bluuebunny/crossref_metadata_2025 huggingface dataset:
Research on Multi-Parameter Error Model of Backcalculated Modulus Using Abaqus Finite Element Batch Modeling Based on Python Language
Authors: Xiong Chunlong , Yu Jiangmiao , Zhang Xiaoning , Luo Chuanxi
Published: October 2024

The error in modulus backcalculation is a crucial component in validating the rationality and reliability of results for engineering applications. The objective of this study is to identify the theoretical limitations associated with backcalculated modulus errors under typical parameter uncertainties and to determine the primary factors contributing to these errors. Firstly, using the actual measurements or data from the Long-Term Pavement Performance (LTPP) project, the statistical distributions of errors for typical parameters in the modulus backcalculation model were determined. Subsequently, a factor level table for orthogonal experimental design was developed, leading to the construction of 81 orthogonal design experimental schemes and their corresponding theoretical pavement structure models based on the actual error distributions. The deflection responses of 81 theoretical pavement structure models were then computed using an ABAQUS finite element batch analysis method devised in Python. Furthermore, a multi-parameter error model for modulus was established using multiple linear regression and variance analysis. Finally, the theoretical limitations of modulus errors under actual errors were analyzed. The results show that the errors of thickness, load amplitude and load frequency follow a normal distribution, while the distribution of backcalculated modulus errors follows an approximate mixed Gaussian distribution. When the errors of multiple parameters are combined randomly, the modulus errors range from −100% to 595%, and the probability of the modulus errors being less than 15% is highest in the asphalt surface layer, followed by the subgrade, and then the base and subbase layers. Within the same error range, the modulus error is random. However, with different error ranges, the overall level of modulus error increases in proportion to the size of those ranges. Compared to factors such as thickness, load amplitude, and load frequency, the errors in deflections have a highly contribution rate on the modulus errors exceeding 99%.
Redesigning Building Thermal Science Education Through Inquiry-Based Experiential Learning
Authors: Zhuang Jinxun , Chen Chenshun , Wang Julian
Published: October 2024

Mastering building thermal science is essential for architectural professionals, as it supports the design of energy-efficient and thermally optimized buildings, which are critical for addressing the growing demands of sustainable architecture. However, traditional teaching methods often disconnect theoretical instruction from practical application, limiting students’ ability to apply core concepts in real-world scenarios. This study introduces a pedagogical reform that integrates design-oriented and inquiry-based experiments, hands-on physical activities, and field-based testing into the teaching of building thermal science. The revised curriculum focuses on applying theoretical principles in real architectural contexts, allowing students to directly design and experience thermal phenomena such as heat transfer and thermal resistance in building envelope structures. To evaluate the effectiveness of this reform, a control group using traditional confirmatory experiments (following predetermined instructions to complete experiments and validate the results) was compared to a reform group engaged in inquiry-based experimental learning. Over the course of three cohorts (2019, 2020, 2021), the reform group consistently outperformed the control group, with statistically significant improvements in average course grades. Specifically, the reform group had mean grade differences of 7.21 points higher in 2019, 4.55 points higher in 2020, and 5.83 points higher in 2021, as demonstrated by t-test results (p < 0.05). The reform group also exhibited more concentrated grade distributions, reflecting enhanced comprehension and retention of key thermal concepts. In addition to improved academic performance, students in the reform group demonstrated superior problem-solving abilities and a heightened awareness of energy conservation and sustainable design practices. This approach not only deepened their understanding of theoretical knowledge but also fostered a greater commitment to integrating sustainability into their architectural projects.
Research on the Factors That Influence and Improve the Quality of Informal Learning Spaces (ILS) in University Campus
Authors: Guo Weihong , Wang Li , Caneparo Luca
Published: October 2024

Currently, with the intensification of global education competition, how to cultivate innovative and versatile talents has become the focus of education today. Informal learning spaces (ILS) have received widespread attention due to their benefits for interdisciplinary interaction. Many forms of ILS have been built, and coffee shops are one of them. However, there is no uniform standard for the design of cafes as ILS, and there are many problems with the spatial quality. This study took a university cafe as a case study and conducted research on the environmental quality and influencing factors from the perspective of environmental behavior. In terms of research methods, this study adopted a combination of ultra-wideband positioning, questionnaire surveys, and environmental data measurements. This research method could obtain the complete relationship between user behavior, time, and location, which improved the shortcomings of traditional research methods of fragmented and accidental data acquisition, and helped to obtain more accurate research results. The study identified the impact proportions of four criteria layer elements and 26 scheme layer factors, which was also the main contribution of this study. In terms of four criteria layer elements, the physical elements had the highest proportion, accounting for 32.46%. The ontology elements ranked second, accounting for 27.07%. The atmosphere elements ranked third, accounting for 24.19%. Finally, facility elements accounted for 16.29%. The top three scheme layer factors were equipment and facilities, noise, and illumination, with weights of 11.18%, 10.71%, and 8.35%, respectively. The study summarized the development directions of cafes as ILS, such as considering the learning needs of different groups, installing sound-absorbing and soundproof devices, adding grilles to external windows, and improving glare problems.
Evaluation and Improvement of Construction Safety for Prefabricated Buildings Under the Concept of Resilience
Authors: Liu Jingyan , Zhang Shuo , Liu Yinhang , Zheng Wenwen , Hu Xinyue
Published: October 2024

In the construction of prefabricated buildings, safety issues occur frequently, posing challenges to project progress and personnel safety. As a new trend in the construction industry, the complexity of the environment in prefabricated construction demands an update to traditional safety management concepts. This study introduces the concept of resilience to analyze safety issues in prefabricated construction and develops a WSR-4Rs framework for a systematic evaluation of construction safety. The study first combines the WSR (Wuli-Shili-Renli) systematic methodology with the 4R resilience theory to construct an evaluation index system for construction safety. Then, it uses the Analytic Hierarchy Process (AHP) and the entropy weight method to determine the combined weights of each index, establishing a balanced and objective weighting scheme. A fuzzy comprehensive evaluation model is then applied to assess actual project cases. Finally, an obstacle degree model is introduced to identify key indicator factors that significantly impact construction safety, and specific improvement measures are proposed based on these findings. The aim is to provide practical references and guidance for enhancing the safety management level in prefabricated construction.
Brainstem Toxicity Following Proton Beam Radiation Therapy in Pediatric Brain Tumors: A Systematic Review and Meta-Analysis
Authors: Alrasheed Abdulrahim Saleh , Aleid Abdulsalam Mohammed , Alharbi Reema Ahmed , Alhodibi Mostafa Habeeb , Alhussain Abdulmonem Ali , Alessa Awn Abdulmohsen , Almalki Sami Fadhel
Published: October 2024

Background: Proton beam radiation therapy (PBRT) is an advanced cancer treatment modality that utilizes the distinctive physical properties of protons to precisely deliver radiation to tumor targets while sparing healthy tissue. This cannot be obtained with photon radiation. In this systematic review and meta-analysis, we aimed to comprehensively assess the risk of brainstem toxicity in pediatric brain tumor patients undergoing PBRT. Methods: With adherence to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, a predetermined search strategy was used to identify eligible articles from PubMed, Web of Science, Scopus, and Cochrane Library through July 2024. Results: The current study included a total of 11 eligible articles. The pooled prevalence of patients who suffered from brainstem toxicity was 1.8% (95% CI: 1%, 2.6%). The pooled prevalences of patients with Grade 1 to Grade 5 brainstem toxicity were found to be 10.6% (95% CI: 8.8%, 30%), 1.5% (95% CI: 0.6%, 2.5%), 0.7% (95% CI: 0.3%, 1.1%), 0.4% (95% CI: 0.1%, 0.7%), and 0.4% (95% CI: 0.1%, 0.8%), respectively, with an overall pooled prevalence of 0.7% (95% CI: 0.4%, 1%). Conclusions: This study revealed a relatively low incidence of symptomatic brainstem toxicity and its related mortality in the pediatric population undergoing PBRT. However, further research is encouraged to study the broader effects of PBRT and to explore various factors that may influence the risk of brainstem toxicity in patients treated with PBRT.
Combined Radiotherapy and Hyperthermia: A Systematic Review of Immunological Synergies for Amplifying Radiation-Induced Abscopal Effects
Authors: Van Dieren Loïc , Quisenaerts Tom , Licata Mackenzie , Beddok Arnaud , Lellouch Alexandre G. , Ysebaert Dirk , Saldien Vera , Peeters Marc , Gorbaslieva Ivana
Published: October 2024

Introduction: The abscopal effect is a systemic immune response characterized by metastases regression at sites distant from the irradiated lesion. This systematic review aims to explore the immunological mechanisms of action underlying the abscopal effect and to investigate how hyperthermia (HT) can increase the chances of radiotherapy (RT) triggering systemic anti-tumor immune responses. Methods: This review is created in accordance with the PRISMA guidelines. Results and Conclusion: HT and RT have both complementary and synergistic immunological effects. Both methods trigger danger signal release, promoting cytokine and chemokine secretion, which increases T-cell infiltration and facilitates cell death. Both treatments upregulate extracellular tumor HSP70, which could amplify DAMP recognition by macrophages and DCs, leading to stronger tumor antigen presentation and CTL-mediated immune responses. Additionally, the combined increase in cell adhesion molecules (VCAM-1, ICAM-1, E-selectin, L-selectin) could enhance leukocyte adhesion to tumors, improving lymphocyte trafficking and boosting systemic anti-tumor effects. Lastly, HT causes vasodilation and improves blood flow, which might exacerbate those distant effects. We suggest the combination of local radiotherapy with fever-range whole-body hyperthermia to optimally enhance the chances of triggering the abscopal effect mediated by the immune system.
Pressurized Intraperitoneal Aerosol Chemotherapy for Peritoneal Carcinomatosis in Colorectal Cancer Patients: A Systematic Review of the Evidence
Authors: Sleiman Marwan-Julien , Jelip Annamaria , Buchs Nicolas , Toso Christian , Liot Emilie , Koessler Thibaud , Meyer Jeremy , Meurette Guillaume , Ris Frederic
Published: October 2024

Introduction: Pressurized intraperitoneal aerosol chemotherapy (PIPAC) consists of the administration of aerosolized chemotherapy into the abdominal cavity of patients suffering from peritoneal carcinomatosis. Our aim was to review the evidence supporting PIPAC in patients with peritoneal carcinomatosis from colorectal cancer. Methods: A systematic review was performed in accordance with the 2020 PRISMA guideline. MEDLINE and CENTRAL were searched using combinations of terms including “Peritoneal carcinomatosis”, “Peritoneal metastasis”, “PIPAC”, “Pressurized intraperitoneal aerosol chemotherapy” and “Colorectal cancer”. Original studies, in English, including patients treated with PIPAC for colorectal peritoneal carcinomatosis, were considered eligible. Case reports, non-English or French language articles and secondary analyses were excluded. Results: A total of 385 articles were screened and 374 articles were excluded, leaving 11 publications for inclusion in the qualitative analysis. The included studies totalized 949 patients who received PIPAC for peritoneal carcinomatosis due to colorectal cancer. The median peritoneal carcinomatosis index (PCI) ranged from 10 to 31. In all studies, the complete PIPAC protocol was achieved with an average of two to three 3 PIPAC sessions per patient. Oxaliplatin (OX) was used as a chemotherapeutic agent in all studies and could be associated with intravenous 5-FU and leucovorin. Most post-operative adverse events were recorded as mild to moderate with no intraoperative complications. Only four studies reported a decrease in the average PCI score for 50% of the patients. Median overall survival ranged from 8 to 37.8 months. Quality of life indicators were stable between PIPAC-OX cycles with a small but not statistically significant trend of improvement of most functional scales. Conclusions: PIPAC for peritoneal carcinomatosis from colorectal origin is feasible, safe and tolerable. Its impact on survival outcomes or quality of life remains to be demonstrated by randomized trials.
TYK2 Protein Expression and Its Potential as a Tissue-Based Biomarker for the Diagnosis of Colorectal Cancer
Authors: Zadka Łukasz , Ustaszewski Adam , Glatzel-Plucińska Natalia , Rusak Agnieszka , Łaczmańska Izabela , Ratajczak-Wielgomas Katarzyna , Kmiecik Alicja , Piotrowska Aleksandra , Haczkiewicz-Leśniak Katarzyna , Gomułkiewicz Agnieszka , Kostrzewska-Poczekaj Magdalena , Dzięgiel Piotr
Published: October 2024

Background/Objectives: The aim of this study was to examine the expression of TYK2 in colorectal cancer (CRC) and to determine the potential diagnostic and prognostic significance of this kinase. Methods: Digital image analysis was performed to assess immunohistochemical TYK2 reactivity. Results: There were significant differences for all positive pixels between CRC and normal colonic mucosa, with higher TYK2 expression levels observed in surgical margins than in adenocarcinomas (p = 0.0004). Paired t tests showed elevated immunoreactivity for overall TYK2 expression in matched pairs of CRC with adjacent surgical margins (p < 0.0001). Higher percentages of weak (p < 0.0001) and strong pixels (p = 0.0260) were detected in normal colonic mucosa than in cancer tissues. To distinguish cancer from normal intestinal mucosa, the following cutoffs for the TYK2 immune score were found: 29.5% for all cases and 31% for matched pairs. Tumor budding (Bd) was negatively correlated with the percentage of strong pixels for TYK2 (ρ = −0.270, p = 0.0096). The percentage of strong pixels was significantly elevated for the T parameter (p = 0.0428). There was a positive correlation between the number of involved lymph nodes and weak pixels (ρ = 0.239, p = 0.0242). Immunofluorescence staining showed significantly higher signal intensities in colonic mucosa than in CRC. The protein level of TYK2 was significantly higher in controls than in cancer tissues. TEM imaging showed lower levels of TYK2 in cancer than in ulcerative colitis. Conclusions: TYK2 protein expression may bring diagnostic value in patients diagnosed with CRC.
Metabolic Risk Factors and Survival in Patients with Glioblastoma
Authors: Aboubechara John Paul , Aboud Orwa
Published: October 2024

Background: Metabolic syndrome increases the risk of developing various systemic cancers. The prevalence of metabolic syndrome in newly diagnosed glioblastoma patients is unknown. Further, there have been contradictory reports about how metabolic syndrome affects clinical outcomes. Therefore, the purpose of this study is to test the hypothesis that metabolic syndrome is associated with an increased prevalence of glioblastoma and worsened survival outcomes. Methods: This retrospective cohort study examines seventy-three patients with isocitrate dehydrogenase (IDH)-wild-type glioblastoma as it provides a relatively homogeneous population to examine. Patient characteristics, vital signs, lab results, tumor molecular markers, and overall survival were analyzed. Patients with metabolic syndrome and individual risk factors were identified, and survival outcomes were examined. Results: Our results demonstrate that there is a higher prevalence of metabolic syndrome in our cohort of patients with glioblastoma than in the general population (41% vs. 33%), though this effect is confounded by older age. We also demonstrate that after correction for confounding variables, metabolic syndrome is not significantly associated with overall survival (p = 0.1). When analyzing individual metabolic risk factors, we demonstrate that there is a significant association between the accumulation of metabolic risk factors and decreased survival (p = 0.03), and hyperglycemia emerges as a significant independent risk factor for decreased survival (p = 0.05). Conclusions: These results suggest that metabolic risk factors can affect survival in patients with glioblastoma, which can have significant implications for clinical practice. These findings need to be further explored through further clinical and mechanistic studies.
Unveiling GATOR2 Function: Novel Insights from Drosophila Research
Authors: Bettedi Lucia , Zhang Yingbiao , Yang Shu , Lilly Mary A.
Published: October 2024

The multiprotein Target of Rapamycin (TOR) Complex 1 (TORC1) is a serine/threonine kinase that stimulates anabolic metabolism and suppresses catabolism. Deregulation of TORC1 is implicated in various human pathologies, including cancer, epilepsy, and neurodegenerative disorders. The Gap Activity Towards Rags (GATOR) complex contains two subcomplexes: GATOR1, which inhibits TORC1 activity; and GATOR2, which counteracts GATOR1s function. Structural and biochemical studies have elucidated how GATOR1 regulates TORC1 activity by acting as a GTPase activating protein for Rag GTPase. However, while cryogenic electron microscopy has determined that the structure of the multi-protein GATOR2 complex is conserved from yeast to humans, how GATOR2 inhibits GATOR1 remains unclear. Here, we describe recent whole-animal studies in Drosophila that have yielded novel insights into GATOR2 function, including identifying a novel role for the GATOR2 subunit WDR59, redefining the core proteins sufficient for GATOR2 activity, and defining a TORC1-independent role for GATOR2 in the regulation of the lysosomal autophagic endomembrane system. Additionally, the recent characterization of a novel methionine receptor in Drosophila that acts through the GATOR2 complex suggests an attractive model for the evolution of species-specific nutrient sensors. Research on GATOR2 function in Drosophila highlights how whole-animal genetic models can be used to dissect intracellular signaling pathways to identify tissue-specific functions and functional redundancies that may be missed in studies confined to rapidly proliferating cell lines.
Stress Granule Assembly in Pulmonary Arterial Hypertension
Authors: Kosmas Kosmas , Papathanasiou Aimilia Eirini , Spyropoulos Fotios , Rehman Rakhshinda , Cunha Ashley Anne , Fredenburgh Laura E. , Perrella Mark A. , Christou Helen
Published: October 2024

The role of stress granules (SGs) in pulmonary arterial hypertension (PAH) is unknown. We hypothesized that SG formation contributes to abnormal vascular phenotypes, and cardiac and skeletal muscle dysfunction in PAH. Using the rat Sugen/hypoxia (SU/Hx) model of PAH, we demonstrate the formation of SG puncta and increased expression of SG proteins compared to control animals in lungs, right ventricles, and soleus muscles. Acetazolamide (ACTZ) treatment ameliorated the disease and reduced SG formation in all of these tissues. Primary pulmonary artery smooth muscle cells (PASMCs) from diseased animals had increased SG protein expression and SG number after acute oxidative stress and this was ameliorated by ACTZ. Pharmacologic inhibition of SG formation or genetic ablation of the SG assembly protein (G3BP1) altered the SU/Hx-PASMC phenotype by decreasing proliferation, increasing apoptosis and modulating synthetic and contractile marker expression. In human PAH lungs, we found increased SG puncta in pulmonary arteries compared to control lungs and in human PAH-PASMCs we found increased SGs after acute oxidative stress compared to healthy PASMCs. Genetic ablation of G3BP1 in human PAH-PASMCs resulted in a phenotypic switch to a less synthetic and more contractile phenotype. We conclude that increased SG formation in PASMCs and other tissues may contribute to PAH pathogenesis.
Helping Educators Learn Pediatric Pain Assessment and Intervention Needs Program (HELP PAIN): Program Development with Community Partners
Authors: Cunningham Natoshia R. , Adler Michelle , Zuckerman Jocelyn , Reid Mallet R. , Love Sarah C. , Theaker Kelly , Pierce Steven J. , Vandenbrink Rachel , Paque Jeanne , Wendling Andrea L. , Arnetz Judith
Published: October 2024

Background/Objectives: This paper details the development of the Helping Educators Learn Pediatric Pain Assessment and Intervention Needs (HELP PAIN) program. Methods: HELP PAIN is an 8 h live training program for school providers (e.g., school nurses and social workers) to use evidence-based nonpharmacologic pediatric pain management tools. The program’s scope reflected the reach of the participating intermediary community organizations, resulting in focused training in rural northwest Michigan due to the Health Department of Northwest Michigan’s service in that region and statewide reach due to the broad representation of members from the Michigan Association of School Nurses. Results: We describe the development of the HELP PAIN program, drawing on evidence-based nonpharmacologic (e.g., cognitive behavioral and mindfulness meditation) strategies for pediatric pain management. Conclusions: In partnership with the key community organizations and community partners, we developed, interactively refined, and delivered this training program.
Relationship Between Multi-Teaching Styles and Didactics Effectiveness on Rugby Instructors and Minirugby Players
Authors: Rigon Marta , Signorini Gabriele , Scurati Raffaele , Trecroci Athos , Colella Dario , Formenti Damiano , Merati Giampiero , Cherubini Domenico , Invernizzi Pietro Luigi
Published: October 2024

Background/Objectives: The concept of educational systems thinking shows the rugby educational system as a network of multiple interactive and interconnected elements. However, the frameworks presented in the literature for developing sports practice through an educational vision and multisport engagement do not always have direct transferability to instructors’ training courses. The study aims to evaluate the correlation between rugby instructors’ methodological and didactical competencies and compare them with children’s motor competence and psychological aspects. Methods: Two hundred twenty children (9.6 ± 1.1 years) and 50 instructors (39.0 ± 13.6 years) were enrolled. Instructors’ competencies were investigated during the internship through evaluation sheets, questionnaires, and video analysis. Children’s motor competence and psychological aspects were investigated through motor tests, questionnaires, and video analysis. Results: The correlation between methodological competencies and didactical-communicative competencies showed a positive significance, especially regarding production styles. Motor competence and play skills in children showed poor results. The group of instructors with more methodological competencies (a greater number of teaching styles used) showed a strong correlation between motor competence and psychological aspects. Conclusions: For successful teaching, knowledge of specific technical skills is not enough, and it is important to consider all the factors (in particular, the teaching-communicative and methodological skills) that contribute most to instructors’ skills.
Progress in Corrosion Protection Research for Supercritical CO2 Transportation Pipelines
Authors: Zhao Cailing , Wang Jianming , Li Xin , Huang Jinzhen , Chen Huikai , Bi Jinye , Liu Sawen , Lu Guoqiang , Song Kun , Guo Shengjun
Published: October 2024

Carbon Capture, Utilization, and Storage (CCUS) technology is an emergent field with the potential for substantial CO2 emissions reduction, enabling low-carbon utilization of fossil fuels. It is widely regarded as a critical technology for combating global climate change and controlling greenhouse gas emissions. According to recent studies, China has identified CCUS as a key emissions reduction technology in climate change response and carbon neutrality objectives. Within this framework, supercritical CO2 (SC-CO2) transport pipelines are an essential means for efficient and safe transportation of CO2. Corrosion protection of pipelines enhances the efficiency and safety of CCUS technology and supports broader implementation and application. This paper reviews the current research on corrosion protection for SC-CO2 transport pipelines, discusses effect factors, compares various corrosion protection strategies, and analyzes the challenges in corrosion protection of SC-CO2 transport pipelines. It concludes with a perspective on future research and development directions in this field. This paper is dedicated to providing new research strategies for pipeline corrosion protection in CCUS technology in the future, and providing technical support for pipeline corrosion protection in CCUS industrial applications.
Long COVID Is Associated with Decreased Quality of Life and Increased Mental Disability
Authors: Kim Jaewhan , Duru Emeka Elvis , Weir Peter , Lee Sanghoon
Published: October 2024

COVID-19’s impact on quality of life (QoL) has been studied; however, data on the effects of long COVID on QoL and mental disability remain limited. This study aimed to investigate whether long COVID is associated with decreased QoL and increased mental disability. We analyzed data from adults (≥18 years) in the 2022 Medical Expenditure Panel Survey (MEPS). Physical and mental QoL were assessed using the Veterans RAND 12-Item Health Survey, while mental disability was measured with the Kessler Index. Long COVID was defined as experiencing COVID-related symptoms for over 3 months. To account for skewness in the outcome variables, the study employed survey-weighted generalized linear regression with a log link and gamma distribution. The analysis included 153,330,408 subjects (unweighted n = 10,975). The average age of those with and without long COVID was similar (51 vs. 52 years, p = 0.46). Subjects with long COVID had a 3% lower physical QoL (β = −0.03, p = 0.02), a 4% lower mental QoL (β = −0.04, p < 0.01), and a 26% higher mental disability score (β = 0.26, p < 0.01) compared to those without long COVID. These findings highlight the urgent need for targeted strategies to address long COVID and support patients in recovering their pre-COVID QoL and mental health.
Detection of Subarachnoid Hemorrhage Using CNN with Dynamic Factor and Wandering Strategy-Based Feature Selection
Authors: Sengupta Jewel , Alzbutas Robertas , Iešmantas Tomas , Petkus Vytautas , Barkauskienė Alina , Ratkūnas Vytenis , Lukoševičius Saulius , Preikšaitis Aidanas , Lapinskienė Indre , Šerpytis Mindaugas , Misiulis Edgaras , Skarbalius Gediminas , Navakas Robertas , Džiugys Algis
Published: October 2024

Objectives: Subarachnoid Hemorrhage (SAH) is a serious neurological emergency case with a higher mortality rate. An automatic SAH detection is needed to expedite and improve identification, aiding timely and efficient treatment pathways. The existence of noisy and dissimilar anatomical structures in NCCT images, limited availability of labeled SAH data, and ineffective training causes the issues of irrelevant features, overfitting, and vanishing gradient issues that make SAH detection a challenging task. Methods: In this work, the water waves dynamic factor and wandering strategy-based Sand Cat Swarm Optimization, namely DWSCSO, are proposed to ensure optimum feature selection while a Parametric Rectified Linear Unit with a Stacked Convolutional Neural Network, referred to as PRSCNN, is developed for classifying grades of SAH. The DWSCSO and PRSCNN surpass current practices in SAH detection by improving feature selection and classification accuracy. DWSCSO is proposed to ensure optimum feature selection, avoiding local optima issues with higher exploration capacity and avoiding the issue of overfitting in classification. Firstly, in this work, a modified region-growing method was employed on the patient Non-Contrast Computed Tomography (NCCT) images to segment the regions affected by SAH. From the segmented regions, the wide range of patterns and irregularities, fine-grained textures and details, and complex and abstract features were extracted from pre-trained models like GoogleNet, Visual Geometry Group (VGG)-16, and ResNet50. Next, the PRSCNN was developed for classifying grades of SAH which helped to avoid the vanishing gradient issue. Results: The DWSCSO-PRSCNN obtained a maximum accuracy of 99.48%, which is significant compared with other models. The DWSCSO-PRSCNN provides an improved accuracy of 99.62% in CT dataset compared with the DL-ICH and GoogLeNet + (GLCM and LBP), ResNet-50 + (GLCM and LBP), and AlexNet + (GLCM and LBP), which confirms that DWSCSO-PRSCNN effectively reduces false positives and false negatives. Conclusions: the complexity of DWSCSO-PRSCNN was acceptable in this research, for while simpler approaches appeared preferable, they failed to address problems like overfitting and vanishing gradients. Accordingly, the DWSCSO for optimized feature selection and PRSCNN for robust classification were essential for handling these challenges and enhancing the detection in different clinical settings.
The Prevalence of Autistic Traits in a Sample of Young Adults Referred to a Generalized Mental Health Outpatient Clinic
Authors: Folatti Irene , Santangelo Giulia , Sanguineti Claudio , Inci Sanem , Faggioli Raffaella , Bertani Angelo , Nisticò Veronica , Demartini Benedetta
Published: October 2024

Background/Objectives: The diagnosis of Autism Spectrum Disorders (ASD) is undergoing significant revisions, impacting prevalence estimates in the general population. Moreover, the rise of a dimensional perspective on psychopathology has broadened our understanding of autism, recognizing that subthreshold autistic features extend throughout the general population. However, there remains a limited understanding of the prevalence of ASD traits in individuals with psychiatric disorders, particularly in young adults, who are at an age where several mental health conditions emerge. The aim of this study was to evaluate the prevalence of ASD traits in a sample of young adults (18–24 years old) attending a generalized mental health outpatient clinic. Methods: A total of 259 young adult patients completed the self-report screening questionnaires Autism Quotient (AQ) and Ritvo Autism and Asperger Diagnostic Scale-Revised (RAADS-R). Results: A total of 16.2% of our sample scored above the cut-off in both scales; this percentage decreased to 13.13% when restricting the RAADS-R cut-off to >119, as suggested for clinical samples. The association with sociodemographic features is discussed. Conclusions: We argue that screening for autistic traits should be integrated into the assessment of young adults presenting with nonspecific psychiatric symptoms or psychological distress. Although there is ongoing debate over the use of self-report screening tools, a positive result on both the AQ and RAADS-R should prompt clinicians to pursue a comprehensive diagnostic evaluation using structured or semi-structured interviews.
Cutaneous Metastasis of Rectal Cancer as a Diagnostic Challenge: A Clinical Case and Literature Review
Authors: Zelenova Ekaterina , Belysheva Tatiana , Sofronov Denis , Semenova Vera , Radjabova Galimat , Vishnevskaya Yana , Kletskaya Irina , Sharapova Elena , Karasev Ivan , Romanov Denis , Denieva Malika , Petrochenko Nikolay , Valiev Timur , Nasedkina Tatiana
Published: October 2024

Background/Objectives: Metastatic colorectal cancer remains a fatal disease, with a 5-year survival rate lower than 15%. The most common metastatic sites are the lungs and the liver, while skin metastases are very rare and often indicate a poor prognosis with a lower survival rate. Methods. Herein, we present the clinical case of a 62-year-old female patient with rectal cancer metastases to the skin of the anogenital and abdominal regions, diagnosed 2 years after completion of treatment of the underlying disease. Results: Histological examination of the skin lesions revealed adenocarcinoma, and expression of the same immunohistochemical markers was also found in the primary tumor and in the cutaneous metastases. However, next-generation sequencing demonstrated differences in the mutational profiles of the primary tumor and metastasis to the skin. Somatic mutations in the APC, TP53, and PTPN11 genes were revealed in primary rectal adenocarcinoma, but another pathogenic TP53 mutation and a frameshift variant in the DYNC1I1 gene were found in cutaneous metastases. The patient underwent several courses of FOLFOX6 chemotherapy in combination with bevacizumab, but the treatment was unsuccessful. An analysis of 50 clinical cases from the literature concerning various manifestations of cutaneous metastases of rectal cancer showed a median survival of 8.5 months from the time of detection of the skin lesions. Conclusions: In this regard, careful skin examination of patients with rectal cancer and timely detection of cutaneous metastases are essential steps in the follow-up of patients who have undergone treatment of the primary tumor.
In Search of Relevant Urinary Biomarkers for Thyroid Papillary Carcinoma and Benign Thyroid Nodule Differentiation, Targeting Metabolic Profiles and Pathways via UHPLC-QTOF-ESI+-MS Analysis
Authors: Berinde Gabriela Maria , Socaciu Andreea Iulia , Socaciu Mihai Adrian , Petre Gabriel Emil , Rajnoveanu Armand Gabriel , Barsan Maria , Socaciu Carmen , Piciu Doina
Published: October 2024

Background: Identification of specific urine metabolic profiles for patients diagnosed with papillary thyroid carcinoma (TC) vs. benign nodules (B) to identify specific biomarkers and altered pathways compared to those of healthy controls (C). Methods: Patient urine samples were collected, before surgery and after a histological confirmation of TC (n = 30) and B (n = 30), in parallel with sample collection from healthy controls (n = 20). The untargeted and semi-targeted metabolomic protocols were applied using UPLC-QTOF-ESI+-MS analysis, and the statistical analysis was performed using the Metaboanalyst 6.0 platform. The results for the blood biomarkers, previously published, were compared with the data obtained from urine sampling using the Venny algorithm and multivariate statistics. Results: Partial least squares discrimination, including VIP values, random forest graphs, and heatmaps (p < 0.05), together with biomarker analysis (AUROC ranking) and pathway analysis, suggested a specific model for the urinary metabolic profile and pathway alterations in TC and B vs. C, based on 190 identified metabolites in urine that were compared with the serum metabolites. By semi-targeted metabolomics, 10 classes of metabolites, considered putative biomarkers, were found to be responsible for specific alterations in the metabolic pathways, from polar molecules to lipids. Specific biomarkers for discrimination were identified in each class of metabolites that were either upregulated or downregulated when compared to those of the controls. Conclusions: The lipidomic window was the most relevant for identifying biomarkers related to thyroid cancer and benign conditions, since this study detected a stronger involvement of lipids and selenium-related molecules for metabolic discrimination.
Comparison of Precision, Agreement, and Accuracy of Two Swept-Source Optical Coherence Tomography Biometers
Authors: Guarro Mercè , Vázquez Meritxell , Díaz Juan Carlos , Ruiz Sergi , Gimeno Maties , Rodríguez Lara , López Elena , Sararols Laura , Biarnés Marc
Published: October 2024

Background/Objectives: This study’s aim was to compare the precision, agreement, and accuracy in axial length (AL) measurements of Argos® (Alcon Healthcare, US) and Eyestar 900® (Haag-Streit, Switzerland) swept-source optical coherence tomography (SS-OCT) biometers. Methods: We performed a prospective evaluation of two diagnostic devices. Three consecutive measurements of AL with the Argos® and the Eyestar® 900 SS-OCT biometers were conducted in random order in eyes undergoing cataract surgery in Barcelona, Spain. The main endpoint was the median difference in AL between devices. Secondary endpoints included agreement on Bland–Altman plots and 95% limits of agreement (LoAs), repeatability as measured within-subject standard deviation (SW), percent of failed AL measurements, percent of eyes within ±0.50 D and ±1.00 D one month after surgery, and median and mean prediction error. Results: We included 107 eyes of 107 patients (60.8% females, mean age of 73.1 years). The median difference in AL (Argos®-Eyestar 900®) was −0.01 mm (interquartile range [IQR], 0.06), p = 0.01. The 95% LoAs were −0.11 to +0.08 mm, with a trend towards less extreme measurements with Argos® for very short and long eyes. The median (IQR) Sw was 0.0058 (0.0058) and 0.0000 (0.0058) for Argos® and Eyestar 900®, respectively. There were no failed AL measurements with either device (0%, 95% CI = 0% to 3.4%). Overall, 96.1% of eyes were within ±0.50 D and 100% were within ±1.00 D. Conclusions: Argos® and Eyestar 900® provided statistically different but clinically negligible differences in AL. However, they are not interchangeable in very long or short eyes, due to the different principles used to determine AL.
The Impact of AI on International Trade: Opportunities and Challenges
Authors: Ozturk Ozcan
Published: October 2024

This study aims to explore the transformative potential of Artificial Intelligence (AI) in international trade, focusing on its key roles in optimizing trade operations, enhancing trade finance, and expanding market access. In trade optimization, AI leverages advanced machine learning and predictive analytics to enhance demand forecasting, route optimization, and customs procedures, leading to more efficient logistics and inventory management. In trade finance, AI can automate document processing and risk assessment, increasing access to finance and enhancing transactional transparency, particularly through integration with blockchain technology. In terms of market access, AI-driven analytics can identify consumer trends and competitive dynamics, enabling personalized marketing and overcoming linguistic and cultural barriers. Due to the lack of quantitative data, this study employed qualitative research methods, specifically a multiple-case-study approach. The case studies of leading companies such as Alibaba, DHL, and Maersk showcase how they leverage AI to optimize their trade operations, improve customer service, and achieve greater efficiency. These real-world examples demonstrate AI’s practical applications and significant benefits in the global trade landscape. However, the adoption of AI in international trade is not without challenges. These include issues around data quality, ethical concerns, technological complexity, and public perception. Policy recommendations highlight the need for a robust data infrastructure, establishing ethical AI guidelines, and fostering international cooperation to align data protection regulations.
Scene Measurement Method Based on Fusion of Image Sequence and Improved LiDAR SLAM
Authors: Liang Dongtai , Li Donghui , Yang Kui , Hu Wenxue , Chen Xuwen , Chen Zhangwei
Published: October 2024

To address the issue that sparse point cloud maps constructed by SLAM cannot provide detailed information about measured objects, and image sequence-based measurement methods have problems with large data volume and cumulative errors, this paper proposes a scene measurement method that integrates image sequences with an improved LiDAR SLAM. By introducing plane features, the positioning accuracy of LiDAR SLAM is enhanced, and real-time odometry poses are generated. Simultaneously, the system captures image sequences of the measured object using synchronized cameras, and NeRF is used for 3D reconstruction. Time synchronization and data registration between the LiDAR and camera data frames with identical timestamps are achieved. Finally, the least squares method and ICP algorithm are employed to compute the scale factor s and transformation matrices R and t between different point clouds from LiDAR and NeRF reconstruction. Then, the precise measurement of the objects could be implemented. Experimental results demonstrate that this method significantly improves measurement accuracy, with an average error within 10 mm and 1°, providing a robust and reliable solution for scene measurement.
Edge Artificial Intelligence for Electrical Anomaly Detection Based on Process-In-Memory Chip
Authors: Jin Jianzi , Qiu Xiang , Lu Cimang
Published: October 2024

Neural-networks (NNs) for the current feature analysis bring novel electrical safety functions in smart circuit breakers (CBs), especially for preventing the fire hazard from electric vehicle/bike battery charging. In this work, the edge artificial intelligence (AI) solutions for the electrical anomaly detection were designed and demonstrated based on the process-in-memory (PIM) AI chip. The ultra-low power and high-performance character of PIM AI chips enable the edge solution to embed in the limited space inside the circuit breaker and to detect improper battery charging at millisecond latency.
Toward Energy Efficient Battery State of Charge Estimation on Embedded Platforms
Authors: Turkmanović Haris , Popović Ivan , Rajović Vladimir
Published: October 2024

Recent studies have focused on accuracy as the key state of charge (SoC) estimation algorithms’ performance metrics, whereas just a few of them compare algorithms in terms of energy efficiency. Such a comparison is important when selecting an algorithm that should be implemented on a resource-constrained, low-power embedded system. In this paper, recursive model-based SoC estimation algorithms, such as the extended Kalman filter, have been identified as well-suited solutions for implementation on an embedded platform, providing a good compromise between estimation accuracy and computational complexity that is correlated to energy consumption. Assuming that a decrease in the estimation rate will result in a decrease in both accuracy and energy consumption of the estimator, a theoretical analysis has been conducted to establish how these two metrics depend on the estimation rate. To verify results obtained in theory, two extended Kalman filter-based SoC estimation algorithms of different complexities have been implemented and compared in terms of accuracy, quantified by root mean square error (RMSE), and energy consumption. The obtained results confirm that for a selected type of recursive model-based SoC estimation algorithm, it is possible to achieve an optimal algorithm estimation rate in the sense of satisfactory accuracy and acceptable energy consumption. The analysis and results presented in this paper establish a foundation for a future development of energy-efficient algorithms for SoC estimation in applications where the energy consumption of the estimation process is comparable to the energy consumption of the complete system.
A Blockchain and Zero Knowledge Proof Based Data Security Transaction Method in Distributed Computing
Authors: Zhang Bowei , Pan Heng , Li Kunyang , Xing Ying , Wang Jiaxiang , Fan Dongdong , Zhang Wenjie
Published: October 2024

In distributed computing, data trading mechanisms are essential for ensuring the sharing of data across multiple computing nodes. Nevertheless, they currently encounter considerable obstacles, including low accuracy in matching trading parties, ensuring fairness in transactions, and safeguarding data privacy throughout the trading process. In order to address these issues, we put forward a data trading security scheme based on zero-knowledge proofs and smart contracts. In the phase of preparing the security parameters, the objective is to reduce the complexity of generating non-interactive zero-knowledge proofs and to enhance the efficiency of data trading. In the pre-trading phase, we devise attribute atomic matching smart contracts based on precise data property alignment, with the objective of achieving fine-grained matching of data attributes between trading parties. In the trading execution phase, lightweight cryptographic algorithms based on elliptic curve cryptography (ECC) and non-interactive zero-knowledge proofs are employed for the dual encryption of trading data and the generation of attribute proof contracts, thus ensuring the security and privacy of the data. The results of experiments conducted on the Ethereum platform in an industrial IoT scenario demonstrate that our scheme maintains stable and low-cost consumption while ensuring accuracy in matching and privacy protection.
Implementation of Fuzzy Logic Scheme for Assessment of Power Transformer Oil Deterioration Using Imprecise Information
Authors: Nishtar Zuhaib , Wang Fangzong
Published: October 2024

This research aims to analyze the implementation of a fuzzy logic-based approach in improving the diagnosis of power transformer oil deterioration, which is critical for maintaining the efficient performance and operational life of transformers. Traditional diagnoses are based on strict measurements that do not account for the factors of variability and uncertainty of the actual data. In this article, we perform six different types of tests in this regard, and data have been collected during the period of 2021 to 2022 of 188 power transformer failures in the New KotLakhpat Lahore unit, whose voltage range is 132/66 kv and rating capacity is 40/50 MVA. In this case, a fuzzy logic-based scheme is developed based upon the membership function, a rule-based and defuzzification method that works with imprecision and the implementation of uncertainty in assessing the condition of transformer oils. Moisture, acidity, and a dissolved gas analysis indicator, along with other indication approaches such as interfacial tension, viscosity, and tangent delta measurement, are used to analyze the deterioration process in transformer oils. In the visual representation, oil samples with the following properties were first fuzzified: 19.9 mm2/s of viscosity, 0.453 mgKOH/g of acidity, 695 ppm of DGA, 20.8 mg/kg of moisture, 19.98 of IFT, and 4.35 × 100.14 of tangent delta. The output that was generated by software using the values entered into the parameters (HI and Age) after defuzzification is 45. Fuzzy logic serves as a concrete framework for transforming the diagnostics system and deterring the threats to the entire transformer’s health and reliability in the future. By using this technique, various faults were hypothetically and practically analyzed in a transformer to implement early detection technologies with the possibility to reduce maintenance costs and extend operational life up to 45 years. Various case studies indicate the effectiveness of fuzzy logic in comparison to traditional diagnostics.