bluuebunny/crossref_metadata_2025 huggingface dataset:
Silica Aerogel-Modified Polyacrylonitrile Nanofibers to Reduce Heat Flux in Heat Storage Tanks of Greenhouse Buildings
Authors: Li Yuze , Zhang Yongping , Sun Wenbo
Published: August 2024

Polyacrylonitrile (PAN) nanofibers have specific characteristics such as thermal insulation, weatherproofing, and sunlight resistance and therefore are appropriate to be applied as insulation materials for various industries, especially in greenhouse construction. The heat source in greenhouse buildings that operate independently in the heating network comes from heat storage tanks. In the present study, employing thermal field numerical simulations, we investigate the heat flux of a cylindrical heat storage tank with silica aerogel-modified PAN nanofibers as thermal insulation materials. The geometric scale of the tank body, thermal insulation material thickness, and outdoor temperature are optimized to improve thermal insulation. The significant discrepancy in heat flux at different parts of the heat storage tank leads to the extreme heat flux arising at the water–gas interface on the inner and outer walls. It is indicated that the heat flux distribution can be effectively ameliorated by modifying the scale of the tank body to retain the overall water temperature. In particular, effective insulation can merely be acquired when the thermal conductivity of the insulation material is below 3.3 W·m−1·K−1. Eventually, the heat storage tank is optimized to store 1400 L water at 100 °C with a radius of 0.6 m and a thermal insulation thickness of 50 mm at an outdoor temperature of −10 °C, which can maintain excellent thermal insulation for 8 and 24 h at 87.7 and 69.9 °C, respectively.
Chemical Recycling of Silicones—Current State of Play (Building and Construction Focus)
Authors: Wolf Andreas T. , Stammer Andreas
Published: August 2024

As the demand for silicone polymers continues to grow across various industries, the need for effective recycling methods has become increasingly important, because recycling silicone products reduces landfill waste, conserves resources, and uses less energy. Chemical recycling involves the depolymerization of silicone waste into oligomers, which can then be used to produce virgin-grade silicone. While this sector of the recycling industry is still in its infancy—we estimate that 35,000 to 45,000 metric tons of silicone waste will be chemically recycled worldwide in 2024—an increasing number of companies are beginning to explore the implementation of closed-loop systems to recycle silicones. This article examines the technical options and challenges for recycling silicone polymers, the major degradation chemistries available for depolymerizing silicones, and the current industrial reality of chemical recycling of silicones.
Response Surface Methodology to Explore the Influence Mechanism of Fiber Diameter in a New Multi-Needle Electrospinning Spinneret
Authors: Jiang Jianmin , Chen Xiaojie , Wang Han , Ou Weicheng , He Jiayi , Liu Maolin , Lu Zehui , Hu Jingyi , Zheng Gaofeng , Wu Dezhi
Published: August 2024

Multi-needle electrospinning is an efficient method for producing nanofiber membranes. However, fluctuations in the fluid flow rate during the process affect membrane quality and cause instability, an issue that remains unresolved. To address this, a multi-stage flow runner spinneret needs to be developed for large-scale nanofiber membrane production. This paper uses COMSOL finite element software to simulate polymer flow in the spinneret runner. From this, the velocity field distribution and velocity instability coefficient were obtained, providing theoretical guidance for optimal spinneret design. In addition, response surface analysis (RSM) was used to experimentally explore the process parameters, and then residual probability plots were used for reliability verification to evaluate the effect of each process parameter on fiber diameter. These process parameters can guide the controlled production of nanofibers during multi-needle electrospinning.
A Green Approach to Oil Spill Mitigation: New Hybrid Materials for Wastewater Treatment
Authors: Apostol Irina , Dinu Maria Valentina , Anghel Narcis , Spiridon Iuliana
Published: August 2024

This study focuses on the development of adsorptive materials to retain degraded 5w40 motor oil. The materials were prepared using xanthan (XG) and XG esterified with acrylic acid (XGAC) as the polymeric matrix. LignoBoost lignin (LB), LB esterified with oleic (LBOL), stearic acid (LBST) and montmorillonite (CL) were added into XG and XGAC matrices to obtain the adsorbents. Adsorption experiments revealed that XG/CL/LBOL had the highest adsorption capacity at 46.80 g/g, followed by XGAC/CL at 45.73 g/g, and XG/CL at 37.58 g/g. The kinetic studies, employing the pseudo-second-order (PSO) model, indicated rapid sorption rates with a good correlation to experimental data. FTIR spectra analysis have evidenced the physical nature of adsorption process, involving interactions such as hydrogen bonding, van der Waals forces, and π–π interactions. Equilibrium data fitting to the Henry, Freundlich, and Temkin isotherm models showed that the adsorption occurs within materials diverse pore structures, enhancing oil retention. Structural parameters like density, porosity, and surface area were pivotal, with XG/CL/LBOL showing the most favorable properties for high oil adsorption. Additionally, it was found that the adsorption efficiency was influenced by the material’s morphology and the presence of chemical modifications. This comprehensive evaluation highlights the potential of these novel adsorptive materials for environmental remediation applications, offering an efficient and sustainable approach to reducing degraded motor oil pollution.
Comprehensive Review on the Impact of Chemical Composition, Plasma Treatment, and Vacuum Ultraviolet (VUV) Irradiation on the Electrical Properties of Organosilicate Films
Authors: Baklanov Mikhail R. , Gismatulin Andrei A. , Naumov Sergej , Perevalov Timofey V. , Gritsenko Vladimir A. , Vishnevskiy Alexey S. , Rakhimova Tatyana V. , Vorotilov Konstantin A.
Published: August 2024

Organosilicate glass (OSG) films are a critical component in modern electronic devices, with their electrical properties playing a crucial role in device performance. This comprehensive review systematically examines the influence of chemical composition, vacuum ultraviolet (VUV) irradiation, and plasma treatment on the electrical properties of these films. Through an extensive survey of literature and experimental findings, we elucidate the intricate interplay between these factors and the resulting alterations in electrical conductivity, dielectric constant, and breakdown strength of OSG films. Key focus areas include the impact of diverse organic moieties incorporated into the silica matrix, the effects of VUV irradiation on film properties, and the modifications induced by various plasma treatment techniques. Furthermore, the underlying mechanisms governing these phenomena are discussed, shedding light on the complex molecular interactions and structural rearrangements occurring within OSG films under different environmental conditions. It is shown that phonon-assisted electron tunneling between adjacent neutral traps provides a more accurate description of charge transport in OSG low-k materials compared to the previously reported Fowler–Nordheim mechanism. Additionally, the quality of low-k materials significantly influences the behavior of leakage currents. Materials retaining residual porogens or adsorbed water on pore walls show electrical conductivity directly correlated with pore surface area and porosity. Conversely, porogen-free materials, developed by Urbanowicz, exhibit leakage currents that are independent of porosity. This underscores the critical importance of considering internal defects such as oxygen-deficient centers (ODC) or similar entities in understanding the electrical properties of these materials.
Carbon Capture and Storage Subsurface Study for a Natural Gas-Burning Power Plant in Oltenia, Romania
Authors: Suditu Silvian , Dumitrache Liviu , Brănoiu Gheorghe , Prundurel Alina , Ghețiu Iuliana
Published: August 2024

The article presents carbon capture and storage, CCS, as a climate change mitigation method. Many industrial processes, such as the manufacture of cement, the metallurgical industry, and the production of electricity from fossil fuels, produce large CO2 quantities. Carbon capture and storage is a method for these industrial areas to become carbon neutral for the environment. To combat climate change, the EU wants to achieve climate neutrality by 2050, and this goal, along with an intermediate goal of reducing emissions by 55% by 2030, is enshrined in the European Climate Law. The EU has launched various initiatives to achieve these goals, one of which is the ‘Fit for 55’ legislation. The first step that countries wanting to apply these technologies must take is the evaluation of the underground CO2 storage potential. The potential for CO2 storage in the depleted hydrocarbon reservoirs in Oltenia, one of the eight regions of Romania, makes it possible to develop safe long-term storage projects for the neighboring power plants currently producing energy from burning coal or hydrocarbons. The results of dynamic simulations of CO2 storage in one of these geological structures, Bradesti, which hosts depleted hydrocarbon reservoirs, using a numerical simulator are successfully presented for the neighboring Isalnita Power Plant. In this case, the impact on the environment and climate will be minimal and in alignment with the European Union’s long-term objectives. Our study also opens the path for future similar analyses.
“Not my God”–Challenging the Usage of ‘Te Atua’ as Māori Terminology for the God of Christianity
Authors: Fuimaono Eugene
Published: August 2024

The usage of the term ‘Te Atua’ for God within Māori contexts has been largely accepted and unchallenged, yet its appropriateness is questioned due to its colonial origins and misalignment with Māori epistemologies. This paper explores the disqualification of ‘Te Atua’ as a Māori term for God through historical analysis and Māori scholarly perspectives. By applying a Kaupapa Māori research rubric which aligns to four statements—1. The source is related to being Māori; 2. Is connected to Māori philosophy and principles; 3. Takes for granted the validity and legitimacy of Māori, the importance of Māori language and culture; and 4. Is concerned with the struggle for autonomy over our own cultural well-being—this paper argues that the term ‘Te Atua’ fails to meet these criteria. I propose that in accordance with Māori epistemologies, we can discern alternative terms for the blanket term ‘God’ that resonates with whakaaro Māori. This paper is a response to the recent Māori language translations of scripture, advocating for the re-indigenizing of the reo Māori bible to make it relevant to an increasingly non-Christian Māori audience and calls for a reimagining of Christianity that is authentically Māori.
The Apse of the Gothic Cathedral of Tortosa versus Augustine of Hippo’s Civitate Dei
Authors: Lluis-Teruel Cinta , Lluis i Ginovart Josep , Ugalde-Blázquez Iñigo , Gómez-Val Ricardo
Published: August 2024

This research delves into the influence of St. Augustine on the construction of the Gothic cathedral of Tortosa. The canonical cathedral of Tortosa underwent re-establishment in 1155, which was carried out by Bishop Godfrey who was the abbot of Saint Rufus of Avignon and was governed by Beati Augustini rule. The presence of St. Augustine in the Capitular archives with De Civitate Dei (ACTo-20) from the XII century is examined. This, coupled with a spatial analysis of the liturgical space using laser scanning (TLS), serves to validate the historiographical thesis put forth by Wilhelm Worringer, Erwin Panofsky, and Otto von Simson for understanding the construction of the apse of the Gothic cathedral (1346–1441). This methodology establishes a bijection between patristic and Neoplatonic sources and the interpretation of the liturgical space’s dimensions using statistical systems. This approach addresses the construction of the apse through the incorporation of a heptagon, a geometric figure that is absent in Euclid’s Elementa and Ptolemy’s Almagest. In conclusion, it is determined that both the imagery and metrics employed in the design of a radial heptagonal apse, as well as its cross-section, are influenced by both St. Augustine and the metrics of the Neoplatonics, which remain present in the Chapter Archives.
Prefigurative Peace in Philippians
Authors: Smit Peter-Ben
Published: August 2024

Paul refers to peace twice in Phil. 4:7 and 4:9. This paper argues that the peace of God is a prefiguration of the eschatological peace to come in God’s world. It is be proposed that as Philippians is dealing with a social order (i.e., that of life in Christ) that is distinct from the dominant social order of the Roman empire or that of the colony of Philippi, political implications are at the very least a corollary of what Paul is writing to the Christ devotees in this city. The main points that will be argued are that peace is best understood as a key dimension for God’s upcoming new world that is already present “in Christ”. The Philippian community is called upon to stand firm in Christ (Phil. 4:1), which is, due to devotional and ethical practices, to result in the experience of God’s peace or the God of peace. This must be understood as both a present and a future reality. Accordingly, the Philippian community can be seen as prefiguring God’s future world by inhabiting this world now already in their communal life.
Laser Observations of GALILEO Satellites at the CBK PAN Astrogeodynamic Observatory in Borowiec
Authors: Lejba Paweł , Michałek Piotr , Suchodolski Tomasz , Smagło Adrian , Matyszewski Mateusz , Zapaśnik Stanisław
Published: August 2024

The laser station (BORL) owned by the Space Research Centre of the Polish Academy of Sciences and situated at the Astrogeodynamic Observatory in Borowiec near Poznań regularly observes more than 100 different objects in low Earth orbit (LEO) and medium Earth orbit (MEO). The BORL sensor’s laser observation range is from 400 km to 24,500 km. The laser measurements taken by the BORL sensor are utilized to create various products, including the geocentric positions and movements of ground stations, satellite orbits, the components of the Earth’s gravitational field and their changes over time, Earth’s orientation parameters (EOPs), and the validation of the precise Galileo orbits derived using microwave measurements, among others. These products are essential for supporting local and global geodetic and geophysics research related to time. They are crucial for the International Terrestrial Reference Frame (ITRF), which is managed by the International Earth Rotation and Reference Systems Service (IERS). In 2023, the BORL laser station expanded its list of tracked objects to include all satellites of the European satellite navigation system GALILEO, totaling 28 satellites. During that year, the BORL laser station recorded 77 successful passes of GALILEO satellites, covering a total of 21 objects. The measurements taken allowed for the registration of 7419 returns, resulting in 342 normal points. The average RMS for all successful GALILEO observations in 2023 was 13.5 mm.
High-Resolution Rainfall Estimation Using Ensemble Learning Techniques and Multisensor Data Integration
Authors: Putra Maulana , Rosid Mohammad Syamsu , Handoko Djati
Published: August 2024

In Indonesia, the monitoring of rainfall requires an estimation system with a high resolution and wide spatial coverage because of the complexities of the rainfall patterns. This study built a rainfall estimation model for Indonesia through the integration of data from various instruments, namely, rain gauges, weather radars, and weather satellites. An ensemble learning technique, specifically, extreme gradient boosting (XGBoost), was applied to overcome the sparse data due to the limited number of rain gauge points, limited weather radar coverage, and imbalanced rain data. The model includes bias correction of the satellite data to increase the estimation accuracy. In addition, the data from several weather radars installed in Indonesia were also combined. This research handled rainfall estimates in various rain patterns in Indonesia, such as seasonal, equatorial, and local patterns, with a high temporal resolution, close to real time. The validation was carried out at six points, namely, Bandar Lampung, Banjarmasin, Pontianak, Deli Serdang, Gorontalo, and Biak. The research results show good estimation accuracy, with respective values of 0.89, 0.91, 0.89, 0.9, 0.92, and 0.9, and root mean square error (RMSE) values of 2.75 mm/h, 2.57 mm/h, 3.08 mm/h, 2.64 mm/h, 1.85 mm/h, and 2.48 mm/h. Our research highlights the potential of this model to accurately capture diverse rainfall patterns in Indonesia at high spatial and temporal scales.
The Influence of Induced Head Acceleration on Lower-Extremity Biomechanics during a Cutting Task
Authors: Forbes Warren O. , Dufek Janet S.
Published: August 2024

Sports-related concussions are caused by one substantial impact or several smaller-magnitude impacts to the head or body that lead to an acceleration of the head, causing shaking of the brain. Athletes with a history of sports-related concussion demonstrate lower-extremity biomechanics during landing tasks that are conducive to elevated injury risk. However, the effect of head acceleration on lower-extremity biomechanics during landing tasks is unknown. Twenty participants were evenly separated into a vertical hopping group and a lateral hopping group. Participants performed several land-and-cut maneuvers before and after a hopping intervention. Vertical head acceleration (g) was measured via an accelerometer during the hopping interventions. Comparisons in head acceleration during the hopping tasks were made between groups. Additionally, kinematic and kinetic variables were compared pre- and post-intervention within groups as well as post-intervention between groups. The vertical hopping group demonstrated greater vertical head acceleration compared to the lateral hopping group (p = 0.04). Additionally, the vertical hopping group demonstrated greater knee abduction angles during landing post-intervention compared to the lateral hopping group (p < 0.000). Inducing head acceleration via continuous hopping had an influence on lower-extremity biomechanics during a landing task.
HRP-OG: Online Learning with Generative Feature Replay for Hypertension Risk Prediction in a Nonstationary Environment
Authors: Lin Shaofu , Yan Haokang , Zhou Shiwei , Qiao Ziqian , Chen Jianhui
Published: August 2024

Hypertension is a major risk factor for many serious diseases. With the aging population and lifestyle changes, the incidence of hypertension continues to rise, imposing a significant medical cost burden on patients and severely affecting their quality of life. Early intervention can greatly reduce the prevalence of hypertension. Research on hypertension early warning models based on electronic health records (EHRs) is an important and effective method for achieving early hypertension warning. However, limited by the scarcity and imbalance of multivisit records, and the nonstationary characteristics of hypertension features, it is difficult to predict the probability of hypertension prevalence in a patient effectively. Therefore, this study proposes an online hypertension monitoring model (HRP-OG) based on reinforcement learning and generative feature replay. It transforms the hypertension prediction problem into a sequential decision problem, achieving risk prediction of hypertension for patients using multivisit records. Sensors embedded in medical devices and wearables continuously capture real-time physiological data such as blood pressure, heart rate, and activity levels, which are integrated into the EHR. The fit between the samples generated by the generator and the real visit data is evaluated using maximum likelihood estimation, which can reduce the adversarial discrepancy between the feature space of hypertension and incoming incremental data, and the model is updated online based on real-time data using generative feature replay. The incorporation of sensor data ensures that the model adapts dynamically to changes in the condition of patients, facilitating timely interventions. In this study, the publicly available MIMIC-III data are used for validation, and the experimental results demonstrate that compared to existing advanced methods, HRP-OG can effectively improve the accuracy of hypertension risk prediction for few-shot multivisit record in nonstationary environments.
YOLOv8-G: An Improved YOLOv8 Model for Major Disease Detection in Dragon Fruit Stems
Authors: Huang Luobin , Chen Mingxia , Peng Zihao
Published: August 2024

Dragon fruit stem disease significantly affects both the quality and yield of dragon fruit. Therefore, there is an urgent need for an efficient, high-precision intelligent detection method to address the challenge of disease detection. To address the limitations of traditional methods, including slow detection and weak micro-integration capability, this paper proposes an improved YOLOv8-G algorithm. The algorithm reduces computational redundancy by introducing the C2f-Faster module. The loss function was modified to the structured intersection over union (SIoU), and the coordinate attention (CA) and content-aware reorganization feature extraction (CARAFE) modules were incorporated. These enhancements increased the model’s stability and improved its accuracy in recognizing small targets. Experimental results showed that the YOLOv8-G algorithm achieved a mean average precision (mAP) of 83.1% and mAP50:95 of 48.3%, representing improvements of 3.3% and 2.3%, respectively, compared to the original model. The model size and floating point operations per second (FLOPS) were reduced to 4.9 MB and 6.9 G, respectively, indicating reductions of 20% and 14.8%. The improved model achieves higher accuracy in disease detection while maintaining a lighter weight, serving as a valuable reference for researchers in the field of dragon fruit stem disease detection.
Intensity-Product-Based Optical Sensing to Beat the Diffraction Limit in an Interferometer
Authors: Ham Byoung S.
Published: August 2024

The classically defined minimum uncertainty of the optical phase is known as the standard quantum limit or shot-noise limit (SNL), originating in the uncertainty principle of quantum mechanics. Based on the SNL, the phase sensitivity is inversely proportional to K, where K is the number of interfering photons or statistically measured events. Thus, using a high-power laser is advantageous to enhance sensitivity due to the K gain in the signal-to-noise ratio. In a typical interferometer, however, the resolution remains in the diffraction limit of the K = 1 case unless the interfering photons are resolved as in quantum sensing. Here, a projection measurement method in quantum sensing is adapted for classical sensing to achieve an additional K gain in the resolution. To understand the projection measurements, several types of conventional interferometers based on N-wave interference are coherently analyzed as a classical reference and numerically compared with the proposed method. As a result, the Kth-order intensity product applied to the N-wave spectrometer exceeds the diffraction limit in classical sensing and the Heisenberg limit in quantum sensing, where the classical N-slit system inherently satisfies the Heisenberg limit of π/N in resolution.
Surrogate-Assisted Differential Evolution for the Design of Multimode Resonator Topology
Authors: Stanovov Vladimir , Khodenkov Sergey , Gorbunov Sergey , Rozhnov Ivan , Kazakovtsev Lev
Published: August 2024

The microstrip devices based on multimode resonators represent a class of electromagnetic microwave devices, promising use in tropospheric communication, radar, and navigation systems. The design of wideband bandpass filters, diplexers, and multiplexers with required frequency-selective properties, i.e., bandpass filters, is a complex problem, as electrodynamic modeling is a time-consuming and computationally intensive process. Various planar microstrip resonator topologies can be developed, differing in their topology type, and the search for high-quality structures with unique frequency-selective properties is an important research direction. In this study, we propose an approach for performing an automated search for multimode resonators’ conductor topology parameters using a combination of evolutionary computation approach and surrogate modeling. In particular, a variant of differential evolution optimizer is applied, and the model of the target function landscape is built using Gaussian processes. At every iteration of the algorithm, the model is used to search for new high-quality solutions. In addition, a general approach for target function formulation is presented and applied in the proposed approach. The experiments with two microwave filters have demonstrated that the proposed algorithm is capable of solving the problem of tuning two types of topologies, namely three-mode resonators and six-mode resonators, to the required parameters, and the application of surrogated-assisted algorithm has significantly improved overall performance.
A 1 × 8 Optical Splitter Based on Polycarbonate Multicore Polymer Optical Fibers
Authors: Lanziano Liora , Sherf Ilay , Malka Dror
Published: August 2024

Visible light communication (VLC) is becoming more relevant due to the accelerated advancement of optical fibers. Polymer optical fiber (POF) technology appears to be a solution to the growing demand for improved transmission efficiency and high-speed data rates in the visible light range. However, the VLC system requires efficient splitters with low power losses to expand the optical energy capability and boost system performance. To solve this issue, we propose an effective 1 × 8 optical splitter based on multicore polycarbonate (PC) POF technology suitable for functioning in the green-light spectrum at a 530 nm wavelength. The new design is based on replacing 23 air-hole layers with PC layers over the fiber length, while each PC layer length is suitable for the light coupling of the operating wavelength, which allows us to set the right size of each PC layer between the closer PC cores. To achieve the best result, the key geometrical parameters were optimized through RSoft Photonics CAD suite software that utilized the beam propagation method (BPM) and analysis using MATLAB script codes for finding the tolerance ranges that can support device fabrication. The results show that after a light propagation of 2 mm, an equally green light at a 530 nm wavelength is divided into eight channels with very low power losses of 0.18 dB. Additionally, the splitter demonstrates a large bandwidth of 25 nm and stability with a tolerance range of ±8 nm around the operated wavelength, ensuring robust performance even under laser drift conditions. Furthermore, the splitter can function with 80% and above of the input signal power around the operated wavelength, indicating high efficiency. Therefore, the proposed device has a great potential to boost sensing detection applications, such as Raman spectroscopic and bioengineering applications, using the green light.
Research into the Applications of a Multi-Scale Feature Fusion Model in the Recognition of Abnormal Human Behavior
Authors: Li Congcong , Li Yifan , Wang Bin , Zhang Yuting
Published: August 2024

Due to the increasing severity of aging populations in modern society, the accurate and timely identification of, and responses to, sudden abnormal behaviors of the elderly have become an urgent and important issue. In the current research on computer vision-based abnormal behavior recognition, most algorithms have shown poor generalization and recognition abilities in practical applications, as well as issues with recognizing single actions. To address these problems, an MSCS–DenseNet–LSTM model based on a multi-scale attention mechanism is proposed. This model integrates the MSCS (Multi-Scale Convolutional Structure) module into the initial convolutional layer of the DenseNet model to form a multi-scale convolution structure. It introduces the improved Inception X module into the Dense Block to form an Inception Dense structure, and gradually performs feature fusion through each Dense Block module. The CBAM attention mechanism module is added to the dual-layer LSTM to enhance the model’s generalization ability while ensuring the accurate recognition of abnormal actions. Furthermore, to address the issue of single-action abnormal behavior datasets, the RGB image dataset RIDS (RGB image dataset) and the contour image dataset CIDS (contour image dataset) containing various abnormal behaviors were constructed. The experimental results validate that the proposed MSCS–DenseNet–LSTM model achieved an accuracy, sensitivity, and specificity of 98.80%, 98.75%, and 98.82% on the two datasets, and 98.30%, 98.28%, and 98.38%, respectively.
Deep Learning System for User Identification Using Sensors on Doorknobs
Authors: Vegas Jesús , Rao A. Ravishankar , Llamas César
Published: August 2024

Door access control systems are important to protect the security and integrity of physical spaces. Accuracy and speed are important factors that govern their performance. In this paper, we investigate a novel approach to identify users by measuring patterns of their interactions with a doorknob via an embedded accelerometer and gyroscope and by applying deep-learning-based algorithms to these measurements. Our identification results obtained from 47 users show an accuracy of 90.2%. When the sex of the user is used as an input feature, the accuracy is 89.8% in the case of male individuals and 97.0% in the case of female individuals. We study how the accuracy is affected by the sample duration, finding that is its possible to identify users using a sample of 0.5 s with an accuracy of 68.5%. Our results demonstrate the feasibility of using patterns of motor activity to provide access control, thus extending with it the set of alternatives to be considered for behavioral biometrics.
Best Practices for Measuring the Modulation Transfer Function of Video Endoscopes
Authors: Wang Quanzeng , Tran Chinh , Burns Peter , Namazi Nader M.
Published: August 2024

Endoscopes are crucial for assisting in surgery and disease diagnosis, including the early detection of cancer. The effective use of endoscopes relies on their optical performance, which can be characterized with a series of metrics such as resolution, vital for revealing anatomical details. The modulation transfer function (MTF) is a key metric for evaluating endoscope resolution. However, the 2020 version of the ISO 8600-5 standard, while introducing an endoscope MTF measurement method, lacks empirical validation and excludes opto-electronic video endoscopes, the largest family of endoscopes. Measuring the MTF of video endoscopes requires tailored standards that address their unique characteristics. This paper aims to expand the scope of ISO 8600-5:2020 to include video endoscopes, by optimizing the MTF test method and addressing parameters affecting measurement accuracy. We studied the effects of intensity and uniformity of image luminance, chart modulation compensation, linearity of image digital values, auto gain control, image enhancement, image compression and the region of interest dimensions on images of slanted-edge test charts, and thus the MTF based on these images. By analyzing these effects, we provided recommendations for setting and controlling these factors to obtain accurate MTF curves. Our goal is to enhance the standard’s relevance and effectiveness for measuring the MTF of a broader range of endoscopic devices, with potential applications in the MTF measurement of other digital imaging devices.
A Performance Evaluation Method for Long and Steep Uphill Sections of Heavy-Haul Railway Lines
Authors: He Jing , Di Ao , Zhang Changfan , Jia Lin
Published: August 2024

Any system for evaluating the safety service performance of heavy-haul railway lines must effectively reflect the real-time service status of the line. The working conditions of heavy-load lines are complex and diverse, particularly on uphill sections. Existing evaluation systems struggle to accurately reflect the service conditions of long and steep uphill sections bearing heavy loads, posing a significant threat to the safe operation of these lines. To address this problem, we propose a new method for evaluating the safety service performance of long and steep uphill sections of heavy-haul railway lines by establishing a scoring system based on the Analytic Hierarchy Process (AHP). First, damage indicators for heavy-haul lines are categorized into three groups: track geometry status indicators, track structure status indicators, and track traffic status indicators. Using data from existing heavy-haul lines and maintenance experiences, we determine a score deduction standard, classifying lines into four levels based on their safety service quality. Next, we establish a coefficient table for the service performance of long and steep uphill sections after the corresponding scores are deducted. Using data for the length and elevation grade of the actual uphill section, we adjust the deducted scores of the track structure status indicators, enhancing the evaluation system’s accuracy in describing the working conditions. Finally, we verify the stability of the entire system by conducting a sensitivity analysis of the indicator evaluation results using the One-At-a-Time (OAT) method. This method fills a critical gap in the safe operation and maintenance of heavy-haul railways and provides a safety guarantee for the operation of long uphill sections of heavy-haul railways.
Behavioral Efficiency and Residential Electricity Consumption: A Microdata Study
Authors: Weyman-Jones Thomas , Boucinha Júlia Mendonça
Published: August 2024

Sustainability requires that policy makers be able to use market signals to implement energy and environmental policy and that energy consumers respond rationally to these signals. Therefore, it is essential to understand how consumers’ responses to market signals are formed. We propose a new model to measure behavioral efficiency in residential electricity consumption derived from the individual householder indirect utility function. This leads to a pair of simultaneous stochastic demand frontiers for electricity consumption (kWh) and power demand (kVA). Each is a function of power demand (standing) charges and energy demand (running) charges together with the net income after demand charges, the stock of appliances and household characteristics. We estimate the model using two samples of household responses, each of which represents around one percent of the total national population available, and we also pool these samples using pseudo-panel data procedures. We demonstrate how the resulting elasticity and efficiency estimates are related to the theory of behavioral agents from recent developments in behavioral economics. These developments also use the individual indirect utility function to derive propositions based on internality and hyperbolic discounting. The econometric estimates permit the calibration of the individual welfare effects of policy initiatives using carbon tax and price incentives with behavioral agents.
Physicochemical and Nutritional Characterization of Green Banana Flour from Discarded Cavendish Bananas
Authors: Martín Lorenzo Mercedes , Piedra-Buena Díaz Ana , Díaz Romero Carlos , Rodríguez-Rodríguez Elena M. , Lobo M. Gloria
Published: August 2024

Fifteen percent of harvested bananas are discarded daily in the Canary Islands at packing houses because of marketing standards, mainly based on their appearance, or are retired to avoid falls in the market price of bananas. This discarded fruit is an environmental issue, and green banana flour (GBF) is an interesting management alternative for it. In this paper, the artisanal process for obtaining GBF was optimized. The study of physicochemical and nutritional characteristics of this gluten-free flour indicated a high contribution of starch, fiber, phenolics, K, and Mg to dietary intake. Storage of GBF at room temperature (20 ± 5 °C) for ten months slightly increased its moisture and acidity and decreased its starch content, phenolic content, and pH. Some color changes were observed after 5 months, but sensory characteristics were still acceptable after ten months. Green bananas storage prior to GBF elaboration showed they were suitable for obtaining good quality GBF even after 7 weeks at 6 °C, but only 4 weeks at 12 °C. Discriminant analysis classified the GBF correctly according to the cooperative origin, time, and storage temperature of the bananas used in its preparation. These results provide information that could be used in other banana-producing regions for reducing the environmental impact of fruit waste and obtaining GBF using a simple and inexpensive technological process.
Incorporating AI into the Inner Circle of Emotional Intelligence for Sustainability
Authors: Cinar Ayse Basak , Bilodeau Stephane
Published: August 2024

This paper delves into the fusion of artificial intelligence (AI) and emotional intelligence (EQ) by analyzing the frameworks of international sustainability agendas driven by UNESCO, WEF, and UNICEF. It explores the potential of AI integrated with EQ to effectively address the Sustainable Development Goals (SDGs), with a focus on education, healthcare, and environmental sustainability. The integration of EQ into AI use is pivotal in using AI to improve educational outcomes and health services, as emphasized by UNESCO and UNICEF’s significant initiatives. This paper highlights the evolving role of AI in understanding and managing human emotions, particularly in personalizing education and healthcare. It proposes that the ethical use of AI, combined with EQ principles, has the power to transform societal interactions and decision-making processes, leading to a more inclusive, sustainable, and healthier global community. Furthermore, this paper considers the ethical dimensions of AI deployment, guided by UNESCO’s recommendations on AI ethics, which advocate for transparency, accountability, and inclusivity in AI developments. It also examines the World Economic Forum’s insights into AI’s potential to revolutionize learning and healthcare in underserved populations, emphasizing the significance of fair AI advancements. By integrating perspectives from prominent global organizations, this paper offers a strategic approach to combining AI with EQ, enhancing the capacity of AI systems to meaningfully address global challenges. In conclusion, this paper advocates for the establishment of a new Sustainable Development Goal, SDG 18, focused on the ethical integration of AI and EQ across all sectors, ensuring that technology advances the well-being of humanity and global sustainability.
Experimental Study on Heat Release Performance for Sorption Thermal Battery Based on Wave Analysis Method
Authors: Yu Meng , Liu Wei , Lin Yuchen , Gao Neng , Zhang Xuejun , Jiang Long
Published: August 2024

Recent developments in water-based open sorption thermal batteries (STBs) have drawn burgeoning attention due to their advantages of high energy storage density and flexible working modes for space heating. One of the main challenges is how to improve heat release performance, e.g., longer stable heat output and effective output temperature. This paper aims to explore the heat release performance of sorption thermal batteries based on wave analysis methods. Zeolite 13X is used for the experimental investigation in terms of the relative humidity of inlet gas, system air velocity, and the length of the reactor. The results demonstrate that the optimal stable temperature output time of the sorption thermal battery experimental rig is 80 min, and heat release per unit volume reaches 115.6 MJ for the most appropriate reactor length. Thus, the optimal heat release time of the STB under the condition of various relative humidity and air velocities is 152 min and 182 min, respectively, and the corresponding stable heat release could reach 161.1 MJ and 136.5 MJ, respectively. Therefore, the heat release performance of STBs could be adjusted by adopting the wave analysis method, which would facilitate the reactor design and system arrangement.
Macroeconomic Determinants of Circular Economy Investments: An ECM Approach
Authors: Kalaš Branimir , Radovanov Boris , Milenković Nada , Horvat Aleksandra Marcikić
Published: August 2024

The study aims to identify which main macroeconomic determinants affect investment in a circular economy. The main purpose of the investment determinants in a circular economy is to determine how macroeconomic determinants such as real GDP per capita, government expenditure, unemployment, inflation, tax revenue, and interest rate affect an investment in the circular economy in the European Union for the period 2004–2022. Using an error correction model, empirical findings confirmed that government expenditure, inflation, and tax revenue have positive effects on investment in the circular economy in the short run and long run. Conversely, unemployment and interest rate negatively affect investment in the circular economy for both the short term and long term. The contribution of the paper is providing valuable insights into the determinants driving investment in the circular economy, which may help with developing sustainable business policies and practices in the European Union.
The Role of Precision Agriculture Technologies in Enhancing Sustainable Agriculture
Authors: Sanyaolu Mary , Sadowski Arkadiusz
Published: August 2024

Despite the known benefits of precision agriculture, the adoption is challenging due to the cost of investment and the farm sizes. Therefore, profitability is an important aspect to consider. This study aimed to evaluate the net returns, profitability, and investment efficiencies of PA by different economic farm sizes. The study was based on data retrieved from the Farm Accountancy Data Network (FADN) and Eurostat (year 2021). The study examined four countries (Poland, Germany, France, and Romania) under field crop farming using an investment cost of EUR 35,941–EUR 71,883 and a 20% and 15% reduction in the cost of crop protection and fertilizer usage, respectively, without compromising productivity. There is a positive relationship between the adoption of PA and farm returns for larger-scale farms. The result of the profitability and analysis of investment efficiency using Net Present Value (NPV) showed a positive value for economic farm sizes of EUR 100,000 and above. Hence, it is not economically advisable that all farmers use PA technologies with the hope that they will be profitable but with public support (subsidies) more farms will be able to use PA and be profitable. This is also an opportunity to meet the goals of the European Union Green Deal of minimizing emissions that cause climate change.
Some Properties on Normalized Tails of Maclaurin Power Series Expansion of Exponential Function
Authors: Bao Zhi-Hua , Agarwal Ravi Prakash , Qi Feng , Du Wei-Shih
Published: August 2024

In the paper, (1) in view of a general formula for any derivative of the quotient of two differentiable functions, (2) with the aid of a monotonicity rule for the quotient of two power series, (3) in light of the logarithmic convexity of an elementary function involving the exponential function, (4) with the help of an integral representation for the tail of the power series expansion of the exponential function, and (5) on account of Čebyšev’s integral inequality, the authors (i) expand the logarithm of the normalized tail of the power series expansion of the exponential function into a power series whose coefficients are expressed in terms of specific Hessenberg determinants whose elements are quotients of combinatorial numbers, (ii) prove the logarithmic convexity of the normalized tail of the power series expansion of the exponential function, (iii) derive a new determinantal expression of the Bernoulli numbers, deduce a determinantal expression for Howard’s numbers, (iv) confirm the increasing monotonicity of a function related to the logarithm of the normalized tail of the power series expansion of the exponential function, (v) present an inequality among three power series whose coefficients are reciprocals of combinatorial numbers, and (vi) generalize the logarithmic convexity of an extensively applied function involving the exponential function.
Tri-Phase Implementation of an Innovative Fuzzy Logic Approach for Decision-Making
Authors: Tarray Tanveer Ahmad , Khaki Zahid Gulzar , Ganie Zahoor Ahmad , Sultan Adil , Danish Faizan , Albalawi Olayan
Published: August 2024

This paper proposes a novel approach to decision-making based on a three-phase application of a new fuzzy logic model that embraces the principles of symmetry by balancing competing objectives in data collection and analysis. Our study, which employs a three-stage stratified random sample strategy with a randomized response technique, addresses the critical challenges of cost management and volatility reduction. Using the alpha-cut method, our model creates an effective allocation strategy that finds a balance between cost constraints and variance reduction objectives. We use numerical examples from real-world scenarios to demonstrate our approach’s durability and practicality. Our revolutionary technique maintains data quality and cost-effectiveness while offering a game-changing answer to sensitive information acquisition concerns. By combining randomized response techniques and fuzzy logic, this study establishes a new standard for decision-making models that prioritizes both data-gathering precision and privacy preservation, encapsulating the essential principle of symmetry in balancing competing aims.