bluuebunny/crossref_metadata_2025 huggingface dataset:
Numerical Study of Bearing Strength of Infilled Concrete in Large Diameter CFST Column Reinforced by Shear Stoppers
Authors: Pham My , Dinh Ngoc-Hieu , Dang Cong-Thuat , Truong Hoai-Chinh
Published: January 2024

Ensuring an adequate bond between the steel tube and infilled concrete interface plays an essential role in achieving composite action for concrete-filled steel tubular (CFST) columns. Thus, this study proposes a new type of large diameter CFST column where the steel tube is reinforced by shear stoppers. The bearing strength of the infilled concrete is the decisive factor in evaluating the overall working efficiency between infilled concrete and steel tube. In this paper, we use nonlinear finite element analysis (NFEA) to investigate the bearing strength of the infilled concrete concerning the ratio of the steel tube’s diameter to its thickness (D/t), the number of shear stoppers N, the height of the shear stopper hb, and the concrete compressive strength (CCS) fc′. Our results show that the influencing factors on the bearing strength of the infilled concrete were arranged in descending order as follows: the number of shear stoppers, the height of shear stopper, the CCS, and the D/t ratio. We also analyze and highlight some significant parameters related to the bearing strength of infilled concrete.
Accurate Intervertebral Disc Segmentation Approach Based on Deep Learning
Authors: Cheng Yu-Kai , Lin Chih-Lung , Huang Yi-Chi , Lin Guo-Shiang , Lian Zhen-You , Chuang Cheng-Hung
Published: January 2024

Automatically segmenting specific tissues or structures from medical images is a straightforward task for deep learning models. However, identifying a few specific objects from a group of similar targets can be a challenging task. This study focuses on the segmentation of certain specific intervertebral discs from lateral spine images acquired from an MRI scanner. In this research, an approach is proposed that utilizes MultiResUNet models and employs saliency maps for target intervertebral disc segmentation. First, a sub-image cropping method is used to separate the target discs. This method uses MultiResUNet to predict the saliency maps of target discs and crop sub-images for easier segmentation. Then, MultiResUNet is used to segment the target discs in these sub-images. The distance maps of the segmented discs are then calculated and combined with their original image for data augmentation to predict the remaining target discs. The training set and test set use 2674 and 308 MRI images, respectively. Experimental results demonstrate that the proposed method significantly enhances segmentation accuracy to about 98%. The performance of this approach highlights its effectiveness in segmenting specific intervertebral discs from closely similar discs.
Increased Risk of Coronary Artery Disease in People with Diagnosis of Neuromuscular Disorders: A Nationwide Retrospective Population-Based Case–Control Study
Authors: Chang Yi-Chuan , Lay Ing-Shiow , Tu Cheng-Hao , Lee Yu-Chen
Published: January 2024

The existing literature has explored carpal tunnel syndrome (CTS) and determined that it could be a risk for coronary artery disease (CAD), but there has been little research comparing the relevance of CAD with other neuromuscular disorders (NMDs) to CTS. This case–control study explored the association between CTS, stenosing tenosynovitis (ST), and ulnar side NMDs and CAD. The study utilized data from Taiwan’s National Health Insurance Research Database, focusing on health insurance claims. Between January 2000 and December 2011, we employed the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) diagnostic codes to identify 64,025 CAD patients as the case group. The control group consisted of an equal number of individuals without CAD, matched for age, sex, and index year of CAD. Logistic regression analysis was employed to calculate the odds ratios (ORs) and 95% confidence intervals (CIs) for each variable. Multivariate analysis, after adjusting for sociodemographic factors and comorbidities, revealed a significantly higher likelihood of a previous diagnosis of CTS in the CAD group compared to the comparison control group. However, neither ST nor the ulnar side NMDs had any statistical significance. These results indicated that median nerve injury, rather than other NMDs, may uniquely serve as a predisposing factor of CAD.
Filtering and Detection of Real-Time Spam Mail Based on a Bayesian Approach in University Networks
Authors: Sharabov Maksim , Tsochev Georgi , Gancheva Veska , Tasheva Antoniya
Published: January 2024

With the advent of digital technologies as an integral part of today’s everyday life, the risk of information security breaches is increasing. Email spam, commonly known as junk email, continues to pose a significant challenge in the digital realm, inundating inboxes with unsolicited and often irrelevant messages. This relentless influx of spam not only disrupts user productivity but also raises security concerns, as it frequently serves as a vehicle for phishing attempts, malware distribution, and other cyber threats. The prevalence of spam is fueled by its low-cost dissemination and its ability to reach a wide audience, exploiting vulnerabilities in email systems. This paper marks the inception of an in-depth investigation into the viability and potential implementation of a robust spam filtering and prevention system tailored explicitly to university networks. With the escalating threat of email-based hacking attacks and the incessant deluge of spam, the need for a comprehensive and effective defense mechanism within academic institutions becomes increasingly imperative. In exploring potential solutions, this study delves into the applicability and efficacy of Bayesian filters, a class of probabilistic classifiers renowned for their aptitude in distinguishing between legitimate emails and spam messages. Bayesian filters utilize statistical algorithms to analyze email content, learning patterns and features to accurately categorize incoming emails.
Research on Power Device Fault Prediction of Rod Control Power Cabinet Based on Improved Dung Beetle Optimization–Temporal Convolutional Network Transfer Learning Model
Authors: Ye Liqi , Chen Zhi , Liu Jie , Lin Chao , Jian Yifan
Published: January 2024

In order to improve the reliability and maintainability of rod control power cabinets in nuclear power plants, this paper uses insulated gate bipolar transistors (IGBTs), the key power device of rod control power cabinets, as the object of research on cross-working-condition fault prediction. An improved transfer learning (TL) model based on a temporal convolutional network (TCN) is proposed to solve the problem of low fault prediction accuracy across operating conditions. First, the peak emitter voltage of an IGBT aging dataset is selected as the source domain failure characteristic, and the TCN model is trained after the removal of outliers and noise reduction. Then, the time–frequency features are extracted according to the characteristics of the target domain data, and the target domain representation data are obtained using kernel principal component analysis (KPCA) for dimensionality reduction. Finally, the TCN model trained on the source domain is transferred; the model is fine-tuned according to the target domain data, and the learning rate, the number of hidden layer nodes, and the number of training times in the network model are optimized using the dung beetle optimization (DBO) algorithm to obtain the optimal network, making it more suitable for target sample fault prediction. The prediction results of this TCN model, the long short-term memory (LSTM) model, the gated recurrent unit (GRU) model, and the recursive neural network (RNN) model are compared and analyzed by selecting prediction performance evaluation indexes. The results show that the TCN model has a better predictive effect. Comparing the prediction results of the TCN-based optimized transfer learning model with those of the directly trained TCN model, the mean square error, root mean square error, and mean absolute error are reduced by a factor of two to three, which provides an effective solution for fault prediction across operating conditions.
Progress in Achieving Fire-Retarding Cellulose-Derived Nano/Micromaterial-Based Thin Films/Coatings and Aerogels: A Review
Authors: Turku Irina , Rohumaa Anti , Tirri Tapio , Pulkkinen Lasse
Published: January 2024

The enormous potential of renewable bioresources is expected to play a key role in the development of the EU’s sustainable circular economy. In this context, inexhaustible, biodegradable, non-toxic, and carbon-neutral forest-origin resources are very attractive for the development of novel sustainable products. The main structural component of wood is cellulose, which, in turn, is the feedstock of nanocellulose, one of the most explored nanomaterials. Different applications of nanocellulose have been proposed, including packaging, functional coatings, insulating materials, nanocomposites and nanohybrids manufacturing, among others. However, the intrinsic flammability of nanocellulose restricts its use in some areas where fire risk is a concern. This paper overviews the most recent studies of the fire resistance of nanocellulose-based materials, focusing on thin films, coatings, and aerogels. Along with effectiveness, increased attention to sustainable approaches is considered in developing novel fire-resistant coatings. The great potential of bio-based fire-resistant materials, combined with conventional non-halogenated fire retardants (FRs), has been established. The formulation methods, types of FRs and their action modes, and methods used for analysing fireproof are discussed in the frame of this overview.
Study on the Frying Performance Evaluation of Refined Soybean Oil after PLC Enzymatic Degumming
Authors: Zhou Wenting , Peng Yuxin , Wu Zongyuan , Zhang Weinong , Cong Yanxia
Published: January 2024

It is known that phospholipase C (PLC) enzymatic degumming can hydrolyze phospholipids into diacylglycerol (DAG), which improves the efficiency of oil processing. However, it is unclear whether the presence of DAG and the use of enzymes affect the performance of the oil. This paper evaluated the frying performance of PLC-degummed refined soybean oil. Following the chicken wings and potato chips frying trials, results revealed that after 30 cycles of frying, free fatty acid (FFA) levels were 0.22% and 0.21%, with total polar compounds (TPC) at 23.75% and 24.00%, and peroxide value (PV) levels were 5.90 meq/kg and 6.45 meq/kg, respectively. Overall, PLC-degummed refined soybean oil showed almost the same frying properties as traditional water-degummed refined oil in terms of FFA, PV, TPC, polymer content, viscosity, color, foaming of frying oils, and appearance of foods. Moreover, FFA, TPC, polymer content, foaming, and color showed significant positive correlations with each other (p < 0.05) in soybean oil intermittent frying processing.
Fractal Analysis of the Centrifuge Vibrograms
Authors: Lavrenko Iaroslav , Popov Anton , Seleznov Ivan , Kiyono Ken
Published: January 2024

This paper presents a new approach to analyzing the components of centrifuge rotor vibrograms using a 2D trajectory fractal analysis based on the Detrended Moving Average method. The method identifies the different noise oscillatory behavior of the rotor depending on the rotation frequencies, ranging from non-stationary unbounded and 1/f pink noise to correlated and uncorrelated noise. Fractal characteristics of the vibrograms were computed for the first time and demonstrated differences for rotation frequencies close to the eigenfrequencies and far from them. This paper also discusses the influence of gyroscopic effects on the natural frequencies of centrifuge oscillations and the excitation of second harmonics when the centrifuge rotates at higher frequencies. The main cause of rotor vibration is identified as the mass imbalance of the rotors, and this paper proposes a vibration classification according to source nodes to diagnose serviceable and faulty technical systems. Finally, the possibility of anisotropy of the vibrogram is discussed, and the oriented fractal scaling components analysis method is applied to pave the way for further investigation.
Slack Is Needed to Solve the Shortage of Nurses
Authors: Van Merode Frits , Groot Wim , Somers Melline
Published: January 2024

Healthcare systems are facing a shortage of nurses. This article identifies some of the major causes of this and the issues that need to be solved. We take a perspective derived from queuing theory: the patient–nurse relationship is characterized by a scarcity of time and resources, requiring comprehensive coordination at all levels. For coordination, we take an information-theoretic perspective. Using both perspectives, we analyze the nature of healthcare services and show that ensuring slack, meaning a less than exhaustive use of human resources, is a sine qua non to having a good, functioning healthcare system. We analyze what coordination efforts are needed to manage relatively simple office hours, wards, and home care. Next, we address the level of care where providers cannot themselves prevent the complexity of organization that possibly damages care tasks and job quality. A lack of job quality may result in nurses leaving the profession. Job quality, in this context, depends on the ability of nurses to coordinate their activities. This requires slack resources. The availability of slack that is efficient depends on a stable inflow and retention rate of nurses. The healthcare system as a whole should ensure that the required nurse workforce will be able to coordinate and execute their tasks. Above that, workforce policies need more stability.
Missed Nursing Care; Prioritizing the Patient’s Needs: An Umbrella Review
Authors: Papathanasiou Iokasti , Tzenetidis Vasileios , Tsaras Konstantinos , Zyga Sofia , Malliarou Maria
Published: January 2024

The objective of this review of reviews was to identify the reasons for missed nursing care and to shed light on how nurses prioritize what care they miss. Missed nursing care refers to essential nursing activities or tasks that are omitted or not completed as planned during a patient’s care. This omission can result from various factors, such as staffing shortages, time constraints, or communication issues, and it can potentially compromise the quality of patient care and safety. Identifying and addressing missed nursing care is crucial to ensure optimal patient outcomes and the well-being of healthcare professionals. To be included, reviews had to use the systematic review process, be available in the English language, examine missed care in hospitals and at home, and include participants who were over eighteen years old. The review intended to answer the following questions: ‘Why nursing care is missed?’ ‘How nurses prioritize what care they missed?’. An umbrella review was developed guided by the JBI methodology and using PRISMA-ScR. A total of 995 reviews were identified. According to the inclusion criteria, only nine reviews were finally evaluated. The findings indicate that care is missed due to staffing levels, organizational problems, and the working climate. Prioritization of care depends on acute care needs as well as educational and experiential background. Missed nursing care is associated with patient safety and the quality of provided nursing care. Specifically, it has negative impacts on patients, healthcare professionals, and healthcare service units. Organizational characteristics, nursing unit features, and the level of teamwork among nursing staff affect Missed Nursing Care. Individual demographic characteristics of the staff, professional roles, work schedules, and adequate staffing may potentially contribute to the occurrence of Missed Nursing Care, which is why they are under investigation. However, further consideration is needed regarding the management of patient needs and nurse prioritization.
Climbing the Ranks: A Study of Firefighter Health Disparities
Authors: Hare McKenzie M. , Wohlgemuth Kealey J. , Jesko Alex , Conner Michael J. , Frost-Piedrahita Vanessa , Mota Jacob A.
Published: January 2024

The fire service command structure encompasses recruit, incumbent firefighter, and officer positions. The purpose of this study was to quantify the effect of rank (recruits, incumbent firefighters, and officers) on health and physical ability characteristics within the fire service. Retrospective data from thirty-seven recruits (age = 29 ± 5 yrs, BMI = 26.5 ± 2.3 kg/m2); eighty-two incumbent firefighters (age = 30 ± 7 yrs, BMI = 28.8 ± 4.3 kg/m2); and forty-one officers (age = 41 ± 6 yrs, BMI = 28.6 ± 4.3 kg/m2) from a single department were used. Participants completed body composition tests (i.e., body fat percentage [%BF] and body mass index [BMI]), an air consumption test (ACT), and cardiopulmonary exercise testing. The ACT consisted of 10 standardized tasks. Five separate one-way analyses of co-variance (ANCOVA) were calculated, accounting for age. Partial eta squared statistics were calculated and Bonferroni-corrected post-hoc analyses were employed. The results demonstrated a significant effect of rank on %BF (F = 9.61, p < 0.001, η2 = 0.10); BMI (F = 3.45, p = 0.02, η2 = 0.05); relative VO2MAX (F = 12.52, p < 0.001; η2 = 0.11); and HRMAX (F = 18.89, p < 0.001, η2 = 0.03), but not on ACT time (F = 0.71, p = 0.55, η2 = 0.01). These outcomes suggest there are variations in anthropometric and physiological metrics of health across firefighter ranks. Administrators should be aware how these markers of health may vary across firefighter ranks.
Identification of the Loci Associated with Resistance to Banana Xanthomonas Wilt (Xanthomonas vasicola pv. musacearum) Using DArTSeq Markers and Continuous Mapping
Authors: Uwimana Brigitte , Nakato Gloria Valentine , Kanaabi Reagan , Nasuuna Catherine , Mwanje Gerald , Mahuku George Simba , Akech Violet , Vuylsteke Marnik , Swennen Rony , Shah Trushar
Published: January 2024

Banana Xanthomonas wilt, caused by Xanthomonas vasicola pv. musacearum (Xvm), is a devastating disease that results in total yield loss of affected plants. Resistance to the disease is limited in Musa acuminata, but it has been identified so far in the zebrina subspecies. This study identified markers associated with tolerance to Xvm in Monyet, a tetraploid banana from the zebrina subspecies which was identified to be partially resistant to the bacterium. We used a triploid progeny of 135 F1 hybrids resulting from a cross between Monyet (Xvm partially resistant) and Kokopo (diploid and Xvm susceptible). The F1 hybrids were screened in pots for resistance to Xvm. The population was genotyped using the genotyping-by-sequencing platform of Diversity Array Technology (DArTSeq). The adjusted means of the phenotypic data were combined with the allele frequencies of the genotypic data in continuous mapping. We identified 25 SNPs associated with resistance to Xvm, and these were grouped into five quantitative traits loci (QTL) on chromosomes 2, 3, 6, and 7. For each marker, we identified the favorable allele and the additive effect of replacing the reference allele with the alternative allele. The comparison between weevil borer (Cosmopolites sordidus (Germar)) and Xvm QTL revealed one QTL shared between the two biotic stresses at the distal end of chromosome 6 but with a repulsion linkage. This linkage should be broken down by generating more recombinants in the region. We also identified 18 putative alleles in the vicinity of the SNPs associated with resistance to Xvm. Among the 18 putative genes, two particularly putative genes, namely, Ma06_g13550 and Ma06_g36840, are most likely linked to disease resistance. This study is a basis for marker-assisted selection to improve banana resistance to banana Xanthomonas wilt, especially in East and Central Africa where the disease is still devastating the crop.
Anchoring of Copper(II)–Schiff Base Complex in SBA-15 Matrix as Efficient Oxidation and Biomimetic Catalyst
Authors: Mureseanu Mihaela , Bleotu Irina , Spînu Cezar-Ionuț , Cioatera Nicoleta
Published: January 2024

A new mononuclear Cu(II) complex [Cu(L2)(H2O)2], where L is the Schiff base 2-[2-(3-bromopropoxy)benzylideneamino] benzoic acid, was synthesized and covalently anchored onto an amino-functionalized SBA-15 mesoporous silica in order to obtain an efficient heterogeneous catalyst. The elemental, structural, textural and morphological characterization confirmed the coordination of the central Cu(II) ion with two ligands and two H2O molecules in the synthesized complex and its successful immobilization into the inner pore surface of the NH2-functionalized support without the loss of the mesoporous structure. The catalytic activity of the free or immobilized Cu(II) complex was tested in the oxidation of cyclohexene with H2O2 under an air atmosphere and the dismutation reaction of the superoxide radical anions with very good results. In addition, catalyst reuse tests claim its suitability in alkene oxidation processes or as a biomimetic catalyst.
Deciphering Interactions Involved in Immobilized Metal Ion Affinity Chromatography and Surface Plasmon Resonance for Validating the Analogy between Both Technologies
Authors: Irankunda Rachel , Camaño Echavarría Jairo Andrés , Paris Cédric , Selmeczi Katalin , Stefan Loïc , Boschi-Muller Sandrine , Muhr Laurence , Canabady-Rochelle Laetitia
Published: January 2024

Various peptides can be obtained through protein enzymatic hydrolysis. Immobilized metal ion affinity chromatography (IMAC) is one of the methods which can be used to separate metal chelating peptides (MCPs) in a hydrolysate mixture. In this context, this work aims to understand deeply the interactions in IMAC and surface plasmon resonance (SPR) in order to validate experimentally the analogy between both technologies and to be further able to perform IMAC modeling in the next work using peptide sorption isotherm parameters obtained from SPR. Indeed, chromatography modeling can be used to predict separation of MCPs in IMAC and the knowledge of peptide sorption isotherm obtained from SPR is a crucial step. For this purpose, 22 peptides were selected and investigated in IMAC using HisTrap X-Ni2+ and HiFliQ NTA-Ni2+ columns and were also studied in SPR as well. Results showed that peptides with histidine residues had good affinity to Ni2+, while the high positive charge of peptides was responsible of ionic interactions. Further, most of the peptides with good retention time in IMAC showed a good affinity in SPR as well, which validated experimentally the SPR-IMAC analogy.
The African Psyllid Trioza erytreae Del Guercio (1918) Is Very Sensitive to Low Relative Humidity and High Temperatures
Authors: Pérez-Otero Rosa , Pérez-Turco Raquel , Neto Joana , Fereres Alberto
Published: January 2024

The African citrus psyllid, Trioza erytreae, is one of the two vectors of Huanglongbing, the most serious citrus disease worldwide. The first detection of T. erytreae in the European mainland was on the northwest of the Iberian Peninsula in 2014. Since then, the pest has spread throughout northern Spain (Galicia, Asturias, Cantabria, País Vasco) and along the western Atlantic coast of Portugal (from the Douro e Minho region to the Algarve). We conducted a series of laboratory experiments on lemon plants at different temperatures (from 8 to 34 °C) and humidity conditions (from 40 to 90%) to find out the influence of extreme temperatures and relative humidities (RHs) on the mortality, development and reproduction of T. erytreae. Our results show that temperatures above 30 °C and below 10 °C are very detrimental for nymphal development and nymphs were unable to reach the adult stage. Furthermore, eggs were unable to hatch under temperatures above 33 °C and below 8 °C. Adult mortality was highest at 34 °C and killed more than 50% of the population. We also found that relative humidity is crucial for the development and survival of T. erytreae. Nymphs were unable to reach the adult stage at an RH of 90% and 40%. Also, fecundity was significantly reduced at 90 and 40% RH, and fertility was lowest at 40% RH. Nymphal mortality was highest at an RH of 40%, which was the most detrimental humidity among all tested for the survival and development of T. erytreae. Our work concludes that T. erytreae establishment and spread will be maximum in regions with a temperate and humid climate, being rare in regions where dry and hot weather conditions predominate.
Is the Ventilatory Efficiency in Endurance Athletes Different?—Findings from the NOODLE Study
Authors: Kasiak Przemysław , Kowalski Tomasz , Rębiś Kinga , Klusiewicz Andrzej , Ładyga Maria , Sadowska Dorota , Wilk Adrian , Wiecha Szczepan , Barylski Marcin , Poliwczak Adam Rafał , Wierzbiński Piotr , Mamcarz Artur , Śliż Daniel
Published: January 2024

Background: Ventilatory efficiency (VE/VCO2) is a strong predictor of cardiovascular diseases and defines individuals’ responses to exercise. Its characteristics among endurance athletes (EA) remain understudied. In a cohort of EA, we aimed to (1) investigate the relationship between different methods of calculation of VE/VCO2 and (2) externally validate prediction equations for VE/VCO2. Methods: In total, 140 EA (55% males; age = 22.7 ± 4.6 yrs; BMI = 22.6 ± 1.7 kg·m−2; peak oxygen uptake = 3.86 ± 0.82 L·min−1) underwent an effort-limited cycling cardiopulmonary exercise test. VE/VCO2 was first calculated to ventilatory threshold (VE/VCO2-slope), as the lowest 30-s average (VE/VCO2-Nadir) and from whole exercises (VE/VCO2-Total). Twelve prediction equations for VE/VCO2-slope were externally validated. Results: VE/VCO2-slope was higher in females than males (27.7 ± 2.6 vs. 26.1 ± 2.0, p < 0.001). Measuring methods for VE/VCO2 differed significantly in males and females. VE/VCO2 increased in EA with age independently from its type or sex (β = 0.066–0.127). Eleven equations underestimated VE/VCO2-slope (from −0.5 to −3.6). One equation overestimated VE/VCO2-slope (+0.2). Predicted and observed measurements differed significantly in nine models. Models explained a low amount of variance in the VE/VCO2-slope (R2 = 0.003–0.031). Conclusions: VE/VCO2-slope, VE/VCO2-Nadir, and VE/VCO2-Total were significantly different in EA. Prediction equations for the VE/VCO2-slope were inaccurate in EA. Physicians should be acknowledged to properly assess cardiorespiratory fitness in EA.
A Review of Intraocular Lens Power Calculation Formulas Based on Artificial Intelligence
Authors: Stopyra Wiktor , Cooke David L. , Grzybowski Andrzej
Published: January 2024

Purpose: The proper selection of an intraocular lens power calculation formula is an essential aspect of cataract surgery. This study evaluated the accuracy of artificial intelligence-based formulas. Design: Systematic review. Methods: This review comprises articles evaluating the exactness of artificial intelligence-based formulas published from 2017 to July 2023. The papers were identified by a literature search of various databases (Pubmed/MEDLINE, Google Scholar, Crossref, Cochrane Library, Web of Science, and SciELO) using the terms “IOL formulas”, “FullMonte”, “Ladas”, “Hill-RBF”, “PEARL-DGS”, “Kane”, “Karmona”, “Hoffer QST”, and “Nallasamy”. In total, 25 peer-reviewed articles in English with the maximum sample and the largest number of compared formulas were examined. Results: The scores of the mean absolute error and percentage of patients within ±0.5 D and ±1.0 D were used to estimate the exactness of the formulas. In most studies the Kane formula obtained the smallest mean absolute error and the highest percentage of patients within ±0.5 D and ±1.0 D. Second place was typically achieved by the PEARL DGS formula. The limitations of the studies were also discussed. Conclusions: Kane seems to be the most accurate artificial intelligence-based formula. PEARL DGS also gives very good results. Hoffer QST, Karmona, and Nallasamy are the newest, and need further evaluation.
Case Series: Vestibular Migraines in Fragile X Premutation Carriers
Authors: Tak YeEun , Tassone Flora , Hagerman Randi J.
Published: January 2024

Background: Vestibular migraine (VM) is one of the most common causes of recurrent vertigo and presents with a history of spontaneous or positional vertigo with a history of migraine headaches. While research has identified a high prevalence of migraine headaches and vestibular deficits among fragile X premutation carriers, there has been no discussion about VM within this population. Objective: This case series and review seeks to describe the clinical characteristics and pathophysiology of VM among individuals with the fragile X premutation. We also seek to discuss treatment and future steps in addressing VM in this population. Methods: A review of the literature regarding vestibular migraine and presentation of migraine headaches and vestibular deficits among premutation carriers was performed. A detailed clinical history of migraine headaches and vertigo was obtained from three patients with the fragile X premutation seen by the senior author (RJH). Results: All three cases first developed symptoms of migraine headaches earlier in life, with the development of VM near menopause. Two of the three cases developed progressive balance issues following the development of VM. All three cases found that their VM episodes were improved or resolved with pharmacological and/or lifestyle interventions. Conclusions: It is important to recognize VM among premutation carriers because beneficial treatments are available. Future studies are needed regarding the prevalence of VM and the relationship to subsequent FXTAS. The pathophysiology of VM remains uncertain but possibilities include mitochondrial abnormalities, cranial nerve VIII toxicity secondary to neurotoxic protein accumulation, and calcitonin gene-related peptide (CGRP) signaling dysfunction due to altered levels of fragile X messenger ribonucleoprotein (FMRP).
Navigating the Labyrinth: Intensive Care Challenges for Patients with Acute-on-Chronic Liver Failure
Authors: Saner Fuat H. , Raptis Dimitri A. , Alghamdi Saad A. , Malagó Massimo M. , Broering Dieter C. , Bezinover Dmitri
Published: January 2024

Acute-on-chronic liver failure (ACLF) refers to the deterioration of liver function in individuals who already have chronic liver disease. In the setting of ACLF, liver damage leads to the failure of other organs and is associated with increased short-term mortality. Optimal medical management of patients with ACLF requires implementing complex treatment strategies, often in an intensive care unit (ICU). Failure of organs other than the liver distinguishes ACLF from other critical illnesses. Although there is growing evidence supporting the current approach to ACLF management, the mortality associated with this condition remains unacceptably high. In this review, we discuss considerations for ICU care of patients with ACLF and highlight areas for further research.
Fully Self-Supervised Out-of-Domain Few-Shot Learning with Masked Autoencoders
Authors: Walsh Reece , Osman Islam , Abdelaziz Omar , Shehata Mohamed S.
Published: January 2024

Few-shot learning aims to identify unseen classes with limited labelled data. Recent few-shot learning techniques have shown success in generalizing to unseen classes; however, the performance of these techniques has also been shown to degrade when tested on an out-of-domain setting. Previous work, additionally, has also demonstrated increasing reliance on supervised finetuning in an off-line or online capacity. This paper proposes a novel, fully self-supervised few-shot learning technique (FSS) that utilizes a vision transformer and masked autoencoder. The proposed technique can generalize to out-of-domain classes by finetuning the model in a fully self-supervised method for each episode. We evaluate the proposed technique using three datasets (all out-of-domain). As such, our results show that FSS has an accuracy gain of 1.05%, 0.12%, and 1.28% on the ISIC, EuroSat, and BCCD datasets, respectively, without the use of supervised training.
Prediction of Beach Sand Particle Size Based on Artificial Intelligence Technology Using Low-Altitude Drone Images
Authors: Yoo Ho-Jun , Kim Hyoseob , Kang Tae-Soon , Kim Ki-Hyun , Bang Ki-Young , Kim Jong-Beom , Park Moon-Sang
Published: January 2024

Coastal erosion is caused by various factors, such as harbor development along coastal areas and climate change. Erosion has been accelerated recently due to sea level rises, increased occurrence of swells, and higher-power storm waves. Proper understanding of the complex coastal erosion process is vital to prepare measures when they are needed. Monitoring systems have been widely established around a high portion of the Korean coastline, supported by several levels of governments, but valid analysis of the collected data and the following preparation of measures have not been highly effective yet. In this paper, we use a drone to obtain bed material images, and an analysis system to predict the representative grain size of beach sands from the images based on artificial intelligence (AI) analysis. The predicted grain sizes are verified via field samplings. Field bed material samples for the particle size analysis are collected during two seasons, while a drone takes photo images and the exact positions are simultaneously measured at Jangsa beach, Republic of Korea. The learning and testing results of the AI technology are considered satisfactory. Finally, they are used to diagnose the overall stability of Jangsa beach. A beach diagnostic grade is proposed here, which reflects the topography of a beach and the distribution of sediments on the beach. The developed beach diagnostic grade could be used as an indicator of any beach stability on the east coast of the Republic of Korea. When the diagnostic grade changes rapidly at a beach, it is required to undergo thorough investigation to understand the reason and foresee the future of the beach conditions, if we want the beach to function as well as before.
Late Prevalence of Typical and Atypical Symptoms of Frey’s Syndrome after Parotidectomy for Benign Tumor
Authors: Marchese Maria Raffaella , Rossi Federica , Settimi Stefano , Galli Jacopo
Published: January 2024

Background: The treatment of choice for tumors located in the parotid gland is surgery. Nevertheless, postoperative complications are not infrequent. Regardless of the type of surgical procedure, the most common complication is Frey’s syndrome (FS). Traditionally, FS includes unilateral gustatory sweating and flushing of the facial skin lining the parotid compartment. Recent research describes atypical discomfort associated with FS. The aim of this study was to assess the late prevalence and severity of both usual and atypical symptoms after parotidectomy for benign tumors. Methods: We conducted a cross-sectional study involving 86 subjects who underwent superficial parotidectomy at least one year before the study. The questionnaire included the sweating–flushing–itch–paresthesia–pain (SFIPP) Frey scale supplemented by specific questions about symptoms. Results: Sixty-seven out of eighty-six (77.9%) cases reported almost one symptom. The most frequent symptom was itch (36/67—53.7%), followed by pain (35/67—52.2%), while 28/67 (41.8%) subjects complained of atypical symptoms without flushing or sweating. A desire to treat the discomfort was reported by 50/67 (74.6%) subjects. Conclusions: Late postparotidectomy local discomfort is not infrequent and includes both usual and “unusual” symptoms almost equally. Our results suggest the importance of informing patients about the occurrence of the syndrome and the available treatment options during pre- and postoperative counseling.
Abdominal Wall Hernias—State of the Art of Laparoscopic versus Robotic Surgery
Authors: Anoldo Pietro , Manigrasso Michele , D’Amore Anna , Musella Mario , De Palma Giovanni Domenico , Milone Marco
Published: January 2024

Abdominal wall hernia repair, a common surgical procedure, includes various techniques to minimize postoperative complications and enhance outcomes. This review focuses on the comparison between laparoscopic and robotic approaches in treating inguinal and ventral hernias, presenting the ongoing situation of this topic. A systematic search identified relevant studies comparing laparoscopic and robotic approaches for inguinal and ventral hernias. Randomized control trials, retrospective, and prospective studies published after 1 January 2000, were included. Search terms such as hernia, inguinal, ventral, laparoscopy, robotic, and surgery were used. A total of 23 articles were included for analysis. Results indicated similar short-term outcomes for robotic and laparoscopic techniques in inguinal hernia repair, with robotic groups experiencing less postoperative pain. However, longer operative times and higher costs were associated with robotic repair. Robotic ventral hernia repair demonstrated potential benefits, including shorter hospital stay, lower recurrence and lower reoperation rates. While robotic surgery offers advantages such as shorter hospital stays, faster recovery, and less postoperative pain, challenges including costs and training requirements need consideration. The choice between laparoscopic and robotic approaches for abdominal wall hernias should be tailored based on individual surgeon expertise and resource availability, emphasizing a balanced evaluation of benefits and challenges.
A Multi-Objective Trajectory Planning Method of the Dual-Arm Robot for Cabin Docking Based on the Modified Cuckoo Search Algorithm
Authors: Liu Ronghua , Pan Feng
Published: January 2024

During the assembly of mechanical systems, the dual-arm robot is always used for cabin docking. In order to ensure the accuracy and reliability of cabin docking, a multi-objective trajectory planning method for the dual-arm robot was proposed. A kinematic model of the dual-arm robot was constructed based on the Denavit–Hartenberg (D-H) method firstly. Then, in the Cartesian space, the end trajectory of the dual-arm robot was confirmed by the fifth-order B-spline curve. On the basis of a traditional multi-objective cuckoo search algorithm, a modified cuckoo algorithm was built using the improved initial population generation method and the step size. The total consumption time and joint impact were selected as the objective functions, the overall optimal solution for the modified cuckoo algorithm was obtained using the normalized evaluation method. The optimal trajectory planning was achieved. Finally, the feasibility and effectiveness of the trajectory planning method were verified with the experiments.
GAN-Based Tabular Data Generator for Constructing Synopsis in Approximate Query Processing: Challenges and Solutions
Authors: Fallahian Mohammadali , Dorodchi Mohsen , Kreth Kyle
Published: January 2024

In data-driven systems, data exploration is imperative for making real-time decisions. However, big data are stored in massive databases that are difficult to retrieve. Approximate Query Processing (AQP) is a technique for providing approximate answers to aggregate queries based on a summary of the data (synopsis) that closely replicates the behavior of the actual data; this can be useful when an approximate answer to queries is acceptable in a fraction of the real execution time. This study explores the novel utilization of a Generative Adversarial Network (GAN) for the generation of tabular data that can be employed in AQP for synopsis construction. We thoroughly investigate the unique challenges posed by the synopsis construction process, including maintaining data distribution characteristics, handling bounded continuous and categorical data, and preserving semantic relationships, and we then introduce the advancement of tabular GAN architectures that overcome these challenges. Furthermore, we propose and validate a suite of statistical metrics tailored for assessing the reliability of GAN-generated synopses. Our findings demonstrate that advanced GAN variations exhibit a promising capacity to generate high-fidelity synopses, potentially transforming the efficiency and effectiveness of AQP in data-driven systems.
On Completeness and Fixed Point Theorems in Fuzzy Metric Spaces
Authors: Gregori Valentín , Miñana Juan-José , Roig Bernardino , Sapena Almanzor
Published: January 2024

This paper is devoted to showing the relevance of the notion of completeness used to establish a fixed point theorem in fuzzy metric spaces introduced by Kramosil and Michalek. Specifically, we show that demanding a stronger notion of completeness, called p-completeness, it is possible to relax some extra conditions on the space to obtain a fixed point theorem in this framework. To this end, we focus on a fixed point result, proved by Mihet for complete non-Archimedean fuzzy metric spaces (Theorem 1). So, we define a weaker concept than the non-Archimedean fuzzy metric, called t-strong, and we establish an alternative version of Miheţ’s theorem for p-complete t-strong fuzzy metrics (Theorem 2). In addition, an example of t-strong fuzzy metric spaces that are not non-Archimedean is provided.
Comparison of Statistical Approaches for Reconstructing Random Coefficients in the Problem of Stochastic Modeling of Air–Sea Heat Flux Increments
Authors: Belyaev Konstantin P. , Gorshenin Andrey K. , Korolev Victor Yu. , Osipova Anastasiia A.
Published: January 2024

This paper compares two statistical methods for parameter reconstruction (random drift and diffusion coefficients of the Itô stochastic differential equation, SDE) in the problem of stochastic modeling of air–sea heat flux increment evolution. The first method relates to a nonparametric estimation of the transition probabilities (wherein consistency is proven). The second approach is a semiparametric reconstruction based on the approximation of the SDE solution (in terms of distributions) by finite normal mixtures using the maximum likelihood estimates of the unknown parameters. This approach does not require any additional assumptions for the coefficients, with the exception of those guaranteeing the existence of the solution to the SDE itself. It is demonstrated that the corresponding conditions hold for the analyzed data. The comparison is carried out on the simulated samples, modeling the case where the SDE random coefficients are represented in trigonometric form, which is related to common climatic models, as well as on the ERA5 reanalysis data of the sensible and latent heat fluxes in the North Atlantic for 1979–2022. It is shown that the results of these two methods are close to each other in a quantitative sense, but differ somewhat in temporal variability and spatial localization. The differences during the observed period are analyzed, and their geophysical interpretations are presented. The semiparametric approach seems promising for physics-informed machine learning models.
Factors Influencing the Duration of Rehabilitation in Infants with Torticollis—A Pilot Study
Authors: Parau Daniela , Todoran Anamaria Butila , Balasa Rodica
Published: January 2024

Background and Objectives: Torticollis is a common pediatric condition, with an incidence of 0.3–2.0%. Studies show that an adequate, tailored, and early treatment helps 90% to 95% of children recover before the first year of life and 97% of patients recover if treatment starts before the first six months. To identify the relationships between variables considered essential in the recovery process of infants with torticollis, we included factors such as the type of torticollis, age at onset of treatment, gender, birth weight, mode of delivery, fetal position in the uterus, the presence of craniofacial deformities, regions affected by postural asymmetries, and duration of the rehabilitation program. The hypothesis of the study is that early initiation of therapy can contribute to achieving favorable outcomes in the recovery process. Material and Methods: This retrospective cohort pilot study was conducted within a rehabilitation facility, spanning a duration of 1 year. The study involved a population of 41 children aged between 0 and 6 months. The rehabilitation program consisted of the application of Vojta therapy. Each session lasted 20 min, with a frequency of three times per week. Results: A total of 41% of those who started therapy in the first 3 months of life were fully recovered after 4–6 weeks of therapy. Of infants who started therapy at 5 and 6 months of age, 15% showed no improvement in measurements from 14 to 16 weeks of age, at which point the use of a cranial orthosis was recommended, and 23% experienced a plateau in measurements from 10 to 14 weeks, requiring the use of a cervical collar in conjunction with therapy. Conclusions: The findings from the study suggest that there may be a correlation between early initiation of therapy and favorable outcomes in the recovery process. The primary factors influencing the duration of recovery were identified as the presence of body asymmetries and the age at which therapy was initiated.
Association between Ranolazine, Ischemic Preconditioning, and Cardioprotection in Patients Undergoing Scheduled Percutaneous Coronary Intervention
Authors: Kourtis Konstantinos , Bourazana Angeliki , Xanthopoulos Andrew , Skoularigkis Spyridon , Papadakis Emmanouil , Patsilinakos Sotirios , Skoularigis John
Published: January 2024

Background and Objectives: Remote ischemic preconditioning (RIPC) has demonstrated efficacy in protecting against myocardial ischemia–reperfusion injury when applied before percutaneous coronary revascularization. Ranolazine, an anti-ischemic drug, has been utilized to minimize ischemic events in chronic angina patients. However, there is a lack of trials exploring the combined effects of ranolazine pretreatment and RIPC in patients undergoing percutaneous coronary interventions (PCIs). Materials and Methods: The present study is a prospective study which enrolled 150 patients scheduled for nonemergent percutaneous coronary revascularization. Three groups were formed: a control group undergoing only PCIs, an RIPC group with RIPC applied to either upper limb before the PCI (preconditioning group), and a group with RIPC before the PCI along with prior ranolazine treatment for stable angina (ranolazine group). Statistical analyses, including ANOVAs and Kruskal–Wallis tests, were conducted, with the Bonferroni correction for type I errors. A repeated-measures ANOVA assessed the changes in serum enzyme levels (SGOT, LDH, CRP, CPK, CK-MB, troponin I) over the follow-up. Statistical significance was set at p < 0.05. Results: The ranolazine group showed (A) significantly lower troponin I level increases compared to the control group for up to 24 h, (B) significantly lower CPK levels after 4, 10, and 24 h compared to the preconditioning group (p = 0.020, p = 0.020, and p = 0.019, respectively) and significantly lower CPK levels compared to the control group after 10 h (p = 0.050), and (C) significantly lower CK-MB levels after 10 h compared to the control group (p = 0.050). Conclusions: This study suggests that combining RIPC before scheduled coronary procedures with ranolazine pretreatment may be linked to reduced ischemia induction, as evidenced by lower myocardial enzyme levels.