bluuebunny/crossref_metadata_2025 huggingface dataset:
Nighttime Warming Reduced Copper Concentration and Accumulation in Wheat Grown in Copper-Contaminated Soil by Affecting Physiological Traits
Authors: Cheng Xianghan , Liu Feifei , Song Peng , Liu Xiaolei , Liu Qin , Kou Taiji
Published: June 2024

The changes in biomass (including yield), copper (Cu) concentration, and the accumulation of wheat (Triticum aestivum. L) in response to soil Cu pollution under nighttime warming had still not been explored. Hence, this study was carried out, and these variations were analyzed from a physiological perspective. Pot trials were performed at two levels of ambient temperatures (no-warming (NT) and average nighttime warming of 0.28 °C (WT)) and two levels of soil Cu concentrations (control check without Cu application (CK) and 100 mg/kg Cu application (Cu)). Soil was collected from the carbonate cinnamon soil region of central China. The warming effects of the passive nighttime warming system were prominent, and the average increment was 0.28 °C. Antioxidant enzyme activities were promoted by warming (p < 0.05) and Cu. The highest yield was achieved in NT-Cu, mainly attributed to relatively strong root activity and photosynthesis caused by supplemental Cu, but the Cu concentration in its grains was close to the threshold (10 mg/kg) for Cu concentration in foodstuff and could present a potential food safety risk. Though nighttime warming did not increase the total biomass and yield of wheat, it decreased the Cu accumulation of wheat grown in Cu-contaminated soil, especially in grains. Moreover, WT-CK and WT-Cu increased the Cu concentration in the roots and glumes and reduced the Cu concentration in grains by 13.09% and 55.84%, respectively, probably because of a lower transpiration rate. Among them, the Cu concentration of grains in WT-Cu was the lowest and significantly lower than other applications. Our findings reveal that nighttime warming has the potential to reduce the Cu risk of grains in wheat grown in the Cu-contaminated carbonate cinnamon soil region of central China and could then provide a theoretical reference for risk assessment of food quality for wheat subjected to dual stress from nighttime warming and Cu pollution.
Efficacy of Extreme Temperatures on All Life Stages of the Mediterranean Flour Moth, Ephestia kuehniella Zeller (Lepidoptera: Pyralidae)
Authors: Sakka Maria K. , Gourgouta Marina , Athanassiou Christos G.
Published: June 2024

In the present study, we examined the effect of extreme temperatures on different life stages of Ephestia kuehniella Zeller (Lepidoptera: Pyralidae). The individuals were exposed to different temperatures ranging between 5 and −18 °C for cold treatment, and between 30 and 55 °C for heat treatment, and different exposure intervals, ranging from minutes to days. Complete control was achieved at −10 and −15 °C for cold treatment and 50 and 55 °C for heat treatment at all exposure intervals. Considering the efficacy of extreme temperatures for the control of E. kuehniella, our study provides specific temperature exposure modules that can be effective for the control of this species.
Responses of Digestive, Antioxidant, Immunological and Metabolic Enzymes in the Intestines and Liver of Largemouth Bass (Micropterus salmoides) under the Biofloc Model
Authors: Jin Yuqin , Meng Shunlong , Xu Huimin , Song Chao , Fan Limin , Qiu Liping , Li Dandan
Published: June 2024

To investigate the activities of intestinal digestive enzymes, liver antioxidant enzymes, immunological enzymes, and glucometabolic enzymes in largemouth bass (Micropterus salmoides) under the biofloc model, an experiment was conducted in 300-liter glass tanks. The experiment comprised a control group, which was fed a basal diet, and a biofloc group, where glucose was added to maintain a C/N ratio of 15. Each group had three parallel setups, with a stocking density of 20 fish per tank. The experiment ran for 60 days, employing a zero-water exchange aquaculture model. The results showed that at the end of the culture period, there were no significant differences between the initial weight, final weight, WGR, SGR, and SR of the biofloc group and the control group of largemouth bass (p > 0.05), whereas the lower FCR and the higher PER in the biofloc group were significant (p < 0.05); intestinal α-amylase, trypsin, and lipase activities of largemouth bass in the biofloc group were significantly increased by 37.20%, 64.11%, and 51.69%, respectively, compared with the control group (p < 0.05); liver superoxide dismutase and catalase activities, and total antioxidant capacity of largemouth bass in the biofloc group were significantly increased by 49.26%, 46.87%, and 98.94% (p < 0.05), while the malondialdehyde content was significantly reduced by 19.91% (p < 0.05); liver lysozyme, alkaline phosphatase, and acid phosphatase activities of largemouth bass in the biofloc group were significantly increased by 62.66%, 41.22%, and 29.66%, respectively (p < 0.05); liver glucokinase, pyruvate kinase, glucose-6-phosphate kinase, pyruvate kinase, glucose-6-phosphatase, and glycogen synthase activities were significantly increased by 46.29%, 99.33%, 32.54%, and 26.89%, respectively (p < 0.05). The study showed that the biofloc model of culturing largemouth bass can not only enhance digestive enzyme activities, antioxidant capacity, and immune response but can also promote the process of glucose metabolism and reduce feeding costs. This study provides data support for healthy culturing of largemouth bass in future production, provides a theoretical reference for optimizing the biofloc technology culture model, and is crucial for promoting the healthy and green development of aquaculture.
Deep Reinforcement Learning and Discrete Simulation-Based Digital Twin for Cyber–Physical Production Systems
Authors: Krenczyk Damian
Published: June 2024

One of the goals of developing and implementing Industry 4.0 solutions is to significantly increase the level of flexibility and autonomy of production systems. It is intended to provide the possibility of self-reconfiguration of systems to create more efficient and adaptive manufacturing processes. Achieving such goals requires the comprehensive integration of digital technologies with real production processes towards the creation of the so-called Cyber–Physical Production Systems (CPPSs). Their architecture is based on physical and cybernetic elements, with a digital twin as the central element of the “cyber” layer. However, for the responses obtained from the cyber layer, to allow for a quick response to changes in the environment of the production system, its virtual counterpart must be supplemented with advanced analytical modules. This paper proposes the method of creating a digital twin production system based on discrete simulation models integrated with deep reinforcement learning (DRL) techniques for CPPSs. Here, the digital twin is the environment with which the reinforcement learning agent communicates to find a strategy for allocating processes to production resources. Asynchronous Advantage Actor–Critic and Proximal Policy Optimization algorithms were selected for this research.
Research on Calculation and Optimization Methods for Tooth Flash Temperature and Meshing Power Loss of the Gear System in Drum Shearer
Authors: Bai Bo , Mao Run , Guo Wenchao , Mao Shimin
Published: June 2024

The operating conditions of the drum shearer are very complex, and its ranging arm gear system often suffers from gear scuffing and wear. Gear scuffing is caused by the adhesive wear, which is due to the instantaneous friction and flash temperature of the tooth surface, and the gear meshing power loss is also caused by tooth surface friction. In order to resist tooth scuffing and improve meshing efficiency of the transmission system, an improved semi-analytical tooth surface flash temperature calculation method was used. The tooth flash temperature status under various working conditions were analyzed in detail. Based on the mechanical model of the shearer drum picks, the load condition of the drum was analyzed. Under these load and boundary conditions, the misalignments of each gear pair in the ranging arm were calculated. The tooth surface load distribution was calculated under the gear misalignments, and then the theoretical tooth surface flash temperature and meshing power loss were determined. Next, the tooth micro-geometry was modified to reduce flash temperature and meshing power loss. The flash temperature distribution pattern of the optimized tooth surface was studied under various working conditions, and the meshing power loss was also obtained. Finally, experiments were conducted to verify the effects of the optimized tooth surface on the friction temperature rise and the effectiveness of the modification method. Tooth surface optimization aimed at reducing tooth surface flash temperature can also effectively reduce meshing power loss, which has a significant effect on gear anti-scuffing and energy saving.
Design of an Intelligent Cascade Control Scheme Using a Hybrid Adaptive Neuro-Fuzzy PID Controller for the Suppression of Drill String Torsional Vibration
Authors: Laib Abdelbaset , Gharib Mohamed
Published: June 2024

Eliminating the excessive stick–slip torsional vibrations of drill strings by utilizing an effective controller can significantly increase penetration rates and reduce drilling operation costs. The present study aims to develop a fast and intelligent cascade control structure for a multi-degree-of-freedom drill string system under torsional vibrations. The proposed control configuration consists of two control loops in a cascade arrangement. The first controller estimates the top drive velocity reference from the actual drill bit velocity and its reference. The role of the second controller is to regulate the top drive velocity to its reference by generating the necessary torque for the drilling operation process to progress. Each control loop is designed based on a hybrid adaptive neuro-fuzzy PID and feedforward term. The latter assures fast regulation when there are sudden changes in operation. To evaluate the performance of the suggested cascade feedforward neuro-fuzzy PID (CFF-NFPID) control structure, extensive simulations were conducted using Matlab/Simulink. The simulation results clearly showed that the proposed CFF-NFPID controller provided high-performance control with variations in the weight on the bit and the desired drill bit rotary speed in comparison with that of cascade feedforward fuzzy PID, sliding-mode, cascade feedforward PID, cascade PID, and conventional PID controllers. Furthermore, the control robustness is very suitable despite the change in the system parameters.
Axial Load Transfer Mechanism in Fully Grouted Rock Bolting System: A Systematic Review
Authors: Jodeiri Shokri Behshad , Mirzaghorbanali Ali , Nourizadeh Hadi , McDougall Kevin , Karunasena Warna , Aziz Naj , Entezam Shima , Entezam Alireza
Published: June 2024

The main objective of implementing primary ground-controlling methods, such as applying rock bolting systems, is to increase the strength of surrounding rock mass. Among all rock bolting systems, fully grouted rock bolting systems are the most popular and reliable retaining systems due to their simplicity, availability of materials, ease of installation in the field, and cost-effectiveness. While these types of rock bolts experience both axial and shear forces, understanding their response to axial loads remains complex and dependent on several factors. Extensive research has addressed the overall behaviour of the fully grouted rock bolting system, but a systematic review of the axial load transfer mechanism and its impact on overall performance is lacking. This study addresses this gap by employing a bibliometric analysis of 77 peer-reviewed publications to explore the current state of knowledge regarding the axial load transfer mechanism in fully grouted rock bolting systems. The analysis identifies influential journals, publishers, researchers, highly cited articles, and emerging keywords within this field. Furthermore, it reveals three key parameters significantly impacting the axial behaviour: (a) rock mass and boundary conditions, (b) mechanical behaviours of the grouts, and (c) the geometry and surface profile of the rock bolt. These parameters are subsequently discussed in detail, highlighting their influence on the axial performance of the system. Finally, this article concludes by suggesting promising directions for future research.
Design and Material Optimization of Oil Plant Piping Structure for Mitigating Erosion Wear
Authors: Ahn Jun-Hyuk , Asif Rabea , Lee Heon-Woo , Hwang In-Ju , Hu Jong-Wan
Published: June 2024

Erosion in piping structures poses a significant challenge for oil industries as the conveyance of solid particles leads to operational malfunctions and structural failures affecting the overall oil plant operation. Conventional oil recovery methods have historically dominated, while in response to the challenges imposed by declining conventional oil production, the global shift towards non-conventional methods necessitates a reevaluation of erosion mitigation strategies due to increased piping infrastructure. Therefore, in this study research has been conducted to reduce erosion and optimize the piping structure. Variables impacting the erosion in piping were investigated from the literature, and simulation cases were made based on the impacted variables. Computational Fluid Dynamics (CFDs) analysis was performed using the Discrete Phase Model (DPM) to determine the erosion wear rate in each simulation case; based on the CFD results, variables with low Turbulent Dissipation Rates (TDRs) and Erosion Rates (ERs) were determined, and the optimized piping structure was designed. As a result, the optimized piping structure showed an 80% reduction in the turbulent dissipation rate and a 99.2% decrease in the erosion wear rate. These findings highlight a substantial improvement in erosion control, ensuring the safety and longevity of piping structures in oil plant operations.
Research on Clustering-Based Fault Diagnosis during ROV Hovering Control
Authors: Park Jung-Hyeun , Cho Hyunjoon , Gil Sang-Min , Choo Ki-Beom , Kim Myungjun , Huang Jiafeng , Jung Dongwook , Yun ChiUng , Choi Hyeung-Sik
Published: June 2024

The objective of this study was to perform fault diagnosis (FD) specific to various faults that can occur in the thrusters of remotely operated vehicles (ROVs) during hovering control. Underwater thrusters are predominantly utilized as propulsion systems in the majority of ROVs and are essential components for implementing motions such as trajectory tracking and hovering. Faults in the underwater thrusters can limit the operational capabilities of ROVs, leading to permanent damage. Therefore, this study focused on the FD for faults frequently caused by external factors such as entanglement with floating debris and propeller breakage. For diagnosing faults, a data-based technique that identifies patterns according to data characteristics was utilized. In imitation of the fault situations, data for normal, breakage and entangled conditions were acquired, and Density-Based Spatial Clustering of Applications with Noise (DBSCAN) was employed to differentiate between these fault conditions. The proposed methodology was validated by configuring an ROV and conducting experiments in an engineering water tank to verify the performance of the FD.
Identifying Key Success Factors for Industry 4.0 Implementation: An Empirical Analysis Using SEM and fsQCA
Authors: Zhou Hui , Zhou Baoru , Nie Zhenguo , Zheng Li
Published: June 2024

Industry 4.0 technologies have been gaining significant momentum in recent years. Despite widespread adoption, many companies struggle with the successful implementation of these technologies. This study aims to identify the critical success factors for implementing Industry 4.0 technologies and to examine the effects of various factor combinations. Using the technology–organization–environment framework and the practice-based view, this paper proposes a comprehensive research model. This study employs a hybrid approach combining structural equation modeling (SEM) and fuzzy-set qualitative comparative analysis (fsQCA) to analyze survey data collected from 202 Chinese manufacturing firms. The SEM results indicate that top management support, technology competence, supplier support, and pilot projects are significantly associated with successful implementation. However, the fsQCA results reveal that individual factors alone are insufficient for success; rather, it is the combinations of these factors that drive successful implementation. Specifically, three key combinations lead to success: (1) top management support and technology competence; (2) top management support and supplier support; and (3) technology competence, supplier support, and pilot projects. By recognizing these combinations, manufacturing firms can develop more effective implementation strategies for Industry 4.0 technologies.
Evaluating the Impact of Mobility on Differentially Private Federated Learning
Authors: Kim Eun-ji , Lee Eun-Kyu
Published: June 2024

This paper investigates differential privacy in federated learning. This topic has been actively examined in conventional network environments, but few studies have investigated it in the Internet of Vehicles, especially considering various mobility patterns. In particular, this work aims to measure and enumerate the trade-off between accuracy of performance and the level of data protection and evaluate how mobility patterns affect it. To this end, this paper proposes a method considering three factors: learning models, vehicle mobility, and a privacy algorithm. By taking into account mobility patterns, local differential privacy is enhanced with an adaptive clipping method and applied to a mobility-based federated learning model. Experiments run the model on vehicular networks with two different mobility scenarios representing a non-accident traffic situation and traffic events, respectively. Results show that our privacy-enhanced federated learning models degrade accuracy performance by 2.96–3.26% on average, which is compared to the performance drop (42.97% on average) in conventional federated learning models.
Study on the Detection Mechanism of Multi-Class Foreign Fiber under Semi-Supervised Learning
Authors: Zhou Xue , Wei Wei , Huang Zhen , Su Zhiwei
Published: June 2024

Foreign fibers directly impact the quality of raw cotton, affecting the prices of textile products and the economic efficiency of cotton textile enterprises. The accurate differentiation and labeling of foreign fibers require domain-specific knowledge, and labeling scattered cotton foreign fibers in images consumes substantial time and labor costs. In this study, we propose a semi-supervised foreign fiber detection approach that uses unlabeled image information and a small amount of labeled data for model training. Our proposed method, Efficient YOLOv5-cotton, introduces CBAM to address the issue of the missed detection and false detection of small-sized cotton foreign fibers against complex backgrounds. Second, the algorithm designs a multiscale feature information extraction network, SPPFCSPC, which improves its ability to generalize to fibers of different shapes. Lastly, to reduce the increased network parameters and computational complexity introduced by the SPPFCSPC module, we replace the C3 layer with the C3Ghost module. We evaluate Efficient YOLOv5 for detecting various types of foreign fibers. The results demonstrate that the improved Efficient YOLOv5-cotton achieves a 1.6% increase in mAP@0.5 (mean average precision) compared with the original Efficient YOLOv5 and reduces model parameters by 10% compared to the original Efficient YOLOv5 with SPPFCSPC. Our experiments show that our proposed method enhances the accuracy of foreign fiber detection using Efficient YOLOv5-cotton and considers the trade-off between the model size and computational cost.
Congenital Cytomegalovirus-Related Hearing Loss
Authors: Gana Nicoleta , Huluță Iulia , Cătănescu Mihai-Ștefan , Apostol Livia-Mihaela , Nedelea Florina Mihaela , Sima Romina-Marina , Botezatu Radu , Panaitescu Anca Maria , Gică Nicolae
Published: June 2024

Congenital hearing loss is a significant global health concern that affects millions of newborns and infants worldwide, posing substantial challenges for affected individuals, their families, and healthcare systems. This condition, present at birth, can stem from genetic factors, in utero exposures, infections, or complications during pregnancy or childbirth. The spectrum of congenital hearing loss ranges from mild to profound, impacting the development of speech, language, and cognitive skills, thereby influencing educational achievements, social integration, and future employment opportunities. Early detection and intervention strategies, such as newborn hearing screenings, genetic counseling, and the use of hearing aids or cochlear implants, are crucial for mitigating these impacts. This review article aims to explore the diagnostic approaches and management strategies for congenital cytomegalovirus-related hearing loss, emphasizing the importance of interdisciplinary care and the potential for technological advances to improve outcomes for affected individuals.
Genetic Polymorphisms in Exon 5 and Intron 5 and 7 of AIRE Are Associated with Rheumatoid Arthritis Risk in a Hungarian Population
Authors: Bérczi Bálint , Nusser Nóra , Péter Iván , Németh Balázs , Kulisch Ágota , Kiss Zsuzsanna , Gyöngyi Zoltán
Published: June 2024

Background: Rheumatoid arthritis (RA) is chronically persistent synovitis and systemic inflammation. Although multiple contributors are detected, only one is pivotal in the neonatal period: the negative selection of autoimmune naïve T-cells by the autoimmune regulator (AIRE) transcriptional factor. Methods: Single-nucleotide polymorphisms (SNPs) in the DNA-binding site of AIRE may determine its function and expression. We intended to analyse site-specific allelic polymorphisms in two exon (rs878081 and rs1055311) and three intron (rs1003853, rs2075876, and rs1003854) loci with an RA risk. Our analytical case-control study analysed 270 RA patients and 322 control subjects in five different genetic models using quantitative real-time PCR (qPCR) with TaqMan® assays. Results: Statistically significant differences were found between the odds of allelic polymorphisms in the loci of rs878081, rs1003854, and rs1003853 among the controls and RA patients, and the disease activity seemed to be significantly associated with the genotypic subgroups of rs878081 and rs1055311. Our in silico analysis supported this, suggesting that allele-specific alterations in the binding affinity of transcriptional factor families might determine RA activity. Conclusion: Our findings highlight the involvement of neonatal self-tolerance in RA pathogenesis, providing novel insights into disease development and paving the way for an analysis of further site-specific genetic polymorphisms in AIRE to expand the intervention time for RA.
Conservation and Evolution of Wildlife in the Context of Climate Change and Human Population Growth
Authors: Liao Wenbo , Cao Lingsen
Published: June 2024

Global climate change results in variations in morphological traits, resource competition, species diversity, physiological activity, genetic diversity, habitat use, distributional range, and conservation status in organisms [...]
Clinical Insights in RNA-Binding Protein Motif 20 Cardiomyopathy: A Systematic Review
Authors: Martini Marika , Bueno Marinas Maria , Rigato Ilaria , Pilichou Kalliopi , Bauce Barbara
Published: June 2024

Dilated cardiomyopathy (DCM) is a common cause of heart failure (HF) and heart transplantation (HTx), with genetic factors playing a significant role. In recent years, the RNA-binding protein motif 20 (RBM20), which affects the gene splicing of various proteins with different cellular functions, was identified as the first DCM gene with regulatory properties. Variants of RBM20 have been associated with severe forms of DCM. The aim of this critical systematic review was to analyse RBM20 cardiomyopathy clinical features and outcomes. According to PRISMA guidelines, a search was run in the PubMed, Scopus and Web of Science electronic databases using the following keywords: “RBM20”; “cardiomyopathy”; “arrhythmias”; “heart failure”. A total of 181 records were screened, of which 27 studies were potentially relevant to the topic. Through the application of inclusion and exclusion criteria, eight papers reporting 398 patients with RBM20 pathogenic variants were analysed. The mean age at presentation was 41 years. Familiarity with cardiomyopathy was available in 59% of cases, with 55% of probands reporting a positive family history. Imaging data indicated a mild reduction of left ventricular ejection fraction (mean LVEF 40%), while tissue characterization was reported in 24.3% of cases, showing late gadolinium enhancement in 33% of patients. Composite outcomes of sustained monomorphic ventricular tachycardia or ventricular fibrillation occurred in 19.4% of patients, with 12% undergoing HTx. There were no gender differences in arrhythmic outcomes, while 96.4% of patients who underwent HTx were male. In conclusion, RBM20 cardiomyopathy exhibits a severe phenotypic expression, both in terms of arrhythmic burden and HF progression.
Myogenic Anti-Nucleolin Aptamer iSN04 Inhibits Proliferation and Promotes Differentiation of Vascular Smooth Muscle Cells
Authors: Miyoshi Mana , Shimosato Takeshi , Takaya Tomohide
Published: June 2024

De-differentiation and subsequent increased proliferation and inflammation of vascular smooth muscle cells (VSMCs) is one of the mechanisms of atherogenesis. Maintaining VSMCs in a contractile differentiated state is therefore a promising therapeutic strategy for atherosclerosis. We have reported the 18-base myogenetic oligodeoxynucleotide, iSN04, which serves as an anti-nucleolin aptamer and promotes skeletal and myocardial differentiation. The present study investigated the effect of iSN04 on VSMCs because nucleolin has been reported to contribute to VSMC de-differentiation under pathophysiological conditions. Nucleolin is localized in the nucleoplasm and nucleoli of both rat and human VSMCs. iSN04 without a carrier was spontaneously incorporated into VSMCs, indicating that iSN04 would serve as an anti-nucleolin aptamer. iSN04 treatment decreased the ratio of 5-ethynyl-2′-deoxyuridine (EdU)-positive proliferating VSMCs and increased the expression of α-smooth muscle actin, a contractile marker of VSMCs. iSN04 also suppressed angiogenesis of mouse aortic rings ex vivo, which is a model of pathological angiogenesis involved in plaque formation, growth, and rupture. These results demonstrate that antagonizing nucleolin with iSN04 preserves VSMC differentiation, providing a nucleic acid drug candidate for the treatment of vascular disease.
Accurate Early Detection and EGFR Mutation Status Prediction of Lung Cancer Using Plasma cfDNA Coverage Patterns: A Proof-of-Concept Study
Authors: Bie Zhixin , Ping Yi , Li Xiaoguang , Lan Xun , Wang Lihui
Published: June 2024

Lung cancer is a major global health concern with a low survival rate, often due to late-stage diagnosis. Liquid biopsy offers a non-invasive approach to cancer detection and monitoring, utilizing various features of circulating cell-free DNA (cfDNA). In this study, we established two models based on cfDNA coverage patterns at the transcription start sites (TSSs) from 6X whole-genome sequencing: an Early Cancer Screening Model and an EGFR mutation status prediction model. The Early Cancer Screening Model showed encouraging prediction ability, especially for early-stage lung cancer. The EGFR mutation status prediction model exhibited high accuracy in distinguishing between EGFR-positive and wild-type cases. Additionally, cfDNA coverage patterns at TSSs also reflect gene expression patterns at the pathway level in lung cancer patients. These findings demonstrate the potential applications of cfDNA coverage patterns at TSSs in early cancer screening and in cancer subtyping.
A Study on Identifying the Spatial Characteristic Factors of Traditional Streets Based on Visitor Perception: Yuanjia Village, Shaanxi Province
Authors: Liu Yixin , Li Zhimin , Tian Yixin , Gao Bo , Wang Simin , Qi Yingtao , Zou Zejing , Li Xuanlin , Wang Ruqin
Published: June 2024

The street spaces in tourist-oriented traditional villages served both the daily lives of villagers and the leisure activities of tourists. However, due to insufficient understanding of the spatial characteristics and under-exploration of spatial genes, these spaces often suffered from homogenization during tourism development. Thus, identifying the characteristics and connotations of such streets, understanding the relationship between tourists’ perceptions and built environment elements, and developing optimization strategies for these rural street spaces were urgent issues. Many studies have evaluated street space characteristics from tourists’ behavior, but few have focused on rural areas. Especially, research combining new technologies like artificial intelligence to study the psychological perceptions of tourists is still in its infancy. This study used a typical traditional village as a case study and applied the YOLOv5 deep-learning model to build a perception evaluation system based on three dimensions: tourists’ aggregation degree, stay time, and facial expressions. The study conducted a multivariate regression analysis on 21 factors across 4 aspects: street scale morphology, environmental facilities, ground-floor interface, and street business types. Results indicated that the functional business type of the scene had the greatest impact on tourists’ perception of the street space environment, followed by ground-floor features and environmental facilities. The regression coefficient for business in situ values and spatial perception was 0.47, highlighting it as a key factor influencing characteristic perception. Landscape water systems, flat ground-floor façades, and business diversity also positively affected tourists’ perception. This study utilized advanced techniques like the YOLOv5 model, known for its speed and accuracy, to scientifically analyze tourists’ behavior and perceptions, serving as feedback and evaluation for the village’s built environment. Empirical analysis of Yuanjia Village validated the effectiveness of the multidimensional approach and spatial gene theory. Ultimately, this method identified 12 street characteristic factors significantly affecting tourists’ perceptions. The uniqueness of this study lies in its comprehensive approach, combining empirical research, spatial gene theory, and advanced object detection technology, providing new insights for village spatial planning and construction.
MFRWA: A Multi-Frequency Rayleigh Wave Approximation Method for Concrete Carbonation Depth Evaluation
Authors: Sun Xiangtao , Cui Yongxiang , Chen Jiawei , Yi Shanchang , Li Xiuquan , Chen Lin
Published: June 2024

Carbonation depth is essential to determine the durability and predict the remaining service life of concrete structures. This study proposes a multi-frequency Rayleigh wave approximation method (MFRWA) to evaluate carbonation depth by exploiting the frequency-dependent penetration depths of ultrasonic Rayleigh waves. A series of numerical simulations are conducted to investigate the effective penetration depth of Rayleigh waves and the feasibility of the proposed MFRWA method on carbonation depth evaluation. Subsequently, the accelerated carbonation experiment is conducted to evaluate the carbonation depth using low-frequency and high-frequency Rayleigh waves, and the measured results from the Rayleigh wave method are compared with the ones from the phenolphthalein indicator and thermalgravimetric analysis (TGA) method. The results show that carbonation depth measured by Rayleigh wave method meets well with the one from TGA technique, demonstrating that the proposed method could provide a non-destructive and precise carbonation depth estimation. The proposed MFRWA method contributes a novel scheme for concrete carbonation evaluation and holds substantial potential in both laboratory and field applications.
Numerical Investigation of the Seismic-Induced Rocking Behavior of Unbonded Post-Tensioned Bridge Piers
Authors: Bao Zehua , Xu Wenjing , Gao Haoyuan , Zhong Xueqi , Li Jianzhong
Published: June 2024

It is essential and convenient to use accurate and validated numerical models to simulate the seismic performance of post-tensioned (PT) rocking bridge piers, with a particular emphasis on accurately capturing rocking behavior. The primary contribution of this study is a comparison of the effectiveness of four commonly used numerical base rocking models (namely, the lumped plasticity (LP) model and the multi-contact spring (MCS) models with linear elastic (MCS-LE), bilinear elastic–plastic (MCS-EP) and nonlinear plastic (MCS-NP) material behavior, respectively) in modeling both the cyclic and seismic responses of PT rocking bridge piers. Also, this study validates the 3D contact stiffness equation for numerical models and assesses the differences between the dynamic and static stiffness values of the contact springs. Both quasi-static and shaking table tests of typical PT rocking piers are adopted to calibrate/validate these numerical models. These models describing the PT rocking piers’ seismic performance are formulated and calibrated, showing good agreement with test results for test specimens. Additionally, the suggested values of model spring stiffness for dynamic and quasi-static analyses are identified by parametric analysis. All base rocking models can predict the pier’s cyclic and seismic behavior after the calibration of contact spring stiffness values. The recommended contact stiffness for the dynamic analysis of PT rocking piers is smaller than that used for the quasi-static analysis. The results and findings provide a valuable reference and solution for the numerical simulation of PT rocking piers.
Small Extracellular Vesicle-Derived Circular RNA hsa_circ_0007386 as a Biomarker for the Diagnosis of Pleural Mesothelioma
Authors: Zhand Sareh , Liao Jiayan , Castorina Alessandro , Yuen Man-Lee , Ebrahimi Warkiani Majid , Cheng Yuen-Yee
Published: June 2024

Pleural mesothelioma (PM) is a highly aggressive tumor that is caused by asbestos exposure and lacks effective therapeutic regimens. Current procedures for PM diagnosis are invasive and can take a long time to reach a definitive result. Small extracellular vesicles (sEVs) have been identified as important communicators between tumor cells and their microenvironment via their cargo including circular RNAs (circRNAs). CircRNAs are thermodynamically stable, highly conserved, and have been found to be dysregulated in cancer. This study aimed to identify potential biomarkers for PM diagnosis by investigating the expression of specific circRNA gene pattern (hsa_circ_0007386) in cells and sEVs using digital polymerase chain reaction (dPCR). For this reason, 5 PM, 14 non-PM, and one normal mesothelial cell line were cultured. The sEV was isolated from the cells using the gold standard ultracentrifuge method. The RNA was extracted from both cells and sEVs, cDNA was synthesized, and dPCR was run. Results showed that hsa_circ_0007386 was significantly overexpressed in PM cell lines and sEVs compared to non-PM and normal mesothelial cell lines (p < 0.0001). The upregulation of hsa_circ_0007386 in PM highlights its potential as a diagnostic biomarker. This study underscores the importance and potential of circRNAs and sEVs as cancer diagnostic tools.
Lysosome-Disrupting Agents in Combination with Venetoclax Increase Apoptotic Response in Primary Chronic Lymphocytic Leukemia (CLL) Cells Mediated by Lysosomal Cathepsin D Release and Inhibition of Autophagy
Authors: Manivannan Madhumita S. , Yang Xiaoyan , Patel Nirav , Peters Anthea , Johnston James B. , Gibson Spencer B.
Published: June 2024

Venetoclax and obinutuzumab are becoming frontline therapies for chronic lymphocytic leukemia (CLL) patients. Unfortunately, drug resistance still occurs, and the combination could be immunosuppressive. Lysosomes have previously been identified as a target for obinutuzumab cytotoxicity in CLL cells, but the mechanism remains unclear. In addition, studies have shown that lysosomotropic agents can cause synergistic cell death in vitro when combined with the BTK inhibitor, ibrutinib, in primary CLL cells. This indicates that targeting lysosomes could be a treatment strategy for CLL. In this study, we have shown that obinutuzumab induces lysosome membrane permeabilization (LMP) and cathepsin D release in CLL cells. Inhibition of cathepsins reduced obinutuzumab-induced cell death in CLL cells. We further determined that the lysosomotropic agent siramesine in combination with venetoclax increased cell death in primary CLL cells through an increase in reactive oxygen species (ROS) and cathepsin release. Siramesine treatment also induced synergistic cytotoxicity when combined with venetoclax. Microenvironmental factors IL4 and CD40L or incubation with HS-5 stromal cells failed to significantly protect CLL cells from siramesine- and venetoclax-induced apoptosis. We also found that siramesine treatment inhibited autophagy through reduced autolysosomes. Finally, the autophagy inhibitor chloroquine failed to further increase siramesine-induced cell death. Taken together, lysosome-targeting drugs could be an effective strategy in combination with venetoclax to overcome drug resistance in CLL.
Association of Connective Tissue Grafts in Immediate Implants: Systematic Review and Meta-Analysis
Authors: Torra-Moneny Marta , Mauri-Obradors Elisabet , Egido-Moreno Sonia , Valls-Roca-Umbert Joan , Marí-Roig Antonio , López-López José
Published: June 2024

Background: The increase in soft tissue (ST) around implants can benefit peri-implant health and aesthetic results. The objective was to compare the gingival and esthetic health benefits of immediate implant placement (IIP) with simultaneous or delayed connective tissue graft (CTG) compared to IIP without CTG. Methods: A systematic review was carried out by two reviewers in Medline-Pubmed, Scopus, and Cochrane. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) were considered. Randomized Clinical Trials (RCTs) that were published between April 2017 and February 2024 were used. Studies that analyzed the performance of a simultaneous or deferred CTG after the placement of an implant in the aesthetic zone, with or without immediate provisionalization, without previous regeneration, with a follow-up of 6 months, and that were performed in humans were included. Results: Quantitative analysis was performed using data provided by the RCTs. The five RCTs that were selected analyzed a total “n” of 245 subjects who met the inclusion criteria and focused on the subject of the study. In the quantitative analysis, four RCTs were included. The studies evaluated buccal gingiva levels when placing the IIP with and without CTG, obtaining a mean buccal gingiva level difference of 0.09 mm (95% CI: −0.54 to 0.72, p = 0.05), statistically not significant, but with a favorable trend. Conclusions: The use of CTG associated with the II can maintain the gum level but not increase the volume. CTG is favorable for achieving successful esthetic results when immediate placement of an implant with a provisional prosthesis is planned.
(Up)Grading: A (Re)Humanizing Assessment Process with a Focus on Feedback
Authors: Livers Stefanie D. , Harbour Kristin E. , Sullivan Patrick L.
Published: June 2024

Researchers across two universities and three different mathematics education courses implemented their vision of a novel grading approach called (Up)grading. (Up)grading shifts the focus of assessment from grades to growth. Key features of implementing (Up)grading included (a) providing students with opportunities to reflect upon and grow from their learning experiences, and (b) giving them a voice in determining their course grade. The findings suggest that most students perceived (Up)grading as a positive experience in their learning and as an assessment approach. The features of (Up)grading students believed contributed to the positive experience included giving them opportunities to reflect on their work and learn from their mistakes, as well as targeted feedback, enabling them to independently move their thinking forward. Tensions in the process did arise, including students’ initial anxiety with the norm shift from grades to growth and instructors’ management of the flow of assignments.
PBL Impact on Learning Outcomes in Computer Engineering: A 12-Year Analysis
Authors: Lara-Bercial Pedro José , Gaya-López María Cruz , Martínez-Orozco Juan-Miguel , Lavado-Anguera Silvia
Published: June 2024

This article describes an evaluation of the Project-Based Learning (PBL) methodology implemented in the STEAM School of Universidad Europea in the Computer Engineering degree. The study raises research questions related to the perception of technical and soft skills acquired by students who used or considered PBL as their primary learning methodology compared to those who did not. Students’ motivation and adaptability to work after graduation have also been examined. The sample of students includes graduates from the last 20 years and therefore analyzes both the period in which the methodology was already implemented (from 2012) and some previous years. The study concludes that students who have identified or experienced PBL as their main learning methodology perceive a better acquisition of technical competencies and some soft skills, as well as better motivation and adaptability to the work environment.
El Cid: Can an Aesthetics Lens Save Transformational Leadership from Itself?
Authors: English Fenwick Walter , Ehrich Lisa Catherine
Published: June 2024

Countless articles and books have been written about transformational leadership theory since the late 1970s when it first appeared in the literature. The purpose of this conceptual paper is to illustrate that transformational leadership contains both logical and psychological problems when explaining the nature of leadership and as an empirically supportable and verifiable construct. It aims to show that its failure to garner evidence from a scientific methodological analysis may not invalidate its efficacy if it is viewed from an alternative lens, such as aesthetics. An aesthetic frame is one that recognizes sensuous ways of knowing since feelings and emotions are just as important as reason and logic. An aesthetic approach to leadership would see leadership as more of an art than a science. This paper is not arguing for the abandonment of transformational leadership theory; rather it is saying that an aesthetic lens is likely to yield a richer, more artistic, and more nuanced account of what is understood and enacted as transformational leadership. This way, the manifestations of transformational leadership may live on in the arts and continue to inspire and motivate us.
MFSC: A Multimodal Aspect-Level Sentiment Classification Framework with Multi-Image Gate and Fusion Networks
Authors: Zi Lingling , Pan Xiangkai , Cong Xin
Published: June 2024

Currently, there is a great deal of interest in multimodal aspect-level sentiment classification using both textual and visual information, which changes the traditional use of only single-modal to identify sentiment polarity. Considering that existing methods could be strengthened in terms of classification accuracy, we conducted a study on aspect-level multimodal sentiment classification with the aim of exploring the interaction between textual and visual features. Specifically, we construct a multimodal aspect-level sentiment classification framework with multi-image gate and fusion networks called MFSC. MFSC consists of four parts, i.e., text feature extraction, visual feature extraction, text feature enhancement, and multi-feature fusion. Firstly, a bidirectional long short-term memory network is adopted to extract the initial text feature. Based on this, a text feature enhancement strategy is designed, which uses text memory network and adaptive weights to extract the final text features. Meanwhile, a multi-image gate method is proposed for fusing features from multiple images and filtering out irrelevant noise. Finally, a text-visual feature fusion method based on an attention mechanism is proposed to better improve the classification performance by capturing the association between text and images. Experimental results show that MFSC has advantages in classification accuracy and macro-F1.
Mobility Extraction Using Improved Resistance Partitioning Methodology for Normally-OFF Fully Vertical GaN Trench MOSFETs
Authors: Ackermann Valentin , Mohamad Blend , El Rammouz Hala , Maurya Vishwajeet , Frayssinet Eric , Cordier Yvon , Charles Matthew , Lefevre Gauthier , Buckley Julien , Salem Bassem
Published: June 2024

In this work, fully vertical GaN trench MOSFETs were fabricated and characterized to evaluate their electrical performances. Transistors show a normally-OFF behavior with a high ION/IOFF (~109) ratio and a significantly small gate leakage current (10−11 A/mm). Thanks to an improved resistance partitioning method, the resistances of the trench bottom and trench channel were extracted accurately by taking into account different charging conditions. This methodology enabled an estimation of the effective channel and bottom mobility of 11.1 cm2/V·s and 15.1 cm2/V·s, respectively.
Synthetic Data for Semantic Segmentation: A Path to Reverse Engineering in Printed Circuit Boards
Authors: Phoulady Adrian , Choi Hongbin , Suleiman Yara , May Nicholas , Shahbazmohamadi Sina , Tavousi Pouya
Published: June 2024

This paper presents an innovative solution to the challenge of part obsolescence in microelectronics, focusing on the semantic segmentation of PCB X-ray images using deep learning. Addressing the scarcity of annotated datasets, we developed a novel method to synthesize X-ray images of PCBs, employing virtual images with predefined geometries and inherent labeling to eliminate the need for manual annotation. Our approach involves creating realistic synthetic images that mimic actual X-ray projections, enhanced by incorporating noise profiles derived from real X-ray images. Two deep learning networks, based on the U-Net architecture with a VGG-16 backbone, were trained exclusively on these synthetic datasets to segment PCB junctions and traces. The results demonstrate the effectiveness of this synthetic data-driven approach, with the networks achieving high Jaccard indices on real PCB X-ray images. This study not only offers a scalable and cost-effective alternative for dataset generation in microelectronics but also highlights the potential of synthetic data in training models for complex image analysis tasks, suggesting broad applications in various domains where data scarcity is a concern.