bluuebunny/crossref_metadata_2025 huggingface dataset:
Analytical Pricing of Commodity Futures with Correlated Jumps and Seasonal Effects: An Empirical Study of Thailand’s Natural Rubber Market
Authors: Sutchada Athinan , Rujivan Sanae , Djehiche Boualem
Published: February 2025

This paper presents a novel multivariate mean-reverting jump-diffusion model that incorporates correlated jumps and seasonal effects to capture the complex dynamics of commodity prices. The model also accounts for the interplay between price volatility and convenience yield, offering a comprehensive framework for commodity futures pricing. By leveraging the Feynman–Kac theorem, we derive a partial integro-differential equation for the conditional moment generating function of the log price, enabling an analytical solution for pricing commodity futures. This solution is validated against Monte Carlo simulations, demonstrating high accuracy and computational efficiency. The model is empirically applied to historical futures prices of natural rubber from the Thailand Futures Exchange. Key parameters—including commodity price dynamics, convenience yields, and seasonal factors—are estimated, revealing the critical role of jumps and seasonality in influencing market behavior. Notably, our findings show that convenience yields are negative, reflecting higher inventory costs, and tend to increase with rising spot prices. These results provide actionable insights for traders, risk managers, and policymakers in commodity markets, emphasizing the importance of correlated jumps and seasonal patterns in pricing and risk assessment.
Simulation of MCDM Process—Stope and Fan Pattern Selection in an Underground Mine with Uncertainty
Authors: Urošević Katarina , Gligorić Zoran , Janković Ivan , Gluščević Branko , Beljić Čedomir
Published: February 2025

Multi-criteria decision making (MCDM) refers to methods and processes used to evaluate and prioritize options when multiple criteria are involved. Extensive research conducted in the past has shown that uncertainty is a pervasive challenge in the decision-making process, particularly in complex and dynamic environments, such as mining. When making decisions under uncertainty, especially in stope and fan pattern selection for underground mining, it is crucial to consider various aspects, including economic and production factors. This paper presents an application of simulation combined with the ranking alternatives by perimeter similarity (RAPS) method for optimal stope and fan pattern selection in an underground mine. The results obtained were compared with existing MCDM methodology technique for order of preference by similarity to ideal solution (TOPSIS) and showed a very high correlation, which indicates the applicability of new methodology for decision making in mining industry problems.
Dynamic Modeling and Disturbance-Observer-Enhanced Control for Mecanum-Wheeled Vehicles Under Load and Noise Disturbance
Authors: Li Chensheng , Li Zhi
Published: February 2025

This paper investigates the dynamic modeling and robust control of a Mecanum-wheeled vehicle (MWV) under load disturbances and measurement noise. The system is modeled as a cascaded state-space representation, where the motor transfer function (PWM input → torque output) and the vehicle transfer function (torque input → vehicle speed output) are combined. The PWM-induced motor delay is linearized, and the complete dynamic model is derived using Lagrangian mechanics, addressing the limitations of conventional models that are incomplete and unable to decouple control signals from disturbance signals. For the developed model, a robust stability controller is designed by integrating Internal Model Control (IMC) with a Disturbance Observer (DOB), enhancing real-time disturbance rejection. Open-loop experiments validate the model’s accuracy, showing a Dynamic Time Warping (DTW) error of 0.2662 m, significantly lower than the 0.3198 m observed in traditional models. In closed-loop simulations, under load disturbances (TL=0.1 to TL=−0.7) and Gaussian noise (power: 0.0001–0.00005), the proposed IMC + DOB controller achieves 97.6% faster stabilization than IMC and 98.3% faster than PID, demonstrating superior convergence speed, robustness, and disturbance rejection. This study provides a novel control strategy that effectively handles non-square system dynamics while mitigating external disturbances in real time. The proposed framework enhances trajectory tracking accuracy and stability, with potential applications in autonomous robotics and vehicular systems.
Visual Servo Tracking Control and Scene Depth Identification of Mobile Robots with Velocity Saturation Constraints
Authors: Zhang Qiaomei , Li Baoquan , Sun Fuyun
Published: February 2025

Velocity saturation constraints are a significant issue for wheeled mobile robots (WMRs) when designing kinematics-based control laws. To handle the problem of velocity saturation constraints, a novel monocular visual servoing controller is developed for WMRs to solve tracking problems and enable unknown depth estimation. By analyzing the kinematic model of the robot system and employing the homography decomposition technique, measurable signals are obtained to develop a visual tracking error model for non-holonomic mobile robots. To ensure that the velocity commands are consistently constrained within the allowed limits, a saturation function is employed in the designed visual servoing control law. Furthermore, an adaptive updating law is designed to estimate the unknown depth information. The boundedness of the velocity commands is analyzed to evaluate the saturation performance of the developed visual servoing controller. With the aid of Lyapunov techniques and Barbalat’s lemma, the stability of this scheme is demonstrated. The simulation and experiment verify the performance of the proposed method.
Thermal Stability Calculation of Typical Phases in Tungsten Cathodes
Authors: Wang Jiaxuan , Yang Jiancan , Zhang Po , Nie Zuoren
Published: February 2025

Thermodynamic calculations were carried out on typical tungsten cathode materials using Factsage software within a temperature range of 1000–3400 °C. The relationship between the phase stability and electron emission performance of the cathode in a vacuum environment and under a protective atmosphere was investigated. The thermodynamic stability of tungsten cathodes doped with different proportions of carbides and oxides was calculated. It was found that when the doped phase (ThO2, La2O3, Y2O3, Lu2O3, Er2O3, Gd2O3, TiO2, ZrO2, HfO2, ThC2, LaC2, YC2, TiC, ZrC, and HfC) in the cathode starts to be consumed, the electron emission performance of the cathode will decline. Therefore, the high-temperature stability of the doped phase carbides and oxides also affects the operating temperature of the cathode. To verify these results, this study tested the electron emission performance of W–La2O3, W–ThO2, W–ZrO2, W–ZrC, and W–HfC, plotting their volt–ampere characteristic curves. The results indicated that the W-La2O3 cathode exhibits the best emission performance at low temperatures, while the W-ThO2, W–ZrO2, W–ZrC, and W–HfC cathodes showed better emission performance at high temperatures. The experimental results are in good agreement with the simulation results. The thermal stability of the doped phase is closely related to the high-temperature thermal stability of the cathode.
Bacillus halophilus BH-8 Combined with Coal Gangue as a Composite Microbial Agent for the Rehabilitation of Saline-Alkali Land
Authors: Bi Weilin , Sun Yixuan , Yao Zhipeng , Zhao Zhe , Niu Yusheng
Published: February 2025

Saline-alkali land represents a crucial reserve of arable land essential for ensuring food security. However, there remains a significant deficiency in converting saline-alkali land into productive cultivated or grazing areas. Microbial agents hold substantial potential for the reclamation of saline-alkali soils. In this study, a moderately halophilic bacterium, Bacillus halophilus BH-8, was screened from coastal saline soil. We combined strain BH-8 with coal gangue to create a composite microbial agent, which was shown to effectively increase the levels of available nitrogen, available phosphorus, available potassium, and organic matter, while reducing the pH value of saline-alkali soils. Moreover, it significantly enhanced the activity of various enzymes and altered the microbial community composition in the soil, notably increasing the abundance of Pseudomonas and Bacteroidota. These results demonstrate the application value of this composite microbial agent for rehabilitating saline-alkali land and highlight the potential of the BH-8 strain as a promising candidate for microbial agent research.
Thermochronology of the Kalba–Narym Batholith and the Irtysh Shear Zone (Altai Accretion–Collision System): Geodynamic Implications
Authors: Travin Alexey , Buslov Mikhail , Murzintsev Nikolay , Korobkin Valeriy , Kotler Pavel , Khromykh Sergey V. , Zindobriy Viktor D.
Published: February 2025

The granitoids of the Kalba–Narym batholith and the Irtysh shear zone (ISZ) are among the main geological features of the late Paleozoic Altai accretion–collision system (AACS) in Eastern Kazakhstan. Traditionally, it is believed that late Paleozoic strike-slip faults played a pivotal role at all stages of the development of the AACS, they were supposed to control deformation, magmatism, and ore deposits. This work is devoted to solving the problem of the tectonic evolution of the AACS based on the reconstruction of the thermal history of granitoids of the Kalba–Narym batholith in connection with the Chechek metamorphic dome structure, which is one of the highly metamorphosed blocks mapped within the ISZ. The new geological and geochronological data presented in this work allowed us to establish the sequence of formation of the Kalba–Narym granitoid batholith and link it with the evolution of the Irtysh shear zone (ISZ). It was revealed that in the late Carboniferous–early Permian (312–289 Ma), during the NE–SW compression, the Irtysh shear zone formed as a gently dipping thrust system into which gabbro of the Surov massif intruded. The combined manifestation of magmatic and tectonic processes caused the formation of tectonic mélange with cataclastic gabbro and metamorphic rocks of the Chechek metamorphic dome structure (312–289 Ma). Compression caused the formation of a cover-thrust structure. The thickening of the crust under the probable thermal action of the Tarim plume led to the formation of the early Permian Kalba–Narym batholith (297–284 Ma) within the Kalba–Narym terrane. Denudation of the orogen occurred before the Early Triassic (280–229 Ma). In this way the sequence of formation of the Kalba–Narym batholith and the ISZ is consistent with the concepts of the stages of plume-lithosphere interaction within the AACS under the influence of the late Carboniferous–early Permian Tarim igneous province, but in the cover-thrust tectonic setting.
Evaluation and Characterization of High-Uniformity SiNx Thin Film with Controllable Refractive Index by Home-Made Cat-CVD Based on Orthogonal Experiments
Authors: Li Caifang , Li Minghui , Shi Jinsong , Huang Haibin , Li Zhimei
Published: February 2025

Silicon nitride (SiNx) thin film is a promising coating with great physiochemical and optical properties. However, the preparation of films with good comprehensive properties still faces challenges. This study focused on developing a method for the preparation of uniform SiNx thin film with a controllable refractive index using home-made catalytic chemical vapor deposition (Cat-CVD) equipment. Orthogonal experimental design was employed to investigate the effects of four key influence factors, including reaction pressure, the ratio of SiH4 to NH3, the ratio of SiH4 to H2, and substrate temperature. The response parameters evaluated were the refractive index, extinction coefficient, uniformity, and deposition rate of SiNx thin film. Compared with the single-factor variable tests, an orthogonal experiment could obtain the optimal preparation process of the SiNx thin film with the best comprehensive quality through the least number of experiments. At the same time, the microstructures of SiNx thin film were analyzed by various characterization methods, including Fourier-transform infrared spectroscopy (FTIR), X-ray photoelectron spectroscopy (XPS), and scanning electron microscopy (SEM), to research the relationship between preparation factors and the properties of SiNx thin film. This paper provides the theoretical guidance for fine-regulating the properties of SiNx thin film in practical applications.
Controllable Preparation of Low-Cost Coal Gangue-Based SAPO-5 Molecular Sieve and Its Adsorption Performance for Heavy Metal Ions
Authors: Kang Le , Xu Boyang , Li Pengfei , Wang Kai , Chen Jie , Du Huiling , Liu Qianqian , Zhang Li , Lian Xiaoqing
Published: February 2025

With the advancement of industrial production and urban modernization, pollution from heavy metal ions and the accumulation of solid waste have become critical global environmental challenges. Establishing an effective recycling system for solid waste and removing heavy metals from wastewater is essential. Coal gangue was used in this study as the primary material for the synthesis of a fully coal gangue-based phosphorus-silicon-aluminum (SAPO-5) molecular sieve through a hydrothermal process. The SAPO-5 molecular sieve was characterized through several methods, including X-ray diffraction (XRD), scanning electron microscopy (SEM), BET surface analysis, Fourier-transform infrared (FT-IR) spectroscopy, and X-ray photoelectron spectroscopy (XPS), to examine its mineral phases, microstructure, pore characteristics, and material structure. Adsorption performance towards wastewater with Cd2+ and Pb2+ ions was investigated. It was found that the adsorption processes of these ions are well described by both the pseudo-second-order model and the Langmuir isotherm. According to the Langmuir model, the coal gangue-based SAPO-5 molecular sieve exhibited maximum adsorption capacities of 93.63 mg·g−1 for Cd2+ and 157.73 mg·g−1 for Pb2+. After five cycles, the SAPO-5 molecular sieve retained strong stability in adsorbing Cd2+ and Pb2+, with residual adsorption capacities of 77.03 mg·g−1 for Cd2+ and 138.21 mg·g−1 for Pb2+. The excellent adsorption performance of the fully solid waste coal gangue-based SAPO-5 molecular sieve is mainly attributed to its mesoporous channel effects, the complexation of -OH functional groups, and electrostatic attraction.
Impact of Prenatal Dietary Soy on Cerebellar Neurodevelopment and Function in Experimental Fetal Alcohol Spectrum Disorder
Authors: de la Monte Suzanne M. , Tong Ming , Ziplow Jason , Mark Princess , Van Stephanie , Nguyen Van Ahn
Published: February 2025

Background: Prenatal alcohol exposure (PAE) models can cause neurodevelopmental abnormalities like those observed in fetal alcohol spectrum disorder (FASD). Previous studies link experimental PAE effects in the brain to impaired signaling through insulin/IGF and Notch pathways that mediate neuronal survival, growth, migration, energy metabolism, and plasticity. Importantly, concurrent administration of peroxisome proliferator-activated receptor agonists or dietary soy prevented many aspects of FASD due to their insulin-sensitizing, anti-inflammatory, and antioxidant properties. Objective: To determine if dietary soy interventions during pregnancy would be sufficient to normalize central nervous system structure and function, we examined the effects of maternal gestation-limited dietary soy on cerebellar postnatal development, motor function, and critical signaling pathways. Methods: Pregnant Long Evans rats were fed isocaloric liquid diets containing 0% or 26% caloric ethanol with casein or soy isolate as the protein source. The ethanol and soy feedings were discontinued upon delivery. The offspring were subjected to rotarod motor function tests, and on postnatal day 35, they were sacrificed to harvest cerebella for histological and molecular studies. Results: Despite the postnatal cessation of alcohol exposure, chronic gestational exposure reduced brain weight, caused cerebellar hypoplasia, and impaired motor performance. Gestational dietary soy prevented the ethanol-associated reduction in brain weight and largely restored the histological integrity of the cerebellum but failed to normalize motor performance. Ethanol withdrawal abolished the impairments in insulin/IGF signaling that were previously associated with ongoing ethanol exposures, but ethanol’s inhibitory effects on Notch and Wnt signaling persisted. Soy significantly increased cerebellar expression of the insulin and IGF-1 receptors and abrogated several ethanol-associated impairments in Notch and Wnt signaling. Conclusions: Although gestation-restricted dietary soy has significant positive effects on neurodevelopment, optimum prevention of FASD’s long-term effects will likely require dietary soy intervention during the critical periods of postnatal development, even after alcohol exposures have ceased.
Development and Evaluation of an AI-Assisted Answer Assessment (4A) for Cognitive Assessments in Nursing Education
Authors: Xuto Piyanut , Prasitwattanaseree Piyaporn , Chaiboonruang Tareewan , Chaiwuth Sujitra , Khwanngern Podjanee , Nuntakwang Chadchadaporn , Nimarangkul Karnjana , Suwansin Wara , Khiaokham Lawitra , Bressington Daniel
Published: February 2025

Artificial intelligence (AI) can potentially enhance cognitive assessment practices in maternal and child health nursing education. Objectives: To evaluate the reliability, accuracy and precision, and external validity of an AI-assisted answer assessment (4A) program for cognitive assessments in nursing education. Methods: This study is a validation study. Initially, 170 nursing students from northern Thailand participated, with 52 randomly selected for detailed testing. Agreement testing between the 4A program and human experts was conducted using the intraclass correlation coefficient (ICC). Accuracy and precision testing compared 4A scores with human expert assessments via the McNemar test. External validation involved 138 participants to compare the 4A program’s assessments against national examination outcomes using logistic regression. Results: Results indicated a high level of consistency between the 4A program and human experts (ICC = 0.886). With an accuracy of 0.808 and a precision of 0.913, compared to the human expert’s accuracy of 0.923 and precision of 1.000. The McNemar test (χ2 = 0.4, p = 0.527) showed no significant difference in evaluation performance between AI and human experts. Higher scores on the 4A program significantly predicted success in the national nursing examination (OR: 1.124, p = 0.031). Conclusions: The 4A program demonstrates potential in reliably assessing nursing students’ cognitive abilities and predicting exam success. This study advocates for the continued integration of AI in educational assessments and the importance of refining AI systems to better align with traditional assessment methods.
Comparison of Two Bacillus Strains Isolated from the Coastal Zone in Barley (Hordeum vulgare L.) Under Salt Stress
Authors: Teker Yıldız Müge , Acar Okan
Published: February 2025

Salt stress is one of the most important abiotic stress factors that negatively affects sustainable crop production, agricultural productivity, and microbial life. Increasing salt stress negatively affects the growth and development of barley, posing a threat to global food security. It is now known that inoculation of plant growth-promoting rhizobacteria (PGPR) has significant potential in increasing stress tolerance and yield in agricultural products. This study focused on the effects of Bacillus cereus CUN6 and Bacillus thuringiensis SIRB2, isolated from the coastal zone and tested for their PGPR capacities, on physiological (root length, shoot length, biomass, dry weight) and biochemical (total chlorophyll, total protein, hydrogen peroxide, lipid peroxidation, peroxidase activity (POX), catalase activity (CAT)) analyses in Hordeum vulgare L. seedlings under salt stress. The results showed that the two bacterial inoculations alleviated the negative effects of salt stress by increasing the root-shoot length, biomass, dry weight, chlorophyll content, and total protein content in barley plants. However, B.thuringiensis increased growth and development especially in root length, biomass, and dry weight compared to B.cereus. On the other hand, B.cereus significantly increased root length, biomass, and chlorophyll content under salt stress; these increases were 17%, 5%, and 7%, respectively. B.thuringiensis chlorophyll content increased by 4% in 300 mM NaCl compared to the control. When compared in terms of the antioxidant defense system, B.thuringiensis inoculation was more effective on CAT activity, while B.cereus inoculation was more effective on POX activity. Under salt stress, B.cereus and B.thuringiensis inoculation significantly decreased H2O2 content in barley; these decreases were 16% and 10%, respectively. Additionally, TBARs content was significantly decreased by B.cereus and B.thuringiensis inoculation under salt stress; these decreases were determined as 8% and 9%, respectively, compared to the control. These results indicated that both bacterial inoculations can alleviate the salt tolerance of barley seedlings by regulating antioxidant metabolism. This research focused on the potential of B.cereus and B.thuringiensis as biofertilizers against salt stress in barley based on physiological and biochemical analysis.
Impact of Water Management on Growth and Pigment Composition of Cauliflower and Broccoli
Authors: Izadpanah Fatemeh , Abbasi Navid , Soltani Forouzande , Baldermann Susanne
Published: February 2025

Global climate change minimizes fresh water resources used in agriculture worldwide. It causes drought stress, which has adverse effects on plants. To ensure food security, crops and vegetables capable of tolerating shortages of water over the growth period are needed. This study aimed to elucidate the morphological and biochemical responses of three colored cauliflower (Brassica oleracea var. botrytis) cultivars (Clapton, Trevi, and Di Sicilia Violetto) and one broccoli cultivar (Brassica oleracea var. italica var. Magic) to different irrigation treatments (85–100%, 65–80%, 45–60%, and 25–40% field capacity). Assessment of growth parameters revealed no significant difference among all the treatments for root fresh weight, leaf area, and floret size. Major water shortages reduced the floret and stem fresh weight of the Clapton cultivar. Additionally, under severe drought stress, only the Di Sicilia Violetto cultivar had a decrease in plant height, but no impact on the number of leaves was observed. The measurement of pigment contents in the leaves showed no significant difference in carotenoids in all the cultivars; just the chlorophyll contents decreased with moderate stress in the Di Sicilia Violetto cultivar. This research demonstrates that cauliflower and broccoli are likely drought-tolerant vegetables and common irrigation regimes may be reviewed.
Domain-Specific Manufacturing Analytics Framework: An Integrated Architecture with Retrieval-Augmented Generation and Ollama-Based Models for Manufacturing Execution Systems Environments
Authors: Choi Hangseo , Jeong Jongpil
Published: February 2025

To support data-driven decision-making in a Manufacturing Execution System (MES) environment, a system that can quickly and accurately analyze a wide range of production, quality, asset, and material information must be deployed. However, existing MES data management approaches rely on predefined queries or report templates that lack flexibility and limit real-time decision support. In this paper, we proposes a domain-specific Retrieval-Augmented Generation (RAG) architecture that extends LangChain’s capabilities with Manufacturing Execution System (MES)-specific components and the Ollama-based Local Large Language Model (LLM). The proposed architecture addresses unique MES requirements including real-time sensor data processing, complex manufacturing workflows, and domain-specific knowledge integration. It implements a three-layer structure: an application layer using FastAPI for high-performance asynchronous processing, an LLM layer for natural language understanding, and a data storage layer combining MariaDB, Redis, and Weaviate for efficient data management. The system effectively handles MES-specific challenges such as schema relationships, temporal data processing, and security concerns without exposing sensitive factory data. This is an industry-specific, customized approach focusing on problem-solving in manufacturing sites, going beyond simple text-based RAG. The proposed architecture considers the specificity of data sources, real-time and high-availability requirements, the reflection of domain knowledge and workflows, compliance with security and quality control regulations, and direct interoperability with MES systems. The architecture can be further enhanced through integration with various manufacturing systems, an advanced LLM, and distributed processing frameworks while maintaining its core focus on MES domain specialization.
High-Accuracy Simulation of Polymer Flooding Based on Weighted Essentially Non-Oscillatory (WENO) Scheme
Authors: Wei Jun , Zhang Zhijun , Zhang Xinlong , Rao Xiang
Published: February 2025

This paper develops a numerical simulation method for polymer-flooding reservoirs using the high-order Weighted Essentially Non-Oscillatory (WENO) scheme. The research begins by leveraging the WENO method to obtain high-order approximations of the saturation and polymer concentration functions and formulates a sequential solution strategy for the hyperbolic mass conservation equations of the water phase and polymer component in these reservoirs. Three numerical tests compare the WENO scheme with the traditional first-order upwind difference method. The results show that the WENO scheme has higher computational accuracy, especially in predicting fronts, which improves the prediction of water cut and polymer production concentration. Under the same accuracy, the WENO method requires fewer grids and has much higher computational efficiency. A sensitivity analysis of the polymer solution viscosity parameters verifies that the WENO method can accurately simulate reservoir production behavior, providing an efficient and accurate reservoir simulation alternative.
Data Clustering-Driven Fuzzy Inference System-Based Optimal Power Flow Analysis in Electric Networks Integrating Wind Energy
Authors: Grigoras Gheorghe , Livadariu Bogdan , Neagu Bogdan-Constantin
Published: February 2025

The development of smart grids has led to an increased focus by transmission and distribution network operators on the Optimal Power Flow (OPF) problem. The solutions identified for an OPF problem are vital to ensure the real-time optimal control and operation of electric networks and can help enhance their efficiency. In this context, this paper proposed an original solution to the OPF problem, represented by optimal voltage control in electric networks integrating wind farms. Based on a fuzzy inference system (FIS) built in the Fuzzy Logic Designer of the Matlab environment, where the fuzzification process was improved through fuzzy K-means clustering, two approaches were developed, representing novel tools for OPF analysis. The decision-maker can use these two approaches only successively. The FIS-based first approach considers the load requested at the PQ-type buses and the powers injected by the wind farms as the fuzzy input variables. Based on the fuzzy inference rules, the FIS determines the suitable tap positions for power transformers to minimise active power losses. The second approach (I-FIS), representing an improved variant of FIS, calculates the steady-state regime to determine power losses based on the suitable tap positions for power transformers, as determined with FIS. A real 10-bus network integrating two wind farms was used to test the two proposed approaches, considering comprehensive characteristic three-day tests to thoroughly highlight the performance under different injection active power profiles of the wind farms. The results obtained were compared with those of the best methods in constrained nonlinear mathematical programming used in OPF analysis, specifically sequential quadratic programming (SQP). The errors calculated throughout the analysis interval between the SQP-based approach, considered as the reference, and the FIS and I-FIS-based approaches were 5.72% and 2.41% for the first day, 1.07% and 1.19% for the second day, and 1.61% and 1.33% for the third day. The impact of the OPF, assessed by calculating the efficiency of the electric network, revealed average percentage errors between 0.04% and 0.06% for the FIS-based approach and 0.01% for the I-FIS-based approach.
Religious Passions and Prayer Channeling Divine Disclosure: The Testimony of the Fourth-Century Syrian Fathers
Authors: Vassányi Miklós
Published: February 2025

In this paper, I investigate what role religious emotions, passions, and prayer may play in what may be called the religion of the heart in early Syrian theology, especially in the several works of ’Aphrahaṭ, Saint Ephrem, and the anonymous collection titled the Book of Steps, all from the fourth century. In the original Syriac sources, one may see how in this vast corpus, religious emotions and prayer act as a corridor channeling the believer’s striving for the disclosure of the mysteries surrounding God. It will also be shown that while these sources advocate in unison for the heart’s function in connecting the believer with God, their respective interpretive theological contexts are different. These points are substantiated by virtue of a number of citations from the original texts.
Optimization of Agricultural Enterprises’ Sown Areas Considering Crop Rotation
Authors: Shmygol Nadiia
Published: February 2025

This article explores contemporary scientific approaches to improving the efficiency of agricultural operations in Ukraine. It has been identified that insufficient attention has been given to optimizing the activities of agricultural enterprises. A model for optimizing crop areas, considering crop rotations in crop production or mixed-type enterprises, has been developed to ensure an increase in crop yields. The model incorporates factors such as soil health, pest management, and the economic feasibility of different cropping systems. By applying crop rotation principles, the model aims to achieve a balanced and sustainable agricultural practice, promoting both productivity and environmental sustainability. The findings highlight the importance of considering ecological factors and economic optimization in agricultural planning. The model demonstrates how the rotation of crops can prevent soil depletion and improve overall land use efficiency, thereby boosting the agricultural output of enterprises. The proposed approach is distinguished by its uniqueness, as it leverages advanced economic–mathematical methodologies and state-of-the-art information–analytical tools to enable the automation of the crop rotation planning process. The implementation of this approach can lead to more sustainable farming practices, enhanced soil fertility, and increased profitability.
Paraxial Propagation of Scattered Light Based on the Chirp Z-Transform
Authors: Zhao Lujia , Liu Yu-Ang , Ji Huiru , Wang Haibo , Tan Hao , Mo Yan , Ma Donglin
Published: February 2025

In the simulation of partially coherent light propagation within optical systems utilizing the Wigner function, the constraints imposed by the Fourier transform necessitate that the dimensions of the input and output matrices remain congruent. Consequently, the extent of the image plane is dictated by the dimensions of the light source matrix and the propagation distance. For optical systems of greater complexity, such simulations are highly memory-intensive. This paper innovatively incorporates the displacement theorem of the chirp z-transform and integrates it with the Wigner function. This approach affords enhanced flexibility in the simulation of partially coherent light transmission, enabling the targeted simulation of regions of interest within the frequency domain of the optical system, thereby significantly improving simulation efficiency. The efficacy of this novel method is demonstrated through the simulation of a Wigner transmission algorithm based on the chirp z-transform, applied to an RC (Ritchey–Chrétien) telescope system. The RC telescope, known for its optical design that minimizes aberrations and provides high-quality imaging, serves as a critical foundation for the simulation. The resultant simulations exhibit a high degree of consistency with traditional methods while offering increased flexibility, thus corroborating the validity and effectiveness of the proposed approach.
Recipe Based Anomaly Detection with Adaptable Learning: Implications on Sustainable Smart Manufacturing
Authors: Lee Junhee , Jang Jaeseok , Tang Qing , Jung Hail
Published: February 2025

The advent of Industry 4.0 has significantly transformed the manufacturing sector, bringing advancements in quality control efficiency, environmental sustainability, and production development. These changes have led to the development of intelligent technologies such as artificial intelligence (AI). However, implementing AI solutions in manufacturing processes still presents challenges in many aspects, particularly in handling irregular datasets influenced by diverse manufacturing settings. In the field of injection molding, quality inspection often occurs at the batch level rather than at the individual level, providing only the overall defect ratio of batch production instead of labeling each individual product. These issues limit the general application of AI and data-driven decision-making. To address these limitations and enhance product efficiency, this study proposes a novel anomaly detection framework for a specific manufacturing process. In Recipe-Based Learning, we first apply K-Means clustering to account for the flexible manufacturing process, which relies on diverse settings. The injection molding data are classified into setting-specific recipes to ensure data normality and uniqueness. The Kruskal-Wallis test is conducted to provide statistical evidence of differences in data based on varying settings, further justifying the necessity of Recipe-Based Learning. Then, Autoencoders for anomaly detection are trained with normal data from each recipe. With this data-driven AI approach, 61 defective products are predicted, compared to the existing 41 defects. Meanwhile, the integrated model, which does not consider variations in settings, only predicted 2 defects, indicating poor and distorted quality inspection. For Adaptable Learning, which focuses on new inputs with unseen settings, we apply KL-Divergence to identify the closest trained recipe data and its corresponding model. This approach outperformed both the integrated and additionally trained models in predictive power. As a result, continuous prediction is achieved without the need for further training, successfully enhancing process optimization. In the context of smart factories in the injection molding industry, such improvements in process management can significantly enhance overall productivity and decision-making, primarily through a data-driven AI approach.
A Secure and Lightweight Group Mobility Authentication Scheme for 6LoWPAN Networks
Authors: Ashrif Fatma Foad , Sundararajan Elankovan A. , Hasan Mohammad Kamrul , Ahmad Rami
Published: February 2025

The integration of Internet Protocol version 6 over Low-Power Wireless Personal Area Networks (6LoWPANs) provided IP technologies within wireless sensor networks that dramatically increased the Internet of Things (IoT). Therefore, to facilitate efficient mobility management for resource-constrained IP-based sensor nodes, the Proxy Mobile IPv6 (PMIPv6) standard has been introduced to reduce communication overhead. However, the standard has addressed security and mobility authentication challenges in 6LoWPANs, although recent solutions have yet to focus much on facilitating secure group handovers. Considering these issues, a Secure and Lightweight Group Mobility Authentication Scheme (SL_GAS) is proposed for 6LoWPAN’s highly constrained sensor nodes. SL_GAS innovatively utilizes one-time alias identities, temporary IDs, tickets, and an aggregated MAC with tags to ensure mutual authentication while maintaining sensor anonymity, providing a balanced security and privacy approach. SL_GAS’s robustness against a variety of security threats is validated through formal automated verification using the Scyther tool alongside SVO logic, while an informal analysis demonstrates its resilience to known attacks. Comparative analysis with existing schemes highlights SL_GAS’s advantages in reducing signal cost, transmission delay, communication, and computation overhead. SL_GAS stands out for its combination of security, privacy, and efficiency, making it a promising approach for enhancing IoT connectivity in resource-constrained settings.
Exploring Vulnerability to Stress and Its Correlation with Bullying in the Nurse’s Workplace
Authors: João Ana Lúcia , Coelho Anabela , Branco Nuno Sérgio , Portelada António
Published: February 2025

Background: Vulnerability to stress is associated with susceptibility to react to certain events, taking into account individual factors, beliefs, and available resources. Workplace bullying increases stress, absenteeism, and turnover among nurses, creating a toxic environment. This negatively impacts their well-being and compromises the quality of nursing care. As a result, patient safety and healthcare outcomes may be affected. Objectives: To assess the prevalence of vulnerability to stress in Portuguese nurses and its relationship with the experience of workplace bullying. Methodology: This study used a descriptive–correlational approach with a cross-sectional design. The data collection instrument used was a questionnaire consisting of a sociodemographic component and a scale assessing vulnerability to stress (QVS-23) and workplace bullying (NAQ-R). The total sample consisted of 2015 nurses working in healthcare institutions. Results: Nurses who perceived themselves as victims of workplace bullying were shown to be more vulnerable to stress, with a higher mean value for perfectionism and dramatization of existence, inhibition and functional dependence, lack of support and deprivation of affection, intolerance of frustration and rejection, and adverse living conditions. Conclusions: Organizations must create a healthy, respectful, and productive working environment by identifying the various factors that make them vulnerable to stress in the workplace. They must also act to prevent workplace bullying, thus protecting the health of nurses and promoting positive relationships and a harmonious work culture.
The Epidemiology of Injuries and Illnesses During SailGP Season 4: A Prospective Cohort Study
Authors: Fallon Thomas , Rousselon Hélène , Heron Neil
Published: February 2025

Introduction: Sailing is a high-intensity sport that demands a combination of physical strength, endurance, and technical skill. Sail Grand Prix (SailGP), inaugurated in 2019, epitomises a transformative approach to professional sailing. This study aims to provide a comprehensive analysis of injury and illness epidemiology among SailGP elite sailors, comparing injury and illness types and locations across different sailing activities. Methods: This prospective cohort study analysed injury and illness data from professional sailors throughout season 4 (2023/2024) of the professional sailing league. Data were collected on the number of hours spent in training, racing, and foiling, alongside injury reports, categorising injury types and locations. Incidence rates were calculated per 1000 h of sailing and 365 athlete days. Injuries were stratified by sex, position on the boat, and specific sailing activities to provide a detailed comparison. Results: A total of 100 sailors participated in the Sail GP 2024 season, accumulating 4919.84 h of recorded sailing activity: 2186.03 h in racing and 2733.80 h in training. The overall injury incidence rate was 9.96 per 1000 h of activity (95% CI: 7.17–12.75) and 7.43 per 365 athlete days (95% CI: 4.99–9.86). The injury rate was notably higher for foiling at 26.52 per 1000 h (95% CI: 19.09–33.94) compared to general sailing at 14.51 per 1000 h (95% CI: 10.44–18.57). Racing posed a greater injury risk than training, with an injury rate of 11.89 per 1000 h (95% CI: 7.77–16.46) compared to 8.41 per 1000 h for training (95% CI: 5.12–12.07). Grinders had the greatest rate of injuries at 3.86 (2.24, 5.69) injuries per 1000 h of sailing. The illness incidence rate was 5.14 per 1000 h (95% CI: 3.21–7.28), with respiratory illnesses being the most frequently reported. Conclusion: This study highlights the injury and illness risks amongst elite sailors in Sail GP. Males were at higher risk of injury, with the position of grinders being the most commonly injured. Ankle and knee injuries were the most prevalent. Future research should focus on developing sport-specific injury prevention programmes and examining long-term outcomes in sailors.
Quantitative Methods for Sustainable Product Development
Authors: Relich Marcin
Published: February 2025

Traditional approaches to product development have primarily focused on aspects related to business profits and providing a suitable functionality of products [...]
Greening Language Learning Pathways: Three Sustainable Practices Using the STAR Framework
Authors: Yıldırım Meral , Aytan Talat
Published: February 2025

Earth is currently facing a multifaceted planetary emergency, primarily due to a lack of fundamental knowledge regarding critical global issues. This situation necessitates the integration of the 17 Sustainable Development Goals (SDGs) established by the United Nations, which are to be achieved by 2030, into educational curricula. Such integration will ensure that future generations develop a comprehensive understanding of emerging threats and assume shared responsibility for sustaining the planet. In this context, language education serves as a foundational means of fostering global awareness. In this paper, the Common European Framework of Reference for Languages is adopted as a guide for pedagogical alignment and language development. Three course plans have been developed for A1, B1, and C1 proficiency levels to raise awareness of sustainability and enhance language competencies. Nature-related themes have been integrated into teaching Turkish as a foreign language using the STAR (Situation, Task, Action, Result) framework. Consequently, learners of Turkish as a foreign language engage with meaningful, real-life contexts that relate to the environmental and climate components of the SDGs. Based on this framework, this study aims to foster both linguistic and ecological literacy through the integration of sustainability themes into foreign language teaching.
Determinants of Superior Long-Term Business Performance in Thai Small and Medium-Sized Enterprises: An Integrated Analysis Using Fuzzy Rough Set Theory and Second Order Confirmatory Factor Analysis
Authors: Paweehirunkrai Tanyatron , Pankham Sumaman
Published: February 2025

This study investigates the determinants of superior long-term business performance in Thai digital entrepreneurship through an innovative mixed-method approach combining Rough Set Fuzzy Theory and Second-order Confirmatory Factor Analysis. This research addresses a significant gap in the existing literature by incorporating business strategies, product innovation, social media adoption, and entrepreneurial orientation into a comprehensive framework, extending beyond traditional Technology–Organization–Environment (TOE) models. This study analyzes seven key factors that influence digital business success: technology, organization, external environment, social media adoption, business strategy, product innovation, and entrepreneurial orientation. The methodological approach employed for this study utilized expert consensus validation and model verification techniques to develop a novel integrated model specifically tailored for Thailand’s digital SME context. The findings reveal that business strategy and entrepreneurial orientation are primary drivers of business success. This research provides valuable insights for practitioners in the Thai digital entrepreneurship ecosystem, offering a structured approach to achieving sustainable long-term business success.
Diagnosis of Lung Cancer Using Endobronchial Ultrasonography Image Based on Multi-Scale Image and Multi-Feature Fusion Framework
Authors: Wang Huitao , Nakajima Takahiro , Shikano Kohei , Nomura Yukihiro , Nakaguchi Toshiya
Published: February 2025

Lung cancer is the leading cause of cancer-related deaths globally and ranks among the most common cancer types. Given its low overall five-year survival rate, early diagnosis and timely treatment are essential to improving patient outcomes. In recent years, advances in computer technology have enabled artificial intelligence to make groundbreaking progress in imaging-based lung cancer diagnosis. The primary aim of this study is to develop a computer-aided diagnosis (CAD) system for lung cancer using endobronchial ultrasonography (EBUS) images and deep learning algorithms to facilitate early detection and improve patient survival rates. We propose M3-Net, which is a multi-branch framework that integrates multiple features through an attention-based mechanism, enhancing diagnostic performance by providing more comprehensive information for lung cancer assessment. The framework was validated on a dataset of 95 patient cases, including 13 benign and 82 malignant cases. The dataset comprises 1140 EBUS images, with 540 images used for training, and 300 images each for the validation and test sets. The evaluation yielded the following results: accuracy of 0.76, F1-score of 0.75, AUC of 0.83, PPV of 0.80, NPV of 0.75, sensitivity of 0.72, and specificity of 0.80. These findings indicate that the proposed attention-based multi-feature fusion framework holds significant potential in assisting with lung cancer diagnosis.
Susceptibility and Mechanism of Aflatoxin Contamination of Ziziphus jujuba var. spinosa
Authors: Elamin Abdelrahman , Sakuda Shohei
Published: February 2025

The susceptibility and mechanism of aflatoxin (AF) contamination in Ziziphus jujuba var. spinosa, whose seeds are important for medicinal use, were evaluated in this study. First, the susceptibility of intact fruits, classified into four maturity groups, to AF accumulation was assessed through artificial contamination with an aflatoxigenic Aspergillus flavus strain. AF analysis revealed that mid-mature fruits were highly susceptible to AF contamination. Next, AF accumulation in seed parts was examined by artificially inoculating A. flavus on intact fruits, showing AF presence in seeds after 30 days of incubation. The susceptibility of jujube kernels to AF accumulation in seed parts was then studied. The artificial inoculation of A. flavus on kernels, classified into three groups based on the pedicel condition, showed no correlation between AF contamination and the pedicel condition, with large fluctuations within each group. Finally, the effect of the hilar region morphology on AF contamination in seeds was investigated. The microscopic investigation of artificially contaminated seeds and AF quantification revealed that variations in AF concentration were linked to differences in the hilar region morphology.