This study aims to analyse and determine the effect of Big Data, the Internet of Things (IoT), and physical-cyber system variables on human factors in refinery industry operators and the influence of human factors and managerial initiatives on sustainable manufacturing. The method used in this study is a quantitative method using partial least square-structural equation modelling (PLS-SEM). The respondents in this study were workers of Indonesia\'s upstream oil and gas sector. The results of this study indicate that Big Data, IoT, and Physical Cyber Systems (PCS) have a positive and significant effect on the human factor. In addition, there is a significant relationship between human factors and sustainable manufacturing. Furthermore, it is also found that there is a relationship between managerial initiatives and sustainable manufacturing. However, the managerial initiative cannot moderate the human factor and sustainable manufacturing.
This research explores the profound influence of Industry 4.0 technologies, encompassing big data, IoT, and physical-cyber systems (PCS), on the human aspects of Indonesia’s oil and gas sector. The outcomes of this study offer valuable perspectives on how Industry 4.0 technologies can revolutionise the Indonesian oil and gas industry while underscoring the significance of factoring in human elements and sustainable practices within this dynamic landscape.

Recent maritime cybersecurity accidents reveal that shipping is facing increased exposure to cyber threats, especially due to the fast-growing digitalisation of the sector, leaving vessels and their onboard systems vulnerable to cyberattacks. This research aims at evaluating the relationship among the critical dimensions influencing cybersecurity performance in the maritime industry. To achieve this, six critical dimensions related to cybersecurity preparedness are first identified through literature review, namely \'regulations\', \'company procedures\' from a managerial perspective and \'shipboard systems readiness\', \'training and awareness\', \'human factor\' and \'compliance monitoring\' at an operation level. A Likert-scale questionnaire is designed and used to collect empirical data from 133 seafarers and shore-based staff. Structural Equation Modelling (SEM) is applied to examine the causal relationships between the six dimensions and shipboard cybersecurity performance. The results show that \'regulations\' positively influence shipping companies\' cybersecurity-related \'procedures\', which in turn positively affects \'shipboard systems readiness\', \'training and awareness\', and \'monitoring\'. Further, \'training and awareness\' positively influences the cybersecurity performance of ships. The results have profound implications for the shipping industry on how to strengthen their cyber practices in order to improve their cybersecurity performance. Recommendations for future academic research related to maritime cybersecurity are also provided.

The human condition is linked to error in any activity that is performed, and the healthcare world is no exception. The origin of human error does not lie within the perversity of human nature, instead, it has its origins in latent failures in the healthcare environment and is a consequence of the processes and procedures applied. The science of the Human Factor deals with the application of knowledge to people (capabilities, characteristics and limitations), with the design and the management of the equipment they use and with the environments in which they work and the activities they carry out. Part of the Human Factor are the non-technical skills. These skills greatly influence people\'s behavior and, therefore, their performance and the quality of healthcare in a very complex socio-technical system.

This paper takes ethnic minority villages in Yunnan province of China, which have significant characteristics of multi-ethnic integration, as the research object. Through various spatial statistical analysis methods, we analyzed the overall distribution characteristics of ethnic villages in Yunnan, the distribution difference among various ethnic groups, and the influencing factors of the distribution pattern. It was found that: (1) The ethnic minority villages in Yunnan generally exhibit a kernel density characteristic of \"three concentrated areas and multiple scattered points\" and distribution characteristic of \"hot spots in the west and cold spots in the east\". Each ethnic group has a relatively concentrated region, presenting significant ethnic autocorrelation. (2) The differences in the relationship between villages and landscape among various ethnic groups have given rise to a unique three-dimensional distribution pattern, which is relate to ethnic origin and livelihood culture. Meanwhile, Han traditional villages tend to occupy areas with relatively better geographical conditions. (3) Natural factors, such as topographic relief, the distance between ethnic villages and rivers, and elevation, have a significant impact on the distribution of ethnic villages in Yunnan. Meanwhile, test results of social and human factors, including the distance from central cities, per capita GDP, and the gross annual output values of primary industry, indicate that the development of social economy and the promotion of urbanization pose challenges to the preservation of ethnic villages.

Biopharmaceuticals are complex biological molecules that require careful storage and handling to ensure medication integrity. In this study, a work system analysis of real-world protein drug (PD) handling was performed with the following goals: identify main barriers and facilitators for successful adherence to accepted recommendations in PD handling, analyse differences in two organizations, and define a Best Current Practice in the real-life handling of PDs based on the results of the work system analysis. Observational study was held in two university hospitals in Spain and Sweden. Based on the Systems Engineering Initiative for Patient Safety (SEIPS) model, the tools chosen were: the PETT scan, in order to indicate the presence of barriers or facilitators for the PETT components (People, Environment, Tools, Tasks); the Tasks and tools matrices to construct a checklist to record direct observations during the real-life handling of biopharmaceuticals, and the Journey map to depict the work process. Observations were performed between March and November 2022. Each episode of direct observation included a single protein drug in some point of the supply chain and considered all the elements in the work system. Based on the results of the work system analysis and the literature review, the authors propose a list of items which could be assumed as Best Current Practice for PDs handling in hospitals. There were a total of 34 observations involving 19 PDs. Regarding People involved in the work process, there was a diversity of professionals with different previous training and knowledge, leading to an information gap. With respect to Environment, some structural and organizational differences between hospitals lead to risks related to the time exposure of PDs to room temperature and mechanical stress. Some differences also existed in the Tools and Tasks involved in the process, being especially relevant to the lack of compatibility information of PDs with new technologies, such as pneumatic tube system, robotic reconstitution, or closed-system transfer devices. Finally, 15 suggestions for best current practice are proposed. Main barriers found for compliance with accepted recommendations were related to the information gap detected in professionals involved in the handling of protein drugs, unmonitored temperature, and the lack of compatibility information of protein drugs with some new technologies. By applying a Human Factors and Systems Engineering Approach, the comparison of two European hospitals has led to a suggested list of Best Current Practices in the handling of protein drugs in a hospital.

The development of PFS requires a detailed understanding of the forces occurring during the drug administration process and patient\'s capability. This research describes an advanced mathematic injection force model that consisting hydrodynamic force and friction force. The hydrodynamic force follows the basic law of Hagen-Poiseuille but refines the modeling approach by delving into specific properties of drug viscosity (Newtonian and Shear-thinning) and syringe shape constant, while the friction force was accounted from empty barrel injection force. Additionally, we take actual temperature of injection into consideration, providing more accurate predication. The results show that the derivation of the needle dimension constant and the rheological behavior of the protein solutions are critical parameters. Also, the counter pressure generated by the tissue has been considered in actual administration to address the issue of the inaccuracies of current injection force evaluation preformed in air, especially when the viscosity of the injected drug solution is below 9.0 cP (injecting with 1 mL L PFS staked with 29G ½ inch needle). Human factor studies on patients\' capability against medication viscosity filled the gap in design space of PFS drug product and available viscosity data in very early phase.

UNASSIGNED: The tunnel section is a complex traffic scenario and an accident prone area. There are differences in the performance of different driving groups in tunnel environments, which may have an impact on traffic safety.
UNASSIGNED: To study the differences in the impact of tunnel environment on professional and non-professional drivers.
UNASSIGNED: Based on the vehicle experimental data, the electroencephalography (EEG) power was compared for professional and non-professional drivers. The impact of illumination changes and longitudinal slope on different driving groups was analyzed.
UNASSIGNED: At tunnel entrance with severely reduced lighting, the adaptation time of non-professional drivers to the light environment is 1.5 times that of professional drivers. When driving on the longitudinal slope, professional drivers perform better. The greater the longitudinal slope, the more obvious the advantages of professional drivers. However, in areas with relatively good traffic conditions, professional drivers are more prone to be distracted.
UNASSIGNED: Professional and non-professional drivers have their own advantages and disadvantages in the tunnel environment. In general, the driving adaptability of professional drivers is better than that of non-professional drivers in tunnel sections. The research conclusions provide a reference for driver safety training.

Vegetation plays a critical role in the water and carbon cycling and energy flow, serving as an indicator for regulating land carbon balance and reflecting climate change and human activities. We analyzed the spatiotemporal variations of normalized difference vegetation index (NDVI) during the growing season in southern Jiangxi from 2000 to 2020, using statistical methods, including the Mann-Kendall test, Theil-Sen Median analysis, Hurst index, and coefficient of variation. We employed the geodetector model to comprehensively assess the impacts of climate, topography, soil and human factors on spatial differentiation of vegetation NDVI. The results showed NDVI exhibited an upward fluctuating trend with a rate of 0.003 per year from 2000 to 2020. The proportion of high-grade and medium-high-grade NDVI areas were 55.8% and 41.9%, respectively, while the areas with low and relatively low fluctuations accounted for 92.3%. The proportions of areas showing extremely significant improvement and significant improvement were 40.4% and 19.4%, respectively. In contrast, the combined proportion of areas displaying extremely significant degradation and significant degradation was only 2.2%. The proportions of areas demonstrating continuous improvement and future improvement were 28.0% and 60.2%, respectively. Elevation, precipitation, relative humidity, temperature, landform type, land use type, population density, and nighttime light were identified as the major factors for the vairations of NDVI in the study area, followed by slope, soil type, and GDP, while slope aspect and vegetation type had indirect influence. Throughout the study period, NDVI in southern Jiangxi was overall stable, with future changes primarily indicating improvement. Notably, human factors such as land use type, population density, and nighttime light index exhibited an upward trend in their impacts on NDVI.
植被在水、碳循环和能量流动中起着重要作用,是调节陆地碳平衡和反映气候变化、人类活动的重要指标。本研究采用Mann-Kendall检验、Theil-Sen Median分析、Hurst指数和变异系数等方法分析2000—2020年赣南生长季植被归一化植被指数(NDVI)的时空变化,用地理探测器综合分析气候、地形、土壤和人为因子等对植被NDVI空间分异的影响。结果表明: 2000—2020年,植被NDVI以0.003·a-1的速率波动上升。高等级和中高等级植被NDVI面积占比分别为55.8%和41.9%,低波动变化和较低波动变化的区域面积占比为92.3%。植被NDVI极显著改善和显著改善面积占比分别为40.4%、19.4%,极显著退化和显著退化面积总占比仅为2.2%,持续改善和未来改善面积占比分别为28.0%和60.2%。高程、降水量、相对湿度、温度、地貌类型、土地利用类型、人口密度和夜间灯光指数为研究区植被NDVI的主要影响因子,其次是坡度、土壤类型和GDP,坡向和植被类型为间接影响因子。研究期间,赣南植被NDVI整体上稳定性较好,未来植被变化趋势以改善为主,人为因子中土地利用类型、人口密度和夜间灯光指数对植被NDVI的影响整体呈上升趋势。.

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Exploring metagenomic contigs and \"binning\" them into metagenome-assembled genomes (MAGs) are essential for the delineation of functional and evolutionary guilds within microbial communities. Despite the advances in automated binning algorithms, their capabilities in recovering MAGs with accuracy and biological relevance are so far limited. Researchers often find that human involvement is necessary to achieve representative binning results. This manual process however is expertise demanding and labor intensive, and it deserves to be supported by software infrastructure.
We present BinaRena, a comprehensive and versatile graphic interface dedicated to aiding human operators to explore metagenome assemblies via customizable visualization and to associate contigs with bins. Contigs are rendered as an interactive scatter plot based on various data types, including sequence metrics, coverage profiles, taxonomic assignments, and functional annotations. Various contig-level operations are permitted, such as selection, masking, highlighting, focusing, and searching. Binning plans can be conveniently edited, inspected, and compared visually or using metrics including silhouette coefficient and adjusted Rand index. Completeness and contamination of user-selected contigs can be calculated in real time. In demonstration of BinaRena\'s usability, we show that it facilitated biological pattern discovery, hypothesis generation, and bin refinement in a complex tropical peatland metagenome. It enabled isolation of pathogenic genomes within closely related populations from the gut microbiota of diarrheal human subjects. It significantly improved overall binning quality after curating results of automated binners using a simulated marine dataset.
BinaRena is an installation-free, dependency-free, client-end web application that operates directly in any modern web browser, facilitating ease of deployment and accessibility for researchers of all skill levels. The program is hosted at https://github.com/qiyunlab/binarena , together with documentation, tutorials, example data, and a live demo. It effectively supports human researchers in intuitive interpretation and fine tuning of metagenomic data. Video Abstract.