bluuebunny/crossref_metadata_2025 huggingface dataset:
Construction and Application of Dynamic Threshold Model for Agricultural Drought Grades Based on Near-Infrared and Short-Wave Infrared Bands for Spring Maize
Authors: Wu Xia , Wang Peijuan , Gong Yanduo , Zhang Yuanda , Wang Qi , Li Yang , Guo Jianping , Han Shuxin
Published: September 2024

Maize (Zea mays L.) is one of the most important grain crops in the world. Drought caused by climate change in recent years may greatly threaten water supply and crop production, even if the drought only lasts for a few days or weeks. Therefore, effective daily drought monitoring for maize is crucial for ensuring food security. A pivotal challenge in current related research may be the selection of data collection and the methodologies in the construction of these indices. Therefore, orthorectified reflectance in the short-wave infrared (SWIR) band, which is highly sensitive to variations in vegetation water content, was daily obtained from the MODIS MCD43A4 product. Normalized Difference Water Index (NDWI) calculated using the NIR and SWIR bands and days after planting (DAP) were normalized to obtain the Vegetation Water Index (VWI) and normalized days after planting (NDAP), respectively. The daily dynamic threshold model for different agricultural drought grades was constructed based on the VWI and NDAP with double-logistic fitting functions during the maize growing season, and its specific threshold was determined with historical drought records. Verification results indicated that the VWI had a good effect on the daily agricultural drought monitoring of spring maize in the “Golden Maize Belt” in northeast China. Drought grades produced by the VWI were completely consistent with historical records for 84.6% of the validation records, and 96.2% of the validation records differed by only one grade level or less. The VWI can not only daily identify the occurrence and development process of drought, but also well reflect the impact of drought on the yield of maize. Moreover, the VWI could be used to monitor the spatial evolution of drought processes at both regional and precise pixel scales. These results contribute to providing theoretical guidance for the daily dynamic monitoring and evaluation of spring maize drought in the “Golden Maize Belt” of China.
Enhanced Tailings Dam Beach Line Indicator Observation and Stability Numerical Analysis: An Approach Integrating UAV Photogrammetry and CNNs
Authors: Wang Kun , Zhang Zheng , Yang Xiuzhi , Wang Di , Zhu Liyi , Yuan Shuai
Published: September 2024

Tailings ponds are recognized as significant sources of potential man-made debris flow and major environmental disasters. Recent frequent tailings dam failures and growing trends in fine tailings outputs underscore the critical need for innovative monitoring and safety management techniques. Here, we propose an approach that integrates UAV photogrammetry with convolutional neural networks (CNNs) to extract beach line indicators (BLIs) and conduct enhanced dam safety evaluations. The significance of real 3D geometry construction in numerical analysis is investigated. The results demonstrate that the optimized You Only Look At CoefficienTs (YOLACT) model outperforms in recognizing the beach boundary line, achieving a mean Intersection over Union (mIoU) of 72.63% and a mean Pixel Accuracy (mPA) of 76.2%. This approach shows promise for future integration with autonomously charging UAVs, enabling comprehensive coverage and automated monitoring of BLIs. Additionally, the anti-slide and seepage stability evaluations are impacted by the geometry shape and water condition configuration. The proposed approach provides more conservative seepage calculations, suggesting that simplified 2D modeling may underestimate tailings dam stability, potentially affecting dam designs and regulatory decisions. Multiple numerical methods are suggested for cross-validation. This approach is crucial for balancing safety regulations with economic feasibility, helping to prevent excessive and unsustainable burdens on enterprises and advancing towards the goal of zero harm to people and the environment in tailings management.
Characterization of Root Hair Curling and Nodule Development in Soybean–Rhizobia Symbiosis
Authors: Lu Wei , Wang Xiaochan , Jia Weidong
Published: September 2024

Soybean plants form symbiotic nitrogen-fixing nodules with specific rhizobia bacteria. The root hair is the initial infection site for the symbiotic process before the nodules. Since roots and nodules grow in soil and are hard to perceive, little knowledge is available on the process of soybean root hair deformation and nodule development over time. In this study, adaptive microrhizotrons were used to observe root hairs and to investigate detailed root hair deformation and nodule formation subjected to different rhizobia densities. The result showed that the root hair curling angle increased with the increase of rhizobia density. The largest curling angle reached 268° on the 8th day after inoculation. Root hairs were not always straight, even in the uninfected group with a relatively small angle (<45°). The nodule is an organ developed after root hair curling. It was inoculated from curling root hairs and swelled in the root axis on the 15th day after inoculation, with the color changing from light (15th day) to a little dark brown (35th day). There was an error between observing the diameter and the real diameter; thus, a diameter over 1 mm was converted to the real diameter according to the relationship between the perceived diameter and the real diameter. The diameter of the nodule reached 5 mm on the 45th day. Nodule number and curling number were strongly related to rhizobia density with a correlation coefficient of determination of 0.92 and 0.93, respectively. Thus, root hair curling development could be quantified, and nodule number could be estimated through derived formulation.
Releaf: An Efficient Method for Real-Time Occlusion Handling by Game Theory
Authors: Osooli Hamid , Joshi Nakul , Khurana Pranav , Nikoofard Amirhossein , Shirmohammadi Zahra , Azadeh Reza
Published: September 2024

Receiving uninterrupted videos from a scene with multiple cameras is a challenging task. One of the issues that significantly affects this task is called occlusion. In this paper, we propose an algorithm for occlusion handling in multi-camera systems. The proposed algorithm, which is called Real-time leader finder (Releaf), leverages mechanism design to assign leader and follower roles to each of the cameras in a multi-camera setup. We assign leader and follower roles to the cameras and lead the motion by the camera with the least occluded view using the Stackelberg equilibrium. The proposed approach is evaluated on our previously open-sourced tendon-driven 3D-printed robotic eye that tracks the face of a human subject. Experimental results demonstrate the superiority of the proposed algorithm over the Q-leaning and Deep Q Networks (DQN) baselines, achieving an improvement of 20% and 18% for horizontal errors and an enhancement of 81% for vertical errors, as measured by the root mean squared error metric. Furthermore, Releaf has the superiority of real-time performance, which removes the need for training and makes it a promising approach for occlusion handling in multi-camera systems.
Research on Integrated Control Strategy for Wind Turbine Blade Life
Authors: An Bairen , Liu Jun , Zhang Zeqiu
Published: September 2024

Wind turbine blades bear the maximum cyclic load and varying self-weights in turbulent wind environments, which accelerate the propagation of cracks that ultimately progress from minor faults, resulting in blade failure and significant maintenance and shutdown costs. To address this issue, this paper proposes an adaptive control strategy for the blade’s useful life. The control system is divided into the inner control loop and the outer control loop. The outer loop is based on the Paris crack propagation model combined with a particle filtering algorithm and calculates the degradation of the blade life under the crack threshold conditions provided by the operation and maintenance strategy to determine the parameter settings of the inner-loop load-shedding controller. The control strategy we propose can balance the load-shedding capability of the controller with the fatigue load of the pitch actuator while considering the predefined remaining useful blade life in the operation and maintenance strategy, avoiding unplanned downtime and reducing maintenance costs.
Comparative Analysis of Ventilation Systems for Aging Salami
Authors: Giametta Ferruccio , Catalano Filippo , La Fianza Giovanna , Bianchi Biagio
Published: September 2024

The aim of this study was to evaluate the influence of different ventilation systems in two aging cells. One cell featured transverse airflow starting from the top, while the other had a dual-flow system with vertical air motion from top to bottom and vice versa. In addition to monitoring weight loss during aging, chemical and physical analyses were conducted on various salamis to assess the influence of ventilation both between the two aging cells and among different positions of the salamis within the same cell. It was found that the dual-evaporator (DEV) cell behaved better than transverse flow (TFL) cell.
Enhanced Production of Therapeutic Metabolites in Cork-Oak Somatic Embryos under Abiotic Stress Conditions
Authors: López Beatriz Pintos , Manzanera José Antonio , Pérez-Urria Elena , Jiménez Carlos , Montoro Alba , Gomez-Garay Arancha
Published: September 2024

This study investigates the enhanced production of key therapeutic metabolites (ellagic acid, serotonin, and chlorogenic acid) in response to abiotic stress in in vitro cultures of Quercus suber somatic embryos. Findings indicate significant increases in metabolite levels under various stress conditions, highlighting the potential for commercial-scale production of these compounds, known for their antioxidant, anticancer, and anti-COVID-19 properties. Under osmotic/saline stress, ellagic acid production significantly increased, representing an 80% increase compared to control conditions. In embryos exposed to different stressors, serotonin accumulation showed a six-fold increase under osmotic/saline stress. Although the elicitors used did not increase chlorogenic acid levels, exploring alternative stress types may enhance its production. This research paves the way for sustainable, large-scale production of health-beneficial metabolites, addressing global health challenges and promoting resource sustainability.
Understanding Food Insecurity and Participation in Food Assistance Programs among Hispanic/Latino Residents of Hialeah, Florida, before and during the COVID-19 Pandemic
Authors: Treloar Destiny , Taylor Dorceta E. , Bell Ashley
Published: September 2024

The 63.6 million Hispanic individuals living in the United States constitute the largest ethnic or racial minority group in the country. Hispanic/Latino households report a high prevalence of food insecurity, and often, food-insecure individuals cope by turning to emergency and federal food assistance programs for immediate or long-term assistance. This paper focuses on Hialeah, Florida, a predominantly Hispanic/Latino city in Miami-Dade County. It examines which demographic factors influence participation in food assistance programs and the occurrences of periods of disrupted food access. This study examines two questions: (1) What factors are associated with participation in food assistance programs? (2) To what extent did study participants use food assistance programs before and during the COVID-19 pandemic? We conducted a survey and collected 684 responses from April to August 2022. We gathered data on participants’ identities, household attributes, and their usage of federal and emergency food assistance programs. We used Pearson’s chi-square tests to identify significant associations between food assistance usage, food access, and respondents’ demographic characteristics. We also used binary logistic regression models to assess probabilities. The findings of this research are significant, indicating that the COVID-19 pandemic exacerbated food access challenges in Hispanic/Latino households in 2022. The data also revealed that low-income households, respondents below the age of 40, individuals born in the United States, those with low educational attainment, and those living in multifamily households had the highest likelihood of using food assistance programs. Single- and non-single-parent households, employment status, languages spoken at home, and number of children in the household were also statistically significant factors in predicting food assistance usage. This research provides valuable insights into how individuals in a city responded to the pandemic by utilizing food assistance programs.
Herbaceous Vegetation in Slope Stabilization: A Comparative Review of Mechanisms, Advantages, and Practical Applications
Authors: Gong Chuangang , Ni Dazhi , Liu Yuna , Li Yalei , Huang Qingmei , Tian Yu , Zhang Hao
Published: September 2024

Shallow slope instability poses a significant ecological threat, often leading to severe environmental degradation. While vegetation, particularly woody plants, is commonly employed in slope stabilization, herbaceous vegetation offers distinct and underexplored advantages. This paper reviews the role of herbaceous plants in enhancing slope stability, analyzing their mechanical and ecological mechanisms. Through an extensive review of the literature, this review challenges the prevailing view that woody vegetation is superior for slope stabilization, finding that herbaceous plants can be equally or more effective under certain conditions. The key findings include the identification of specific root parameters and species that contribute to soil reinforcement and erosion control. The review highlights the need for further research on optimizing plant species selection and management practices to maximize the slope stabilization effects. These insights have practical implications for ecological slope engineering, offering guidance on integrating herbaceous vegetation into sustainable land management strategies.
Transforming Urban Sanitation: Enhancing Sustainability through Machine Learning-Driven Waste Processing
Authors: Gude Dhanvanth Kumar , Bandari Harshavardan , Challa Anjani Kumar Reddy , Tasneem Sabiha , Tasneem Zarin , Bhattacharjee Shyama Barna , Lalit Mohit , Flores Miguel Angel López , Goyal Nitin
Published: September 2024

The enormous increase in the volume of waste caused by the population boom in cities is placing a considerable burden on waste processing in cities. The inefficiency and high costs of conventional approaches exacerbate the risks to the environment and human health. This article proposes a thorough approach that combines deep learning models, IoT technologies, and easily accessible resources to overcome these challenges. Our main goal is to advance a framework for intelligent waste processing that utilizes Internet of Things sensors and deep learning algorithms. The proposed framework is based on Raspberry Pi 4 with a camera module and TensorFlow Lite version 2.13. and enables the classification and categorization of trash in real time. When trash objects are identified, a servo motor mounted on a plastic plate ensures that the trash is sorted into appropriate compartments based on the model’s classification. This strategy aims to reduce overall health risks in urban areas by improving waste sorting techniques, monitoring the condition of garbage cans, and promoting sanitation through efficient waste separation. By streamlining waste handling processes and enabling the creation of recyclable materials, this framework contributes to a more sustainable waste management system.
Improving Air Quality Data Reliability through Bi-Directional Univariate Imputation with the Random Forest Algorithm
Authors: Arnaut Filip , Đurđević Vladimir , Kolarski Aleksandra , Srećković Vladimir A. , Jevremović Sreten
Published: September 2024

Forecasting the future levels of air pollution provides valuable information that holds importance for the general public, vulnerable populations, and policymakers. High-quality data are essential for precise and reliable forecasts and investigations of air pollution. Missing observations arise when the sensors utilized for assessing air quality parameters experience malfunctions, which result in erroneous measurements or gaps in the dataset and hinder the data quality. This research paper presents a novel approach for imputing missing values in air quality data in a univariate approach. The algorithm employs the random forest (RF) algorithm to impute missing observations in a bi-directional (forward and reverse in time) manner for air quality (particulate matter less than 2.5 μm (PM2.5)) data from the Republic of Serbia. The algorithm was evaluated against simple methods, such as the mean and median imputation methods, for missing observations over durations of 24, 48, and 72 h. The results indicate that our algorithm yielded comparable error rates to the median imputation method for all periods when imputing the PM2.5 data. Ultimately, the algorithm’s higher computational complexity proved itself as not justified considering the minimal error decrease it achieved compared with the simpler methods. However, for future improvement, additional research is needed, such as utilizing low-code machine learning libraries and time-series forecasting techniques.
Degradation of Malachite Green Dye by Solar Irradiation Assisted by TiO2 Biogenic Nanoparticles Using Vaccinium corymbosum Extract
Authors: Balderas-León Iván , Silva-Jara Jorge Manuel , López-Álvarez Miguel Ángel , Ortega-Gudiño Pedro , Barrera-Rodríguez Arturo , Neri-Cortés Cristina
Published: September 2024

The green synthesis of metal oxide nanoparticles (NPs) offers an alternative to chemical procedures, which can be harmful to human health due to exposure to hazardous substances and harsh synthesis conditions. The following work synthesized titanium dioxide nanoparticles (TiO2 NPs) using a green synthesis method. As a precursor, food-grade TiO2 was used with blueberry extract. This approach makes the process safer, cheaper, and simpler, requiring minimal effort to achieve effective TiO2 NP synthesis. The TiO2 NP characterization was performed by solid-state techniques, such as Ultraviolet-visible (UV-Vis) spectroscopy, X-ray diffraction (XRD), Fourier transform infrared (FTIR) spectroscopy, X-ray photoelectron spectroscopy (XPS), and transmission electron microscopy (TEM). According to the XRD diffractograms, TiO2 NPs were obtained in the anatase phase with incidence peaks of 25.28 (101). TEM confirmed their pseudo-spherical shape with an average size of 170 nm. The 3.2 eV bandgap of TiO2 NPs enables UV absorption, making them ideal for efficient photocatalytic degradation under sunlight. On the other hand, the photocatalytic activity of TiO2 NPs was examined using malachite green (MG) dye as a pollutant model under direct sunlight. After 30 min, a degradation of 94% was achieved. The kinetic analysis identified parabolic diffusion and modified-Freundlich kinetics as primary mechanisms, emphasizing diffusion and adsorption in electron transfer. The main reactive oxygen species (ROS) involved in the photodegradation of MG dye were h+ and OH•.
Unveiling the Complex Relationship between Open Circular Innovation and Business Circularity: The Role of Circular-Based Dynamic Capabilities and Circular Ambidexterity
Authors: Hadi Noor Ul
Published: September 2024

Following calls for more research on the circular economy and open innovation, this study sheds light on the scant mechanisms influencing the relationship between open circular innovation and business circularity. This study theorizes that achieving business circularity requires a radical shift, and those circular exploitative activities may not be an effective strategy for this transition. Therefore, circular-based dynamic capabilities and circular ambidexterity are proposed as moderated-mediation mechanisms that explain the relationship between open circular innovation and business circularity. This study employs a quantitative approach to examine the hypothesized relationships. Data were purposively collected from owners and managers of marble manufacturing units due to the significant amount of waste generated by these units. A total of 292 valid responses were analyzed using SmartPLS version 4.1.0.5. The results revealed that the combined effect of open circular innovation and circular-based dynamic capabilities stimulates circular ambidexterity, which in turn leads to business circularity. This signifies that the complementary role of circular ambidexterity and circular-based dynamic capabilities foster the implementation of business circularity. This study empirically confirmed the application of three frameworks into a single new structure called the circular resource-based view, which has been neglected in previous literature. This study concluded that an organization’s circular resources, capabilities, and competencies, when combined harmoniously with circular strategies, could lead to business circularity.
The Evolution of Government–Enterprise Strategies of “Expressway + Logistics Distribution”
Authors: Jiang Peiling , Shui Wenbing , He Mingwei
Published: September 2024

Currently, China’s expressway revenue and expenditure imbalance problem is serious. The development of an “Expressway Derivative Economy” (EDE) helps address expressway deficits, ensuring the expressway’s sustainable operation. The “Expressway + Logistics Distribution” (ELD) mode is a crucial form of the EDE and enhances expressway traffic flow and asset income. However, the cooperation mechanism among stakeholders remains unclear, hindering the widespread promotion of this mode. This study designs two ELD modes and elaborates on their respective advantages. Therefore, a three-party evolutionary game model involving the government, expressway groups, and logistics enterprises is established. Government “land-use-right” grant and tax incentive policies are formulated to explore the cooperation mechanism among stakeholders. The results indicate that both government “land-use-right” grant and tax incentive policies positively influence the positive evolution of the system. However, when the government “land-use-right” grants reach a high level, the willingness of logistics enterprises to choose entry will decrease due to resource crowding. Comparatively, a higher-level “land-use-right” grant policy significantly enhances the role of government tax incentive policy in promoting the positive development of the system. During tight government funding, it is a feasible policy to prioritize expressway groups by providing more tax incentives. The findings provide theoretical guidance for promoting the ELD mode.
Organ Donation through the Eyes of Jordanian Medical Students
Authors: Yamin Saif , Alshahwan Hamzeh Feras , AlSamhori Jehad Feras , Alfreahat Osama , Alhalbouni Abdallah , Alwarawrah Zaid
Published: September 2024

Background: Organ donation is a critical component in the field of transplantation medicine, offering lifesaving opportunities for patients with end-stage organ failure. This study investigated the knowledge, attitude, and practice (KAP) survey regarding organ donation among medical students in Jordan. Methods: A cross-sectional survey was conducted among medical students across six Jordanian universities. Using a convenience sampling method, participants were invited via email, social media, and professional networks to complete a structured online questionnaire. The survey captured data on demographics, knowledge about organ donation processes, attitudes toward organ donation, and self-reported practices. Statistical analyses explored associations between students’ KAP and their demographic characteristics. Results: A total of 539 medical students participated in the study. Findings revealed moderate knowledge and generally positive attitudes toward organ donation, with significant variability influenced by demographic factors. Students from various universities demonstrated different levels of knowledge and attitudes. Notably, religious and cultural beliefs significantly affected students’ attitudes toward organ donation. Conclusions: The study highlighted a gap between the positive attitudes and the actual commitment to organ donation among the participants, revealing a need for targeted educational interventions to address misconceptions and enhance the willingness to donate organs. Promoting organ donation education within medical schools could foster a more supportive environment for organ donation, ultimately contributing to increased donor rates and improved transplantation outcomes in Jordan.
Investigations on the Potential Role of Free-Ranging Wildlife as a Reservoir of SARS-CoV-2 in Switzerland
Authors: Kuhn Juliette , Marti Iris , Ryser-Degiorgis Marie-Pierre , Wernike Kerstin , Jones Sarah , Tyson Grace , Delalay Gary , Scherrer Patrick , Borel Stéphanie , Hosie Margaret J. , Kipar Anja , Kuhlmeier Evelyn , Chan Tatjana , Hofmann-Lehmann Regina , Meli Marina L.
Published: September 2024

Amid the SARS-CoV-2 pandemic, concerns surfaced regarding the spread of the virus to wildlife. Switzerland lacked data concerning the exposure of free-ranging animals to SARS-CoV-2 during this period. This study aimed to investigate the potential exposure of Swiss free-ranging wildlife to SARS-CoV-2. From 2020 to 2023, opportunistically collected samples from 712 shot or found dead wild mustelids (64 European stone and pine martens, 13 European badgers, 10 European polecats), canids (449 red foxes, 41 gray wolves, one golden jackal) and felids (56 Eurasian lynx, 18 European wildcats), as well as from 45 captured animals (39 Eurasian lynx, 6 European wildcats) were tested. A multi-step serological approach detecting antibodies to the spike protein receptor binding domain (RBD) and N-terminal S1 subunit followed by surrogate virus neutralization (sVNT) and pseudotype-based virus neutralization assays against different SARS-CoV-2 variants was performed. Additionally, viral RNA loads were quantified in lung tissues and in oronasal, oropharyngeal, and rectal swabs by reverse transcription polymerase chain reactions (RT-qPCRs). Serologically, SARS-CoV-2 exposure was confirmed in 14 free-ranging Swiss red foxes (prevalence 3.1%, 95% CI: 1.9–5.2%), two Eurasian lynx (2.2%, 95% CI: 0.6–7.7%), and one European wildcat (4.2%, 95% CI: 0.2–20.2%). Two positive foxes exhibited neutralization activity against the BA.2 and BA.1 Omicron variants. No active infection (viral RNA) was detected in any animal tested. This is the first report of SARS-CoV-2 antibodies in free-ranging red foxes, Eurasian lynx, and European wildcats worldwide. It confirms the spread of SARS-CoV-2 to free-ranging wildlife in Switzerland but does not provide evidence of reservoir formation. Our results underscore the susceptibility of wildlife populations to SARS-CoV-2 and the importance of understanding diseases in a One Health Concept.
Copper and Temperature Interaction Induced Gill and Liver Lesions and Behaviour Alterations in Mozambique Tilapia (Oreochromis mossambicus)
Authors: Ribeiro Ondina , Pinto Mónica Quelhas , Tavares Diana , Ferreira-Cardoso Jorge Ventura , Correia Alberto Teodorico , Carrola João Soares
Published: September 2024

Climate changes linked to extreme events pose a threat to freshwater biodiversity, impacting organs, behaviour, and reproduction. Moreover, these changes can be amplified by pollution. Copper sulphate (CuSO4) is used in agriculture and aquaculture, so the copper can reach streams, rivers, and lakes impacting fish. This study evaluated the combined effects of temperature and copper on gills and liver histology biomarkers and in the behaviour of Mozambique tilapia over 28 days. Tilapias were exposed to different water temperatures (25 °C and 32 °C) and CuSO4 concentrations (1.1 and 3.6 mg/L). Fish from the control group were exposed to water without copper sulphate and at 25 °C (within their optimum range). Histopathological analysis revealed significant tissue lesions, namely aneurysms and bending of gill lamellae, and hyalinization and vacuolization in the liver at the higher temperature and CuSO4 level. Moreover, behavioural observations revealed increased stress changes under the same conditions. These findings highlight the effects of fast climate change, and rising temperatures on copper toxicity, underlining the necessity for strict monitoring and regulation of copper use due to future climate change scenarios to protect aquatic ecosystems, ichthyofauna population and trophic web dynamics. This data also alerts for similar problems with other toxic metals or chemicals, at short term, in streams and rivers, under rapid climate changes and more frequent extreme events.
Modeling and Application of Drought Monitoring with Adaptive Spatial Heterogeneity Using Eco–Geographic Zoning: A Case Study of Drought Monitoring in Yunnan Province, China
Authors: Xu Quanli , Li Shan , Yi Junhua , Wang Xiao
Published: September 2024

Drought, characterized by frequent occurrences, an extended duration, and a wide range of destruction, has become one of the natural disasters posing a significant threat to both socioeconomic progress and agricultural livelihoods. Large-scale geographical environments often exhibit obvious spatial heterogeneity, leading to significant spatial differences in drought’s development and outcomes. However, traditional drought monitoring models have not taken into account the impact of regional spatial heterogeneity on drought, resulting in evaluation results that do not match the actual situation. In response to the above-mentioned issues, this study proposes the establishment of ecological–geographic zoning to adapt to the spatially stratified heterogeneous characteristics of large-scale drought monitoring. First, based on the principles of ecological and geographical zoning, an appropriate index system was selected to carry out ecological and geographical zoning for Yunnan Province. Second, based on the zoning results and using data from NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS) and the Tropical Rainfall Measuring Mission (TRMM) 3B43, the vegetation condition index (VCI), the temperature condition index (TCI), the precipitation condition index (TRCI), and three topographic factors including the digital elevation model (DEM), slope (SLOPE), and aspect (ASPECT) were selected as model parameters. Multiple linear regression models were then used to establish integrated drought monitoring frameworks at different eco–geographical zoning scales. Finally, the standardized precipitation evapotranspiration index (SPEI) was used to evaluate the monitoring effects of the model, and the spatiotemporal variation patterns and characteristics of winter and spring droughts in Yunnan Province from 2008–2019 were further analyzed. The results show that (1) compared to the traditional non-zonal models, the drought monitoring model constructed based on ecological–geographic zoning has a higher correlation and greater accuracy with the SPEI and (2) Yunnan Province experiences periodic and seasonal drought patterns, with spring being the peak period of drought occurrence and moderate drought and light drought being the main types of drought in Yunnan Province. Therefore, we believe that ecological–geographic zoning can better adapt to geographical spatial heterogeneity characteristics, and the zonal drought monitoring model constructed can more effectively identify the actual occurrence of drought in large regions. This research finding can provide reference for the formulation of drought response policies in large-scale regions.
Selection of AI Architecture for Autonomous Vehicles Using Complex Intuitionistic Fuzzy Rough Decision Making
Authors: Mahmood Tahir , Idrees Ahmad , Hayat Khizar , Ashiq Muhammad , Rehman Ubaid ur
Published: September 2024

The advancement of artificial intelligence (AI) has become a crucial element in autonomous cars. A well-designed AI architecture will be necessary to attain the full potential of autonomous vehicles and will significantly accelerate the development and deployment of autonomous cars in the transportation sector. Promising autonomous cars for innovating modern transportation systems are anticipated to address many long-standing transporting challenges related to congestion, safety, parking, and energy conservation. Choosing the optimal AI architecture for autonomous vehicles is a multi-attribute decision-making (MADM) dilemma, as it requires making a complicated decision while considering a number of attributes, and these attributes can have two-dimensional uncertainty as well as indiscernibility. Thus, in this framework, we developed a novel mathematical framework “complex intuitionistic fuzzy rough set” for tackling both two-dimensional uncertainties and indiscernibility. We also developed the elementary operations of the deduced complex intuitionistic fuzzy rough set. Moreover, we developed complex intuitionistic fuzzy rough (weighted averaging, ordered weighted averaging, weighted geometric, and ordered weighted geometric) aggregation operators. Afterward, we developed a method of MADM by employing the devised operators and investigated the case study “Selection of optimal AI architecture for autonomous vehicles” to reveal the practicability of the devised method of MADM. Finally, to reveal the dominance and supremacy of our proposed work, a benchmark dilemma was used for comparison with various prevailing techniques.
Trends and prospects for the development of modeling in accounting
Authors:   Federal State Budgetary Educational Institution of Higher Education «Udmurt State Agrarian University», Izhevsk, Russia, Knyazeva O. P. , Akmarov P. B. ,   Federal State Budgetary Educational Institution of Higher Education «Udmurt State Agrarian University», Izhevsk, Russia, Alborov G. R. ,   Federal State Budgetary Educational Institution of Higher Education «Udmurt State Agrarian University», Izhevsk, Russia
Published: September 2024

The historical role of modeling in the development of accounting and the modern interpretation of the use of models for solving management problems in accounting automation are shown. The dynamics of the spread of different models of integrated accounting automation are presented, and trends in the complexity of models with the development of information technology are highlighted. The features of the development of modeling of management tasks in the digital transformation of agriculture are shown. The need to develop accounting modeling at the macroeconomic level is noted.
PYALLFFS: An Open-Source Library for All Filter Feature Selection Methods
Authors: Yousefi Tohid , Varlıklar Özlem
Published: September 2024

Feature selection is a significant data mining and machine learning technique that enhances model performance by identifying important features within a dataset, reducing the risk of overfitting while aiding the model in making faster and more accurate predictions. Pyallffs is a Python library developed to optimize the feature selection process, offering rich content and low dependency requirements. With 19 different filtering methods, pyallffs assists in analyzing dataset features to determine the most relevant ones. Users can apply custom filtering methods to their datasets using pyallffs, thereby achieving faster and more effective results in data analytics and machine learning projects. The source codes, supplementary materials, and guidance is publicly available on GitHub: https://github.com/tohid-yousefi/pyallffs.
Penerapan Metode Fuzzy Time Series untuk Memprediksi Hasil Panen Kopi pada Dinas Pertanian
Authors: WAHYU FUNGKI , Nurcahyo Gunadi Widi , Arlis Syafri
Published: September 2024

Kopi merupakan salah satu produk tanaman di bidang perkebunan yang dibutuhkan oleh masyarakat di seluruh dunia. Indonesia merupakan salah satu negara sebagai produsen penghasil kopi terbesar keempat setelah Brazil, Columbia dan Vietnam. Produksi kopi Indonesia mencapai 640 ribu ton per tahun, sekitar 71 persen (460 ribu ton) diekspor ke manca negara, Indonesia mengekspor kopi ke lebih dari 50 negara. Jenis tanaman kopi bermacam-macam di antaranya kopi robusta, arabika dan jenis kopi liberika. Penelitian ini bertujuan untuk memprediksi hasil panen kopi pada periode yang akan datang. Metode yang digunakan dalam penelitian ini adalah Fuzzy Time Series. Pemilihan  metode Fuzzy  Time  Series dikarenakan  data hasil panen kopi yang naik turun sesuai  dengan  prinsip  Fuzzy  dan  data  deret  waktu  (time series) yang bertujuan untuk menentukan pola dan keteratuan agar dapat digunakan untuk meramalkan kejadian pada periode yang akan datang Metode ini memiliki tujuh tahapan yaitu, pembentukan universe of discourse, menentukan jumlah kelas dan Panjang interval, menentukan himpunan fuzzy dan derajat keanggotaan, fuzzifikasi, pembentukan fuzzy logic relationship, pembentukan fuzzy logic relationship group, dan defuzzifikasi. Dataset yang diolah dalam penelitian ini bersumber dari dinas pertanian kabupaten kerinci. Dataset terdiri dari data hasil panen kopi perbulan selama 5 tahun terakhir, dengan jumlah data sebanyak 60. Hasil penelitian ini dapat memprediksi hasil panen kopi dengan perhitungan akurasi prediksi menggunakan MAPE didapatkan persentase nilai error 9.2 %. sesuai dengan kriteria MAPE, suatu peramalan dianggap akurat jika nilai error yang dihasilkan kurang dari 10%. Oleh karena itu, informasi ini dapat menjadi acuan untuk membantu para petani kopi dan pemangku kepentingan lainnya dalam mengatur strategi produksi, distribusi dan pemasaran kopi
Iterative Root-Finding Algorithm for Accurate Parameter Extraction of Solar Photovoltaic Cells
Authors: Douırı Moulay Rachid
Published: September 2024

The performance of photovoltaic models depends significantly on the accuracy of their parameters, which are determined by the chosen method and objective function. Extracting these parameters accurately under different environmental conditions is essential to enhance reliability, accuracy, and minimize system costs. In this research, a novel technique is proposed for extracting the electrical parameters of the solar cell single diode model, including saturation current, serial resistance, parallel resistance, and ideality factor. To overcome the challenges posed by the chaotic behavior of the I-V curve equation, an improved Iterative Root-Finding algorithm is introduced. This algorithm acts as an optimization tool, increasing the likelihood of obtaining highly accurate solutions by minimizing the quadratic error between experimental and theoretical characteristics in a shorter time frame. The numerical and experimental results demonstrate the effectiveness of this approach in solar module modeling, showing squared errors approaching zero. This study opens new possibilities for improving the accuracy and reliability of photovoltaic models, leading to more efficient solar energy systems.
Association of HBA1C level with extent of Acute Myocardial Infarction and Short Term Mortality
Authors: Panhwar Shahnawaz , Memon Shahid Hussain , Soomro Muhammad Khan , Soomro Tahir Hussian , Memon Abdul Ghaffar
Published: September 2024

ABSTRACT
Objectives: To determine the prognostic value of HBA1C level with extent of acute Myocardial Infarction (MI) and short-term mortality in patients without known Diabetes.
MATERIAL AND METHODS
The prospective cohort, department of Cardiology at Liaquat University Hospital Hyderabad during the period of one year from February 2020 January 2021. All the patients aged 20-75 years, both genders with acute MI (STEMI and NSTEMI) were included. All the patients diagnosed for MI according to ECG and serum cardiac biomarkers such as Troponin-T and Troponin-I. Blood sample were taken from all the cases for assessment of HbA1c level. Echocardiography was done and categorized according to the left ventricle ejection fraction. Short term mortality was assessed in all patients. All the data was recorded in the proforma for the purpose of analysis. After collection of data the analysis was conducted by using SPSS version 22.0.
Results:  Total 377 patients of acute MI were studied; their mean age was 50.42+11.71 years. Out of all study subjects’ males were in majority 83.0% and females were 17.0%. Out of all 59.4% had HbA1c level <5.5 and 40.6% had HbA1c was <6.5.  Most of the study subjects 62.9% had left ventricular ejection fraction was <40%. Majority of the cases 77.7% had STEMI and NSTEMI was seen in 22.3% of the cases. Overall short-term mortality (30 days) was found 14.3%.
In this study short term mortality (30 days) was statistically significant according to the gender, HbA1c, left ventricular ejection fraction and types of the MI, P-<0.05).
Conclusion: As pers study conclusion overall short-term mortality (30 days) was 14.3%. Higher HbA1c was observed to be a potential indicator for short term mortality among patients of acute coronary syndrome (ACS) and a predictor for short-term mortality in ACS patients without known DM and without DM
Key words: Acute MI, 30 days mortality, Hba1c
A unified global model accompanied with a voltage and current sensor for low-pressure capacitively coupled RF discharge
Authors: Seong Inho , Kim Sijun , Lee Woobeen , Lee Youngseok , Cho Chulhee , Jeong Wonnyoung , Choi Minsu , Choi Byeongyeop , Seo Huichan , Song Sangheon , You Shinjae
Published: September 2024

A global model (GM) assumes ion energy (

ε

) on the electrode equals the time-averaged sheath voltage (

V

sh

t

t

). However, using particle-in-cell simulation, we found that

ε

differs from

V

sh

t

t

.

We propose a unified global model (UGM) that calculates

ε

and collisional energy losses of ions by employing plasma circuit and sheath models, accompanied by a voltage and current sensor. We compared the results of the UGM with the experimental measurements and the results revealed that UGM is closer to the experiment than GM. UGM shows a linear relationship with the experiment, indicating that the UGM is applicable for plasma monitoring.
Eplingiella sanoi sp. nov. (Hyptidinae-Lamiaceae): supports the urgent need for campos rupestres conservation in the Serra do Espinhaço Septentrional, Minas Gerais state, Brazil
Authors: Antar Guilherme Medeiros , Harley Raymond Mervyn , Barêa Pastore José Floriano , Verdi Marcio , De Souza Soares Arthur
Published: September 2024

A new species of Lamiaceae, Eplingiella sanoi, from the campo rupestre of an ecotone zone between the Cerrado and the Caatinga domains is described and illustrated. The new species expands the distribution of the genus to Southeast Brazil, previously restricted to Northeast Brazil. Eplingiella sanoi is compared to the three other species of the genus, especially E. cuniloides, the morphologically closest related species. We present an identification key for all the species of the genus, an occurrence map for Eplingiella sanoi, E. cuniloides and E. brightoniae and a formal conservation assessment for the new species. Eplingiella sanoi is endemic to the region between Pico da Formosa and Pico do Sucuruiú (Minas Gerais state, Serra do Espinhaço), an area under threat due to a planned wind farm installation. Recognizing this species emphasizes the imperative for more taxonomic studies and conservation of Serra do Espinhaço.
Xylopia nilotica (Annonaceae) in Ethiopia, Sudan, South Sudan, and Uganda, with a review of the genus in North Eastern Tropical Africa
Authors: Friis Ib , Weber Odile
Published: September 2024

Based on written records and specimens of the new species, Xylopia nilotica D. M. Johnson & N. A. Murray (2018), described from Uganda and west of the Nile in Sudan and South Sudan, we have mapped the species. We find that it also occurs east of the Nile in South Sudan and in western Ethiopia. Its habitats range from open rain forest to open woodland. Modelling the potential distribution of X. nilotica suggests that it occurs in the periphery of the upper Nile basin, but it is probably undercollected. The potential distributions of X. longipetala (a Guineo-Congolian species) and X. holtzii Engl. (an East African coastal species), distinct but previously considered conspecific with X. nilotica, only marginally overlap with that of X. nilotica, which is endemic to the countries Uganda, South Sudan, Sudan, and Ethiopia, apparently a unique pattern of endemism. The new information does not change the assessment of X. nilotica as Vulnerable (VU). Other species of Xylopia in North Eastern Tropical Africa are X. rubescens Oliver and X. thomsonii Oliver in the Equatoria region of South Sudan, and X. rubescens, X. staudtii Engl. & Diels, and X. aethiopica (Dunal) A. Rich. in Uganda. A record of X. aethiopica in Ethiopia is based on false label information on the only known specimen.
Programa de educación emocional para el fomento de competencias emocionales en el personal de salud: Una aplicación práctica en ambientes hospitalarios
Authors: Bustos Lucero Jeraldine Gabriela , Matabanchoy Salazar Johana Madelyn , Bastidas Jurado Claudia Fernanda , Muñoz Muñoz Diego Fernando , Lopez Barreto Lina María , Ordoñez Mayra Fernanda
Published: September 2024

El entorno hospitalario se caracteriza por altos niveles de estrés y demandas laborales intensas, junto con la exposición constante a situaciones emocionalmente exigentes como enfermedades graves y la muerte de pacientes. Sin embargo, pese a las implicaciones de las demandas emocionales como factor de riesgo psicosocial para el personal de salud, en la literatura revisada no son populares las intervenciones en educación emocional dirigidas a dicho personal. En este artículo se propone un programa de educación emocional (PEE) para la atención de demandas emocionales del personal de salud del área asistencial de un hospital pediátrico de alta complejidad. El PEE propuesto tiene su base en la teoría de competencias emocionales y de mindfulness, y metodológicamente utiliza un diseño cuasi experimental con medidas pretest y posttest. Como resultado, se encontró que el programa tuvo un impacto positivo en las competencias emocionales de los participantes, específicamente en la competencia referida a conciencia emocional. Este estudio confirma la importancia de la conciencia emocional como base para el desarrollo de competencias emocionales, mientras que allana el camino para la generación de programas de educación emocional en el sector de la salud.