine experiments with animals in order to reduce their suffering, and to reduce the number of animals that had to be used for experiments to the minimum. Sixty years later, a group of pioneering and leading scientists and researchers in the field gathered to share how the publi­cation came about and how the vision inspired international collaborations and successes on many different levels including new laws. The paper includes an overview of important milestones in the history of alternatives to animal experimentation.

Spatio-temporal heterogeneity and coupling effect of mining economy, social governance and environmental conservation: Evidence from Guangxi Zhuang Autonomous Region, China.

In order to solve the problem of coordinated development among mining economy, social governance and environmental conservation in global resource-based cities, we choose Guangxi Zhuang Autonomous Region as the research area. The advantage of resource endowment and resource industry was measured by location quotient and input-output method. The panel data related to mining governance from 2010 to 2021 were selected to build the evaluation and coupling analysis model between mining economic, social governance and environmental conservation, and the spatial-temporal heterogeneity and coupling effect of them were analyzed by comprehensive empowerment evaluation, spatial autocorrelation analysis and barrier degree methods. The results show that: (1) Except for the overall upward trend of social governance, the development level of mining economy and environmental conservation are basically stable; (2) The resource-rich areas have obvious mining economic advantages, and the central cities have good social governance capabilities, and the environmental conservation effectiveness is uncertain; (3) The coupling effect between mining economy and social governance is stronger than that between mining economy and environment conservation, and the synergistic coupling effect of the three is relatively random. Finally, we put forward some policy response strategies to Guangxi, and theoretical and practical reference would be provided for resource-based cities around the world.

Facile fabrication of amorphous Al/Fe based metal-organic framework as effective heterogeneous fenton catalyst for environmental remediation.

This study presents a facile preparation and durable amorphous Fe and Al-based MOF nanoplate (AlFe-BTC MOFs) catalyst with notable stability in Fenton reactions. Rigorous characterization using XRD, HR-TEM, and BET confirms the amorphous nature of the synthesized AlFe-BTC MOFs, revealing mesopores (3.4 nm diameter), a substantial surface area (232 m2/g), and a pore volume of 0.69 cc/g. XPS analysis delineates distinct Al2p and Fe2p binding energy values, signifying specific chemical bonding. FE-SEM elemental mapping elucidates the distinctive distribution of Fe and Al within the framework of AlFe-BTC MOFs. In catalytic activity testing, the amorphous AlFe-BTC MOFs exhibited outstanding performance, achieving complete degradation of Methylene blue (MB) dye and 78% TOC removal over 45 min of treatment under mild reaction conditions. The catalyst's durability was assessed, revealing about 75% TOC removal and complete dye decomposition over five successive recycles, with less than 1 mg/L of Fe and Al leaching. UV-Vis spectra revealed the destruction of MB dye over multiple recycling studies. Based on this finding, the amorphous AlFe-BTC MOF nanoplates emerge as a promising solution for efficient dye removal from industrial wastewater, underscoring their potential in advanced environmental remediation processes.

Occupational accidents in Slovak Military Forests and Estates: incidence, timing, and trends over 10 years.

Introduction: Forestry provides a wide range of employment opportunities worldwide and is seen as one of the high-risk industries in terms of occupational accidents. Objectives: The submitted study analyzed the injury rate in the Military Forests and Estates of the Slovak Republic (62.6 thousand ha) between 2013 and 2022. Methods: The data analyses included regression and correlation analyses, χ2 tests to analyze the relationships between studied variables, and incidence rates. Results: During the observed period, employees suffered 26 occupational accidents, of which 19.2% were light, 57.7% were registered, 23.1% were severe, and 0% were fatal. For every 1 million m3 of harvested timber, 7.7 accidents occurred. The incidence rate during the observed period was 672.1/100,000 employees. The highest proportion of accidents was in the age group 51-60 years and in employees with the lowest length of work experience <5 years. Regarding time, the highest proportion of occupational accidents occurred between 8:01 and 10:00 AM (53.8%) and day-wise on Thursdays (46.2%). The highest proportion of accidents occurred among forest workers (65.3%) during pruning and silviculture activities (42.3%). The most common injury site was forest stands (65.3%). Superficial injuries (34.6%) were the most common, mainly affecting the lower limbs (50%). The most frequent material agents causing the accidents were work and transport areas as sources of worker fall (38.5%), and the most frequent reason for an accident to occur was the lack of personal requirements for proper work performance (92.4%), whereas only (3.8%) of accidents occurred due to the use of forbidden or hazardous working procedures. Conclusion: The presented study identified the most vulnerable worker groups and provided an overview of the overall injury rate at the state forest company in Slovakia. The documentation can be incorporated into the safety strategies of forest enterprises.

Prioritization of control measures in leakage scenario using Hendershot theory and FBWM-TOPSIS.

Currently, there is increasing concern about the safety and leakage of process industries. Therefore, the present study aims to prioritize control measures before and after the leakage scenario by using the Hendershot theory and MCDM techniques. In this study, two proactive and reactive layers were selected before and after leakage of tanks, respectively. Then, criteria and alternatives were selected to perform fuzzy TOPSIS (FTOPSIS) and find the best alternative based on the literature review and Hendershot approach. The linear model of the fuzzy Best-Worst method (FBWM) was constructed and resolved using Lingo 17 software. Subsequently, criteria were assigned weights based on thorough calculations of the inconsistency rate. The weight of study experts was equal to 0.25. The results of FBWM showed that the reliability index with a weight of 0.3727 was ranked first and the inconsistency rate ([Formula: see text]) was calculated to be equal to 0.040. Inherent Safety Design (ISD) (0.899) and passive safety (0.767) also ranked first before and after tank leaks, respectively. Using the FBWM method leads to fewer pairwise comparisons and at the same time more stability. Although ISD and passive strategies are more valid and strict, elements of all strategies are necessary for a comprehensive process safety management program.

Gold Nanoparticles (AuNPs)-Toxicity, Safety and Green Synthesis: A Critical Review.

In recent years, the extensive exploration of Gold Nanoparticles (AuNPs) has captivated the scientific community due to their versatile applications across various industries. With sizes typically ranging from 1 to 100 nm, AuNPs have emerged as promising entities for innovative technologies. This article comprehensively reviews recent advancements in AuNPs research, encompassing synthesis methodologies, diverse applications, and crucial insights into their toxicological profiles. Synthesis techniques for AuNPs span physical, chemical, and biological routes, focusing on eco-friendly "green synthesis" approaches. A critical examination of physical and chemical methods reveals their limitations, including high costs and the potential toxicity associated with using chemicals. Moreover, this article investigates the biosafety implications of AuNPs, shedding light on their potential toxic effects on cellular, tissue, and organ levels. By synthesizing key findings, this review underscores the pressing need for a thorough understanding of AuNPs toxicities, providing essential insights for safety assessment and advancing green toxicology principles.

Employee Grievance Redressal and Corporate Ethics: Lessons from the Boeing 737-MAX Crashes.

Two Boeing 737-MAX passenger planes crashed in October 2018 and March 2019, suspending all 737-MAX aircraft. The crashes put Boeing's corporate practices and culture under the spotlight. The main objective of this paper is to use the case of Boeing to highlight the importance of efficient employee grievance redressal mechanisms and an independent external regulator. The methodology adopted is a qualitative analysis of statements of various whistleblowers and Boeing and the Federal Aviation Administration (FAA) stakeholders. It suggests that employee feedback flowing up the chain of command should be more flexible and dealt with more seriousness. It recommends that companies adopt a cooling-off period or a lifetime restriction for employees who have gone through the revolving door between regulators and the industry. The Boeing 737-MAX case, which emphasizes the ethical obligations of the job, can offer value to engineers, engineering educators, managers, ombudsmen, and human resource professionals.

[Exploration of Application of Reliability Standard YY/T 1837-2022 in Development of Active Implantable Medical Devices].

In the field of medical devices, there has been a long-term lack of a general technical requirements framework for reliability that can be applied in the development of high-risk active implantable medical devices. This study combines the requirements of YY/T 1837-2022 to comprehensively explain and explore the requirements for reliability work that can be performed at each stage of development of active implantable medical device products, and provides a reference for product reliability work in the industry.

Proceedings of the 2023 Viral Clearance Symposium, Session 1: Regulatory Updates.

At the time of the 2023 Viral Clearance Symposium in Vienna, the ongoing revision of ICH Guideline Q5A(R1) Viral Safety Evaluation of Biotechnology Products Derived from Cell Lines of Human or Animal Origin clearly was the dominant regulatory topic. At the symposium, the changes expected for Q5A(R2) to mirror advances of scientific knowledge, for example, the inclusion of new products, including viral-vector-derived ones, that can be subject to virus clearance, deliberations around continuous manufacturing processes, the use of prior knowledge to supplement or in part replace virus validation studies, and new molecular methods for detection of adventitious viruses, were discussed by a European and a US regulator as well as representatives from industry associations that had been involved with the drafting process.

Proceedings of the 2023 Viral Clearance Symposium: 2023 VCS Summary, Pending Questions, and Next Steps.

The 2023 Viral Clearance Symposium (VCS) was hosted by Takeda on 24 and 25 May 2023 in Vienna, Austria. The present conference extended the structure of the previous biennial symposia held between 2009 and 2019. As recapitulated in the introductory session, the genesis of the VCS, as described in the Proceedings of the 2009 VCS was "the worldwide regulatory and industry recognition that challenges, gaps, and opportunities exist, that it formally addressed could benefit the field as whole." This report provides a synopsis of the progress achieved at the conference resulting from detailed technical discussions and the pending questions that still require attention to address. The 2023 VCS was composed of nine individual sessions of short presentations followed by in-depth panel discussions from the presenters. Sessions included Regulatory Updates (with a focus on ICH Q5A(R2) efforts), including a summary of lessons learned from the 2019 VCS, and progress on these key areas mapped into 2023 VCS topics: Viral Clearance Strategy and Case Studies, New Modalities in Chromatography and Adsorptive Filters, Continuous Processing, Viral Clearance Strategy and Process Understanding, Virus Inactivation, Upstream and Downstream Virus Retentive Filtration and Cell Banks, and Advanced Technologies (advanced therapy medicinal products, next-generation sequencing).

Intelligence level evaluation and influencing factors analysis of equipment manufacturing industry in the Yangtze River Delta.

The Yangtze River Delta (YRD) bears the vital task of driving the growth of China's equipment manufacturing industry (EMI) intelligence as an advanced region. Fostering the transformation and upgrading of the EMI in the YRD and constructing a modern production mode is vital to developing and reforming China's manufacturing industry. This paper uses industrial robot data to assess the level of intelligence (LoI) in the EMI from 2016 to 2019. The OLS (ordinary least squares) model is used for the measurements, and the MQ (the modified contribution index) is used to estimate the degree of contribution from a host of variables. It is identified that the LoI is on the rise. However, excluding railways, aerospace, shipbuilding, and other transportation equipment manufacturing, the LoI is significantly higher than in other subsectors. It is also identified that technological innovation ability, human capital density, and enterprise cost pressure govern the industry's LoI. Moreover, while there is a difference in the main influencing factors in LoI within different industries, R&D investment, technological innovation ability, and enterprise cost pressure have the most significant impact across most equipment manufacturing sub-industries.

Digital economy, innovation factor allocation and industrial structure transformation-A case study of the Yangtze River Delta city cluster in China.

The attainment of regional high-quality development necessitates the critical role of the digital economy in facilitating the transformation of industrial structures. This study intends to investigate the effect of the digital economy on industrial structure transformation from the perspective of innovation factor allocation using a panel dataset of 41 cities in the Yangtze River Delta region for the period from 2011 to 2020. This paper considers four dimensions to measure the level of industrial structure transformation i.e. industrial structure servitization, industrial structure upgradation, service industry structure upgradation and industrial interaction level. The results of the study suggest that the digital economy can significantly improve industrial structure transformation. The results remain consistent even after several robustness checks. Further, the analysis of the mechanism of action shows that the digital economy can promote industrial structure transformation by optimizing the innovation factor allocation. The study provides several policy implications for the digital economy and its role in the promotion of industrial structure transformation.

Microorganism-mediated biodegradation for effective management and/or removal of micro-plastics from the environment: a comprehensive review.

Micro- plastics (MPs) pose significant global threats, requiring an environment-friendly mode of decomposition. Microbial-mediated biodegradation and biodeterioration of micro-plastics (MPs) have been widely known for their cost-effectiveness, and environment-friendly techniques for removing MPs. MPs resistance to various biocidal microbes has also been reported by various studies. The biocidal resistance degree of biodegradability and/or microbiological susceptibility of MPs can be determined by defacement, structural deformation, erosion, degree of plasticizer degradation, metabolization, and/or solubilization of MPs. The degradation of microplastics involves microbial organisms like bacteria, mold, yeast, algae, and associated enzymes. Analytical and microbiological techniques monitor microplastic biodegradation, but no microbial organism can eliminate microplastics. MPs can pose environmental risks to aquatic and human life. Micro-plastic biodegradation involves fragmentation, assimilation, and mineralization, influenced by abiotic and biotic factors. Environmental factors and pre-treatment agents can naturally degrade large polymers or induce bio-fragmentation, which may impact their efficiency. A clear understanding of MPs pollution and the microbial degradation process is crucial for mitigating its effects. The study aimed to identify deteriogenic microorganism species that contribute to the biodegradation of micro-plastics (MPs). This knowledge is crucial for designing novel biodeterioration and biodegradation formulations, both lab-scale and industrial, that exhibit MPs-cidal actions, potentially predicting MPs-free aquatic and atmospheric environments. The study emphasizes the urgent need for global cooperation, research advancements, and public involvement to reduce micro-plastic contamination through policy proposals and improved waste management practices.

A review of experimental Assessment Processes of material resistance to marine and freshwater biofouling.

Biofouling presents hazards to a variety of freshwater and marine underwater infrastructures and is one of the direct causes of species invasion. These negative impacts provide a unified goal for both industry practitioners and researchers: the development of novel antifouling materials to prevent the adhesion of biofouling. The prohibition of tributyltin (TBT) by the International Maritime Organization (IMO) in 2001 propelled the research and development of new antifouling materials. However, the evaluation process and framework for these materials remain incomplete and unsystematic. This mini-review starts with the classification and principles of new antifouling materials, discussing and summarizing the methods for assessing their biofouling resistance. The paper also compiles the relevant regulations and environmental requirements from different countries necessary for developing new antifouling materials with commercial potential. It concludes by highlighting the current challenges in antifouling material development and future outlooks. Systematic evaluation of newly developed antifouling materials can lead to the emergence of more genuinely applicable solutions, transitioning from merely laboratory products to materials that can be effectively used in real-world applications.