bluuebunny/crossref_metadata_2025 huggingface dataset:
Attentional Bias Modification Training Based on Virtual Reality and Eye Tracking in Anorexia Nervosa Patients
Authors: Ascione Mariarca , Carulla-Roig Marta , Miquel-Nabau Helena , Porras-Garcia Bruno , Meschberger-Annweiler Franck-Alexandre , Serrano-Troncoso Eduardo , Ferrer-Garcia Marta , Moreno-Sánchez Manuel , Gutierrez-Maldonado Jose
Published: September 2023

Anorexia nervosa (AN) patients exhibit attentional bias (AB) related to the body, which is the tendency to pay greater attention to weight-related body areas compared to non-weight-related ones. This phenomenon has been linked to elevated levels of body dissatisfaction (BD) and may potentially reduce the effectiveness of body exposure therapy. The purpose of this pilot study is to assess the efficacy of a single session of a new body-related AB modification task (ABMT) that combines virtual reality with eye tracking in patients with AN. The goals of the ABMT are to reduce body-related AB by balancing attention between weight and non-weight-related body areas and to reduce BD levels. Twenty-three adolescent patients with AN were embodied in a virtual avatar and immersed in a virtual environment where they completed the ABMT. Body-related AB measures and BD levels were assessed before and after the training. A paired samples t-test showed statistically significant differences between pre-assessment and post-assessment; the complete fixation time on weight-related body parts was reduced and BD levels decreased. The initial evidence of the efficacy of this ABMT has important clinical implications, since AB and BD are considered risk factors for developing and maintaining eating disorder symptomatology among patients with AN.
Microvascular Obstruction in Acute Myocardial Infarction, a Potential Therapeutic Target
Authors: Ghobrial Mina , Bawamia Bilal , Cartlidge Timothy , Spyridopoulos Ioakim , Kunadian Vijay , Zaman Azfar , Egred Mohaned , McDiarmid Adam , Williams Matthew , Farag Mohamed , Alkhalil Mohammad
Published: September 2023

Microvascular obstruction (MVO) is a recognised phenomenon following mechanical reperfusion in patients presenting with ST-segment elevation myocardial infarction (STEMI). Invasive and non-invasive modalities to detect and measure the extent of MVO vary in their accuracy, suggesting that this phenomenon may reflect a spectrum of pathophysiological changes at the level of coronary microcirculation. The importance of detecting MVO lies in the observation that its presence adds incremental risk to patients following STEMI treatment. This increased risk is associated with adverse cardiac remodelling seen on cardiac imaging, increased infarct size, and worse patient outcomes. This review provides an outline of the pathophysiology, clinical implications, and prognosis of MVO in STEMI. It describes historic and novel pharmacological and non-pharmacological therapies to address this phenomenon in conjunction with primary PCI.
Long-Term Consequences of COVID-19 in Predominantly Immunonaive Patients: A Canadian Prospective Population-Based Study
Authors: Benoit-Piau Justine , Tremblay Karine , Piché Alain , Dallaire Frédéric , Bélanger Mathieu , d’Entremont Marc-André , Pasquier Jean-Charles , Fortin Martin , Bourque Catherine , Lapointe Fanny , Betala-Belinga Jean-François , Petit Geneviève , Jourdan Guillaume , Bahous Renata , Maya Camilo , Benzina Amira , Faiyaz Hossain Muhammad , Peel Marie-Audrey , Houle Olivier , Auger Marie-Sandrine , Rioux Antoine , Farand Paul
Published: September 2023

Background: Lingering symptoms are frequently reported after acute SARS-CoV-2 infection, a condition known as post-COVID-19 condition (PCC). The duration and severity of PCC in immunologically naïve persons remain unclear. Furthermore, the long-term consequences of these chronic symptoms on work and mental health are poorly documented. Objective: To determine the outcome, the risk factors, and the impact on work and mental health associated with post-COVID-19 symptoms. Methods: This prospective population-based study assessed acute COVID-19 symptoms and their evolution for up to nine months following infection. Individuals aged 18 years and older with COVID-19 in three Canadian regions between 1 November 2020 and 31 May 2021 were recruited. Participants completed a questionnaire that was either administered by trained student investigators over the phone or self-administered online. Results: A total of 1349 participants with a mean age of 46.6 ± 16.0 years completed the questionnaire. Participants were mostly unvaccinated at the time of their COVID-19 episode (86.9%). Six hundred and twenty-two participants (48.0%) exhibited one symptom or more, at least three months post-COVID-19. Among participants with PCC, 23.0% to 37.8% experienced fatigue at the time of survey. Moreover, 6.1% expressed psychological distress. Risk factors for PCC and fatigue included female sex (OR = 1.996), higher number of symptoms (OR = 1.292), higher severity of episode (OR = 3.831), and having a mental health condition prior to the COVID-19 episode (OR = 5.155). Conclusions: In this multicenter cohort study, almost half (47%) of the participants reported persistent symptoms >3 months after acute infection. Baseline risk factors for PCC include female sex, number and severity of symptoms during acute infection, and a previous diagnosis of mental health disorder. Having PCC negatively impacted health-related quality of life and these patients were more likely to exhibit psychological distress, as well as fatigue.
Machine Learning Predicts 30-Day Outcome among Acute Myeloid Leukemia Patients: A Single-Center, Retrospective, Cohort Study
Authors: Lee Howon , Han Jay Ho , Kim Jae Kwon , Yoo Jaeeun , Yoon Jae-Ho , Cho Byung Sik , Kim Hee-Je , Lim Jihyang , Jekarl Dong Wook , Kim Yonggoo
Published: September 2023

Acute myeloid leukemia (AML) is a clinical emergency requiring treatment and results in high 30-day (D30) mortality. In this study, the prediction of D30 survival was studied using a machine learning (ML) method. The total cohort consisted of 1700 survivors and 130 non-survivors at D30. Eight clinical and 42 laboratory variables were collected at the time of diagnosis by pathology. Among them, six variables were selected by a feature selection method: induction chemotherapy (CTx), hemorrhage, infection, C-reactive protein, blood urea nitrogen, and lactate dehydrogenase. Clinical and laboratory data were entered into the training model for D30 survival prediction, followed by testing. Among the tested ML algorithms, the decision tree (DT) algorithm showed higher accuracy, the highest sensitivity, and specificity values (95% CI) of 90.6% (0.918–0.951), 70.4% (0.885–0.924), and 92.1% (0.885–0.924), respectively. DT classified patients into eight specific groups with distinct features. Group 1 with CTx showed a favorable outcome with a survival rate of 97.8% (1469/1502). Group 6, with hemorrhage and the lowest fibrinogen level at diagnosis, showed the worst survival rate of 45.5% (25/55) and 20.5 days. Prediction of D30 survival among AML patients by classification of patients with DT showed distinct features that might support clinical decision-making.
Impact of the COVID-19 Pandemic on the Epidemiology of Bloodstream Infections in Hospitalized Patients—Experience from a 4th Military Clinical Hospital in Poland
Authors: Słabisz Natalia , Dudek-Wicher Ruth , Leśnik Patrycja , Majda Jacek , Kujawa Krzysztof , Nawrot Urszula
Published: September 2023

Bloodstream infections (BSIs) are associated with high mortality and inappropriate or delayed antimicrobial therapy. The purpose of this study was to investigate the impact of the COVID-19 pandemic on the epidemiology of BSIs in hospitalized patients. The research aimed to compare the incidence of BSIs and blood culture results in patients hospitalized before and during the COVID-19 pandemic. Methods: Retrospective and prospective data were collected from blood cultures obtained from 4289 patients hospitalized between June 2018 and July 2022. Two groups of patients were distinguished: those with BSIs admitted during the pre-COVID-19 period and those admitted during the COVID-19 surge. Demographic and clinical data, blood cytology, and biochemistry results were analyzed, and the usefulness of PCT was assessed in patients with COVID-19. Results: The study showed a significant increase in the incidence of BSIs during the pandemic compared to the pre-COVID-19 period. Positive blood cultures were obtained in 20% of patients hospitalized during the pandemic (vs. 16% in the pre-COVID-19 period). The incidence of BSIs increased from 1.13 to 2.05 cases per 1000 patient days during COVID-19, and blood culture contamination was more frequently observed. The mortality rate was higher for patients hospitalized during the COVID-19 pandemic. An increased frequency of MDRO isolation was observed in the COVID-19 period. Conclusions: The incidence of BSIs increased and the mortality rate was higher in the COVID-19 period compared to the pre-COVID-19 period. The study showed limited usefulness of procalcitonin in patients with COVID-19, likely due to the administered immunosuppressive therapy.
ANRIL rs4977574 Gene Polymorphism in Women with Recurrent Pregnancy Loss
Authors: Cherouveim Panagiotis , Mavrogianni Despoina , Drakaki Eirini , Potiris Anastasios , Zikopoulos Athanasios , Papamentzelopoulou Myrto , Kouvoutsaki Konstantina , Machairiotis Nikolaos , Karampitsakos Theodoros , Skentou Chara , Domali Ekaterini , Vrachnis Nikolaos , Drakakis Peter , Stavros Sofoklis
Published: September 2023

Background: ANRIL rs4977574 gene polymorphism has been associated with arterial thrombosis and cardiovascular disease development. ANRIL rs4977574 gene polymorphism could also be associated with recurrent pregnancy loss (RPL) since there is increasing evidence in favor of a potential shared pathophysiological mechanism with cardiovascular disease, potentially through arterial thrombosis. This study’s goal is to investigate the differences in ANRIL rs4977574 gene polymorphism between women with and without RPL, if any, as well as a potential association with the number of pregnancy losses. Methods: DNA was isolated from peripheral blood samples, and the sequence containing the polymorphism of interest was amplified with PCR. Results were visualized under UV light following electrophoresis in 3% agarose gel with ethidium bromide. ANRIL rs4977574 (A>G) prevalence was compared between 56 women with and 69 without RPL. Results were adjusted for women’s age and BMI, while a stratified analysis was performed according to number of pregnancy losses. Results: Allele A was significantly more prevalent in the control group compared to RPL women [31 (44.9%) vs. 14 (25%), p = 0.021]. Although not reaching statistical significance, a gradually decreasing prevalence of allele A with an increasing number of pregnancy losses was observed [31 (44.9%) in control, eight (30.7%) with two, six (23.1%) with three, and 0 (0.0%) with four pregnancy losses, p = 0.078]. Results were also similar following adjustment. Conclusions: This is the first study that demonstrates an association between RPL presence and ANRIL rs4977574 gene polymorphism (lower prevalence of allele A), while a difference according to the number of pregnancy losses cannot be excluded.
Cannulation Technique of Vascular Access in Hemodialysis and the Impact on the Arteriovenous Fistula Survival: Systematic Review and Meta-Analysis
Authors: Peralta Ricardo , Sousa Luís , Cristovão António Filipe
Published: September 2023

Adequate cannulation technique (CT) methods and successful puncture are essential for hemodialysis (HD) and arteriovenous fistula (AVF) maintenance. This systematic review and meta-analysis was designed to identify which CT allows better AVF primary patency and lower rates of complications in HD patients. The search was carried out on the CINAHL, MEDLINE, Cochrane Library, and Joanna Briggs Institute Library databases to identify all randomized controlled trials (RCTs) and observational studies comparing clinical outcomes of buttonhole (BH) versus rope ladder cannulation (RL) from 2010 to 2022. The Risk-of-Bias (Rob 2) tool was used for RCTs and the ROBINS-I was used for non-randomized studies. RevMan 5.4 was used for the meta-analysis. A total of five RCTs, one quasi-randomized controlled trial, and six observational studies were included. When compared with RL cannulation, BH cannulation significantly increased bacteremia (RR, 2.76, 95% CI (1.14, 6.67), p = 0.02) but showed no differences in AVF primary patency (HR, 1.06, 95% CI (0.45, 4.21), p = 0.90). There was no thrombosis reduction (RR, 0.51, 95% CI (0.23, 1.14), p = 0.10) or intervention number reduction (RR, 0.93, 95% CI (0.49, 1.80), p = 0.84) with BH. Outcomes like pain, hematoma, and aneurism could not be merged due to a lack of data, reported as medians, as well as due to different definitions. The quality in general was poor and the heterogeneity among the studies prevented us from merging the outcomes.
Multifunctional Fiber-Reinforced Polymer Composites for Damage Detection and Memory
Authors: Demo Luke B. , Tronci Eleonora M. , Feng Maria Q.
Published: September 2023

Self-structural health monitoring (SHM) functionalities for fiber-reinforced polymer composites have become highly sought after to ensure the structural safety of newly advancing components in the automotive, civil, mechanical, and aerospace industries. This paper introduces a self-damage detection and memory (SDDM) hybrid composite material, where the structural carbon fiber tow is transformed into a piezoresistive sensor network, and the structural glass fiber operates as electrical insulation. In this study, SDDM specimens were fabricated, and tensile and impact tests were performed. The tensile tests of SDDM specimens find two distinct loading peaks: first where the carbon fiber fails, and second where the glass fiber fails. A linear correlation was observed between the carbon fiber resistance and composite strain up to a threshold, beyond which a sharp nonlinear increase in resistance occurred. The resistance then approached infinity, coinciding with the first loading peak and failure of the carbon fiber elements. This demonstrates the potential for a damage early warning threshold. Additionally, the effect of stitching the sensor tow in a zig-zag pattern over a large area was investigated using tailored fiber placement (TFP) of 1-loop, 3-loop, and 5-loop specimens. Tensile testing found that increasing the number of loops improved the sensor’s accuracy for strain sensing. Furthermore, impact tests were conducted, and as the impact energy progressively increased, the sensor resistance permanently increased. This illustrates a capability for self-memory of microdamage throughout the life cycle of the structure, potentially useful for predicting the remaining life of the composite.
Graphene Nanocomposites for Electromagnetic Interference Shielding—Trends and Advancements
Authors: Kausar Ayesha , Ahmad Ishaq , Zhao Tingkai , Aldaghri Osamah , Ibnaouf Khalid H. , Eisa M. H. , Lam Tran Dai
Published: September 2023

Electromagnetic interference is considered a serious threat to electrical devices, the environment, and human beings. In this regard, various shielding materials have been developed and investigated. Graphene is a two-dimensional, one-atom-thick nanocarbon nanomaterial. It possesses several remarkable structural and physical features, including transparency, electron conductivity, heat stability, mechanical properties, etc. Consequently, it has been used as an effective reinforcement to enhance electrical conductivity, dielectric properties, permittivity, and electromagnetic interference shielding characteristics. This is an overview of the utilization and efficacy of state-of-the-art graphene-derived nanocomposites for radiation shielding. The polymeric matrices discussed here include conducting polymers, thermoplastic polymers, as well as thermosets, for which the physical and electromagnetic interference shielding characteristics depend upon polymer/graphene interactions and interface formation. Improved graphene dispersion has been observed due to electrostatic, van der Waals, π-π stacking, or covalent interactions in the matrix nanofiller. Accordingly, low percolation thresholds and excellent electrical conductivity have been achieved with nanocomposites, offering enhanced shielding performance. Graphene has been filled in matrices like polyaniline, polythiophene, poly(methyl methacrylate), polyethylene, epoxy, and other polymers for the formation of radiation shielding nanocomposites. This process has been shown to improve the electromagnetic radiation shielding effectiveness. The future of graphene-based nanocomposites in this field relies on the design and facile processing of novel nanocomposites, as well as overcoming the remaining challenges in this field.
Estrogen Deficiency Impairs Osseointegration in Hypertensive Rats Even Treated with Alendronate Coated on the Implant Surface
Authors: Mulinari-Santos Gabriel , dos Santos Jaqueline Silva , Kitagawa Igor Lebedenco , de Souza Batista Fábio Roberto , Botacin Paulo Roberto , Antoniali Cristina , Lisboa-Filho Paulo Noronha , Okamoto Roberta
Published: September 2023

Hypertension and estrogen deficiency can affect bone metabolism and therefore increase the risk of osseointegration. Antihypertensive drugs such as losartan not only control blood pressure but also enhance bone healing. In addition, alendronate sodium is widely used to treat postmenopausal osteoporosis. Hence, we evaluated the effect of systemic antihypertensive and local alendronate coted on implants on osseointegration under hypertensive and estrogen-deficiency conditions. A total of 64 spontaneously hypertensive rats (SHRs) treated with losartan were randomly divided according to the estrogen-deficiency induction by ovariectomy (OVX) or not (SHAM), and whether the implant surface was coated with sodium alendronate (ALE) or not, resulting in four groups: SHR SHAM, SHR SHAM ALE, SHR OVX, and SHR OVX ALE. The removal torque, microcomputed tomography, and epifluorescence microscopy were the adopted analyses. The hypertensive and estrogen-deficiency animals presented a lower removal torque even when treated with alendronate on implant surface. The microcomputed tomography revealed a higher bone volume and bone-to-implant contact in the SHRs than the SHR OVX rats. Epifluorescence showed a decreased mineral apposition ratio in the SHR OVX ALE group. The data presented indicate that estrogen deficiency impairs osseointegration in hypertensive rats; in addition, alendronate coated on the implant surface does not fully reverse this impaired condition caused by estrogen deficiency.
Fungal Glycosidases in Sporothrix Species and Candida albicans
Authors: Ortiz-Ramírez Jorge A. , Cuéllar-Cruz Mayra , Villagómez-Castro Julio C. , López-Romero Everardo
Published: September 2023

Glycoside hydrolases (GHs) are enzymes that participate in many biological processes of fungi and other organisms by hydrolyzing glycosidic linkages in glycosides. They play fundamental roles in the degradation of carbohydrates and the assembly of glycoproteins and are important subjects of studies in molecular biology and biochemistry. Based on amino acid sequence similarities and 3-dimensional structures in the carbohydrate-active enzyme (CAZy), they have been classified in 171 families. Members of some of these families also exhibit the activity of trans-glycosydase or glycosyl transferase (GT), i.e., they create a new glycosidic bond in a substrate instead of breaking it. Fungal glycosidases are important for virulence by aiding tissue adhesion and colonization, nutrition, immune evasion, biofilm formation, toxin release, and antibiotic resistance. Here, we review fungal glycosidases with a particular emphasis on Sporothrix species and C. albicans, two well-recognized human pathogens. Covered issues include a brief account of Sporothrix, sporotrichosis, the different types of glycosidases, their substrates, and mechanism of action, recent advances in their identification and characterization, their potential biotechnological applications, and the limitations and challenges of their study given the rather poor available information.
Becoming aWARE: The Development of a Web-Based Tool for Autism Research and the Environment
Authors: Singh Anisha , Lawler Cindy P. , Walker Vickie R. , Pelch Katherine E. , Garton Amanda E. , Rooney Andrew A. , Haugen Astrid C.
Published: September 2023

A sharp rise in autism spectrum disorder (ASD) prevalence estimates, beginning in the 1990s, suggested factors additional to genetics were at play. This stimulated increased research investment in nongenetic factors, including the study of environmental chemical exposures, diet, nutrition, lifestyle, social factors, and maternal medical conditions. Consequently, both peer- and non-peer-reviewed bodies of evidence investigating environmental contributors to ASD etiology have grown significantly. The heterogeneity in the design and conduct of this research results in an inconclusive and unwieldy ‘virtual stack’ of publications. We propose to develop a Web-based tool for Autism Research and the Environment (aWARE) to comprehensively aggregate and assess these highly variable and often conflicting data. The interactive aWARE tool will use an approach for the development of systematic evidence maps (SEMs) to identify and display all available relevant published evidence, enabling users to explore multiple research questions within the scope of the SEM. Throughout tool development, listening sessions and workshops will be used to seek perspectives from the broader autism community. New evidence will be indexed in the tool annually, which will serve as a living resource to investigate the association between environmental factors and ASD.
VNF-Enabled 5G Network Orchestration Framework for Slice Creation, Isolation and Management
Authors: Srinivasan Thiruvenkadam , Venkatapathy Sujitha , Jo Han-Gue , Ra In-Ho
Published: September 2023

Network slicing is widely regarded as the most critical technique for allocating network resources to varied user needs in 5G networks. A Software Defined Networking (SDN) and Network Function Virtualization (NFV) are two extensively used strategies for slicing the physical infrastructure according to use cases. The most efficient use of virtual networks is realized by the application of optimal resource allocation algorithms. Numerous research papers on 5G network resource allocation focus on network slicing or on the best resource allocation for the sliced network. This study uses network slicing and optimal resource allocation to achieve performance optimization using requirement-based network slicing. The proposed approach includes three phases: (1) Slice Creation by Machine Learning methods (SCML), (2) Slice Isolation through Resource Allocation (SIRA) of requests via a multi-criteria decision-making approach, and (3) Slice Management through Resource Transfer (SMART). We receive a set of Network Service Requests (NSRs) from users. After receiving the NSRs, the SCML is used to form slices, and SIRA and SMART are used to allocate resources to these slices. Accurately measuring the acceptance ratio and resource efficiency helps to enhance overall performance. The simulation results show that the SMART scheme can dynamically change the resource allocation according to the test conditions. For a range of network situations and Network Service Requests (NSRs), the performance benefit is studied. The findings of the simulation are compared to those of the literature in order to illustrate the usefulness of the proposed work.
Study into the Evolution of Spatiotemporal Characteristics and Driving Mechanisms of Production–Living–Ecological Spaces on the Indochina Peninsula
Authors: Lu Shuang , Zhou Zibo , Houding Mingyang , Yang Liu , Gao Qiang , Cao Chenglong , Li Xiang , Bu Ziqiang
Published: September 2023

Influenced by historical background, regional economic development, and the frequent occurrence of armed conflict, the human–earth relationship in the Central and Southern Peninsula, which is located in a “fragmented zone”, is characteristic of the region. The Indochina Peninsula has now become an area of interest for the study of spatial changes in production–living–ecological spaces (PLES). Taking the Indochina Peninsula as the study area, this paper explores the evolution of the spatiotemporal patterns of PLES and its driving mechanism in the Indochina Peninsula, from 2010 to 2020, based on a grid scale. Methods such as the land-use transition matrix, land-use dynamics index, and geographically and temporally weighted regression (GTWR) were used in our model, which will provide the basic data and reference for sustainable development planning across the Indochina Peninsula. Our results show that, from 2010 to 2020, ecological space dominated the PLES pattern on the Indochina Peninsula, but its area gradually decreased, accompanied by a sharp increase in the areas of productive and living spaces. The area of PLES interconversion on the Indochina Peninsula in 2010–2020 was 212,818.70 km2, and the intertransfer of production and ecological spaces was distributed in a networklike manner throughout the Indochina Peninsula, while the transfer of living space was distributed in a pointlike manner. The migration path of the center of gravity of PLES on the Indochina Peninsula demonstrated a significant directional difference, and the direction and extent of the standard deviation ellipse distribution of the ecological space was similar to that of the production space. The PLES’s pattern evolution was affected by the degree of multiple factors, with a significant spatial and temporal heterogeneity. The positive and negative feedback effects of the factors were distributed in different areas and in different transfer directions.
Enhanced Understanding of Key Soil Properties in Northern Xinjiang Using Water-Heat-Spectral Datasets Based on Bioclimatic Guidelines
Authors: Wang Fei , Wei Yang , Yang Shengtian
Published: September 2023

Current digital soil mapping of soil properties (soil organic carbon, SOC; electrical conductivity, EC; and pH) is mainly based on transfer learning, which is inadequate in terms of accuracy for the northern plain area of Xinjiang. To address this issue, establishing a new model is urgently required that can improve our understanding of the soil properties in this region. To this end, based on the global bioclimatic variables and surface dry–wet and wet–dry transitions, The study developed a spectral–water–heat database (SWHD). The study then incorporated this database and background data into machine learning algorithms (XGBoost, LightGBM, and random forest) to establish models applicable to the study area and draw spatial changes in the key soil properties. Our findings revealed that the organic carbon content was the highest in grasslands, whereas shrublands had high soil salinity. The pH value indicated overall alkalinity in the study area. Additionally, the SWHD-based predictions outperformed the mean or maximum value datasets, with LightGBM showing superior performance among all models. Furthermore, the validation accuracy obtained through our optimal algorithm was significantly higher than that obtained by other products, such as Harmonized World Soil Database (HWSD) and SoilGrid250, likely because of the limitations of these datasets, which may represent historical soil properties rather than current variations in the soil properties in the region. The study also observed that the mean SOC and EC values significantly decreased compared to the historical data, while the decrease in pH was smaller but not significant. Structural equation modeling and variable importance analysis revealed that the variables with the greatest influence on modeling SOC, EC, and pH were BIO10, DTW2021_406-426_B3 (Surface reflectance acquired in spring), and land use type. Our improved model developed based on the SWHD dataset offers important scientific evidence and decision support for land use management and provides a solid foundation for future research in this field.
An Exploratory Study of EFL Learners’ Use of ChatGPT for Language Learning Tasks: Experience and Perceptions
Authors: Xiao Yangyu , Zhi Yuying
Published: September 2023

ChatGPT, a general-purpose intelligent chatbot developed by OpenAI, has introduced numerous opportunities and challenges in the field of language education. With its remarkable ability to generate diverse forms of text, answer questions, and provide translations within minutes, ChatGPT has become an influential tool in the era of advanced AI technology. However, to what extent ChatGPT can be used to assist students in completing language learning tasks remains largely unexplored. Against this background, this study aimed to investigate students’ experiences with ChatGPT and their perceptions of its role in language learning through a small-scale qualitative study. The data were collected through semi-structured interviews with five students at a top-tier international university in China. Students’ responses revealed that ChatGPT has the potential to serve as a valuable learning partner and aid students in completing language-related tasks. Furthermore, participants exhibited critical judgment in evaluating the quality of ideas and outputs generated by ChatGPT, as well as the ability to modify prompts to maximize learning benefits. Such critical judgment offsets the potential threats to academic integrity posed by ChatGPT. Our findings contribute to the understanding of the potential of ChatGPT in language education by adding empirical evidence from students’ perspectives. This study supports the idea that ChatGPT can work as an effective tool for providing students with immediate feedback and personalized learning experiences. Such findings generate implications for future pedagogical practices in the new era by providing students with personalized guidance, designing technology-embedded language support, and developing students’ lifelong learning skills (e.g., autonomy and evaluative judgment) with the support of ChatGPT.
Medication Overuse Headaches among Children—The Contribution of Migraine and TTH
Authors: Genizi Jacob , Shnaider Morya , Yaniv Liat , Kerem Nogah , Nathan Keren , Chistyakov Irina
Published: September 2023

Medication overuse headaches are a frequent phenomenon observed in individuals suffering from chronic headaches. It arises due to the excessive consumption of pain-relief medications, resulting in the escalation and continuous persistence of headache symptoms. Nevertheless, the prevalence and distinctive characteristics of medication overuse headaches in the pediatric population have not been comprehensively explored. The primary objective of this research is to delineate the features of medication overuse headaches in children, particularly emphasizing the investigation of its epidemiology and the diagnostic patterns for headaches. We conducted a retrospective study and analyzed the medical records of children and adolescents who were evaluated at the outpatient pediatric headache clinic at the Bnai Zion Medical Center for headaches during the period spanning 2007 to 2017. Our study encompassed a cohort of 1008 patients experiencing headaches. Among these participants, 268 individuals (26.6%) were diagnosed with migraine, 250 (24.8%) exhibited tension-type headaches (TTH), and 490 (48.6%) were classified as having undifferentiated headaches. Out of the whole group, 65 had chronic headaches: 35 (54%) with migraine, 20 (30%) with tension-type headaches (TTH), and 10 (15%) with the undifferentiated headache of childhood, with the majority (73%) being female. In summary, medication overuse headaches are a prevalent issue among children grappling with chronic headaches. Intriguingly, they appear to be more pronounced within the tension-type headache (TTH) group compared to migraine sufferers and exhibit a higher prevalence among females. This study underscores the significance of early detection and careful management of medication overuse headaches in pediatric cases, shedding light on its distinct characteristics in the realm of childhood headache disorders. Further research is warranted to elucidate the underlying factors contributing to the observed gender disparity and the distinct prevalence rates among different headache subtypes.
Correction: Podury et al. Severe Acute Respiratory Syndrome and Particulate Matter Exposure: A Systematic Review. Life 2023, 13, 538
Authors: Podury Sanjiti , Kwon Sophia , Javed Urooj , Farooqi Muhammad S. , Li Yiwei , Liu Mengling , Grunig Gabriele , Nolan Anna
Published: September 2023

In the original publication [...]
Operative Findings of over 5000 Microvascular Decompression Surgeries for Hemifacial Spasm: Our Perspective and Current Updates
Authors: Park Jae Sung , Park Kwan
Published: September 2023

Hemifacial spasm (HFS) is a hyperactive cranial neuropathy, and it has been well established that the cause of primary HFS is compression on the root exit zone (REZ) of the facial–vestibulocochlear nerve complex (CN VII-VIII) by a vessel or vessels. MVD is the only curative treatment option for HFS with a high success rate and low incidence of recurrence and complications. We categorize six classical compressive patterns on the REZ as well as five challenging types. Knowledge of these patterns may help in achieving a better surgical outcome.
Reducing Wheel Loading in the Grinding of Titanium Alloys through Ultrasonic-Assisted Plasma Oxidation Modification
Authors: Wu Hanqiang , Ye Ximin , Chen Zhuo , Zhang Shibo , Zeng Jiang , Wang Qiang , Wu Yongbo
Published: September 2023

To reduce wheel loading caused by chip adhesion in the grinding of titanium alloys, a new method named ultrasonic-assisted plasma oxidation modification grinding is suggested. The processing principle was introduced in this research, and based on that, the experimental apparatus was established. Then, the surface and cross-sectional morphologies of a workpiece with an oxide layer were characterized, followed by the detection of its microhardness and surface composition. On this basis, in the absence and presence of the oxide layer, the dynamic changes in wheel loading on the grinding wheel surface and the evolution behavior of chip adhesion on the grains were both investigated after gradually increasing the grinding passes. Finally, the effects of wheel loading on the ground surface morphologies were analyzed. The results showed that the oxide layer with low microhardness was mainly composed of TiO2 and Al2O3. Moreover, with an increase in grinding passes, the overall occupied area of chip adhesion on the grinding wheel surface increased proportionally in the absence of the oxide layer, which finally caused severe wheel loading. Conversely, yet at almost the same rate, the overall occupied area of chip adhesion increased after remaining comparatively unchanged in a short range of grinding passes in the presence of the oxide layer, which effectively inhibited the wheel loading. Compared with the ground surface obtained without an oxide layer, the generation of plastic-stacking was significantly restrained with the assistance of the oxide layer, thereby improving the ground surface quality.
Planar Reconstruction of Regular Surfaces’ Three-Dimensional Morphology and Tribology Application
Authors: Xu Xiang , Feng Zekang , Xiao Nengqi , Zhao Xinze , Zhang Zuyue
Published: September 2023

The three-dimensional morphology of frictional sub-surfaces holds significant importance for studying tribological issues. However, the uniformity of the horizontal datum in 3D scanning is limited for curved surfaces, resulting in the inability to obtain accurate contour characterization parameters from the scanning results. This study aims to address this issue by constructing regular surface equations and normalizing the 3D profiler scanning results. By fitting the data, a “plane” surface representative of the surface features is obtained, and the paper demonstrates this approach on the surface morphology of different worn parts in the frictional area of spherical bearings located in the specific environment of the Three Gorges gate. The results indicate that the obtained “plane” effectively reconstructs the three-dimensional morphology map of the regular surface. Moreover, this reconstructed plane not only clearly illustrates the surface characteristics but also provides the foundation for analyzing the wear mechanism.
Microstructure Evolution of the Ti-46Al-8Nb-2.5V Alloy during Hot Compression and Subsequent Annealing at 900 °C
Authors: Cao Shouzhen , Li Zongze , Pu Jiafei , Han Jianchao , Dong Qi , Zhu Mingdong
Published: September 2023

TiAl alloys are high-temperature structural materials with excellent comprehensive properties, and their ideal service temperature range is about 700–950 °C. High-Nb containing the Ti-46Al-8Nb-2.5V alloy was subjected to hot compression and subsequent annealing at 900 °C. During hot compression, work-hardening and strain-softening occurred. The peak stresses during compression are positively correlated with the compressive strain rates and negatively correlated with the compression temperatures. The α2 phase exhibited a typical (0001)α2 basal plane texture after hot compression, while the β0 and γ phases did not show a typical strong texture. Subsequent annealing at 900 °C of the hot-compressed samples resulted in significant phase transformations, specifically the α2 → γ and β0 → γ phase transformations. After 30 min of annealing, the volume fraction of the α2 phase decreased from 39.0% to 4.6%. The microstructure characteristics and phase fraction after 60 min of annealing were similar to those after 30 min. According to the calculation of Miller indexes and texture evolution during annealing, the α2 → γ phase transformation did not follow the Blackburn orientation relationship. Multiple crystal-oriented α2 phases with nanoscale widths (20~100 nm) precipitate within the γ phase during the annealing process, which means the occurrence of γ → α2 phase transformation. Still, the γ → α2 phase transformation follows the Blackburn orientation relationship.
Comparative Analysis of Engineering Carbonation Model Extensions to Account for Pre-Existing Cracks
Authors: Schultheiß Annika Lidwina , Patel Ravi Ajitbhai , Vogel Michael , Dehn Frank
Published: September 2023

Cracks in reinforced concrete structures can accelerate the local depassivation of reinforcement due to carbonation. Different approaches have been proposed to account for pre-existing cracks within engineering models to predict the carbonation depth. In this study, we provide a detailed comparative analysis of different extensions available for the fib carbonation model to account for cracks, viz., crack influence factor (CIF) approaches, a diffusion-based model and the crack depth adaption. The model extensions are first validated against a dataset of lab data collected from the literature and additional experiments performed as the part of this study. The CIF approaches achieved the highest accuracy for the carbonation depth prediction when compared against lab data. The diffusion-based model was inaccurate for low CO2 concentrations. The crack depth adaption provides overly conservative results. No model was found to be best performing, and large scatter was observed between predicted and experimental values. This emphasizes the need for more detailed multi-physics-based models to achieve accurate predictions. For further comparison, service life predictions were conducted for two structural scales, viz., the whole structure and the cracked area. It is concluded that the choice of model extension and the structural scale of analysis have a large influence on predicted probability of failure.
Study on Magnetization Roasting Kinetics of High-Iron and Low-Silicon Red Mud
Authors: Xie Lei , Hao Jiao , Hu Chaojie , Zhang Hanquan
Published: September 2023

High-iron and low-silicon red mud is not only an alkaline solid waste from Bayer process alumina production, but it is also a very important secondary iron resource. Magnetization roasting is considered as an effective and typical method for the iron recovery and removal of impurities in red mud. In this work, based on the characteristics of large specific surface area and high porosity of red mud, the kinetics of magnetization roasting and phase transformation of red mud were studied. Thermodynamic analysis results show that the reduction of iron oxide in red mud is more easily promoted by CO as reducing agent at low roasting temperature. The reduction reaction is prone to overreduction, and fayalite and ferrospinel can be formed in the reaction system. The phase transformation and iron reduction mechanism during the roasting process were evaluated. Most of hematite and goethite in the red mud decomposed in the process of magnetization roasting, released CO2, and transformed into strongly magnetic magnetite. The reaction process has some characteristics controlled by homogeneous reaction. The process of magnetization roasting reduction with CO was controlled by the hybrid control dynamics model, and the apparent activation energy was 38.31 kJ·mol−1.
Double-Forming Mechanism of TaOx-Based Resistive Memory Device and Its Synaptic Applications
Authors: Ju Dongyeol , Kim Sunghun , Lee Subaek , Kim Sungjun
Published: September 2023

The bipolar resistive switching properties of Pt/TaOx/InOx/ITO-resistive random-access memory devices under DC and pulse measurement conditions are explored in this work. Transmission electron microscopy and X-ray photoelectron spectroscopy were used to confirm the structure and chemical compositions of the devices. A unique two-step forming process referred to as the double-forming phenomenon and self-compliance characteristics are demonstrated under a DC sweep. A model based on oxygen vacancy migration is proposed to explain its conduction mechanism. Varying reset voltages and compliance currents were applied to evaluate multilevel cell characteristics. Furthermore, pulses were applied to the devices to demonstrate the neuromorphic system’s application via testing potentiation, depression, spike-timing-dependent plasticity, and spike-rate-dependent plasticity.
Synergistic Effect of Strontium and Melt Quenching on the Solidification Microstructure of Hypereutectic Al-Si Alloys
Authors: Wang Yunfei , Chen Wenyao , Liu Ya , Peng Haoping , Wang Jianhua , Su Xuping
Published: September 2023

The synergistic effect between strontium (Sr) and melt quenching on the solidified microstructure of hypereutectic Al-Si alloys was investigated by optical and scanning electron microscopy. The results indicate that melt quenching can suppress the growth of primary Si particles in the solidified structure of the hypereutectic Al-Si alloy, resulting in a significant decrease of in the average size of primary Si particles in Al-(18~22)Si alloys from 30.35~66.31 μm to 15.13~34.63 μm. The synergistic effect between Sr and melt quenching can further inhibit the precipitation of primary Si particles in the Al-18Si alloy. After the addition of Sr to Al-18Si alloy and undergoing melt quenching, the area fraction of primary Si clearly decreases. When the added amount of Sr increases from 0.1 wt.% to 0.5 wt.%, the area fraction of primary Si decreases from 1.13% to 0.16%. With 0.5 wt.% Sr in the tested alloy, the inhibiting effect on primary Si precipitation was significantly improved. Research has shown that the cooling rate has a significant impact on the solidified structure of the melt-quenched Al-18Si-0.5Sr alloy. There exists no primary Si in solidified structures on the area of 1/8R and 1/4R from the surface of the round bar sample, but the area fraction of primary Si increases, respectively, to 1.97% and 12.48% on the area of 1/2R and R from the surface. The higher the cooling rate, the higher the inhibitory effect on the primary Si precipitation in the Al-18Si-0.5Sr alloy.
A Predictive Maintenance Strategy for Multi-Component Systems Based on Components’ Remaining Useful Life Prediction
Authors: Lv Yaqiong , Zheng Pan , Yuan Jiabei , Cao Xiaohua
Published: September 2023

Industries increasingly rely on intricate multi-component systems, necessitating efficient maintenance strategies to ensure system reliability and minimize downtime. Predictive maintenance, an emerging approach that utilizes data-driven techniques to forecast and prevent failures, holds significant potential in this regard. This paper presents a predictive maintenance strategy tailored specifically for multi-component systems. In order to accurately anticipate the remaining useful life (RUL) of components, we develop a method that combines data and model fusion based on a particle filtering approach and a degradation distribution model. By integrating degradation data with models, our method outperforms traditional model-based approaches in terms of prediction accuracy. Subsequently, we apply an optimized maintenance model to individual components based on the trigger threshold for RUL. This model determines the most optimal maintenance actions for each component, with the aim of minimizing maintenance costs. Furthermore, we introduce an optimized maintenance strategy that incorporates opportunistic maintenance to further reduce the overall maintenance cost of the system. This strategy leverages predicted RUL information to schedule proactive maintenance actions at the opportune moment, resulting in a significant cost reduction compared to traditional periodic maintenance approaches. To validate the feasibility and effectiveness of our proposed strategy, we utilize experimental data from open-source lithium-ion batteries at the NASA PCoE Center. Through this empirical validation, we provide real-world evidence showcasing the applicability and performance of our strategy in a multi-component system.
Quantitative Stability of Optimization Problems with Stochastic Constraints
Authors: Ouyang Wei , Mei Kui
Published: September 2023

In this paper, we consider optimization problems with stochastic constraints. We derive quantitative stability results for the optimal value function, the optimal solution set and the feasible solution set of optimization models in which the underlying stochastic constraints involve the mathematical expectation of random single-valued and set-valued mappings, respectively. New primal sufficient conditions are developed for the uniform error bound property of the stochastic constraint system for the single-valued case.
Control of Network Bursting in a Model Spiking Network Supplied with Memristor—Implemented Plasticity
Authors: Stasenko Sergey V. , Mikhaylov Alexey N. , Kazantsev Victor B.
Published: September 2023

We consider an unstructured neuron network model composed of excitatory and inhibitory neurons. The synaptic connections are supplied with spike timing-dependent plasticity (STDP). We take the STDP model implemented using a memristor. In normal conditions, the network forms so-called bursting discharges typical of unstructured living networks in dissociated neuronal cultures. Incorporating a biologically inspired model, we demonstrate how memristive plasticity emulates spike timing-dependent plasticity, which is crucial for regulating synchronous brain activity. We have found that, when the memristor-based STDP for inhibitory connections is activated, the bursting dynamics are suppressed and the network turns to a random spiking mode. The dependence of bursting properties on the degree of the memristor-based STDP plasticity is analyzed. These findings hold implications for advancing invasive neurointerfaces and for the identification and management of epileptiform activity.