Resource Assessment Research Articles

Psychological Capital Promotion in Universities

Abstract Background The rise in student depression and anxiety highlights a crucial intersection between education and public health. Academic pressures intensify mental health issues, necessitating comprehensive strategies to address them. Objectives This study assessed the effectiveness of a Psychological Capital (PsyCap) intervention in enhancing university students’ PsyCap and reducing anxiety, aligning with broader public health education goals. Methods A randomized controlled trial was conducted, where students either received a PsyCap intervention or were placed on a wait-list. The intervention, based on Luthans et al.’s guidelines, was delivered online and included self-reflection, goal-setting, and resource assessment. Results Post-intervention, the PsyCap of students in the intervention group significantly increased (M = 1.098, SD = 0.24, CI [0.98, 1.21], t(17) = 19.72, p < .001). There was also a significant reduction in GAD scores (M = -0.24, SD = 0.46, CI [-0.47, -0.01], t(17) = -2.19, p = .043). No significant changes were observed in the control group. Conclusions Short-term PsyCap interventions can significantly improve students’ mental resilience and decrease anxiety, suggesting their integration into educational curricula. This study underlines the need for educational and public health sectors to collaborate in mitigating mental health issues among students, particularly in response to crises like COVID-19. Addressing the rising anxiety among students through brief, online PsyCap interventions shows promise. This approach not only enhances PsyCap but also lowers anxiety, advocating for their regular inclusion in educational settings to support student mental health. Key messages • Results from a controlled trial revealed increases in PsyCap and decreases in anxiety.Findings advocate integrating such interventions into educational curricula promoting student mental health. • Recent trends indicate a rise in anxiety among students, challenging both educational and public health. Addressing this, the study evaluated the impact of a brief online (PsyCap) intervention.

Ocean Wave Energy Conversion: A Review

The globally increasing demand for energy has encouraged many countries to search for alternative renewable sources of energy. To this end, the use of energy from ocean waves is of great interest to coastal countries. Hence, an assessment of the available resources is required to determine the appropriate locations where the higher amount of wave energy can be generated. The current paper presents a review of the resource characterizations for wave energy deployment. The paper gives, at first, a brief introduction and background to wave energy. Afterward, a detailed description of formulations and metrics used for resource characterization is introduced. Then, a classification of WECs (wave energy converters) according to their working principle, as well as PTO (power take off) mechanisms used for these WECs are introduced. Moreover, different sources for the long-term characterization of wave climate conditions are reviewed, including in situ measurements, satellite altimeters, and data reanalysis on one hand, and numerical simulations based on spectral wave models on the other hand. Finally, the review concludes by illustrating the economic feasibility of wave farms based on the use of the levelized cost of the energy index.

Model for Predicting Maize Crop Yield on Small Farms Using Clusterwise Linear Regression and GRASP

Planting a crop involves several key steps: resource assessment, crop selection, crop rotation, planting schedules, soil preparation, planting, care, and harvesting of crops. In this context, estimating the productivity of a crop based on available information, such as expected climatic conditions and agricultural practices, helps farmers reduce the uncertainty of their investment. In Colombia, maize is the fourth most important crop in the country. Significant efforts are required to improve productivity in traditional and technified production systems. In this sense, this research proposes and evaluates an approach called Clusterwise Linear Regression (CLR) to predict the crop maize yield in small farms, considering data on climate, soil, fertilization, and management practices, among others. To develop the CLR model, we conducted the following steps: data collection and preparation, clustering using k-means, cluster optimization with Greedy Random Adaptive Search Procedure (GRASP), and performance evaluation. The cluster optimization process allows the identification of clusters with similar characteristics and generates multiple linear regression models with mixed variables that explain the yield of the farms on each cluster. The Simulated Multiple Start Annealing (MSSA) metaheuristics were also evaluated, but the results of GRASP were the best. The results indicate that the proposed CLR approach is more effective than the linear and nonlinear algorithms mentioned in the literature, such as multiple lasso linear regression, random forests, XGBoost, and support vector machines. These algorithms achieved an accuracy of 70%. However, with the new CLR model, a significantly improved accuracy of 87% was achieved with test data. The clusters’ studies revealed key factors affecting crop yield, such as fertilization, drainage, and soil type. This transparency is a benefit over black-box models, which can be harder to interpret. This advancement can allow farmers to make better decisions about the management of their crops.

A modified transactional model of stress and coping on depressive symptoms among informal caregivers of persons with dementia

Informal caregivers are crucial to the care of persons with dementia (PWD), but their role is often reported as challenging. This study aims to examine caregiver stress and depressive symptoms among informal caregivers of PWD using a modified transactional stress and coping model. Path analysis was conducted among a sample of informal caregivers of PWD in Singapore (n = 281) using information on functional dependence and memory and behavioral problems of PWD, and self-reported measurements on caregivers’ knowledge of dementia, perceived positive aspects of caregiving, social support, coping patterns, caregiving self-efficacy, caregiving burden and depressive symptoms. The initial model reflecting our assumptions for the transactional stress and coping model showed a poor fit (model 1 - CFI = 0.858, TLI = 0.665, RMSEA = 0.118). Logical modifications were made until sufficient model fit was achieved (model 2 - CFI = 0.987, TLI = 0.955, RMSEA = 0.043). We then removed the insignificant paths in model 2 and obtained our final model (model 3 - CFI = 0.990, TLI = 0.974, RMSEA = 0.033). The final model supported our hypotheses, with some adjustments. This study advances our understanding of caregiver distress by modifying the transactional stress and coping model, including (1) the key role of caregiver self-efficacy in the primary appraisal process, (2) the dynamic assessment of coping resources across all stages of the model, and (3) the importance of coping patterns. Future studies could explore the generalizability of these findings.

Assessment of Clinical Toxicological Resources in Countries Belonging to the World Health Organization's Regional Office of the Eastern Mediterranean.

Poison Centers are vital to prevent and manage exposures to chemicals, toxins, and ionizing radiation. However, many countries still lack sufficient poison information center services. Within the World Health Organization's Eastern Mediterranean Regional Office (EMRO) region, we were not able to identify a formal assessment of its toxicological resources. We sought to assess the clinical toxicological resources in the EMRO region and the attitudes, needs, andperspective of the workforce in thatregion. METHODS: This was a two part survey study. First, wedeveloped a poison center questionnaire and scoring system based on the World Health Organization's Guidelines for Establishing a Poison Center; thisinstrument wasadministeredby phone to poison center directors and faculty in the EMROregion. Questions assessed for the presence or absence of important poison center capabilities listed in the WHO guidelines, and points were assigned based on response. Secondly, we administered an electronicworkforce survey to clinical toxicology professionals in the region; participanteligibility for the workforce survey was based on themembership roster ofMENATOX. Out of 22 EMRO countries, 16 countries have an established poison center, and 14 of 16 participated in the poison center survey. The results reflected a wide variability in capabilities amongcountries. Areas such as call centers, clinical toxicology units, laboratory services, and data management were relatively lacking while some other areas including toxicovigilance, chemical incidents and emergencies, antidotes/antivenoms, poisoning information sources, and the availability of free services were relatively stronger.Twenty-seven out of 32 workforce respondents were physicians. Results from that survey highlighted a desire for more support from government and better compensation. Our studyidentified areas of need for the EMRO region.The poison center survey results reflect large disparities amongcountries with some areas being stronger than others. The workforce survey highlighted issues such as compensation and government recognition. Overall, a formal assessment of individual poison centers can provide benchmarks to drive improvement of services, but further research is needed to identify and characterize country-specific needs.

School adjustment experiences of ventilator-dependent children: A phenomenological study of mothers' perspectives

PurposeThis study aimed to describe the experiences of ventilator-dependent children (VDC) in adjusting to school life from the perspectives of their mothers. Design and methodThis study employed a descriptive phenomenological approach. From July 2021 to September 2022, ten mothers of VDC were recruited via purposive sampling and underwent in-depth individual interviews. Data were analyzed using Colaizzi's phenomenological method. This study adheres to the COREQ guidelines for qualitative study. FindingsFour themes emerged: (1) the transition and burden of the mother's role; (2) positive adjustment and assessment of resources; (3) develop strategies to meet health and learning needs; (4) expectations for accessible school environments. ConclusionsThe mothers extensively assessed and adjusted their coping strategies on a rolling basis to ensure that their children received the resources that met their individual needs, promoted peer interactions, and helped adjustment to school life. The children's improvement and progress surpassed their mothers' expectations and demonstrated the benefits of a school education. Future educational settings should focus on building accessible school environments for special needs children. Practice implicationsThese findings allow healthcare professionals to assess the needs of VDC at different educational levels and create care plans that meet their healthcare and educational needs. This study also provides a reference for amending policies and regulations on individualized educational programs for VDC and developing guidelines for realizing accessible school environments to help them adjust to school life.

Delineation of Groundwater Potential Zones Using Geospatial Techniques. Case Study: Roman City and the Surrounding Area in the Northeastern Region, Romania

Effective groundwater management is crucial under the current climatic conditions, addressing both qualitative and quantitative aspects. An important step in delineating groundwater potential zones involves remote sensing (RS) data and geographic information systems (GISs), facilitating resource assessment, and the implementation of suitable field data management. This study introduces the delineation of potential groundwater zones using seven layers and the Multi-Criteria Decision Analysis (MCDA) method. Satty’s Analytic Hierarchy Process (AHP) was employed to rank the seven selected parameters, contributing to the advancement of groundwater research and resource assessment. All seven thematic layers (Rainfall, Geology, Land Use/Land Cover, Drainage Density, Elevation, Slope, and Soil) were prepared and analyzed to delineate groundwater potential zones. The resulting groundwater potential zone map was categorized into four classes, Very Good, Good, Moderate, and Poor, covering areas of 81.53 km2 (45.1%), 56.36 km2 (31.2%), 19.54 km2 (10.8%), and 23.17 km2 (12.8%) of the total area, respectively. The accuracy of the output was validated by comparing it with information on groundwater prospects in the area, and the overall accuracy of the method was approximately 72%. High-yield boreholes were drilled and concentrated in the Very Good groundwater potential zones, while low-yield ones were developed in the Poor areas.

Spatial Configuration and Accessibility Assessment of Recreational Resources in Hainan Tropical Rainforest National Park

Recreational resources, fundamental to ecological experiences, are critical in balancing conservation with development. Effective ecotourism planning is especially vital for newly established protected areas such as the Hainan Tropical Rainforest National Park in China’s developing system of natural conservation areas. Targeting Hainan Tropical Rainforest National Park, this study applies nearest neighbor index, kernel density analysis, and exploratory spatial data analysis (ESDA) to study the spatial pattern of 274 recreational resource points. Results indicate a clustered spatial pattern with significant differences in resource density among municipalities. Specifically, 98% of these resources can be reached in 3 h, with an average travel time of 91 min, and cultural resources exhibit greater accessibility than natural resources. Natural resource availability and ethnic culture are major factors of resource distribution and accessibility. This research offers a theoretical basis and practical guidance for optimizing recreational resource allocation and promoting ecotourism in the park, contributing to the ongoing discussion of sustainable tourism development.

Assessment of agroclimatic resources in agricultural landscapes of the Turkestan region of the Republic of Kazakhstan Askha

The article presents the scientific results of a study assessing agroclimatic resources in agricultural landscapes located in various natural zones of the Turkestan region of the RK (Republic of Kazakhstan). The research methods included classical and modern methods of mathematical statistics using digital technology and time series graphs to develop a mathematical model for climatic and hydrological indicators. Assessment of changes in indicators of agroclimatic resources in agricultural landscapes for 1941–2020 showed that the sum of air temperature, evaporation from the water surface and radiation balance of the daytime surface, characterising the energy resources of landscapes, increased by 10–15%, which contributes to increase in the total water consumption of agricultural land by 10–12%. Meanwhile, the decreasing tendency of the amount of precipitation by 5–10% in all natural climatic zones of the region has become one of the factors leading to a decrease in the natural moisture supply of the soil and vegetation cover of landscapes by 10–15%, acting as important environment-forming and ecological functions. The combined impact of these environment-forming factors has become the key reason for the increase in the deficit of agricultural land water consumption by 15–20%, the reduction of solar energy costs for the soil-forming process by 10–15% and the increase of the climate aridisation, and has become a signal for the need in the safety of agricultural activities, requiring the development of a set of adaptive measures to mitigate this process in the region.

Wind power plant site selection problem solution using GIS and resource assessment and analysis of wind energy potential by estimating Weibull distribution function for sustainable energy production: The case of Bitlis/Turkey

Wind energy, being a sustainable energy source, is a benign, dependable, limitless, and cost-effective source of energy. This study involved the creation of a wind power plant site selection map at a provincial scale using a GIS application. The map took into account both environmental risks and environmental criteria. A wind energy measurement station of the PCE-FWS 20 type, equipped with a touch screen, was installed in the Rahva campus of Bitlis Eren University. Over the course of one year, data on wind direction, wind speed, temperature, relative humidity, and air pressure were collected at 5-s intervals and averaged over 20-min periods. The purpose of this study was to assess the suitability of the measured region for wind energy potential. A comprehensive statistical analysis was conducted using all the data collected during this period to assess the wind energy potential in the studied region. The Weibull distribution was employed to analyse the wind energy potential of this particular region. We employed graphical techniques to ascertain the Weibull distribution. The wind data analysis and simulation were conducted using the Matlab application. Analysed were the monthly statistical wind energy potential of the region, wherein the average wind speed and power density values were determined and presented through graphs at 20-min intervals. Upon analyzing the map generated using the Geographical Information Systems (GIS) technique, it has been ascertained that Bitlis Eren University Rahva campus is located in favorable areas.

Presenting a transdisciplinary robust approach for comprehensive assessment of large-scale underground water resources in western Indo-Gangetic Basin

Overexploitation, pollution, and anthropogenic activities threaten the sustainability of groundwater resources in the western Indo-Gangetic Basin. Meanwhile, distinguishing regions prone to contamination and understanding the natural and anthropogenic factors affecting groundwater quality is challenging due to the heterogeneous nature of aquifer systems and the lack of high-resolution spatial and temporal data on aquifer protective hydrogeological layers. This study presents a transdisciplinary robust approach combining regional electrical resistivity surveys, hydrogeological data, physicochemical analyses, and geospatial datasets to identify regions prone to contamination and understand the impacts of natural and anthropogenic factors on groundwater resources. This approach involves three key steps: evaluating the geohydraulic nature of aquifer protective hydrogeological layers, mapping the aquifer vulnerability index (AVI), and conducting comparative analyses of potentially vulnerable areas with groundwater quality index (GWQI) and hydrological factors. Firstly, model-based inversion of ID Vertical Electrical Sounding (VES) data provides insights into geoelectrical indices such as depth, thickness, apparent resistivity, longitudinal conductance, transverse resistance, and longitudinal resistivity of aquifer protective hydrogeological layers. Second, the Artificial Neural Network (ANN) model is used as a multilayer perceptron network to simulate hydraulic conductivity (K) using geoelectrical indices of aquifer protective hydrogeological layers. Subsequently, by considering ANN-derived K and VES-derived h of aquifer protective hydrogeological layers, the dynamic hydraulic resistance to the vertical flow of wastewater through the protective hydrogeological layers evaluated the index of the potentially vulnerable areas. Comparative analyses of potentially vulnerable areas with GWQI and hydrological factors (e.g., digital elevation model, soil, drainage density, lineament density, slope) enhance understanding regions prone to contaminants and land surface stress. Findings show that the ANN approach to simulate K, reducing effort with costs associated with slug testing is significant for AVI assessment. Furthermore, the geohydraulic characteristics, vulnerability indexing, and comparative analyses assist in identifying contamination-prone areas, improving groundwater resource protection and exploration activities.

Hydrological Modeling to Unravel the Spatiotemporal Heterogeneity and Attribution of Baseflow in the Yangtze River Source Area, China

Revealing the spatiotemporal variation in baseflow and its underlying mechanisms is critical for preserving the health and ecological functions of alpine rivers, but this has rarely been conducted in the source region of the Yangtze River (SRYR). Our study employed the Soil and Water Assessment Tool (SWAT) model coupled with two-parameter digital filtering and geostatistical approaches to obtain a visual representation of the spatiotemporal heterogeneity characteristics of the baseflow and baseflow index (BFI) in the SRYR. The SWAT model and multiple linear regression model (MLR) were used to quantitatively estimate the contribution of climate change and human activities to baseflow and BFI changes. The results underscore the robust applicability of the SWAT model within the SRYR. Temporally, the precipitation, temperature, and baseflow exhibited significant upward trends, and the baseflow and BFI showed contrasting intra-annual distribution patterns, which were unimodal and bimodal distribution, respectively. Spatially, the baseflow increased from northwest to southeast, and from the watershed perspective, the Tongtian River exhibited higher baseflow values compared to other regions of the SRYR. The baseflow and BFI values of the Dangqu River were greater than those of other tributaries. More than 50% of the entire basin had an annual BFI value greater than 0.7, which indicates that baseflow was the major contributor to runoff generation. Moreover, the contributions of climate change and human activities to baseflow variability were 122% and −22%, and to BFI variability, 60% and 40%. Specifically, precipitation contributed 116% and 60% to the baseflow and BFI variations, while the temperature exhibited contributions of 6% and 8%, respectively. Overall, it was concluded that the spatiotemporal distributions of baseflow and the BFI are controlled by various factors, and climate change is the main factor of baseflow variation. Our study offers valuable insights for the management and quantitative assessment of groundwater resources within the SRYR amidst climate change.

Research on Evaluation Method of Natural Gas Hydrate Resources Based on Probability Distribution Model

Natural gas hydrate, as a highly efficient and clean energy source, has garnered significant attention from both developed and energy-deficient nations. However, to achieve industrial application, several technical challenges must be addressed, including resource exploration, spatial positioning, resource assessment, economic production evaluation, and climate change impact assessment. Currently, our exploration and evaluation system for gas hydrate resources remains immature. This study aims to determine the probability distribution of effective thickness, porosity, and saturation of natural gas hydrate resource parameters in the study area and their variations. Utilizing probability statistics theory, we calculated specific values for all gas hydrate resource parameters from open-source data of 14 exploration well locations, determined their probability distributions, and conducted distribution detection to identify specific distributions. Data analysis was performed using linear graphs and bar charts to summarize patterns. Subsequently, by applying the mathematical formula Q = A×Z×∅×S×E, we categorized natural gas hydrate resource parameters, calculated gas hydrate resources at each effective depth, determined the probability distribution of each obtained data point, and ultimately solved for the total natural gas hydrate resources, yielding a final solution of 31875763695.08.

Field-scale variability and dynamics of soil moisture in Southwestern Nigeria

This research leverages field-based sensors and Geographic Information Systems (GIS) to elucidate soil moisture dynamics across diverse land uses in Southwestern Nigeria, including Cocoa, Cassava, Oil Palm, and Riparian ecosystems. The study synthesizes soil moisture data and geospatial coordinates from strategically selected land covers with satellite-derived soil moisture records from NASA's Prediction of Worldwide Energy Resources (POWER) and the US Geological Survey. Through a robust analytical framework combining cross-correlation functions, wavelet analysis, and inverse distance weighting interpolation, we revealed distinct soil moisture patterns ranging from 0 to 47.9% in arable farms, 0 to 46.8% in built-up areas, 0 to 49.9% in cocoa farms, 0.2 to 49.7% in oil palm farms, and 5.6 to 94.1% in riparian vegetation. The coefficient of determination values between 0.7 and 0.97 (p ≤ 0.05) underscore the significant influence of periodic land use on soil moisture during the study period. A comparative analysis of ground-based and satellite data revealed a potential overestimation of minimum soil moisture values by 66% and an underestimation of maximum values by 4%. This investigation provides critical insights into the interplay between hydrological variables and agro-meteorological factors, informing the management and assessment of agricultural resources.

HYDROLOGICAL REGIME AND WATER RESOURCES OF RIVERS OF THE ZERAFSHAN BASIN UNDER CLIMATE CHANGE

The work assessed the impact of climate change on the hydrological regime - long-term fluctuations, intra-annual distributions, maximum flow rates and, in general, on the water resources of the rivers of the Zeravshan basin. Calculations to assess changes in meteorological parameters were performed for two climatic periods. Some changes in the regime of air temperature and precipitation were revealed. Their influence on the hydrological regime of rivers is assessed. Particular attention is paid to the issues of quantitative assessment of water resources of the rivers of the studied basin.

Swedish L2 teacher cognitions of the initial assessment of students' L1 literacy resources

In this paper, we explore second language (L2) teachers’ cognitions regarding the initial assessment of adult learner literacy in their strongest language. Instruction can thus be adapted according to what is stipulated in the curriculum and syllabus. The literacy assessment is conducted in the student’s strongest language with assistance from an interpreter, translated decoding and reading comprehension tasks and concerns assessment of learners with little or no prior education. Questionnaires and interviews with L2 teachers reveal great variation based on four categories of teacher knowledge, namely, Subject matter knowledge, Knowledge of students, Pedagogical knowledge, and Knowledge of educational contexts. These four categories were partly intertwined with each other and both a resource and a deficit perspective emerged. The teachers’ cognitions regarding the concept of literacy, the value of initial L1 literacy assessment and students’ prior literacy and multilingual resources, as well as its potential for instruction planning were diverse. This may have significant implications for what emerges in initial assessments of a student's L1 literacy. In turn, this affects the validity of the assessment and, ultimately, the quality of education.

Research on planting planning of Glycyrrhiza uralensis in Naiman Banner based on MaxEnt model and remote sensing technology

Benefits of Glycyrrhiza uralensis include removing heat, detoxifying, and moistening the lungs, easing coughs, refueling the spleen, and balancing medications. In addition to providing theoretical guidance for the development of the G. uralensis industry and rural revitalization plan, it is anticipated that this paper will also provide basic data for the formulation of production layout of the G. uralensis industry at the county level, the control of cultivation industry direction, the establishment of high-quality G. uralensis cultivation technology system. The Maximum Entropy (MaxEnt) model was used to simulate the potential distribution of G. uralensis, a Chinese medicine resource, in Naiman Banner. By conducting a field inquiry and a broad assessment of the available Chinese medicine resources, the distribution information was acquired. The random forest technique was used to classify G. uralensis. The phenological cycle and development mode of vegetation, which exhibits diverse temporal traits and aids in identification, were elucidated through long-term series analysis. The random forest classification algorithm based on multiple features showed high accuracy in remote sensing (RS) recognition of G. uralensis. Comparative analysis of the MaxEnt and RS results showed that the planting area of G. uralensis was smaller than that of its potential distribution. The expansion to high-suitability areas planting should be prioritized. Based on the dual analysis of regional and remote sensing, it not only proved the great potential of using geographic information to predict the distribution of G. uralensis, but also verified the great potential of extracting the distribution of G. uralensis from GF-6 images. These results will guide the planting and development of G. uralensis in Naiman Banner and a scientific basis for the development of G. uralensis economy, conducive to optimizing the ecological environment and promoting rural revitalization programs.

Integrated geophysical and GIS approaches for groundwater potential assessment: a case study of Aladja, Delta State, Nigeria

ABSTRACT This study explores the groundwater potential in Aladja, Udu, Local Government Area of Delta State, Nigeria, using an integrated approach combining electrical resistivity techniques with Remote Sensing (RS) and Geographic Information System (GIS) methods. The primary aim is to delineate aquifers and comprehensively assess groundwater resources. Methods include Vertical Electrical Sounding (VES) to gather resistivity data, RS and GIS for analyzing geological and hydrological parameters such as lineament density, drainage density, slope, soil type, and land use. The resistivity values ranged from 147 to 460.50 Ωm, with aquifer thicknesses varying between 6.50 and 36.30 m. The RS and GIS analysis indicated high groundwater potential in regions characterized by significant lineament density and moderate slopes. The study highlights the complementarity of VES and RS/GIS in groundwater exploration, revealing substantial groundwater resources in the northwestern regions of the study area. This approach underscores the importance of integrating these methods for a more accurate assessment of groundwater potential. The novelty of this study lies in validating RS and GIS findings with VES data, ensuring reliable groundwater potential mapping and effective resource management. This integrated methodology offers a robust framework for sustainable groundwater resource assessment and management in similar geological settings.

A Novel Framework to Evaluate the Effect of Strategic Systems Thinking on Sustainable Supply Chain Risks, LARG Capabilities and Performance

Supply chain (SC) disruptions created due to sustainable, social, economic, environmental and technical risks are mitigated by lean, agile, resilient and green (LARG) capabilities across the SC node. This study aims at the assessment and alignment of SC risks and capabilities for a strategic fit of appropriate practices resulting in performance, efficiency and continuity of operations. The novelty of this research work is the investigation of the direct and mediating effects of strategic system thinking (SST) between SC risks, capabilities and performance. A survey comprising of 78 items was administered to 255 managers of Pakistan automotive SC industries. The exploratory factor analysis and confirmatory factor analysis were executed to identify the valid constructs along with their reliability and validity. The structural equation modeling (SEM) was used to test the conceptual model by establishing the second order constructs. SEM results indicated only technical risks having negative significant effect with performance. In terms of capabilities, the general, efficiency, integration as well as the redundant resources were found to have significant association with SC performance. The SST approach was found to be significantly associated with technical risks and capabilities such as general, recovery and redundancy. The hypothesis of SST as a mediating variable across all factors was not observed to be valid in this research. This study can help in the policy and decision-making as well as strategic assessment, planning, development, positioning and alignment of resources across the sustainable SC. The operations can be influenced positively through system integration and conservation of resources for a sustainable performance. The green, environmental and social risks had higher SC impact and need to be focused upon in Pakistan automotive SC for higher performance and sustainability.

Оценка обеспеченности человеческим капиталом аграрного сектора экономики

Abstract. The formation and use of human capital in the agricultural economy must meet modern economic requirements and the level of development of agricultural production. The assessment of the efficiency of the use of human resources and the quality of products plays a key role in adapting to changing market conditions. Therefore, it is important to constantly strengthen human resources to ensure a prompt response to market challenges. At the same time, agricultural production is currently undergoing changes in all key areas. This article analyzes the availability and efficiency of the use of agricultural enterprises' labor resources, based on statistical data for the Russian Federation. In this regard, the purpose of this scientific study is to analyze the availability of human capital in agriculture. The objectives of the study include carrying out a qualitative and quantitative assessment of labor resources. Methods. The methodological basis is based on the general scientific principles of a systematic approach. The analysis uses logical, factorial, comparative and strategic methods, as well as methods of qualitative research of the main trends in the presence and use of human capital in agriculture. Results. The analysis of the formation and use of human capital in agriculture in its quantitative and qualitative assessment in the Russian Federation is carried out: the dynamics of rural population density and the number of workers, the growth rate of wages of agricultural workers, the grouping of those employed in agriculture by level of education, gender and age is given. Scientific novelty. As a result of the research, new theoretical and practical conclusions were obtained, including: 1) identification and classification of socio-economic conditions that promote or, conversely, hinder the effective use and preservation of human capital in the agricultural sector; 2) comprehensive schemes for the formation of human capital in the agricultural sector are proposed, taking into account internal and external factors; 3) the need for the formation of a comfortable socio-economic environment in rural areas is justified; 4) confirmed the need to provide special support measures to attract highly qualified specialists to rural areas.