bluuebunny/crossref_metadata_2025 huggingface dataset:
Symptomatic Vasospasm Refractory to Clazosentan after Subarachnoid Hemorrhage of Ruptured Vertebral Artery Dissecting Aneurysm: Clinical Implications from Two Contrasting Cases
Authors: Yoshida Yasuyuki , Mutoh Tatsushi , Moroi Junta , Ishikawa Tatsuya
Published: September 2024

Clazosentan prevents vasospasms after aneurysmal subarachnoid hemorrhage (SAH). However, clinical data on patients with SAH with ruptured vertebral artery dissecting aneurysms (VADAs) are limited. We report the case of a 49-year-old male patient with mild-grade (WFNS grade 1) thick and diffuse (modified Fisher grade 3) SAH who underwent endovascular trapping of a ruptured VADA, resulting in a poor functional outcome with a modified Rankin Scale score of 4 due to severe symptomatic vasospasm refractory to clazosentan, requiring repeated rescue endovascular therapies and chronic communicating hydrocephalus. A retrospective analysis of the clot density in the basal and Sylvian cisterns, assessed by the Hounsfield unit (HU) values of serial CT scans, in this patient showed persistent higher values, distinct from another VADA case that showed a decline in HU values with a good clinical course. These results imply the limited effectiveness of clazosentan in cases of thick and diffuse SAH after a ruptured VADA, even in good-clinical-grade patients treated with less invasive modalities. The HU values may become a simple quantitative marker for predicting symptomatic vasospasms and chronic hydrocephalus.
Immune mRNA Expression and Fecal Microbiome Composition Change Induced by Djulis (Chenopodium formosanum Koidz.) Supplementation in Aged Mice: A Pilot Study
Authors: Villanueva Brian Harvey Avanceña , Huang Huai-Ying , Tyan Yu-Chang , Lin Pei-Ju , Li Chang-Wei , Minh Hoang , Tayo Lemmuel L. , Chuang Kuo-Pin
Published: September 2024

Background and Objectives: The aging process has always been associated with a higher susceptibility to chronic inflammatory lung diseases. Several studies have demonstrated the gut microbiome’s influence on the lungs through cross-talk or the gut–lungs axis maintaining nutrient-rich microenvironments. Taiwan djulis (Chenopodium formosanum Koidz.) provides antioxidant and anti-inflammatory characteristics that could modulate the gut microbiome. This could induce the gut–lung axis through microbial cross-talk, thus favoring the modulation of lung inflammation. Materials and Methods: Here, we investigate the immune mRNA expression in the spleen, fecal microbiome composition, and hyperplasia of the bronchial epithelium in aged 2-year-old BALB/c mice after 60 days of supplementation of djulis. Results: The pro-inflammatory cytokines IFN-γ, TNF-α, and IL-1β, T; cells CD4 and CD8; and TLRs TLR3, TLR4, TLR5, TLR7, TLR8, and TLR9 were reduced in their mRNA expression levels, while the anti-inflammatory cytokines IL-2, IL-4, and IL-10 were highly expressed in the C. formosanum-treated group. Interestingly, the fecal microbiome composition analysis indicated higher diversity in the C. formosanum-treated group and the presence of butyrate-producing bacteria that are beneficial in the gut microbiome. The histopathology showed reduced hyperplasia of the bronchial epithelium based on the degree of lesions. Conclusions: Our findings suggest that Taiwan djulis can modulate the gut microbiome, leading to microbial cross-talk; reducing the mRNA expression of pro-inflammatory cytokines, T cells, and TLRs; and increasing anti-inflammatory cytokines in the spleen, as cytokines migrate in the lungs, preventing lung inflammation damage in aged mice or the gut–lung axis. Thus, Taiwan djulis could be considered a beneficial dietary component for the older adult population. The major limitation includes a lack of protein validation of cytokines and TLRs and quantification of the T cell population in the spleen as a marker of the gut–lung axis.
Editorial from the New Editor-in-Chief of Merits
Authors: Topa Gabriela
Published: September 2024

As the new Editor-in-Chief of Merits, I am truly excited to help steer the journal in a new direction [...]
Soil Fungal Community Diversity, Co-Occurrence Networks, and Assembly Processes under Diverse Forest Ecosystems
Authors: Yang Bing , Yang Zhisong , He Ke , Zhou Wenjia , Feng Wanju
Published: September 2024

Fungal communities are critical players in the biogeochemical soil processes of forest ecosystems. However, the factors driving their diversity and community assembly are still unclear. In the present study, five typical vegetation types of soil fungal communities in Liziping Nature Reserve, China, were investigated using fungal ITS sequences. The results show that the topsoil fungal community is mainly dominated by the phyla Ascomycota, Basidiomycota, and Mortierellomycota. Although there was no significant difference in α diversity (Shannon, Simpson, and Pielou evenness indices) among different forest types, there was a significant difference in β diversity (community composition). This study found that soil pH, soil organic carbon, total nitrogen (TN), total phosphorus (TP), and the total nitrogen/total phosphorus (N/P) ratio are the main environmental factors that affect soil fungal communities. Each forest type has a specific co-occurrence network, indicating that these community structures have significant specificities and complexities. Deciduous evergreen broad-leaved forests as well as deciduous broad-leaved and evergreen broad-leaved mixed forests showed high modularity and average path lengths, indicating their highly modular nature without distinct small-scale characteristics. Furthermore, our findings indicate that the structures of topsoil fungal communities are mainly shaped by stochastic processes, with the diffusion limitation mechanism playing a particularly significant role.
The Influence of Dietary Supplementation with Dried Olive Pulp on Gut Microbiota, Production Performance, Egg Quality Traits, and Health of Laying Hens
Authors: Dedousi Anna , Kotzamanidis Charalampos , Malousi Andigoni , Giantzi Virginia , Sossidou Evangelia
Published: September 2024

This study examines the dietary effect of dried olive pulp (OP) on the overall performance, egg quality, health, and gut microbiota of laying hens during a 36-week trial. A total of 180 Isa Brown layers, aged 23 weeks, were assigned to 15-floor pens and divided into three feeding groups (CON, OP4, and OP6) based on the dietary level of OP. Egg quality and biochemical parameters were assessed in 39- and 59-week-old hens. Fecal samples were collected for microbiota analysis. Data were analyzed with an Analysis of Variance. The percentage of broken eggshells was found to be 15–34% lower in the OP groups compared to the CON groups. At 59 weeks of age, a significant reduction in shell thickness was observed in the CON eggs compared to the OP eggs (p < 0.05). At 39 weeks of age, OP6 eggs had the darkest yolk color of all groups (p < 0.05). Fecal microbial diversity was affected only by hens’ age. However, an enrichment in bacterial species belonging to the genera Megasphaera and Megamonas was found in the OP groups at 59 weeks of age. Our results demonstrate that OP feeding beneficially affects egg quality and promotes the proliferation of bacteria involved in the degradation of complex plant compounds, potentially contributing to the overall health of the gut microbiota.
A WO3–CuCrO2 Tandem Photoelectrochemical Cell for Green Hydrogen Production under Simulated Sunlight
Authors: Díaz-García Ana K. , Gómez Roberto
Published: September 2024

The development of photoelectrochemical tandem cells for water splitting with electrodes entirely based on metal oxides is hindered by the scarcity of stable p-type oxides and the poor stability of oxides in strongly alkaline and, particularly, strongly acidic electrolytes. As a novelty in the context of transition metal oxide photoelectrochemistry, a bias-free tandem cell driven by simulated sunlight and based on a CuCrO2 photocathode and a WO3 photoanode, both unprotected and free of co-catalysts, is demonstrated to split water while working with strongly acidic electrolytes. Importantly, the Faradaic efficiency for H2 evolution for the CuCrO2 electrode is found to be about 90%, among the highest for oxide photoelectrodes in the absence of co-catalysts. The tandem cell shows no apparent degradation in short-to-medium-term experiments. The prospects of using a practical cell based on this configuration are discussed, with an emphasis on the importance of modifying the materials for enhancing light absorption.
Antioxidant Effects of Cactus Seed Oil against Iron-Induced Oxidative Stress in Mouse Liver, Brain and Kidney
Authors: Bouchab Habiba , Ishaq Abbas , Limami Youness , Saretzki Gabriele , Nasser Boubker , El Kebbaj Riad
Published: September 2024

In recent times, exploring the protective potential of medicinal plants has attracted increasing attention. To fight reactive oxygen species (ROS), which are key players in hepatic, cerebral and renal diseases, scientists have directed their efforts towards identifying novel compounds with antioxidant effects. Due to its unique composition, significant attention has been given to Cactus Seed Oil (CSO). Iron, as a metal, can be a potent generator of reactive oxygen species, especially hydroxyl radicals, via the Fenton and Haber–Weiss reactions. Here, we employed ferrous sulfate (FeSO4) to induce oxidative stress and DNA damage in mice. Then, we used CSO and Colza oil (CO) and evaluated the levels of the antioxidants (superoxide dismutase [SOD], glutathione peroxidase [GPx] and glutathione [GSH]) as well as a metabolite marker for lipid peroxidation (malondialdehyde [MDA]) relating to the antioxidant balance in the liver, brain and kidney. In addition, we measured DNA damage levels in hepatic tissue and the effects of CSO on it. Our study found that iron-dependent GPx activity decreases in the liver and the kidney tissues. Additionally, while iron decreased SOD activity in the liver, it increased it in the kidney. Interestingly, iron treatment resulted in a significant increase in hepatic MDA levels. In contrast, in brain tissue, there was a significant decrease under iron treatment. In addition, we found varying protective effects of CSO in alleviating oxidative stress in the different tissues with ameliorating DNA damage after iron overload in a mouse liver model, adding compelling evidence to the protective potential of CSO.
A Multi-Spectroscopic and Molecular Docking Analysis of the Biophysical Interaction between Food Polyphenols, Urolithins, and Human Serum Albumin
Authors: Zelenović Nevena , Ristić Predrag , Polović Natalija , Todorović Tamara , Kojadinović Milica , Popović Milica
Published: September 2024

Secondary polyphenol metabolites, urolithins (UROs), have anti-oxidative, anti-inflammatory, and antidiabetic properties. Therefore, their biological activity relies on blood transport via human serum albumin (HSA) and tissue distribution. The main goal we set was to investigate the interaction between HSA and different URO (URO A, URO B, URO C, URO D, and glucuronidated URO A and B) using a combination of multi-spectroscopic instrumental and in silico approaches. The fluorescence spectroscopy revealed that URO can quench the naturally occurring fluorescence of HSA in a concentration-dependent manner. The HSA fluorescence was quenched by both a static and dynamic mechanism. The results showed that free UROs bind to HSA with higher affinity than their conjugated forms. CD spectroscopy and FTIR revealed that the alpha-helical structure of HSA is preserved. The calculated Gibbs free energy change indicates that the URO–HSA complex forms spontaneously. There is a single binding site on the HSA surface. The molecular docking results indicated that unconjugated Uro binds to Sudlow I, while their conjugation affects this binding site, so in the conjugated form, they bind to the cleft. Docking experiments indicate that all UROs are capable of binding to both thyroxine recognition sites of ligand-bound HSA proteins. Examining interactions under the following conditions (298 K, 303 K, and 310 K, pH 7.4) is of great importance for determining the pharmacokinetics of these bioactive compounds, as the obtained results can be used as a basis for modulating the potential dosing regimen.
Zn/Cr-MOFs/TiO2 Composites as Adsorbents for Levofloxacin Hydrochloride Removal
Authors: Wei Fuhua , Zhang Qin , Ren Qinhui , Chen Hongliang , Zhang Yutao , Liang Zhao
Published: September 2024

The Zn/Cr-MOFs/TiO2 composites were synthesized using the solvothermal method. XRD, FTIR, and SEM techniques were utilized to characterize the Zn/Cr-MOFs/TiO2 composites employed for simulating levofloxacin hydrochloride in wastewater. The impact of the mass of the Zn/Cr-MOFs/TiO2 composite, concentration of levofloxacin hydrochloride, solution pH, and temperature on the adsorption performance was investigated. Experimental findings indicated that at pH 6, the maximum removal efficiency of levofloxacin hydrochloride by the Zn/Cr-MOFs/TiO2 composite was achieved at 88.8%, with an adsorption capacity of 246.3 mg/g. To analyze the experimental data, both pseudo-first-order and pseudo-second-order kinetics models were applied, revealing that the pseudo-second-order model provided a better fit to the data. Additionally, Langmuir and Freundlich isotherm models were used to study equilibrium adsorption behavior and showed good agreement with both kinetic modeling and Langmuir isotherm analysis results. These observations suggest that monolayer adsorption predominates during the removal process of levofloxacin hydrochloride by Zn/Cr-MOFs/TiO2 composites.
Music as a Tool for Affiliative Bonding: A Second-Person Approach to Musical Engagement
Authors: Reybrouck Mark
Published: September 2024

Music listening or playing can create a feeling of connection with other listeners or performers, with distinctive levels of immersion and absorption. A major question, in this regard, is whether the music does have an ontological status, as an end in itself, or whether it is only a tool for the mediation of something else. In this paper we endorse a mediating perspective, with a focus on the music’s potential to increase affiliative bonding between listeners, performers and even the music. Music, then, is hypostasized as “something that touches us” and can be considered a partner of affiliative exchange. It has the potential to move us and to modulate the way we experience the space around us. We therefore elaborate on the tactile dimension of being moved, as well as on the distinction between personal, peripersonal, and extrapersonal space, with a corresponding distinction between first-person, second-person, and third-person perspectives on musical engagement.
Cultural Perspectives on the Efficacy and Adoption of the Crohn’s Disease Exclusion Diet across Diverse Ethnicities: A Case-Based Overview
Authors: Sigall Boneh Rotem , Park Sowon , Soledad Arcucci Maria , Herrador-López Marta , Sarbagili-Shabat Chen , Kolonimos Nitzan , Wierdsma Nicolette , Chen Min , Hershkovitz Einat , Wine Eytan , Van Limbergen Johan
Published: September 2024

Background: The Crohn’s Disease Exclusion Diet (CDED) is a whole-foods regimen that has demonstrated efficacy in inducing remission among children and adults with mild-to-moderate disease. While initial studies predominantly originated from Israel, recent years have witnessed the expansion of experiences to diverse cultures, culminating in the recognition of CDED in the latest ESPEN guidelines. However, implementing dietary therapy poses significant challenges across various cultures, necessitating adaptations. Aim and Methods: This case-based study aims to present the collective experience from different cultures, shedding light on the encountered challenges and the corresponding solutions devised to surmount them by convening healthcare providers (dietitians and physicians across six countries and eight cultural settings) with extensive experience in utilizing the CDED. Results and Conclusions: Our findings underscore the efficacy of CDED across diverse cultural contexts and emphasize the pivotal role of dietitians in tailoring the diet to accommodate patients’ cultural behaviors and traditions. We highlight challenges encountered and delineate strategies for overcoming them by customizing the diet and offering tailored guidance. Additionally, we provide insights into implementing CDED in various regions through adjusted recipes and personalized counseling from dietitians. This study contributes to the growing body of literature on CDED, and offers practical guidance for its effective adoption in diverse cultural settings.
ITIH4 in Rheumatoid Arthritis Pathogenesis: Network Pharmacology and Molecular Docking Analysis Identify CXCR4 as a Potential Receptor
Authors: Joshi Lovely , Chakraborty Debolina , Kumar Vijay , Biswas Sagarika
Published: September 2024

Elevated levels of Inter-alpha-trypsin-inhibitor heavy chain 4 (ITIH4) have grabbed attention in rheumatoid arthritis (RA) pathogenesis, though its precise mechanisms remain unexplored. To elucidate these mechanisms, a comprehensive strategy employing network pharmacology and molecular docking was utilized. RA targets were sourced from the DisGeNET Database while interacting targets of ITIH4 were retrieved from the STRING and Literature databases. Venny 2.1 was used to identify overlapping genes, followed by Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) through Cytoscape 3.10.2 software, and molecular docking was performed in the ClusPro server. The study identified 18 interacting proteins of ITIH4 associated with RA, demonstrating their major involvement in the chemokine signaling pathway by enrichment analysis. Molecular docking of ITIH4 with the 18 proteins revealed that C-X-C chemokine-receptor type 4 (CXCR4), a major protein associated with chemokine signaling, has the highest binding affinity with ITIH4 with energy −1705.7 kcal/mol forming 3 Hydrogen bonds in the active site pocket of ITIH4 with His441, Arg288, Asp443 amino acids. The effect of ITIH4 on CXCR4 was analyzed via knockdown studies in rheumatoid arthritis fibroblast-like synoviocytes (RA-FLS), demonstrating the significant downregulation of CXCR4 protein expression validated by Western blot in RA-FLS. In conclusion, it was speculated that CXCR4 might serve as a potential receptor for ITIH4 to activate the chemokine signaling, exacerbating RA pathogenesis.
Low Complexity Parallel Carrier Frequency Offset Estimation Based on Time-Tagged QPSK Partitioning for Coherent Free-Space Optical Communication
Authors: Zhang Siqi , Wang Liqian , Liu Kunfeng , Ding Shuang
Published: September 2024

To effectively mitigate the effects of atmospheric turbulence in free space optical (FSO) communication, we propose a parallel carrier frequency offset estimation (FOE) scheme based on time-tagged QPSK partitioning (TTQP). This scheme can be applied to spatial diversity polarization multiplexing (PM) coherent FSO communication systems. Specifically, the TTQP scheme performs QPSK partitioning by time-tagging signal points, accurately recording the time intervals between signals, and significantly reducing implementation complexity through a modified Mth power algorithm. The simulation results for the PM 16-quadrature amplitude modulation (QAM) validate the effectiveness of the proposed scheme. Compared to traditional QPSK partitioning algorithms, the TTQP algorithm achieves high accuracy, low complexity, and multi-format versatility in high-speed coherent FSO communication.
A Bidirectional Mode-Locked Fiber Laser for Asynchronous Noise-like Pulse Generation
Authors: Zheng Yongguo , Wang Anshuang , Cai Yue , Zhang Fan , Zhang Xinhai
Published: September 2024

We demonstrate a bidirectional fiber laser with an artificial saturable absorber of a step-index multimode fiber sandwiched by single-mode fibers. Two asynchronous noise-like pulse sequences with a repetition frequency difference of 3.16 kHz are obtained. The average power of the bidirectional asynchronous noise-like pulses is greater than 36 mW, and the pulse energy is greater than 3 nJ. The laser we demonstrate has potential applications in micromachining, supercontinuum spectrum generation, and signal processing.
Format-Free Submissions in Psychology-Related Journals
Authors: Cole Geoff G. , Benfield Ellie , Samuel Steven
Published: September 2024

Scientists have a duty to spend their time, and hence public money, in an efficient manner. One particularly wasteful task concerns the formatting of articles submitted to academic journals. Around a decade or so ago some academics began to challenge this inefficiency and a small number of articles have been published advocating for change. There has, however, been little progress, particularly within psychology. In the present article, we advocate for what is sometimes referred to as the Format-Free Submission. In order to quantify progression, we also examined a sample (n = 500) of psychology-related journals to determine which offer this. Results showed that only 73 (i.e., 14.6%) have formatting requirements that are relatively flexible for initial submissions. We suggest that the current system within psychology publishing is unethical, in that it wastes a huge amount of taxpayers’ money, and that change is needed.
Mission Planning and Trajectory Optimization in UAV Swarm for Track Deception against Radar Network
Authors: Li Yihan , Shi Chenguang , Yan Mu , Zhou Jianjiang
Published: September 2024

In this article, a mission planning and trajectory optimization scheme in unmanned aerial vehicle (UAV) swarm for track deception against radar networks is proposed. The core of this scheme is to formulate the track deception problem as a model with the objective of simultaneously maximizing the number of phantom tracks while minimizing the total flight distance of the UAV swarm, subject to the constraints of UAV kinematic performance, phantom track rotation angles, and a homology test. It is shown that the formulated track deception problem is a mixed-integer programming, multivariable, and non-linear optimization model. By incorporating mission planning based on platform reuse and a particle swarm optimization (PSO) algorithm, a three-stage solution methodology is proposed to tackle the above problem. Through joint optimization for mission planning and flight trajectories of the UAV swarm, a low-speed UAV swarm is capable of generating a number of high-speed phantom tracks. Numerical results demonstrate that the proposed scheme enables a low-speed UAV swarm to generate as many high-speed phantom tracks as possible, effectively achieving track deception against radar network.
Cumulative Rainfall Radar Recalibration with Rain Gauge Data Using the Colour Pattern Regression Algorithm QGIS Plugin
Authors: Blanco-Gómez Pablo , Estrany-Planas Pau , Jiménez-García José Luis
Published: September 2024

Climate change is a major issue in wastewater management at local and regional levels, as it affects the frequency of flooding and therefore the need to update infrastructure and design regulations. To this end, rainfall data are the main input to hydraulic models used for the design of drainage systems and, in advanced contexts, for their real-time monitoring. Field observations are of great interest and water authorities are increasing the number of existing rain gauges, but at present they are scarce and require maintenance, so their number needs to be considered with their O&M costs. Remote sensors, including both the existing satellite rain products (SRPs) and radar imagery (RI), can complete the spatial distribution of rainfall and optimise the cost of observations. While most SRPs are based on re-analysis and have a lag in availability, RI can be obtained in near real time and is becoming increasingly popular in weather forecasting applications. Unfortunately, actual rainfall forecasts from RI observations are not accurate enough for real-time monitoring of drainage systems. In this paper, the Colour Pattern Regression (CPR) algorithm is used to recalibrate the 6 h rainfall values from RI provided by the Agencia Estatal de Meteorología (AEMET) with the observed rain gauge data, using as a case study the metropolitan area of Palma (Spain).
Comparison of Time-Lapse Ground-Penetrating Radar and Electrical Resistivity Tomography Surveys for Detecting Pig (Sus spp.) Cadaver Graves in an Australian Environment
Authors: Berezowski Victoria , Mallett Xanthé , Seckiner Dilan , Crebert Isabella , Ellis Justin , Rau Gabriel C. , Moffat Ian
Published: September 2024

Locating clandestine graves presents significant challenges to law enforcement agencies, necessitating the testing of grave detection techniques. This experimental study, conducted under Australian field conditions, assesses the effectiveness of time-lapse ground-penetrating radar (GPR) and electrical resistivity tomography (ERT) in detecting pig burials as simulated forensic cases. The research addresses two key questions: (1) observability of graves using GPR and ERT, and (2) changes in geophysical responses with reference to changing climatic conditions. The principal novelty of this research is its Australian focus—this is the first time-lapse GPR and ERT study used to locate clandestine graves in Australia. The results reveal that both GPR and ERT can detect graves; however, ERT demonstrates greater suitability in homogeneous soil and anomalously wet climate conditions, with the detectability affected by grave depth. This project also found that resistivity values are likely influenced by soil moisture and decomposition fluids; however, these parameters were not directly measured in this study. Contrastingly, although GPR successfully achieved 2 m penetration in each survey, the site’s undeveloped soil likely resulted in inconsistent detectability. The findings underscore the significance of site-specific factors when employing GPR and/or ERT for grave detection, including soil homogeneity, climate conditions, water percolation, and body decomposition state. These findings offer practical insights into each technique’s utility as a search tool for missing persons, aiding law enforcement agencies with homicide cases involving covert graves.
Has the Pilot Project of Innovative Cities Increased Economic Growth? An Empirical Study Based on Chinese Cities
Authors: Xu Enni , Xiao Zihan , Wang Zhengwen
Published: September 2024

In an era of global economic slowdown, effectively stimulating urban economic development has become a critical challenge for governments around the world. Based on the panel data of 280 prefecture-level cities in China from 2006 to 2017, this study adopts the double-difference method to evaluate the impacts of innovative cities pilot policies on urban economic growth, explore the mechanism through the intermediary effect model, and study the heterogeneity of cities with different development endowments by sub-samples. This study shows the following: (1) The policy of innovative pilot cities has significantly promoted their economic growth: GDP growth rates in the pilot cities are 1.14 percent higher than those in non-pilot cities. (2) The innovative city policy can effectively improve technological progress and human capital, thereby promoting economic growth. (3) The promotion effect of the pilot policy on the economy varies by region, city size, administration grade, market level, and government efficiency. Specifically, the policies have the most substantial positive effects in cities with lower administrative levels, smaller sizes, less market orientation, and higher government efficiency. This research, based on the city data from the world’s largest economy, evaluates the impact of government intervention—targeted urban innovation policies—on economic development, providing valuable insights into how innovation policies can be tailored and optimized for diverse urban contexts.
DSC-Net: Enhancing Blind Road Semantic Segmentation with Visual Sensor Using a Dual-Branch Swin-CNN Architecture
Authors: Yuan Ying , Du Yu , Ma Yan , Lv Hejun
Published: September 2024

In modern urban environments, visual sensors are crucial for enhancing the functionality of navigation systems, particularly for devices designed for visually impaired individuals. The high-resolution images captured by these sensors form the basis for understanding the surrounding environment and identifying key landmarks. However, the core challenge in the semantic segmentation of blind roads lies in the effective extraction of global context and edge features. Most existing methods rely on Convolutional Neural Networks (CNNs), whose inherent inductive biases limit their ability to capture global context and accurately detect discontinuous features such as gaps and obstructions in blind roads. To overcome these limitations, we introduce Dual-Branch Swin-CNN Net(DSC-Net), a new method that integrates the global modeling capabilities of the Swin-Transformer with the CNN-based U-Net architecture. This combination allows for the hierarchical extraction of both fine and coarse features. First, the Spatial Blending Module (SBM) mitigates blurring of target information caused by object occlusion to enhance accuracy. The hybrid attention module (HAM), embedded within the Inverted Residual Module (IRM), sharpens the detection of blind road boundaries, while the IRM improves the speed of network processing. In tests on a specialized dataset designed for blind road semantic segmentation in real-world scenarios, our method achieved an impressive mIoU of 97.72%. Additionally, it demonstrated exceptional performance on other public datasets.
Eddy Current Array for Defect Detection in Finely Grooved Structure Using MSTSA Network
Authors: Gao Shouwei , Zheng Yali , Li Shengping , Zhang Jie , Bai Libing , Ding Yaoyu
Published: September 2024

In this paper, we focus on eddy current array (ECA) technology for defect detection in finely grooved structures of spinning cylinders, which are significantly affected by surface texture interference, lift-off distance, and mechanical dither. Unlike a single eddy current coil, an ECA, which arranges multiple eddy current coils in a specific configuration, offers not only higher accuracy and efficiency for defect detection but also the inherent properties of space and time for signal acquisition. To efficiently detect defects in finely grooved structures, we introduce a spatiotemporal self-attention mechanism to ECA testing, enabling the detection of defects of various sizes. We propose a Multi-scale SpatioTemporal Self-Attention Network for defect detection, called MSTSA-Net. In our framework, Temporal Attention (TA) and Spatial Attention (SA) blocks are incorporated to capture the spatiotemporal features of defects. Depth-wise and point-wise convolutions are utilized to compute channel weights and spatial weights for self-attention, respectively. Multi-scale features of space and time are extracted separately in a pyramid manner and then fused to regress the bounding boxes and confidence levels of defects. Experimental results show that the proposed method significantly outperforms not only traditional image processing methods but also state-of-the-art models, such as YOLOv3-SPP and Faster R-CNN, with fewer parameters and lower FLOPs in terms of Recall and F1 score.
Deep Deterministic Policy Gradient-Based Resource Allocation Considering Network Slicing and Device-to-Device Communication in Mobile Networks
Authors: de Souza Lopes Hudson Henrique , Ferreira Lima Lucas Jose , de Lima Soares Telma Woerle , Teles Vieira Flávio Henrique
Published: September 2024

Next-generation mobile networks, such as those beyond the 5th generation (B5G) and 6th generation (6G), have diverse network resource demands. Network slicing (NS) and device-to-device (D2D) communication have emerged as promising solutions for network operators. NS is a candidate technology for this scenario, where a single network infrastructure is divided into multiple (virtual) slices to meet different service requirements. Combining D2D and NS can improve spectrum utilization, providing better performance and scalability. This paper addresses the challenging problem of dynamic resource allocation with wireless network slices and D2D communications using deep reinforcement learning (DRL) techniques. More specifically, we propose an approach named DDPG-KRP based on deep deterministic policy gradient (DDPG) with K-nearest neighbors (KNNs) and reward penalization (RP) for undesirable action elimination to determine the resource allocation policy maximizing long-term rewards. The simulation results show that the DDPG-KRP is an efficient solution for resource allocation in wireless networks with slicing, outperforming other considered DRL algorithms.
Assessing the Quality of Solvent-Assisted Lipid Bilayers Formed at Different Phases and Aqueous Buffer Media: A QCM-D Study
Authors: Lavrič Marta , Bar Laure , Villanueva Martin E. , Losada-Pérez Patricia , Iglič Aleš , Novak Nikola , Cordoyiannis George
Published: September 2024

Supported lipid bilayers (SLBs) are low-complexity biomimetic membranes, serving as popular experimental platforms to study membrane organization and lipid transfer, membrane uptake of nanoparticles and biomolecules, and many other processes. Quartz crystal microbalance with dissipation monitoring has been utilized to probe the influence of several parameters on the quality of SLBs formed on Au- and SiO2-coated sensors. The influence of the aqueous medium (i.e., buffer type) and the adsorption temperature, above and below the lipid melting point, is neatly explored for SLBs of 1,2-dimyristoyl-sn-glycero-3-phosphocholine and 1,2-dipalmitoyl-sn-glycero-3-phosphocholine formed by a solvent exchange. Below the lipid melting temperature, quality variations are observed upon the formation on Au and SiO2 surfaces, with the SLBs being more homogeneous for the latter. We further investigate how the buffer affects the detection of lipid melting in SLBs, a transition that necessitates high-sensitivity and time-consuming surface-sensitive techniques to be detected.
Preservation and Protection of Cultural Heritage: Vibration Monitoring and Seismic Vulnerability of the Ruins of Carmo Convent (Lisbon)
Authors: Mendes Nuno , Bianchini Nicoletta , Karanikoloudis Georgios , Blyth Anna , Scacco Jacopo , Flores Salazar Luis Gerardo , Cullimore Cassie , Jain Lavina
Published: September 2024

Preservation of cultural heritage sites is of paramount importance. The ruins of Carmo Convent in Lisbon stand as a poignant reminder of the city’s rich history, but challenges regarding structural integrity and safety are present in a highly populated and touristic area. In this paper, a comprehensive study of the Carmo Convent is presented, focused on non-destructive testing (NDT), structural health monitoring (SHM) and numerical modelling. Given its state of ruin and historical relevance, the study relied heavily on NDT. Additionally, a metro line passing underneath the convent raised concerns regarding potential hazards from induced vibrations. Thus, metro vibration monitoring (MVM) was implemented to assess the impact of induced vibrations on the structure. One of the challenges was the scarcity of standards specific to historic structures. However, through a combination of finite element method (FEM) and discrete element method (DEM) numerical modelling, valuable insights into the current condition of the structure were obtained. MVM revealed that the maximum velocity induced by metro activities remained within safe limits, indicating minimal impact. These results not only provide crucial information on structural preservation but also empower stakeholders to make informed decisions regarding the implementation of protective measures.
Real-Time Air-Writing Recognition for Arabic Letters Using Deep Learning
Authors: Qedear Aseel , AlMatrafy Aldanh , Al-Sowat Athary , Saigh Abrar , Alayed Asmaa
Published: September 2024

Learning to write the Arabic alphabet is crucial for Arab children’s cognitive development, enhancing their memory and retention skills. However, the lack of Arabic language educational applications may hamper the effectiveness of their learning experience. To bridge this gap, SamAbjd was developed, an interactive web application that leverages deep learning techniques, including air-writing recognition, to teach Arabic letters. SamAbjd was tailored to user needs through extensive surveys conducted with mothers and teachers, and a comprehensive literature review was performed to identify effective teaching methods and models. The development process involved gathering data from three publicly available datasets, culminating in a collection of 31,349 annotated images of handwritten Arabic letters. To enhance the dataset’s quality, data preprocessing techniques were applied, such as image denoising, grayscale conversion, and data augmentation. Two models were experimented with using a convolution neural network (CNN) and Visual Geometry Group (VGG16) to evaluate their effectiveness in recognizing air-written Arabic characters. Among the CNN models tested, the standout performer was a seven-layer model without dropout, which achieved a high testing accuracy of 96.40%. This model also demonstrated impressive precision and F1-score, both around 96.44% and 96.43%, respectively, indicating successful fitting without overfitting. The web application, built using Flask and PyCharm, offers a robust and user-friendly interface. By incorporating deep learning techniques and user feedback, the web application meets educational needs effectively.
Detecting Denial of Service Attacks (DoS) over the Internet of Drones (IoD) Based on Machine Learning
Authors: Alsumayt Albandari , Nagy Naya , Alsharyofi Shatha , Al Ibrahim Noor , Al-Rabie Renad , Alahmadi Resal , Alesse Roaa Ali , Alahmadi Amal A.
Published: September 2024

The use of Unmanned Aerial Vehicles (UAVs) or drones has increased lately. This phenomenon is due to UAVs’ wide range of applications in fields such as agriculture, delivery, security and surveillance, and construction. In this context, the security and the continuity of UAV operations becomes a crucial issue. Spoofing, jamming, hijacking, and Denial of Service (DoS) attacks are just a few categories of attacks that threaten drones. The present paper is focused on the security of UAVs against DoS attacks. It illustrates the pros and cons of existing methods and resulting challenges. From here, we develop a novel method to detect DoS attacks in UAV environments. DoS attacks themselves have many sub-categories and can be executed using many techniques. Consequently, there is a need for robust protection and mitigation systems to shield UAVs from DoS attacks. One promising security solution is intrusion detection systems (IDSs). IDs paired with machine learning (ML) techniques provide the ability to greatly reduce the risk, as attacks can be detected before they happen. ML plays an important part in improving the performance of IDSs. The many existing ML models that detect DoS attacks on UAVs each carry their own strengths and limitations.
Youth Engagement in Sexual Violence Prevention Programs and Research: A Systematic Review
Authors: Hjelm Linnea L.
Published: September 2024

Youth in the US experience high rates of sexual violence. Historically, adults design and deliver preventive initiatives, with youth limited to participants and recipients. The use of community-based participatory research and other participatory approaches can expand the reach and impact of adolescent sexual violence prevention initiatives by positioning youth as leaders and co-researchers. This systematic review explores both adolescent violence prevention programs and research projects that take a participatory, youth-engaged, or youth-led approach. This review aims to understand what activities youth are involved in and how they are equipped for their roles. Following PRISMA guidelines, the review located eight eligible articles that involved high school youth or younger as more than data, focused on adolescent sexual or dating violence prevention, and whose programs or studies were conducted in the United States. I reviewed each article for programmatic and study specifics, with special attention to which stages youth participated in and how capacity-building was incorporated. The results revealed that youth can participate in a variety of activities, though they are involved in certain stages more than others, and that capacity-building ranged in breadth and frequency. I call researchers to detail youth activities and training, and explain clearly their participatory approach and decisions.
Low-Loaded Pt Nanoparticles Supported on Electrochemically Exfoliated Graphene as a Sustainable Catalyst for Electrochemical Ethanol Oxidation
Authors: Srejić Irina , Maksić Aleksandar , Novaković Mirjana , Potočnik Jelena , Rakočević Lazar , Živković Sanja , Smiljanić Milutin
Published: September 2024

Securing ever-increasing energy demands while reducing resilience on fossil fuels is a major task of modern society. Fuel cells are devices in which the chemical energy of various fuels can be converted into clean electricity. Direct ethanol fuel cells (DEFC) are increasingly popular for their eco-friendliness and significantly easier liquid fuel manipulation compared to hydrogen-fed fuel cells. Carbon-supported Pt nanoparticles are considered reference catalysts for fuel oxidation in DEFCs. Several challenges hinder DEFC commercialization: high Pt-loading, Pt poisoning by CO intermediates, and the instability of the Pt and carbon supports. This work demonstrates an efficient electrocatalyst for ethanol oxidation reaction (EOR) composed of Pt nanoparticles supported on electrochemically exfoliated graphene (Pt/el-rGO). Graphene was obtained through anodic electrochemical exfoliation using graphitic tape as the anode, while Pt nanoparticles were synthesized using chemical reduction with formic acid. As-obtained Pt/el-rGO with only 7.5 wt.% Pt was characterized using TEM, SEM, and XPS. Pt/el-rGO exhibited notably higher EOR catalytic activity in an alkaline electrolyte than the Pt/C benchmark. This enhancement can be linked with the functional groups present on the graphene support, which facilitate ethanol dehydrogenation as the first step in the EOR mechanism and thus enhance reaction kinetics on Pt-active sites.
Overview of Recent Solar Photovoltaic Cooling System Approach
Authors: Ahmed Yaareb Elias , Maghami Mohammad Reza , Pasupuleti Jagadeesh , Danook Suad Hassan , Basim Ismail Firas
Published: September 2024

In recent years, research communities have shown significant interest in solar energy systems and their cooling. While using cells to generate power, cooling systems are often used for solar cells (SCs) to enhance their efficiency and lifespan. However, during this conversion process, they can generate heat. This heat can affect the performance of solar cells in both advantageous and detrimental ways. Cooling cells and coordinating their use are vital to energy efficiency and longevity, which can help save energy, reduce energy costs, and achieve global emission targets. The primary objective of this review is to provide a thorough and comparative analysis of recent developments in solar cell cooling. In addition, the research discussed here reviews and compares various cooling systems that can be used to improve cell performance, including active cooling and passive cooling. The outcomes reveal that phase-change materials (PCMs) help address critical economic goals, such as reducing the cost of PV degradation, while enhancing the lifespan of solar cells and improving their efficiency, reliability, and quality. Active PCMs offer precise control, while passive PCMs are simpler and more efficient in terms of energy use, but they offer less control over temperature. Moreover, an innovative review of advanced cooling methods is presented, highlighting their potential to improve the efficiency of solar cells.
Catalytic Ozonation Treatment of Coal Chemical Reverse Osmosis Concentrate: Water Quality Analysis, Parameter Optimization, and Catalyst Deactivation Investigation
Authors: Qin Yihe , Yuan Run , Wang Shaozhou , Zhang Xuewei , Luo Shaojun , He Xuwen
Published: September 2024

Catalytic ozone oxidation, which is characterized by strong oxidizing properties and environmental friendliness, has been widely used in organic wastewater treatments. However, problems such as a low organic pollutant removal efficiency and unstable operation during the catalytic ozone treatment process for wastewater remain. To address these disadvantages, in this study, the treatment efficacy of catalytic ozone oxidation on a coal chemical reverse osmosis concentrate was investigated. The basic water quality indicators of the chemical reverse osmosis concentrate were analyzed. The effects of initial pollutant concentration, pH, ozone concentration, and catalyst concentration on the COD removal rate from the coal chemical reverse osmosis concentrate were explored. Water quality indicators of the chemical reverse osmosis concentrate before and after the catalytic ozone treatment were studied using spectroscopic analysis methods. The RO concentrate demonstrated large water quality fluctuations, and the catalytic ozonation process removed most of the pollutants from the treated wastewater. A possible deactivation mechanism of the ozone catalyst was also proposed. This study provides a theoretical reference and technical support for the long-term, efficient, and stable removal of organic pollutants from coal chemical reverse osmosis concentrate using a catalytic ozone oxidation process in practical engineering applications.
Source Apportionment and Risk Assessment of Potentially Toxic Elements Based on PCA and PMF Model in Black Soil Area of Hailun City, Northeast China
Authors: Yang Zhiwei , Yu Junbo , Yang Ke , Zhang Qipeng , Chen Yangyang , Qiao Shaozhong
Published: September 2024

This study assessed the presence of potentially toxic elements (PTEs) in China’s northeastern black soil belt, an area with limited prior research. We collected 304 soil samples (0–20 cm) from Gonghe Town, Hailun City, and analyzed the PTE contamination degree using the single-factor pollution index and Nemerow pollution index. The results demonstrated that the mean concentrations of arsenic (As), cadmium (Cd), chromium (Cr), copper (Cu), mercury (Hg), nickel (Ni), lead (Pb), and zinc (Zn) were 11.16, 0.11, 65.29, 22.56, 0.03, 27.07, 26.09, and 66.01 mg/kg, respectively. Source apportionment was conducted via correlation analysis, principal component analysis, and positive matrix factorization, identifying four main sources: natural (33.2%), irrigation (29.5%), fuel (23.4%), and fertilizer (13.2%). The ecological risk index indicated a slight ecological risk, while the human health risk showed that non-carcinogenic risks were negligible and carcinogenic risks were acceptable. Our findings emphasize the need to prioritize controlling PTEs from fertilizer, particularly cadmium, and to a lesser extent, irrigation and fuel sources, focusing on As, Pband Hg. This research provides critical insights for policymakers aiming to manage PTE contamination in black soils.