bluuebunny/crossref_metadata_2025 huggingface dataset:
Transcriptome analysis reveals key regulatory genes for root growth related to potassium utilization efficiency in rapeseed (Brassica napus L.)
Authors: Ibrahim Sani , Ahmad Nazir , Kuang Lieqiong , Li Keqi , Tian Ze , Sadau Salisu Bello , Tajo Sani Muhammad , Wang Xinfa , Wang Hanzhong , Dun Xiaoling
Published: July 2023

Root system architecture (RSA) is the primary predictor of nutrient intake and significantly influences potassium utilization efficiency (KUE). Uncertainty persists regarding the genetic factors governing root growth in rapeseed. The root transcriptome analysis reveals the genetic basis driving crop root growth. In this study, RNA-seq was used to profile the overall transcriptome in the root tissue of 20 Brassica napus accessions with high and low KUE. 71,437 genes in the roots displayed variable expression profiles between the two contrasting genotype groups. The 212 genes that had varied expression levels between the high and low KUE lines were found using a pairwise comparison approach. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional classification analysis revealed that the DEGs implicated in hormone and signaling pathways, as well as glucose, lipid, and amino acid metabolism, were all differently regulated in the rapeseed root system. Additionally, we discovered 33 transcription factors (TFs) that control root development were differentially expressed. By combining differential expression analysis, weighted gene co-expression network analysis (WGCNA), and recent genome-wide association study (GWAS) results, four candidate genes were identified as essential hub genes. These potential genes were located fewer than 100 kb from the peak SNPs of QTL clusters, and it was hypothesized that they regulated the formation of the root system. Three of the four hub genes’ homologs—BnaC04G0560400ZS, BnaC04G0560400ZS, and BnaA03G0073500ZS—have been shown to control root development in earlier research. The information produced by our transcriptome profiling could be useful in revealing the molecular processes involved in the growth of rapeseed roots in response to KUE.
Determining factors affecting the user's intention to disclose privacy in online health communities: a dual-calculus model
Authors: Sun Zhuo , Zang Guoquan , Wang Zongshui , Ge Shuang , Liu Wei , Wang Kaiyang
Published: July 2023

Background

As a new type of medical service application for doctor-patient interaction, online health communities (OHCs) have alleviated the imbalance between the supply and demand of medical resources in different regions and the problems of “difficult and expensive access to medical care”, but also raised the concern of patients about the risk of disclosure of their health privacy information.

Methods

In this study, a dual-calculus model was developed to explore users' motivation and decision-making mechanism in disclosing privacy information in OHCs by combining risk calculus and privacy calculus theories.

Results

In OHCs, users' trust in physicians and applications is a prerequisite for their willingness to disclose health information. Meanwhile, during the privacy calculation, users' perceived benefits in OHCs had a positive effect on both trust in doctors and trust in applications, while perceived risks had a negative effect on both trusts in doctors and trust in applications. Furthermore, in the risk calculation, the perceived threat assessment in OHCs had a significant positive effect on perceived risk, while the response assessment had a significant negative effect on perceived risk, and the effect of users' trust in physicians far exceeded the effect of trust in applications. Finally, users' trust in physicians/applications is a mediating effect between perceived benefits/risks and privacy disclosure intentions.

Conclusion

We combine risk calculus and privacy calculus theories to construct a dual-calculus model, which divides trust into trust in physicians and trust in applications, in order to explore the intrinsic motivation and decision-making mechanism of users' participation in privacy disclosure in OHCs. On the one hand, this theoretically compensates for the fact that privacy computing often underestimates perceived risk, complements the research on trust in OHCs, and reveals the influencing factors and decision transmission mechanisms of user privacy disclosure in OHCs. On the other hand, it also provides guidance for developing reasonable privacy policies and health information protection mechanisms for platform developers of OHCs.
Design and Optimization of a Permanent Magnet-Based Spring–Damper System
Authors: Gori Nicolò , Simonelli Claudia , Musolino Antonino , Rizzo Rocco , Díez Jiménez Efren , Sani Luca
Published: July 2023

This paper reports the design and optimization of a permanent magnet-based spring. The aim of the optimization, performed using a particular form of the self-organizing map (SOM) algorithm, was to determine the dimensions of a ring PM-based spring with a force–displacement curve similar to a desired one. For each step in the optimization process, a spring composed of different ring-shaped magnets was analyzed using a semi-analytical model. Its characteristic was compared with the desired one to search for a minimum cost function obtained by subtracting the evaluated and the desired force–displacement curve. The resulting algorithm was efficient in the design of a spring with a desired characteristic. The geometry obtained was used to study an electrodynamic damper based on the exploitation of the interaction between the moving magnet of the spring and a conductive cylinder. A parametric analysis was performed: the damping effect grows when the cylinder thickness increases and decreases with the gap between the cylinder and the magnets. Also, the cylinder thickness needed to reduce to one the number of overshoots in the moving magnet’s position decreases with the gap increase. Computations were performed using the research code EN4EM (Electric Network 4 ElectroMagnetics) developed by the authors.
Combined Effect of Salicylic Acid and Proline Mitigates Drought Stress in Rice (Oryza sativa L.) through the Modulation of Physiological Attributes and Antioxidant Enzymes
Authors: Urmi Tahmina Akter , Islam Md. Moshiul , Zumur Kamrun Naher , Abedin Md. Anwarul , Haque M. Moynul , Siddiqui Manzer H. , Murata Yoshiyuki , Hoque Md. Anamul
Published: July 2023

Salicylic acid (SA) and proline exhibit protective effects against a wide range of stresses. However, the combined impact of SA and proline on rice under drought stress is still unknown. Therefore, we investigated the protective roles of SA and/or proline in conferring drought tolerance in rice. There were eight treatments comprising the control (T1; 95–100% FC), 1.5 mM SA (T2), 2 mM proline (T3), 0.75 mM SA + 1 mM proline (T4), 45–50% FC (T5, drought stress), T5 + 1.5 mM SA (T6), T5 + 2 mM proline (T7), and T5 + 0.75 mM SA + 1 mM proline (T8), and two rice varieties: BRRI dhan66 and BRRI dhan75. Drought stress significantly decreased the plant growth, biomass, yield attributes, photosynthetic rate (Pn), stomatal conductance (gs), transpiration rate (Tr), photosynthetic pigments (chlorophyll and carotenoids content), relative water content (RWC), membrane stability index (MSI), soluble sugar and starch content, and uptake of N, P and K+ in roots and shoots. Drought-induced oxidative stress in the form of increased hydrogen peroxide (H2O2) production and lipid peroxidation (MDA) was observed. The combined application of SA (0.75 mM) + proline (1 mM) was found to be more effective than the single application of either for drought stress mitigation in rice. A combined dose of SA + proline alleviated oxidative stress through boosting antioxidant enzymatic activity in contrast to their separate application. The application of SA + proline also enhanced proline, soluble sugar and starch content, which resulted in the amelioration of osmotic stress. Consequently, the combined application of SA and proline significantly increased the gas exchange characteristics, photosynthetic pigments, RWC, MSI, nutrient uptake, plant growth, biomass and yield of rice. Therefore, the combined application of SA and proline alleviated the detrimental impacts of drought stress more pronouncedly than their separate application did by increasing osmoprotectants, improving nutrient transport, up-regulating antioxidant enzyme activity and inhibiting oxidative stress.
Establishment and Application of Crowd-Sensing-Based System for Bridge Structural Crack Detection
Authors: Yuan Hangming , Jin Tao , Ye Xiaowei
Published: July 2023

The inspection of bridge structural cracks is essential to the structural safety evaluation and could provide reference for preventive maintenance. The traditional bridge structure inspection methods rely heavily on trained engineers with professional equipment. While such kind of way could provide reliable crack inspection data, the enormous amount of existing bridges waiting for inspection challenges the efficiency of these methods. Fortunately, the development of smartphones facilitates the possibility of making the pedestrian taking smartphones a mobile sensing node, which is able to collect crack information such as images and locations. At the same time, the booming deep learning methods could offer remarkable crack detection capacity to deal with the crack images automatically. Given this consideration, this paper established a crowd-sensing-based system for bridge structural crack detection. The system was composed of the cloud-based management platform and the mobile based application (APP) for crack information collection. The mobile-based APP was used by the volunteer pedestrians to collect the crack images as well as the locations, and the location accuracy was estimated to be around 5~10 m. Meanwhile, the cloud-based management platform was used for the management of the users and the collected crack information uploaded by all of the volunteers. A deep neural network was used to deal with the crack detection tasks and evaluate the quality of the collected images to see if they could be fitted for crack detection in bridge inspection works.
A Novel DFA on AES: Based on Two–Byte Fault Model with Discontiguous Rows
Authors: Wan Xusen , Zhang Jinbao , Cheng Shi , Wu Weixiang , Wang Jiehua
Published: July 2023

Differential fault attack (DFA) is a distinctive methodology for acquiring the key to block ciphers, which comprises two distinct strategies: DFA on the state and DFA on the key schedule. Given the widespread adoption of the Advanced Encryption Standard (AES), it has emerged as a prominent target for DFA. This paper presents an efficient DFA on the AES, utilizing a two−byte fault model that induces faults at the state with discontiguous rows. The experiment demonstrates that, based on the proposed fault model, the key for AES–128, AES–192, and AES–256 can be successfully recovered by exploiting two, two, and four faults, respectively, without the need for exhaustive research. Notably, in the case of AES–256, when considering exhaustive research, two (or three) faults are needed with 232 (or 216) exhaustive searches. In comparison to the currently available DFA on the AES state, the proposed attack method shows a higher efficiency due to the reduced induced faults.
Video Super-Resolution Network with Gated High-Low Resolution Frames
Authors: Ouyang Ning , Ou Zhishan , Lin Leping
Published: July 2023

In scenes with large inter-frame motion variations, distant targets, and blurred targets, the lack of inter-frame alignment can greatly affect the effectiveness of subsequent video super-resolution reconstruction. How to perform inter-frame alignment in such scenes is the key to super-resolution reconstruction. In this paper, a new motion compensation method is proposed to design an alignment network based on gated high-low resolution frames. The core idea is to introduce a gating mechanism while using the information of high-low resolution neighboring frames to perform motion compensation adaptively. Meanwhile, within this alignment framework, we further introduce a pre-initial hidden state network and a local scale hierarchical salient feature fusion network. The pre-initial hidden state network is mainly used to reduce the impact of unbalanced quality effects between frames that occur in one-way cyclical networks; the local scale hierarchical salient feature fusion network is used to fuse the features of aligned video frames to extract contextual information and locally salient features to improve the reconstruction quality of the video. Compared with existing video super-resolution methods, this method achieves good performance and clearer edge and texture details.
A Short Review of Through-Silicon via (TSV) Interconnects: Metrology and Analysis
Authors: Wang Jintao , Duan Fangcheng , Lv Ziwen , Chen Si , Yang Xiaofeng , Chen Hongtao , Liu Jiahao
Published: July 2023

This review investigates the measurement methods employed to assess the geometry and electrical properties of through-silicon vias (TSVs) and examines the reliability issues associated with TSVs in 3D integrated circuits (ICs). Presently, measurements of TSVs primarily focus on their geometry, filling defects, and the integrity of the insulating dielectric liner. Non-destructive measurement techniques for TSV contours and copper fillings have emerged as a significant area of research. This review discusses the non-destructive measurement of contours using high-frequency signal analysis methods, which aid in determining the stress distribution and reliability risks of TSVs. Additionally, a non-destructive thermal detection method is presented for identifying copper fillings in TSVs. This method exploits the distinct external characteristics exhibited by intact and defective TSVs under thermoelectric coupling excitation. The reliability risks associated with TSVs in service primarily arise from copper contamination, thermal fields in 3D-ICs, stress fields, noise coupling between TSVs, and the interactions among multiple physical fields. These reliability risks impose stringent requirements on the design of 3D-ICs featuring TSVs. It is necessary to electrically characterize the influence of copper contamination resulting from the TSV filling process on the reliability of 3D-ICs over time. Furthermore, the assessment of stress distribution in TSVs necessitates a combination of micro-Raman spectroscopy and finite element simulations. To mitigate cross-coupling effects between TSVs, the insertion of a shield between them is proposed. For efficient optimization of shield placement at the chip level, the geometric model of TSV cross-coupling requires continuous refinement for finite element calculations. Numerical simulations based on finite element methods, artificial intelligence, and machine learning have been applied in this field. Nonetheless, comprehensive design tools and methods in this domain are still lacking. Moreover, the increasing integration of 3D-ICs poses challenges to the manufacturing process of TSVs.
Effect of Drying Temperature of Ambar Pumpkin on Proximate Composition and Content of Bioactive Ingredients
Authors: Koziorzębska Agata , Łozicki Andrzej , Rygało-Galewska Anna , Zglińska Klara
Published: July 2023

Pumpkins are often used as a fodder component and food due to their high nutritional value and share of bioactive components (e.g., carotenoids, polyunsaturated fatty acid (PUFAs)). Due to their high moisture content, they must be preserved; drying is still the most popular method. Our work aimed to assess the optimal drying temperature to keep the best possible nutritional value of the raw material. For this purpose, pumpkin was dried at 40 °C, 60 °C and 80 °C. Then, the proximate composition, carotenoid content, fatty acids, and antioxidant properties were determined. The results indicate that the carotenoids were relatively stable up to 60 °C and then decreased sharply. Furthermore, antioxidant activity was the highest at 40 °C and 60 °C. However, in the case of PUFA content, drying at 80 °C was the most effective, probably due to the shorter exposure time to the stimulus.
Cyclic Hardening and Fatigue Damage Features of 51CrV4 Steel for the Crossing Nose Design
Authors: Gomes Vítor , Eck Sven , De Jesus Abílio
Published: July 2023

A crossing nose is a component of railway infrastructure subject to very severe loading conditions. Depending on the severity of these loads, the occurrence of structural fatigue, severe plastic deformation, or rolling fatigue may occur. Under fatigue conditions with high plastic deformation, cyclic plasticity approaches, together with local plasticity models, become more viable for mechanical design. In this work, the fatigue behavior in strain-controlled conditions of 51CrV4 steel, applicable to the crossing nose component, was evaluated. In this investigation, both strain-life and energy-life approaches were considered for fatigue prediction analysis. The results were considered through obtaining a Ramberg-Osgood cyclic elasto-plastic curve. Since this component is subject to cyclic loading, even if spaced in time, the isotropic and kinematic cyclic hardening behavior of the Chaboche model was subsequently analyzed, considering a comparative approach between experimental data and the FEM. As a result, the material properties and finite element model parameters presented in this work can contribute to the enrichment of the literature on strain-life fatigue and cyclic plasticity, and they could be applied in mechanical designs with 51CrV4 steel components or used in other future analyses.
Implementation of Augmented Reality in Dental Surgery Using HoloLens 2: An In Vitro Study and Accuracy Assessment
Authors: Akulauskas Mykolas , Butkus Karolis , Rutkūnas Vygandas , Blažauskas Tomas , Jegelevičius Darius
Published: July 2023

Computer-guided dynamic navigation systems have elevated dental implant surgery into a more patient-friendly and efficient procedure. However, commercially available systems use displays as an output for guidance. This implies that surgeons have to take their eyes off the surgery site frequently in order to accurately adjust surgical instruments. The solution for such an issue is to use augmented reality (AR) head-mounted devices to showcase all necessary guiding instructions without any distractions. In this work, the implementation of augmented reality in dental surgery using the HoloLens 2 AR headset for the assessment of accuracy is described. The experiments were performed in vitro with two implementation steps, evaluating calibration and perspective of the virtual dental model alignment accuracies using a newly created marker. The calibration results showed overall accuracy and precision surpassing the 1 mm threshold in distance-related measurements. Dependency on the side on which the marker was observed and the movement of the user’s head were considered to be the most influential factors regarding the perspective of the virtual dental model alignment accuracy estimate.
Semantic Similarity Analysis for Examination Questions Classification Using WordNet
Authors: Goh Thing Thing , Jamaludin Nor Azliana Akmal , Mohamed Hassan , Ismail Mohd Nazri , Chua Huangshen
Published: July 2023

Question classification based on Bloom’s Taxonomy (BT) has been widely accepted and used as a guideline in designing examination questions in many institutions of higher learning. The misclassification of questions may happen when the classification task is conducted manually due to a discrepancy in the understanding of BT by academics. Hence, several automated examination question classification systems have been proposed by researchers to perform question classification accurately. Most of this research has focused on specific subject areas only or single-sentence type questions. There has been a lack of research on question classification for multi-sentence type and multi-subject questions. This paper proposes a question classification system (QCS) to perform the examination of question classification using a semantic and synthetic approach. The questions were taken from various subjects of an engineering diploma course, and the questions were either single- or multiple-sentence types. The QCS was developed using a natural language toolkit (NLTK), Stanford POS tagger (SPOS), Stanford parser’s universal dependencies (UD), and WordNet similarity approaches. The QCS used the NLTK to process the questions into sentences and then word tokens, such as SPOS, to tag the word tokens and UD to identify the important word tokens, which were the verbs of the examination questions. The identified verbs were then compared with the BT’s verbs list in terms of word sense using the WordNet similarity approach before finally classifying the questions according to BT. The developed QCS achieved an overall 83% accuracy in the classification of a set of 200 examination questions, according to BT.
Repurposing Niclosamide as a Novel Anti-SARS-CoV-2 Drug by Restricting Entry Protein CD147
Authors: Yang Zhe , Zhang Qi , Wu Xiaoqing , Hao Siyuan , Hao Xinbao , Jones Elizabeth , Zhang Yuxia , Qiu Jianming , Xu Liang
Published: July 2023

The outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has led to the global coronavirus disease 2019 (COVID-19) pandemic, and the search for effective treatments has been limited. Furthermore, the rapid mutations of SARS-CoV-2 have posed challenges to existing vaccines and neutralizing antibodies, as they struggle to keep up with the increased viral transmissibility and immune evasion. However, there is hope in targeting the CD147-spike protein, which serves as an alternative point for the entry of SARS-CoV-2 into host cells. This protein has emerged as a promising therapeutic target for the development of drugs against COVID-19. Here, we demonstrate that the RNA-binding protein Human-antigen R (HuR) plays a crucial role in the post-transcriptional regulation of CD147 by directly binding to its 3′-untranslated region (UTR). We observed a decrease in CD147 levels across multiple cell lines upon HuR depletion. Furthermore, we identified that niclosamide can reduce CD147 by lowering the cytoplasmic translocation of HuR and reducing CD147 glycosylation. Moreover, our investigation revealed that SARS-CoV-2 infection induces an upregulation of CD147 in ACE2-expressing A549 cells, which can be effectively neutralized by niclosamide in a dose-dependent manner. Overall, our study unveils a novel regulatory mechanism of regulating CD147 through HuR and suggests niclosamide as a promising therapeutic option against COVID-19.
Repurposing Anti-Dengue Compounds against Monkeypox Virus Targeting Core Cysteine Protease
Authors: Imran Mohd , Abida  , Alotaibi Nawaf M. , Thabet Hamdy Khamees , Alruwaili Jamal Alhameedi , Eltaib Lina , Alshehri Ahmed , Alsaiari Ahad Amer , Kamal Mehnaz , Alshammari Abdulmajeed Mohammed Abdullah
Published: July 2023

The monkeypox virus (MPXV) is an enveloped, double-stranded DNA virus belonging to the genus Orthopox viruses. In recent years, the virus has spread to countries where it was previously unknown, turning it into a worldwide emergency for public health. This study employs a structural-based drug design approach to identify potential inhibitors for the core cysteine proteinase of MPXV. During the simulations, the study identified two potential inhibitors, compound CHEMBL32926 and compound CHEMBL4861364, demonstrating strong binding affinities and drug-like properties. Their docking scores with the target protein were −10.7 and −10.9 kcal/mol, respectively. This study used ensemble-based protein–ligand docking to account for the binding site conformation variability. By examining how the identified inhibitors interact with the protein, this research sheds light on the workings of the inhibitors’ mechanisms of action. Molecular dynamic simulations of protein–ligand complexes showed fluctuations from the initial docked pose, but they confirmed their binding throughout the simulation. The MMGBSA binding free energy calculations for CHEMBL32926 showed a binding free energy range of (−9.25 to −9.65) kcal/mol, while CHEMBL4861364 exhibited a range of (−41.66 to −31.47) kcal/mol. Later, analogues were searched for these compounds with 70% similarity criteria, and their IC50 was predicted using pre-trained machine learning models. This resulted in identifying two similar compounds for each hit with comparable binding affinity for cysteine proteinase. This study’s structure-based drug design approach provides a promising strategy for identifying new drugs for treating MPXV infections.
Tailored Gas Sensors as Rapid Technology to Support the Jams Production
Authors: Greco Giuseppe , Núñez-Carmona Estefanía , Genzardi Dario , Bianchini Linda , Piccoli Pierpaolo , Zottele Ivano , Tamanini Armando , Motolose Carola , Scalmato Antonello , Sberveglieri Giorgio , Sberveglieri Veronica
Published: July 2023

Nowadays, innovation in food technologies is fundamental and consumers are increasingly aware and demanding. To create a final product that is more and more appealing, health and safety guidelines are pushing towards new challenges. It is precisely due to the high quality required by the producers that the aim discussed in this project has been conceived. Until today, the controls on the entire production line have been slowed down by the limitations of the technologies involved, including the high cost of instrumentation for microbiological analysis, the need for qualified personnel to carry them out, the long execution times and the invasiveness of the techniques themselves. This project has, therefore, proposed a user-friendly solution that is minimally invasive, fast and at a lower cost. This system makes use of classical microbiological analysis and, in parallel, use of an innovative electronic-nose small sensor system (S3+), which can be trained to recognize the volatile fingerprint of a specific product and customized for a specific use. The aim of this project was to develop a system that is able to detect the mold contamination on fruit and vegetable jams and marmalades, using a new kind of innovative metal semiconductor gas sensor (MOS) device. The application of this technology has, therefore, made it possible to classify various samples of uncontaminated and contaminated fruit and vegetable preparations. Thanks to the classification implemented by a data-driven algorithm, it has been possible to build an anomaly detector that is able to recognize the occurrence of possible contamination, thus acting as an early alert system in the food chain. All this will occur in less than 1 min once the system is trained, in contrast with classical microbiological or chemical techniques that normally require longer timeframes to obtain a result and involve the use of reagents, increasing the costs.
The Role of Genetic Risk Factors in Pathogenesis of Childhood-Onset Systemic Lupus Erythematosus
Authors: Sestan Mario , Kifer Nastasia , Arsov Todor , Cook Matthew , Ellyard Julia , Vinuesa Carola G. , Jelusic Marija
Published: July 2023

The pathogenesis of childhood-onset systemic lupus erythematosus (cSLE) is complex and not fully understood. It involves three key factors: genetic risk factors, epigenetic mechanisms, and environmental triggers. Genetic factors play a significant role in the development of the disease, particularly in younger individuals. While cSLE has traditionally been considered a polygenic disease, it is now recognized that in rare cases, a single gene mutation can lead to the disease. Although these cases are uncommon, they provide valuable insights into the disease mechanism, enhance our understanding of pathogenesis and immune tolerance, and facilitate the development of targeted treatment strategies. This review aims to provide a comprehensive overview of both monogenic and polygenic SLE, emphasizing the implications of specific genes in disease pathogenesis. By conducting a thorough analysis of the genetic factors involved in SLE, we can improve our understanding of the underlying mechanisms of the disease. Furthermore, this knowledge may contribute to the identification of effective biomarkers and the selection of appropriate therapies for individuals with SLE.
X-rays Stimulate Granular Secretions and Activate Protein Kinase C Signaling in Human Platelets
Authors: Khan Muhammad Shoaib , Liu Chunliang , Meng Fanbi , Yang Mengnan , Zhou Kangxi , Hu Renping , Wang Xuexiang , Dai Kesheng
Published: July 2023

X-rays can induce morphological as well as functional changes in cells. Platelets are anuclear cellular fragments originating from megakaryocytes and are the major regulators in hemostasis and thrombosis. Platelet products are irradiated to avoid medical complications associated with platelet transfusion. So far, gamma, UV, and laser radiation have been used for this purpose. However, scientists are divided about the effects of radiation on platelet quality. The present study was designed to explore the possible effects of X-rays in washed human platelets and understand the molecular mechanism behind them. In the present study, we exposed washed human platelets to 10 or 30 Gy X-rays at 0.25 Gy/min. Flow cytometry, aggregometry, and western blot were performed to investigate the effect of X-rays on platelet degranulation, integrin activation, platelet aggregation, and apoptosis. It was found that X-rays immediately induced granular secretions with no effect on GP IIb/IIIa activation. Not surprisingly, due to granule secretions in irradiated platelets, platelet aggregation was significantly reduced. In contrast to granular secretions and platelet aggregation, X-rays induced mitochondrial transmembrane potential depolarization in a time-dependent manner to induce apoptosis and activated protein kinase C (PKC) signaling. This study revealed and explained the molecular mechanism activated by X-rays in washed human platelets. Here we also introduced Gö 6983, a PKC inhibitor, as an agent that counteracts X-ray-induced changes and maintains the integrity of platelets.
Efficient Day-Ahead Scheduling of PV-STATCOMs in Medium-Voltage Distribution Networks Using a Second-Order Cone Relaxation
Authors: Montoya Oscar Danilo , Florez-Cediel Oscar David , Gil-González Walter
Published: July 2023

This paper utilizes convex optimization to implement a day-ahead scheduling strategy for operating a photovoltaic distribution static compensator (PV-STATCOM) in medium-voltage distribution networks. The nonlinear non-convex programming model of the day-ahead scheduling strategy is transformed into a convex optimization model using the second-order cone programming approach in the complex domain. The main goal of efficiently operating PV-STATCOMs in distribution networks is to dynamically compensate for the active and reactive power generated by renewable energy resources such as photovoltaic plants. This is achieved by controlling power electronic converters, usually voltage source converters, to manage reactive power with lagging or leading power factors. Numerical simulations were conducted to analyze the effects of different power factors on the IEEE 33- and 69-bus systems. The simulations considered operations with a unity power factor (active power injection only), a zero power factor (reactive power injection only), and a variable power factor (active and reactive power injections). The results demonstrated the benefits of dynamic, active and reactive power compensation in reducing grid power losses, voltage profile deviations, and energy purchasing costs at the substation terminals. These simulations were conducted using the CVX tool and the Gurobi solver in the MATLAB programming environment.
The Role of Retention Trees in Providing a Habitat for Bryophytes and Lichens in Young Forest Stands: A Mid-Term Perspective
Authors: Gerra-Inohosa Linda , Matisons Roberts , Jansone Diāna , Jansons Āris , Lībiete Zane
Published: July 2023

Retention of trees from the previous generation is one of the most widespread conservation practices in forests used for timber production. Despite the comparatively long history of this approach in Europe, there is a lack of long-term studies on the effectiveness of retention trees in preserving epiphyte communities. We compared the diversity of bryophyte and lichen species on retention trees in 20 young forest stands in Latvia in two assessments, 11 years and 18 years after clearfelling. Linear mixed-effects models showed that richness of both lichens and bryophytes remained stable during the assessment years, while bryophyte cover and diversity on retention trees increased over time. The main indicator of higher species richness, cover and diversity on retention trees in managed forests in hemi-boreal vegetation zone was the tree species, with deciduous trees playing the key role. They also provided essential habitat for rare species. Regarding bryophytes, ash, elm, and aspen can be suggested as more efficient retention trees, thus aiding the continuity of bryophyte succession in young forest stands. For lichens, lime could also be prioritised.
Modulation Recognition of Low-SNR UAV Radar Signals Based on Bispectral Slices and GA-BP Neural Network
Authors: Liu Xuemin , Song Yaoliang , Chen Kuiyu , Yan Shihao , Chen Si , Shi Baihua
Published: July 2023

In this paper, we address the challenge of low recognition rates in existing methods for radar signals from unmanned aerial vehicles (UAV) with low signal-to-noise ratios (SNRs). To overcome this challenge, we propose the utilization of the bispectral slice approach for accurate recognition of complex UAV radar signals. Our approach involves extracting the bispectral diagonal slice and the maximum bispectral amplitude horizontal slice from the bispectrum amplitude spectrum of the received UAV radar signal. These slices serve as the basis for subsequent identification by calculating characteristic parameters such as convexity, box dimension, and sparseness. To accomplish the recognition task, we employ a GA-BP neural network. The significant variations observed in the bispectral slices of different signals, along with their robustness against Gaussian noise, contribute to the high separability and stability of the extracted bispectral convexity, bispectral box dimension, and bispectral sparseness. Through simulations involving five radar signals, our proposed method demonstrates superior performance. Remarkably, even under challenging conditions with an SNR as low as −3 dB, the recognition accuracy for the five different radar signals exceeds 90%. Our research aims to enhance the understanding and application of modulation recognition techniques for UAV radar signals, particularly in scenarios with low SNRs.
Diffusion Nonlinear Estimation and Distributed UAV Path Optimization for Target Tracking with Intermittent Measurements and Unknown Cross-Correlations
Authors: Wang Shen , Li Yinya , Qi Guoqing , Sheng Andong
Published: July 2023

This paper focuses on distributed state estimation (DSE) and unmanned aerial vehicle (UAV) path optimization for target tracking. First, a diffusion cubature Kalman filter with intermittent measurements based on covariance intersection (DCKFI-CI) is proposed, to address state estimation with the existence of detection failure and unknown cross-correlations in the network. Furthermore, an alternative transformation of DCKFI-CI based on the information form is developed utilizing a pseudo measurement matrix. The performance of the proposed DSE algorithm is analyzed using the consistency and the bounded error covariance of the estimate. Additionally, the condition of the bounded error covariance is derived. In order to further improve the tracking performance, a UAV path optimization algorithm is developed by minimizing the sum of the trace of fused error covariance, based on the distributed optimization method. Finally, simulations were conducted to verify the effectiveness of the proposed algorithm.
Multi-Group Tracking Control for MASs of UAV with a Novel Event-Triggered Scheme
Authors: Zhao Can , Shi Kaibo , Tang Yiqian , Xiao Jianying , He Nanrong
Published: July 2023

The flight control of UAVs can be implemented and theoretically analyzed using multi-agent systems (MASs), and tracking control is one of the important control technologies. This paper studies multi-group tracking control for multi-agent systems of UAV, in which the control scheme combines event-triggered technology and impulsive theory. The advantage of multi-group tracking control lies in its ability to realize multiple groups of tracking targets and make the UAV complete multiple groups of tasks. The tracking control makes use of a novel dynamic event-triggered control (DETC) proposed in this paper, in which it can better regulate and optimize the triggering frequency by adjusting the parameters. Furthermore, several forms of network interference that may affect the safety of UAV tracking control have also been resolved. Lastly, simulations are presented with numerical examples to showcase the efficacy of the proposed tracking control.
Wavelet-Based Multiscale Intermittency Analysis: The Effect of Deformation
Authors: Angulo José M. , Madrid Ana E.
Published: July 2023

Intermittency represents a certain form of heterogeneous behavior that has interest in diverse fields of application, particularly regarding the characterization of system dynamics and for risk assessment. Given its intrinsic location-scale-dependent nature, wavelets constitute a useful functional tool for technical analysis of intermittency. Deformation of the support may induce complex structural changes in a signal. In this paper, we study the effect of deformation on intermittency. Specifically, we analyze the interscale transfer of energy and its implications on different wavelet-based intermittency indicators, depending on whether the signal corresponds to a ‘level’- or a ‘flow’-type physical magnitude. Further, we evaluate the effect of deformation on the interscale distribution of energy in terms of generalized entropy and complexity measures. For illustration, various contrasting scenarios are considered based on simulation, as well as two segments corresponding to different regimes in a real seismic series before and after a significant earthquake.
Air Pollution and Health in Africa: The Burden Falls on Children
Authors: Mlambo Courage , Ngonisa Phillip , Ntshangase Bhekabantu , Ndlovu Nomusa , Mvuyana Bongekile
Published: July 2023

This study sought to examine the impact of air pollution on health in Africa. Air pollution is a major public health concern around the world. Exposure to air pollution has been linked to a slew of negative health consequences, ranging from subclinical effects, physiological changes in pulmonary functions and the cardiovascular system, to clinical symptoms, outpatient and emergency-room visits, hospital admissions, and finally to premature death. Health impact assessments indicate that sub-Saharan Africa suffers a high burden of disease and premature deaths, attributable to environmental pollution in the world. The health and economic repercussions of rapid pollution increases could jeopardize African efforts to enhance economic development, establish human capital, and achieve the Sustainable Development Goals (SDGs). Despite all these, literature on pollution and health is still scanty in the case of Africa. This study was quantitative in nature, and it used a difference GMM approach to estimate its model. The GMM results showed that children are negatively affected by pollution. Children under the age of five are especially at risk, and the effects are believed to be most severe in developing countries, where exposure to high levels of ambient air pollution throughout childhood is thought to lower total life expectancy by an average of 4–5 years. Based on the findings of this study, it is recommended that African countries must not overlook the pollution problem. They must promote and use low carbon technologies and services. In the absence of active intervention, pollution will soon raise morbidity and death.
Same Word, Same Picture, Different Responses: Exploring Teachers’ and Autistic Adolescents’ Conceptions of Autism
Authors: Alexander Vanessa , Bissaker Kerry
Published: July 2023

Individuals’ understandings of autism vary significantly, with multiple factors influencing their conceptions of autism. Varying conceptions between teachers and students in inclusive school settings may lead to diminished educational experiences for both groups. Our research was focused on exploring the influences on teachers’ and autistic students’ conceptions or misconceptions of autism. We were also interested in whether more implicit influences, including the commodification of autism, influence teachers’ and autistic students’ conceptions of autism. To ensure the research respected the needs of the young autistic participants, the purposes and processes involved in the research design were presented to a group of autistic adults for feedback and recommendations. Therefore, this paper presents two distinct aspects of the research: the outcomes of engagement with autistic adults in the design phase of the research and the outcomes of engaging with the research participants, six teachers, and four autistic adolescents. The qualitative research involved semi-structured interviews and photo-elicitation responses. A key starting question encouraged the participants to share a feeling, memory, or image on hearing the word autism, and following an exploration of their responses, they were invited to select a photo from those presented that reminded them of an aspect of autism. The autistic adults contributed to the selection of the final twelve black-and-white images used in the photo-elicitation process. The adults were asked to select those they felt most closely represented their conceptions of autism. Of interest, only one photo was chosen in common by all research participants, but their explanations for choosing the image varied. Responses to other selected photos are also shared to highlight the varied conceptions of autism generated by the teachers and autistic students and the explicit and implicit influences on their conceptions. The influence of lived experiences and the commodification of autism were evident in the participants’ responses.
The Antecedents of the Technology Acceptance Model in Microentrepreneurs’ Intention to Use Social Networking Sites
Authors: Bonfanti Rubinia Celeste , Tommasi Francesco , Ceschi Andrea , Sartori Riccardo , Ruggieri Stefano
Published: July 2023

Social media platforms offer significant growth opportunities for enterprises, particularly microenterprises, due to the chance to establish direct contact with customers. Drawing on the Technology-Acceptance Model (TAM), in the present study, we investigate the psychological reasons that lead microentrepreneurs to use Social Networking Sites (SNSs) for their business. In doing so, we also extend TAM by taking into account entrepreneurs’ personalities (e.g., extraversion and openness to experience) and their perceived risk. We collected data by examining 247 microentrepreneurs engaged in the production of handmade objects. Our results confirm that of all the TAM behavioral antecedents tested, perceived usefulness and attitude toward SNSs’ usage for business proved to be the best predictors of the intention to use SNSs for business activity. The results also indicate that extraversion, openness to experience, and perceived risk, as external factors, significantly affect the TAM constructs. We discuss implications and suggestions for future research.
Automation, Operation and Maintenance of Control and Communication Systems
Authors: Szymak Piotr , Piskur Paweł , Hożyń Stanisław
Published: July 2023

The special issue is devoted to selected papers, which results of the research were presented during the XVIII Conference on Automation, Operation and Maintenance of Control and Communication Systems ASMOR 2022. The conference was conducted from the 12th to the 14th of October 2022 in Władysławowo, Poland. The scope of the conference is quite wide, focusing mainly on automation and exploitation aspects of the control and communications systems. Due to the specified scope of the Electronics, only the papers selected by the ASMOR Scientific Committee and the Electronics Editors were published after an extensive reviewing and revising process.
Intelligent Recognition of Seismic Station Environmental Interference Based on YOLOv5
Authors: Cai Yin , Tian Pengxin , Song Haoran , Yin Yuzhen , Si Guannan , Liu Ruifeng
Published: July 2023

In recent years, human interference in seismic-station environments has posed challenges to the quality and accuracy of seismic signals, making data processing difficult. To accurately identify interference caused by personnel and ensure the reliability of seismic-network instrument detection data, it is necessary to track the detected targets across consecutive frames. Deep neural networks have made significant progress in this field. Therefore, an intelligent identification solution for environmental interference at seismic stations is proposed, which combines deep learning with multi-object tracking techniques. A centroid-matching tracking algorithm based on Kalman filtering is introduced to identify the entry/exit timestamps, alongside motion trajectories of interfering individuals, thereby marking the anomalous data caused by the presence of interfering personnel in seismic time-series data. Experimental results demonstrate that this research provides an effective solution for intelligent identification of environmental interference in seismic station environments.
A Lifetime Improvement Active Thermal Control Strategy for Wind Turbine Parallel Converters Based on Reactive Circulating Current
Authors: Wang Qichao , Liu Jun , Wu Peidong , Qin Xiaoying
Published: July 2023

When the wind turbine operates under frequently fluctuating mission profiles, the power semiconductors of its converter will generate low-frequency junction temperature fluctuations, resulting in accumulation of damage to the devices and affecting the converter’s lifetime. To address the above issues, an active thermal control (ATC) strategy based on reactive circulating current for the parallel converter of permanent magnet synchronous generator wind power system was proposed in this paper, by introducing reactive circulating current during sudden wind speed drops, the thermal cycle of the power semiconductor can be effectively smoothed. On the other hand, considering the impact of the proposed strategy on the voltage vector and modulation index of the converter, both the machine-side converter (MSC) and the grid-side converter (GSC) during the control process will be analyzed in detail, then the reactive current of GSC will be limited to prevent excessive modulation index and maintain system stability without reducing the filter size. Finally, a 2 MW wind power system is utilized as a benchmark, and both short-term simulation analysis and long-term numerical results reveal the effectiveness of the control strategy proposed in this paper.