bluuebunny/crossref_metadata_2025 huggingface dataset:
Mechanism and Performance Characterization of Heat Treatment on Laser-Cladded Ni-WC Coatings
Authors: Zhou Mingu , Cui Wenbo , Chen Zexi , Wang Hongkun , Yi Xuemei
Published: December 2024

To enhance the wear resistance of laser-cladded Ni-WC coatings, recrystallization and stress-relief annealing treatments were applied. The effects of different annealing treatments on the friction performance of the coatings were analyzed using XRD, SEM, and a friction wear tester. The results showed that recrystallization annealing refined the grains and transformed the Ni4B3 phase, with the lowest crack rate (10.1%) observed at 800 °C. Stress-relief annealing effectively released residual stress, achieving the lowest crack rate (6.3%) at 500 °C, while promoting the transformation of the Cr7C3 phase and improving coating stability. Furthermore, recrystallization annealing was more suitable for enhancing wear resistance, as the coating treated at 800 °C exhibited a lower friction coefficient (0.46) and the smallest wear volume (0.351 mm3). In contrast, stress-relief annealing was more effective in improving hardness, with the coating treated at 500 °C achieving the highest microhardness (936.54 HV1).
Inventory Model for Instantaneously Deteriorating Items with Multiple Trade Facilities, Stock- and Price-Dependent Demand, and Full Backlogging
Authors: Sarker Rabeya , Uddin Md. Sharif , Helal Md Abu , Khan Aminur Rahman , AlArjani Ali , Attia El-Awady
Published: December 2024

This paper formulates six inventory models for products with instantaneous deterioration, focusing on the impacts of full and partial advance payment structures. The demand function depends on both price and stock levels and accounts for shortages through full backlogging. The primary objective is to determine the optimal payment policy under varying trade facilities, analyzing six distinct payment scenarios commonly employed in business practice. Each model is presented with closed-form solutions and supported by mathematical formulations. For each case, algorithms and mathematical proofs are developed to determine the optimal cycle duration and corresponding unit cost. Numerical examples and 2D graphical representations generated using MATLAB are included to validate the proposed models. Additionally, a sensitivity analysis is conducted to examine the effects of each payment policy and parameter variation, providing key managerial insights into payment planning in inventory management.
Polymorphism in N-(3-Hydroxyphenyl)-3-methoxybenzamide
Authors: Al-Rawe Sumaya K. , Baranov Daniil , Bronowska Agnieszka K. , Cano Celine , Carroll Michael A. , Waddell Paul G.
Published: December 2024

N-(3-hydroxyphenyl)-3-methoxybenzamide was synthesised by amide coupling. After crystallisation, single-crystal X-ray diffraction revealed two distinct polymorphs of the compound: one in the orthorhombic space group Pna21 with one molecule in the asymmetric unit (Z′ = 1) and a second in the triclinic space group P-1 with two molecules in the asymmetric unit (Z′ = 2). A comparison of the structures reveals that the differences between the two can be attributed to conformational variations, disorder, and the dimensionality of the hydrogen bonding networks, with one forming a three-dimensional net and the other forming layers that exhibit approximate p21/b11 layer group symmetry. Molecular dynamics simulations and well-tempered metadynamics-enhanced sampling calculations provide insight into the transition of one polymorph into the other at room temperature. The efficiency of the crystal packing is assessed by a comparison of the densities and melting points of the two structures.
Anthropogenic Effects on Amphibian Diversity and Habitat Similarity in the Yoko Forest Reserve, Democratic Republic of the Congo
Authors: Musubaho Loving , Iyongo Léon , Mukinzi Jean-Claude , Mukiranya Alain , Mutahinga Jasmin , Dufrêne Marc , Bogaert Jan
Published: December 2024

Anthropogenic disturbance of natural environments has negative impacts on biodiversity. Amphibians are especially sensitive to deforestation, and there is a high rate of this phenomenon in the Democratic Republic of the Congo. We studied the effects of this modification of forest ecosystems on the diversity of amphibians in the Yoko Forest Reserve. During twenty-four field sampling campaigns organized over a period of twelve months, amphibians were collected from nocturnal surveys supported by three techniques: visual spotting using a headlamp, systematic searching of habitats and acoustic hearing of vocalizations. Twelve sampling sites were chosen, and three habitats were explored at each site. Of these three habitats, one is the undisturbed habitat (primary forest), and two are disturbed habitats (fallow and field). Amphibian abundance, species richness, diversity, evenness and density were compared between these two types of habitat. A total of 4443 amphibians in 10 families, 17 genera and 33 species were recorded throughout the study area. Abundance, species richness and relative density were significantly higher in non-disturbed habitats than in disturbed habitats. On the other hand, primary forest is less diverse than fallow, but not significantly. It is, however, significantly more diverse than the field. The undisturbed habitat is also characterized by lower evenness than the disturbed habitats, with which it shares low similarities. The species Amnirana albolabris, Phrynobatrachus auritus, Leptopelis notatus, Leptopelis millsoni, Xenopus pygmaeus, Hyperolius platyceps, Leptopelis calcaratus, Leptopelis christyi, Leptopelis ocellatus, Arthroleptis tuberosus, Ptychadena perreti, Amietia nutti, Arthroleptis variabilis, Cardioglossa leucomystax, Phrynobatrachus perpalmatus and Chiromantis rufescens were recognized, in order of importance, as primary forest indicators according to the results of this study. All these differences between the two habitat statuses (undisturbed and disturbed) confirm the negative effects of natural habitat alteration on forest amphibians.
PRAME Staining of Adnexal Lesions and Common Skin Cancer Types: Biomarker with Potential Diagnostic Utility
Authors: Bahmad Hisham F. , Alexis John
Published: December 2024

PRAME (PReferentially expressed Antigen in MElanoma) is a tumor-associated antigen first identified in tumor-reactive T-cell clones derived from a patient with metastatic melanoma. Immunohistochemistry (IHC) for PRAME is useful for diagnostic purposes to support a suspected diagnosis of melanoma. Anecdotally, PRAME has been observed to stain sebaceous units in glands in background skin. We examined the expression of PRAME in adnexal lesions and common skin cancers to determine whether it is of potential diagnostic utility in supporting the differentiation between sebaceous and non-sebaceous lesions. IRB approval from Mount Sinai Medical Center (MSMC) was obtained. This is a single-center retrospective cohort analysis over a ten-year period (1 January 2012, and 31 December 2023). We used the pathological database of skin lesions, including sebaceous, sweat gland, and follicular lesions, in addition to basal cell carcinomas (BCCs) and squamous cell carcinomas (SCCs), from 81 patients who underwent shave/punch biopsies or surgical excisions. We evaluated the IHC staining percentage positivity and intensity for PRAME. Staining intensity was subcategorized into negative, weak, moderate, and strong, whereas expression percentage positivity was subcategorized into 0%, 1–25%, 26–50%, 51–75%, and 76–100%. Most sebaceous versus non-sebaceous lesions exhibited cytoplasmic staining of moderate to strong intensity in >75% of cells. PRAME has a sensitivity and specificity of 100.0% and 86.7%, respectively, to support distinguishing between sebaceous and non-sebaceous adnexal lesions (regardless of whether they are benign or malignant). BCCs and SCCs showed weak to moderate nuclear staining for PRAME in >75% of cells. None of the 13 lesions of hair follicle origin showed any staining. A total of 26 of the 32 lesions of sweat gland origin were negative while 6 (18.75%) showed positive staining. In conclusion, we confirm the potential utility of PRAME for supporting the distinction between sebaceous and non-sebaceous adnexal lesions on one hand, and on the other, distinguishing BCC and SCC that may show nuclear staining from sebaceous carcinoma that shows cytoplasmic staining.
Convolutional Neural Network–Vision Transformer Architecture with Gated Control Mechanism and Multi-Scale Fusion for Enhanced Pulmonary Disease Classification
Authors: Chibuike Okpala , Yang Xiaopeng
Published: December 2024

Background/Objectives: Vision Transformers (ViTs) and convolutional neural networks (CNNs) have demonstrated remarkable performances in image classification, especially in the domain of medical imaging analysis. However, ViTs struggle to capture high-frequency components of images, which are critical in identifying fine-grained patterns, while CNNs have difficulties in capturing long-range dependencies due to their local receptive fields, which makes it difficult to fully capture the spatial relationship across lung regions. Methods: In this paper, we proposed a hybrid architecture that integrates ViTs and CNNs within a modular component block(s) to leverage both local feature extraction and global context capture. In each component block, the CNN is used to extract the local features, which are then passed through the ViT to capture the global dependencies. We implemented a gated attention mechanism that combines the channel-, spatial-, and element-wise attention to selectively emphasize the important features, thereby enhancing overall feature representation. Furthermore, we incorporated a multi-scale fusion module (MSFM) in the proposed framework to fuse the features at different scales for more comprehensive feature representation. Results: Our proposed model achieved an accuracy of 99.50% in the classification of four pulmonary conditions. Conclusions: Through extensive experiments and ablation studies, we demonstrated the effectiveness of our approach in improving the medical image classification performance, while achieving good calibration results. This hybrid approach offers a promising framework for reliable and accurate disease diagnosis in medical imaging.
Trigeminal Pontine Sign: From Imaging to Diseases Beyond Trigeminal Neuralgia
Authors: Zedde Marialuisa , Pascarella Rosario
Published: December 2024

The so-called trigeminal pontine sign has been described as a marker of different diseases, from multiple sclerosis to herpetic infections. First, it has been proposed as linear hyperintensity in the pons on the Magnetic Resonance Imaging (MRI) of patients with multiple sclerosis and trigeminal neuralgia. After these descriptions, it has been reported as incidental findings in the same patients and in patients with HSV or VZV infections. In addition, patients with neuromyelitis optica spectrum disorders (NMOSD) have been more rarely described with this neuroradiological sign. In this review, the main anatomical and neuroradiological issues underlying the trigeminal pontine sign are described, together with the limitations of the published studies from the clinical and neuroimaging point of view. Finally, the association with different diseases is detailed.
Testing the Isotropic Cauchy Hypothesis
Authors: Fahs Jihad , Abou-Faycal Ibrahim , Issa Ibrahim
Published: December 2024

The isotropic Cauchy distribution is a member of the central α-stable family that plays a role in the set of heavy-tailed distributions similar to that of the Gaussian density among finite second-moment laws. Given a sequence of n observations, we are interested in characterizing the performance of Likelihood Ratio Tests, where two hypotheses are plausible for the observed quantities: either isotropic Cauchy or isotropic Gaussian. Under various setups, we show that the probability of error of such detectors is not always exponentially decaying with n, with the leading term in the exponent shown to be logarithmic instead, and we determine the constants in that leading term. Perhaps surprisingly, the optimal Bayesian probabilities of error are found to exhibit different asymptotic behaviors.
Financial Uncertainty and Gold Market Volatility: Evidence from a Generalized Autoregressive Conditional Heteroskedasticity Variant of the Mixed-Data Sampling (GARCH-MIDAS) Approach with Variable Selection
Authors: Chuang O-Chia , Gupta Rangan , Pierdzioch Christian , Shu Buliao
Published: December 2024

We analyze the predictive effect of monthly global, regional, and country-level financial uncertainties on daily gold market volatility using univariate and multivariate GARCH-MIDAS models, with the latter characterized by variable selection. Based on data over the period of July 1992 to May 2020, we highlight the role of the global financial uncertainty factor in accurately forecasting gold price volatility relative to the benchmark GARCH-MIDAS-realized volatility model, with a dominant role of European financial uncertainties, and 36 out of the 42 regional financial market uncertainties. The forecasting performance of the global financial uncertainty factor is as good as an index of global economic conditions, with results based on a combination of these two models depicting evidence of complementary information. Moreover, the GARCH-MIDAS model with global financial uncertainty cannot be outperformed by the multivariate version of the GARCH-MIDAS framework, estimated using the adaptive LASSO, involving the top five developed and developing countries each, chosen based on their ability to explain the movements of overall global financial uncertainty. Our results imply that as financial uncertainties can improve the accuracy of the forecasts of gold returns volatility, it would help investors to design optimal portfolios to counteract financial risks. Also, as gold returns volatility reflects financial uncertainty, accurate forecasts of it would provide information about the future path of economic activity, and assist policy authorities in preventing possible economic slowdowns.
Wheat Value Chains and Vertical Price Transmission in South Africa: A Nonlinear Autoregressive Diagnostic Lag Bound Approach
Authors: Swapi Asemahle , Akande Joseph , Hosu Yiseyon Sunday
Published: December 2024

This study examined the vertical transmission of wheat price among the main value chain, looking at the pricing behaviour of certain role players in the wheat production/supply and the distribution of bread, which is a major staple food consumed in South Africa. A nonlinear autoregressive distributed lag (NARDL) model was used to analyse the yearly time series data for the period of 2000 to 2022. The results of the stationarity test showed that all variables were of order one, I (1). The study used two pairs, namely farmgate price and retail price, and farmgate price and wholesale price, to examine the existence of asymmetry between these prices, with rainfall and temperature as control variables. The results indicate the existence of a positive long-run asymmetry of 35.9% between the farmgate price of wheat and retail price of bread, and 3.49% asymmetry between the farmgate price and wholesale price of wheat. To develop informed policies on food security, this study suggests that the government should enhance regular access to data and sustain its monitoring and communication of food price information across the whole country. For farmers, a policy on price transparency can help them to establish a public platform to share market prices, ensuring that they receive fair prices. This paper also recommends the provision of subsidies for wheat farmers to help the wheat industry, reduce the cost of bread production, and make bread more affordable and accessible for consumers.
Technology and K-12 Environmental Education in Ontario, Canada: Teacher Perceptions and Recommendations
Authors: Millward Andrew A. , Carrier Courtney , Bhagat Nickesh , LeBreton Gregory T. O.
Published: December 2024

This research explores the perspectives of kindergarten through to Grade 12 (K-12) teachers on incorporating information and communication technology (ICT) into the environmental education (EE) curriculum. In the context of the increasing influence of ICT in education, this study examines both the potential enhancements ICT offers to EE and the challenges it poses. Using data from an online survey and an in-person focus group, the investigation addresses the capacity of ICT to promote environmental stewardship and personal growth, alongside concerns regarding technology’s potential to alienate students from nature and the divided opinions among educators regarding optimal technology use. Attention is given to systemic barriers that complicate EE integration and the variability of its implementation in Ontario, Canada, where EE is mandated across K-12 curricula. The findings illuminate educators’ concerns about digital dependencies among their students and the difficulty they face in striking a balance between the use of ICT and non-technical pedagogical approaches when engaging students in environmental lessons. Importantly, study participants identified limited contemporary and timely technological tools to support EE delivery that deemphasize using personal mobile devices (e.g., smartphones and tablets). In response, we recommend three forms of technology (and accompanying lesson ideas) that are affordable, easy to integrate into classrooms, and do not require off-site trips, thereby enhancing accessibility and equity. This study’s implications are aimed at educators, policymakers, and stakeholders seeking to enhance EE delivery within a technologically evolving educational framework and ensure the development of environmentally conscious students.
A Scoping Literature Review on Parent Interactions with Teachers and School Environments at the Middle Level
Authors: Pennington Sarah E. , Tang Judy H. , Divoll Kent , Correll Pamela
Published: December 2024

This scoping literature review explores parent interactions with teachers and school environments at the middle level, particularly how parents and teachers perceive middle school environments and parent–teacher relationships, the strategies that schools use to foster parent–teacher collaboration, and the impacts of these interactions on students. The research team identified 14 peer-reviewed studies from 2015 to 2024 that focused on parent interactions with teachers and school environments at the middle level, including parent and teacher perceptions of school environments and parent–teacher relationships and collaborations. The findings revealed a common disconnect between how parents and teachers view school environments, but also showed that intentional, structured communication can help to bridge these gaps. The review also highlights that research on strategies to enhance parent–teacher partnerships is limited and context-specific. Based on this review of the literature, more research is needed on how home–school relationships benefit diverse middle school communities and how collaboration can support student success, particularly during the critical middle school years.
General Obstacle Avoidance Capability Assessment for Autonomous Vehicles
Authors: Lowe Evan , Guvenc Levent
Published: December 2024

As autonomous vehicle (AV) capabilities expand, it is important to ensure their safety during testing and deployment for public usage. While several testing regulations have been proposed in research, US federal, and even global guidelines for low-speed vehicles in metropolitan settings, regulations for high-speed travel are mainly vacant—this is especially true for regulations relating to AV emergency obstacle avoidance maneuvers (EOAMs). Research in this manuscript introduces a general obstacle avoidance capability assessment (GOACA) for AVs traveling at highway speeds. This GOACA includes test modes including car and bicycle active road objects (AROs) in rural and urban highway settings. These tests were novel in their definitions, methodologies, and execution, especially in the context of AVs driving at highway speeds—critically, this research proposes a test evaluation protocol such that it could serve as a foundation for an official regulation in the future. These GOACA tests included adjacent traffic vehicles which have not been utilized in the prior literature when considering EOAMs within a wholistic AV system context. While the vehicle type will cause simulation results to var, in general, vehicle-to-vehicle (V2V) communication is recommended for usage with AVs at highway speeds for critical safety. This is especially true when considering oncoming traffic and low surface μ conditions.
A Bluetooth-Based Automated Agricultural Machinery Positioning System
Authors: Bian Wentao , Liu Yanyi , Wu Yin
Published: December 2024

With the rapid advancement of technology, precision agriculture, as a modern agricultural production model, has seen significant progress in recent years. Its widespread adoption is gradually transforming traditional farming methods, providing strong support for the modernization of global agriculture. In particular, the application of positioning technology plays a crucial role in precision agriculture. This paper focuses on an automated agricultural machinery positioning system based on Bluetooth technology. The system uses Bluetooth at the 2.4 GHz frequency for transmission, processing Constant Tone Extension (CTE) and Received Signal Strength Indicator (RSSI) signals collected from blind nodes. The Propagator Direct Data Acquisition (PDDA) algorithm is employed to calculate angle information from CTE signals, while the Two-Ray Ground Reflection Model is applied to manage the correlation between RSSI and distance, making it suitable for outdoor environments. These two types of data are fused for positioning, with an optimized objective function converting the positioning task into an optimization problem. An Adaptive Secretary Bird Optimization Algorithm (ASBOA) is introduced to enhance the accuracy and efficiency of the positioning process. In the simulation, anchor and blind nodes are deployed to simulate a real farm environment. Anchor nodes receive CTE and RSSI signals from blind nodes. Considering that the tags mounted on agricultural machinery are set at a fixed height in real scenarios, the simulation also fixes the tags at this height. We then compare the accuracy of five algorithms in both static and dynamic tracking. The final simulation results indicate that ASBOA achieves satisfactory high-precision positioning, both for static points and dynamic tracking, theoretically meeting the needs for continuous positioning and laying a solid foundation for future field trials.
MGAFN-ISA: Multi-Granularity Attention Fusion Network for Implicit Sentiment Analysis
Authors: Huo Yifan , Liu Ming , Zheng Junhong , He Lili
Published: December 2024

Although significant progress has been made in sentiment analysis tasks based on image–text data, existing methods still have limitations in capturing cross-modal correlations and detailed information. To address these issues, we propose a Multi-Granularity Attention Fusion Network for Implicit Sentiment Analysis (MGAFN-ISA). MGAFN-ISA that leverages neural networks and attention mechanisms to effectively reduce noise interference between different modalities and captures distinct, fine-grained visual and textual features. The model includes two key feature extraction modules: a multi-scale attention fusion-based visual feature extractor and a hierarchical attention mechanism-based textual feature extractor, each designed to extract detailed and discriminative visual and textual representations. Additionally, we introduce an image translator engine to produce accurate and detailed image descriptions, further narrowing the semantic gap between the visual and textual modalities. A bidirectional cross-attention mechanism is also incorporated to utilize correlations between fine-grained local regions across modalities, extracting complementary information from heterogeneous visual and textual data. Finally, we designed an adaptive multimodal classification module that dynamically adjusts the contribution of each modality through an adaptive gating mechanism. Extensive experimental results demonstrate that MGAFN-ISA achieves a significant performance improvement over nine state-of-the-art methods across multiple public datasets, validating the effectiveness and advancement of our proposed approach.
Formation and Evolution of Multi-Genetic Overpressure and Its Effect on Hydrocarbon Accumulation in the Dabei Area, Kuqa Depression, Tarim Basin, China
Authors: Wen Chenxi , Wang Zhenliang
Published: December 2024

The Kuqa Foreland Basin is an important hydrocarbon-producing basin in western China. The Dabei area is an important zone for hydrocarbon accumulation. High fluid overpressures in the Lower Cretaceous Bashijiqike Formation are related to multi-genetic processes. However, the formation and evolution of pressure remain unclear, hindering the further development of oil and gas migration and accumulation. In this study, the overpressure distribution is described based on a drill stem test and mud density data. The formation and quantification of multi-genetic overpressure were evaluated based on well-logging data and basin simulation technology (Ansys Workbench). The coupling evolution of multi-genetic overpressure was examined based on the basin simulation technique. Finally, the influence of overpressure on hydrocarbon accumulation was explored. The results showed that the residual pressure of the Bashijiqike Formation in the Dabei area ranged from 40 to 60 MPa. The main causes of pressure in the Bashijiqike Formation in the Dabei area were disequilibrium compaction overpressure (2–6 MPa, contribution of 8–15%), tectonic compression overpressure (10 MPa, contribution of 30%), and fracture transfer overpressure (15–20 MPa, contribution of 8–15%). With respect to the evolution process of multiple pressures in the Bashijiqike Formation in the Dabei region, at 0–23.3 Ma, the overpressure due to disequilibrium compaction was <10 MPa and increased slowly to 18 MPa at 2.48–23.3 Ma. At 2.48 Ma, the tectonic compression was enhanced, and the residual pressure reached ~50 MPa. At 1.75–2.48 Ma, fracture activity was enhanced, leading to the generation of fracture transfer overpressure. Under these conditions, the residual pressure exceeded 60 MPa. Finally, the Bashijiqike Formation in the Dabei area is a favorable area for vertical and lateral migration of oil and gas. This study is of great significance to the formation and evolution of multi-origin overpressure in the same basin type and its influence on oil and gas accumulation.
Virtual Power Plant Reactive Power Voltage Support Strategy Based on Deep Reinforcement Learning
Authors: Lou Qihe , Li Yanbin , Chen Xi , Wang Dengzheng , Ju Yuntao , Han Liu
Published: December 2024

After the large-scale access of distributed power sources to the distribution network, significant high/low voltage problems have emerged. Using a virtual power plant to provide reactive power voltage regulation as an ancillary service effectively addresses voltage issues. However, since a third party manages the virtual power plant and contains both discrete and continuous regulation devices internally, there is a need to consider privacy protection. To address this, a training method that requires minimal boundary information and reward–penalty information for interaction between discrete and continuous action agents is proposed. This method uses distributed two-layer multi-agent deep reinforcement learning for the virtual power plant’s reactive power voltage support strategy. By utilizing actual engineering data and comparing it with the “centralized training” framework algorithm, this study proves the effectiveness of the deep reinforcement learning training method and reactive power voltage control strategy. It demonstrates advantages such as protecting the privacy of the virtual power plant and low training difficulty.
Resilient Operation Strategies for Integrated Power-Gas Systems
Authors: Faridpak Behdad , Musilek Petr
Published: December 2024

This article presents a novel methodology for analyzing the resilience of an active distribution system (ADS) integrated with an urban gas network (UGN). It demonstrates that the secure adoption of gas turbines with optimal capacity and allocation can enhance the resilience of the ADS during high-impact, low-probability (HILP) events. A two-level tri-layer resilience problem is formulated to minimize load shedding as the resilience index during post-event outages. The challenge of unpredictability is addressed by an adaptive distributionally robust optimization strategy based on multi-cut Benders decomposition. The uncertainties of HILP events are modeled by different moment-based probability distributions. In this regard, considering the nature of each uncertain variable, a different probabilistic method is utilized. For instance, to account for the influence of power generated from renewable energy sources on the decision-making process, a diurnal version of the long-term short-term memory network is developed to forecast day-ahead weather. In comparison with standard LSTM, the proposed approach reduces the mean absolute error and root mean squared error by approximately 47% and 71% for wind speed, as well as 76% and 77% for solar irradiance network. Finally, the optimal operating framework for improving power grid resilience is validated using the IEEE 33-bus ADS and 7-node UGN.
Dynamic Capacity Sharing for Cyber–Physical Resilience of EV Charging
Authors: Gümrükcü Erdem , Joglekar Charukeshi , Muriithi Grace , Arsalan Ali , Aboulebdeh Ahmed , Papari Behnaz , Zehir Alparslan , Ponci Ferdinanda , Monti Antonello
Published: December 2024

Electric vehicle (EV) charging infrastructure hardware–software solutions and communication protocols have inherent vulnerabilities against cyberattacks. Due to the wide range of back doors and infiltration possibilities, there is an important need for solutions that can maintain critical service continuity during incidents. This study proposes a dynamic capacity sharing method for effective use of the constrained grid capacity between neighboring charging clusters in distribution grids when the communication link between the clusters’ operators and the grid operator is disrupted due to hardware faults or cyberattacks. The performance of the developed solution is thoroughly investigated in a Denial-of-Service cyberattack scenario that may take place at different times of the day in realistic scenarios involving residential demand and stochastic EV charging behavior. The analyses validated the effectiveness of the proposed method in improving the deteriorated service level per charging cluster and better utilization of an overall constrained capacity.
A Method Coupling NDT and VGICP for Registering UAV-LiDAR and LiDAR-SLAM Point Clouds in Plantation Forest Plots
Authors: Wang Fan , Wang Jiawei , Wu Yun , Xue Zhijie , Tan Xin , Yang Yueyuan , Lin Simei
Published: December 2024

The combination of UAV-LiDAR and LiDAR-SLAM (Simultaneous Localization and Mapping) technology can overcome the scanning limitations of different platforms and obtain comprehensive 3D structural information of forest stands. To address the challenges of the traditional registration algorithms, such as high initial value requirements and susceptibility to local optima, in this paper, we propose a high-precision, robust, NDT-VGICP registration method that integrates voxel features to register UAV-LiDAR and LiDAR-SLAM point clouds at the forest stand scale. First, the point clouds are voxelized, and their normal vectors and normal distribution models are computed, then the initial transformation matrix is quickly estimated based on the point pair distribution characteristics to achieve preliminary alignment. Second, high-dimensional feature weighting is introduced, and the iterative closest point (ICP) algorithm is used to optimize the distance between the matching point pairs, adjusting the transformation matrix to reduce the registration errors iteratively. Finally, the algorithm converges when the iterative conditions are met, yielding an optimal transformation matrix and achieving precise point cloud registration. The results show that the algorithm performs well in Chinese fir forest stands of different age groups (average RMSE—horizontal: 4.27 cm; vertical: 3.86 cm) and achieves high accuracy in single-tree crown vertex detection and tree height estimation (average F-score: 0.90; R2 for tree height estimation: 0.88). This study demonstrates that the NDT-VGICP algorithm can effectively fuse and collaboratively apply multi-platform LiDAR data, providing a methodological reference for accurately quantifying individual tree parameters and efficiently monitoring 3D forest stand structures.
Analysis of Vegetation Changes and Driving Factors on the Qinghai-Tibet Plateau from 2000 to 2022
Authors: Ren Xiaoqi , Hou Peng , Ma Yutiao , Ma Rongfei , Wang Jiahao , Xie Le
Published: December 2024

This study assesses the impact of climate change and human activities on vegetation dynamics (kNDVI) on the Qinghai-Tibet Plateau (QTP) between 2000 and 2022, considering both lag and cumulative effects. Given the QTP’s high sensitivity to climate change and human activities, it is imperative to understand their effects on vegetation for the sustainable development of regional and national terrestrial ecosystems. Using MOD13Q1 NDVI and climate and human activity data, we applied methods such as Sen-MK, lag and cumulative effect analysis, improved residual analysis, and geographical detector analysis. The outcomes were as follows. (1) The vegetation kNDVI on the QTP showed an overall fluctuating growth trend between 2000 and 2022; improved regions were more significant than degraded regions, with improved regions primarily distributed in humid and semi-humid areas with favorable climate conditions, and degraded regions primarily in arid and semi-arid areas; this implies that climate conditions have a significant impact on vegetation changes on the QTP. (2) The analysis of lag and cumulative effects revealed that temperature and precipitation have a substantial cumulative effect on vegetation kNDVI on the QTP. The vegetation kNDVI showed a lag effect of 0 months and a cumulative effect of 1 month for temperature, and a lag effect of 0 months and a cumulative effect of 2 months for precipitation, respectively. (3) Improved residual analysis based on lag and cumulative effects revealed that human activities positively contributed 66% to the changes in vegetation kNDVI on the QTP, suggesting a notable positive impact of human activities. Geographical detector analysis indicated that, among different human activity factors affecting vegetation kNDVI changes, the explanatory power in 2005 and 2015 ranked as X3 (livestock density) > X1 (population density) > X2 (per capita GDP) > X4 (artificial afforestation density) > X5 (land use type), and in 2020, as X3 > X4 > X1 > X5 > X2. The explanatory power of afforestation density and land use type has relatively increased, indicating that recent efforts in ecological protection and restoration on the QTP, including developing artificial forest areas and afforestation programs, have considerably contributed to vegetation greening.
Using Random Forest Regression to Model the Spatial Distribution of Concentrations of Selected Metals in Groundwater in Forested Areas of the Wielkopolska National Park, Poland
Authors: Fiedler Michał
Published: December 2024

Monitoring groundwater pollution is an important issue in terms of analyzing threats to protected, environmentally valuable areas. The topographical and environmental characteristics of a given area are often mentioned among the factors affecting the dynamics and chemistry of groundwater. In this study, the random forest regression (RFR) model was used to determine the spatial distribution of selected metals, such as aluminum, calcium, iron, potassium, magnesium, manganese, sodium, and zinc. In the role of indicators describing terrain variability, derivatives of the digital elevation model (DEM) were employed, with a spatial resolution of 5 m, describing the topography of the terrain on a local scale, such as, among others, slopes, the aspect and curvatures of slopes, the topographic position index, and the SAGA wetness index, as well as generalized values determined for each sampling point of the areas contributing their runoff. In addition, environmental parameters were taken into consideration: forest habitat types, the structure of soil cover, and the seasons when samples were collected. This study used samples collected from 15 wells located in forested areas of the Wielkopolska National Park on seven dates. The results obtained show that random forest can be used with very good results to model the spatial variability of the concentrations of aluminum, potassium, magnesium, manganese, and sodium in groundwater. However, in the case of calcium and zinc, no correlations were found between the adopted indicators describing the spatial variability of the area and their concentrations in groundwater. In addition, the degree of importance of each predictor was determined in order to rank their importance in modeling the concentration of each of the metals in groundwater. The summary ranking of predictors indicates that the strongest influence on the predicted concentration of metals in groundwater is exhibited by profile curvatures, planar curvatures, multiscale TPI, and then the habitat type of the forest. On the other hand, curvature classifications, soil composition, and seasonality exhibit the smallest generalized impact on the results of modeling.
Development of High-Glucosinolate-Retaining Lactic-Acid-Bacteria-Co-Fermented Cabbage Products
Authors: Hsieh Chen-Che , Liu Yuan-Heng , Lin Shin-Ping , Santoso Shella Permatasari , Jantama Kaemwich , Tsai Tsung-Yu , Hsieh Chang-Wei , Cheng Kuan-Chen
Published: December 2024

Cabbage (Brassica oleracea var. capitata) is rich in dietary fiber, vitamins, trace elements, and functional components like glucosinolates, which are essential for promoting health. This study aims to enhance the health benefits and nutritional content of cabbage through lactic acid fermentation using a bioreactor, with a particular focus on glucosinolate retention. The fermentation utilized a consortium of Lactiplantibacillus plantarum, known for its robust acidifying capabilities, and antioxidant-rich strains Lactobacillus acidophilus and Bifidobacterium longum. A 5 L bioreactor facilitated the controlled fermentation process (35 °C, 24 h of fermentation at 5 rpm). The efficacy of glucosinolate retention was quantitatively assessed alongside the analysis of antioxidant properties via 1,1-diphenyl-2-picrylhydrazil (DPPH) and 2,2′-Azino-bis (3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) assays. The results indicated a notable enhancement in antioxidant capacity with a 16.32% increase in the DPPH radical scavenging rate compared to non-fermented cabbage. Glucosinolate retention was impressively sustained at 82.02% in bioreactor conditions. Storage stability tests conducted at 4 °C revealed minimal degradation of glucosinolates, maintaining significant levels up to 14 days (from 90.34% to 66.49%). This study underscores the potential of bioreactor-facilitated lactic acid fermentation in preserving and enhancing the nutritional and functional qualities of cabbage, thereby extending its market value and promoting sustainable agricultural practices.
Two-Stage Multi-Objective Optimization for Improving the Aerodynamic Characteristics of High-Speed Train Nose Shape
Authors: Yun Suhwan , Kwak Minho , Kang Hyungmin , Park Wonhee , Kwon Taesoo
Published: December 2024

An optimal high-speed train nose design was formulated to reduce aerodynamic drag, mitigate tunnel micro-pressure waves, and improve crosswind safety. Using the vehicle modeling function, the EMU-320 nose shape was derived and applied as the base model for the optimal design. Following the initial optimization stage aimed at reducing aerodynamic drag, the second stage of optimization was conducted, using the results of the first stage as constraints, to further reduce tunnel micro-pressure waves and enhance crosswind safety. In the first stage, the aerodynamic drag was reduced by 8.7% due to the pointed nose shape. In the second stage, a Pareto front of optimal shapes was derived to reduce tunnel micro-pressure waves and improve crosswind safety, ensuring that the aerodynamic drag did not exceed the optimum achieved in the first stage by more than 1.5%. This two-stage multi-objective optimization is expected to be effectively utilized in the optimal design of high-speed train shapes that meet the intended purposes.
In-House Validation of Four Duplex Droplet Digital PCR Assays to Quantify GM Soybean Events
Authors: Verginelli Daniela , Ciuffa Sara , Spinella Katia , La Rocca Davide , Misto Marisa , Quarchioni Cinzia , Bonini Pamela , Fusco Cristiana , Peroni Lorella , Peddis Stefania , Marchesi Ugo
Published: December 2024

Due to the increasing number of authorized events in the European Union, it is crucial for the official laboratories to enforce market control to detect and quantify genetically modified organisms. In this study, an in-house validation of quantitative duplex ddPCR methods was performed involving MON87701, MON87769, MON89788 and CV-127-9 assays with respect to the lectin reference gene. Since the ddPCR methods provide accurate quantification, show less sensitivity to PCR inhibitors and are more suitable for multiplexing compared to the real-time PCR, the optimization of the existing assays was performed with the exception of MON87701, according to the JRC Guidance documents and technical reports. However, some concerns related to practical settings for the quantitative multiplex of ddPCR methods and their validation were encountered; therefore, a general workflow to develop and validate a ddPCR-based method is shown. The obtained data and the validation performance parameters such as specificity, cross-talk, robustness, dynamic range, linearity, the limit of quantification, trueness and precision comply with international recommendations for GMO quantification methods. The duplex ddPCR methods here investigated are equivalent in terms of performance compared to the singleplex real-time PCR methods, showing higher flexibility and cost effectiveness.
Nanoencapsulated Essential Oils for Post-Harvest Preservation of Stored Cereals: A Review
Authors: Maurya Akash , Yadav Arati , Soni Monisha , Paul Kishor Kumar , Banjare Umakant , Jha Manish Kumar , Dwivedy Abhishek Kumar , Dubey Nawal Kishore
Published: December 2024

Cereal grains are frequently attacked by microorganisms and insects during storage and processing, which negatively affects their quality, safety, and market value. Therefore, protecting stored grains from microbial contamination is crucial for food industries, farmers, public health associations, and environmental agencies. Due to the negative impact of synthetic gray chemicals, antimicrobial plant-based essential oils (EOs) can serve as alternative, safer, environmentally friendly preservatives that can prolong the shelf life of cereals. However, high volatility, low solubility, hydrophobicity, and quick oxidation limit their practical applicability. Using nanotechnology for the nanoencapsulation of EOs into polymeric matrices allows sustained release and ensures targeted delivery without significantly altering the organoleptic attributes of cereals, making EOs a new-generation green preservative. This ultimately overcomes the challenges of practical applications. The application of nanoencapsulated EOs in grain storage provides an effective and novel defense against microbes, insects, and other contaminants. Hence, the current review thoroughly examines the preservative potential of nanoencapsulated EOs in terms of antimicrobial and insecticidal efficacy for protecting stored cereal grains. It also highlights the challenges encountered during application and the safety concerns of using nanoencapsulated EOs in protecting cereal grains during post-harvest storage.
Combining Metal(loid) and Secondary Metabolite Levels in Olea europaea L. Samples for Geographical Identification
Authors: Nardin Raffaello , Tamasi Gabriella , Baglioni Michele , Fattori Giacomo , Boldrini Amedeo , Esposito Rodolfo , Rossi Claudio
Published: December 2024

To fight counterfeits, and to protect the consumer, the interest in certifying the origin of agricultural goods has been growing in recent years. In this context and to increase the accuracy of zoning models, multiple analytical techniques must be combined via a multivariate approach. During the sampling campaign, leaves and fruits (olives or drupes) were collected from multiple orchards and farms. By means of HPLC-DAD, metabolite levels were evaluated and combined with the trace and ultra-trace metal/metalloid levels evaluated by ICP-MS (QqQ). The combined dataset was then used to develop a model for geographical traceability. Furthermore, the mineral content of the soil, evaluated by means of ICP-MS, was correlated with both the mineral content in the leaves and drupes and the metabolomic profiles to further investigate the connection between the orchard’s location and characteristics of the final products.
Antioxidant Effects and Potential Mechanisms of Citrus reticulata ‘Chachi’ Components: An Integrated Approach of Network Pharmacology and Metabolomics
Authors: Xiao Jiahao , Sun Tian , Jiang Shengyu , Xiao Zhiqiang , Shan Yang , Li Tao , Pan Zhaoping , Li Qili , Fu Fuhua
Published: December 2024

Citrus reticulata ‘Chachi’ (CRC), recognized for its considerable edible and medicinal significance, is a valuable source of metabolites beneficial to human health. This research investigates the metabolic distinctions and antioxidant properties across four different parts of CRC, using multivariate statistical analysis to interpret metabolomic data and network pharmacology to identify potential antioxidant targets and relevant signaling pathways. The results indicate considerable metabolic differences in different parts of the sample, with 1622 metabolites showing differential expression, including 816 secondary metabolites, primarily consisting of terpenoids (31.02%) and flavonoids (25.22%). The dried mature citrus peel (CP) section demonstrates the highest level of total phenolics (6.8 mg/g), followed by the pulp without seed (PU) (4.52 mg/g), pulp with seed (PWS) (4.26 mg/g), and the seed (SE) (2.16 mg/g). Interestingly, targeted high-performance liquid chromatography of flavonoids reveals the highest level of nobiletin and tangeretin in CP, whereas PU has the highest level of hesperidin, narirutin, and didymin. Furthermore, all four sections of CRC exhibit robust antioxidant properties in in vitro assessments (CP > PU > PWS > SE). Lastly, the network pharmacology uncovered potential antioxidant mechanisms in CRC. This research offers deeper insights into the development and utilization of byproducts in the CRC processing industry.