bluuebunny/crossref_metadata_2025 huggingface dataset:
Deep Learning-Based Prediction Model for the Cobb Angle in Adolescent Idiopathic Scoliosis Patients
Authors: Chui Chun-Sing (Elvis) , He Zhong , Lam Tsz-Ping , Mak Ka-Kwan (Kyle) , Ng Hin-Ting (Randy) , Fung Chun-Hai (Ericsson) , Chan Mei-Shuen , Law Sheung-Wai , Lee Yuk-Wai (Wayne) , Hung Lik-Hang (Alec) , Chu Chiu-Wing (Winnie) , Mak Sze-Yi (Sibyl) , Yau Wing-Fung (Edmond) , Liu Zhen , Li Wu-Jun , Zhu Zezhang , Wong Man Yeung (Ronald) , Cheng Chun-Yiu (Jack) , Qiu Yong , Yung Shu-Hang (Patrick)
Published: June 2024

Scoliosis, characterized by spine deformity, is most common in adolescent idiopathic scoliosis (AIS). Manual Cobb angle measurement limitations underscore the need for automated tools. This study employed a vertebral landmark extraction method and Feedforward Neural Network (FNN) to predict scoliosis progression in 79 AIS patients. The novel intervertebral angles matrix format showcased results. The mean absolute error for the intervertebral angle progression was 1.5 degrees, while the Pearson correlation of the predicted Cobb angles was 0.86. The accuracy in classifying Cobb angles (<15°, 15–25°, 25–35°, 35–45°, >45°) was 0.85, with 0.65 sensitivity and 0.91 specificity. The FNN demonstrated superior accuracy, sensitivity, and specificity, aiding in tailored treatments for potential scoliosis progression. Addressing FNNs’ over-fitting issue through strategies like “dropout” or regularization could further enhance their performance. This study presents a promising step towards automated scoliosis diagnosis and prognosis.
ML Models Built Using Clinical Parameters and Radiomic Features Extracted from 18F-Choline PET/CT for the Prediction of Biochemical Recurrence after Metastasis-Directed Therapy in Patients with Oligometastatic Prostate Cancer
Authors: Urso Luca , Cittanti Corrado , Manco Luigi , Ortolan Naima , Borgia Francesca , Malorgio Antonio , Scribano Giovanni , Mastella Edoardo , Guidoboni Massimo , Stefanelli Antonio , Turra Alessandro , Bartolomei Mirco
Published: June 2024

Oligometastatic patients at [18F]F-Fluorocholine (18F-choline) PET/CT may be treated with metastasis-directed therapy (MDT). The aim of this study was to combine radiomic parameters extracted from 18F-choline PET/CT and clinical data to build machine learning (ML) models able to predict MDT efficacy. Methods: Oligorecurrent patients (≤5 lesions) at 18F-choline PET/CT and treated with MDT were collected. A per-patient and per-lesion analysis was performed, using 2-year biochemical recurrence (BCR) after MDT as the standard of reference. Clinical parameters and radiomic features (RFts) extracted from 18F-choline PET/CT were used for training five ML Models for both CT and PET images. The performance metrics were calculated (i.e., Area Under the Curve—AUC; Classification Accuracy—CA). Results: A total of 46 metastases were selected and segmented in 29 patients. BCR after MDT occurred in 20 (69%) patients after 2 years of follow-up. In total, 73 and 33 robust RFTs were selected from CT and PET datasets, respectively. PET ML Models showed better performances than CT Models for discriminating BCR after MDT, with Stochastic Gradient Descent (SGD) being the best model (AUC = 0.95; CA = 0.90). Conclusion: ML Models built using clinical parameters and CT and PET RFts extracted via 18F-choline PET/CT can accurately predict BCR after MDT in oligorecurrent PCa patients. If validated externally, ML Models could improve the selection of oligorecurrent PCa patients for treatment with MDT.
Advancements in Artificial Intelligence for Medical Computer-Aided Diagnosis
Authors: Al-antari Mugahed A.
Published: June 2024

Rapid advancements in artificial intelligence (AI) and machine learning (ML) are currently transforming the field of diagnostics, enabling unprecedented accuracy and efficiency in disease detection, classification, and treatment planning. This Special Issue, entitled “Artificial Intelligence Advances for Medical Computer-Aided Diagnosis”, presents a curated collection of cutting-edge research that explores the integration of AI and ML technologies into various diagnostic modalities. The contributions presented here highlight innovative algorithms, models, and applications that pave the way for improved diagnostic capabilities across a range of medical fields, including radiology, pathology, genomics, and personalized medicine. By showcasing both theoretical advancements and practical implementations, this Special Issue aims to provide a comprehensive overview of current trends and future directions in AI-driven diagnostics, fostering further research and collaboration in this dynamic and impactful area of healthcare. We have published a total of 12 research articles in this Special Issue, all collected between March 2023 and December 2023, comprising 1 Editorial cover letter, 9 regular research articles, 1 review article, and 1 article categorized as “other”.
CT Angiography-Guided Needle Insertion for Interstitial Brachytherapy in Locally Advanced Cervical Cancer
Authors: Kirsch-Mangu Alexandra Timea , Pop Diana Cristina , Tipcu Alexandru , Andries Alexandra Ioana , Pasca Gina Iulia , Fekete Zsolt , Roman Andrei , Irimie Alexandru , Ordeanu Claudia
Published: June 2024

CT angiography might be a suitable procedure to avoid arterial puncture in combined intracavitary and interstitial brachytherapy for cervical cancer curatively treated with combined chemoradiation and brachytherapy boost. Data in the literature about this technique are scarce. We introduced this method and collected brachytherapy data from patients treated in our department between May 2021 and April 2024. We analyzed the applicator subtype, needle insertion (planned versus implanted), implanted depth and the role of CT angiography in selecting needle trajectories and insertion depths. None of the patients managed through this protocol experienced atrial puncture and consequent hemorrhage. Needle positions were accurately selected with the aid of CT angiography with proper coverage of brachytherapy targets and avoidance of organs at risk. CT angiography is a promising method for guiding needle insertion during interstitial brachytherapy.
Community-Based View on Diagnostic Imaging at the End of COVID-19 Pandemic: Online Survey-Assisted Study
Authors: Anfinogenova Nina D. , Maksimova Aleksandra S. , Shelkovnikova Tatiana A. , Ryumshina Nadezhda I. , Kuznetsova Alina D. , Chesalov Nazary P. , Karpov Rostislav S. , Ussov Wladimir Y. , Repin Alexey N.
Published: June 2024

(1) Background: An online survey-based observational cross-sectional study aimed at elucidating the experience and attitudes of an unstructured population regarding diagnostic imaging. (2) Methods: Invitations to participate were distributed using mixed-mode design to deidentified residents aged 18 years and older. Main outcome measures included morbidity structure and incidence of diagnostic imaging administrations. (3) Results: Respondents (n = 1069) aged 44.3 ± 14.4 years; 32.8% suffered from cardiovascular diseases (CVD); 9.5% had chronic respiratory pathology; 28.9% considered themselves healthy. Respondents with COVID-19 history (49.7%) reported higher rates of computed tomography (CT) (p < 0.0001), magnetic resonance imaging (MRI) (p < 0.001), and ultrasound (p < 0.05). COVID-19 history in CVD respondents shifted imaging administrations towards CT and MRI (p < 0.05). Every tenth respondent received MRI, CT, and ultrasound on a paid basis; 29.0% could not pay for diagnostic procedures; 13.1% reported unavailable MRI. Professional status significantly affected the pattern of diagnostic modalities (p < 0.05). MRI and CT availability differed between respondents in urban and rural areas (p < 0.0001). History of technogenic events predisposed responders to overestimate diagnostic value of fluorography (p < 0.05). (4) Conclusions: Preparedness to future pandemics requires the development of community-based outreach programs focusing on people’s awareness regarding medical imaging safety and diagnostic value.
Uterine Tumor Resembling Ovarian Sex-Cord Tumor (UTROSCT): A Rare Polyphenotypic Neoplasm
Authors: Giordano Giovanna , Guareschi Debora , Thai Elena
Published: June 2024

Uterine tumor resembling ovarian sex-cord tumor (UTROSCT) is a rare form of uterine mesenchymal neoplasm. Although UTROSCT generally exhibits benign behavior with a favorable prognosis, this neoplasm is nevertheless classified as being of uncertain malignant potential, given its low rate of recurrence and the fact that it rarely produces metastases (e.g., in the lymph nodes, epiploic appendix, omentum, small bowel, subcutaneous tissue, lungs). Its histogenesis is also uncertain. Typically, UTROSCT occurs in peri-menopausal or menopausal women, but it can sometimes be observed in young women. Usually, this neoplasm can be found in the uterine corpus as a nodular intramural lesion, while it is less frequently submucosal, subserosal, or polypoid/intracavitary. UTROSCT can cause abnormal bleeding, pelvic pain, enlarged uterus, and mass sensation, but sometimes it is found purely by chance. This neoplasm can be considered polyphenotypic on morphological, immunohistochemical, and genetic analyses. Generally, upon microscopic examination, UTROSCT shows a predominant pattern of the cords, nests, and trabeculae typical of sex-cord tumors of the ovary, while immunohistochemically it is characterized by a coexpression of epithelial, smooth muscle, and sex-cord markers. The aim of this review is to report clinical and pathological data and genetic alterations to establish their impact on the prognosis and management of patients affected by this rare entity.
A Case of Refractory Vernal Keratoconjunctivitis Showing Improvement after the Administration of Upadacitinib for the Treatment of Atopic Dermatitis
Authors: Mima Yoshihito , Tsutsumi Eri , Ohtsuka Tsutomu , Ebato Ippei , Nakata Yukihiro , Kubota Taro , Norimatsu Yuta
Published: June 2024

Vernal keratoconjunctivitis is a persistent allergic ocular disease predominantly mediated by the T-helper 2 lymphocyte-associated immune response. The standard therapeutic approaches for vernal keratoconjunctivitis include topical corticosteroids and immunosuppressive eye drops. However, managing vernal keratoconjunctivitis with only topical treatments becomes challenging during seasonally exacerbated periods. Systemic treatments such as oral corticosteroids or cyclosporine may be alternative options. Recently, dupilumab’s efficacy in refractory vernal keratoconjunctivitis treatment has been documented. Here, we report a case of refractory vernal keratoconjunctivitis coexisting with atopic dermatitis that rapidly improved after upadacitinib administration. An 18-year-old Japanese woman presented with atopic dermatitis, vernal keratoconjunctivitis, and hay fever. In winter, the patient experienced widespread erythema and escalated itching, leading to significant discomfort and insomnia. Owing to the difficulty in maintaining her current regimen, upadacitinib (15 mg), a Janus kinase inhibitor was initiated. After upadacitinib administration, the treatment-resistant vernal keratoconjunctivitis and erythema improved. Upadacitinib is beneficial in severe cases of atopic dermatitis. Consequently, in our case, upadacitinib may offer therapeutic benefits for refractory vernal conjunctivitis by improving the T-helper 1/2 type immune response, autoimmunity, and oxidative stress. To our knowledge, this is the first report suggesting the potential utility of upadacitinib in managing severe vernal conjunctivitis.
Inoculum Size and False-Positive Detection of NDM- and OXA-48-Type Carbapenemases Using Two Multiplex Lateral Flow Assays
Authors: Lee Chung-Ho , Cao Huiluo , Jiang Shuo , Wong Tammy Ting-Yan , Tse Cindy Wing-Sze , Ho Pak-Leung
Published: June 2024

The NG-Test CARBA 5 and Carbapenem-resistant K.N.I.V.O. Detection K-Set are lateral flow assays (LFAs) that rapidly detect five carbapenemases (KPC, NDM, IMP, VIM and OXA-48-like). We evaluated the effect of inoculum size on the performance of these two assays using 27 Enterobacterales isolates. Whole-genome sequencing (WGS) was used as the reference method. Using the NG-Test CARBA 5, eight Serratia spp. and six M. morganii isolates showed false-positive NDM results with a high inoculum. Using the Carbapenem-resistant K.N.I.V.O. Detection K-Set, eight M. morganii, four Serratia spp. and one K. pneumoniae isolates showed false-positive NDM and/or OXA-48-like bands at large inoculum sizes, while the other two M. morganii isolates demonstrated false-positive NDM and OXA-48-like results at all inoculum sizes. The false-positive bands varied in intensity. WGS confirmed that no carbapenemase gene was present. No protein sequence with a ≥50% identity to NDM or OXA-48-like enzymes was found. This study emphasizes the importance of assessing inoculum size in the diagnostic evaluation of LFAs.
Anxiety and Mood Disruption in Collegiate Athletes Acutely Following Mild Traumatic Brain Injury
Authors: Zhang Rachel , Martyna Michael , Cornwell Jordan , Teramoto Masaru , Selfridge Mollie , Brown Amanda , Ghajar Jamshid , Lumba-Brown Angela
Published: June 2024

Objective: To report the symptom burden of anxiety and mood-related indicators following mTBI in collegiate student-athletes. Study Design: Retrospective cohort study of varsity collegiate athletes. Setting: University sports medicine at a tertiary care center. Patients: Division I college varsity athletes diagnosed with mTBI at a single institution between 2016 and 2019. Independent Variables: Pre- and post-injury. Main Outcome Measures: Comparisons between baseline testing and post-mTBI symptom scale assessments were made to determine changes in scores at the individual and group levels. The primary outcome was the prevalence of post-mTBI symptoms from within 72 h of injury through return to play. Associations with sport, sex, age, and return-to-play time were included. Results: Compared to baseline, mood and anxiety symptom scores were significantly higher acutely following mTBI (2.1 ± 3.3 vs. 14.3 ± 12.2; p < 0.001). A family history of migraine was significantly associated with higher mood and anxiety symptom scores (20.0 ± 14.9 with history vs. 13.3 ± 11.3 without history; p = 0.042). Mood and anxiety symptom scores were highly correlated with non-mood and anxiety symptom scores for all athletes, including the subgroup with prolonged symptoms (r = 0.769; p < 0.001). Conclusions: Symptoms of anxiety or mood disruption are common during the acute period post-injury in varsity college athletes. Risk factors for higher symptom reports immediately following mTBI and for prolonged symptoms (>10 days) included female sex, those with a family history of migraine, and those with an overall higher symptom burden post-injury.
Morphological Characteristics of the Double Mental Foramen and Its Relevance in Clinical Practice: An Observational Study
Authors: Bruna-Mejias Alejandro , Nova-Baeza Pablo , Torres-Riquelme Florencia , Delgado-Retamal Maria Fernanda , Orellana-Donoso Mathias , Suazo-Santibañez Alejandra , Sepulveda-Loyola Walter , Valdés-Orrego Iván , Sanchis-Gimeno Juan , Valenzuela-Fuenzalida Juan José
Published: June 2024

The mental foramen (MF) is an opening found bilaterally on the anterolateral aspect of the mandible; it can be round or oval and have different diameters. One of the anatomical variants of the jaw is the presence of an accessory mental foramen (AMF). These are usually smaller than the MF and can be located above, below, or to the sides of the main MF. The objective of this study was to recognize the presence of AMF in dry jaws of the Chilean population and collect information about its clinical relevance reported in the literature. In this descriptive observational study, we have collected dried jaws obtained from three higher education institutions in Santiago de Chile, from the Department of Morphology of the Andrés Bello University, the Normal Human Anatomy Unit of the University of Santiago, and the Human Anatomy pavilion from the Faculty of Medicine of the Finis Terrae University. The samples for this research were obtained by convenience, and the observation of the jaws was carried out in the human anatomy laboratories of each institution by three evaluators independently, and a fourth evaluator was included to validate that each evaluation was correct. The sample for this research came from 260 dry jaws, showing the following findings from the total jaws studied, and to classify as an accessory MF, it will be examined and measured so that it complies with what is declared in the literature as the presence of AMF, which is between 0.74 mm. and 0.89 mm. There were 17 studies included with a sample that fluctuated between 1 and 4000, with a cumulative total of 7946 and an average number of jaws analyzed from the studies of 467.4, showing statistically significant differences between the means with the sample analyzed in this study; p = 0.095. For the cumulative prevalence of the presence of AMF, this was 3.07 in this study, and in the compared studies, the average of AMF was 8.01%, which did not present a statistically significant difference; p = 0.158. Regarding the presence of variants of unilateral AMF, this occurred in five jaws, which is equivalent to 1.84% in the sample of this study, while in previous studies, it was 7.5%, being higher on the left side than on the right. The presence of AMF is a variant with high prevalence if we compare it with other variants of the jaw. Knowledge of the anatomy and position of the AMF is crucial to analyze different scenarios in the face of surgical procedures or conservative treatments of the lower anterior dental region.
Non-Invasive Prediction of Choledocholithiasis Using 1D Convolutional Neural Networks and Clinical Data
Authors: Mena-Camilo Enrique , Salazar-Colores Sebastián , Aceves-Fernández Marco Antonio , Lozada-Hernández Edgard Efrén , Ramos-Arreguín Juan Manuel
Published: June 2024

This paper introduces a novel one-dimensional convolutional neural network that utilizes clinical data to accurately detect choledocholithiasis, where gallstones obstruct the common bile duct. Swift and precise detection of this condition is critical to preventing severe complications, such as biliary colic, jaundice, and pancreatitis. This cutting-edge model was rigorously compared with other machine learning methods commonly used in similar problems, such as logistic regression, linear discriminant analysis, and a state-of-the-art random forest, using a dataset derived from endoscopic retrograde cholangiopancreatography scans performed at Olive View–University of California, Los Angeles Medical Center. The one-dimensional convolutional neural network model demonstrated exceptional performance, achieving 90.77% accuracy and 92.86% specificity, with an area under the curve of 0.9270. While the paper acknowledges potential areas for improvement, it emphasizes the effectiveness of the one-dimensional convolutional neural network architecture. The results suggest that this one-dimensional convolutional neural network approach could serve as a plausible alternative to endoscopic retrograde cholangiopancreatography, considering its disadvantages, such as the need for specialized equipment and skilled personnel and the risk of postoperative complications. The potential of the one-dimensional convolutional neural network model to significantly advance the clinical diagnosis of this gallstone-related condition is notable, offering a less invasive, potentially safer, and more accessible alternative.
The Impact of AI on Metal Artifacts in CBCT Oral Cavity Imaging
Authors: Wajer Róża , Wajer Adrian , Kazimierczak Natalia , Wilamowska Justyna , Serafin Zbigniew
Published: June 2024

Objective: This study aimed to assess the impact of artificial intelligence (AI)-driven noise reduction algorithms on metal artifacts and image quality parameters in cone-beam computed tomography (CBCT) images of the oral cavity. Materials and Methods: This retrospective study included 70 patients, 61 of whom were analyzed after excluding those with severe motion artifacts. CBCT scans, performed using a Hyperion X9 PRO 13 × 10 CBCT machine, included images with dental implants, amalgam fillings, orthodontic appliances, root canal fillings, and crowns. Images were processed with the ClariCT.AI deep learning model (DLM) for noise reduction. Objective image quality was assessed using metrics such as the differentiation between voxel values (ΔVVs), the artifact index (AIx), and the contrast-to-noise ratio (CNR). Subjective assessments were performed by two experienced readers, who rated overall image quality and artifact intensity on predefined scales. Results: Compared with native images, DLM reconstructions significantly reduced the AIx and increased the CNR (p < 0.001), indicating improved image clarity and artifact reduction. Subjective assessments also favored DLM images, with higher ratings for overall image quality and lower artifact intensity (p < 0.001). However, the ΔVV values were similar between the native and DLM images, indicating that while the DLM reduced noise, it maintained the overall density distribution. Orthodontic appliances produced the most pronounced artifacts, while implants generated the least. Conclusions: AI-based noise reduction using ClariCT.AI significantly enhances CBCT image quality by reducing noise and metal artifacts, thereby improving diagnostic accuracy and treatment planning. Further research with larger, multicenter cohorts is recommended to validate these findings.
Deep Learning for Alzheimer’s Disease Prediction: A Comprehensive Review
Authors: Malik Isra , Iqbal Ahmed , Gu Yeong Hyeon , Al-antari Mugahed A.
Published: June 2024

Alzheimer’s disease (AD) is a neurological disorder that significantly impairs cognitive function, leading to memory loss and eventually death. AD progresses through three stages: early stage, mild cognitive impairment (MCI) (middle stage), and dementia. Early diagnosis of Alzheimer’s disease is crucial and can improve survival rates among patients. Traditional methods for diagnosing AD through regular checkups and manual examinations are challenging. Advances in computer-aided diagnosis systems (CADs) have led to the development of various artificial intelligence and deep learning-based methods for rapid AD detection. This survey aims to explore the different modalities, feature extraction methods, datasets, machine learning techniques, and validation methods used in AD detection. We reviewed 116 relevant papers from repositories including Elsevier (45), IEEE (25), Springer (19), Wiley (6), PLOS One (5), MDPI (3), World Scientific (3), Frontiers (3), PeerJ (2), Hindawi (2), IO Press (1), and other multiple sources (2). The review is presented in tables for ease of reference, allowing readers to quickly grasp the key findings of each study. Additionally, this review addresses the challenges in the current literature and emphasizes the importance of interpretability and explainability in understanding deep learning model predictions. The primary goal is to assess existing techniques for AD identification and highlight obstacles to guide future research.
Introducing a Novel Innovative Technique for the Recording and Interpretation of Dynamic Coronary Angiography
Authors: Nguyen Thach , Ngo Khiem , Vu Tri Loc , Nguyen Hien Q. , Pham Dat H. , Kodenchery Mihas , Zuin Marco , Rigatelli Gianluca , Nanjundappa Aravinda , Gibson Michael
Published: June 2024

In the study of coronary artery disease (CAD), the mechanism of plaque formation and development is still an important subject for investigation. A limitation of current coronary angiography (CAG) is that it can only show static images of the narrowing of arterial channels without identifying the mechanism of the disease or predicting its progression or regression. To address this limitation, the CAG technique has been modified. The new approach emphasizes identifying and analyzing blood flow patterns, employing methodologies akin to those used by hydraulic engineers for fluid or gas movement through domestic or industrial pipes and pumps. With the new technique, various flow patterns and arterial phenomena—such as laminar, turbulent, antegrade, retrograde, and recirculating flow and potentially water hammer shock and vortex formation—are identified, recorded, and classified. These phenomena are then correlated with the presence of lesions at different locations within the coronary vasculature. The formation and growth of these lesions are explained from the perspective of fluid mechanics. As the pathophysiology of CAD and other cardiovascular conditions becomes clearer, new medical, surgical, and interventional treatments could be developed to reverse abnormal coronary flow dynamics and restore laminar flow, leading to improved clinical outcomes.
Impact of Ocrelizumab on Disease Progression, Memory Improvement, and Quality of Life in Patients with Relapsing-Remitting Multiple Sclerosis: A Longitudinal MRI and Clinical Criteria Analysis
Authors: Schuldesz Amanda Claudia , Maganti Ram Kiram , Tudor Raluca , Cornea Amalia , Prodan Mihaela , Toma Ana-Olivia , Fericean Roxana Manuela , Simu Mihaela
Published: June 2024

Multiple sclerosis (MS) is a chronic, progressive neurological disorder that significantly impacts quality of life and functionality. Ocrelizumab, a monoclonal antibody targeting CD20-positive B cells, has emerged as a treatment for relapsing-remitting MS (RRMS). This study aimed to assess the impact of ocrelizumab on disease progression and quality of life over a longitudinal course, utilizing clinical criteria and magnetic resonance imaging (MRI) analyses. Conducted at the Neurology Department of Pius Brinzeu Clinical Emergency Hospital in Western Romania from 2020 to 2023, this observational study enrolled 93 patients with RRMS who commenced ocrelizumab therapy. The study employed the Expanded Disability Status Scale (EDSS) and MRI to evaluate disease progression, while quality of life was assessed using the World Health Organisation Quality of Life (WHOQOL) questionnaire, Beck Depression Index (BDI), and MOCA scales. Significant improvements were observed post-treatment. EDSS scores decreased from 4.61 to 4.08 (p = 0.038), indicating reduced disability. MRI analyses showed a substantial decrease in expansive lesions (from 67.74% to 26.88%, p < 0.001) and an increase in stationary lesions (from 32.26% to 73.12%, p < 0.001). Quality of life improvements were notable in the physical (from 58.42 to 64.84, p = 0.005) and environmental domains (from 63.21 to 68.44, p = 0.033). Cognitive functions, assessed via Montreal Cognitive Assessment (MOCA), showed a significant total score increase from 20.38 to 22.30 (p < 0.001). Subgroup analysis revealed more pronounced effects in females and younger patients, with a significant reduction in depressive symptoms measured by BDI scores (from 14.35 to 11.62, p = 0.003). Ocrelizumab significantly reduced disease activity and disability in RRMS patients, as demonstrated by improvements in EDSS scores and MRI findings. Quality of life and cognitive functions also showed considerable enhancements. These findings support ocrelizumab’s efficacy in not only managing MS symptoms but also improving overall patient well-being.
Evaluation of a New Simplified Approach for Upper Superficial Impacted Third Molar Extraction—A Retrospective Split-Mouth Study
Authors: Materni Alberto , Apaza Alccayhuaman Karol Alí , Maltagliati Alberto , Botticelli Daniele , Benedicenti Stefano
Published: June 2024

Background: A new access technique was developed to reduce postoperative adverse events after the extraction of impacted maxillary wisdom teeth. Hence, this study aimed to assess the occurrence of adverse events after the extraction of maxillary impacted wisdom teeth using a traditional access (TA) or a new technique (NT). Methods: Two different surgical incision designs were used for bilateral wisdom tooth extractions in 30 patients. The traditional incision was performed distal to the second molar in the center of the tuberosity, followed by a buccal releasing incision. After the tooth extraction, the wound was secured by sutures. The new technique consists of an oblique incision from the distal palatal aspect of the tuberosity towards the buccal aspect of the second molar. After the tooth extraction, cyanoacrylate glue was used on the wound. Results: Lower pain was reported by patients at the site treated with the new technique (p < 0.01). Edema, postsurgical bleeding, and hematoma were similar in both groups. The surgical time was shorter for the new technique (p < 0.01). Conclusions: The new technique applied for the extraction of impacted maxillary wisdom teeth reduced postsurgical pain and the duration of surgery.
Survival Rates of Short Dental Implants (≤6 mm) Used as an Alternative to Longer (>6 mm) Implants for the Rehabilitation of Posterior Partial Edentulism: A Systematic Review of RCTs
Authors: Emfietzoglou Rodopi , Dereka Xanthippi
Published: June 2024

Short dental implants have been proposed as an alternative treatment option to bone regeneration procedures for the rehabilitation of resorbed alveolar ridges. The aim of this paper was to systematically review randomized controlled trials (RCTs) comparing short implants (≤6 mm) and longer implants (>6 mm) in atrophic alveolar ridges in terms of implant survival rates, peri-implant marginal bone loss (MBL), prevalence of peri-implantitis and technical complications. A thorough electronic search was performed until September 2023. RCTs with follow-up of at least 1-year post-loading comparing short implants with rough surfaces to longer implants in the posterior jaws of systemically and periodontally healthy, partially edentulous adults were considered. Studies with incomplete information on the number of patients, follow-up or definition of “short implants” were excluded. The revised Cochrane risk-of-bias tool for randomized trials was used for Risk of bias assessment. Fixed-effects meta-analysis of the selected studies was applied to compare the outcome variables. Random-effect meta-analysis was performed, on the basis of within-study comparisons. In total, 16 articles were selected for meta-analysis and incorporated 408 short implants and 475 longer implants inserted in 317 and 388 patients, respectively. The survival rates of longer implants in pristine or augmented bone were significantly increased compared to short implants (95%CI: 2–5%, p < 0.001). Standard-length implants displayed increased, although non-statistically significant MBL (95%CI: −0.17–0.04, p > 0.05), and prevalence of peri-implantitis (95%CI: 0–5%, p > 0.05). No statistically significant differences were observed between short and long implants in terms of technical complications (implant-level 95%CI: −4–6%, p > 0.05). Short implants represent a promising alternative treatment option for the rehabilitation of posterior jaws to avoid additional bone augmentation procedures. Nonetheless, they should be selected cautiously due to a potentially limited survival rate compared to longer implants. A major limitation of this study is the variability in the included studies regarding sample size, patient profile, type of bone, loading protocol, definition of peri-implantitis, among others. This study received no external funding. The study protocol was registered in PROSPERO (CRD42023485514).
Tendon-Driven Continuum Robots for Aerial Manipulation—A Survey of Fabrication Methods
Authors: Uthayasooriyan Anuraj , Vanegas Fernando , Jalali Amir , Digumarti Krishna Manaswi , Janabi-Sharifi Farrokh , Gonzalez Felipe
Published: June 2024

Aerial manipulators have seen a rapid uptake for multiple applications, including inspection tasks and aerial robot–human interaction in building and construction. Whilst single degree of freedom (DoF) and multiple DoF rigid link manipulators (RLMs) have been extensively discussed in the aerial manipulation literature, continuum manipulators (CMs), often referred to as continuum robots (CRs), have not received the same attention. This survey seeks to summarise the existing works on continuum manipulator-based aerial manipulation research and the most prevalent designs of continuous backbone tendon-driven continuum robots (TDCRs) and multi-link backbone TDCRs, thereby providing a structured set of guidelines for fabricating continuum robots for aerial manipulation. With a history spanning over three decades, dominated by medical applications, CRs are now increasingly being used in other domains like industrial machinery and system inspection, also gaining popularity in aerial manipulation. Fuelled by diverse applications and their associated challenges, researchers have proposed a plethora of design solutions, primarily falling within the realms of concentric tube (CT) designs or tendon-driven designs. Leveraging research works published in the past decade, we place emphasis on the preparation of backbones, support structures, tendons, stiffness control, test procedures, and error considerations. We also present our perspectives and recommendations addressing essential design and fabrication aspects of TDCRs in the context of aerial manipulation, and provide valuable guidance for future research and development endeavours in this dynamic field.
Comparative Analysis of Deterministic and Nondeterministic Decision Trees for Decision Tables from Closed Classes
Authors: Ostonov Azimkhon , Moshkov Mikhail
Published: June 2024

In this paper, we consider classes of decision tables with many-valued decisions closed under operations of the removal of columns, the changing of decisions, the permutation of columns, and the duplication of columns. We study relationships among three parameters of these tables: the complexity of a decision table (if we consider the depth of the decision trees, then the complexity of a decision table is the number of columns in it), the minimum complexity of a deterministic decision tree, and the minimum complexity of a nondeterministic decision tree. We consider the rough classification of functions characterizing relationships and enumerate all possible seven types of relationships.
Investigation of Equilibrium in Oligopoly Markets with the Help of Tripled Fixed Points in Banach Spaces
Authors: Ilchev Atanas , Ivanova Vanya , Kulina Hristina , Yaneva Polina , Zlatanov Boyan
Published: June 2024

In the study we explore an oligopoly market for equilibrium and stability based on statistical data with the help of response functions rather than payoff maximization. To achieve this, we extend the concept of coupled fixed points to triple fixed points. We propose a new model that leads to generalized triple fixed points. We present a possible application of the generalized tripled fixed point model to the study of market equilibrium in an oligopolistic market dominated by three major competitors. The task of maximizing the payout functions of the three players is modified by the concept of generalized tripled fixed points of response functions. The presented model for generalized tripled fixed points of response functions is equivalent to Cournot payoff maximization, provided that the market price function and the three players’ cost functions are differentiable. Furthermore, we demonstrate that the contractive condition corresponds to the second-order constraints in payoff maximization. Moreover, the model under consideration is stable in the sense that it ensures the stability of the consecutive production process, as opposed to the payoff maximization model with which the market equilibrium may not be stable. A possible gap in the applications of the classical technique for maximization of the payoff functions is that the price function in the market may not be known, and any approximation of it may lead to the solution of a task different from the one generated by the market. We use empirical data from Bulgaria’s beer market to illustrate the created model. The statistical data gives fair information on how the players react without knowing the price function, their cost function, or their aims towards a specific market. We present two models based on the real data and their approximations, respectively. The two models, although different, show similar behavior in terms of time and the stability of the market equilibrium. Thus, the notion of response functions and tripled fixed points seems to present a justified way of modeling market processes in oligopoly markets when searching whether the market has reached equilibrium and if this equilibrium is unique and stable in time
The Relationship between Credit Rating and Environmental, Social, and Governance Score in Banking
Authors: Vortelinos Dimitrios , Menegaki Angeliki N. , Alexiou Spyros
Published: June 2024

The present paper investigates the relationship between stock prices, credit ratings, and ESG scores for banks internationally. First, it describes stock prices and ESG scores at an annual frequency, as well as stock price and credit risk at a daily frequency. The relationships between (a) stock price and credit rating returns with ESG score returns and (b) among ESG scores are examined by pairwise annual correlation, and daily correlations are examined between price and credit rating returns. Furthermore, Granger causality is used to examine the relationships between the following: (a) price and ESG score annual returns; (b) price and credit rating daily returns; and (c) total and pillar annual ESG scores. This study makes a significant contribution to the literature by providing a detailed temporal analysis using both annual and daily data frequencies, which is relatively rare in the field. There is evidence of statistically and empirically important relations in the form of pairwise correlations. The regressions reveal a low significance of few ESG score changes in explaining credit rating changes. A unique aspect of this paper is the comprehensive analysis of 16 granular ESG scores, including overall scores, pillar scores, and sub-scores, allowing for a multi-faceted understanding of how specific ESG factors impact financial metrics. We found evidence of the significance of COVID-19 in all research questions. Additionally, this paper highlights the impact of the COVID-19 pandemic on the relationships between ESG scores, credit ratings, and stock prices, offering timely insights into the heightened importance and volatility of ESG factors during crisis periods. Future research needs to shed more light on this relationship, however.
Urbanization and Health Expenditure: An Empirical Investigation from Households in Vietnam
Authors: Nguyen-Phung Hang Thu , Le Hai
Published: June 2024

This study examines the effects of urbanization on household health expenditure. Using a unique bi-annually household-level dataset from 2012–2016 from Vietnam, we obtain key findings as follows. To mitigate possible endogeneity concerns, we utilize a two-stage least squares regression (2SLS) approach, employing the development of information and communication (ICT) infrastructure at the province level as an instrumental variable (IV). The key findings can be summarized as follows. First, urbanization significantly reduces Vietnamese households’ inpatient and outpatient health expenses. Second, the self-treatment expenses of households increase as the process of urbanization advances. In addition, we perform various robustness checks, encompassing different measures of urbanization, the use of lag of urbanization as an additional IV, and the plausible exogenous IV. The outcomes derived from these rigorous sensitivity analyses substantiate the reliability and consistency of our key results. Finally, we propose different ways to explain these results, including health insurance expenses and household income.
Impact of Physical Model Projects and Multidisciplinary Teams in Fluid Mechanics Education
Authors: Sekaran Aarthi , Rodak Carolyn M.
Published: June 2024

Fluid mechanics, a required course in many undergraduate engineering disciplines, is often described as a challenging subject as it weaves together advanced mathematics and physics to solve conventional engineering problems. This study examines the effect of incorporating a physical model project via multidisciplinary teams into two theory-based fluid mechanics courses to address two general questions: Does the design and construction of the physical model aid in understanding fluid mechanics concepts? Does working with students of different engineering disciplines improve student experience and comprehension? The study was conducted in Spring 2023 with a cohort of 49 mechanical and civil engineering students; each project team had a mix of both disciplines. At the end of the semester, all projects were presented at a common venue, followed by an anonymous paper-based survey. The results indicate that around 83.7% of students felt the project had an overall positive impact on their learning experience. Despite initial student apprehension about multidisciplinary teams, 72% of students appreciated the opportunity to work with engineers from other disciplines, with qualitative inputs describing the value added from varied skill sets. In conclusion, this project enabled students to apply their in-class training to a real-world model while working in multidisciplinary teams. The results provide insight into the implementation of similar projects and the value of multidisciplinary teams.
Open Source Software-Defined Networking Controllers—Operational and Security Issues
Authors: Mardaus Aleksandra , Biernacka Edyta , Wójcik Robert , Domżał Jerzy
Published: June 2024

The Software-Defined Networking concept plays an important role in network management. The central controller, which is the main element of SDN, allows the provision of traffic engineering and security solutions in single- and multiple-layer networks based on optical transmission. In this work, we compare selected open-source implementations of SDN controllers. Throughput and latency measurements were analyzed using the CBench program. The simulation of a link failure and a controller failure were conducted using the API provided by the Mininet network simulator. To detect security vulnerabilities, a dedicated program, called sdnpwn, was used. This work provides an overview of the selected controllers, indicating their strengths and weaknesses. Moreover, some implemention suggestions and recommendations are presented.
Challenges: ESD Protection for Heterogeneously Integrated SoICs in Advanced Packaging
Authors: Pan Zijin , Li Xunyu , Hao Weiquan , Miao Runyu , Yue Zijian , Wang Albert
Published: June 2024

Electrostatic discharge (ESD) failure is a major reliability problem for all forms of microelectronics products. ESD protection is required for all integrated circuits (ICs). As dimension scaling-down approaches its physical limit, heterogeneous integration (HI) emerges as a main pathway towards the age beyond Moore’s Law to facilitate advanced microsystem chips with extreme performance and rich functionalities. Advanced packaging is a key requirement for HI-enabled integrated systems-on-chiplets (SoIC) that require robust ESD protection solutions. This article outlines key emerging technical challenges associated with smart future SoIC microsystem superchips in the context of advanced packaging technologies.
An Input-Series Output-Parallel DC–DC Converter Based on Fuzzy PID Three-Loop Control Strategy
Authors: Wen Chunxue , Li Shuhui , Wang Peng , Li Jianlin
Published: June 2024

In order to achieve high and low voltage isolation transformation in DC transmission and distribution networks, a multi module input-series output-parallel (ISOP) system consisting of a buck/boost converter and a CLLLC resonant converter as submodules was studied. This system can ensure that the CLLLC converter operates in the optimal state during frequency changes, achieves a soft switching function, and maintains a high conversion efficiency. This article establishes a mathematical model of a cascaded converter, analyzes its gain characteristics, and proposes a fuzzy PID three-loop control strategy to achieve good input voltage and output current sharing in the ISOP system. A simulation model is built on the MATLAB(R2023a)/Simulink platform to verify the effectiveness and superiority of the proposed control strategy. Finally, by building a prototype platform, the feasibility of the ISOP system and the effectiveness of fuzzy PID three-loop control were verified through experiments.
Dual-Core Photonic Crystal Fiber Polarization Beam Splitter Based on a Nematic Liquid Crystal with an Ultra-Short Length and Ultra-Wide Bandwidth
Authors: Ji Yuxiang , Du Yuhang , Dai Jixuan , Zou Hui , Zhang Ruizhe , Zhou Dinghao
Published: June 2024

This paper presents a novel pentagonal structure dual-core photonic crystal fiber polarizing beam splitter (PS-DC-PCF PBS) filled with a nematic liquid crystal (NLC) in the central hole. Unlike previous designs with symmetric arrangements, the upper and lower halves of the structure have different air hole arrangements. The upper half consists of air holes arranged in a regular quadrilateral pattern, while the lower half features a regular hexagonal arrangement of air holes. By filling the central hole with birefringent liquid crystal, the birefringence of the structure is enhanced, reducing the coupling lengths along the x polarization and y polarization directions. The polarization properties, coupling characteristics, and the influence of different structural parameters on the extinction ratio of the polarizing beam splitter are analyzed using the full-vector finite element method. Simulation results demonstrate that the designed PS-DC-PCF PBS achieves a maximum extinction ratio (ER) of 72.94 dB with a splitting length of only 61.9 μm and a wide operating bandwidth of 423 nm (1.324–1.747 μm), covering most of the O, E, S, C, L, and U communication bands. It exhibits not only ultra-short splitting lengths and ultra-wide splitting bandwidth but also good manufacturing tolerances and anti-interference capabilities. The designed PS-DC-PCF PBS could provide crucial device support for future all-optical communication systems and has potential applications in fiber optic communication or fiber laser systems.
Enhancing Cataract Detection through Hybrid CNN Approach and Image Quadration: A Solution for Precise Diagnosis and Improved Patient Care
Authors: Nguyen Van-Viet , Lin Chun-Ling
Published: June 2024

Cataracts, characterized by lens opacity, pose a significant global health concern, leading to blurred vision and potential blindness. Timely detection is crucial, particularly in regions with a shortage of ophthalmologists, where manual diagnosis is time-consuming. While deep learning and convolutional neural networks (CNNs) offer promising solutions, existing models often struggle with diverse datasets. This study introduces a hybrid CNN approach, training on both full retinal fundus images and quadrated parts (i.e., the fundus images divided into four segments). Majority voting is utilized to enhance accuracy, resulting in a superior performance of 97.12%, representing a 1.44% improvement. The hybrid model facilitates early cataract detection, aiding in preventing vision impairment. Integrated into applications, it supports ophthalmologists by providing rapid, cost-efficient predictions. Beyond cataract detection, this research addresses broader computer vision challenges, contributing to various applications. In conclusion, our proposed approach, combining CNNs and image quadration enhances cataract detection’s accuracy, robustness, and generalization. This innovation holds promise for improving patient care and aiding ophthalmologists in precise cataract diagnosis.