bluuebunny/crossref_metadata_2025 huggingface dataset:
Does Size Matter? Two Subterranean Biodiversity Hotspots in the Lessini Mountains in the Veneto Prealps in Northern Italy
Authors: Latella Leonardo
Published: December 2023

In the Lessini Mountains, the southernmost prealpine area in the Veneto region, thousands of caves are found, many of which have been extensively studied from the biological point of view. Numerous studies have been carried out on taxonomic and biogeographic aspects over the last hundred years. Two caves, in particular, have been found to be extremely rich in species adapted to life in subterranean environments. These are the Arena Cave in the Monti Lessini Veronesi and the Buso della Rana cave system in the Monti Lessini Vicentini. The two caves have extremely different development: Arena Cave is about 100 meters in length, and the Buso della Rana-Pisatela cave system is more than 37 km in length. Despite this huge difference in size, they both have the highest number of subterranean dwelling species in northern Italy (16 troglobionts and 8 stygobionts in Arena Cave, and 7 troglobionts and 11 stygobionts in the Buso della Rana-Pisatela cave system).
Wi-Gitation: Replica Wi-Fi CSI Dataset for Physical Agitation Activity Recognition
Authors: Sharma Nikita , Klein Brinke Jeroen , Braakman Jansen L. M. A. , Havinga Paul J. M. , Le Duc V.
Published: December 2023

Agitation is a commonly found behavioral condition in persons with advanced dementia. It requires continuous monitoring to gain insights into agitation levels to assist caregivers in delivering adequate care. The available monitoring techniques use cameras and wearables which are distressful and intrusive and are thus often rejected by older adults. To enable continuous monitoring in older adult care, unobtrusive Wi-Fi channel state information (CSI) can be leveraged to monitor physical activities related to agitation. However, to the best of our knowledge, there are no realistic CSI datasets available for facilitating the classification of physical activities demonstrated during agitation scenarios such as disturbed walking, repetitive sitting–getting up, tapping on a surface, hand wringing, rubbing on a surface, flipping objects, and kicking. Therefore, in this paper, we present a public dataset named Wi-Gitation. For Wi-Gitation, the Wi-Fi CSI data were collected with twenty-three healthy participants depicting the aforementioned agitation-related physical activities at two different locations in a one-bedroom apartment with multiple receivers placed at different distances (0.5–8 m) from the participants. The validation results on the Wi-Gitation dataset indicate higher accuracies (F1-Scores ≥0.95) when employing mixed-data analysis, where the training and testing data share the same distribution. Conversely, in scenarios where the training and testing data differ in distribution (i.e., leave-one-out), the accuracies experienced a notable decline (F1-Scores ≤0.21). This dataset can be used for fundamental research on CSI signals and in the evaluation of advanced algorithms developed for tackling domain invariance in CSI-based human activity recognition.
Experimental Tests of the Piston Axial Pump with Constant Pressure and Variable Flow
Authors: Petrović Radovan , Banaszek Andrzej , Andjelković Maja , Qananah Hana R. , Alnagasa Khalefa A.
Published: December 2023

Constant pressure variable flow reciprocating axial pumps (CPAP) are used in various applications, where a constant output pressure is maintained when the flow rate changes. When the hydraulic system is at rated pressure or less, the swash plate has maximum tilt, and the pump delivers maximum flow. The swash plate comes into this position thanks to the action of a reactive piston in which there are two springs. However, when the pressure rises above the nominal pressure value, the piston of the hydraulic pressure transducer (HPT) distributes the fluid under pressure to the hydraulic cylinder (HC), which causes a decrease in the tilt angle of the swash plate and a decrease in flow. The CPAP was selected as a component of the hydraulic system of the aircraft for the experimental tests in this paper. The experimental tests covered the structural and working parameters of the pump and analyzed their performance, efficiency and reliability. Experimental tests of structural and operating parameters of the CPAP were carried out in the Laboratory for Hydraulics and Pneumatics “PPT-Namenska” Trstenik on the hydraulic system, which simulated the real conditions prevailing in the hydraulic system of the aircraft. A system was used for data acquisition and recording of pump characteristics, which were obtained during experimental testing. The results of the measurement and testing of the structural parameters of the CPAP are shown in tabular form, and the experimental tests of static characteristics and dynamic behavior are shown diagrammatically.
Analysis of Hand Function, Upper Limb Disability, and Its Relationship with Peripheral Vascular Alterations in Raynaud’s Phenomenon
Authors: Tapia-Haro Rosa Mª , García-Ríos Mª Carmen , Castro-Sánchez Adelaida Mª , Toledano-Moreno Sonia , Casas-Barragán Antonio , Aguilar-Ferrándiz Mª Encarnación
Published: December 2023

This study aimed to compare vascular involvement, hand functionality, and upper limb disability between Raynaud’s phenomenon participants and controls. Also, we analyzed the relationships between vascular impairment, mobility, and strength with disability in this Raynaud population. We conducted a case–control study with fifty-seven participants. We registered sociodemographic and clinical data; vascular variables (temperature, cold test, blood flow, and oxygen saturation); functional variables (pinch strength, range of motion), and disability (Shortened Disabilities of the Arm, Shoulder and Hand Questionnaire) (Q-DASH). Raynaud participants present more disability in all Q-DASH subscales, lower hands’ temperature pre and post cold test, decreased blood flow on radial artery, decreased ranges of motions at passive extension of index finger, and active flexion and extension of thumb than the healthy controls. The multivariate regression analysis showed that extension of the index finger, lateral pinch strength, and oxygen saturation were significantly associated with disability in RP, almost the 55% of the total variance on the upper limb, 27% at sports/arts, and 42% at work. Our findings suggest that RP has a disabling effect on the upper extremities and a practice of activities in people who suffer it. Also, disability in Raynaud seems to be more related with hand mobility and strength impairment than vascular injury.
Application of a 21-Gene Recurrence Score in a Swiss Single-Center Breast Cancer Population: A Comparative Analysis of Treatment Administration before and after TAILORx
Authors: Chiru Elena Diana , Oseledchyk Anton , Schoetzau Andreas , Kurzeder Christian , Mosimann Raphael , Vetter Marcus , Grašič Kuhar Cvetka
Published: December 2023

In patients with hormone receptor positive, human epidermal receptor 2 negative (HR+/HER2−) negative breast cancer (BC), the TAILORx study showed the benefit of adding chemotherapy (CHT) to endocrine therapy (ET) in a subgroup of patients under 50 years with an intermediate Oncotype DX recurrence score (RS 11–25). The aim of the present study was to determine if the TAILORx findings, including the changes in the RS categories, impacted CHT use in the intermediate RS (11–25) group in daily practice, as well as to identify the main factors for CHT decisions. We conducted a retrospective study on 326 BC patients (59% node-negative), of which 165 had a BC diagnosis before TAILORx (Cohort A) and 161 after TAILORx publication (Cohort B). Changes in the RS categories led to shifts in patient population distribution, thereby leading to a 40% drop in the low RS (from 60% to 20%), which represented a doubling in the intermediate RS (from 30% to 60%) and an increase of 5% in the high RS (from 8–10% to 15%). The overall CHT recommendation and application did not differ significantly between cohort B when compared with A (19% vs. 22%, resp., p = 0.763). In the intermediate RS (11–25), CHT use decreased by 5%, while in the high-risk RS category (>25), there was an increase of 13%. The tumor board recommended CHT for 90% of the patients according to the new RS guidelines in cohort A and for 85% in cohort B. The decision for CHT recommendation was based on age (OR 0.93, 95% CI 0.08–0.97, p = 0.001), nodal stage (OR 4.77, 95% CI 2.03–11.22, p < 0.001), and RS categories (RS 11–25 vs. RS 0–10: OR 0.06 (95% CI 0.02–0.17), p < 0.001; RS > 26 vs. RS 11–25: OR 618.18 95% CI 91.64–4169.91, p < 0.001), but did not depend on the cohort. In conclusion, while the tumor board recommendation for CHT decreased in the intermediate RS category, there was an increase being reported in the high RS category, thus leading to overall minor changes in CHT application. As expected, among the younger women with intermediate RS and unfavorable histopathological factors, CHT use increased.
Patterned Sensory Enhancement, a Music Rehabilitation Therapy for Elderly Patients with Neuromotor Deficit during the COVID-19 Pandemic: A Pilot Study
Authors: Toma Iulia , Dinu Anca , Abu-Awwad Ahmed , Sandesc Mihai-Alexandru , Abu-Awwad Simona-Alina , Nitu Razvan , Popean Mihai
Published: December 2023

(1) Background: The Patterned Sensory Enhancement (PSE) technique refers to a music-based rehabilitation therapy strategy used in neurological pathologies. (2) Methods: This study aims at developing a music-drill protocol for recovery in elderly patients with neuromuscular degenerative pathologies. Each music drill is based on a number of specific music-composition parameters. The conclusions represent suggestions for further enhancing the PSE technique through collaborations between the rehabilitation team and the musicians involved due to the importance of the music stimuli used as a therapy. (3) Results: The music-composition parameters used in this study relate to the existence of music homogeneity factors such as the key signature and rhythm; the importance of the major scale and the tonal system in general; the obvious music suggestions of movement, repetition or absence of movement; the importance of rhythm; the introduction of musical instruments in order to harmonize the music material as much as possible; the connection between PSE music along with patients’ musical taste and the musical recording as a therapy during patient outcare; (4) Conclusions: The therapy efficiency was observed by measurements taken before and after the therapeutic intervention by means of a Takei dynamometer. The present study asserts that for a patient undergoing the PSE technique, the researcher should compose personalized music material adapted to each patient’s peculiarities.
Automated Flight Technology for Integral Path Planning and Trajectory Tracking of the UAV
Authors: Gao Mengjing , Yan Tian , Fu Wenxing , Feng Zhenfei , Guo Hang
Published: December 2023

In view of the problem that path planning and trajectory tracking are rarely solved simultaneously in the current research, which hinders their practical implementation, this paper focuses on enhancing the autonomous flight planning capability of unmanned aerial vehicles (UAVs) by investigating integrated path planning and trajectory tracking technologies. The autonomous flight process is divided into two sub-problems: waypoint designing/optimizing and waypoint tracking. Firstly, an improved DB-RRT* algorithm is proposed for waypoint planning to make the algorithm have higher planning efficiency, better optimization results, and overcome the defects of accidental and low reliability of single RRT* planning results. Secondly, the scheme of “offline design + online flight” is adopted to lead the UAV to fly online according to the waypoints’ instructions by using the sliding mode guidance based on angle constraint with finite-time convergence so that it can fly to the destination autonomously. In order to check the performance of the proposed algorithm, a variety of simulations are conducted to verify the feasibility of the proposed algorithm.
Assessing Risk Acceptability and Tolerability in Italian Tunnels with the Quantum Gu@larp Model
Authors: Guarascio Massimo , Alakbarli Emin , Despabeladera Carlota , Cardinale Vincenzo , Ghasemichamazkoti Azadeh , Darabi Nima
Published: December 2023

Road tunnels are associated with numerous risks including traffic accidents and fires, posing threats to individual or group users. Key risk indicators such as Risk Quantum, Individual Risk, Societal Risk, and Expected Number of Fatalities are instrumental in evaluating the level of risk exposure. These indicators empower Rights-Holders and Duty-Holders to report hazards, prevent disasters, and implement timely remedial measures. A crucial indicator, the Scenario Risk Quantum, has its roots in the forensic evaluation of responsibility in a fatal tunnel accident in the UK since 1949. The Quantum of Risk of each design scenario, reasonably selected among rational and practicable possibilities, has both a deterministic and probabilistic character. The Risk Tolerability and Acceptability criteria are modelled according to risk indicators by selecting the parameters according to ethical principles and societal policy. Scenarios are meticulously identified, described, probabilised and assigned probabilities prior to the quantitative risk analysis. These risk indicators are integral to the risk assessment process. This article delves into the understanding of these indicators within the context of Italian road tunnels, employing the Quantum Gu@larp Model to analyse Risk Acceptability and Tolerability.
The Onset of Parisi’s Complexity in a Mismatched Inference Problem
Authors: Camilli Francesco , Contucci Pierluigi , Mingione Emanuele
Published: December 2023

We show that a statistical mechanics model where both the Sherringhton–Kirkpatrick and Hopfield Hamiltonians appear, which is equivalent to a high-dimensional mismatched inference problem, is described by a replica symmetry-breaking Parisi solution.
Supply Chain Interconnectedness in Times of Crises: A Gravity Model with DiD Analysis of COVID-19 Effects on Central and Eastern European Trade
Authors: Burinskas Arūnas , Cohen Viktorija , Droždz Jolanta
Published: December 2023

This paper explores the impact of COVID-19-induced disruptions on supply chains, specifically focusing on the interconnectedness of supply chains and the transmission effects they cause. The gravity model framework, together with difference-in-differences analysis, is employed to analyze monthly trade patterns among Central and Eastern European (CEE) countries, Western European countries, and other trading partner countries. The model presented accounts for the country’s roles in global value chains (GVCs) by incorporating data related to exports, imports of intermediate and capital goods, and imports of final consumption goods. CEE countries have demonstrated a certain resilience during the COVID-19 pandemic. Yet, they were not immune to adverse consequences due to disrupted supply chains, primarily in the imports of intermediate and capital goods. We find that the countries that suffered from the COVID-19 pandemic the least demonstrated remarkable resilience against disrupted GVCs. The findings of our study enrich the literature on the effects of the COVID-19 pandemic, specifically for the CEE region, by providing a framework for understanding the pandemic’s impact on international trade. The results show that supply shock might be greater than demand shocks on production and trade dynamics. Furthermore, our results suggest that policymakers seek adaptability to changing supply and demand patterns, while enterprises should consider broader diversification both within the region and locally.
A Systematic Review of the Role of Learning Analytics in Supporting Personalized Learning
Authors: Khor Ean Teng , K Mutthulakshmi
Published: December 2023

Personalized learning is becoming more important in today’s diverse classrooms. It is a strategy that tailors instruction to each student’s abilities and interests. The benefits of personalized learning include students’ enhanced motivation and academic success. The average teacher-to-student ratio in classes is 1:15.3, making it challenging for teachers to identify each student’s areas of strength (or weakness). Learning analytics (LA), which has recently revolutionized education by making it possible to gather and analyze vast volumes of student data to enhance the learning process, has the potential to fill the need for personalized learning environments. The convergence of these two fields has, therefore, become an important area for research. The purpose of this study is to conduct a systematic review to understand the ways in which LA can support personalized learning as well as the challenges involved. A total of 40 articles were included in the final review of this study, and the findings demonstrated that LA could support personalized instruction at the individual, group, and structural levels with or without teacher intervention. It can do so by (1) gathering feedback on students’ development, skill level, learning preferences, and emotions; (2) classifying students; (3) building feedback loops with continuously personalized resources; (4) predicting performance; and (5) offering real-time insights and visualizations of classroom dynamics. As revealed in the findings, the prominent challenges of LA in supporting personalized learning were the accuracy of insights, opportunity costs, and concerns of fairness and privacy. The study could serve as the basis for future research on personalizing learning with LA.
SAR Image Ship Target Detection Based on Receptive Field Enhancement Module and Cross-Layer Feature Fusion
Authors: Zheng Haokun , Xue Xiaorong , Yue Run , Liu Cong , Liu Zheyu
Published: December 2023

The interference of natural factors on the sea surface often results in a blurred background in Synthetic Aperture Radar (SAR) ship images, and the detection difficulty is further increased when different types of ships are densely docked together in nearshore scenes. To tackle these hurdles, this paper proposes a target detection model based on YOLOv5s, named YOLO-CLF. Initially, we constructed a Receptive Field Enhancement Module (RFEM) to improve the model’s performance in handling blurred background images. Subsequently, considering the situation of dense multi-size ship images, we designed a Cross-Layer Fusion Feature Pyramid Network (CLF-FPN) to aggregate multi-scale features, thereby enhancing detection accuracy. Finally, we introduce a Normalized Wasserstein Distance (NWD) metric to replace the commonly used Intersection over Union (IoU) metric, aiming to improve the detection capability of small targets. Experimental findings show that the enhanced algorithm attains an Average Precision (AP50) of 98.2% and 90.4% on the SSDD and HRSID datasets, respectively, which is an increase of 1.3% and 2.2% compared to the baseline model YOLOv5s. Simultaneously, it has also achieved a significant performance advantage in comparison to some other models.
Deep Convolutional Neural Network for Indoor Regional Crowd Flow Prediction
Authors: Teng Qiaoshuang , Sun Shangyu , Song Weidong , Bei Jinzhong , Wang Chongchang
Published: December 2023

Crowd flow prediction plays a vital role in modern city management and public safety prewarning. However, the existing approaches related to this topic mostly focus on single sites or road segments, and indoor regional crowd flow prediction has yet to receive sufficient academic attention. Therefore, this paper proposes a novel prediction model, named the spatial–temporal attention-based crowd flow prediction network (STA-CFPNet), to forecast the indoor regional crowd flow volume. The model has four branches of temporal closeness, periodicity, tendency and external factors. Each branch of this model takes a convolutional neural network (CNN) as its principal component, which computes spatial correlations from near to distant areas by stacking multiple CNN layers. By incorporating the output of the four branches into the model’s fusion layer, it is possible to utilize ensemble learning to mine the temporal dependence implicit within the data. In order to improve both the convergence speed and prediction performance of the model, a building block based on spatial–temporal attention mechanisms was designed. Furthermore, a fully convolutional structure was applied to the external factors branch to provide globally shared external factors contexts for the research area. The empirical study demonstrates that STA-CFPNet outperforms other well-known crowd flow prediction methods in processing the experimental datasets.
A YOLOv8-Based Approach for Real-Time Lithium-Ion Battery Electrode Defect Detection with High Accuracy
Authors: Zhou Hongcheng , Yu Yongxing , Wang Kaixin , Hu Yueming
Published: December 2023

Targeting the issue that the traditional target detection method has a high missing rate of minor target defects in the lithium battery electrode defect detection, this paper proposes an improved and optimized battery electrode defect detection model based on YOLOv8. Firstly, the lightweight GhostCony is used to replace the standard convolution, and the GhostC2f module is designed to replace part of the C2f, which reduces model computation and improves feature expression performance. Then, the coordinate attention (CA) module is incorporated into the neck network, amplifying the feature extraction efficiency of the improved model. Finally, the EIoU loss function is employed to swap out the initial YOLOv8 loss function, which improves the regression performance of the network. The empirical findings demonstrate that the enhanced model exhibits increments in crucial performance metrics relative to the original model: the precision rate is elevated by 2.4%, the recall rate by 2.3%, and the mean average precision (mAP) by 1.4%. The enhanced model demonstrates a marked enhancement in the frames per second (FPS) detection rate, significantly outperforming other comparative models. This evidence indicates that the enhanced model aligns well with the requirements of industrial development, demonstrating substantial practical value in industrial applications.
Proving Mutual Authentication Property of Industrial Internet of Things Multi-Factor Authentication Protocol Based on Logic of Events
Authors: Xiao Meihua , Chen Yuqiong , Li Zehuan , Chen Quangang , Xu Ruihan
Published: December 2023

Security protocols are the basis of modern network communication, proving that the security problem of protocols is one of the hot research topics today. The data in industrial IoT are usually transmitted through insecure channels, which brings certain security risks. The Logic of Events is a formal method for proving the security properties of protocols based on event systems. The new theoretical extension is based on the Logic of Events theory, which proposes new event classes Compurte, TimeGap, Construct, and Reconstruct and an axiom AxiomRe and related inference rules for malicious attacks and security privacy issues in emerging protocols, as well as extending the matching descriptions of protocol behaviours in complex cryptographic algorithms and information sharing techniques for applications for the formal analysis of authentication protocols for the Industrial Internet of Things. Finally, formal analysis is carried out using the example of a secure multi-factor authentication protocol for the industrial IoT, which proves the security of the protocol.
Facial Beauty Prediction Combined with Multi-Task Learning of Adaptive Sharing Policy and Attentional Feature Fusion
Authors: Gan Junying , Luo Heng , Xiong Junling , Xie Xiaoshan , Li Huicong , Liu Jianqiang
Published: December 2023

Facial beauty prediction (FBP) is a leading research subject in the field of artificial intelligence (AI), in which computers make facial beauty judgments and predictions similar to those of humans. At present, the methods are mainly based on deep neural networks. However, there still exist some problems such as insufficient label information and overfitting. Multi-task learning uses label information from multiple databases, which increases the utilization of label information and enhances the feature extraction ability of the network. Attentional feature fusion (AFF) combines semantic information and introduces an attention mechanism to reduce the risk of overfitting. In this study, the multi-task learning of an adaptive sharing policy combined with AFF is presented based on the adaptive sharing (AdaShare) network in FBP. First, an adaptive sharing policy is added to multi-task learning with ResNet18 as the backbone network. Second, the AFF is introduced at the short skip connections of the network. The proposed method improves the accuracy of FBP by solving the problems of insufficient label information and overfitting issues. The experimental results based on the large-scale Asia facial beauty database (LSAFBD) and SCUT-FBP5500 databases show that the proposed method outperforms the single-database single-task baseline and can be applied extensively in image classification and other fields.
High-Speed Tracking Controller for Stable Power Control in Discontinuous Charging Systems
Authors: Lim Sang-Kil , Park Jin-Hyun , Jun Hyang-Sig , Hwang Kwang-Bok , Hwangbo Chan , Lee Jung-Hwan
Published: December 2023

The global population is rapidly increasing, and the urban population is on an even faster trend; therefore, the population density is expected to rise. As the number of people in cities grows, the demand for high-rise buildings is anticipated to increase to address the problem of limited land resources. Therefore, efficient energy management using distributed resources has become increasingly important. Elevators are a vital vertical means of transportation in high-rise buildings, and reducing the weight of their components can lead to favorable conditions for energy utilization and increased speed. Therefore, this study presents an elevator system that supplies power inside an elevator car by eliminating the traveling cable and applying a small-capacity energy storage system (ESS). Additionally, we propose a charging algorithm suitable for the proposed system. Generally, batteries have sensitive electrical properties among the distributed energy resources (DERs). Therefore, controlling the stable maintenance of the transient state of the charging current—even when the DC power is unstable or the load changes rapidly in a system requiring fast charging—is crucial. Owing to the nature of the elevator system to be applied, discontinuous charging is frequent, and the active and efficient management of the battery state of charge (SOC) may be challenging. In addition, since it is necessary to be able to charge as much as possible during a short discontinuous charging time, a current control algorithm with a stable and high-speed response is required. The proposed transient high-speed tracking controller (THSTC) is a method for tracking the time of applying an inductor’s excitation voltage without pulse–width modulation (PWM) switching, which is less sensitive to the controller gain values and has fast responsiveness as well as stable transient response characteristics. The proposed method has good dynamic characteristics with a simple control structure without a complex design, which is useful for systems with repeated discontinuous charging. We validate the performance and effectiveness of the proposed controller through simulations and experiments.
Emissions from Light-Duty Vehicles—From Statistics to Emission Regulations and Vehicle Testing in the European Union
Authors: Pacura Wiktor , Szramowiat-Sala Katarzyna , Gołaś Janusz
Published: December 2023

The article offers a comprehensive examination of vehicle emissions, with a specific focus on the European Union’s automotive industry. Its main goal is to provide an in-depth analysis of the factors influencing the emission of microcontaminants from light-duty vehicles and the challenges associated with their removal via exhaust aftertreatment systems. It presents statistical insights into the automotive sector and explores the relationships between vehicle categories, fuel types, and the emission of regulated and nonregulated pollutants, as well as relevant legal regulations such as the European Emission Standard. The article delves into the characteristics of vehicle exhaust, compares exhaust-gas aftertreatment systems, and introduces factors affecting emissions from gasoline engines, including downsizing, fuel composition, and engine operating parameters. It also considers the impact of driving style, start–stop systems, and related factors. Concluding, the article offers an overview of vehicle-testing procedures, including emission tests on dynamometer chassis and real driving emissions. With the growing global vehicle population and international environmental regulations, a focus on solid particles containing microcontaminants is paramount, as they pose significant risks to health and the environment. In summary, this article provides valuable insights into vehicle emissions, significantly contributing to our understanding of this crucial environmental issue.
Experimental and Numerical Study of Novel Vortex Bladeless Wind Turbine with an Economic Feasibility Analysis and Investigation of Environmental Benefits
Authors: Hamdan Hasan , Dol Sharul Sham , Gomaa Abdelrahman Hosny , Tahhan Aghyad Belal Al , Al Ramahi Ahmad , Turkmani Haya Fares , Alkhedher Mohammad , Ajaj Rahaf
Published: December 2023

This study combines experimental and numerical evaluations of Vortex Bladeless Wind Turbines (VBWTs) to understand their potential in renewable energy generation. The methodology employs Two-Way Fluid–Solid Interface (FSI) simulations, alongside real-world data, providing important insights into the turbine’s vibration dynamics and flow interactions during operation. Key findings include identifying optimal vibration frequencies and amplitudes that enhance energy harvesting and a clear advantage in power-generation estimations shown by one of the models used. The study reveals possible applications of VBWT in various settings like airport runways, highways, and buildings, indicating a promising avenue for incorporating such renewable-energy solutions. Discussions on the economic feasibility and environmental benefits of VBWT deployment are also presented, suggesting a need for further research and optimization in this area. A conceptual generator design and business model are introduced as part of a broader discussion on technology integration and energy storage. The research in this study encompasses experimental and numerical analysis, to achieve a broader understanding of the workings of a VBWT, realizing the feasibility of using such systems in lower-wind-speed conditions and upscaling to higher-wind-speed cases.
Experimental Study on Mechanical and Thermal Properties of Backfill Body with Paraffin Added
Authors: Zhang Xiaoyan , Han Ziyi , Liu Lang , Xia Xiang , Liu Qingjiang , Duan Yiran , Wang Xuan
Published: December 2023

Based on phase-change heat storage backfill, paraffin microcapsules were selected as the phase change material and were directly mixed with backfill materials for preparing backfill specimens. The mechanical and thermal properties of specimens with different paraffin percentages and slurry concentrations were tested and analyzed. The results show that compressive strength gradually decreases with an increasing paraffin percentage while it significantly increases with increasing slurry concentration, thermal conductivity decreases with increasing paraffin percentage and specific heat capacity increases with an increasing paraffin percentage and slurry concentration. For a paraffin percentage from 0% to 10%, compressive strength decreases by an average of 22.5%, thermal conductivity decreases by an average of 43.8% and specific heat capacity increases by an average of 8.7% at a phase-change temperature of 30 °C. For a slurry concentration from 68% to 72%, compressive strength increases by an average of 4.12 times, and specific heat capacity increases by an average of 3.5% at a phase-change temperature of 30 °C. The weakening effect of phase-change materials on compressive strength can be effectively improved by the increase of slurry concentration, and the increases of paraffin percentage and slurry concentration can both improve the sensible heat storage capacity of backfill materials.
Integrating Statistical Simulation and Optimization for Redundancy Allocation in Smart Grid Infrastructure
Authors: Alidaee Bahram , Wang Haibo , Huang Jun , Sua Lutfu S.
Published: December 2023

It is a critical issue to allocate redundancy to critical smart grid infrastructure for disaster recovery planning. In this study, a framework to combine statistical prediction methods and optimization models for the optimal redundancy allocation problem is presented. First, statistical simulation methods to identify critical nodes of very large-scale smart grid infrastructure based on the topological features of embedding networks are developed, and then a linear integer programming model based on generalized assignment problem (GAP) for the redundancy allocation of critical nodes in smart grid infrastructure is presented. This paper aims to contribute to the field by employing a general redundancy allocation problem (GRAP) model from high-order nonlinear to linear model transformation. The model is specifically implemented in the context of smart grid infrastructure. The innovative linear integer programming model proposed in this paper capitalizes on the logarithmic multiplication property to reframe the inherently nonlinear resource allocation problem (RAP) into a linearly separable function. This reformulation markedly streamlines the problem, enhancing its suitability for efficient and effective solutions. The findings demonstrate that the combined approach of statistical simulation and optimization effectively addresses the size limitations inherent in a sole optimization approach. Notably, the optimal solutions for redundancy allocation in large grid systems highlight that the cost of redundancy is only a fraction of the economic losses incurred due to weather-related outages.
Public School Choice Options in the United States
Authors: Smith Shelby L. , Dawson-Amoah Margaret , Tong Tong , Pardo Nicolas , Alonso-Morris Elizabeth Ann , Kho Adam
Published: December 2023

Under the structure of compulsory education, students in the United States are required to attend school until at least 16 years of age, which can be done at a variety of educational institutions, both public and private. Amongst public schools, students are each assigned a neighborhood school but also frequently have the option to attend a choice school. While the purpose of neighborhood schools is to provide a guaranteed educational option that accommodates most students, choice schools serve varied purposes that accommodate specific learning styles and societal goals. Four types of publicly funded choice schools are magnet, charter, alternative, and virtual schools. While each was established to serve a specific societal goal, their purposes have shifted over time and have produced varied student outcomes, both academic and non-academic.
Habitat Filtering Covers the Strength of Density Dependence and Functional Density Dependence on Seedling Survival in Cangshan Mountain, Southwest China
Authors: Feng Zhe , Wu Junjie , Sun Jiwen , Yu Xiaoli , Wang Liping , Chen Fengxian , Hu Xiaokang
Published: December 2023

Conspecific negative density dependence (CNDD) is an important mechanism for species coexistence and community dynamics. Phylogenetic negative density dependence (PNDD) and functional negative density dependence (FNDD) are extensions of CNDD, and many studies have shown that they have become powerful and reliable methods for exploring the mechanisms of species coexistence. However, most studies have focused on only one or two of these mechanisms and have not considered whether and how habitat variables affect the detection of these density dependences. To investigate the relative importance of these mechanisms, we set up three 0.09 ha dynamic plots at Cangshan Mountain in southwest China, and used generalized linear mixed models to analyze how the survival of 546 woody plant seedlings was affected by neighborhood density and habitat variables. Our results showed that heterospecific seedling density dependence and functional trait density dependence played key roles in seedling survival. Habitat factors, phylogenetic densities, and adult neighbors had no significant effect on seedling survival in the three plots. However, habitat filtering covered the detection of density dependence and functional trait density dependence. Our study demonstrates that failure to control for habitat variables may obscure the importance of density dependence and functional trait density dependence on seedling survival.
Nitrogen Enrichment Regulates the Changes in Soil Aggregate-Associated Bacterial Community: Evidence from a Typical Temperate Forest
Authors: Lv Wenwen , Liu Yulin , Hai Xuying , Liao Yang , Li Jiwei , Dong Lingbo , Shangguan Zhouping , Deng Lei
Published: December 2023

The nitrogen (N) enrichment induced by atmospheric N deposition affects both soil physicochemical properties and bacterial communities. However, how N enrichment affects soil aggregate-associated bacterial communities remains largely unclear. In this study, we conducted a two-year N addition experiment (four N levels: 0, 5, 10, and 20 g N m−2 year−1, corresponding to normal N, low N, medium N, and high N, respectively) in a Quercus liaotungensis Koidz–dominated forest. The distribution, nutrient content, and bacterial community composition of the soil aggregates were measured under various N enrichment conditions. N enrichment changed the aggregate distribution, increased the content of nutrients in aggregates, and altered the aggregate-associated bacterial community composition. N enrichment reduced the complexity of the bacterial co-occurrence network and degraded the interactions between bacteria compared with those observed under the normal N level. Aggregate-associated bacterial community was determined to be primarily affected by N enrichment level but not by aggregate size. The litter properties are the key factors affecting the composition of bacteria in aggregates. These findings improve our understanding of aggregate-associated bacterial responses to N enrichment and the related influencing factors.
Wood from Field Tests as a Model for Assessing the Suitability of Post-Consumer Wood
Authors: Perdoch Waldemar , Benc Mateusz , Mazela Bartłomiej
Published: December 2023

The circular economy forces societies to take actions aimed at giving post-consumer products a “second life”. As we know, wood is perfect for this. Moreover, reusing wood helps keep carbon in circulation, thus limiting its emissions into the atmosphere. It turns out that extensive research on determining the durability of wood is very useful and valuable for one more reason. Well, they can be used to create a model to determine the usefulness of wood, which has only apparently lost its utility value during many years of exposure to external factors. The research subject was samples of wood impregnated with protection agents and modified, originating from many years of field tests. The aim of the research was to correlate the results of wood durability determined after a period of exposure in open space with the results of determining the potential usefulness of such wood. On this basis, a model for determining the value of post-consumer wood was created. As a main result of post-consumer wood analysis, the high durabilities against C. puteana with mass loss below 3% were noticed for acetylated, furfurylated, and CCA-treated wood. Moreover, high color stabilities (ΔE < 10) were observed for thermowood and furfurylated wood.
Multifiltering Algorithm for Enhancing the Accuracy of Individual Tree Parameter Extraction at Eucalyptus Plantations Using LiDAR Data
Authors: Huang Jinjun , He Wen , Yao Yuefeng
Published: December 2023

Accurately quantifying individual tree parameters is a critical step for assessing carbon sequestration in forest ecosystems. However, it is challenging to gather comprehensive tree point cloud data when using either unmanned aerial vehicle light detection and ranging (UAV-LiDAR) or terrestrial laser scanning (TLS) alone. Moreover, there is still limited research on the effect of point cloud filtering algorithms on the extraction of individual tree parameters from multiplatform LiDAR data. Here, we employed a multifiltering algorithm to increase the accuracy of individual tree parameter (tree height and diameter at breast height (DBH)) extraction with the fusion of TLS and UAV-LiDAR (TLS-UAV-LiDAR) data. The results showed that compared to a single filtering algorithm (improved progressive triangulated irregular network densification, IPTD, or a cloth simulation filter, CSF), the multifiltering algorithm (IPTD + CSF) improves the accuracy of tree height extraction with TLS, UAV-LiDAR, and TLS-UAV-LiDAR data (with R2 improvements from 1% to 7%). IPTD + CSF also enhances the accuracy of DBH extraction with TLS and TLS-UAV-LiDAR. In comparison to single-platform LiDAR (TLS or UAV-LiDAR), TLS-UAV-LiDAR can compensate for the missing crown and stem information, enabling a more detailed depiction of the tree structure. The highest accuracy of individual tree parameter extraction was achieved using the multifiltering algorithm combined with TLS-UAV-LiDAR data. The multifiltering algorithm can facilitate the application of multiplatform LiDAR data and offers an accurate way to quantify individual tree parameters.
Transcriptome Analysis Reveals the Response of Cryptomeria japonica to Feeding Stress of Dendrolimus houi Lajonquière Larvae
Authors: Que Yuwen , Xie Weiwei , Fang Xinyuan , Xu Han , Ye Shuting , Wu Shanqun , Zheng Yican , Lin Xiaochun , Zhang Feiping , Liang Guanghong
Published: December 2023

The Japanese fir, Cryptomeria japonica, is ecologically and commercially vital in China. However, infestations by Dendrolimus houi Lajonquière larvae cause widespread dieback, mimicking mechanical damage effects, with unclear differential impacts and mechanisms. To address this, 6th instar larvae of D. houi were introduced to three-year-old C. japonica seedlings to induce pest infestation, while mechanical damage and non-infested pests were controlled. Then, next-generation sequencing techniques were employed, and transcriptome sequencing was conducted to analyze the distinct damage mechanisms responding to C. japonica. This study revealed 10,412 DEGs between pest infestation and controls and 5535 DEGs comparing pest infestation to mechanical damage. Functional enrichment analysis highlighted the involvement of these DEGs in crucial processes such as photosynthesis, amino acid and nucleotide metabolism, flavonoid biosynthesis, and plant hormone signaling pathways. In particular, 786 unique DEGs were discerned in pest-infested samples. Key enriched pathways, such as pyruvate and propionate metabolism, were pinpointed, with flavonoid biosynthesis potentially closely linked to pest-feeding inductions. These findings provided valuable insights into the molecular responses of C. japonica to D. houi infestation, laying the foundation for future research aimed at developing pest-resistant varieties of Japanese fir.
Biochemical Characterization of Three Heterologous Lactic Acid Bacteria Laccases from Pediococcus, Lactobacillus, and Lactococcus Genus and Their Potential to Degrade Biogenic Amines Using ABTS and Epicatechin as Mediators
Authors: Monroy Isaac , Olmeda Isidoro , Ferrer Sergi , Pardo Isabel
Published: December 2023

In this study, we cloned and characterized three bacterial laccases from strains of the species Pediococcus parvulus, Lacticaseibacillus paracasei, and Lactococcus lactis isolated from wine and cheese and evaluated their biogenic amine degradation abilities in the presence/absence of artificial 2,2′-azinobis(3-ethylbenzothiazoline-6-sulphonic acid (ABTS) or natural (epicatechin) mediator compounds. Although some recombinant bacterial laccases have been characterized and found to be biological tools for degrading biogenic amines with or without the use of mediators, no prior research has investigated the role of natural mediators, like phenolic substrates found in wine and certain vegetable foods, in the degradation of biogenic amines. The three recombinant bacterial laccases exhibited sigmoidal kinetics and had similar molecular mass but varied in k0.5, kcat, and specific activity toward ABTS. They are acidophilic and have an optimal temperature of 28 °C. However, they exhibit low thermal stability at temperatures higher than 37 °C. The three laccases were capable of degrading dopamine without the use of mediators, while the other amines were not degraded. The presence of ABTS enhanced the degradation of dopamine and tyramine, but the addition of epicatechin did not improve their degradation. This study presents a comparison of the laccases’ biogenic amine-degrading efficiency using different mediators. This is the first time such a comparison has been made.
Microbial Electrosynthesis Using 3D Bioprinting of Sporomusa ovata on Copper, Stainless-Steel, and Titanium Cathodes for CO2 Reduction
Authors: Bajracharya Suman , Krige Adolf , Matsakas Leonidas , Rova Ulrika , Christakopoulos Paul
Published: December 2023

Acetate can be produced from carbon dioxide (CO2) and electricity using bacteria at the cathode of microbial electrosynthesis (MES). This process relies on electrolytically-produced hydrogen (H2). However, the low solubility of H2 can limit the process. Using metal cathodes to generate H2 at a high rate can improve MES. Immobilizing bacteria on the metal cathode can further proliferate the H2 availability to the bacteria. In this study, we investigated the performances of 3D bioprinting of Sporomusa ovata on three metal meshes—copper (Cu), stainless steel (SS), and titanium (Ti), when used individually as a cathode in MES. Bacterial cells were immobilized on the metal using a 3D bioprinter with alginate hydrogel ink. The bioprinted Ti mesh exhibited higher acetate production (53 ± 19 g/m2/d) at −0.8 V vs. Ag/AgCl as compared to other metal cathodes. More than 9 g/L of acetate was achieved with bioprinted Ti, and the least amount was obtained with bioprinted Cu. Although all three metals are known for catalyzing H2 evolution, the lower biocompatibility and chemical stability of Cu hampered its performance. Stable and biocompatible Ti supported the bioprinted S. ovata effectively. Bioprinting of synthetic biofilm on H2-evolving metal cathodes can provide high-performing and robust biocathodes for further application of MES.