bluuebunny/crossref_metadata_2025 huggingface dataset:
Intelligent Construction Monitoring Method for Large and Complex Steel Structures Based on Laser Point Cloud
Authors: Sun Wenxiao , Wang Jian , Jin Fengxiang , Li Guoyuan , Xu Fubin
Published: July 2023

Large and complex steel structures play a vital role in building construction. However, deviations between the design model and the actual construction state are inevitable, which seriously affects the quality and safety of building construction. In our study, an intelligent construction monitoring method for large and complex steel structures based on laser point cloud is proposed. Firstly, three-dimensional laser scanning technology is introduced to capture accurate and complete spatial information on steel structures. Then, considering the inconsistency of the coordinate system between the design model and the laser point cloud, the building information model (BIM) is converted into the point cloud model, and the datum unification of the two types of the point cloud is achieved by adopting a coarse-to-fine registration strategy. Finally, the spatial information of steel structures is extracted from the laser point cloud based on the as-designed model, and the distance deviation between the two models is analyzed to reflect the actual construction state. To demonstrate the applicability of the proposed method, the steel structures’ point cloud of the stadium and the high-speed railway station is captured by the terrestrial three-dimensional laser scanner. The experimental results demonstrate that the method can extract the deviation between the design model and the actual construction, to provide accurate data sources for the intelligent fine construction of steel structures.
Endoscopic Resection of Residual or Recurrent Lesions after Circumferential Radiofrequency Ablation for Flat Superficial Esophageal Squamous Cell Neoplasias
Authors: Tsou Yung-Kuan , Yeh Chi-Ju , Le Puo-Hsien , Chen Bo-Huan , Lin Cheng-Hui
Published: July 2023

The optimal treatment of residual/recurrent superficial esophageal squamous cell neoplasias (SESCNs) after circumferential radiofrequency (RFA) remains unclear. We aimed to report the efficacy and safety of endoscopic resection (ER) of residual/recurrent SESCNs after RFA. Patients who underwent circumferential RFA with residual/recurrent SESCNs and were treated with ER were retrospectively collected. SESCN patients treated with primary endoscopic submucosal dissection (ESD) served as the control group. Eleven patients who underwent RFA had a total of 17 residual (n = 8) or recurrent (n = 9) SESCNs and were treated for ER. EMR failed to remove one residual SESCN. Of the 16 resected specimens, 10 were high-grade intraepithelial neoplasia (HGIN) and six were cancer. Eight cases had neoplasia extending to esophageal ducts/submucosal glands (SMGs). The pathological results may imply three possible routes in which residual/recurrent SESCNs occurred: HGIN without ductal/SMG involvement (37.5%), HGIN with ductal/SMG involvement (25.0%), and SCC with muscularis mucosae or deeper involvement (37.5%). Compared with the control group, the study group had similar procedural speed, en bloc resection rate, R0 resection rate, and complication rate. In conclusion, the safety and efficacy of post-RFA ESD were similar to those of primary ESD. ESD should be the treatment of choice for residual/recurrent SESCNs after initial RFA.
Ferroptosis in Cancer Progression
Authors: Zhang Rongyu , Chen Jinghong , Wang Saiyang , Zhang Wenlong , Zheng Quan , Cai Rong
Published: July 2023

Ferroptosis is a newly discovered iron-dependent form of regulated cell death driven by phospholipid peroxidation and associated with processes including iron overload, lipid peroxidation, and dysfunction of cellular antioxidant systems. Ferroptosis is found to be closely related to many diseases, including cancer at every stage. Epithelial–mesenchymal transition (EMT) in malignant tumors that originate from epithelia promotes cancer-cell migration, invasion, and metastasis by disrupting cell–cell and cell–cell matrix junctions, cell polarity, etc. Recent studies have shown that ferroptosis appears to share multiple initiators and overlapping pathways with EMT in cancers and identify ferroptosis as a potential predictor of various cancer grades and prognoses. Cancer metastasis involves multiple steps, including local invasion of cancer cells, intravasation, survival in circulation, arrest at a distant organ site, extravasation and adaptation to foreign tissue microenvironments, angiogenesis, and the formation of “premetastatic niche”. Numerous studies have revealed that ferroptosis is closely associated with cancer metastasis. From the cellular perspective, ferroptosis has been implicated in the regulation of cancer metastasis. From the molecular perspective, the signaling pathways activated during the two events interweave. This review briefly introduces the mechanisms of ferroptosis and discusses how ferroptosis is involved in cancer progression, including EMT, cancer angiogenesis, invasion, and metastasis.
Development and Validation of Epilepsy Life Skills Guidelines for Primary School Learners and Teachers in Limpopo and Mpumalanga Provinces
Authors: Makhado Thendo Gertie , Lebese Rachel Tsakani , Maputle Maria Sonto
Published: July 2023

Epilepsy is a disorder that disturbs nerve cell activity in the brain, resulting in seizures. It was noted that it occurs mostly in children, especially at the primary school level, and could result from a genetic condition. The aim of this study was to develop and validate life skills education guidelines for primary school learners of Limpopo and Mpumalanga provinces in South Africa to educate them about epilepsy with the aim of reducing stigma and discrimination towards people with epilepsy. The guidelines were developed by adapting the World Health Organization (WHO) guideline development guide, which included the formulation of PICOS (population, intervention, comparison, outcome, study design) questions, conducting a systematic review of the literature, and using GRADE (grading of recommendations assessment, development, and evaluation) to develop evidence-based recommendations. The recommendations that informed the guideline development were that epilepsy education should be included in the primary school life skills curriculum to improve learners’ understanding, attitudes, and skills related to epilepsy. This epilepsy education should be tailored to the needs of primary school learners and cover topics such as seizure recognition, management, medication, and coping strategies. Collaboration between healthcare providers, educators, and policymakers is crucial to developing culturally appropriate and evidence-based epilepsy education guidelines. Teachers and healthcare providers should also receive training on how to support learners living with epilepsy. The resulting guidelines provide clear and concise guidance on epilepsy education in life skills for primary school learners, caregivers, and teachers. The guidelines are expected to improve the quality of epilepsy life skills education and contribute to the overall well-being and inclusion of learners with epilepsy in Mpumalanga and Limpopo provinces, South Africa.
Physiological Responses during Parental Conflicts as Potential Biomarkers for Adolescent Depression
Authors: Wei Zegao , Yan Chao , Cui Lixian , Zhao Xudong , Liu Liang
Published: July 2023

Adolescents are a vulnerable population with a high prevalence of depression, yet there is a scarcity of biological markers for diagnosing depression specifically in this age group. In this case–control study, we examined physiological responses and facial expressions in adolescents with depression compared to healthy controls during parental conflict to identify potential biomarkers for adolescent depression. We recruited 33 families with adolescents diagnosed with depression and 25 families with healthy adolescents, matched for gender, age, and education. Baseline physiological measures, including electrocardiography (ECG), electrodermal activity (EDA), and respiration (RESP). During a 30 min parental conflict discussion, recorded on video, we analyzed the adolescents’ responses. The major depressive disorder (MDD) group displayed higher baseline heart rate (HR) and lower respiratory sinus arrhythmia (RSA). During the conflict discussion, they showed increased HR and shorter tonic periods of EDA compared to the healthy group. Facial expressions of both groups included neutral, sad, angry, and surprised. The MDD group exhibited fewer happy expressions. Receiver operating characteristic (ROC) curve analysis indicated that HR, interbeat interval (IBI), average NN interval (AVNN), number of NN50 intervals (NN50), and percentage of NN50 intervals (pNN50) had diagnostic potential for adolescent depression, with an area under the curve (AUC) greater than 0.7. Our findings suggest that adolescents with depression experience heightened sympathetic activation (higher HR) and weakened parasympathetic activity (lower RSA and HRV). These biomarkers hold promise for diagnosing adolescent depression.
Inhibition of Autophagy and the Cytoprotective Role of Smac Mimetic against ROS-Induced Cancer: A Potential Therapeutic Strategy in Relapse and Chemoresistance Cases in Breast Cancer
Authors: Rafat Sahar , Hakami Mohammed Ageeli , Hazazi Ali , Alsaiari Ahad Amer , Rashid Summya , Hasan Mohammad Raghibul , Aloliqi Abdulaziz A. , Eisa Alaa Abdulaziz , Dar Mohammad Irfan , Khan Mohd Faisal , Dev Kapil
Published: July 2023

With more than a million deaths each year, breast cancer is the top cause of death in women. Around 70% of breast cancers are hormonally responsive. Although several therapeutic options exist, cancer resistance and recurrence render them inefficient and insufficient. The major key reason behind this is the failure in the regulation of the cell death mechanism. In addition, ROS was also found to play a major role in this problem. The therapeutic benefits of Smac mimetic compound (SMC) BV6 on MCF7 were examined in the current study. Treatment with BV6 reduces viability and induces apoptosis in MCF7 breast cancer cells. BV6 suppresses autophagy and has demonstrated a defensive role in cancer cells against oxidative stress caused by H2O2. Overall, the present investigation shows that SMC has therapeutic and cytoprotective potential against oxidative stress in cancer cells. These Smac mimetic compounds may be used as anti-cancer drugs as well as antioxidants alone or in conjunction with other commonly used antioxidants.
Sea Coast of the Western Part of the Russian Arctic under Climate Change: Dynamics, Technogenic Influence and Potential Economic Damage
Authors: Ogorodov Stanislav , Badina Svetlana , Bogatova Daria
Published: July 2023

The Arctic coast dynamics has been an urgent problem over the last years, from both a practical and a fundamental point of view. In this research, for the first time for the Russian Arctic coast, we assessed the damage from the loss of territories in the western part of the Russian Arctic, where the active production and transportation of hydrocarbon material are carried out. Most of the studied coastline is composed of frozen unlithified soils with inclusions of underground ice. In this regard, the coastal zone is highly sensitive to climate change and its economic consequences. According to our investigation and literature data, the erosion rates could rich up to 2–3 m/year in some part of the coastline. Having estimated the cadastral cost of land and the area of the possible loss of territory, as well as the cost of transport infrastructure in the risk zone, we tried to predict the damage from changes in the total structure of the area under consideration. In particular, the economic damages from coastal permafrost processes were estimated. The assessment was conducted for the middle of the 21st century, taking into account the current climatic trend, erosion rate and probable maximum warming in this region.
Properties and Performance of TiAlSiN and AlCrN Monolayer and Multilayer Coatings for Turning Ti-6Al-4V
Authors: Liu Jie , Wang Yongchao , Liu Guiqian , Hua Junfang , Deng Xin
Published: July 2023

The high chemical activity, low thermal conductivity, and high strength of titanium alloys lead to severe tool wear during cutting. The coating applied to the tool surface insulates the effect of heat and chemical reactions. TiAlSiN coating and AlCrN coating are two representative coatings with excellent properties in TiN-based and CrN-based applications, respectively. Three types of nanocoatings—TiAlSiN monolayer, AlCrN monolayer, and TiAlSiN/AlCrN multilayer—were prepared, and the microstructure, mechanical properties, oxidation resistance, diffusion properties with titanium alloy, and cutting performance of the coatings were investigated utilizing SEM, TEM, XRD, TGA, GD-OES, nanoindentation, and scratching instruments. The hardness, elastic modulus, and adhesion strength of TiAlSiN/AlCrN multilayer coatings are between TiAlSiN monolayer and AlCrN monolayer coatings, which meet the “law of mixtures”. Adhesion strength is the primary condition for cutting applications and should have a minimum threshold value. Ti and N elements are the most significant in the diffusion between coatings and titanium alloys. The nitride coating containing Cr aggravates the loss of N in contact with the titanium alloy. In addition, multilayer structural coatings can lead to more severe diffusion than monolayer coatings due to their inherent interlayer defects. Although diffusion between titanium alloys and coated tools is more severe than with other workpiece materials, the main factor affecting tool cutting life is still the H3/E*2 value determined by the hardness and modulus of elasticity together.
Density-Functional Study of the Si/SiO2 Interfaces in Short-Period Superlattices: Structures and Energies
Authors: Smirnov Mikhail , Roginskii Evgenii , Savin Aleksandr , Mazhenov Nurlan , Pankin Dmitrii
Published: July 2023

The oxide-semiconductor interface is a key element of MOS transistors, which are widely used in modern electronics. In silicon electronics, SiO2 is predominantly used. The miniaturization requirement raises a problem regarding the growing of heterostructures with ultrathin oxide layers. Two structural models of interface between crystalline Si and cristobalite SiO2 are studied by using DFT-based computer modelling. The structures of several Si/SiO2 superlattices (SL), with layer thicknesses varied within 0.5–2 nm, were optimized and tested for stability. It was found that in both models the silicon lattice conserves its quasi-cubic structure, whereas the oxide lattice is markedly deformed by rotations of the SiO4 tetrahedra around axes perpendicular to the interface plane. Based on the analysis of the calculated total energy of SLs with different thicknesses of the layers, an assessment of the interface formation energy was obtained. The formation energy is estimated to be approximately 3–5 eV per surface Si atom, which is close to the energies of various defects in silicon. Elastic strains in silicon layers are estimated at 5–10%, and their value rapidly decreases as the layer thickens. The elastic strains in the oxide layer vary widely, in a range of 1–15%, depending on the interface structure.
Structure and Phase Transformations in Thin Films
Authors: Czigány Zsolt
Published: July 2023

The field of thin films has gone through a great development in recent decades [...]
Sustainable Alternatives to Cement: Synthesizing Metakaolin-Based Geopolymer Concrete Using Nano-Silica
Authors: Mohmmad Sarwar H. , Shakor Pshtiwan , Muhammad Jaza H. , Hasan Mustafa F. , Karakouzian Moses
Published: July 2023

The emission of carbon dioxide gas from the cement manufacturing industry has raised concerns about global warming. Geopolymer concrete (GC) is gaining attention as a sustainable and environmentally friendly alternative to traditional cement concrete. The current study focused on using local clay to synthesize and characterize metakaolin-based GC with varying percentages of nanosilica (NS) (1.5%, 3.0%, 4.5%, 6.0%, and 7.5% by weight of MK content) using NaOH/sodium silicate. The geopolymer specimens were cured at room temperature for 28 days, and their workability, compressive, tensile, and flexural strengths were measured to evaluate the influence of NS on the concrete’s mechanical properties. The study found that the compressive, tensile, and flexural strengths of the GC increased gradually up to 6.0% NS, but any further increase in its ratio resulted in a reduction in mechanical characteristics. The study concludes that the addition of 6.0% NS in metakaolin (MK)-based GC produces the highest mechanical properties, improving the compressive strength of the GC mix by 34.3% compared to the control GC mix and improving the flexural and split tensile strengths by 39% and 37%, respectively, compared to control GC strengths. Furthermore, the statistical analysis confirms nano-silica’s significant impact on geopolymer concrete’s mechanical properties, emphasizing its role in improving performance and sustainability as an alternative to cement-based materials.
Analysis and Characterization of Three Charge Thicknesses in TA1/Al1060/Al7075 Explosive Welding Composite Process
Authors: Xia Zhiqun , Wang Haitao , Shi Changgen , Sun Zerui , Wang Qiang , Luo Xvchuan
Published: July 2023

The titanium/aluminum composite materials overcome the limitations of single metal materials and achieve lightweight, high-strength, and corrosion-resistant properties. However, there have been no reports on explosion-welded composites of titanium alloys and seven-series aluminum alloys. Therefore, TA1/Al1060/Al7075 explosion-welded plates with three different explosive thicknesses were successfully prepared using Al1060 as the transition layer. The SPH-FEM coupled algorithm was employed to analyze the detonation process in detail and predict the interface under different explosive thicknesses. The results showed that during the explosion welding process, the high temperature, pressure, and high-speed impact resulted in significant plastic deformation and jetting phenomena at the bonding interface, which were in good agreement with the experimental observations. With the increase in explosive thickness, the TA1/Al1060 bonding interface exhibited a flat shape, while the Al1060/Al7075 interface transitioned from a flat to a wavy morphology. Moreover, the crack, vortex, and TiAl3 were observed at the interface. Mechanical testing results revealed that the composite plate with a 35 mm explosive thickness exhibited the best tensile, shear, and bending performance, indicating the optimal process parameter. This study provides significant support and reference for the application of explosion welding technology in titanium alloys and seven-series aluminum alloy composite materials.
Rapid Bio-Assisted Synthesis and Magnetic Behavior of Zinc Oxide/Carbon Nanoparticles
Authors: Abd-Elkader Omar H. , Deraz Nasrallah M. , Aleya Lotfi
Published: July 2023

The biomimetic synthesis of a ZnO/C nanocomposite has been achieved using the egg white-assisted self-combustion method. The characterization of this composite has been carried out using different techniques, such as XRD, FTIR, Raman, SEM/EDS and TEM. A comparative study was conducted between ZnO in the form of this composite and pristine ZnO, which was prepared via the same procedures but without the egg white. The resulting ZnO had a hexagonal structure, similar to wurtzite, with a P63mc space group. When this egg white method was used to produce a ZnO-based material, a ZnO/C nanocomposite was developed, and the ZnO’s crystallite size was significantly decreased. The structural properties—including the unit cell volume, strain, atom displacement and dislocation density—of this ZnO crystal are increased as a result of the presence of a C atom. On the other hand, the length of the Zn–O bond is reduced by the presence of the C atom. Results derived from a combination of Raman, FTIR, and EDS demonstrate that the carbonaceous layers and ZnO nanoparticles were integrated with a close interfacial contact. The preparation method used here brought about obvious changes in the morphological and magnetic behaviors of the as-prepared materials. Using a small amount of egg white resulted in the transformation of the particle’s shape from a hexagonal cone-type structure to an ellipsoidal structure. Based on an analysis of diffuse reflectance, the ZnO and ZnO/C band gap values were revealed using UV–VIS spectra. ZnO and ZnO/C exhibit band gap energies of 3.09 and 2.60 eV, respectively. A phase transition from weakly ferromagnetic to completely diamagnetic magnetic was discovered.
Strategic Insight into the Combination Therapies for Metastatic Colorectal Cancer
Authors: Kano Yoshihito , Suenaga Mitsukuni , Uetake Hiroyuki
Published: July 2023

Colorectal cancer (CRC) is the second most common cause of cancer-related deaths worldwide. The 5-year survival rate after curative resection is almost 80%, however, it is still less than satisfactory for metastatic CRC (mCRC). The combination approach including surgery, chemotherapy, molecular targeted therapy, and immunotherapy is a promising strategy due to its synergistic anticancer effect. Moreover, circulating tumor DNA (ctDNA) analysis has been reported to stratify the post-operative risk of recurrence, thus providing clinically valuable information for deciding to conduct adjuvant chemotherapy. Furthermore, multiple new drugs that potentially target undruggable genes, including KRAS, have been developed. In this review, we discuss the current management of patients with mCRC and future perspectives in the light of a combination therapeutic strategy.
Seminal Vesicle Treatment for Localized Prostate Cancer Treated with External Beam Radiotherapy
Authors: Steed Tanner , Chopra Nikki , Yun Jihyun , Hill Jordan , Burke Benjamin , Ghosh Sunita , Warkentin Brad , Usmani Nawaid
Published: July 2023

This study retrospectively reviewed data from men with localized prostate cancer treated with external beam radiotherapy (EBRT). We identified 359 men with localized prostate cancer treated with curative EBRT at the Cross Cancer Institute between 2010–2011. The volume of seminal vesicles (SVs) treated as well as dose values were extracted. These volumes were compared to gold standard contours drawn by a trained expert based on consensus European Society for Radiotherapy and Oncology (ESTRO) contouring guidelines. Patient and tumor characteristics were extracted for these patients. Memorial Sloan Kettering prostate cancer nomogram was used to assign a predicted risk of SV involvement for each patient based on baseline tumor characteristics. In patients with a predicted risk of SV involvement greater than 15% (n = 184), 86.5% (SD = 18.6) of the base of the SVs were treated with EBRT, compared to 66.7% (SD = 32.6) for patients with a predicted risk of SV involvement less than 15% (n = 175, p < 0.0001). Similarly, the mean percentage of proximal and total SV volumes treated with EBRT was 75.6% (SD = 24.4) and 68.7% (SD = 26.0) for patients with a predicted risk of SV involvement of greater than 15%, compared to 50.3% (SD = 31.0, p < 0.0001) and 41.0% (SD = 27.8, p < 0.0001) for patients with a risk of less than 15%. The results indicate that all parts of the SVs are more likely to be contoured in men with >15% risk of SV involvement than those with <15% risk. However, radiation oncologists still contour a high percentage of SVs in men with <15% risk of SV involvement, suggesting that there may be over-treatment of SVs that increases the risk of rectal or bladder toxicity.
Unipolar and Bipolar Depression Detection and Classification Based on Actigraphic Registration of Motor Activity Using Machine Learning and Uniform Manifold Approximation and Projection Methods
Authors: Zakariah Mohammed , Alotaibi Yousef Ajami
Published: July 2023

Modern technology frequently uses wearable sensors to monitor many aspects of human behavior. Since continuous records of heart rate and activity levels are typically gathered, the data generated by these devices have a lot of promise beyond counting the number of daily steps or calories expended. Due to the patient’s inability to obtain the necessary information to understand their conditions and detect illness, such as depression, objectively, methods for evaluating various mental disorders, such as the Montgomery–Asberg depression rating scale (MADRS) and observations, currently require a significant amount of effort on the part of specialists. In this study, a novel dataset was provided, comprising sensor data gathered from depressed patients. The dataset included 32 healthy controls and 23 unipolar and bipolar depressive patients with motor activity recordings. Along with the sensor data collected over several days of continuous measurement for each patient, some demographic information was also offered. The result of the experiment showed that less than 70 of the 100 epochs of the model’s training were completed. The Cohen Kappa score did not even pass 0.1 in the validation set, due to an imbalance in the class distribution, whereas in the second experiment, the majority of scores peaked in about 20 epochs, but because training continued during each epoch, it took much longer for the loss to decline before it fell below 0.1. In the second experiment, the model soon reached an accuracy of 0.991, which is as expected given the outcome of the UMAP dimensionality reduction. In the last experiment, UMAP and neural networks worked together to produce the best outcomes. They used a variety of machine learning classification algorithms, including the nearest neighbors, linear kernel SVM, Gaussian process, and random forest. This paper used the UMAP unsupervised machine learning dimensionality reduction without the neural network and showed a slightly lower score (QDA). By considering the ratings of the patient’s depressive symptoms that were completed by medical specialists, it is possible to better understand the relationship between depression and motor activity.
Comparative Evaluation of Breast Ductal Carcinoma Grading: A Deep-Learning Model and General Pathologists’ Assessment Approach
Authors: Köteles Maria Magdalena , Vigdorovits Alon , Kumar Darshan , Mihai Ioana-Maria , Jurescu Aura , Gheju Adelina , Bucur Adeline , Harich Octavia Oana , Olteanu Gheorghe-Emilian
Published: July 2023

Breast cancer is the most prevalent neoplasia among women, with early and accurate diagnosis critical for effective treatment. In clinical practice, however, the subjective nature of histological grading of infiltrating ductal adenocarcinoma of the breast (DAC-NOS) often leads to inconsistencies among pathologists, posing a significant challenge to achieving optimal patient outcomes. Our study aimed to address this reproducibility problem by leveraging artificial intelligence (AI). We trained a deep-learning model using a convolutional neural network-based algorithm (CNN-bA) on 100 whole slide images (WSIs) of DAC-NOS from the Cancer Genome Atlas Breast Invasive Carcinoma (TCGA-BRCA) dataset. Our model demonstrated high precision, sensitivity, and F1 score across different grading components in about 17.5 h with 19,000 iterations. However, the agreement between the model’s grading and that of general pathologists varied, showing the highest agreement for the mitotic count score. These findings suggest that AI has the potential to enhance the accuracy and reproducibility of breast cancer grading, warranting further refinement and validation of this approach.
Real-Life Diagnostic Performance of the Hypersensitivity Pneumonitis Guidelines: A Multicenter Cohort Study
Authors: Freund Ophir , Hadad Yitzhac , Shalmon Tamar , Wand Ori , Schneer Sonia , Perluk Tal Moshe , Kleinhendler Eyal , Hershko Tzlil , Tiran Boaz , Aviram Galit , Gershman Evgeni , Adir Yochai , Shitrit David , Bar-Shai Amir , Unterman Avraham
Published: July 2023

Hypersensitivity pneumonitis (HP) is a heterogeneous interstitial lung disease (ILD) that may be difficult to confidently diagnose. Recently, the 2020 ATS/JRS/ALAT HP diagnostic guidelines were published, yet data validating their performance in real-life settings are scarce. We aimed to assess the diagnostic performance of the HP guidelines compared to the gold-standard multidisciplinary discussion (MDD). For this purpose, we included consecutive ILD patients that underwent diagnostic bronchoscopy between 2017 and 2020 in three large medical centers. Four diagnostic factors (antigen exposure history, chest computed tomography pattern, bronchoalveolar lavage lymphocyte count, and histology results) were used to assign guidelines-based HP diagnostic confidence levels for each patient. A sensitivity analysis was performed, with MDD diagnosis as the reference standard. Overall, 213 ILD patients were included, 45 (21%) with an MDD diagnosis of HP. The guidelines’ moderate (≥70%) confidence threshold produced optimal performance with 73% sensitivity for HP, 89% specificity, and a J-index of 0.62. The area under the receiver operating characteristic curve (AUC) for a correct guidelines-based diagnosis was 0.86. The guidelines had better performance for non-fibrotic than fibrotic HP (AUC 0.92 vs. 0.82). All diagnostic factors, except bronchoalveolar lavage lymphocyte count, were independent predictors for MDD diagnosis of HP in a multivariate analysis. In conclusion, the HP guidelines exhibited a good diagnostic performance compared to MDD diagnosis in real-life setting.
QEHLR: A Q-Learning Empowered Highly Dynamic and Latency-Aware Routing Algorithm for Flying Ad-Hoc Networks
Authors: Xue Qiubei , Yang Yang , Yang Jie , Tan Xiaodong , Sun Jie , Li Gun , Chen Yong
Published: July 2023

With the growing utilization of intelligent unmanned aerial vehicle (UAV) clusters in both military and civilian domains, the routing protocol of flying ad-hoc networks (FANETs) has promised a crucial role in facilitating cluster communication. However, the highly dynamic nature of the network topology, owing to the rapid movement and changing direction of aircraft nodes, as well as frequent accesses and exits from the network, has resulted in an increased interruption rate of FANETs links. While traditional protocols can satisfy basic network service quality (QoS) requirements in mobile ad-hoc networks (MANETs) with relatively fixed topology changes, they may fail to achieve optimal routes and consequently restrict information dissemination in FANETs with topology changes, which ultimately leads to elevated packet loss and delay. This paper undertakes an in-depth investigation of the challenges faced by current routing protocols in high dynamic topology scenarios, such as delay and packet loss. It proposes a Q-learning empowered highly dynamic, and latency-aware routing algorithm for flying ad-hoc networks (QEHLR). Traditional routing algorithms are unable to effectively route packets in highly dynamic FANETs; hence, this paper employs a Q-learning method to learn the link status in the network and effectively select routes through Q-values to avoid connection loss. Additionally, the remaining time of the link or path lifespan is incorporated into the routing protocol to construct the routing table. QEHLR can delete predicted failed links based on network status, thereby reducing packet loss caused by failed route selection. Simulations show that the enhanced algorithm significantly improves the packet transmission rate, which addresses the challenge of routing protocols’ inability to adapt to various mobility scenarios in FANETs with dynamic topology by introducing a calculation factor based on the QEHLR protocol. The experimental results indicate that the improved routing algorithm achieves superior network performance.
Identifying Key Factors of Hazardous Materials Transportation Accidents Based on Higher-Order and Multilayer Networks
Authors: Ren Cuiping , Chen Bianbian , Xie Fengjie
Published: July 2023

This paper focuses on the application of higher-order and multilayer networks in identifying critical causes and relationships contributing to hazardous materials transportation accidents. There were 792 accidents of hazardous materials transportation that occurred on the road from 2017 to 2021 which have been investigated. By considering time sequence and dependency of causes, the hazardous materials transportation accidents causation network (HMTACN) was described using the higher-order model. To investigate the structure of HMTACN such as the importance of causes and links, HMTACN was divided into three layers using the weighted k-core decomposition: the core layer, the bridge layer and the peripheral layer. Then causes and links were analyzed in detail. It was found that the core layer was tightly connected and supported most of the causal flows of HMTACN. The results showed that causes should be given hierarchical attention. This study provides an innovative method to analyze complicated accidents, which can be used in identifying major causes and links. And this paper brings new ideas about safety network study and extends the applications of complex network theory.
Ecological Half-Life of 137Cs in Fish
Authors: Zarubina Nataliia , Semak Vladislav , Burdo Oleg S. , Ponomarenko Liliia P.
Published: July 2023

In this study, the long-term (i.e., over a 27-year period) dynamics of 137Cs content are presented for seven species of fish in both the cooling pond (CP) of the Chornobyl Nuclear Power Plant and the Kaniv Reservoir (KR). The decline of 137Cs specific activity in fish exhibits various patterns. For certain years in the KR, fish belonging to different ecological groups experienced an increase rather than a decrease in specific activity levels of 137Cs. From 2012 to 2014, the concentration of 137Cs in all studied species in the KR ranged from 4 to 23 Bq/kg. In the CP during 2012–2013, fish still showed high contamination levels, ranging from 770 to 8300 Bq/kg. The ecological half-life (Teco) was determined for all the studied fish species. For most fish species (i.e., P. fluviatilis, B. bjoerkna, A. brama, S. lucioperca, A. aspius), the shortest 137Cs Teco values were obtained in the CP, being a highly radiocaesium-contaminated waterbody. In contrast, two fish species (R. rutilus and S. glanis) in the CP exhibited a considerably slower rate of 137Cs removal from their bodies compared to even the relatively cleaner KR. Moreover, the 137Cs Teco in R. rutilus and S. glanis was nearly twice as long as that observed in other species within the CP. We assume that the redistribution of 137Cs in the body of fish is affected by multidirectional mechanisms: accumulation, retention, and/or excretion. The functioning of these mechanisms can vary among different fish species. The observed level of 137Cs content in a particular fish species at a given time point results from the combined effects of these mechanisms. Fish likely have the ability to absorb and accumulate radiocaesium in their bodies selectively, and this demand appears to be species-specific.
A COVID-19 Shift to Online Learning: A Comparison of Student Outcomes and Engagement for the Bacterial Unknown Identification Project
Authors: Fricker Ashwana Devi , Perri Kayla , Abdelhaseib Maha
Published: July 2023

Many microbiology classes include a bacterial unknown identification project (BUIP), in which students identify an unknown microorganism. The COVID-19 pandemic forced a change in instructional methods from an in-person to an online version of this project. Our aim was to determine how the shift in learning from in person to online impacted three aspects of student engagement: student satisfaction, as measured by the withdrawal rate from the course; student enthusiasm, evaluated by student self-efficacy; and student learning, determined using non-point-based questions. To address the effectiveness of these modified versions of the BUIP, approximately five hundred students completed multiple-choice and Likert-style surveys before and after the project across two semesters: the semesters immediately prior to and during the initial phase of the COVID-19 pandemic. We found that while each semester reflected increases in perceived engagement with the material (p < 0.05), overall, students reported feeling comfortable with the process of unknown identification irrespective of the semester. Surprisingly, learned information, as measured by pre- minus post-survey scores, was equal across semesters. Additionally, we observed fewer course withdrawals during the semester in which the project transitioned online. These data shed light on how the curriculum during the transition to online learning led to equivalent student learning but greater student engagement, and therefore points to the importance of comparing shifts in a curriculum within one course.
Undergraduate Skills Training in Pandemic Times: Where Is the Future of Medical Education?
Authors: Hecker Andrzej , Nischwitz Sebastian P. , Petritsch Johanna , Holzer-Geissler Judith C. J. , Draschl Alexander , Wegscheider Thomas , Lumenta David Benjamin
Published: July 2023

Background: The COVID-19 pandemic forced medical programs to rapidly switch to remote teaching from scratch, impacting hands-on skills training. This study compared the efficacy of a hybrid online format to a regular in-person session for a mandatory surgical skills class. Methods: Third-year undergraduate medical students attending the surgical skills class in the winter semester of 2020/21 at the Medical University of Graz were randomly assigned to either the hybrid or in-person class, depending on their course schedule and government regulations. The hybrid class involved online videos, one-on-one peer tutoring, and an Objective Structured Clinical Examination (OSCE). Pre- and post-class self-assessments were conducted to evaluate their theoretical and practical knowledge of a single interrupted suture. Results: The study included 85 students in the regular in-person class and 50 in the hybrid class. A pre-class assessment revealed higher self-assessments in the hybrid class for theoretical and practical knowledge, but a post-class assessment showed no significant difference. The advantages and disadvantages of both modalities were identified, providing valuable insights for future curriculum development. Conclusions: Both teaching modes were effective for undergraduate surgical skills training. This study recommends implementing positive aspects of both the hybrid and in-person formats while recognizing their respective limitations.
Testing the Associations between Coping, Mental Health, and Satisfaction with Life in Portuguese Workers
Authors: Rodrigues Filipe , Morouço Pedro , Santos Tiago
Published: July 2023

The present study aimed to explore the relationships between coping strategies, symptoms of depression, anxiety, and stress, and satisfaction with life among Portuguese workers. A sample of 402 participants (207 male, 195 female), ranging in age from 18 to 70 years (M = 32.90, SD = 11.75), was included in the study. Participants reported varying levels of work experience, ranging from 1 to 45 years (M = 10.62, SD = 4.07). The sample encompassed diverse occupations, including arts and design (n = 28), engineering (n = 23), marketing (n = 27), administration (n = 50), transportation and logistics (n = 57), clerks (n = 63), lawyers (n = 21), factory workers (n = 20), accountant and finance (n = 41), journalism (n = 27), health care (n = 29), and others (n = 16). To examine the associations between each determinant and satisfaction with life, hierarchical multiple regression analyses were conducted. Two models were tested, with predictors entered in blocks based on theoretical and empirical considerations. The second model accounted for 52.4% of the variance in satisfaction with life (F (14, 384) = 3.884, p < 0.001, R2 = 0.27, adjusted R2 = 0.24). Depressive symptoms and stress consistently exhibited a significant association (p < 0.05) with satisfaction with life across all tested models. In terms of coping mechanisms, instrumental support reinterpretation, disengagement, and humor demonstrated a significant association with satisfaction with life (p < 0.05). The findings suggest that employing adaptive coping strategies may help mitigate symptoms of mental distress and enhance satisfaction with life. By understanding the relationships between coping strategies, mental health symptoms, and satisfaction with life, interventions can be developed to promote well-being and improve overall quality of life among Portuguese workers.
An Optimal Network-Aware Scheduling Technique for Distributed Deep Learning in Distributed HPC Platforms
Authors: Lee Sangkwon , Raza Shah Syed Asif , Seok Woojin , Moon Jeonghoon , Kim Kihyeon , Raza Shah Syed Hasnain
Published: July 2023

Deep learning is a growing technique used to solve complex artificial intelligence (AI) problems. Large-scale deep learning has become a significant issue as a result of the expansion of datasets and the complexity of deep learning models. For training large-scale models, the cloud can be used as a distributed HPC (high-performance computing) tool with benefits in cost and flexibility. However, one of the major performance barriers in distributed deep learning in a distributed HPC environment is the network. The performance is often limited by heavy traffic like many stochastic gradient descent transfers for distributed communication. There are many network studies in distributed deep learning to solve these problems, but most research only focuses on improving communication performance and applying new methods or algorithms like overlapping parameter synchronization to minimize communication delay rather than considering the actual network. In this paper, we are focusing on the actual network, especially in a distributed HPC environment. In such an environment, if cluster nodes are assigned to different zones/regions which means a set of an appropriate number of distributed HPC nodes when performing distributed deep learning tasks, performance degradation due to network delay may occur. The proposed network optimization algorithm ensures that distributed work is placed in the same zone as much as possible to reduce network delay. Furthermore, scoring using network monitoring tools like loss, delay, and throughput is applied to select the optimal node within the zone. Our proposal has been validated on the Kubernetes platform, an open source orchestrator for the automatic management and deployment of micro-services. The performance of distributed deep learning is improved through the proposed scheduler.
Improved Vehicle Detection Using Weather Classification and Faster R-CNN with Dark Channel Prior
Authors: Tian Ershang , Kim Juntae
Published: July 2023

Recent advancements in artificial intelligence have led to significant improvements in object detection. Researchers have focused on enhancing the performance of object detection in challenging environments, as this has the potential to enhance practical applications. Deep learning has been successful in image classification and target detection and has a wide range of applications, including vehicle detection. However, object detection models trained on high-quality images often struggle to perform well under adverse weather conditions, such as fog and rain. In this paper, we propose an improved vehicle detection method using weather classification and a Faster R-CNN with a dark channel prior (DCP). The proposed method first classifies the weather within the image, preprocesses the image using the dark channel prior (DCP) based on the classification result, and then performs vehicle detection on the preprocessed image using a Faster R-CNN. The effectiveness of the proposed method is shown through experiments with images in various weather conditions.
Research on the Classification Methods of Social Bots
Authors: Liu Xiaohan , Zhan Yue , Jin Hao , Wang Yuan , Zhang Yi
Published: July 2023

In order to ensure the healthy development of social networks and the harmony and stability of the society, as well as to facilitate effective supervision by regulatory authorities, a classification method of social bots is proposed based on the identification of social bots in the early stage. First of all, the topic-related introduction is used to expand the topic, and on this basis, the SBERT (Sentence-BERT) model is applied to make relevance judgments between the micro-blog text and the expanded topics to identify polluters. Then, an opinion sentence recognition method that combines social bots opinion sentence generation rules with a deep learning model TextCNN is proposed to further distinguish commenters and spreaders. Finally, in order to improve the classification effect of the model, the transfer learning method is used to train the model with the help of a large number of micro-blogs of ordinary Weibo accounts, so as to better improve the classification effect of social bots. The comparative experimental results show that the topic expansion method can effectively improve the classification results of the SBERT model for the relevance of micro-blog text topics. When the parameter k of the expanded topic model is set at 20, the content of the expanded topic sequence is more consistent with the core content of most Weibo text sequences, and the obtained model has the best performance. By analyzing the opinion-based micro-blog text generation rules of social bots, focusing on the keywords that express opinions, the problem of difficulty in recognizing opinion sentences produced by the low quality of opinion sentences of social bots is well resolved, and the recognition effect of opinion sentences has been improved by more than 10%. Through the introduction of transfer learning, the problem of insufficient social bots data is effectively alleviated, and the classification effect of social bots is greatly improved, with an increase of more than 10%.
Enhancing Artifact Protection in Smart Transportation Monitoring Systems via a Porous Structural Triboelectric Nanogenerator
Authors: Zhang Jiabin , Su Erming , Li Chengyu , Xu Shuxing , Tang Wei , Cao Leo N.Y. , Li Ding , Wang Zhong Lin
Published: July 2023

Artifacts are irreplaceable treasures of human culture, and transportation monitoring is critical for safeguarding valuable artifacts against damage during culture exchanges. However, current collision-monitoring technologies have limitations in regard to real-time monitoring, cushioning protection, and power supply requirements. Here, we present a method for constructing a smart artifact-monitoring system (SAMS) based on a porous carbon black (CB)/Ecoflex triboelectric nanogenerator (PCE-TENG) that can monitor collisions in real time and absorb vibrations during artifact transportation. The PCE-TENG is assembled using a flexible printed circuit board (FPCB) and a porous Ecoflex layer with CB powder. It exhibits cushioning protection, stretchability, pressure sensitivity, and durability. To enhance its electrical output, modifications were made to optimize the CB content and surface structure. The SAMS comprises six PCE-TENGs attached to the inner wall of the artifact transport package and enables collision monitoring and protection in different directions. Moreover, the SAMS has the capability to instantly transmit warning information to monitoring terminals in the event of improper operations, empowering carriers to promptly and efficiently safeguard artifacts by taking necessary measures. This paper presents a practical strategy for artifact transportation monitoring and package engineering that could have significant implications for the field.