bluuebunny/crossref_metadata_2025 huggingface dataset:
Remote Eye Movement Desensitization and Reprocessing Treatment of Long-COVID- and Post-COVID-Related Traumatic Disorders: An Innovative Approach
Authors: Russo Samuele , Fiani Francesca , Napoli Christian
Published: November 2024

Background/Objectives: The COVID-19 pandemic has led to increased mental health issues, particularly among long-COVID patients, who experience persistent symptoms post-recovery, potentially leading to chronic conditions. The psychological impact of long-COVID is still largely unknown, but it may contribute to mental disorders like Post-Traumatic Stress Disorder (PTSD). Given the global rise in anxiety and depression, exploring therapies like Eye Movement Desensitization and Reprocessing (EMDR) for long-COVID traumatic disorders is crucial. This study explores the effectiveness of remote EMDR therapy for PTSD-like symptoms in long-COVID conditions (LCC), assessing their emergence, the impact of LCC on mental health, and identifying key commonalities. It also examines the potential advantages of an artificial intelligence (AI)-powered platform for EMDR treatments for both therapists and patients, evaluating the response differences between remote and in-person treatment. Methods: We enrolled a total of 160 participants divided into two groups of 80, with the experimental group receiving EMDR treatment for PTSD-like symptoms via a remote AI-powered platform, and the control group receiving traditional in-person therapy. We compared the ANOVA for Subjective Units of Disturbance (SUDs) scores, PTSD Checklist for DSM-5 (PCL-5) scores, and Impact of Event Scale-Revised (IES-R) scores between our two groups for three cases: pre-treatment, post-treatment, and decrement. Results: Statistical significance analysis showed a consistent absence of significant differences between online AI-powered platforms and traditional in-presence sessions. This effectively confirms our hypothesis and highlights that no significant differences were observed between the two groups. Conclusions: The AI-supported remote platform demonstrates comparable efficacy in delivering EMDR therapy, confirming its potential as an effective alternative to traditional in-person methods while providing added advantages in accessibility and adaptability (e.g., remote areas, hikikomori, natural disasters).
The Road to Recovery: A Two-Year Longitudinal Analysis of Mental Health Among University Students During and After the COVID-19 Pandemic
Authors: Allen Rosie E. , Hochard Kevin D. , Kannangara Chathurika , Carson Jerome
Published: November 2024

Longitudinal research into the impact of COVID-19 on university students’ mental health beyond the pandemic is lacking. This study aims to address the gap in the literature by tracking the mental health of university students over a two-year period, spanning the COVID-19 pandemic and its aftermath. A two-year longitudinal study surveyed a sample of university students (n = 302) three times between May 2020 and May 2022. Students’ psychological distress, generalised anxiety, flourishing, and personal wellbeing were assessed at each time point. It was found that students’ psychological distress levels spiked in May 2021 (T1) during the first year of the pandemic but reverted back to similar levels seen in May 2020 (T0) at the two-year follow-up (T2). While generalised anxiety gradually improved, both students’ psychological distress and generalised anxiety remained considerably worse than pre-pandemic norms obtained in other studies. Students’ flourishing scores remained very low, while their life satisfaction and state happiness improved slightly between May 2021 (T1) and May 2022 (T2). These findings clearly demonstrate that students’ mental health is still in crisis, even after the COVID-19 pandemic. More needs to be done to support students beyond the pandemic generally, including this particularly unique cohort of students who endured unprecedented challenges for prolonged periods, and who are now transitioning into the working world. Practical implications and recommendations are discussed.
Convergence, Mining, and Application: A Data Collaboration Framework for Spatial-Gene Research and Practice
Authors: Lan Wenlong , Chen Jingheng , Duan Jin , Li Junyi
Published: November 2024

In the digital era, data collaboration constitutes a critical trend in urban planning and design. It is of paramount importance in addressing contemporary issues related to the misinterpretation, misapplication, and misunderstanding of spatial genes, as well as facilitating data sharing and value creation associated with spatial genes. In this paper, targeting the complex problems of multiple entities and threads in spatial gene research and practice through, initially, a literature review, the correlation process between urban planning and data collaboration is examined, the spatial gene concept and the background of its proposal are expounded, and the challenges confronted in spatial-gene data collaboration are analyzed. Then, with an elaboration of the data value chain concept, a data collaboration framework for spatial-gene research and practice is constructed, specifically encompassing three main links: convergence, mining, and application. Finally, from the three aspects of data collection and storage, data analysis and processing, and data circulation and sharing, technical implementation paths and suggestions are put forward. We firmly contend that through the establishment of the framework, it is anticipated to promote data collaboration among multiple entities, enhance the efficiency and scientificity of urban design, and thereby facilitate the preservation of cultural diversity and the sustainable development of cities.
Study on the Influence of Window Openings on Seismic Performance of Stone Walls of Tibetan and Qiang Dwellings
Authors: Mo You , Guo Pan , Lu Jun , Wu Zhuohui , Yang Baoshan , Jiang Zhijun , Chen Feiyang , Jiang Wenxi
Published: November 2024

This study focuses on the effect of window openings on the seismic performance of the stone walls of Tibetan and Qiang dwellings. A typical stone wall of a Tibetan and Qiang dwelling constructed using irregular stone and yellow mud masonry in Li County, Sichuan Province, was chosen as a prototype, and two stone walls with different structural window openings were designed for proposed static tests and microscopic electron microscope scanning (SEM), which obtained the damage patterns and microscopic damage mechanisms of the walls and analyzed them in comparison with the test results of the stone walls without window openings. At the same time, a finite element model was established based on the test parameters to study the effects of opening size, shape, and aspect ratio on the seismic performance of the stone walls of Tibetan and Qiang dwellings. The findings indicate that “X”-shaped cracks at the corners of the window openings and extending to the surrounding areas are the primary damage characteristics. The unique microstructure of yellow clay and schist leads to the faster appearance of wall cracks. The peak load, stiffness, and energy dissipation of the windowed walls were less than those of the windowless walls. It was found through simulation that the seismic performance of the wall decreases with the increase in the opening size; as the wall’s openings take on different shapes, the ultimate bearing capacity steadily declines with the order of circular, square, triangular, trapezoidal, and rectangular; and under a range of aspect ratios, the wall’s seismic performance is best when the opening’s aspect ratio is 1:1. The research results of this paper are of reference value for the research, design, and construction of stone walls and other non-engineered masonry works of Tibetan and Qiang dwellings.
Multi-Grade Road Distress Detection Strategy Based on Enhanced YOLOv8 Model
Authors: Li Jiale , Jia Muqing , Li Bo , Meng Lingxin , Zhu Linkai
Published: November 2024

The total mileage of the road network in China has been growing rapidly during the last twenty years. With the development of deep learning, the automatic road distr ess detection method is more accurate and effective than manual detection. However, the road are classified into five grades according to the Chinese road standard and each grade has its own characteristics. A single model cannot effectively identify multi-grade roads with different materials and levels of road distress. This study proposes a YOLOv8-based road distress detection strategy adapted for multiple road grades. The improved URetinex-Net network is used to enhance the spatial features and scenario diversity of the road distress datasets. Compared to the base YOLOv8 model, the enhancements have led to a 12% increase in accuracy for cement roads, a 22.3% improvement in detection speed, a 5.5% increase in accuracy for ordinary asphalt roads, a 7.5% increase in recognition accuracy for highways, and a 9.3% improvement in detection speed, with significant effects. This study refines the classification of roads based on their grades and matches them with corresponding artificial intelligence training strategies, providing guidance for road inspection and maintenance.
Prevalence of Abnormalities at Tandem Endoscopy in Patients Referred for Colorectal Cancer Screening/Surveillance Colonoscopy
Authors: Triadafilopoulos George
Published: November 2024

Introduction: Performing a tandem endoscopy and colonoscopy in selected individuals has advantages, such as the early detection of benign and/or precancerous foregut diseases; it is efficient, and it may allow added therapies. It may also have disadvantages, such as generating anxiety from false-positive screening, possible harm from further testing, and unproven cost-effectiveness. Aims: We aimed to examine the prevalence of foregut endoscopic and histologic abnormalities in subjects referred for screening/surveillance colonoscopy who also underwent a tandem endoscopy. We wanted to (1) assess implications for cancer detection, intervention, and surveillance of precancerous foregut abnormalities, (2) identify benign foregut lesions, and (3) generate data on the utilities of this tandem approach. Patients and Methods: A retrospective cohort study of consecutive subjects referred for screening or surveillance colonoscopy who also underwent an endoscopy. Based on national screening guidelines, responses to prompting questions, personal or family history, or other risk factors, subjects were assigned to tandem endoscopy with biopsies (modified Seattle and Sydney protocols), under one anesthesia. Results: Of the 1004 patients referred for colonoscopy, 317 (32%) underwent tandem endoscopy. There were 214 women and 103 men. There were 237 Whites, 16 Asians, 40 Blacks, and 24 Hispanics. Median age was 59 (range 19–85). At endoscopy, we identified actionable benign (45%) peptic, inflammatory, and H. pylori-related abnormalities, and premalignant findings (i.e., intestinal metaplasia, 27%, dysplasia, 2%, and cancer 0.9%), comparable to the premalignant (40.3%) and malignant (0.6%) colonoscopy yield. Conclusions: When implemented based on national screening guidelines, tandem EGD and colonoscopy combines Barrett’s esophagus and gastric cancer screening in one examination, and it has a high yield in a diverse US population.
Disruptions in Lung Cancer Detection During COVID-19
Authors: Lal Trisha , Kim Uriel , Boutros Christina S. , Chakraborty Natalie N. , Doh Susan J. , Towe Christopher W. , Hoehn Richard S.
Published: November 2024

Objective: To quantify the extent of the disruption and recovery of lung cancer detection during the first two years of the pandemic, focusing on disparities across demographic and community factors. Methods: This retrospective cohort study used the SEER database to identify lung cancer cases from 2001 to 2021. Expected incidence rates for 2020 and 2021 were projected based on pre-pandemic trends (2000–2019) using the NCI’s Joinpoint Regression program. Percent differences between expected and observed incidence rates were calculated. Multivariate and propensity score analyses were conducted to quantify changes in the odds of being diagnosed with metastatic disease during the pandemic. Results: Lung cancer incidence fell by 10% in 2020 compared to pre-pandemic projections, with rural populations, non-Hispanic Black and Asian patients, and females disproportionately affected. By 2021, detection rates partially recovered but remained 5% below expected levels. Localized disease detection improved significantly, while rural communities not adjacent to metropolitan areas faced further declines. Adjusted analyses showed that patients with small-cell lung cancer (SCLC) and those of Hispanic, non-Hispanic Black, or Asian/Pacific Islander ethnicity had persistently higher rates of distant disease presentation through 2021. Conclusions: The pandemic significantly reduced lung cancer detection, with only partial recovery by 2021. Persistent gaps, particularly in rural and minoritized populations, highlight the need for targeted interventions to reengage these communities.
Real-World Evidence on Adverse Events and Healthcare Resource Utilization in Patients with Chronic Lymphocytic Leukaemia in Spain Using Natural Language Processing: The SRealCLL Study
Authors: Abrisqueta-Costa Pau , García-Marco José Antonio , Gutiérrez Antonio , Hernández-Rivas José Ángel , Andreu-Lapiedra Rafael , Arguello-Tomas Miguel , Leiva-Farré Carolina , López-Roda María Dolores , Callejo-Mellén Ángel , Álvarez-García Esther , Loscertales Javier
Published: November 2024

Objectives: The SRealCLL study described the occurrence of adverse events (AEs) and healthcare resource utilization in patients with chronic lymphocytic leukaemia (CLL) using artificial intelligence in a real-world scenario in Spain. Methods: We collected real-world data on patients with CLL from seven Spanish hospitals between January 2016 and December 2018, focusing on their AE and healthcare service utilization. Data extraction from electronic health records of 385,904 patients was performed using the EHRead® technology, which is based on natural language processing and machine learning. Results: Among the 534 CLL patients finally included, 270 (50.6%) were categorized as watch and wait (W&W), 230 (43.1%) as first-line treatment (1L), and 58 (10.9%) as relapse/refractory with second-line treatment (2L). The median study follow-up periods were 14.4, 8.4, and 6 months for W&W, 1L, and 2L, respectively. The most common antineoplastic treatments were ibrutinib (64.8%) and bendamustine + rituximab (12.6%) in 1L, and ibrutinib (62.1%) and venetoclax (15.5%) in 2L. Among the most frequent AEs, anaemia and thrombocytopenia presented higher rates in the treated groups (1L and 2L) compared with W&W (2.01 and 2.32 vs. 0.93; p ≤ 0.05 and 1.29 and 1.62 vs. 0.42; p ≤ 0.05). Moreover, several AEs, such as major bleeding, digestive symptoms, general symptoms, or Richter syndrome, were more frequent in 1L than W&W (all p ≤ 0.05). No differences were shown between groups in the rates of outpatient visits. However, rates of outpatient visits due to AE were higher in 1L than in W&W (1.07 vs. 0.65, p ≤ 0.05). The rates of patients being hospitalized were higher in the treated groups compared to W&W (1.68 and 1.9 vs. 0.88; p ≤ 0.05), and those due to AE were higher in 1L than W&W (1.23 vs. 0.60; p ≤ 0.05). Conclusions: Patients with CLL in 1L or 2L treatments often require healthcare resources due to AEs, particularly cytopenias. The methodology used in this study likely enabled us to identify higher rates of AEs that may be underreported using other real-world approaches. Addressing AEs with effective agents that maximize patient safety and optimize healthcare resource use is crucial in this typically older and comorbid population.
Core Outcomes of Self-Care Behaviours in Patients with Breast Cancer Treated with Oral Anticancer Agents: A Systematic Review
Authors: Ucciero Silvia , Lacarbonara Federica , Durante Angela , Torino Francesco , Lomper Katarzyna , Vellone Ercole , Di Nitto Marco
Published: November 2024

Background/Objectives: The use of oral anticancer agents (OAA) dates to the late 20th century in cancer treatment. It is crucial that patients implement self-care behaviours to keep their disease stable and manage their OAA treatment. The three dimensions of self-care according to Riegel et al., self-care maintenance, self-care monitoring, and self-care management, may be implemented to avoid negative outcomes. This paper seeks to identify outcomes associated with self-care in breast cancer patients during treatment with OAA and to compare which of these outcomes fall into the core outcome categorizations in oncology (minimal set of outcomes that research on a given health issue should measure). Methods: A systematic review with narrative synthesis was conducted. This study included patients with breast cancer taking any kind of OAA and described outcomes of self-care. The search was performed on MEDLINE, Web of Science and CINAHL/PsycINFO; Results: Of 4173 records, eight studies were selected and reviewed. The core outcomes mainly considered were mortality, survival, disease recurrence and quality of life. All studies focused only on pharmacological adherence outcome; none of them focused on other dimensions of self-care. Conclusions: This systematic review highlighted that there is a great lack of research on outcomes related to self-care in patients with breast cancer taking OOA. Even though pharmacological adherence to OAA is important, other behaviours are also important to improve patients’ outcomes, but they have not been studied. Further research is needed to study how self-care behaviours can impact patients’ outcomes.
The Role of the Cytoskeletal Regulatory Protein, Mammalian Enabling Protein (Mena), in Invasion and Metastasis of HPV16-Related Oral Squamous Cell Carcinoma
Authors: Guo Zhichen , Xie Linyang , Cui Hao , Yang Xin , Qi Hong , Yu Ming , Gong Yuxin , Tu Junbo , Na Sijia
Published: November 2024

Background: The objective of this study was to investigate the effect of mammalian-enabled protein (Mena) on invasion and metastasis of HPV16-related oral squamous cell carcinoma (OSCC) and the underlying mechanism. Materials and methods: The Mena gene expression profile of HPV-related OSCC was analyzed from the TCGA, GEO and TIMER databases. Immunohistochemistry was performed to study Mena, and the expression of invasion and metastasis-related markers and their clinicopathological characteristics. The role of Mena in the biological behavior of OSCC cell lines was assessed through both non-transfected and stably transfected models, analyzing EMT-related markers in vitro. The effect of Mena on HPV16-related OSCC metastasis through immunodeficient mouse model in vivo. Results: Mena expression was significantly decreased in HPV16-positive OSCC, and Mena expression in HPV16-negative OSCC was related with lymphatic metastasis and TNM stages, and E-cadherin, vimentin and MMP-2, but it was not statistically significant in HPV16-positive OSCC. Increased Mena expression was significantly correlated with a poor overall survival and disease-free survival in an HPV16-negative OSCC patient. Mena plays a vital role in promoting OSCC cell migration, invasion and metastasis. Conclusions: Mena promotes OSCC invasion and metastasis in HPV-negative OSCC by activating the EMT process. However, Mena expression in OSCC infected with HPV16 is inhibited, thus suppressing its invasion and metastasis ability.
Oligodendrocytes, the Forgotten Target of Gene Therapy
Authors: Ozgür-Gunes Yasemin , Le Stunff Catherine , Bougnères Pierre
Published: November 2024

If the billions of oligodendrocytes (OLs) populating the central nervous system (CNS) of patients could express their feelings, they would undoubtedly tell gene therapists about their frustration with the other neural cell populations, neurons, microglia, or astrocytes, which have been the favorite targets of gene transfer experiments. This review questions why OLs have been left out of most gene therapy attempts. The first explanation is that the pathogenic role of OLs is still discussed in most CNS diseases. Another reason is that the so-called ubiquitous CAG, CBA, CBh, or CMV promoters—widely used in gene therapy studies—are unable or poorly able to activate the transcription of episomal transgene copies brought by adeno-associated virus (AAV) vectors in OLs. Accordingly, transgene expression in OLs has either not been found or not been evaluated in most gene therapy studies in rodents or non-human primates. The aims of the current review are to give OLs their rightful place among the neural cells that future gene therapy could target and to encourage researchers to test the effect of OL transduction in various CNS diseases.
Motile Cilia in Female and Male Reproductive Tracts and Fertility
Authors: Wloga Dorota , Joachimiak Ewa , Osinka Anna , Ahmadi Salman , Majhi Sumita
Published: November 2024

Motile cilia are evolutionarily conserved organelles. In humans, multiciliated cells (MCCs), assembling several hundred motile cilia on their apical surface, are components of the monolayer epithelia lining lower and upper airways, brain ventricles, and parts of the reproductive tracts, the fallopian tube and uterus in females, and efferent ductules in males. The coordinated beating of cilia generates a force that enables a shift of the tubular fluid, particles, or cells along the surface of the ciliated epithelia. Uncoordinated or altered cilia motion or cilia immotility may result in subfertility or even infertility. Here, we summarize the current knowledge regarding the localization and function of MCCs in the human reproductive tracts, discuss how cilia and cilia beating-generated fluid flow directly and indirectly contribute to the processes in these organs, and how lack or improper functioning of cilia influence human fertility.
Advances in Induced Pluripotent Stem Cell-Derived Natural Killer Cell Therapy
Authors: Qiao Wenhua , Dong Peng , Chen Hui , Zhang Jianmin
Published: November 2024

Natural killer (NK) cells are cytotoxic lymphocytes of the innate immune system capable of killing virus-infected cells and/or cancer cells. The commonly used NK cells for therapeutic applications include primary NK cells and immortalized NK cell lines. However, primary NK cell therapy faces limitations due to its restricted proliferation capacity and challenges in stable storage. Meanwhile, the immortalized NK-92 cell line requires irradiation prior to infusion, which reduces its cytotoxic activity, providing a ready-made alternative and overcoming these bottlenecks. Recent improvements in differentiation protocols for iPSC-derived NK cells have facilitated the clinical production of iPSC-NK cells. Moreover, iPSC-NK cells can be genetically modified to enhance tumor targeting and improve the expansion and persistence of iPSC-NK cells, thereby achieving more robust antitumor efficacy. This paper focuses on the differentiation-protocols efforts of iPSC-derived NK cells and the latest progress in iPSC-NK cell therapy. Additionally, we discuss the current challenges faced by iPSC-NK cells and provide an outlook on future applications and developments.
Role of Protein Tyrosine Phosphatases in Inflammatory Bowel Disease, Celiac Disease and Diabetes: Focus on the Intestinal Mucosa
Authors: Bellomo Claudia , Furone Francesca , Rotondo Roberta , Ciscognetti Ilaria , Carpinelli Martina , Nicoletti Martina , D’Aniello Genoveffa , Sepe Leandra , Barone Maria Vittoria , Nanayakkara Merlin
Published: November 2024

Protein tyrosine phosphatases (PTPs) are a family of enzymes essential for numerous cellular processes, such as cell growth, inflammation, differentiation, immune-mediated responses and oncogenic transformation. The aim of this review is to review the literature concerning the role of several PTPs—PTPN22, PTPN2, PTPN6, PTPN11, PTPσ, DUSP2, DUSP6 and PTPRK—at the level of the intestinal mucosa in inflammatory bowel disease (IBD), celiac disease (CeD) and type 1 diabetes (T1D) in both in vitro and in vivo models. The results revealed shared features, at the level of the intestinal mucosa, between these diseases characterized by alterations of different biological processes, such as proliferation, autoimmunity, cell death, autophagy and inflammation. PTPs are now actively studied to develop new drugs. Also considering the availability of organoids as models to test new drugs in personalized ways, it is very likely that soon these proteins will be the targets of useful drugs.
Effect of Graphene and Graphene Oxide Addition to Polyethylene Film on Lipid Quality of African Catfish (Clarias gariepinus) Fillets During Refrigerated Storage
Authors: Domiszewski Zdzisław , Mierzejewska Sylwia , Michalska-Pożoga Iwona , Rybka Klaudia , Rydzkowski Tomasz
Published: November 2024

The purpose of this study was to investigate the effect of the addition of graphene (G) and graphene oxide (GO) to polyethylene film on the lipid oxidation level and sensory quality of African catfish fillets during refrigerated storage. The study was conducted on de-skinned fillets from a local farm. A composite film with 0.1%, 0.6%, and 1% G nanoplatelets and 0.1% GO nanoplatelets was used to package the fillets. The film was obtained using the free-blowing vertical upward method. The fillets were stored in polyethylene bags at 4 °C, and tests were conducted on the day of packaging and after 3, 7, 10, and 14 days of refrigerated storage. The peroxide number, anisidine number, and Totox index were determined in the extracted lipids using the Bligh and Dyer method. Sensory analysis of the fillets was carried out using the spot method and sensory profiling. Global migration for the film was also investigated. After 14 days, fillets packaged in the plain film exhibited, on average, 50%–100% higher lipid oxidation indices than those packaged in the film with G and GO. The film with 1% G and 0.1% GO additive showed the best properties for retarding the formation of aldehydes and ketones in lipids during fillet storage. There was no significant effect of the addition of nanomaterials to the film on the sensory quality of the fillets. The global migration did not exceed the allowed limit of 10 mg/dm2 for any of the films. Composite films with nanomaterials have great potential as packaging in slowing down oxidation processes in foods.
Metastable Racemic Ibuprofen Supercooled Liquid
Authors: Li Tuanjia , Xiao Wangchuan , Ren Shizhao , Xue Rongrong , Chen Fenghua
Published: November 2024

Amorphous solid dispersions are good candidates for improving solubility in water and the oral bioavailability of poorly water-soluble active pharmaceutical ingredients (APIs). Amorphous solids become supercooled liquids when the temperature reaches the glass transition temperature (Tg). For APIs with low melting points, Tg can be below room temperature, which makes it difficult to prepare long-term stable amorphous solids. Studies on the physicochemical properties of supercooled liquids shed light on the design of ASDs for APIs with low melting points. Racemic ibuprofen (IBU) supercooled liquid has been detected using differential scanning calorimetry and powder X-ray diffraction during the melt-quenching of IBU at a low temperature (0 °C). In this work, gram-scaled IBU supercooled liquid was prepared using the melt-quenching method, maintaining a liquid state for minutes at room temperature and for hours at 10 °C, as confirmed by visual observation. The Raman spectra, IR spectra, and UV-vis spectra results indicate that the structure of the IBU supercooled liquid is similar to that of an IBU solution instead of IBU Form I. The rate of recrystallization into Form I can be adjusted by controlling the temperature and additives, as confirmed by visual observation. Moreover, long-term stable IBU dispersions, with improved aqueous solubility, were inspired by the IBU supercooled liquid. The IBU supercooled liquid model can guide the preparation of ASDs for low melting point drugs.
Hemodynamic and Genetic Associations with the Risk of Idiopathic Pulmonary Arterial Hypertension Development in an Ethnic Cohort of Kazakhs
Authors: Taizhanova Dana , Nurpissova Togzhan , Abildinova Gulshara , Martynyuk Tamilla , Kulmyrzayeva Nazgul , Zholdybayeva Elena
Published: November 2024

Introduction: Idiopathic pulmonary arterial hypertension (IPAH) is a progressive and fatal disease. The aim of this study was to evaluate the association of polymorphism of the type 2 bone morphogenetic protein receptor gene (BMPR2) with the risk of IPAH development in an ethnic group of Kazakhs. We also describe the clinical and hemodynamic characteristics and outcomes of patients with and without carriers of BMPR2 gene mutations in IPAH. No available research highlights this problem in an ethnic group of Kazakhs. Materials and methods: A total of 53 patients of only Kazakh nationality with IPAH participated in the study. Clinical, functional, and hemodynamic characteristics, as well as the outcome of the disease, were compared among carriers and non-carriers of the BMPR2 mutation. Results: When receiving IPAH diagnosis, the average age of patients was 40.0 (32.0–48.0) years. Women predominated among the patients (86.8%). Of these, 17 (32.0%) were carriers of the gene mutation, and 36 (68.0%) did not have this mutation. The results of our research demonstrate that the Rs17199249 variant in BMPR2 contributed to increased susceptibility to IPAH. The T allele was associated with an increased risk of IPAH, with T = 75 (70.75%), G = 31 (29.24%), MAF—0.2925, x2—0.001, and HWE p—0.975. Carriers of the BMPR2 mutation were predominantly women (80.0%), and they had higher pulmonary vascular resistance (8.7–14.9 vs. 5.9–12.6 WU; p = 0.038), a low cardiac index (1.9–2.6 vs. 2.3–3.1 L/min per m2; p = 0.027), and a shorter time to death (p = 0.022). Conclusions: This is the first study of the genetic causes of IPAH that demonstrates the genetic polymorphism of BMPR2 is associated with an increased risk of IPAH developing with worse hemodynamic parameters and clinical outcomes.
Enhancing Radiologist Efficiency with AI: A Multi-Reader Multi-Case Study on Aortic Dissection Detection and Prioritization
Authors: Cotena Martina , Ayobi Angela , Zuchowski Colin , Junn Jacqueline C. , Weinberg Brent D. , Chang Peter D. , Chow Daniel S. , Soun Jennifer E. , Roca-Sogorb Mar , Chaibi Yasmina , Quenet Sarah
Published: November 2024

Background and Objectives: Acute aortic dissection (AD) is a life-threatening condition in which early detection can significantly improve patient outcomes and survival. This study evaluates the clinical benefits of integrating a deep learning (DL)-based application for the automated detection and prioritization of AD on chest CT angiographies (CTAs) with a focus on the reduction in the scan-to-assessment time (STAT) and interpretation time (IT). Materials and Methods: This retrospective Multi-Reader Multi-Case (MRMC) study compared AD detection with and without artificial intelligence (AI) assistance. The ground truth was established by two U.S. board-certified radiologists, while three additional expert radiologists served as readers. Each reader assessed the same CTAs in two phases: assessment unaided by AI assistance (pre-AI arm) and, after a 1-month washout period, assessment aided by device outputs (post-AI arm). STAT and IT metrics were compared between the two arms. Results: This study included 285 CTAs (95 per reader, per arm) with a mean patient age of 58.5 years ±14.7 (SD), of which 52% were male and 37% had a prevalence of AD. AI assistance significantly reduced the STAT for detecting 33 true positive AD cases from 15.84 min (95% CI: 13.37–18.31 min) without AI to 5.07 min (95% CI: 4.23–5.91 min) with AI, representing a 68% reduction (p < 0.01). The IT also reduced significantly from 21.22 s (95% CI: 19.87–22.58 s) without AI to 14.17 s (95% CI: 13.39–14.95 s) with AI (p < 0.05). Conclusions: The integration of a DL-based algorithm for AD detection on chest CTAs significantly reduces both the STAT and IT. By prioritizing urgent cases, the AI-assisted approach outperforms the standard First-In, First-Out (FIFO) workflow.
Gingivitis and Its Causes in Children Aged 3–7 Years
Authors: Olczak-Kowalczyk Dorota , Turska-Szybka Anna , Studnicki Marcin , Piekoszewska-Ziętek Paula
Published: November 2024

Objectives: Gingivitis manifests as redness, swelling, and bleeding of the gingiva but no loss of connective tissue attachment. It is usually painless and rarely leads to spontaneous bleeding, and most patients are unaware of the disease or are unable to recognize it. In children and adolescents, it is most often caused by plaque accumulation. The purpose of the following study was to determine the prevalence of gingivitis and its causes in children aged 3 to 7 years. Methods: Patients were classed in the following three age groups: 3-year-olds, 5-year-olds, and 7-year-olds, who were generally healthy, not taking permanent medication, and without developmental defects of dentition were eligible for the study. A questionnaire survey assessed socioeconomic factors, frequency of dental visits, and hygiene and dietary habits. The clinical examination assessed the condition of the teeth based on dmft/DMFT, and the presence of gingivitis was based on the bleeding on probing. The obtained results were subjected to statistical analysis. Results: A total of 3558 patients were examined. Gingivitis was present in 436 (12.25%) of the patients. In the group of 3-year-olds, gingivitis was significantly more common in boys (p = 0.0024). There were significant positive correlations between gingivitis and the average number of teeth affected by caries for the male gender in the group of 5- and 7-year-olds and in all age groups with dmft/DMFT > 0 values and the occurrence of symptomatic visits. Conclusions: The prevalence of gingivitis in children aged 3–7 years is influenced by socioeconomic, oral hygiene, and diet-related factors. Poor dental health predisposes to the occurrence of gingivitis.
Primary and Metastatic Pancreatic Ewing Sarcomas: A Case Report and Review of the Literature
Authors: Koufopoulos Nektarios I. , Samaras Menelaos G. , Kotanidis Christakis , Skarentzos Konstantinos , Pouliakis Abraham , Boutas Ioannis , Kontogeorgi Adamantia , Zanelli Magda , Palicelli Andrea , Zizzo Maurizio , Broggi Giuseppe , Caltabiano Rosario , Kyriazoglou Anastasios I. , Goutas Dimitrios
Published: November 2024

Ewing sarcomas are rare tumors arising mainly in the bones and the surrounding soft tissues. Primary extraosseous Ewing sarcomas have also been described in several other organs and locations other than bones, including the pancreas. These tumors have well-defined histological, immunohistochemical, and molecular characteristics. In this manuscript, we present a case of primary Ewing sarcoma of the pancreas in a 29-year-old patient, and we systematically review the literature on both primary and metastatic Ewing sarcomas of the pancreas, describing their clinicopathological characteristics. We also discuss the differential diagnosis and the treatment of this rare entity.
HawkEye Conv-Driven YOLOv10 with Advanced Feature Pyramid Networks for Small Object Detection in UAV Imagery
Authors: Li Yihang , Yang Wenzhong , Wang Liejun , Tao Xiaoming , Yin Yabo , Chen Danny
Published: November 2024

Current mainstream computer vision algorithms focus on designing suitable network architectures and loss functions to fit training data. However, the accuracy of small object detection remains lower than for other scales, and the design of convolution operators limits the model’s performance. For UAV small object detection, standard convolutions, due to their fixed kernel size, cannot adaptively capture small object spatial information. Many convolutional variants have scattered sampling points, leading to blurred boundaries and reduced accuracy. In response, we propose HawkEye Conv (HEConv), which utilizes stable sampling and dynamic offsets with random selection. By varying the convolution kernel design, HEConv reduces the accuracy gap between small and larger objects while offering multiple versions and plug-and-play capabilities. We also develop HawkEye Spatial Pyramid Pooling and Gradual Dynamic Feature Pyramid Network modules to validate HEConv. Experiments on the RFRB agricultural and VisDrone2019 urban datasets demonstrate that, compared to YOLOv10, our model improves AP50 by 11.9% and 6.2%, APS by 11.5% and 5%, and F1-score by 5% and 7%. Importantly, it enhances small object detection without sacrificing large object accuracy, thereby reducing the multi-scale performance gap.
Physics-Informed Neural Networks for Unmanned Aerial Vehicle System Estimation
Authors: Bianchi Domenico , Epicoco Nicola , Di Ferdinando Mario , Di Gennaro Stefano , Pepe Pierdomenico
Published: November 2024

The dynamic nature of quadrotor flight introduces significant uncertainty in system parameters, such as thrust and drag factors. Consequently, operators grapple with escalating challenges in implementing real-time control actions. This study presents an approach for estimating the dynamic model of Unmanned Aerial Vehicles based on Physics-Informed Neural Networks (PINNs), which is of paramount importance due to the presence of uncertain data and since control actions are required in very short computation times. In this regard, by including physical laws into neural networks, PINNs offer the potential to tackle several issues, such as heightened non-linearities in low-inertia systems, elevated measurement noise, and constraints on data availability or uncertainties, while ensuring the robustness of the solution, thus ensuring effective results in short time, once the network training has been performed and without the need to be retrained. The effectiveness of the proposed method is showcased in a simulation environment with real data and juxtaposed with a state-of-the-art technique, such as the Extended Kalman Filter (EKF). The results show that the proposed estimator outperforms the EKF both in terms of the efficacy of the solution and computation time.
Extended Reality in Agricultural Education: A Framework for Implementation
Authors: Naudé Daniël Haarhoff , Botha Benjamin Stephanus , Hugo Lizemari , Jordaan Henry , Lombard Willem Abraham
Published: November 2024

Agriculture 4.0 technologies have the potential to revolutionise both agricultural production and the way we educate the next generation of agricultural scientists. As many students enrolling in agricultural science education lack an agricultural background, it is difficult for them to grasp complex agricultural principles in an educational setting. Students without experience are thus at a disadvantage compared to others with prior knowledge. Technologies such as extended reality (XR) can be used as a tool to bridge the gap between theory and practice. With its ability to replicate real-world agricultural production principles within a classroom, XR can provide students with the necessary agricultural experience required within the industry. However, existing literature lacks comprehensive frameworks to guide educators on the implementation of this technology, which could lead to unsuccessful implementation. To ensure the successful implementation of XR in agricultural science education in higher education settings and to bridge the theory-practice gap, this article used the best-fit synthesis to develop a comprehensive framework from the existing literature. This framework can guide educators on the implementation of XR in higher education settings. The findings suggest that agriculture determinants, curriculum development, and facilitating conditions are three important concepts to consider for successful implementation. This XR-AgriEdu framework can be used by educators in agricultural science education to successfully implement XR.
DuSiamIE: A Lightweight Multidimensional Infrared-Enhanced RGBT Tracking Algorithm for Edge Device Deployment
Authors: Li Jiao , Wu Haochen , Gu Yuzhou , Lu Junyu , Sun Xuecheng
Published: November 2024

Advancements in deep learning and infrared sensors have facilitated the integration of RGB-thermal (RGBT) tracking technology in computer vision. However, contemporary RGBT tracking methods handle complex image data, resulting in inference procedures with a large number of floating-point operations and parameters, which limits their performance on general-purpose processors. We present a lightweight Siamese dual-stream infrared-enhanced RGBT tracking algorithm, called DuSiamIE.It is implemented on the low-power NVIDIA Jetson Nano to assess its practicality for edge-device applications in resource-limited settings. Our algorithm replaces the conventional backbone network with a modified MobileNetV3 and incorporates light-aware and infrared feature enhancement modules to extract and integrate multimodal information. Finally, NVIDIA TensorRT is used to improve the inference speed of the algorithm on edge devices. We validated our algorithm on two public RGBT tracking datasets. On the GTOT dataset, DuSiamIE achieved a precision (PR) of 83.4% and a success rate (SR) of 66.8%, with a tracking speed of 40.3 frames per second (FPS). On the RGBT234 dataset, the algorithm achieved a PR of 75.3% and an SR of 52.6%, with a tracking speed of 34.7 FPS. Compared with other algorithms, DuSiamIE exhibits a slight loss in accuracy but significantly outperforms them in speed on resource-constrained edge devices. It is the only algorithm among those tested that can perform real-time tracking on such devices.
Mutual Interference Suppression and Signal Enhancement Method for Ground-Penetrating Radar Based on Deep Learning
Authors: Lei Wentai , Tan Xin , Luo Chaopeng , Xue Wei
Published: November 2024

Ground-Penetrating Radar (GPR) is a non-destructive sensing technology that utilizes high electromagnetic frequencies. However, mutual interference waves caused by multiple scattering between targets can significantly complicate the interpretation of GPR B-scan images, especially when shallow targets obscure deeper ones. Existing methods primarily focus on extracting target signals from background clutter, frequently overlooking the impact of mutual interference. This paper proposes a convolutional neural network, termed MIS-SE-Net (Mutual Interference Suppression and Signal Enhancement Network), designed to suppress mutual interference waves while preserving shallow target signals and enhancing deeper ones. MIS-SE-Net incorporates attention gates into its encoder–decoder architecture, thereby improving its capabilities in interference suppression and enhancement of weak signals. The network is optimized using a combination of Mean Absolute Error (MAE) loss and perceptual loss. To evaluate MIS-SE-Net, the multi-scale weighted back projection (MWBP) imaging algorithm is used. Simulation results show that after processing with MIS-SE-Net, the integrated side-lobe ratio (ISLR) metric of MWBP imaging decreases by an average of 2.37%, while the signal-to-clutter ratio (SCR) increases by an average of 1.65%. For measured data, results show an average decrease of 7.51% in ISLR and an increase of 2.47% in SCR. These findings validate the effectiveness of the proposed method in suppressing interference, enhancing weak signals, and improving imaging quality.
Advanced Customer Behavior Tracking and Heatmap Analysis with YOLOv5 and DeepSORT in Retail Environment
Authors: Shili Mohamed , Jayasingh Sudarsan , Hammedi Salah
Published: November 2024

This paper presents a computer-vision-based approach designed to enhance product placement and sales strategies in physical retail stores through real-time analysis of customer behavior. Our method employs DeepSORT for tracking and YOLOv5 for object identification to generate heatmaps that illustrate consumer movement patterns and engagement levels across various retail locations. To precisely track customer paths, the procedure starts with the collection of video material, which is then analyzed. Customer interaction and traffic patterns across various retail zones are represented using heatmap visualization, which offers useful information about consumer preferences and product popularity. In order to maximize customer engagement and optimize the shopping experience, businesses may use the findings of this analysis to improve product placements, store layouts, and marketing strategies. With its low intervention requirements and scalable and non-intrusive solution, this system may be used in a variety of retail environments. This system offers a scalable and non-intrusive solution that requires minimal intervention, making it adaptable across different retail settings. Our findings demonstrate the approach’s effectiveness in identifying strategic areas for improvement and adapting retail environments based on real-time customer interaction data. This study underscores the potential of computer vision in retail analytics, enabling data-driven decisions that enhance both customer satisfaction and operational efficiency. This approach gives merchants useful data to develop more responsive, customized, and effective shopping experiences by providing a dynamic perspective of consumer behavior. Retailers may promote a modernized and customer-centered retail management strategy by using this creative application of computer vision to match marketing tactics and shop design with real consumer behaviors.
Trajectory Planning for Lane Change with Intelligent Vehicles Using Fuzzy Logic and a Dynamic Programming and Quadratic Programming Algorithm
Authors: Li Jiahao , Li Shengqin , Wang Juncheng
Published: November 2024

With the increasing demand for autonomous driving, ensuring safe and efficient lane-changing behavior in multi-lane traffic scenarios has become a key challenge. This paper proposes an algorithm for active lane-changing decision-making and trajectory planning designed for intelligent vehicles in such environments. The lane-changing intent is evaluated using fuzzy logic, followed by an assessment of lane-changing feasibility based on a lane utility evaluation function. A hierarchical model for path and speed planning is established. Path clusters are generated using quintic polynomials. With a multi-objective cost function designed to ensure collision safety, smoothness, road boundaries, and trajectory continuity, dynamic programming (DP) and quadratic programming (QP) are employed to obtain the trajectory with the minimum cost among the trajectory set fitted by fifth-order polynomials, which is the optimal lane-changing trajectory. For speed planning, obstacles are projected onto the S–T coordinate system, which is a coordinate system with time as the horizontal axis and the distance(s) of the planned path as the vertical axis, and multi-objective cost functions for speed, acceleration, and speed continuity are designed. The speed curve is optimized using DP followed by QP under given constraints. Simulation results show that the proposed algorithm makes safe and effective lane-changing decisions based on traffic conditions, vehicle distances, and speeds. The model generates smooth and stable paths while ensuring the safe and efficient execution of lane changes. This process meets real-time requirements and verifies the reliability of the algorithm.
A Fully Integrated 1.8 V Low-Power LDO Regulator with Dynamic Transient Control for SoC Applications
Authors: Zachos Nikolaos , Gogolou Vasiliki , Noulis Thomas
Published: November 2024

This work presents a novel, fully integrated low-dropout (LDO) regulator optimized for low-power applications with a wide load current range. By utilizing dynamic biasing to improve transient response, the LDO regulator achieves impressive performance with 0.26 μV/mA load regulation (LDR) and 19.92 μV/V line regulation (LNR). It also features a fast 8.6 μs settling time during load transitions up to 30 mA and a low quiescent current of 6.3 μA. The LDO regulator maintains a 1.8 V output for input voltages ranging from 2.1 V to 3.3 V, with a dropout voltage of 100 mV and supports load currents from 0.3 mA to 30 mA over a temperature range of −40 °C to +85 °C. The design, implemented in a standard 180 nm CMOS process, offers high accuracy and efficiency, making it a well-suited solution for battery-powered systems.