The accurate tracking of individual calves is essential for health monitoring. However, existing multi tracking frameworks often encounter frequent ID abnormal switching issues during occlusion. To address these challenges, we propose a novel multi-object tracking framework named YSD-BPTrack for calves in occluded environments on cattle farms in this paper. This framework mainly consists of two stages: detection and tracking. Concerning the detection phase, the DCNv4 is integrated into the YOLOv8s model to capture spatial deformation features caused by occlusion, thereby enhancing detection performance under occlusion. Additionally, the Star operation of StarNet is also applied to the model to achieve excellent detection performance with lower computational costs. Concerning the tracking stage, we first propose an innovative rematching algorithm (Rematching module) and a new trajectory removal strategy (Trajectory removal module). The Rematching module performs rematching with detection boxes utilizing extended trajectory prediction boxes in cases of occlusion, resulting in a reduced probability of ID switch errors. Moreover, the Trajectory Removal module dynamically adjusts the removal time for lost matching trajectories, which decreases the likelihood of trajectories being mistakenly removed. Specifically, our proposed novel framework achieves a HOTA (Higher Order Tracking Accuracy) of 91.6%, surpassing other frameworks in both track accuracy and efficiency. Experimental results also validate the superiority of the YSD-BPTrack, with HOTA increasing by 17.6%, MOTA (Multiple Object Tracking Accuracy) by 13.9%, MOTP (Multiple Object Tracking Precision) by 1.8%, IDF1 (Identification F1 Score) by 15.4%, and reducing parameters by 49.1%, IDSw (Identification Switches) by 88.9%, and computational overhead by 39.2% compared to the other frameworks. Overall, the proposed multi-object tracking framework has great potential to revolutionize the tracking of calves.
Background: West Java ranks the highest Province with Human Immunodeficiency Virus (HIV) case in 2023. An estimated 1.648 patients estimated receive antiretroviral therapy (ART). Kidney disease contributes mortality amongst people living with HIV/AIDS (PLWH). Tenofovir disoproxil fumarate (TDF)-based ART was associated as risk factor of kidney disorders, indicate by declining glomerular filtration rate (GFR). However, there is limited study whether kidney disease among PLWH were related to ART use in Indonesia.
Aims: To determine correlation between duration of antiretroviral therapy and glomerular filtration rate (GFR) in people living with HIV/AIDS.
Methods: This is an observational study with cross-sectional design. Eighty-nine HIV patients on antiretroviral therapy for at least three months with normal baseline GFR were studied. Estimated GFR calculated using the Cockcroft-Gault equation. Data obtained were analyzed with spearman correlation test.
Results: Among 89 subjects, as many as 38 patients (42.7%) on therapy less than 12 months, 29 patients (32.6%) were on ART more than 24 months, and 22 patients (24.7%) 12-24 months. ART with normal kidney function were 62 patients (69.7%). Whereas 29.2% were mildly decrease GFR, and only 1.1% were mild to moderate decrease GFR. The analytical statistic showed a no significant between duration of antiretroviral therapy and GFR in PLWH with a p-value of 0.199 and Spearman’s r of 0.137.
Conclusion: There was no significant correlation between duration of antiretroviral therapy and glomerular filtration rate in PLWH.
The most important component of national human capital reproduction is the higher education system, which has undergone radical reorganization over the past twenty years. The most acute issues have been highlighted, and the current trends in the higher education system development in modern conditions have been outlined. It has been suggested that the quality of human capital of scientific and pedagogical workers determines the labor resources quality of a country. The purpose of the study is an attempt to formulate a concept of a comprehensive approach to forming and developing human capital in higher education professors based on the analysis of existing theoretical and methodological approaches, scientific publications, comparative analysis of diverse information, as well as the current state of human resources potential of higher education institutions. Based on the formulated goal, the research tasks have been solved, including the study of theoretical and methodological basis, identificating key features of forming and developing human capital in higher education institutions, creating a mechanism of its formation and development, and determining indicators and indicators of the effectiveness of the current system. The authors’ mechanism of forming and developing human capital in higher education institutions has been proposed. Attention has been emphasized on the importance of ecosystem interaction for intellectual core development. The factors that increase or decrease human capital productivity have been highlighted.
Multiple parafoil landing is an enabling technology for massive supply delivery missions. However, it is still an open question to design a collision-free, computation-efficient guidance and control method for unpowered parafoils. To address this issue, this paper proposes a coordinated guidance and control method for multiple parafoil landing. First, the multiple parafoil landing process is formulated as a trajectory optimization problem. Then, the landing point allocation algorithm is designed to assign the landing point to each parafoil. In order to guarantee flight safety, the collision-free trajectory replanning algorithm is designed. On this basis, the nonlinear model predictive control algorithm is adapted to leverage the nonlinear dynamics model for trajectory tracking. Finally, the parafoil kinematic model is utilized to reduce the computational burden of trajectory calculation, and kinematic model is updated by the moving horizon correction algorithm to improve the trajectory accuracy. Simulation results demonstrate the effectiveness and computational efficiency of the proposed coordinated guidance and control method for the multiple parafoil landing.
Idalmis Acosta Pérez , Fernando Marrero Delgado , José Ángel Espinosa Acosta
et al.
Introducción: La inclusión de la gestión de riesgos de Seguridad y Salud en el Trabajo en la planificación estratégica constituye una herramienta necesaria para que la organización pueda anticiparse y mitigar posibles amenazas e identificar oportunidades para el crecimiento y la mejora continua.
Objetivo: Diseñar un procedimiento, científicamente fundamentado, que permita la inclusión de la gestión de riesgos de Seguridad y Salud dentro de la proyección estratégica, en aras de mejorar el sistema de gestión y por ende, el entorno laboral y las condiciones de trabajo.
Métodos: Incluyó el diseño de un procedimiento para la gestión estratégica de los riesgos de Seguridad y Salud, con una secuencia lógica de cuatro fases, que incluye métodos empíricos como el criterio de expertos y revisión de la documentación legal en materia de gestión de riesgo. Además, el procedimiento contiene pasos para la realización de un diagnostico estratégico donde se definen la política y la filosofía en materia de gestión de riesgos, se identifican los riesgos y se evalúan según la severidad, ocurrencia y detectatibilidad, para luego calcular el Nivel del Prioridad del Riesgo (NPR).
Resultados: Se logró la inclusión de los riesgos de Seguridad y Salud desde la planificación estratégica, además, se conoce el Nivel de Percepción de Convergencia Estratégica en la Gestión de Riesgos de SST (NCERSST).
Conclusiones: El procedimiento diseñado permitirá identificar las principales debilidades que presenta la organización relacionada con la gestión estratégica de sus riesgos
Introduction: The inclusion of Occupational Health and Safety risk management in strategic planning constitutes a necessary tool so that the organization can anticipate and mitigate possible threats and identify opportunities for growth and continuous improvement.
Objective: To design a scientifically based procedure, which allows the inclusion of Health and Safety risk management within the strategic projection, in order to improve the management system and therefore, the work environment and the working conditions.
Methods: Included the design of a procedure for the strategic management of Health and Safety risks, with a logical sequence of four phases, which includes empirical methods such as expert judgment and review of legal documentation on risk management. In addition, the procedure includes steps to carry out a strategic diagnosis where the policy and philosophy regarding risk management are defined, risks are identified and evaluated according to severity, occurrence and detectability, and then calculate the Priority Level of Risk (PLR).
Results: The inclusion of Health and Safety risks is achieved from the strategic planning, in addition, the Level of Perception of Strategic Convergence in (Security and health at work) Risk Management (NCERSST) is known.
Conclusions: The designed procedure will allow identifying the main weaknesses that the organization presents related to the strategic management of its risks
Medicine (General), Industrial hygiene. Industrial welfare
Surya N Reddy, Vaibhav Kurrey, Mayank Nagar
et al.
Proper use of personal protective equipment (PPE) can save the lives of industry workers and it is a widely used application of computer vision in the large manufacturing industries. However, most of the applications deployed generate a lot of false alarms (violations) because they tend to generalize the requirements of PPE across the industry and tasks. The key to resolving this issue is to understand the action being performed by the worker and customize the inference for the specific PPE requirements of that action. In this paper, we propose a system that employs activity recognition models to first understand the action being performed and then use object detection techniques to check for violations. This leads to a 23% improvement in the F1-score compared to the PPE-based approach on our test dataset of 109 videos.
Eloy Peña-Asensio, Álvaro-Steve Neira-Acosta, Juan Miguel Sánchez-Lozano
The selection of a landing site within the Artemis Exploration Zone (AEZ) involves multiple factors and presents a complex problem. This study evaluates potential landing sites for the Artemis III mission using a combination of Geographic Information Systems (GIS) and Multi-Criteria Decision Making (MCDM) methodologies, specifically the TOPSIS algorithm. By integrating topographic, illumination, and mineralogy data of the Moon, we assess 1247 locations that meet the Human Landing System (HLS) requirements within 13 candidate regions and Site 004 near the lunar south pole. Criteria considered include surface visibility, HLS-astronaut line of sight, Permanently Shadowed Regions (PSRs), sunlight exposure, direct communication with Earth, geological units, and mafic mineral abundance. Site DM2 (Nobile Rim 2), particularly the point at latitude 84°12'5.61" S (-84.20156°) and longitude 60°41'59.61" E (60.69989°), is the optimal location for landing. Sensitivity analysis confirms the robustness of our approach, validating the suitability of the best location despite the MCDM method employed and variations in criteria weightings to prioritize illumination and PSRs. This research demonstrates the applicability of GIS-MCDM techniques for lunar exploration and the potential benefits they can bring to the Artemis program.
As quantum computing continues to advance, its ability to compromise widely used cryptographic systems projects a significant challenge to modern cybersecurity. This paper outlines a strategic roadmap for industries to anticipate and mitigate the risks posed by quantum attacks. Our study explores the development of a quantum-resistant cryptographic solutioning framework for the industry, offering a practical and strategic approach to mitigating quantum attacks. We, here, propose a novel strategic framework, coined name STL-QCRYPTO, outlines tailored, industry-specific methodologies to implement quantum-safe security systems, ensuring long-term protection against the disruptive potential of quantum computing. The following fourteen high-risk sectors: Financial Services, Banking, Healthcare, Critical Infrastructure, Government & Defence, E-commerce, Energy & Utilities, Automotive & Transportation, Cloud Computing & Data Storage, Insurance, Internet & Telecommunications, Blockchain Applications, Metaverse Applications, and Multiagent AI Systems - are critically assessed for their vulnerability to quantum threats. The evaluation emphasizes practical approaches for the deployment of quantum-safe security systems to safeguard these industries against emerging quantum-enabled cyber risks. Additionally, the paper addresses the technical, operational, and regulatory hurdles associated with adopting quantum-resistant technologies. By presenting a structured timeline and actionable recommendations, this roadmap with proposed framework prepares industries with the essential strategy to safeguard their potential security threats in the quantum computing era.
When a high impedance fault (HIF) occurs in a distribution network, the detection efficiency of traditional protection devices is strongly limited by the weak fault information. In this study, a method based on S-transform (ST) and average singular entropy (ASE) is proposed to identify HIFs. First, a wavelet packet transform (WPT) was applied to extract the feature frequency band. Thereafter, the ST was investigated in each half cycle. Afterwards, the obtained time-frequency matrix was denoised by singular value decomposition (SVD), followed by the calculation of the ASE index. Finally, an appropriate threshold was selected to detect the HIFs. The advantages of this method are the ability of fine band division, adaptive time-frequency transformation, and quantitative expression of signal complexity. The performance of the proposed method was verified by simulated and field data, and further analysis revealed that it could still achieve good results under different conditions.
Energy conservation, Energy industries. Energy policy. Fuel trade
Motivated by swings in the exchange rate of many developing economies which
exert influence on firms’ input costs, output, stock prices, and profits,
the study investigated the asymmetric reactions of stock prices and
industrial output to various shocks in the exchange rate in Nigeria using a
multiple threshold nonlinear autoregressive distributed lag model and high
frequency series from January 1999 to December 2021. Empirical results
suggest that stock prices and industrial output react asymmetrically in the
opposite direction to exchange rate depreciation. It further indicates that
the reactions of both stock prices and industrial output to exchange rate
changes are sensitive to the size of shocks. Exchange rate shocks above the
25th percentile significantly and inversely affect both stock prices and
industrial output, and the effects of exchange rate shocks on stock prices
and industrial output become pernicious if above the 75th percentile. The
main economic implication of the empirical finding is that in the upper
quantile, both exchange rate depreciation and appreciation hurt industrial
output, and hence, stock values. Thus, the multiple threshold nonlinear
autoregressive distributed lag results suggest that the reactions of both
stock prices and industrial output to exchange rate changes are highly
sensitive to the extent of the shocks.
Mattia Secchiero, Nishanth Bobbili, Yang Zhou
et al.
Autonomous identification and evaluation of safe landing zones are of paramount importance for ensuring the safety and effectiveness of aerial robots in the event of system failures, low battery, or the successful completion of specific tasks. In this paper, we present a novel approach for detection and assessment of potential landing sites for safe quadrotor landing. Our solution efficiently integrates 2D and 3D environmental information, eliminating the need for external aids such as GPS and computationally intensive elevation maps. The proposed pipeline combines semantic data derived from a Neural Network (NN), to extract environmental features, with geometric data obtained from a disparity map, to extract critical geometric attributes such as slope, flatness, and roughness. We define several cost metrics based on these attributes to evaluate safety, stability, and suitability of regions in the environments and identify the most suitable landing area. Our approach runs in real-time on quadrotors equipped with limited computational capabilities. Experimental results conducted in diverse environments demonstrate that the proposed method can effectively assess and identify suitable landing areas, enabling the safe and autonomous landing of a quadrotor.
It is highly predicted that the roads and parking areas will be extremely congested with vehicles to the point that searching for a novel solution will not be an optional choice for conserving the sustainability rate of the overall humanity's development growth. Such issue could be overcome by developing modified generations of the Urban Air Mobility (UAM) vehicles that essentially depend on the Vertical and/or Short Take-Off and Landing (V/STOL) feature to increase the efficiency of landing capabilities on limited-space parking areas. The complexity of integrating an efficient and safe V/STOL feature in such UAM vehicles is notably difficult comparing with the conventional and normal techniques for landing and take-off. The efficient V/STOL feature should be carried out by a complete and collaborative Cyber-Physical System (CPS) processing architecture, such as the CPS-5C architecture. In this paper, we only proposed two CPS-5C physical layers of a V/STOL Autonomous Landing Guidance Assistant System (ALGAS2) processing unit to increase the reliability of the vertical landing mechanism. The proposed V/STOL-ALGAS2 system depends on Fuzzy Logic System (FLS) as the advanced control unit. Furthermore, the proposed ALGAS2 system depends on four symmetric and segregated processing ALGAS2 cores that processing the data in a fully parallel and independent manner to enhance many essential security and safety factors for the futuristic UAM vehicles. The proposed ALGAS2 digital circuits architecture has been designed using MATLAB and VHDL. Also, it has been further analyzed for the implementation and validation tests using the Intel Altera OpenVINO FPGA board. The proposed ALGAS processing unit attained a maximum computational processing performance of about 21.22 Giga Operations per Seconds (GOPS).
Governments have been introducing regulations alongside sustainability-focused incentives, programs, and policies to help address environmental issues associated with agriculture. In this new ecological and policy context, where the socio-economic consequences of environmental limits are beginning to be experienced, old questions are being asked about how agricultural producers engage with advice and advisors and what factors might facilitate a faster transition to more sustainable land use. This paper presents research from Aotearoa New Zealand where a nationwide survey and focus groups have examined how producers are using advisory services. The research draws on the ‘triggering change’ cycle to explain how imperatives to shift to more sustainable land use are changing the knowledge practices of producers and their relationships with farm advisors. The research highlights the importance of conceiving producers as curators of advice and information rather than mere recipients, which involves doing their own research to identify what role they want an advisor to play. These findings have important implications for the development of future extension programs to help producers adopt, adapt and/or co-design more sustainable land use practices.
Purpose ─ The paper empirically explores the conditioning role of loan portfolio diversification in the monetary policy pass-through via the bank lending and risk-taking channels.
Methods ─ Data of Vietnamese commercial banks during 2007–2019 is employed to perform regression using the two-step system generalized method of moments in dynamic panel models. For robustness, we approach different choices of monetary policy indicators, ranging from interest-based tools to quantitative-based policy, and consider a rich set of sectoral exposure measures to proxy loan portfolio diversification.
Findings ─ Lower interest rates or greater liquidity injection during monetary expansion may increase bank lending and bank risk, thus confirming the working of the bank lending and risk-taking channels of monetary policy transmission. Notably, the potency of these banking channels may be weakened for banks diversifying loan portfolios more into various economic sectors.
Implication ─ The findings call for monetary authorities to concentrate on certain types of banks, depending on their loan portfolios when setting monetary policy. When managing banking supervision, banking supervisors should also acknowledge the tradeoff between bank lending and bank risk in response to monetary shocks.
Originality ─ For the first time, this paper explores the conditional role of loan portfolio composition and thus further supports the recent upsurge in empirical studies highlighting the role of business models in monetary policy pass-through.
Economic growth, development, planning, Regional economics. Space in economics