bluuebunny/crossref_metadata_2025 huggingface dataset:
Optimization of Obstructive Sleep Apnea Management: Novel Decision Support via Unsupervised Machine Learning
Authors: de Araújo Costa Arthur Pinheiro , Terra Adilson Vilarinho , de Souza Rocha Junior Claudio , de Araújo Costa Igor Pinheiro , Moreira Miguel Ângelo Lellis , dos Santos Marcos , Gomes Carlos Francisco Simões , da Silva Antonio Sergio
Published: April 2024

This study addresses Obstructive Sleep Apnea (OSA), which impacts around 936 million adults globally. The research introduces a novel decision support method named Communalities on Ranking and Objective Weights Method (CROWM), which employs principal component analysis (PCA), unsupervised Machine Learning technique, and Multicriteria Decision Analysis (MCDA) to calculate performance criteria weights of Continuous Positive Airway Pressure (CPAP—key in managing OSA) and to evaluate these devices. Uniquely, the CROWM incorporates non-beneficial criteria in PCA and employs communalities to accurately represent the performance evaluation of alternatives within each resulting principal factor, allowing for a more accurate and robust analysis of alternatives and variables. This article aims to employ CROWM to evaluate CPAP for effectiveness in combating OSA, considering six performance criteria: resources, warranty, noise, weight, cost, and maintenance. Validated by established tests and sensitivity analysis against traditional methods, CROWM proves its consistency, efficiency, and superiority in decision-making support. This method is poised to influence assertive decision-making significantly, aiding healthcare professionals, researchers, and patients in selecting optimal CPAP solutions, thereby advancing patient care in an interdisciplinary research context.
Silkworm Hemolymph and Cocoon Metabolomics Reveals Valine Improves Feed Efficiency of Silkworm Artificial Diet
Authors: Wu Jinxin , Li Lingyi , Qin Daoyuan , Chen Han , Liu Yuanlin , Shen Guanwang , Zhao Ping
Published: April 2024

Artificial silkworm diets significantly impact farm profitability. Sustainable cocoon production depends on the continuous improvement of feed efficiency to reduce costs and nutrient losses in the feed. This study used metabolomics to explore the differences in silkworm cocoons and hemolymph under two modes of rearing: an artificial diet and a mulberry-leaf diet. Nine metabolites of silkworm cocoons and hemolymph in the mulberry-leaf group were higher than those in the artificial-diet group. Enrichment analysis of the KEGG pathways for these metabolites revealed that they were mainly enriched in the valine, leucine, and isoleucine biosynthesis and degradation pathways. Hence, the artificial silkworm diet was supplemented various concentrations of valine were supplemented to with the aim of examining the impact of valine on their feeding and digestion of the artificial diet. The results indicated that valine addition had no significant effect on feed digestibility in the fifth-instar silkworm. Food intake in the 2% and 4% valine groups was significantly lower than that in the 0% valine group. However, the 2% and 4% valine groups showed significantly improved cocoon-production efficiency, at 11.3% and 25.1% higher, respectively. However, the cocoon-layer-production efficiencies of the 2% and 4% valine groups decreased by 7.7% and 13.9%, respectively. The research confirmed that valine is an effective substance for enhancing the feed efficiency of silkworms.
A Novel Hybrid Ultrasound Abrasive-Driven Electrochemical Surface Finishing Technique for Additively Manufactured Ti6Al4V Parts
Authors: Sun Manyou , Toyserkani Ehsan
Published: April 2024

Poor surface quality is one of the drawbacks of metal parts made by additive manufacturing (AM)—they normally possess relatively high surface roughness and different types of surface irregularities. Post-processing operations are usually needed to reduce the surface roughness to have ready-to-use parts. Among all the surface treatment techniques, electrochemical polishing has the highest finishing efficiency and flexibility. However, although the average surface roughness can be reduced effectively (more than 80% roughness reduction), large-scale surface waviness still remains an issue when finishing metal AM parts. To maintain the finishing efficiency while reducing the surface waviness, a novel hybrid surface finishing technique is designed, which involves the combination of electropolishing, ultrasonic vibration, and abrasion. Preliminary experiments to prove the feasibility of novel hybrid finishing methods were conducted on Ti6Al4V coupons manufactured via laser powder bed fusion (LPBF). Electropolishing, a combination of ultrasound and abrasion, and hybrid finishing were conducted for process optimization and comparison purposes. The effects of the voltage, inter-electrode gap, temperature, ultrasonic amplitude, abrasive concentration, and processing time were studied and optimized. When similar optimal arithmetic mean height values (Sa ≈ 1 μm) are achieved for both processes, the arithmetic mean waviness values (Wa) obtained from hybrid finishing are much less than those from sole electropolishing after the same processing time, with the amount being 61.7% less after 30 min and 40.0% after 45 min.
Comparisons of Two Different Treatment Methods for Impacted Maxillary Canines: A Retrospective Study
Authors: Fekonja Anita
Published: April 2024

Background: The impaction of the maxillary canine is a common occurrence, and orthodontists must be prepared to manage it. The purpose of this article is to present a study of the efficacy of a double-wire orthodontic appliance compared to a control group in the alignment of impacted maxillary canines in the dental arch. Methods: To diagnose an impacted maxillary canine, a panoramic radiograph was taken and a detailed analysis was performed by the same orthodontist. This article presents the results of 28 impacted maxillary canines with inclusion criteria of A2 (tooth angulation to the midline 16°–45°), V1 (vertical height of the tooth crown above the cementoenamel junction but less than half the length of the root of the maxillary lateral incisor), and O3 (medial position of the canine crown of more than half but less than the entire root width of the lateral incisor) positions in 21 patients (7 males and 14 females) with a mean age of 14.02 years (SD = 1.61) who were treated by the same orthodontist for impacted maxillary canines using a fixed double-wire orthodontic appliance. The analyzed data were compared with the control group (treated with a fixed orthodontic appliance and active ligature), which was matched for pretreatment age and the A2, V1, and O3 positions of the impacted maxillary canine. Results: With both methods, the impacted maxillary canines were aligned and guided into a correct position in the dental arch, but the mean active orthodontic traction of 31 ± 4.2 weeks in the SG was statistically significantly shorter (p < 0.05) in comparison to 37 ± 6.3 weeks in the CG, and the number of visits was statistically significantly (p < 0.05) fewer in the SG (5 ± 2) than in the CG (11 ± 5). Conclusions: The findings of this study are important to the field of orthodontics and show that the alignment of impacted maxillary canines with A2, V1, and O3 positions can be achieved with both methods, but with the double-wire appliance, the treatment time was shorter and the number of visits was statistically significantly fewer. The results of this study suggest that this approach may be more efficient and cost-effective compared to conventional methods.
The Obesity Mortality Paradox in Patients with Pulmonary Embolism: Insights from a Tertiary Care Center
Authors: Alkhalfan Fahad , Bukhari Syed , Rosenzveig Akiva , Moudgal Rohitha , Khan Syed Zamrak , Ghoweba Mohamed , Chaudhury Pulkit , Cameron Scott J. , Tefera Leben
Published: April 2024

Background: While obesity is associated with an increased risk of venous thromboembolism (VTE), there is some data to suggest that higher BMI is also associated with decreased all-cause mortality in patients with a pulmonary embolism (PE). Methods: Using PE Response Team (PERT) activation data from a large tertiary hospital between 27 October 2020 and 28 August 2023, we constructed a multivariate Cox proportional hazards model to assess the association between obesity as a dichotomous variable (defined as BMI ≥ 30 vs. BMI 18.5–29.9), BMI as a continuous variable, and 30-day PE-related mortality. Results: A total of 248 patients were included in this analysis (150 with obesity and 98 who were in the normal/overweight category). Obesity was associated with a lower risk of 30-day PE-related mortality (adjusted HR 0.29, p = 0.036, 95% CI 0.09–0.92). A higher BMI was paradoxically associated with a lower risk of PE-related mortality (HR = 0.91 per 1 kg/m2 increase, p = 0.049, 95% CI 0.83–0.999). Conclusions: In our contemporary cohort of patients with a PERT activation, obesity was associated with a lower risk of PE-related mortality.
Maternal–Fetal Compatibility in Recurrent Pregnancy Loss
Authors: Cuadrado-Torroglosa Isabel , García-Velasco Juan A. , Alecsandru Diana
Published: April 2024

Nowadays, recurrent pregnancy loss (RPL) is an undesirable condition suffered by many patients of reproductive age. In this scenario, certain immune cell populations and molecules, involved in maternal–fetal compatibility, have emerged as factors related with the pathogenesis of RPL. Among them, uterine Natural Killer cells (uNKs) appear to be of great relevance. These cells are involved in numerous processes during pregnancy, such as the remodeling of uterine spiral arteries or the control of trophoblast invasion. These functions are regulated by the interactions that these cells establish with the extravillous trophoblast, mainly through their Killer Immunoglobulin-like Receptors (KIRs) and the Human Leukocyte Antigen-C (HLA-C) molecules expressed by the embryo. A high level of polymorphism has been reported for both molecules involved in this interaction, with some of the possible KIR–HLA-C combinations being associated with an increased risk of RPL. However, the complexity of the maternal–fetal interface goes beyond this, as other HLA molecules also appear to be related to this reproductive pathology. In this review, we will discuss the role of uNKs in pregnancy, as well as the polymorphisms and clinical implications of KIR–HLA-C binding. We will also address the involvement of other, different HLA molecules in RPL, and the current advice on the appropriate management of patients with ‘immunological mismatch’, thus covering the main aspects regarding the involvement of maternal–fetal compatibility in RPL.
Trace Elements in Alzheimer’s Disease and Dementia: The Current State of Knowledge
Authors: Tyczyńska Magdalena , Gędek Marta , Brachet Adam , Stręk Wojciech , Flieger Jolanta , Teresiński Grzegorz , Baj Jacek
Published: April 2024

Changes in trace element concentrations are being wildly considered when it comes to neurodegenerative disorders, such as Alzheimer’s disease and Parkinson’s disease. This study aims to present the role that trace elements play in the central nervous system. Moreover, we reviewed the mechanisms involved in their neurotoxicity. Low zinc concentrations, as well as high levels of copper, manganese, and iron, activate the signalling pathways of the inflammatory, oxidative and nitrosative stress response. Neurodegeneration occurs due to the association between metals and proteins, which is then followed by aggregate formation, mitochondrial disorder, and, ultimately, cell death. In Alzheimer’s disease, low Zn levels suppress the neurotoxicity induced by β-amyloid through the selective precipitation of aggregation intermediates. High concentrations of copper, iron and manganese cause the aggregation of intracellular α-synuclein, which results in synaptic dysfunction and axonal transport disruption. Parkinson’s disease is caused by the accumulation of Fe in the midbrain dopaminergic nucleus, and the pathogenesis of multiple sclerosis derives from Zn deficiency, leading to an imbalance between T cell functions. Aluminium disturbs the homeostasis of other metals through a rise in the production of oxygen reactive forms, which then leads to cellular death. Selenium, in association with iron, plays a distinct role in the process of ferroptosis. Outlining the influence that metals have on oxidoreduction processes is crucial to recognising the pathophysiology of neurodegenerative diseases and may provide possible new methods for both their avoidance and therapy.
Factors Associated with Frailty in Older Adults in Community and Nursing Home Settings: A Systematic Review with a Meta-Analysis
Authors: Liu Jia , Zhu Yuezhi , Tan Jen Kit , Ismail Azera Hasra , Ibrahim Roszita , Hassan Nor Haty
Published: April 2024

Background: Frailty is a globally recognized issue. However, there is a lack of evidence exploring factors associated with frailty among older residents in community and nursing-home settings. Methods: To explore the prevalence and factors associated with frailty among older adults in community and nursing-home settings, we conducted a systematic search following the PRISMA guidelines across Web of Science, MEDLINE, EMBASE, PubMed, and Cochrane databases up until January 2024, selecting 38 studies which encompassed 150,642 participants. Results: Our findings showed higher frailty prevalence in nursing homes compared to communities. Frailty was significantly associated with sociodemographic (living alone, poor self-reported health), physiological (poor sleep, low activity of daily living), behavioral (physical inactivity) and disease (chronic conditions, depression) factors in both community and nursing-home settings. Conclusions: There are numerous factors associated with frailty in older adults in nursing-home and community settings. These factors underscore the significance of promptly identifying high-risk individuals and devising appropriate interventions to mitigate frailty among them.
Quantification of Aortic Valve Calcification in Contrast-Enhanced Computed Tomography
Authors: Laohachewin Danai , Ruile Philipp , Breitbart Philipp , Minners Jan , Jander Nikolaus , Soschynski Martin , Schlett Christopher L. , Neumann Franz-Josef , Westermann Dirk , Hein Manuel
Published: April 2024

Background: The goal of our study is to evaluate a method to quantify aortic valve calcification (AVC) in contrast-enhanced computed tomography for patients with suspected severe aortic stenosis pre-interventionally. Methods: A total of sixty-five patients with aortic stenosis underwent both a native and a contrast-enhanced computed tomography (CECT) scan of the aortic valve (45 in the training cohort and 20 in the validation cohort) using a standardized protocol. Aortic valve calcification was semi-automatically quantified via the Agatston score method for the native scans and was used as a reference. For contrast-enhanced computed tomography, a calcium threshold of the Hounsfield units of the aorta plus four times the standard deviation was used. Results: For the quantification of aortic valve calcification in contrast-enhanced computed tomography, a conversion formula (691 + 1.83 x AVCCECT) was derived via a linear regression model in the training cohort. The validation in the second cohort showed high agreement for this conversion formula with no significant proportional bias (Bland–Altman, p = 0.055) and with an intraclass correlation coefficient in the validation cohort of 0.915 (confidence interval 95% 0.786–0.966) p < 0.001. Conclusions: Calcium scoring in patients with aortic valve stenosis can be performed using contrast-enhanced computed tomography with high validity. Using a conversion factor led to an excellent agreement, thereby obviating an additional native computed tomography scan. This might contribute to a decrease in radiation exposure.
Innovative Non-Surgical Plastic Technique for Saddle Nose Correction: A Study on 97 Patients
Authors: Ossanna Riccardo , Ghazanfar Tehrani Sara , Dallatana Alessia , Khabouri Sima , Veronese Sheila , Sbarbati Andrea , Goisis Mario
Published: April 2024

Background: Non-surgical rhinoplasty is one of the best choices in mild cases of the saddle nose, and it represents a solution for the aesthetical amelioration of facial deformity; nevertheless, in most critical cases, surgical intervention is still required. This study reports the experience and results of a single facial plastic surgeon (M.G.) using a non-surgical technique for the correction of saddle noses in a large cohort of patients. Methods: This retrospective study assesses all patients injected from January 2017 through October 2023 in private clinics in Milan (Italy), London (UK), and Dubai (UAE). All patients were followed up for 12 months. The harvested adipose tissues were processed with different systems and with or without acoustic wave therapy (AWT). The extracted products have been characterized in terms of cellular yield and cell growth. Ninety-seven patients were injected with adipose-derived products or hyaluronic acid (HA). Patients were followed up for 12 months, and satisfaction data were analyzed. Results: The stem cells obtained from the patients who previously received AWT displayed a statistically higher cell growth ability in comparison with those of the cells derived from patients who did not receive AWT. The evolution of patient satisfaction during the time for each group of treatment was investigated, and cellular treatments show the best maintenance of patient satisfaction over time. Conclusions: Dermgraft and AWT approaches resulted in the highest patient satisfaction for the non-surgical correction of the saddle nose deformity.
PlasmaBlade versus Electrocautery for Deep Inferior Epigastric Perforator Flap Harvesting in Autologous Breast Reconstruction: A Comparative Clinical Outcome Study
Authors: Augustin Angela , Schoberleitner Ines , Unterhumer Sophie-Marie , Krapf Johanna , Bauer Thomas , Wolfram Dolores
Published: April 2024

(1) Background: DIEP-based breast reconstruction necessitates wide undermining at the abdominal donor site, creating large wound areas. Flap harvesting is usually conducted using electrosurgical dissection devices. This study sought to compare the clinical outcomes in patients after using the PEAK PlasmaBlade (PPB) versus monopolar electrocautery (MPE). (2) Methods: This retrospective cohort study included 128 patients with DIEP-based breast reconstruction. Patient characteristics and information on the postoperative course were collected and a comparative evaluation was conducted. (3) Results: The MPE group exhibited significantly (p* = 0.0324) higher abdominal drainage volume (351.11 ± 185.96 mL) compared to the PPB group (279.38 ± 183.38 mL). A subgroup analysis demonstrated that PPB significantly reduced postoperative wound fluid in patients with BMI > 30 kg/m2 (p* = 0.0284), without prior neoadjuvant chemotherapy (p** = 0.0041), and among non-smokers (p = 0.0046). Furthermore, postoperative pain was significantly (p**** < 0.0001) lower in the PPB cohort. (4) Conclusions: This study confirms the non-inferiority of the PEAK PlasmaBlade to conventional electrocautery for abdominal flap harvesting. The PPB demonstrated advantages, notably reduced drainage volume and lower postoperative pain levels. Recognizing patient subsets that benefit more from the PPB highlights the importance of personalized device selection based on patient characteristics.
The Use of Fish Skin Grafts in Children as a New Treatment of Deep Dermal Burns—Case Series with Follow-Up after 2 Years and Measurement of Elasticity as an Objective Scar Evaluation
Authors: Staubach Raphael , Glosse Helen , Loff Steffan
Published: April 2024

Background: Wound healing in deep dermal burn injuries continues to be a challenge in paediatrics. In the absence quick and spontaneous wound closure, split-thickness skin grafting is often necessary. Since the development of a new type of acellular fish matrix, which is very similar to the human skin matrix, skin closure and wound conditioning can be achieved without split-thickness skin grafting. Methods: The following study shows a case series of 20 children in whom a fish skin graft was used. The aim was to develop an algorithm for selecting and using fish skin and its long-term results after one and two years. Acellular fish skin worked as a granulation base for wound healing and also as a substitute for split-thickness skin grafts. Results: There was no evidence of infection. Skin transplants and, thus, additional operations could be avoided. The follow-up examinations showed an excellent result, both objectively by means of elasticity measurements (DermalabCombo®) and in the subjective assessment of the skin as part of the Patient and Observer Scar Assessment Scale (POSAS). Conclusion: Fish skin grafts are a good alternative to split-thickness skin grafts for deep dermal wounds. These results should be further analysed with a larger number of patients in future publications.
Primary Coenzyme Q10 Deficiency-Related Ataxias
Authors: Lopriore Piervito , Vista Marco , Tessa Alessandra , Giuntini Martina , Caldarazzo Ienco Elena , Mancuso Michelangelo , Siciliano Gabriele , Santorelli Filippo Maria , Orsucci Daniele
Published: April 2024

Cerebellar ataxia is a neurological syndrome characterized by the imbalance (e.g., truncal ataxia, gait ataxia) and incoordination of limbs while executing a task (dysmetria), caused by the dysfunction of the cerebellum or its connections. It is frequently associated with other signs of cerebellar dysfunction, including abnormal eye movements, dysmetria, kinetic tremor, dysarthria, and/or dysphagia. Among the so-termed mitochondrial ataxias, variants in genes encoding steps of the coenzyme Q10 biosynthetic pathway represent a common cause of autosomal recessive primary coenzyme Q10 deficiencies (PCoQD)s. PCoQD is a potentially treatable condition; therefore, a correct and timely diagnosis is essential. After a brief presentation of the illustrative case of an Italian woman with this condition (due to a novel homozygous nonsense mutation in COQ8A), this article will review ataxias due to PCoQD.
The Influence of Inset and Shaping of Abdominal-Based Free Flap Breast Reconstruction on Patient-Reported Aesthetic Outcome Scores—A Systematic Review
Authors: Zucal Isabel , De Pellegrin Laura , Parodi Corrado , Harder Yves , Schweizer Riccardo
Published: April 2024

Background: Nowadays, multimodal cancer therapy results in very high survival rates of early-stage breast cancer and microsurgical flap-based breast reconstruction has become safe and reliable, with gradually increasing demand because of its durable and aesthetically pleasing results. This study aimed to explore the impact of different flap shaping and inset techniques on patient-reported outcome measures (PROMs) with regard to the aesthetic result in abdominal flap-based breast reconstruction. Methods: A systematic review was performed screening Pubmed, Cochrane Library and Web of Science for original articles reporting flap inset strategies, concomitantly providing PROMs on the aesthetic result. Results: Of 319 studies identified, six met the inclusion criteria. The studies described different flap rotation options according to the patient’s morphology, different inset planes, and avoidance of the monitoring skin paddle, and suggested that a higher flap-to-mastectomy mass ratio was associated with better aesthetic results. In two comparative studies, according to the PROMs (BREAST-Q, Likert scale) and independent observer judgement, both higher patient satisfaction and superior aesthetic results were observed with the newly described techniques. Conclusions: Emphasis on the aesthetic outcome in terms of breast shape and symmetry, providing an individualized approach of flap inset, considering the contralateral breast’s shape and volume, results in higher satisfaction scores.
Nursing Interventions to Prevent Secondary Injury in Critically Ill Patients with Traumatic Brain Injury: A Scoping Review
Authors: Figueiredo Rita , Castro Cidália , Fernandes Júlio Belo
Published: April 2024

Background: Traumatic brain injury is a prevalent health issue with significant social and economic impacts. Nursing interventions are crucial in preventing secondary injury and improving patient prognosis. This scoping seeks to map and analyze the existing scientific evidence on nursing interventions aimed at preventing secondary injuries in critically ill patients with traumatic brain injury. Methods: The review was conducted according to Arksey and O’Malley’s methodological framework. The electronic databases Pubmed, MEDLINE Complete, CINAHL Complete, Nursing & Allied Health Collection: Comprehensive, Cochrane Central Register of Controlled Trials, and Cochrane Clinical Answers were consulted in May 2023. We included articles published in English and Portuguese between 2010 and 2023. Results: From the initial search, 277 articles were identified, with 15 meeting the inclusion criteria for the review. Nursing interventions for TBI patients include neuromonitoring, therapeutics, analytical surveillance, professional training, and family support. Nurses play a crucial role in detecting neurological changes, administering treatments, monitoring metabolic markers, training staff, and involving families. These interventions aim to prevent secondary injury and improve patient outcomes. Conclusions: By prioritizing evidence-based practice and utilizing innovative technologies, nurses enhance TBI patient care and contribute to overall well-being.
A Review on the Recent Trends in Forming Composite Joints Using Spot Welding Variants
Authors: Arumugam Aravinthan , Pramanik Alokesh
Published: April 2024

Traditional resistance spot welding (RSW) has been unsuccessful in forming quality composite joints between steel– or aluminum–polymer-based composites. This has led to the development of spot welding variants such as friction stir spot welding (FFSW), ultrasonic spot welding (USW), and laser spot welding (LSW). The paper reviewed the differences in the bonding mechanisms, spot weld characteristics, and challenges involved in using these spot welding variants. Variants of RSW use series electrode arrangement, co-axial electrodes, metallic inserts, interlayers, or external energy to produce composite joints. FFSW and USW use nanoparticles, interlayers, or energy directors to create composite spot welds. Mechanical interlocking is the common composite joint mechanism for all variants. Each spot welding variant has different sets of weld parameters and distinct spot weld morphologies. FFSW is the most expensive variant but is commonly used for composite spot weld joints. USW has a shorter welding cycle compared to RSW and FFSW but can only be used for small components. LSW is faster than the other variants, but limited work was found on its use in composite spot weld joining. The use of interlayers in FFSW and USW to form composite joints is a potential research area recommended in this review.
The Flexion Relaxation Phenomenon in Patients with Radiculopathy and Low Back Pain: A Cross-Sectional Study
Authors: Peharec Marijan , Peharec Stanislav , Srhoj-Egekher Vedran , Jerković Romana , Girotto Dean , Starčević-Klasan Gordana
Published: April 2024

Although the measurements of the lumbar spine and pelvic flexion have shown that subjects with radiculopathy exhibited greater decreases of motion when compared with subjects with low back pain, there is still a lack of evidence regarding the changes in flexion relaxation ratio in patients with radiculopathy. The aims of this study were to investigate the flexion relaxation ratio and flexion of the lumbar spine and pelvis in subjects with low back pain (LBP) and LBP with radiculopathy (LBPR) in comparison with healthy subjects (CG—control group). A total of 146 participants were divided in three groups: LBP patients (54 males; 21 females); LBPR patients (26 males; 11 females); and CG subjects (16 males; 18 females). The lumbar spine and pelvis flexion was recorded using optoelectronic motion capture system. The electrical activity of the erector spinae muscles was assessed by surface electromyography during flexion-extension movements. Comparisons between groups were made using one-way ANOVA tests and Mann–Whithney U test with the level of statistical significance at 0.05. The lumbar and pelvic flexion and electromyography of the erector spinae muscle showed significant differences between LBP and LBPR patients compared to CG. Patients LBPR showed significantly smaller angles of lumbar and pelvic flexion compared to LBP patients and CG. An increase in the erector spinae muscle activity during flexion was also observed in patients with radiculopathy. The increased muscular activity of the erector spinae is related to the reduced flexion of the lumbar spine in order to protect the lumbar spine structure. Measurements of trunk, lumbar spine and pelvic flexion, and the flexion relaxation ratio may allow us to predict better outcomes or responsiveness to treatment of LBPR patients in the future.
Kinesiophobia in Injured Athletes: A Systematic Review
Authors: Ambegaonkar Jatin P. , Jordan Matthew , Wiese Kelley R. , Caswell Shane V.
Published: April 2024

Athletes have a high risk of injury. Kinesiophobia is a condition in which an individual experiences a fear of physical movement and activity after an injury occurs. Our purpose was to systematically review the literature about Kinesiophobia in athletes. A systematic review was conducted in February 2023 using PubMed, CINAHL, SPORTDiscus, Web of Science, Cochrane Library, and Medline. Studies were included if they were peer-reviewed, in English, within the last 20 years and included athletes who had been injured and tracked Kinesiophobia. Articles were checked for quality via the modified Downs and Black checklist. Fourteen studies were included in the review and had an average “fair” quality score. Authors examined Kinesiophobia in injured athletes with mostly lower-extremity injuries. Kinesiophobia was associated with lower physical and mental outcomes. Kinesiophobia exists in athletes and can affect both physical and mental factors. The Tampa Scale of Kinesiophobia (TSK) was the most common tool used to examine Kinesiophobia. Common mental factors associated with Kinesiophobia include anxiety, low confidence, and fear avoidance.
Role of Li and Sc Additions and Machining Conditions on Cutting Forces on Milling Behavior of A7075-Based Alloys
Authors: Tahmasbi Ali , Moungomo Jean Brice Mandatsy , Samuel Agnes M. , Zedan Yasser , Songmene Victor , Samuel Fawzy H.
Published: April 2024

The present study focuses on the dry and wet end milling of three distinct Aluminum 7075 alloys: A7075, A7075–Sc (with a 0.18% Sc addition), and A7075–Li–Sc (containing 2.2% Li and 0.18% Sc additions). The main objective is to explore how cutting parameters (cutting speed and feed rate), heat treatment, alloy composition, and cooling methods influence A lcutting force. In the initial phase of the investigation, all three alloys underwent heat treatment. Subsequently, the machining process centered on the softest and hardest conditions, aiming at analyzing the impact of hardness on machinability behavior of the three studied alloys, using the same milling tool and a consistent depth of cut under both dry and wet conditions. The investigations also highlight the role of Li and Sc additions on the quality of surface finish, as well as burr and chip formation. In total, a sum of 108 operations have been performed on the present alloys.
Research on Abrasive Particle Target Detection and Feature Extraction for Marine Lubricating Oil
Authors: Bai Chenzhao , Ding Jiaqi , Zhang Hongpeng , Xu Zhiwei , Liu Hanlin , Li Wei , Li Guobin , Wei Yi , Wang Jizhe
Published: April 2024

The hydraulic oil of marine equipment contains a large number of abrasive contaminants that reflect the operating condition of the equipment. In order to realize the detection of particulate contaminants, this research first proposes a shape-based classification method for oil abrasive particles, designs an oil abrasive particle collection system, and constructs a new dataset. After that, the research introduces deep learning target detection technology in computer vision, and uses GhostNet to lighten the network structure, the CBAM (Convolutional Block Attention Module) attention mechanism to improve the generalization ability of the model, and the ASPP module to enhance the model sensory wildness, respectively. A lightweight target detection model, WDD, is created for the identification of abrasive particles. In this study, the WDD model is tested against other network models, and the mAP value of WDD reaches 91.2%, which is 4.8% higher than that of YOLOv5s; in addition, the detection speed of the WDD model reaches 55 FPS. Finally, this study uses real ship lubricating oils for validation, and the WDD model still maintains a high level of accuracy. Therefore, the WDD model effectively balances the accuracy and detection speed of marine oil abrasive particle detection, which is superior to other oil abrasive particle detection techniques.
The Response of Mixed Layer Depth Due to Hurricane Katrina (2005)
Authors: Lee Wonhyun , Veeramony Jayaram
Published: April 2024

The ocean’s mixed layer depth (MLD) plays an important role in understanding climate dynamics, especially during extreme weather occurrences like hurricanes. This study investigates the effects of Hurricane Katrina (2005) on the MLD in the Gulf of Mexico, using the Delft3D modeling system. By integrating hydrodynamics and wave dynamics modules, we simulate the ocean’s response to extreme weather, focusing on temperature, salinity and MLD variations. Our analysis reveals significant cooling and mixing induced by Katrina, resulting in spatial and temporal fluctuations in temperature (~±4 °C) and salinity (~±1.5 ppt). The MLD is estimated using a simple threshold method, revealing a substantial deepening to ~120 m on 29–30 August during Hurricane Katrina in the middle of the northern Gulf of Mexico, compared to an average MLD of ~20–40 m during pre-storm conditions. It took about 18 days to recover to ~84% of the pre-storm level after Katrina. Compared to the stand-alone FLOW model, the coupled FLOW+WAVE model yields a deeper MLD of ~5%. The MLD recovery and wave effect on the MLD provide insights from various scientific, environmental and operational perspectives, offering a valuable basis for ocean management, planning and applications, particularly during extreme weather events.
Analytical Review of the Current State of Technology, Structure Formation, and Properties of Variatropic Centrifugally Compacted Concrete
Authors: Shcherban’ Evgenii M. , Stel’makh Sergey A. , Mailyan Levon R. , Beskopylny Alexey N. , Smolyanichenko Alla S. , Chernil’nik Andrei , Elshaeva Diana , Beskopylny Nikita
Published: April 2024

Current regulatory documents and the scientific literature lack a theoretical framework and practical guidance for calculating centrifugally compacted reinforced concrete structures, taking into account the variatropy of their structure and the material’s characteristics across the section. A problem related to this research lies in the need to form a systematized, theoretical, and practical knowledge base about variatropic concretes, the importance of which has been proven by various scientists without, to date, the creation of a unified scientific methodological base. The importance of this study is linked to the need for the world’s construction projects and processes to transition to the most economically, materially, and resource-efficient types of building structures, which, of course, include structures made of variable-type concrete. This study’s objective is to fill these scientific and engineering gaps. The purpose of this study was to systematize the existing knowledge base about the technology, structure formation, and properties of variatropic concrete, using an analytical review of previously conducted studies by ourselves and others, both in Russia and abroad. A theoretical justification for the formation of the structure of variatropic materials is presented. An analysis of the basic physical and mechanical properties of variatropic concretes is carried out and the features of their microstructures are considered. The main structures created using centrifugation technology are considered. Variatropic concrete has an increased amount of mechanical characteristics compared to traditional concrete, on average by up to 45%. The durability of variatropic concrete is improved, on average, by up to 30% compared to conventional concrete.
Enhancing Legal Sentiment Analysis: A Convolutional Neural Network–Long Short-Term Memory Document-Level Model
Authors: Abimbola Bolanle , de La Cal Marin Enrique , Tan Qing
Published: April 2024

This research investigates the application of deep learning in sentiment analysis of Canadian maritime case law. It offers a framework for improving maritime law and legal analytic policy-making procedures. The automation of legal document extraction takes center stage, underscoring the vital role sentiment analysis plays at the document level. Therefore, this study introduces a novel strategy for sentiment analysis in Canadian maritime case law, combining sentiment case law approaches with state-of-the-art deep learning techniques. The overarching goal is to systematically unearth hidden biases within case law and investigate their impact on legal outcomes. Employing Convolutional Neural Network (CNN)- and long short-term memory (LSTM)-based models, this research achieves a remarkable accuracy of 98.05% for categorizing instances. In contrast, conventional machine learning techniques such as support vector machine (SVM) yield an accuracy rate of 52.57%, naïve Bayes at 57.44%, and logistic regression at 61.86%. The superior accuracy of the CNN and LSTM model combination underscores its usefulness in legal sentiment analysis, offering promising future applications in diverse fields like legal analytics and policy design. These findings mark a significant choice for AI-powered legal tools, presenting more sophisticated and sentiment-aware options for the legal profession.
Disturbing Fuzzy Multi-Attribute Decision-Making Method with If Weight Information Is Disturbing Fuzzy Number
Authors: Li Li , Yang Jin
Published: April 2024

Fuzzy multi-attribute decision-making is a hot research topic in which weight information is one of the conditions for forming a complete decision-making model, and it is also an important factor affecting the decision result. In most fuzzy multi-attribute decision-making problems, the weight information is often given in the form of real numbers. However, in real life, the weight information may not be suitable for specific numerical representation, or we cannot accurately determine the weight information. Therefore, it is very important to use fuzzy numbers to represent weight information. In this paper, we study the problem of disturbing fuzzy multi-attribute decision-making in which the attribute weight, decision-maker weight, and attribute information are given in the form of disturbing fuzzy numbers. Firstly, a new disturbing fuzzy integration operator, namely the disturbing fuzzy ring and multiplication aggregation (DFRMA) operator, is proposed, and its characteristics of closure, monotonicity, and boundary are studied. Then, the general steps of the disturbing fuzzy multi-attribute decision method based on the disturbing fuzzy ring and multiplication aggregation (DFRMA) operator are given, which include the single decision step and group decision step. Finally, an example is given to illustrate the practicability and effectiveness of the method.
A Speech Adversarial Sample Detection Method Based on Manifold Learning
Authors: Ma Xiao , Xu Dongliang , Yang Chenglin , Li Panpan , Li Dong
Published: April 2024

Deep learning-based models have achieved impressive results across various practical fields. However, these models are susceptible to attacks. Recent research has demonstrated that adversarial samples can significantly decrease the accuracy of deep learning models. This susceptibility poses considerable challenges for their use in security applications. Various methods have been developed to enhance model robustness by training with more effective and generalized adversarial examples. However, these approaches tend to compromise model accuracy. Currently proposed detection methods mainly focus on speech adversarial samples generated by specified white-box attack models. In this study, leveraging manifold learning technology, a method is proposed to detect whether a speech input is an adversarial sample before feeding it into the recognition model. The method is designed to detect speech adversarial samples generated by black-box attack models and achieves a detection success rate of 84.73%. It identifies the low-dimensional manifold of training samples and measures the distance of a sample under investigation to this manifold to determine its adversarial nature. This technique enables the preprocessing detection of adversarial audio samples before their introduction into the deep learning model, thereby preventing adversarial attacks without affecting model robustness.
LLE-NET: A Low-Light Image Enhancement Algorithm Based on Curve Estimation
Authors: Cao Xiujie , Yu Jingjun
Published: April 2024

Low-light image enhancement is very significant for vision tasks. We introduce Low-light Image Enhancement via Deep Learning Network (LLE-NET), which employs a deep network to estimate curve parameters. Cubic curves and gamma correction are employed for enhancing low-light images. Our research trains a lightweight network to estimate the parameters that determine the correction curve. By the results of the deep learning network, accurate correction curves are confirmed, which are used for the per-pixel correction of RGB channels. The image enhanced by our models closely resembles the input image. To further accelerate the inferring speed of the low-light enhancement model, a low-light enhancement model based on gamma correction is proposed with one iteration. LLE-NET exhibits remarkable inference speed, achieving 400 fps on a single GPU for images sized 640×480×3 while maintaining pleasing enhancement quality. The enhancement model based on gamma correction attains an impressive inference speed of 800 fps for images sized 640×480×3 on a single GPU.
RUL Prediction for Piezoelectric Vibration Sensors Based on Digital-Twin and LSTM Network
Authors: Fu Chengcheng , Gao Cheng , Zhang Weifang
Published: April 2024

Piezoelectric vibration sensors (PVSs) are widely used in high-temperature environments, such as vibration measurements in aero-engines, because of their high accuracy, small size, and high temperature resistance. Accurate prediction of its RUL (Remaining Useful Life) is essential for applying and maintaining PVSs. Based on PVSs’ characteristics and main failure modes, this work combines the Digital-Twin (DT) and Long Short-Term Memory (LSTM) networks to predict the RUL of PVSs. In this framework, DT can provide rich data collection, analysis, and simulation capabilities, which have advantages in RUL prediction, and LSTM network has good results in predicting time sequence data. The proposed method exploits the advantages of those techniques in feature data collection, sample optimization, and RUL multiclassification. To verify the prediction of this method, a DT platform is established to conduct PVS degradation tests, which generates sample datasets, then the LSTM network is trained and validated. It has been proved that prediction accuracy is more than 99.7%, and training time is within 94 s. Based on this network, the RUL of PVSs is predicted using different test samples. The results show that the method performed well in prediction accuracy, sample data utilization, and compatibility.
Brain-Inspired Agents for Quantum Reinforcement Learning
Authors: Andrés Eva , Cuéllar Manuel Pegalajar , Navarro Gabriel
Published: April 2024

In recent years, advancements in brain science and neuroscience have significantly influenced the field of computer science, particularly in the domain of reinforcement learning (RL). Drawing insights from neurobiology and neuropsychology, researchers have leveraged these findings to develop novel mechanisms for understanding intelligent decision-making processes in the brain. Concurrently, the emergence of quantum computing has opened new frontiers in artificial intelligence, leading to the development of quantum machine learning (QML). This study introduces a novel model that integrates quantum spiking neural networks (QSNN) and quantum long short-term memory (QLSTM) architectures, inspired by the complex workings of the human brain. Specifically designed for reinforcement learning tasks in energy-efficient environments, our approach progresses through two distinct stages mirroring sensory and memory systems. In the initial stage, analogous to the brain’s hypothalamus, low-level information is extracted to emulate sensory data processing patterns. Subsequently, resembling the hippocampus, this information is processed at a higher level, capturing and memorizing correlated patterns. We conducted a comparative analysis of our model against existing quantum models, including quantum neural networks (QNNs), QLSTM, QSNN and their classical counterparts, elucidating its unique contributions. Through empirical results, we demonstrated the effectiveness of utilizing quantum models inspired by the brain, which outperform the classical approaches and other quantum models in optimizing energy use case. Specifically, in terms of average, best and worst total reward, test reward, robustness, and learning curve.
Measurement and Forecasting of Systemic Risk: A Vine Copula Grouped-CoES Approach
Authors: Duan Huiting , Yu Jinghu , Wei Linxiao
Published: April 2024

Measuring systemic risk plays an important role in financial risk management to control systemic risk. By means of a vine copula grouped-CoES method, this paper aims to measure the systemic risk of Chinese financial markets. The empirical study indicates that the banking industry has a low risk and a strong ability to resist risks, but also contributes the most of the systemic risk. On the other hand, insurance companies and securities have high ES but low ΔCoES, indicating their low risk tolerance and small contribution to the systemic risk. Furthermore, this study employs a sliding window in Monte Carlo simulation to forecast systemic risk. The findings of this paper suggest that different types of financial industries should adopt different systemic risk measures.
Hybrid Optimization Method Based on Coupling Local Gradient Information and Global Evolution Mechanism
Authors: Zhu Caicheng , Zhao Xin , He Xinlei , Tang Zhili
Published: April 2024

Multi-objective evolutionary algorithms (MOEA) have attracted much attention because of their good global exploration ability; however, their local search ability near the optimal value is weak, and for large-scale decision-variable optimization problems the number of populations and iterations required by MOEA are very large, so the optimization efficiency is low. Gradient optimization algorithms can overcome these difficulties well, but gradient search methods are difficult to apply to multi-objective optimization problems (MOPs). To this end, this paper introduces a stochastic weighting function based on the weighted average gradient and proposes two multi-objective stochastic gradient operators. Further, two efficient evolutionary algorithms, MOGBA and HMOEA, are developed. Their local search capability has been greatly enhanced while retaining the good global exploration capability by using different offspring update strategies for different subpopulations. Numerical experiments show that HMOEA has excellent capture ability for various Pareto formations, and it can easily solve multi-objective optimization problems with many objectives, which improves the efficiency by a factor of 5–10 compared with typical multi-objective evolutionary algorithms. HMOEA is further applied to the multi-objective aerodynamic optimization design of the RAE2822 airfoil and the ideal Pareto front is obtained, which indicates that HMOEA is an efficient optimization algorithm with potential applications in aerodynamic optimization design.