Abstract Regional impoverishment is an external manifestation of unbalanced human-land relationship in specific areas. The important role of the full utilization of land resources in alleviating the man-land contradiction has been gradually recognized. As one of the most prominent poverty-stricken countries in the world, China has been innovating the way of land use to alleviate poverty. Under the background of land system innovation, land consolidation is an instrument to alleviate poverty. This study first analyzed the mechanism and path behind land consolidation boosting poverty alleviation, then systematically reviewed the evolution of China’s land policies related to poverty alleviation since 1978, and finally explained the successful practice of land consolidation boosting poverty alleviation through a typical case study. Results show that land consolidation has multi-functional characteristics. Land consolidation has played an active role in increasing cultivated land area, promoting agricultural production scale, improving rural production conditions and living environment, alleviating ecological risk and supporting for rural development. It also helps to create employment opportunities, promote the capitalization of land resources, widen the way for farmers to increase their income, solve the predicament of lack of land, technology and funds faced by the development of poor areas and revitalize rural economy, thus contributing to rural development and poverty alleviation. Nevertheless, third-party assessment of the whole process of socio-economic and ecological impacts of land consolidation is still needed. Decision-making of land consolidation needs to take full account of different stakeholders’ interests and bottom-up participation is also necessary. These findings will provide beneficial reference for making-decision for sustainable land use and effective poverty alleviation in other developing countries.
Weiwei Wang, Elena Blanc-Betes, Madhu Khanna
et al.
Abstract Energy crops will be critical for scaling up production of Sustainable Aviation Fuel in the United States and reducing greenhouse gas emissions. Here we examine the economic incentives for the extent and type of land conversion needed to scale up fuel production from a mix of cellulosic feedstocks and quantify its greenhouse gas intensity. We show that even with the availability of marginal non-cropland, there will be incentives for converting cropland to produce energy crops as the price of sustainable aviation fuel increases. But contrary to expectations, we find that scaling up fuel production by converting more cropland and more non-cropland from existing uses to energy crops lowers its net greenhouse gas intensity, due to high soil carbon sequestration rate of energy crops, even after considering land use change emissions.The potential savings in emissions are larger than the foregone soil carbon accumulation benefits from keeping that land in current uses.
Abstract Understanding spatiotemporal changes in land use, land cover (LULC), and vegetation dynamics is crucial for sustainable environmental management and planning. This study investigated LULC and vegetation changes in the Gambela region of Ethiopia using Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data from 2004 to 2024. This study relied on MOD13A3 (NDVI, 1 km, monthly) to track vegetation changes from to 2004–2024, as well as Landsat image classification was used to LULC estimation. The IGBP was refined using a random forest with NDVI thresholding to identify shifts. The accuracy was 87% through Sentinel-2 and ground truth, and NDVI deviations were associated (0.80) with yields. Geospatial and statistical techniques were employed to detect and quantify transitions between land cover classes and fluctuations in greenness in the study area. Six LULC classes, namely forest, agricultural land, grassland, irrigated land, built‑up area, and water bodies, were mapped and analyzed. Between 2004 and 2024, forest cover declined by 2 693.9 km2 (from 74.2% to 65.3%), agricultural land expanded by 4 618.4 km2 (from 5.3% to 20.6%), and grasslands contracted by 2 397.8 km2 (from 19.5% to 11.5%). Irrigated areas more than tripled (0.4% to 1.2%), and built‑up extent grew nearly five‑fold (0.2% to 0.9%), whereas water bodies remained largely stable during this period. NDVI analysis revealed a 12% reduction in high-greenness areas, typically corresponding to NDVI values ≥ 0.6 (often 0.6–0.8), and a mean NDVI drop from 0.62 to 0.59 in non-forest zones, indicating declining vegetation health in converted landscapes. The study found significant LULC changes driven by agricultural expansion, settlement growth, and climate variability, with declining natural vegetation and increasing cultivated and built-up areas in the western and central regions. MODIS data are valuable for environmental monitoring, offering insights into land management and climate adaptation.
Diante da crescente estatística de empresas brasileiras decretando falência ou tentando uma recuperação judicial, é preciso que as empresas disponham de uma ferramenta com uma metodologia mais precisa para estampar a realidade da sua liquidez. Esse artigo, traz uma proposta de um novo indicador financeiro (IRF) como um novo parâmetro, desenvolvido para fornecer uma análise mais exata da solvência, especialmente para empresas com alta alavancagem. O IRF trabalha relacionando a relação entre empréstimos e patrimônio líquido (PL), excluindo estoques e ajustando a análise para a estrutura de capital da empresa, reagindo tempestivamente as variações econômicas da empresa, dando tempo hábil para tomar decisões assestadas e preventivas, e assim evitar possíveis falências empresariais. Com base em dados de 14 empresas brasileiras listadas na B3, entre elas sete em recuperação judicial, o IRF demonstrou uma eficácia superior em comparação aos indicadores tradicionais. Portanto, o IRF é recomendado como uma métrica preferencial para análise de liquidez, em ambientes econômicos desafiadores.
The main aim of the article is to present practical examples of HR practices with respect to the quality management system and its standards. A bibliometric analysis was conducted to obtain an overview of research trends in the field of HR management in the context of quality management. The article also presents the connections of HR practices with quality management systems (QMS) with an emphasis on the importance of a process approach in human resource management. The article presents selected human resource management processes such as recruitment, hiring and adaptation. Examples of documents related to human resource management processes are also provided. A standardized job description structure is presented as an output of the job analysis process. An example of a responsibility matrix is provided, defining employee responsibilities, in which their readiness to perform specific work activities, acquired through training, is also recorded.
Guillaume Hummel, David Pflieger, Alexandre Berr
et al.
Transfer RNAs (tRNAs) are universal adaptors of the genetic code, yet their evolutionary dynamics across photosynthetic eukaryotes remain underexplored. Here, we present the largest comparative re-analysis integrating the PlantRNA database with published data to explore tRNA gene evolution. We find that tRNA gene repertoires have been deeply shaped by ecological transitions, genome architecture, and translational demands. Terrestrialization marks a major shift in tRNA evolution, characterized by the loss of selenoproteins and their dedicated selenocysteine tRNAs in land plants compared to algae. Patterns of intron prevalence, position, and structure diverged among lineages, with extensive intron loss occurring around the origin of land plants. Organellar genomes exhibit divergent trajectories: mitochondrial tRNA sets are highly labile due to recurrent gene losses, imports, and horizontal transfers, whereas plastid repertoires are comparatively stable with lineage-specific exceptions. In parallel, angiosperm nuclear tRNA genes exhibit reinforced cis-regulatory elements, consistent with increased and developmentally complex translational demands, and their copy number correlates tightly with codon usage and amino acid composition. Finally, conserved yet family-biased clustering of nuclear tRNA genes reveals contrasting organizational principles in plants versus metazoans. Together, these findings establish tRNA gene evolution as a major determinant of translational capacity and a key driver of photosynthetic diversification.
Air-land bimodal vehicles provide a promising solution for navigating complex environments by combining the flexibility of aerial locomotion with the energy efficiency of ground mobility. However, planning dynamically feasible, smooth, collision-free, and energy-efficient trajectories remains challenging due to two key factors: 1) unknown dynamic disturbances in both aerial and terrestrial domains, and 2) the inherent complexity of managing bimodal dynamics with distinct constraint characteristics. This paper proposes a disturbance-aware motion-planning framework that addresses this challenge through real-time disturbance estimation and adaptive trajectory generation. The framework comprises two key components: 1) a disturbance-adaptive safety boundary adjustment mechanism that dynamically determines the feasible region of dynamic constraints for both air and land modes based on estimated disturbances via a disturbance observer, and 2) a constraint-adaptive bimodal motion planner that integrates disturbance-aware path searching to guide trajectories toward regions with reduced disturbances and B-spline-based trajectory optimization to refine trajectories within the established feasible constraint boundaries. Experimental validation on a self-developed air-land bimodal vehicle demonstrates substantial performance improvements across three representative disturbance scenarios, achieving an average 33.9% reduction in trajectory tracking error while still maintaining superior time-energy trade-offs compared to existing methods.
Autonomous landing is essential for drones deployed in emergency deliveries, post-disaster response, and other large-scale missions. By enabling self-docking on charging platforms, it facilitates continuous operation and significantly extends mission endurance. However, traditional approaches often fall short in dynamic, unstructured environments due to limited semantic awareness and reliance on fixed, context-insensitive safety margins. To address these limitations, we propose a hybrid framework that integrates large language model (LLMs) with model predictive control (MPC). Our approach begins with a vision-language encoder (VLE) (e.g., BLIP), which transforms real-time images into concise textual scene descriptions. These descriptions are processed by a lightweight LLM (e.g., Qwen 2.5 1.5B or LLaMA 3.2 1B) equipped with retrieval-augmented generation (RAG) to classify scene elements and infer context-aware safety buffers, such as 3 meters for pedestrians and 5 meters for vehicles. The resulting semantic flags and unsafe regions are then fed into an MPC module, enabling real-time trajectory replanning that avoids collisions while maintaining high landing precision. We validate our framework in the ROS-Gazebo simulator, where it consistently outperforms conventional vision-based MPC baselines. Our results show a significant reduction in near-miss incidents with dynamic obstacles, while preserving accurate landings in cluttered environments.
This study is aimed at assessing agricultural and environmental performance and analyzing whether observable productivity changes stem from technologically induced or environmentally induced components. Based on individual farm household data from Hubei Province covering the period 2004 to 2010, we decompose total factor productivity (TFP) into technical efficiency change (TEC), technical change (TC), scale effect (SE), and the environmentally related allocative effect (AE) as a means of evaluating environmental performance. The empirical results indicate that the average TFP decrease rate is 2.8%, which reflects the comprehensive outcome of all relevant components. Regarding direct pollution-related inputs (fertilizer and land), improving nitrogen (N) fertilizer application efficiency and land use efficiency can contribute not only to less cropland expansion and greater productivity growth but also to N loss reduction and N pollution abatement in the short and long term. Concerning indirect pollution-related inputs (labor, intermediate input, etc.), although increases in quasi-fixed inputs (labor and intermediate input) can lead to both N and productivity growth, the magnitude of the positive effects of quasi-fixed inputs on productivity cannot offset the negative effect of fertilizer on productivity; thus, more scientific and economical fertilizer application is the key to improving agricultural productivity and benefiting the environment and the ecosystem.
Jérémy Lebreton, Roland Brochard, Nicolas Ollagnier
et al.
Autonomous precision navigation to land onto the Moon relies on vision sensors. Computer vision algorithms are designed, trained and tested using synthetic simulations. High quality terrain models have been produced by Moon orbiters developed by several nations, with resolutions ranging from tens or hundreds of meters globally down to few meters locally. The SurRender software is a powerful simulator able to exploit the full potential of these datasets in raytracing. New interfaces include tools to fuse multi-resolution DEMs and procedural texture generation. A global model of the Moon at 20m resolution was integrated representing several terabytes of data which SurRender can render continuously and in real-time. This simulator will be a precious asset for the development of future missions.
Umul Hidayati, Sumarni Sumarni, Suprapto Suprapto
et al.
The purpose of this study was to investigate how public sector workers in Indonesia use e-learning systems and how they can benefit from them. The researchers analyzed five variables that contribute to the effectiveness of e-learning: system reliability, information sharing, service quality, user satisfaction, and net benefit. Structural Equation Model analysis was used to analyze the data collected from 203 respondents who were public sector employees in Indonesia. The findings of this study revealed that information sharing, and service quality significantly impact user satisfaction, which in turn has a significant effect on net benefits. Additionally, system reliability was found to significantly impact user satisfaction. This theoretical implication suggests that there is a direct relationship between the level of information sharing and service quality provided by a public sector organization and the level of user satisfaction experienced by its usage of e-learning. The practical implication of the finding is that public sector organizations must prioritize the reliability of their e-learning systems. This includes investing in regular maintenance and updates, ensuring proper testing and quality control procedures, and addressing any issues or downtime quickly and effectively.
Social Sciences, Management. Industrial management
Cris Kuntadi, Winda Widyanty, R. Nurhidajat
et al.
AbstractThis study aims to analyze the influence of transformational leadership on the employee performance of National Transportation Safety Committee (NTSC) with the mediating role of work engagement and work motivation. The study employed a census approach utilizing structural equation modeling (SEM) to analyze the data collected from all employees of the NTSC in Indonesia. Primary data were gathered through a comprehensive questionnaire, which was administered to the entire population of 107 NTSC employees, ensuring complete coverage and representation. The results of this study indicate that transformational leadership has a positive and significant effect on work engagement, work motivation, and employee performance. The results show that work engagement and work motivation have a positive and significant effect on employee performance. While the mediation test results show that work engagement and work motivation have an indirect effect on employee performance. The current study provides fresh insights and validates extant knowledge on transformational leadership, work engagement, work motivation and employee performance within the NTSC. This study suggests NTSC management to communicate the company’s vision and mission to employees with openness and realize improvements in operational standards so that the performance created in the organization provides value that can be understood appropriately. In addition, management also needs to create policies that are in line with the NTSC vision and mission.
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).