bluuebunny/crossref_metadata_2025 huggingface dataset:
A Multi-Hazard Approach to Climate Migration: Testing the Intersection of Climate Hazards, Population Change, and Location Desirability from 2000 to 2020
Authors: Hirsch Zachary M. , Porter Jeremy R. , Buresch Jasmina M. , Medgyesi Danielle N. , Shu Evelyn G. , Hauer Matthew E.
Published: September 2024

Climate change intensifies the frequency and severity of extreme weather events, profoundly altering demographic landscapes globally and within the United States. This study investigates their impact on migration patterns, using propensity score matching and LASSO techniques within a larger regression modeling framework. Here, we analyze historical population trends in relation to climate risk and exposure metrics for various hazards. Our findings reveal nuanced patterns of climate-induced population change, including “risky growth” areas where economic opportunities mitigate climate risks, sustaining growth in the face of observed exposure; “tipping point” areas where the amenities are slowly giving way to the disamenity of escalating hazards; and “Climate abandonment” areas experiencing exacerbated out-migration from climate risks, compounded by other out-migration market factors. Even within a single county, these patterns vary significantly, underscoring the importance of localized analyses. Projecting population impacts due to climate risk to 2055, flood risks are projected to impact the largest percentage of areas (82.6%), followed by heatwaves (47.4%), drought (46.6%), wildfires (32.7%), wildfire smoke (21.7%), and tropical cyclone winds (11.1%). The results underscore the importance of understanding hyperlocal patterns of risk and change in order to better forecast future patterns.
Coating of Refractory Surfaces with Fine TiO2 Particles via Gas-Dynamic Cold Spraying
Authors: Aleksieieva Olha , Bozoglu Mustafa , Tretiakov Pavlo , Toporov Andrii , Antonyuk Sergiy
Published: September 2024

Refractory materials are used worldwide in process equipment. However, gaseous and liquid process products penetrate the surface layer and deep into the volume of refractories, destroying rather expensive constructions that are complicated to repair. To address this challenge, there is a need to develop protective coatings for refractory materials that can limit the penetration of working media and extend their operational lifespan. In this work, the application of gas-dynamic cold spraying (CGDS) to produce a coating on the refractory materials using fine titanium dioxide (TiO2) particles is explored. These particles are accelerated within a nitrogen flow, passing through a Laval nozzle, and then sprayed onto a fireclay surface. The mechanisms of particle deposition and layer formation on porous surfaces through experiments and numerical simulations were investigated. The geometry of a typical refractory pore was determined, which was then incorporated into computational fluid dynamics (CFD) simulations to model the cold spraying process of porous substrates. As a result, the influence of the particle size on its velocity and angle of penetration into pores was established. Experimental findings demonstrate the effective closure of pores and the formation of a particle layer on the refractory surface. Furthermore, the nanoindentation tests for the refractory samples showcase capabilities for checking coating thickness for porous materials.
Fatty Imidazolines as a Green Corrosion Inhibitor of Bronze Exposed to Acid Rain
Authors: Vázquez-Aguirre Ian Didiere , Torres-Islas Alvaro , Vázquez-Vélez Edna , Martínez Horacio , del Pozo-Mares Adrián , Cotero-Villegas Ave María
Published: September 2024

Acid rain is one of the primary corrosive agents on bronze exposed to the atmosphere. Bronze naturally forms a layer of oxides on its surface called patina, protecting it from corrosion. However, when exposed to acid rain, this layer dissolves, making it necessary to use a corrosion inhibitor or stabilize the patina. This study investigated fatty imidazolines derived from agro-industrial waste bran as a corrosion inhibitor of SAE-62 bronze in simulated acid rain (pH of 4.16 ± 0.1). Electrochemical impedance spectroscopy (EIS) and potentiodynamic polarization curve (PC) measurements were used to evaluate corrosion inhibition efficiency, which was 90% for an inhibitor concentration of 50 ppm. The EIS measurements showed that the fatty imidazolines formed a protective film that stabilized the patina on the bronze surface to a certain extent by hindering the charge transfer process. SEM–EDS analyzed the morphology and composition of the protective oxide layer. The results were complemented by Raman spectroscopy and XRD analysis, indicating cuprite, tenorite, cassiterite, and covellite in the patina layer formed on the bronze surface. The SEM analysis showed that the protective coating on the bronze surface was homogeneous using a 50-ppm inhibitor concentration. The XRD analysis suggested the presence of an organic complex that stabilizes the corrosion products formed on the bronze surface.
A Narrative Review: Modification of Bio-Based Wood Adhesive for Performance Improvement
Authors: Yu Caizhi , Chen Yi , Li Renjie , Jiang Jun , Wang Xiang
Published: September 2024

Most traditional adhesives applied in the wood industry are synthetic resins obtained from petroleum. However, the production of these resins raises substantial environmental issues because of formaldehyde release, which leads to detrimental impacts on both human health and the environment. In contrast, bio-based adhesives offer an eco-friendly option that is created by renewable biomass resources. These adhesives can effectively overcome the above problems. Hence, it is crucial to pay more attention to bio-based adhesives. However, the inherent characteristics of the raw materials used in the production of bio-based adhesives result in a number of limitations, including weak bond strength, poor water resistance, and susceptibility to mildew, which restrict their further applications. Most researchers have used physical and chemical methods to modify bio-based adhesives in order to improve their overall performance. The defects of bio-based adhesives, including their limited bond strength, inadequate resistance to water, and vulnerability to mildew, are summarized in this paper, and the investigation of potential modification methods on bio-based adhesives is reviewed. Moreover, we encourage the widespread use of bio-based adhesives in various fields to promote sustainable development due to their eco-friendly characters.
Removal of Remazol Red Dyes Using Zeolites-Loaded Nanofibre Coated on Fabric Substrates
Authors: Hami Siddratul Sarah binti Mohd , Affandi Nor Dalila Nor , Indrie Liliana , Harun Ahmad Mukifza
Published: September 2024

Nanofibre-based membranes have shown great potential for removing textile wastewater due to their high porosity and surface area. However, nanofibre membranes exhibit lower dye removal efficiency. Hence, this study aims to improve the dye removal performance of nanofibre membranes by incorporating zeolites. The research involved fabricating composite membranes by electrospinning polyvinyl alcohol (PVA) nanofibres incorporated with zeolites. Mechanical strength was enhanced by placing the PVA/zeolite nanofibre membrane between fusible nonwoven interfacing and woven polyester fabric, followed by heat treatment. Morphological analysis revealed the uniform dispersion of zeolite particles within the PVA nanofibres. EDX analysis confirmed the successful incorporation of zeolites into the fibres. Among all membrane samples, the PZ-0.75 membrane exhibited the highest pure water flux (PWF) with approximately 1358.57 L·m−2·min−1 for distilled water and 499.85 L·m−2·min−1 for batik wastewater. Turbidity of batik wastewater increased proportionally with zeolite concentration, with removal rates of 84.79%, 78.8%, 76.96%, and 74.19% for PZ-0.75, PZ-0.5, PZ-0.25, and PVA membranes, respectively. Furthermore, the UV/Vis spectrophotometer demonstrated that dye removal efficiency increased from 2.22% to 8.89% as the zeolite concentration increased from 0% to 0.75%. In addition, the PZ-0.75 membrane effectively removed RR dye at a concentration of 1 mg/L, with an optimal contact time of approximately 60 min. The adsorption mechanism of the PZ-0.75 membrane aligns with the Freundlich model, with an R2 value of 0.983. Overall, this study demonstrates the efficiency of zeolite in the fabric substrates to improve the filtration and adsorption properties for wastewater treatment, particularly in textile industries.
Electrosprayed Chitosan Nanospheres-Based Films: Evaluating the Effect of Molecular Weight on Physicochemical Properties
Authors: Farias Bruna , Rizzi Francisca , Gerhardt Rafael , Ribeiro Eduardo , Dias Daiane , Cadaval Tito Roberto , Pinto Luiz Antonio
Published: September 2024

This study explores the effect of chitosan molecular weight on the formation of chitosan-based films by electrospraying process. The oxidative pathway was employed in chitosan with 220.1 kDa to obtain samples with 124.5 and 52.7 kDa. Both samples of depolymerized chitosan resulted in spheres within electrosprayed chitosan-based films due to a higher deacetylation degree (~85%). The increase in molecular weight (52.7 to 124.5 kDa) resulted in nanospheres (562 nm) within electrosprayed chitosan-based films, enhancing the surface area-to-volume ratio of the material. The electrospraying process maintained the structural integrity and thermal stability of all chitosan-based films while reducing their crystallinity. These findings highlight the impact of chitosan properties, particularly molecular weight, on the physicochemical characteristics of electrosprayed chitosan-based films. For instance, this work provides insights for the application of electrosprayed chitosan-based films in various fields.
Synergistic Effect of Elliptic Textures and H-DLC Coatings for Enhancing the Tribological Performance of CuAl10Fe5Ni5 Valve Plate Surfaces
Authors: Wang Mengjiao , Zhu Mingbo , Hu Xinzheng , Liu Kun , Fan Xuefeng , Meng Xiangkai , Peng Xudong , Wang Jinqing
Published: September 2024

Axial piston pumps with compact structures and high efficiency are widely used in construction machinery. The efficiency and lifetime strongly depend on the tribological performance of the pump’s valve plate pair. To enhance the tribological performance of the valve plate pair, surface textures, and H-DLC coatings were fabricated to modify the CuAl10Fe5Ni5 surfaces. The influences of elliptic textures of different sizes and textured H-DLC coatings on the surface friction and wear properties of the valve plate surface under oil lubrication were evaluated using a ring-on-disk tribometer. The results reveal that the friction and wear properties of the CuAl10Fe5Ni5 surfaces are significantly enhanced by elliptic textures, and the friction coefficient and wear rate of textured CuAl10Fe5Ni5 with E90 are maximally decreased by 95% and 87%, respectively. Compared with the surface textures and H-DLC coatings, the textured H-DLC coating has the greatest ability to reduce wear and adhesion. The wear rate of the textured H-DLC coating is further reduced by 98%. This improvement can be explained by the synergistic effect of the elliptic textures and H-DLC coatings, which are attributed to the reduced contact area, debris capture, and secondary lubrication of the elliptic textures, and increased surface hardness.
Second-Order Modified Nonstandard Explicit Euler and Explicit Runge–Kutta Methods for n-Dimensional Autonomous Differential Equations
Authors: Alalhareth Fawaz K. , Gupta Madhu , Kojouharov Hristo V. , Roy Souvik
Published: September 2024

Nonstandard finite-difference (NSFD) methods, pioneered by R. E. Mickens, offer accurate and efficient solutions to various differential equation models in science and engineering. NSFD methods avoid numerical instabilities for large time steps, while numerically preserving important properties of exact solutions. However, most NSFD methods are only first-order accurate. This paper introduces two new classes of explicit second-order modified NSFD methods for solving n-dimensional autonomous dynamical systems. These explicit methods extend previous work by incorporating novel denominator functions to ensure both elementary stability and second-order accuracy. This paper also provides a detailed mathematical analysis and validates the methods through numerical simulations on various biological systems.
Room-Temperature Superconductivity in 1D
Authors: Trugenberger Carlo A.
Published: September 2024

We review the theoretical model underpinning the recently reported room-temperature, ambient-pressure superconductivity along line defects on the surface of highly oriented pyrolytic graphite. The main ingredients for this 1D room-temperature superconductivity are pairing by effective strain gauge fields, the formation of an effective Josephson junction array in its Bose metal state on the surface and the suppression of phase slips by dimensional embedding in an extremely well-conducting 3D bulk structure.
Near-Infrared Spectroscopic Study of Secondary Minerals in the Oxidation Zones of Copper-Bearing Deposits
Authors: Wu Shaokun , He Mingyue , Yang Mei , Peng Bijie , Shi Yujia , Sun Kaiyue
Published: September 2024

This study measured the infrared spectra of secondary minerals in the oxidation zones of three types of copper ores: dioptase, malachite, and azurite, and assigned the peak positions of OH stretching vibrations and the origins of OH combination vibrations. Dioptase contains three types of water molecules with different orientations within its ring channels, which exhibit six kinds of OH stretching vibrations in the 3000–3600 cm−1 range; the bond length range is 2.652 to 2.887 Å. Among them, the 3443 cm−1 band shows strong near-infrared activity and combines with Si–O vibrations or OH bending vibrations in the structure, resulting in five combination vibration peaks in the 4000–5000 cm−1 range. Malachite contains two inequivalent hydroxyls in its structure, leading to two OH stretching vibrations in the high-frequency region located at 3314 and 3402 cm−1, respectively. Azurite contains only one type of hydroxyl, and thus only one characteristic OH stretching vibration is present at 3424 cm−1. The OH stretching vibrations of malachite and azurite mainly combine with [CO3]2− vibrations or OH bending vibrations, leading to six and five combination peaks in the OH combination vibration region, respectively. By analyzing the combination of peak positions at 4341 cm−1 in the near-infrared spectrum, the merged OH bending vibration at 921 cm−1 in azurite was discovered. Spectroscopic research on secondary minerals can better provide a basis for ore exploration and geological remote sensing.
Editorial on Special Issue “Artificial Intelligence in Image-Based Screening, Diagnostics, and Clinical Care”
Authors: Rajaraman Sivaramakrishnan , Xue Zhiyun , Antani Sameer
Published: September 2024

In an era of rapid advancements in artificial intelligence (AI) technologies, particularly in medical imaging and natural language processing, strategic efforts to leverage AI’s capabilities in analyzing complex medical data and integrating it into clinical workflows have emerged as a key driver of innovation in healthcare [...]
Hyperglycemia and Venous Thromboembolism
Authors: Panchagnula Neha , Brasher William Philip
Published: September 2024

Patients with diabetes mellitus (DM) have chronically increased blood glucose and multiple physiologic alterations that place them at elevated risk for vascular disease. Traditionally, this vascular risk has mainly referred to chronic atherosclerosis and embolic arterial disease. Retrospective studies have suggested an increased risk of a pulmonary embolism (PE) and deep vein thrombosis (DVT), collectively termed venous thromboembolism (VTE), in patients with DM, but this association has been difficult to demonstrate with comorbidities such as obesity in meta-analysis. Clinical studies have demonstrated worse outcomes for patients with DM who suffer from VTE. In vitro studies show multiple physiologic abnormalities with chronic inflammation, endothelial dysfunction, dysfunction in the coagulation cascade, as well as other changes that drive a vicious cycle of hypercoagulability. Aggressive medical management of DM can improve vascular outcomes, and some anti-hyperglycemic therapies may modify VTE risk as well. Anticoagulation strategies are similar for patients with DM, but with some added considerations, such as high rates of comorbid renal dysfunction. More research is needed to definitively categorize DM as a risk factor for VTE and elucidate specific therapeutic strategies.
Fentanyl and Sudden Death—A Postmortem Perspective for Diagnosing and Predicting Risk
Authors: Strenja Ines , Dadić-Hero Elizabeta , Perković Manuela , Šoša Ivan
Published: September 2024

Sudden, unexpected deaths are extremely difficult for families, especially when the victim is a child. Most sudden deaths occur due to cardiovascular issues, and a smaller number (approximately one-quarter) are attributed to other causes, such as epilepsy. The medicinal and non-medicinal use of the synthetic opioid fentanyl, which can cause breathing problems, is frequently involved in these deaths. It is also being found more often in autopsies of sudden death cases, and the number of overdose deaths from illicit drugs containing fentanyl is increasing. There are cases in which it is mixed with other drugs. A gene known as the KCNH2 gene or human ether-a-go-go-related gene (hERG), involved in the heart’s electrical activity, can be related to abnormal heart rhythms. This gene, along with others, may play a role in sudden deaths related to fentanyl use. In response, we have examined the scientific literature on genetic variations in the KCNH2 gene that can cause sudden death, the impact of fentanyl on this process, and the potential benefits of genetic testing for the victims to offer genetic counseling for their family members.
Medication-Related Osteonecrosis of the Jaw: A Systematic Review of Case Reports and Case Series
Authors: Frutuoso Filipa , Freitas Filipe , Vilares Miguel , Francisco Helena , Marques Duarte , Caramês João , Moreira André
Published: September 2024

Medication-related osteonecrosis of the jaw (MRONJ) is a rare condition, typically seen in patients receiving antiresorptive or antiangiogenic drugs. This study aims to synthesize reports and case series of MRONJ regarding sociodemographic and clinical characteristics and to evaluate the effectiveness of the treatments applied. Following PRISMA guidelines, a search for case reports and case series was carried out in the PubMed-Medline database until March 2024. A total of 88 articles were included in this review, in a total of 151 cases. The key findings reveal that females were the most affected individuals (71% of the cases) with the average age at diagnosis being 66.27 years with a standard deviation of ±13.03. Stage 2 was the most observed stage, in 43% of cases, and zoledronic acid was the most commonly used drug (32% of cases). The oral route was the most common route of administration, in 26% of cases, with an average administration duration of 60.88 months (standard deviation ± 50.92). The mandible was the most commonly affected anatomical location (in 60% of cases). Amoxicillin + clavulanic acid (875 mg + 125 mg) and chlorhexidine (0.12%) were the most used antibiotics and mouthwash, with 16% and 26% of the cases, respectively. Surgical debridement was the most common surgical procedure, in 32% of cases, while the use of an L-PRF membrane was the most prevalent unconventional treatment, in 21% of cases. This study identified a statistically significant relationship between unconventional treatments and the cure of MRONJ (p < 0.001), indicating the need for further research to confirm these results.
Fixed-Time Fault-Tolerant Adaptive Neural Network Control for a Twin-Rotor UAV System with Sensor Faults and Disturbances
Authors: Bacha Aymene , Chelihi Abdelghani , Glida Hossam Eddine , Sentouh Chouki
Published: September 2024

This paper presents a fixed-time fault-tolerant adaptive neural network control scheme for the Twin-Rotor Multi-Input Multi-Output System (TRMS), which is challenging due to its complex, unstable dynamics and helicopter-like behavior with two degrees of freedom (DOFs). The control objective is to stabilize the TRMS in trajectory tracking in the presence of unknown nonlinear dynamics, external disturbances, and sensor faults. The proposed approach employs the backstepping technique combined with adaptive neural network estimators to achieve fixed-time convergence. The unknown nonlinear functions and disturbances of the system are processed via an adaptive radial basis function neural network (RBFNN), while the sensor faults are actively estimated using robust terms. The developed controller is applied to the TRMS using a decentralized structure where each DOF is controlled independently to simplify the control scheme. Moreover, the parameters of the proposed controller are optimized by the gray-wolf optimization algorithm to ensure high flight performance. The system’s stability analysis is proven using a Lyapunov approach, and simulation results demonstrate the effectiveness of the proposed controller.
A Low-Complexity Security Scheme for Drone Communication Based on PUF and LDPC
Authors: Zhang Jiacheng , Gu Peng , Wang Zhen , Zou Jun , Liu Guangzu
Published: September 2024

Due to the limited payload and power of drones, the computational overhead, storage overhead and communication overhead that can be used for secure communication are restricted, making it difficult to apply some complex but fairly secure authentication protocols on drones. In this paper, we propose a low-complexity protocol for storing identity information in a resource-unconstrained device that does not require the UAV to store the information, thereby enhancing the UAV’s resistance to capture. The protocol in this paper mainly consists of quasi-cyclic low-density parity-check (QC-LDPC) codes, physical unclonable functions (PUFs) based on random-access memory (RAM), “XOR” operations, and hash computation. The protocol in this paper is an authentication architecture in which the drone is guided by the ground station to read its identity information, and the drone does not store any identity information in advance. The protocol is divided into two phases: 1. fuzzy authentication of fingerprint PUF and 2. uniqueness authentication accomplished while guiding the recovery of identity PUF. Recovering identity PUF in this paper, QC-LDPC is used as the error control module, and the optimization of bit-flip decoding significantly reduces the probability of decoding failure. After the comparative security analysis and comparative overhead analysis of this paper’s protocol, it can be concluded that this paper’s protocol can withstand common attacks (including attacks attempting to pass authentication, attacks attempting to interfere with authentication, and physical capture attacks), and the storage and communication overhead is small in the case of large time overhead.
Analysis of the Status of Irrigation Management in North Carolina
Authors: Adelabu Anuoluwapo Omolola , Masasi Blessing , Somefun Olabisi Tolulope
Published: September 2024

Farmers in North Carolina are turning to irrigation to reduce the impacts of droughts and rainfall variability on agricultural production. Droughts, rainfall variability, and the increasing demand for food, feed, fiber, and fuel necessitate the urgent need to provide North Carolina farmers with tools to improve irrigation management and maximize water productivity. This is only possible by understanding the current status of irrigated agriculture in the state and investigating its potential weaknesses and opportunities. Thus, the objective of this study was to perform a comprehensive analysis of the current state of irrigation management in North Carolina based on 15-year data from the Irrigation and Water Management Survey by the United States Department of Agriculture–National Agricultural Statistics Service (USDA-NASS). The results indicated a reduction in irrigation acres in the state. Also, most farms in the state have shifted to efficient sprinkler irrigation systems from gravity-fed surface irrigation systems. However, many farms in North Carolina still rely on traditional irrigation scheduling methods, such as examining crop conditions and the feel of soil in deciding when to irrigate. Hence, there are opportunities for enhancing the adoption of advanced technologies like soil moisture sensors and weather data to optimize irrigation schedules for improving water efficiency and crop production. Precision techniques and data-based solutions empower farmers to make informed, real-time decisions, optimizing water use and resource allocation to match the changing environmental conditions. The insights from this study provide valuable information for policymakers, extension services, and farmers to make informed decisions to optimize agricultural productivity and conserve water resources.
Efficient Headline Generation with Hybrid Attention for Long Texts
Authors: Wan Wenjin , Zhang Cong , Huang Lan
Published: September 2024

Headline generation aims to condense key information from an article or a document into a concise one-sentence summary. The Transformer structure is in general effective for such tasks, yet it suffers from a dramatic increase in training time and GPU consumption as the input text length grows. To address this problem, a hybrid attention mechanism is proposed. Both local and global semantic information among words are modeled in a way that significantly improves training efficiency, especially for long text. Effectiveness is not sacrificed; in fact, fluency and semantic coherence of the generated headlines are enhanced. Experimental results on an open benchmark dataset show that, compared to the baseline model’s best performance, the proposed model obtains a 14.7%, 16.7%, 14.4% and 9.1% increase in the F1 values of the ROUGE-1, the ROUGE-2, the ROUGE-L and the ROUGE-WE metrics, respectively. The semantic coherence of the generated text is also improved, as shown by a 2.8% improvement in the BERTScore’s F1 value. These results show that the effectiveness of the proposed headline generation model with the hybrid attention mechanism is also improved. The hybrid attention mechanism could provide references for relevant text generation tasks.
Harmonic State Estimation in Power Systems Using the Jaya Algorithm
Authors: Sepulchro Walace do Nascimento , Encarnação Lucas Frizera
Published: September 2024

The increasing use of nonlinear loads in power systems introduces voltage and current components at non-fundamental frequencies, leading to harmonic distortion, which negatively impacts electrical and electronic devices. A common mitigation strategy involves identifying harmonic sources and installing filters nearby. However, due to the high cost of power quality (PQ) meters, comprehensive harmonic level monitoring across the entire power system is impractical. To address this, various methodologies for Harmonic State Estimation (HSE) have been developed, which estimate distortion levels on unmonitored system buses using data from a minimal set of monitored ones. Many HSE techniques rely on optimization algorithms with numerous tuning parameters, complicating their application. This paper proposes a novel methodology for fundamental frequency power flow and harmonic state estimation using the Jaya algorithm, which is characterized by fewer tuning parameters for easier adjustment. It also introduces a strategy to determine the minimal number of buses that need monitoring to achieve system observability. The methodology is validated on the IEEE-14 and IEEE-30 bus systems, demonstrating its effectiveness. The results of the proposed methodology are compared with those obtained using Evolutionary Strategies (ESs), highlighting its enhanced accuracy and computational efficiency.
AID-YOLO: An Efficient and Lightweight Network Method for Small Target Detector in Aerial Images
Authors: Li Yuwen , Zheng Jiashuo , Li Shaokun , Wang Chunxi , Zhang Zimu , Zhang Xiujian
Published: September 2024

The progress of object detection technology is crucial for obtaining extensive scene information from aerial perspectives based on computer vision. However, aerial image detection presents many challenges, such as large image background sizes, small object sizes, and dense distributions. This research addresses the specific challenges relating to small object detection in aerial images and proposes an improved YOLOv8s-based detector named Aerial Images Detector-YOLO(AID-YOLO). Specifically, this study adopts the General Efficient Layer Aggregation Network (GELAN) from YOLOv9 as a reference and designs a four-branch skip-layer connection and split operation module Re-parameterization-Net with Cross-Stage Partial CSP and Efficient Layer Aggregation Networks (RepNCSPELAN4) to achieve a lightweight network while capturing richer feature information. To fuse multi-scale features and focus more on the target detection regions, a new multi-channel feature extraction module named Convolutional Block Attention Module with Two Convolutions Efficient Layer Aggregation Net-works (C2FCBAM) is designed in the neck part of the network. In addition, to reduce the sensitivity to position bias of small objects, a new function, Normalized Weighted Distance Complete Intersection over Union (NWD-CIoU_Loss) weight adaptive loss function, was designed in this study. We evaluate the proposed AID-YOLO method through ablation experiments and comparisons with other advanced models on the VEDAI (512, 1024) and DOTAv1.0 datasets. The results show that compared to the Yolov8s baseline model, AID-YOLO improves the mAP@0.5 metric by 7.36% on the VEDAI dataset. Simultaneously, the parameters are reduced by 31.7%, achieving a good balance between accuracy and parameter quantity. The Average Precision (AP) for small objects has improved by 8.9% compared to the baseline model (YOLOv8s), making it one of the top performers among all compared models. Furthermore, the FPS metric is also well-suited for real-time detection in aerial image scenarios. The AID-YOLO method also demonstrates excellent performance on infrared images in the VEDAI1024 (IR) dataset, with a 2.9% improvement in the mAP@0.5 metric. We further validate the superior detection and generalization performance of AID-YOLO in multi-modal and multi-task scenarios through comparisons with other methods on different resolution images, SODA-A and the DOTAv1.0 datasets. In summary, the results of this study confirm that the AID-YOLO method significantly improves model detection performance while maintaining a reduced number of parameters, making it applicable to practical engineering tasks in aerial image object detection.
2D and Quasi-2D Halide Perovskite-Based Resistive Switching Memory Systems
Authors: Kim Hyojung , Hyun Daijoon , Hilal Muhammad , Cai Zhicheng , Moon Cheon Woo
Published: September 2024

Resistive switching (RS) memory devices are gaining recognition as data storage devices due to the significant interest in their switching material, Halide perovskite (HP). The electrical characteristics include hysteresis in its current–voltage (I–V) relationship. It can be attributed to the production and migration of defects. This property allows HPs to be used as RS materials in memory devices. However, 3D HPs are vulnerable to moisture and the surrounding environment, making their devices more susceptible to deterioration. The potential of two-dimensional (2D)/quasi-2D HPs for optoelectronic applications has been recognized, making them a viable alternative to address current restrictions. Two-dimensional/quasi-2D HPs are created by including extended organic cations into the ABX3 frameworks. By adjusting the number of HP layers, it is possible to control the optoelectronic properties to achieve specific features for certain applications. This article presents an overview of 2D/quasi-2D HPs, including their structures, binding energies, and charge transport, compared to 3D HPs. Next, we discuss the operational principles, RS modes (bipolar and unipolar switching), in RS memory devices. Finally, there have been notable and recent breakthroughs in developing RS memory systems using 2D/quasi-2D HPs.
Enhanced Coil Design for Inductive Power-Transfer-Based Power Supply in Medium-Voltage Direct Current Sensors
Authors: Jo Seungjin , Kim Dong-Hee , Ahn Jung-Hoon
Published: September 2024

This paper presents an integrated coil design method for inductive power-transfer (IPT) systems. Because a medium-voltage direct current (MVDC) distribution network transmits power at relatively high voltages (typically in the tens of kV), accurate fault diagnosis using high-performance sensors is crucial to improve the safety of MVDC distribution networks. With the increasing power consumption of high-performance sensors, conventional power supplies using optical converters with 5 W-class output characteristics face limitations in achieving the rated output power. Therefore, this paper proposes a safe and reliable power supply method using the principle of IPT to securely maintain the insulation distance between the distribution network and the current sensor-supply line. A 100 W prototype IPT system is investigated, and its feasibility is validated by comparing its performance with conventional optical converters.
An Evaluation of the Autonomic Nervous Activity and Psychomotor Vigilance Level for Smells in the Work Booth
Authors: Yuda Emi , Otani Aoi , Yamada Atsushi , Yoshida Yutaka
Published: September 2024

In this study, we investigated the effects of the smell environment in the work booth on autonomic nervous activity (ANS) and psychomotor vigilance levels (PVLs) using linalool (LNL) and trans-2-nonenal (T2N). The subjects were six healthy males (31 ± 6 years old) and six healthy females (24 ± 5 years old). They sat in the work booth filled with the smells of LNL and T2N for 10 min, and their electrocardiograms (ECGs), skin conductance levels, pulse wave variabilities, skin temperatures, and seat pressure distributions were measured. In addition, the orthostatic load test (OLT) and psychomotor vigilance test (PVT) were performed before and after entering the work booth, and a subjective evaluation of the smell was also performed after the experiment. This paper focused on ECG and PVT data and analyzed changes in heart rate variability indices and PVT scores. Males felt slightly comfortable with the LNL smell and showed promoted sympathetic nerve activity in the OLT after the smell presentation. Females felt slightly uncomfortable with the T2N smell and showed promoted sympathetic nerve activity and a decrease in PVT scores in the OLT after the smell presentation. Gender differences were observed in ANS and PVLs, and it is possible that the comfort of LNL increased sympathetic nervous activity in males, while the uncomfortableness of T2N may have reduced work performance in females.
European Green Deal: Substantiation of the Rational Configuration of the Bioenergy Production System from Organic Waste
Authors: Tryhuba Inna , Tryhuba Anatoliy , Hutsol Taras , Szufa Szymon , Glowacki Szymon , Andrushkiv Oleh , Padyuka Roman , Faichuk Oleksandr , Slavina Nataliia
Published: September 2024

A review of the current state of the theory and practice of bioenergy production from waste allowed us to identify the scientific and applied problem of substantiating the rational configuration of a modular anaerobic bioenergy system, taking into account the volume of organic waste generated in settlements. To solve this problem, this paper develops an approach and an algorithm for matching the configuration of a modular anaerobic bioenergy production system with the amount of organic waste generated in residential areas. Unlike the existing tools, this takes into account the peculiarities of residential areas, which is the basis for accurate forecasting of organic waste generation and, accordingly, determining the configuration of the bioenergy production system. In addition, for each of the scenarios, the anaerobic digestion process is modeled, which allows us to determine the functional indicators that underlie the determination of a rational configuration in terms of cost and environmental performance. Based on the use of the developed tools for the production conditions of the Golosko residential area, Lviv (Ukraine), possible scenarios for the installation of modular anaerobic bioenergy production systems are substantiated. It was found that the greatest annual benefits are obtained from the processing of mixed food and yard waste. The payback period of investments in modular anaerobic bioenergy production systems for given conditions of a residential area largely depends on their configuration and ranges from 3.3 to 8.4 years, which differ from each other by 2.5 times. This indicates that the developed toolkit is of practical value, as it allows the coordination of the rational configuration of modular anaerobic bioenergy production systems with real production conditions. In the future, it is recommended to use the proposed decision support system to model the use of biomass as an energy resource in residential areas, which ensures the determination of the rational configuration of a modular anaerobic bioenergy production system for given conditions.
Simulation of Malfunctions in Home Appliances’ Power Consumption
Authors: Papaioannou Alexios , Dimara Asimina , Papaioannou Christoforos , Papaioannou Ioannis , Krinidis Stelios , Anagnostopoulos Christos-Nikolaos , Korkas Christos , Kosmatopoulos Elias , Ioannidis Dimosthenis , Tzovaras Dimitrios
Published: September 2024

Predicting errors in home appliances is crucial for maintaining the reliability and efficiency of smart homes. However, there is a significant lack of such data on appliance malfunctions that can be used in developing effective anomaly detection models. This research paper presents a novel approach for simulating errors of heterogeneous home appliance power consumption patterns. The proposed model takes normal consumption patterns as input and employs advanced algorithms to produce labeled anomalies, categorizing them based on the severity of malfunctions. One of the main objectives of this research involves developing models that can accurately reproduce anomaly power consumption patterns, highlighting anomalies related to major, minor, and specific malfunctions. The resulting dataset may serve as a valuable resource for training algorithms specifically tailored to detect and diagnose these errors in real-world scenarios. The outcomes of this research contribute significantly to the field of anomaly detection in smart home environments. The simulated datasets facilitate the development of predictive maintenance strategies, allowing for early detection and mitigation of appliance malfunctions. This proactive approach not only improves the reliability and lifespan of home appliances but also enhances energy efficiency, thereby reducing operational costs and environmental impact.
Assessment of the Nutrient Value and In Vitro Rumen Fermentation Characteristics of Garlic Peel, Sweet Potato Vine, and Cotton Straw
Authors: Chen Huiru , Sun Qianqian , Tian Changxin , Tang Xiangfang , Ren Ying , Chen Wenxun
Published: September 2024

This experiment was conducted to determine the nutrient composition of three agricultural by-products, namely garlic peel, sweet potato vine, and cotton straw, calculate their relative feeding value, effective energy value, and other indexes, and comprehensively evaluate their nutrient value by combining with rumen in vitro fermentation technology, with the aim of providing data references for the development and utilization of non-conventional feed resources for ruminants. The results showed that: 1) the dry matter (DM), ash, ether extract (EE), and crude protein (CP) contents of cotton straw were significantly higher than the other two feeds (p < 0.05), while the acid detergent fiber (ADF) and neutral detergent fiber (NDF) contents of garlic peel were highly significantly higher than the others (p < 0.05); 2) the relative feed value (DMI, DDM, TDN, RFV, and RFQ) and effective energy value (GE, DE, ME, NEm, NEg, and NEL) indexes of cotton straw were significantly higher than garlic peel and sweet potato vine (p < 0.01); 3) after 48 h of in vitro fermentation, the dry matter degradation rate (IVDMD) of sweet potato vine was significantly higher than the other two feeds (p < 0.01), and the cumulative gas productions (mL) and estimated gas parameters (a, b, a + b, and c) of sweet potato vine were significantly (p < 0.01) higher than those of garlic peel and cotton straw; 4) the sweet potato vine had lower pH but higher NH3-N compared to garlic peel and cotton straw (p < 0.05). The sweet potato vine had higher propionate, iso-butyrate, butyrate, iso-valerate, and total VFA than the other two roughages, which also had the lowest acetate-to-propionate ratio. Garlic peel produced the lowest acetate, while it produced the highest valerate (p < 0.05). These findings demonstrate that all three by-products have high potential as livestock feed based on their nutritive value parameters. Comparatively, sweet potato vines exhibit higher feeding value due to their relatively moderate NDF content and superior rumen fermentation performance.
Optimization of Bacterial Cellulose Production from Waste Figs by Komagataeibacter xylinus
Authors: Yilmaz Merve , Goksungur Yekta
Published: September 2024

This study aimed to use waste figs as an alternative substrate for bacterial cellulose (BC) production by Komagataeibacter xylinus and optimize the identified process parameters to maximize the concentration of BC. Among the nutrients screened by Plackett–Burman (PB) design, yeast extract was found to be significant in BC production. Response surface methodology was used to investigate the effect of fermentation parameters on BC production. A maximum BC concentration of (8.45 g/L), which is among the highest BC concentrations reported so far, was achieved at the optimum levels of fermentation variables (initial pH 6.05, initial sugar concentration 62.75 g/L, temperature 30 °C). The utilization of response surface methodology (RSM) proved valuable in both optimizing and finding the interactions between process variables during BC production. Scanning electron microscope (SEM) analysis showed a dense structure of BC, characterized by ribbon-like nanofibrils with diameters ranging from 23 to 90 nm while the attenuated total reflection–Fourier transform infrared (ATR-FTIR) spectrum of BC confirmed that the material obtained was cellulose. The X-ray diffraction (XRD) analysis showed that the crystallinity of the BC samples was 70% for BC produced on waste fig medium and 61% for BC produced on Hestrin–Schramm (HS) medium. This is the first detailed study on the production of BC from waste figs, and the findings of this study demonstrated that waste figs can be used as an effective substrate for the production of BC.
Study on Optimal Production Conditions of Fibrinolytic Kinase Derived from the Nereid Worm, Perinereis aibuhitensis Grub
Authors: Song Tuo , Cheng Jun , Diao Xiaozhen , Man Yang , Chen Boyu , Zhang Haixing , Elango Jeevithan , Wu Wenhui
Published: September 2024

The fibrinolytic kinase identified in the nereid worm (Perinereis aibuhitensis Grub) displays exceptional kinase activity, stability, and specificity, suggesting its potential as a promising candidate for the advancement of new thrombolytic drugs. In this study, a process was optimized for the production of fibrinolytic kinase using Escherichia coli, and the effects of factors such as inoculum, pH, OD, temperature, inducer concentration, and time on the protein yield were investigated. The optimum points of key parameters were determined by single-factor experiments, and the initial pH, OD, and time were determined to be significant by PB (Plackett–Burman design) with six factors at two levels of experiments. The response surface experiments highlighted the key roles of initial pH and induced OD values, and the convergence of the model and experimental data confirmed the optimal conditions and reasonable fluctuation intervals, which proved the reliability of the model.
Validation of Optimization Methods for Sensory Characteristics Using Rate-All-That-Apply and Intensity Scales: A Case Study of Apple Juice
Authors: Jeong Yoojin , Kwak Han Sub , Lim Manyoel , Kim Young Jun , Lee Youngseung
Published: September 2024

Preference mapping (PM), which integrates consumer and descriptive analysis (DA) data to identify attributes that drive consumer liking, is widely employed for product optimization. However, a limited group of trained panelists cannot fully represent the diverse consumer population or reliably predict market acceptance. Consequently, numerous studies have explored consumer-based methodologies as potential replacements for DA; however, their efficacy for product optimization remains limited. Therefore, this study was conducted to explore the potential of optimizing products using two consumer-based profiling techniques as alternatives to DA in external preference mapping (EPM). Overall, 8 trained panelists profiled 12 sensory attributes of 7 commercial apple juices, whereas 160 consumers assessed the same attributes using a 5-point rate-all-that-apply (RATA) scale and a 10 cm intensity scale (IS). Danzart’s response surface ideal modeling was employed to identify optimal products using DA, RATA, and IS through barycenter calculations, focusing on three products from the original consumer test located around the group ideal point. Overall, the ideal products of the group and their sensory characteristics were successfully identified using DA, RATA, and IS. Regarding sensory intensities, high concordance was observed between DA and RATA (Rv = 0.92) and between DA and IS (Rv = 0.91). Overall liking and preference scores for products mixed at the optimal ratio for each method showed no significant differences in preference among the ideal products identified using DA, RATA, and IS. This study suggests that both RATA and IS are viable alternatives to DA in EPM for identifying ideal sensory profiles.
Towards Sustainable and Dynamic Modeling Analysis in Korean Pine Nuts: An Online Learning Approach with NIRS
Authors: Li Hongbo , Jiang Dapeng , Dong Wanjing , Cheng Jin , Zhang Xihai
Published: September 2024

Due to its advantages such as speed and noninvasive nature, near-infrared spectroscopy (NIRS) technology has been widely used in detecting the nutritional content of nut food. This study aims to address the problem of offline quantitative analysis models producing unsatisfactory results for different batches of samples due to complex and unquantifiable factors such as storage conditions and origin differences of Korean pine nuts. Based on the offline model, an online learning model was proposed using recursive partial least squares (RPLS) regression with online multiplicative scatter correction (OMSC) preprocessing. This approach enables online updates of the original detection model using a small amount of sample data, thereby improving its generalization ability. The OMSC algorithm reduces the prediction error caused by the inability to perform effective scatter correction on the updated dataset. The uninformative variable elimination (UVE) algorithm appropriately increases the number of selected feature bands during the model updating process to expand the range of potentially relevant features. The final model is iteratively obtained by combining new sample feature data with RPLS. The results show that, after OMSC preprocessing, with the number of features increased to 100, the new online model’s R2 value for the prediction set is 0.8945. The root mean square error of prediction (RMSEP) is 3.5964, significantly outperforming the offline model, which yields values of 0.4525 and 24.6543, respectively. This indicates that the online model has dynamic and sustainable characteristics that closely approximate practical detection, and it provides technical references and methodologies for the design and development of detection systems. It also offers an environmentally friendly tool for rapid on-site analysis for nut food regulatory agencies and production enterprises.