bluuebunny/crossref_metadata_2025 huggingface dataset:
Virtual Simulation and Experiment of Quality Inspection Robot Workstation
Authors: Liu Zhenlei , Wang Dan , Li Yueyue , Zhu Wanan , Ni Haotian , Qi Ji
Published: July 2024

(1) Background: Quality inspection robots are widely used in automated production lines. However, the design cycle is long, iteration costs are high, and algorithm development is challenging. It is difficult to perform effective validation during the design phase. Applying virtual reality technology to simulate quality inspection robot workstations offers a new approach to addressing the issues. (2) Methods: The research creates a simulation platform for quality inspection robot workstations based on a virtual reality architecture. The platform creates an immersive quality inspection robot workstation operation interface and conducts testing of the inspection process, thereby validating the rationality of the quality inspection robot workstation design. Building upon this foundation, we conducted experimental comparisons of various defect detection algorithms. (3) Results: Compared to the traditional YOLOv7 algorithm, the improved YOLOv7 algorithm achieved an 18.1% increase in recognition precision. Experimental results demonstrate that the quality inspection robot workstation simulation platform can be applied to validating workstation design proposals. (4) Conclusions: It has a positive impact on reducing the research and development costs of quality inspection robot workstations and shortening the defect recognition algorithm development cycle.
The Diagnosis-Effective Sampling of Application Traces
Authors: Poghosyan Arnak , Harutyunyan Ashot , Davtyan Edgar , Petrosyan Karen , Baloian Nelson
Published: July 2024

Distributed tracing is cutting-edge technology used for monitoring, managing, and troubleshooting native cloud applications. It offers a more comprehensive and continuous observability, surpassing traditional logging methods, and is indispensable for navigating modern complex software architectures. However, the sheer volume of generated traces is staggering in distributed applications, and the direct storage and utilization of every trace is impractical due to associated operational costs. This entails a sampling strategy to select which traces warrant storage and analysis. Historically, sampling methods have included a rate-based approach, often relying heavily on a manual configuration. There is a need for a more intelligent approach, and we propose a hierarchical sampling methodology to address multiple requirements concurrently. Initial rate-based sampling mitigates the overwhelming volume of traces, as no further analysis can be performed on this level. In the next stage, more nuanced analysis is facilitated based on the previous foundation, incorporating information regarding trace properties and ensuring the preservation of vital process details even under extreme conditions. This comprehensive approach not only aids in the visualization and conceptualization of applications but also enables more targeted analysis in later stages. As we delve deeper into the sampling hierarchy, the technique becomes tailored to specific purposes, such as the simplification of application troubleshooting. In this context, the sampling strategy prioritizes the retention of erroneous traces from dominant processes, thus facilitating the identification and resolution of underlying issues. The focus of this paper is to reveal the impact of sampling on troubleshooting efficiency. Leveraging intelligent and explainable artificial intelligence solutions enables the detection of malfunctioning microservices and provides transparent insights into root causes. We advocate for using rule-induction systems, which offer explainability and efficacy in decision-making processes. By integrating advanced sampling techniques with machine-learning-driven intelligence, we empower organizations to navigate the complexities of large-scale distributed cloud environments effectively.
Machine Learning-Based Feature Extraction and Classification of EMG Signals for Intuitive Prosthetic Control
Authors: Kok Chiang Liang , Ho Chee Kit , Tan Fu Kai , Koh Yit Yan
Published: July 2024

Signals play a fundamental role in science, technology, and communication by conveying information through varying patterns, amplitudes, and frequencies. This paper introduces innovative methodologies for processing electromyographic (EMG) signals to develop artificial intelligence systems capable of decoding muscle activity for controlling arm movements. The study investigates advanced signal processing techniques and machine learning classification algorithms using the GRABMyo dataset, aiming to enhance prosthetic control systems and rehabilitation technologies. A comprehensive analysis was conducted on signal processing techniques, including signal filtering and discrete wavelet transform (DWT), alongside a composite feature set comprising Mean Absolute Value (MAV), Waveform Length (WL), Zero Crossing (ZC), Slope Sign Changes (SSC), Root Mean Square (RMS), Enhanced Waveform Length (EWL), and Enhanced Mean Absolute Value (EMAV). These features, refined through Linear Discriminant Analysis (LDA) for dimensionality reduction, were classified using Support Vector Machine (SVM) algorithms. Signal filtering and DWT improved signal quality, facilitating better feature extraction, while the diverse feature set enhanced classification accuracy. LDA further improved accuracy by isolating the most informative features, and the SVM achieved optimal performance in decoding complex EMG patterns. Machine learning models, including K-Nearest Neighbor (KNN), Naïve Bayes (NB), and the SVM, were evaluated, with the SVM outperforming the others. The significance of these results lies in their potential applications in prosthetic control systems and rehabilitation technologies. By accurately decoding muscle activity, the developed systems can facilitate more intuitive and responsive robotic arm movements, contributing to the advancement of innovative solutions for individuals requiring prosthetic devices or undergoing rehabilitation, hence improving the quality of life for users. This research marks a significant step forward in the integration of advanced signal processing and machine learning in the field of EMG analysis.
The Influence of AI and AR Technology in Personalized Recommendations on Customer Usage Intention: A Case Study of Cosmetic Products on Shopee
Authors: Adawiyah Siti Rabiatul , Purwandari Betty , Eitiveni Imairi , Purwaningsih Erisva Hakiki
Published: July 2024

With the rapid growth of Augmented Reality (AR) in e-commerce, it is necessary to conduct in-depth studies related to the integration of AR with Artificial Intelligence (AI) technology to improve personalization in product recommendations. AI and AR are expected to work together, where AI systems analyze consumer data to provide more suitable product recommendations, while AR helps consumers visualize these recommendations in the real world. This research explores the influence of AI and AR technology integration in personalized recommendations on customer usage intention, with a focus on the cosmetics industry on the e-commerce platform Shopee. Adopting the Technology Acceptance Model (TAM) and the Theory of Planned Behavior (TPB), this research uses quantitative methods with the try-on feature of cosmetic products as the main focus. With a total number of 387 respondents, the results of the PLS-SEM analysis revealed factors impacting the intention to use, such as perceived ease of use, perceived usefulness, and users’ perceived trust, on the intention to use personalized recommendations. This research contributes to the understanding of AI–AR technology acceptance in the context of online shopping, particularly in the cosmetics sector.
Trend Analysis and Spatial Source Attribution of Surface Ozone in Chaozhou, China
Authors: Huang Zhongwen , Tong Lei , Zhu Xuchu , Su Junxiao , Lu Shaoyun , Xiao Hang
Published: July 2024

Surface ozone (O3), a critical air pollutant, poses significant challenges in urban environments, as exemplified by the city of Chaozhou in southeastern China. This study employs a novel combination of trend analysis and spatial source attribution techniques to evaluate the long-term dynamics of surface ozone and identify its sources. Utilizing the Kolmogorov–Zurbenko (KZ) filter and percentile regression, we analyzed the temporal trends of daily maximum 8 h moving average ozone (MDA8 O3) concentrations from 2014 to 2023. Our analysis revealed a general long-term downward trend in MDA8 O3 values alongside notable monthly fluctuations, with peak concentrations typically occurring in October and April. Additionally, the percentile regression analysis demonstrated a significant downward trend in MDA8 O3 concentrations across nearly all percentiles, with larger decline rates at higher percentiles, highlighting the effectiveness of local and regional O3 management strategies in Chaozhou. The changes in MDA8 O3 concentrations were mainly influenced by the short-term component, contributing 62.2%, while the contribution of the long-term fraction is relatively small. This suggests a significant influence of immediate meteorological conditions and transient pollution events on local O3 levels. To further elucidate the origins of high O3 concentrations, trajectory cluster analysis, trajectory sector analysis (TSA), and potential source contribution function (PSCF) analysis were conducted. The trajectory cluster analysis revealed that the northeast air mass was the main transport air mass in Chaozhou during the study period, accounting for 39.1% of occurrences. The northeast cluster C with medium-distance trajectories corresponds to higher concentration of O3, which may be the main transport pathway of O3 pollution in Chaozhou. TSA corroborates these findings, with northeast sectors 1, 2, and 3 accounting for 50.3% of trajectory residence time and contributing 52.2% to O3 levels in Chaozhou. PSCF results further indicate potential high O3 sources from the northeast, especially in autumn. This comprehensive analysis suggests that Chaozhou’s elevated O3 levels are influenced by both regional transport from the northeast and local emissions. These findings offer crucial insights into the temporal dynamics of surface O3 in Chaozhou, paving the way for more effective and targeted air quality management strategies.
Impact of Air Emission Reduction Measures during the Asian Games on Air Quality and Health Risks in Hangzhou and Surrounding Cities
Authors: Huang Jing , Wang Jiayan , Hu Yunan , Zhao Hui
Published: July 2024

The purpose of this study was to analyze the air quality in Hangzhou and its surrounding areas during the 2023 Asian Games and assess the impact of safeguard measures on air quality. By comparing air quality monitoring data from Hangzhou and nearby cities between 23 September 2023, and 8 October 2023, with the same period in 2022, the analysis focused on the changes in air quality and the impact of PM2.5 and O3 on human health. The results show that during the 2023 Asian Games in Hangzhou, compared to the same period in 2022, the concentrations of pollutants showed the following changes: PM10 and NO2 concentrations decreased by 16.1% and 34.1%, respectively. PM2.5, CO, and O3 concentrations increased by 0.9%, 9.5%, and 14.4%, respectively. Spatially, compared with the same period in 2022, the PM2.5 concentration in Quzhou City decreased the most, reaching 23%, while the PM2.5 concentration in Huzhou City increased the most, reaching 27.1%. The largest decrease in PM10 concentration is in Wenzhou City, which is up to 28.2%, while the largest increase is in Zhoushan City, which is 9.2%. The concentration of NO2 generally decreases in all regions, with the biggest decrease in Zhoushan City, which reaches 36.2%. The concentration of CO only decreases in Shaoxing, and the highest increase is in Huzhou City. In terms of O3, the largest proportion increase is 23% in Ningbo. During the 2023 Asian Games in Hangzhou, the number of deaths from all-cause and cardiovascular diseases caused by short-term exposure to PM2.5 was 1780 and 795, respectively, which was 8.2% lower than the same period in 2022. During the Asian Games, the number of deaths from all-cause and cardiovascular diseases due to short-term exposure to O3 was 7332 and 3177, respectively, an increase of 2.8% compared with the same period in 2022.
Dew and Rain Evolution from Climate Change in Semi-Arid South-Western Madagascar between 1991 and 2033 (Extrapolated)
Authors: Rasoafaniry Adriana , Muselli Marc , Beysens Daniel
Published: July 2024

In the context of global warming and the increasing scarcity of fresh water resources, it becomes significant to evaluate the contribution and evolution of non-rainfall waters such as dew. This study therefore aims to evaluate the relative dew and rain contributions in three sites of south-western of Madagascar (Ifaty, Toliara, and Andremba), a semi-arid region which suffers from a strong water deficit. The studied period is 1/1991–7/2023, with extrapolation to 7/2033. Dew is calculated from meteo data by using a well-established energy model. The extrapolation of dew and rain follows an artificial neural network approach. It is found that dew forms regularly (2–3 days on average between events), in contrast to rain (10–15 days). The evolutions of dew and rain are similar, with an increase from 1991 to 2000, a decrease up to 2020 and a further increase until 2033. These oscillations follow the Indian Ocean dipole variations and should be influenced by climate change. Dew contributions to the water balance remain modest on a yearly basis (3–4%) but is important during the dry season (Apr.–Oct.), up to 30%. Dew therefore appears to be a reliable and sustainable resource for plants, small animals, and the population, especially during droughts.
Radon Concentration in Air and Evaluation of the Radiation Dose in Villages near Shizhuyuan, Southern Hunan, China
Authors: Tan Wanyu , Nie Yixun
Published: July 2024

Radon is one of the important natural sources of radiation and pollutants. When radon and its progeny are inhaled by the human body, they can cause radiation damage to the respiratory system and can lead to lung cancer. Indoor and outdoor radon concentrations were measured in five villages near Shizhuyuan W-polymetallic deposit using a RAD7 detector; moreover, the corresponding radiation dose and lifetime risk probability were evaluated. The results show that the average value of indoor radon concentration was 216.6 ± 121.1 Bq m−3, which is above the worldwide average indoor radon level of 40 Bq m−3, and the average outdoor value was 34.6 ± 13.4 Bq m−3, which is higher than the worldwide outdoor average of 10 Bq m−3. A total of 42% of the dwellings investigated in our study had a higher radon level than the Chinese permissible indoor radon level of 200 Bq m−3. The total annual effective dose ranged from 5.21 mSv y−1 to 49.38 mSv y−1, with an average value of 14.63 mSv y−1, which is higher than the ICRP recommended value of 3–10 mSv y−1. This average total dose value corresponds to an average lifetime risk probability of 5.8% for residents in the whole study area.
aPEAch: Automated Pipeline for End-to-End Analysis of Epigenomic and Transcriptomic Data
Authors: Xiropotamos Panagiotis , Papageorgiou Foteini , Manousaki Haris , Sinnis Charalampos , Antonatos Charalabos , Vasilopoulos Yiannis , Georgakilas Georgios K.
Published: July 2024

With the advent of next-generation sequencing (NGS), experimental techniques that capture the biological significance of DNA loci or RNA molecules have emerged as fundamental tools for studying the epigenome and transcriptional regulation on a genome-wide scale. The volume of the generated data and the underlying complexity regarding their analysis highlight the need for robust and easy-to-use computational analytic methods that can streamline the process and provide valuable biological insights. Our solution, aPEAch, is an automated pipeline that facilitates the end-to-end analysis of both DNA- and RNA-sequencing assays, including small RNA sequencing, from assessing the quality of the input sample files to answering meaningful biological questions by exploiting the rich information embedded in biological data. Our method is implemented in Python, based on a modular approach that enables users to choose the path and extent of the analysis and the representations of the results. The pipeline can process samples with single or multiple replicates in batches, allowing the ease of use and reproducibility of the analysis across all samples. aPEAch provides a variety of sample metrics such as quality control reports, fragment size distribution plots, and all intermediate output files, enabling the pipeline to be re-executed with different parameters or algorithms, along with the publication-ready visualization of the results. Furthermore, aPEAch seamlessly incorporates advanced unsupervised learning analyses by automating clustering optimization and visualization, thus providing invaluable insight into the underlying biological mechanisms.
Oligomer Formation by Physiologically Relevant C-Terminal Isoforms of Amyloid β-Protein
Authors: Pandey Rachit , Urbanc Brigita
Published: July 2024

Alzheimer’s disease (AD) is a neurological disorder associated with amyloid β-protein (Aβ) assembly into toxic oligomers. In addition to the two predominant alloforms, Aβ1−40 and Aβ1−42, other C-terminally truncated Aβ peptides, including Aβ1−38 and Aβ1−43, are produced in the brain. Here, we use discrete molecular dynamics (DMD) and a four-bead protein model with amino acid-specific hydropathic interactions, DMD4B-HYDRA, to examine oligomer formation of Aβ1−38, Aβ1−40, Aβ1−42, and Aβ1−43. Self-assembly of 32 unstructured monomer peptides into oligomers is examined using 32 replica DMD trajectories for each of the four peptides. In a quasi-steady state, Aβ1−38 and Aβ1−40 adopt similar unimodal oligomer size distributions with a maximum at trimers, whereas Aβ1−42 and Aβ1−43 oligomer size distributions are multimodal with the dominant maximum at trimers or tetramers, and additional maxima at hexamers and unidecamers (for Aβ1−42) or octamers and pentadecamers (for Aβ1−43). The free energy landscapes reveal isoform- and oligomer-order specific structural and morphological features of oligomer ensembles. Our results show that oligomers of each of the four isoforms have unique features, with Aβ1−42 alone resulting in oligomers with disordered and solvent-exposed N-termini. Our findings help unravel the structure–function paradigm governing oligomers formed by various Aβ isoforms.
De Novo Design of Inhibitors of DNA Methyltransferase 1: A Critical Comparison of Ligand- and Structure-Based Approaches
Authors: Prado-Romero Diana L. , Saldívar-González Fernanda I. , López-Mata Iván , Laurel-García Pedro A. , Durán-Vargas Adrián , García-Hernández Enrique , Sánchez-Cruz Norberto , Medina-Franco José L.
Published: July 2024

Designing and developing inhibitors against the epigenetic target DNA methyltransferase (DNMT) is an attractive strategy in epigenetic drug discovery. DNMT1 is one of the epigenetic enzymes with significant clinical relevance. Structure-based de novo design is a drug discovery strategy that was used in combination with similarity searching to identify a novel DNMT inhibitor with a novel chemical scaffold and warrants further exploration. This study aimed to continue exploring the potential of de novo design to build epigenetic-focused libraries targeted toward DNMT1. Herein, we report the results of an in-depth and critical comparison of ligand- and structure-based de novo design of screening libraries focused on DNMT1. The newly designed chemical libraries focused on DNMT1 are freely available on GitHub.
Differences in Children and Adolescents with Depression before and after a Remediation Program: An Event-Related Potential Study
Authors: Zygouris Nikolaos C.
Published: July 2024

Depression is clinically diagnosed when a defined constellation of symptoms manifests over a specific duration with notable severity. According to the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5), Major Depressive Disorder (MDD) is characterized by the presence of five or more symptoms persisting for at least two weeks. As a profound mental health condition affecting millions globally, depression presents a considerable challenge for researchers and clinicians alike. In pediatric and adolescent populations, depression can precipitate adverse outcomes, including substance abuse, academic difficulties, risky sexual behaviors, physical health problems, impaired social relationships, and a markedly elevated risk of suicide—up to thirty times higher than the general population. This paper details a study that evaluated the efficacy of Cognitive Behavioral Therapy (CBT) alone vs. CBT combined with selective serotonin reuptake inhibitors (SSRIs) in a treatment program. The study cohort comprised sixteen (16) children and adolescents diagnosed with depression (eight males and eight females) and sixteen (16) typically developing peers (eight males and eight females) aged from 9 to 15 years (Mean age = 11.94, standard deviation = 2.02). Initial assessments employed Event-Related Potentials (ERPs), the Children’s Depression Inventory (CDI), and reaction time measurements. The results reveal that participants with depression exhibit cognitive deficits in attention and memory, as evidenced by prolonged P300 latencies. Following intervention with either CBT alone or CBT combined with medication, the depressed participants demonstrated significant improvements, evidenced by lower CDI scores, reduced P300 latencies, and faster reaction times, both compared to their pre-treatment status and relative to the control group.
Impact of Pre-Sleep Visual Media Exposure on Dreams: A Scoping Review
Authors: Diushekeeva Ajar , Hidalgo Santiago , Zadra Antonio
Published: July 2024

A body of experimental research has aimed to investigate processes underlying dream formation by examining the effects of a range of pre-sleep stimuli and events on subsequent dream content. Given its ever-growing presence and salience in people’s everyday lives, pre-sleep media consumption stands out as a key variable that could influence people’s dreams. We conducted a scoping review to evaluate the experimental evidence of the effects of pre-sleep exposure to visual media on dream content. A systematic search on PubMed, PsycInfo, and Web of Science using terms related to moving visual media and dreams yielded 29 studies meeting the inclusion criteria. Overall, we found modest yet varied effects of pre-sleep exposure to visual media on dream content, with rates of stimulus-related incorporation ranging from 3% to 43% for REM dream reports, 4% to 30% for NREM sleep mentation reports, and between 11% and 35% for home dream reports. Our review highlights the large methodological heterogeneity and gaps across studies, the general difficulty in influencing dream content using pre-sleep exposure to visual media, and suggests promising venues for future research to advance our understanding of how and why digital media may impact people’s dreams.
Children and Young Adults with Epilepsy Exhibit an Interictal Autonomic Dysfunction: A Prospective Exploratory Study
Authors: Salluce Carmen , Cocciante Marco , Gazzillo Marisa , Ferrari Anna Rita , Battini Roberta , Santorelli Filippo Maria , Bartolini Emanuele
Published: July 2024

Dysautonomic disorders are an increasingly studied group of conditions, either as isolated diseases or associated with other neurological disorders. There is growing interest in understanding how dysautonomia affects people with epilepsy, who may report autonomic symptoms before, during and after seizures. Furthermore, autonomic abnormalities appear to play a role in sudden unexpected death in epilepsy, likely contributing to the increased mortality rate described in epilepsy. To better understand the association between epilepsy and dysautonomia, we explored electrochemical skin conductance in a group of 18 children and young adults with epilepsy compared to 15 age- and sex-matched healthy controls by the SudoscanTM test. We found a significant difference in terms of electrochemical skin conductance, suggesting that people with epilepsy suffer significantly reduced conductance in small nerve fibers. Within patients, values were significantly different according to the type of epilepsy and to neuroimaging results, with lower conductance values in epilepsies of unknown origin and in patients with morphological abnormalities of the brain. Using a non-invasive test, we identified altered conductance of small sympathetic nerve fibers in children and young adults with epilepsy, suggesting underlying dysautonomia. Further studies are needed to investigate this association and to clarify its neurobiological substrates.
Effects of Fast-Tempo and Binaural Beat Therapy Music during Warm-Up on Repeated Sprint Ability Test Performance among Young Soccer Players
Authors: Wang Songyan , Liu Cheng , Zhang Lin , Sun Cheuk-Kwan , Yang Shang-Yu
Published: July 2024

This prospective crossover study aimed to investigate the effect of binaural beat therapy music on soccer player performance. Between July 2023 and December 2023, 45 athletes (31 females/14 males, mean age = 20.47 ± 0.99) wore Bluetooth earphones through which one of the following was given during initial 20 min warm-up exercises before undergoing repeated sprint ability tests: no music/fast-tempo music/fast-tempo music with background binaural beat therapy music. Heart rate change after warm-up exercises/repeated sprint ability (RSA) tests and the time to finish RSA tests were recorded. Despite no significant difference in heart rate increase after warm-up between the two genders regardless of intervention, larger increases after RSA tests were found in males following any of the three interventions (all p < 0.01) with the most notable difference observed after fast-tempo music (p < 0.0001). A significant effect size (r = 0.2) correlated with fast-tempo music during warm-up in either gender. Binaural beat therapy music during warm-up reached a significant effect size only when all participants were considered, suggesting limited benefits.
Vagus Nerve Stimulation Therapy in Epilepsy: An Overview of Technical and Surgical Method, Patient Selection, and Treatment Outcomes
Authors: Abdennadher Myriam , Rohatgi Pratik , Saxena Aneeta
Published: July 2024

Epilepsy affects over 65 million people worldwide. One-third of people with epilepsy do not respond to medication and may benefit from surgery. Vagus nerve stimulation (VNS) is the first neuromodulation therapy for the treatment of drug-resistant epilepsy. This method is used in combination with anti-seizure medications in adults and in the pediatric population. VNS has also been demonstrated to have benefits for some epilepsy comorbidities, such as depression, and can be used in combination with other neuromodulation therapies in epilepsy. The authors present an overview of VNS physiology, patient selection, surgery and risks, neuromodulation therapy, and application to epilepsy comorbidities.
A Review of In-Flight Thermal Comfort and Air Quality Status in Civil Aircraft Cabin Environments
Authors: Wang Shanran , Cao Xiaodong , Miao Dan , Pang Liping , Li Jiayu
Published: July 2024

The civil aircraft cabin is enclosed and highly occupied, making it susceptible to a decline in indoor environmental quality. The environmental quality of civil aircraft cabins not only depends on objective factors such as temperature, relative humidity, and the presence of air pollutants such as carbon dioxide (CO2), carbon monoxide (CO), ozone (O3), particle matter (PM), and volatile organic compounds (VOCs) but also the subjective factors pertaining to the perceptions and health symptoms of passengers and crew. However, few studies have thoroughly examined the air quality and thermal comfort parameters that are measured during in-flight testing in airplane cabins, as well as the passengers’ subjective perceptions. In order to evaluate the in-flight thermal comfort and air quality status, this study conducted a review of the recent literature to compile data on primary categories, standard limits, and distribution ranges of in-flight environmental factors within civil aircraft cabins. Following a search procedure outlined in this paper, 54 papers were selected for inclusion. Utilizing the Monte Carlo method, the Predicted Mean Vote (PMV) distributions under different exercise intensities and clothing thermal resistance were measured with the in-cabin temperature and humidity from in-flight tests. Recommendations based on first-hand data were made to maintain the relative humidity in the cabin below 40%, ensure wind speed remains within the range of 0–1 m/s, and regulate the temperature between 25–27 °C (for summer) and 22–27 °C (for winter). The current estimated cabin air supply rate generally complies with the requirements of international standards. Additionally, potential carcinogenic and non-carcinogenic risks associated with formaldehyde, benzene, tetrachloroethylene, and naphthalene were calculated. The sorted data of in-flight tests and the evaluation of the subjective perception of the occupants provide an evaluation of current cabin thermal comfort and air quality status, which can serve as a reference for optimizing indoor environmental quality in future generations of civil aircraft cabins.
Managing Intervention Works for Conservation and Revitalization: A Case Study of the Bârnova Monastery, Iași
Authors: Onuțu Cătălin , Ungureanu Dragoș , Țăranu Nicolae , Isopescu Dorina Nicolina
Published: July 2024

This study offers insights into the management of intervention works aimed at conserving and revitalizing historical structures, focusing on the Bârnova Monastery in Iași, Romania. The study begins by contextualizing the broader challenges associated with preserving heritage churches and monastic buildings, elucidating the architectural characteristics and structural aspects typical of traditional Romanian Orthodox churches. Subsequently, the study delves into a detailed case analysis centered on the restoration of the medieval Bârnova Monastery, particularly its paramount structure, the Saint George Church, erected in the XVII century. This church exemplifies the traditional Orthodox architectural and structural norms prevalent during the medieval period. Through a structural diagnosis, the study identifies the vulnerabilities of the Saint George Church, which have been exacerbated by the impact of approximately 24 earthquakes of magnitudes exceeding 6.0 throughout its history. In response, a multifaceted approach to strengthening was devised, involving a combination of grouting and the installation of steel rods within vertically drilled galleries spanning the entire height of the walls. The adoption of this integrated strengthening strategy proved advantageous, significantly enhancing the seismic resilience of the church while simultaneously addressing the preservation needs of its historical features. This case study not only contributes to the body of knowledge on conservation and revitalization practices but also offers valuable insights into the effective management of intervention works for safeguarding heritage structures against seismic risks.
Experimental and Numerical Heat Transfer Assessment and Optimization of an IMSI Based Individual Building Block System of the Kingdom of Bahrain
Authors: Modi Payal Ashish , Mahmoud Abdelgadir Mohamed , Abakr Yousif Abdalla , Abdulqader Abdulla Ebrahim
Published: July 2024

The increase in energy consumption in Bahrain is a significant issue. Insulation blocks are crucial for reducing heat transfer from outside to inside buildings. However, there’s limited research on the thermal performance of Bahrain’s insulation building blocks. No research to date has been conducted in Bahrain to study the effect of plaster and insulation inserts on the R-value of the blocks. This study examines and optimizes the thermal resistance (R-value) of an ‘Integrated Masonry System International, Ltd. (IMSI)’ block, chosen due to its common use in Bahrain’s commercial and residential construction. The study involves experimental analysis using a hot box setup and numerical analysis through the finite element method (FEM), along with assessing the impact of insulation inserts in the block’s cavities. R-values are calculated and validated for accuracy. The R-value discrepancy between numerical and experimental findings is 2.411%, and between numerical and manufacturer’s data is 5.743%. It is also observed that a 25 mm external plaster, as required by Bahrain’s government (EWA), enhances the R-value by 79.34%. Furthermore, optimizing the IMSI block’s height increased the R-value by 10.67%.
Unveiling the Urban Morphology of Small Towns in the Eastern Qinba Mountains: Integrating Earth Observation and Morphometric Analysis
Authors: Zhao Xin , Wu Zuobin
Published: July 2024

In the context of the current information age, leveraging Earth observation (EO) technology and spatial analysis methods enables a more accurate understanding of the characteristics of small towns. This study conducted an in-depth analysis of the urban morphology of small towns in the Qinba Mountain Area of Southern Shaanxi by employing large-scale data analysis and innovative urban form measurement methods. The U-Net3+ model, based on deep learning technology, combined with the concave hull algorithm, was used to extract and precisely define the boundaries of 31,799 buildings and small towns. The morphological characteristics of the town core were measured, and the core areas of the small towns were defined using calculated tessellation cells. Hierarchical clustering methods were applied to analyze 12 characteristic indicators of 89 towns, and various metrics were calculated to determine the optimal number of clusters. The analysis identified eight distinct clusters based on the towns’ morphological differences. Significant morphological differences between the small towns in the Qinba Mountain Area were observed. The clustering results revealed that the towns exhibited diverse shapes and distributions, ranging from irregular and sparse to compact and dense forms, reflecting distinct layout patterns influenced by the unique context of each town. The use of the morphometric method, based on cellular and biological morphometry, provided a new perspective on the urban form and deepened the understanding of the spatial structure of the small towns from a micro perspective. These findings not only contribute to the development of quantitative morphological indicators for town development and planning but also demonstrate a novel, data-driven approach to conventional urban morphology studies.
Seismic Performance of Drop-In Anchors in Concrete under Shear and Tension
Authors: Sennah Khaled , Azimi Hossein , Ahmed Mizan , Hamoda Ahmed
Published: July 2024

This paper presents an experimental study conducted on the behavior of drop-in anchors in uncracked concrete slabs. Both seismic (cyclic) load tests and static load tests to collapse are performed on drop-in anchors subjected to tension or shear forces. Three different anchor sizes are subjected to seismic qualification testing, followed by a static load test to collapse. The test results confirm the capability of the tested anchors to sustain simulated pulsating seismic tension and shear loading with frequency ranges between 0.1 and 2.0 Hz. It was observed that no tension failure occurred at the end of the cyclic load tests for all the tested anchors, and their residual inelastic maximum displacement at the end of the cyclic tension test was relatively small. Moreover, the experimental results show that the anchors’ ultimate capacities are higher than those specified by the anchor manufacturer. Finally, the anchors’ experimental pullout shear capacities are compared with the failure prediction equations in the literature and design codes. It is found that the theoretical models provide a conservative prediction of the concrete breakout of anchors in tension compared to the experimental ultimate loads. The coefficient for pry-out strength (kcp) equal to 2 or slightly smaller than 2 is likely to predict a better pry-out capacity with the experimental results compared to the application of the high conservative value of kcp equal to 1, as given in the code.
Deformation Analysis of Existing Buildings Affected by Shield Tunnels Based on Intelligent Inversion and Measured Data
Authors: Zeng Zhiquan , Wang Yongming , Huang Yong , Zhang Shuaichao , Ma Chunhui , Liu Long
Published: July 2024

In the construction of urban underground shield tunnels, uneven deformation can easily occur when the shield passes through soft soil and other poor strata. Such deformation has a significant impact on surface settlement and may cause potential safety hazards to the surrounding existing buildings, directly affecting the safety of urban operation. When simulating and predicting surface settlements, the small-strain soil hardening model can more accurately characterize the mechanical parameters of soil. Nevertheless, its parameters are numerous and complicated to determine accurately, so parameter inversion is needed to determine the accurate parameters of the soft soil layer in order to more accurately predict the surface settlement. This study uses the EFAST method to analyse the sensitivity of the HSS model parameters of soft soil strata. It is determined that the parameters that have the most significant impact on the surface settlement are the reference tangent modulus, rebound modulus, and effective cohesion. Then, XGBoost’s fast calculation speed and high precision of SSA inversion are used to inverse and optimize the parameters with high sensitivity. Finally, according to the parameters of the soft soil layer obtained from inversion and measured data, the settlement deformation and safety behaviour of existing buildings are analysed. Combined with the actual shield tunnel project in a city along a river, the inversion calculation shows that the overall average error of the transverse monitoring section is 1.04 mm, and the average maximum error of each monitoring point in the overall shield process is 2.87 mm. The prediction effect is significantly improved compared with the original parameters. The accuracy of the inversion of soil layer parameters is verified from the perspective of time and space. The average settlement of the river embankment foundation is 2.5 mm. Compared with the original parameter data, the prediction results have been greatly improved, and the settlement deformation results are more consistent with the measured data.
The Use of Apparent Diffusion Coefficient Values for Differentiating Bevacizumab-Related Cytotoxicity from Tumor Recurrence and Radiation Necrosis in Glioblastoma
Authors: Khalaj Kamand , Jacobs Michael A. , Zhu Jay-Jiguang , Esquenazi Yoshua , Hsu Sigmund , Tandon Nitin , Akhbardeh Alireza , Zhang Xu , Riascos Roy , Kamali Arash
Published: July 2024

Objectives: Glioblastomas (GBM) are the most common primary invasive neoplasms of the brain. Distinguishing between lesion recurrence and different types of treatment related changes in patients with GBM remains challenging using conventional MRI imaging techniques. Therefore, accurate and precise differentiation between true progression or pseudoresponse is crucial in deciding on the appropriate course of treatment. This retrospective study investigated the potential of apparent diffusion coefficient (ADC) map values derived from diffusion-weighted imaging (DWI) as a noninvasive method to increase diagnostic accuracy in treatment response. Methods: A cohort of 21 glioblastoma patients (mean age: 59.2 ± 11.8, 12 Male, 9 Female) that underwent treatment with bevacizumab were selected. The ADC values were calculated from the DWI images obtained from a standardized brain protocol across 1.5-T and 3-T MRI scanners. Ratios were calculated for rADC values. Lesions were classified as bevacizumab-induced cytotoxicity based on characteristic imaging features (well-defined regions of restricted diffusion with persistent diffusion restriction over the course of weeks without tissue volume loss and absence of contrast enhancement). The rADC value was compared to these values in radiation necrosis and recurrent lesions, which were concluded in our prior study. The nonparametric Wilcoxon signed rank test with p < 0.05 was used for significance. Results: The mean ± SD age of the selected patients was 59.2 ± 11.8. ADC values and corresponding mean rADC values for bevacizumab-induced cytotoxicity were 248.1 ± 67.2 and 0.39 ± 0.10, respectively. These results were compared to the ADC values and corresponding mean rADC values of tumor progression and radiation necrosis. Significant differences between rADC values were observed in all three groups (p < 0.001). Bevacizumab-induced cytotoxicity had statistically significant lower ADC values compared to both tumor recurrence and radiation necrosis. Conclusion: The study demonstrates the potential of ADC values as noninvasive imaging biomarkers for differentiating recurrent glioblastoma from radiation necrosis and bevacizumab-induced cytotoxicity.
The Role of PGC-1α in Aging Skin Barrier Function
Authors: Luo Yonghong , Bollag Wendy B.
Published: July 2024

Skin provides a physical and immune barrier to protect the body from foreign substances, microbial invasion, and desiccation. Aging reduces the barrier function of skin and its rate of repair. Aged skin exhibits decreased mitochondrial function and prolonged low-level inflammation that can be seen in other organs with aging. Peroxisome proliferator-activated receptor (PPAR)-γ coactivator-1α (PGC-1α), an important transcriptional coactivator, plays a central role in modulating mitochondrial function and antioxidant production. Mitochondrial function and inflammation have been linked to epidermal function, but the mechanisms are unclear. The aim of this review is to discuss the mechanisms by which PGC-1α might exert a positive effect on aged skin barrier function. Initially, we provide an overview of the function of skin under physiological and aging conditions, focusing on the epidermis. We then discuss mitochondrial function, oxidative stress, cellular senescence, and inflamm-aging, the chronic low-level inflammation observed in aging individuals. Finally, we discuss the effects of PGC-1α on mitochondrial function, as well as the regulation and role of PGC-1α in the aging epidermis.
Indentation Behavior Assessment of As-Built, Solution, and Artificial Aged Heat-Treated Selective Laser Melting Specimens of AlSi10Mg
Authors: Kamil Abubakr Shahnawaz , Muzamil Muhammad , Akhtar Maaz , Alsaleh Naser , Khan Rashid , Samiuddin Muhammad , Siddiqui Ali Khursheed , Yang Junzhou , Djuansjah Joy
Published: July 2024

This study was conducted to determine the indentation behavior of thin AlSi10Mg specimens manufactured using Selective Laser Melting (SLM) in the as-built condition along with two post-treatments, namely solution heat treatment and artificial aging. Four different thicknesses of 1.0 mm, 1.5 mm, 2 mm, and 2.5 mm of SLM specimens, with the different post-treatments, underwent standardized Rockwell hardness tests using a spherical indenter to determine their hardness values and assess the impression using a stereo microscope and scanning electron microscope (SEM). The as-built specimens showed a trend of smaller indentation depths with increasing specimen thickness, and finally creased with 0.1547 mm depth at 2.5 mm. However, the post-treatments altered the behavior of the specimens to a certain degree, giving larger experimental indentation depths of 0.2204 mm, 0.1962 mm, and 0.1798 mm at 1.0 mm, 1.5 mm, and 2.5 mm thickness, respectively, after solution heat treatment. Artificial aging showed a general decrease in indentation depth with increasing specimen thickness in contrast to solution treatment, and resulted in depths of 0.1888 mm and 0.1596 mm at 1.0 mm and 2.5 mm thickness. Furthermore, a material numerical model was made using stress–strain data on ANSYS Workbench to develop a predictive model for the indentation behavior of the specimens in contrast to experimentation. Under multi-linear isotropic hardening, the Finite Element Analysis (FEA) simulation produced indentation geometry with an average accuracy of 95.4% for the artificial aging series.
Pre-Critical and Giant Post-Freezing and Pre-Melting Effects for Dielectric Properties in a Binary Mixture of Limited Miscibility
Authors: Kalabiński Jakub , Drozd-Rzoska Aleksandra , Starzonek Szymon , Rzoska Sylwester J.
Published: July 2024

This report presents the results of dielectric studies in a nitrobenzene–decane critical mixture in the homogeneous liquid, biphasic mesophase, and the solid crystal phase. It focuses on detecting critical effects in the broad surrounding of the critical consolute temperature and pre-melting and post-freezing effects in the solid crystal phase. The strong manifestation of the diameter critical anomaly in the biphasic domain and the Mossotti catastrophe type pre-melting and post-freezing effects in the solid phase are evidenced. Studies include the puzzling low-frequency (LF) domain related to translational processes. The real part of electric conductivity, in LF limit, is well portrayed by the super-Arrhenius-type equation in the homogenous liquid and solid phases. The obtained experimental evidence can be significant for the cognitive progress of the still puzzling melting/freezing canonic discontinuous transition.
Influence of Post-Annealing Treatment on Some Physical Properties of Cerium Oxide Thin Films Prepared by the Sol–Gel Method
Authors: Al-Shomar S. M.
Published: July 2024

In this study, thin films of Cerium Oxide CeO2 were fabricated using the sol–gel technique and deposited onto a glass substrate. The annealing process was carried out at various temperatures ranging from 200 to 600 °C to investigate the structural, morphological, and optical properties of the films and their interrelations. X-ray diffraction (XRD) patterns revealed the crystalline nature of the prepared films, with film quality exhibiting enhancement with increasing annealing temperature. The average crystallite size, dislocation density, microstrain, and lattice constant were determined from XRD patterns. Higher annealing temperatures were found to increase the crystallite size values from 4.71 to 15.33 nm and decrease the dislocation density and microstrain of the unit cell. Scanning electron microscope (SEM) images illustrated the uniformity of the films, presenting a spheroid shape. Optical properties such as transmittance, absorbance, reflectance, the direct band gap, extinction coefficients, the refractive index, and optical conductivity were assessed using optical measurements. The direct optical band gap of the CeO2 film was observed to decrease from 3.99 to 3.75 eV with increasing film thickness. Using the Wemple and DiDomenico (WDD) single-oscillator model, dispersion energy parameters were calculated based on the refractive index. The nonlinear optical properties of the CeO2 thin films were evaluated using these dispersion energy parameters. The improvement of optical parameters holds significance in standardizing CeO2 thin films for various optoelectronic applications.
Setting the Standards: Neonatal Lung Ultrasound in Clinical Practice
Authors: Singh Yogen , Dauengauer-Kirliene Svetlana , Yousef Nadya
Published: July 2024

The use of lung ultrasonography in neonates is increasing at a very fast rate. Evidence-based guidelines on the use of lung ultrasound (LU) in neonates and children have been published and well received across the world. However, there remains a lack of standardized curriculum for lung ultrasound training and standards for its application at the bedside. This article focuses on providing a standardized approach to the application of lung ultrasonography in neonates for the common neonatal conditions and how it can be integrated into bedside clinical decision-making.