bluuebunny/crossref_metadata_2025 huggingface dataset:
Prediction of Ship Painting Man-Hours Based on Selective Ensemble Learning
Authors: Bu Henan , Ge Zikang , Zhu Xianpeng , Yang Teng , Zhou Honggen
Published: March 2024

The precise prediction of painting man-hours is significant to ensure the efficient scheduling of shipyard production and maintain a stable production pace, which directly impacts shipbuilding cycles and costs. However, traditional forecasting methods suffer from issues such as low efficiency and poor accuracy. To solve this problem, this paper proposes a selective integrated learning model (ISA-SE) based on an improved simulated annealing algorithm to predict ship painting man-hours. Firstly, the improved particle swarm optimization (MPSO) algorithm and data grouping techniques are employed to achieve the optimal selection and hyperparameter optimization of base learners, constructing a candidate set of base learners. Subsequently, the simulated annealing algorithm is improved by adding random perturbations and using a parallel perturbation search mechanism to enhance the algorithm’s global search capability. Finally, an optimal set of base learners is composed of the candidate set utilizing the ISA-SE model, and a heterogeneous ensemble learning model is constructed with the optimal set of base learners to achieve the precise prediction of ship painting man-hours. The results indicate that the proposed ISA-SE model demonstrates improvements in accuracy, mean absolute error, and root mean square error compared to other models, validating the effectiveness and robustness of ISA-SE in predicting ship painting man-hours.
Unveiling Nanogranular Advancements in Nickel-Doped Tungsten Oxide for Superior Electrochromic Performance
Authors: Morankar Pritam J. , Amate Rutuja U. , Teli Aviraj M. , Beknalkar Sonali A. , Jeon Chan-Wook
Published: March 2024

Electrochromic materials allow for precise control of their optical properties by applying an electric field, which has led to recent developments in energy-saving and indoor temperature control systems like smart windows. The selective incorporation of metal dopants is an effective technique for generating highly advanced semiconducting metal oxides with precisely customized physicochemical characteristics. In this report, we employed a one-step electrodeposition process to fabricate nickel-doped tungsten oxide (W–Ni) thin films, systematically probing the impact of nickel (Ni) doping on the collective material characteristics. Comprehensive X-ray diffraction research revealed significant changes in diffraction patterns, suggesting slight modifications in the structure caused by Ni doping. The scanning electron microscopy showed complex differences in the microstructure of the film, such as a dense surface, porosity, and clustering of nanogranules. The WNi-3% thin film doped at 3 wt. % exhibited excellent electrochromic performance by efficiently handling lithium ions and displaying favorable electrochromic properties. The improved electrode, WNi-3%, showed a maximum optical modulation of 81.90%, exceptional reversibility of 99.4%, and a high coloration efficiency of 75.12 cm2/C. These findings underscore the efficacy of Ni-doping in tailoring the electrochromic properties of nickel-doped tungsten oxide thin films, thereby advancing the frontiers of high-performance electrochromic materials for energy-efficient applications.
Inverse Trigonometric Fuzzy Preference Programming to Generate Weights with Optimal Solutions Implemented on Evaluation Criteria in E-Learning
Authors: Iryanti Emi , Santosa Paulus Insap , Kusumawardani Sri Suning , Hidayah Indriana
Published: March 2024

Nielsen’s heuristics are widely recognized for usability evaluation, but they are often considered insufficiently specific for assessing particular domains, such as e-learning. Currently, e-learning plays a pivotal role in higher education because of the shift in the educational paradigm from a teacher-centered approach to a student-centered approach. The criteria utilized in multiple sets of heuristics for evaluating e-learning are carefully examined based on the definitions of each criterion. If there are similarities in meaning among these criteria, they are consolidated into a single criterion, resulting in the creation of 20 new criteria (spanning three primary aspects) for the evaluation of e-learning. These 20 new criteria encompass key aspects related to the user interface, learning development, and motivation. Each aspect is assigned a weight to facilitate prioritization when implementing improvements to evaluate e-learning, which is especially beneficial for institutions with limited resources responsible for the relevant units. In terms of weighting, there is room for enhancement to attain more optimal weighting outcomes by employing a Fuzzy Preference Programming method known as Inverse Trigonometric Fuzzy Preference Programming (ITFPP). The higher the assigned weight, the greater the priority for implementing improvements.
How to Develop Information Systems to Improve Accessible Tourism: Proposal of a Roadmap to Support the Development of Accessible Solutions
Authors: Teixeira Pedro , Eusébio Celeste , Teixeira Leonor
Published: March 2024

The right to tourism has become a crucial aspect of society. Through more accessible tourism, it is possible to improve travel conditions for people with disabilities. Nonetheless, barriers still exist, with the lack of information about accessibility conditions representing a main obstacle. Information systems can help overcome these hurdles. However, it is verified that methodologies to support the development of accessible IS are currently very scarce. Thus, this study intends to develop an accessible IS for accessible tourism and propose a roadmap to support the creation of accessible IS solutions. To obtain the intended accessible tourism solution, an action research methodology was followed, which involved adapting already established frameworks, that combine Agile development and user-centered design techniques. Following the methodology, a web application named access@tour by action was created. This mobile solution is capable of improving information management within the accessible tourism market. From this experimental study, a proposal for a methodological roadmap emerged. This roadmap helps to better understand how to develop accessible IS by demonstrating techniques for gathering accessibility requirements and validating them. The roadmap is adaptable and suitable for IS projects involving accessibility. Both results provide a better perspective on how to integrate accessibility during the development of IS, possibly supporting future researchers in creating accessible solutions.
Preparation of FeNiCoCrCu Thin Films by Ionized Jet Deposition Method: Determination of Elemental Transfer Coefficients
Authors: Lis Jáchym , Skočdopole Jakub , Jaroš Petr , Čapek Jiří , Trojan Karel , Dráb Martin , Kučeráková Monika , Vratislav Stanislav , Kalvoda Ladislav
Published: March 2024

Investigation of high-entropy alloys in form of bulk samples as well as thin films is currently one of the fastest growing areas in the study of metal alloys. In this paper, a bulk sample of FeNiCoCuCr high-entropy alloy ingot with equimolar composition is prepared by the laboratory arc melting method under an argon atmosphere and used as a source target for deposition of thin films on Si (111) single-crystalline substrates using a novel ionized jet deposition method. The morphology, chemical composition, and real crystalline structure of the target and the prepared layers were characterized by scanning electron microscopy, atomic force microscopy, energy-dispersive X-ray spectroscopy, and X-ray and neutron diffraction methods. Transfer coefficients characterizing the mass transport between the target and the grown film were calculated for each of the constituting metallic elements as the ratio of the atomic concentration found in the prepared film divided by its concentration in the deposition target. The dependence of the obtained transfer coefficients on the IJD acceleration voltage is discussed with respect to the main physical and geometric parameters of the deposition process, and their correlations with the cohesive energy of the elements forming the HEA are proposed.
Serious Games in Higher Education in the Transforming Process to Education 4.0—Systematized Review
Authors: Brandl Lea C. , Schrader Andreas
Published: March 2024

The digital transformation associated with the Fourth Industrial Revolution is having an impact on the way we teach. Under the term Education 4.0, new teaching methods, new technologies, as well as a student-centered approach, are expected to be used in teaching. One established method of teaching is the use of Serious Games, as it has various positive effects in terms of motivation and engagement. This paper deals with the question of how the transformation towards Education 4.0 influences the way Serious Games are designed and used in the context of higher education. To this end, a systematized literature review was conducted. Out of 550 publications, 28 were included. This revealed works on the general conception as well as studies on Serious Games in various areas of university teaching. The results show different concepts of Serious Games, with the structure often being adapted to learning content and not to students. In terms of technical implementation, Serious Games are mostly web- or desktop-applications instead of new technologies such as VR. As a result, new concepts seem necessary to adapt Serious Games to Education 4.0. In the future, we want to design Serious Games that respond flexibly to students’ needs and make it easy to integrate new technologies.
Musical Instrumental Self-Concept, Social Support, and Grounded Optimism in Secondary School Students: Psycho-Pedagogical Implications for Music Education
Authors: Zarza-Alzugaray Begoña , Casanova Oscar , Zarza-Alzugaray Francisco Javier
Published: March 2024

Research in music education has shown that musical and academic self-concept, the social component, task achievement, and academic performance are highly interrelated constructs in musical learning in general and instrumental learning in particular in secondary school students. However, no studies in Spain have analyzed the relationship between musical self-concept and the variables of social support and optimism in compulsory secondary education. Therefore, our study aimed to explore the relationships between instrumental musical self-concept, social support, and grounded optimism. We hypothesize that there is a significant relationship between the variables of musical self-concept, social support, and grounded optimism The variables were measured using the Instrumental Musical Self-Concept Scale (IMSCS), an adaptation of the Perceived Social Support Scale in Spanish Conservatory Music Students to the Secondary School Level, and the Grounded Optimism Scale (BEEGC-RA/BEECESA-RA24). The study sample consisted of 980 students enrolled in compulsory secondary education in public and semi-private schools in the autonomous communities of Aragon and Navarra. An analysis of correlations and regressions allowed us to explore and quantify the relationship among the variables under study, confirming the existence of a significant relationship among the variables “instrumental musical self-concept”, “social support” and “grounded optimism”. The present study thus provides more in-depth knowledge of the variables involved in the teaching–learning process of music as a school subject and instrumental music in particular, as well as a greater knowledge of the individual’s performance and motivation in the subject, with various future implications to be taken into account.
Cloud-Connected Bracelet for Continuous Monitoring of Parkinson’s Disease Patients: Integrating Advanced Wearable Technologies and Machine Learning
Authors: Channa Asma , Ruggeri Giuseppe , Ifrim Rares-Cristian , Mammone Nadia , Iera Antonio , Popescu Nirvana
Published: March 2024

Parkinson’s disease (PD) is one of the most unremitting and dynamic neurodegenerative human diseases. Various wearable IoT devices have emerged for detecting, diagnosing, and quantifying PD, predominantly utilizing inertial sensors and computational algorithms. However, their proliferation poses novel challenges concerning security, privacy, connectivity, and power optimization. Clinically, continuous monitoring of patients’ motor function is imperative for optimizing Levodopa (L-dopa) dosage while mitigating adverse effects and motor activity decline. Tracking motor function alterations between visits is challenging, risking erroneous clinical decisions. Thus, there is a pressing need to furnish medical professionals with an ecosystem facilitating comprehensive Parkinson’s stage evaluation and disease progression monitoring, particularly regarding tremor and bradykinesia. This study endeavors to establish a holistic ecosystem centered around an energy-efficient Wi-Fi-enabled wearable bracelet dubbed A-WEAR. A-WEAR functions as a data collection conduit for Parkinson’s-related motion data, securely transmitting them to the Cloud for storage, processing, and severity estimation via bespoke learning algorithms. The experimental results demonstrate the resilience and effectiveness of the suggested technique, with 86.4% accuracy for bradykinesia and 90.9% accuracy for tremor estimation, along with good sensitivity and specificity for each scoring class. The recommended approach will support the timely determination of the severity of PD and ongoing patient activity monitoring. The system helps medical practitioners in decision making when initially assessing patients with PD and reviewing their progress and the effects of any treatment.
CD-MAE: Contrastive Dual-Masked Autoencoder Pre-Training Model for PCB CT Image Element Segmentation
Authors: Song Baojie , Chen Jian , Shi Shuhao , Yang Jie , Chen Chen , Qiao Kai , Yan Bin
Published: March 2024

Element detection is an important step in the process of the non-destructive testing of printed circuit boards (PCB) based on computed tomography (CT). Compared with the traditional manual detection method, the image semantic segmentation method based on deep learning greatly improves efficiency and accuracy. However, semantic segmentation models often require a large amount of data for supervised training to generalize better model performance. Unlike natural images, the PCB CT image annotation task is more time-consuming and laborious than the semantic segmentation task. In order to reduce the cost of labeling and improve the ability of the model to utilize unlabeled data, unsupervised pre-training is a very reasonable and necessary choice. The masked image reconstruction model represented by a masked autoencoder is pre-trained on the unlabeled data, learning a strong feature representation ability by recovering the masked image, and shows a good generalization ability in various downstream tasks. In the PCB CT image element segmentation task, considering the characteristics of the image, it is necessary to use a model with strong feature robustness in the pre-training stage to realize the representation learning on a large number of unlabeled PCB CT images. Based on the above purposes, we proposed a contrastive dual-masked autoencoder (CD-MAE) pre-training model, which can learn more robust feature representation on unlabeled PCB CT images. Our experiments show that the CD-MAE outperforms the baseline model and fully supervised models in the PCB CT element segmentation task.
Architectural Proposal for Low-Cost Brain–Computer Interfaces with ROS Systems for the Control of Robotic Arms in Autonomous Wheelchairs
Authors: Rivas Fernando , Sierra Jesús Enrique , Cámara Jose María
Published: March 2024

Neurodegenerative diseases present significant challenges in terms of mobility and autonomy for patients. In the current context of technological advances, brain–computer interfaces (BCIs) emerge as a promising tool to improve the quality of life of these patients. Therefore, in this study, we explore the feasibility of using low-cost commercial EEG headsets, such as Neurosky and Brainlink, for the control of robotic arms integrated into autonomous wheelchairs. These headbands, which offer attention and meditation values, have been adapted to provide intuitive control based on the eight EEG signal values read from Delta to Gamma (high and low/medium Gamma) collected from the users’ prefrontal area, using only two non-invasive electrodes. To ensure precise and adaptive control, we have incorporated a neural network that interprets these values in real time so that the response of the robotic arm matches the user’s intentions. The results suggest that this combination of BCIs, robotics, and machine learning techniques, such as neural networks, is not only technically feasible but also has the potential to radically transform the interaction of patients with neurodegenerative diseases with their environment.
Effects of Different Management Measures on Carbon Stocks and Soil Carbon Stocks in Moso Bamboo Forests: Meta-Analysis and Control Experiment
Authors: Zhao Ziliang , Tao Chunling , Liu Xu , Cheng Xuekun , Zhou Chi , Huang Siyao , Shou Menghan , Zhang Qihan , Huang Banghui , Li Chong , Tu Guoqing , Zhou Yufeng
Published: March 2024

As a crucial forest resource in southern China and a significant economic forest species for forestry production, moso bamboo has a notable influence on carbon stocks across the entire bamboo forest ecosystem. Studying the impact of different management measures on carbon stocks in moso bamboo forests and soil carbon stocks can assist bamboo forest operators in incorporating the carbon sequestration capacity of bamboo into forest production and management decisions, which can contribute to achieving carbon sequestration, emission reduction, and sustainable development in the decision-making processes of forest production and management. In this study, we utilized a randomized block design to investigate the changes in moso bamboo forests’ carbon stocks and soil carbon stocks under different management measures across three intensities: high-intensity intensive management (HT), moderate-intensity intensive management (MT), and regular management (CK). Additionally, we employed meta-analysis methods to enhance the accuracy of our conclusions. The experimental results showed that MT increased the carbon storage in moso bamboo forests by 19.86%, which was significantly different from CK (p < 0.05), while there was no significant difference between the HT group and the MT and CK groups. For soil carbon stocks, in the 10–30 m and 0–50 m soil layers, HT decreased soil carbon storage by 29.89% and 22.38%, while MT increased soil carbon storage by 64.15% and 31.02%, respectively. Both HT and MT were significantly different from CK (p < 0.05). However, for the soil layers of 0–10 m and 30–50 m, there was no significant difference between the treatments within the experimental group. The results of the meta-analysis indicate that, compared to traditional regular management, intensive management, especially high-intensity intensive management, can significantly increase the carbon storage in bamboo forests (p < 0.05). However, it will significantly reduce soil carbon storage (p < 0.05). Moreover, a significant difference in soil carbon storage is observed only within the 0–20 cm soil layer group. Therefore, from the perspective of the long-term ecological benefits of bamboo forest management, the selection of management measures should prioritize reasonable and moderate-intensity intensive management. Additionally, adopting appropriate and moderate-intensity fertilization, ploughing, and other management methods is recommended to enhance the productivity of moso bamboo forests while concurrently protecting the natural environment and improving the carbon sequestration capacity of moso bamboo forests.
Metabolomic and Transcriptomic Analyses Reveal the Molecular Mechanism Underlying the Massive Accumulation of Secondary Metabolites in Fenugreek (Trigonella foenum-graecum L.) Seeds
Authors: Zhao Qiuyu , Wu Guoxing , Yang Pu , Shi Yuanchong , Fu Zuoyi , Mo Haifeng , Shi Chunlan , Yu Shuhui
Published: March 2024

Fenugreek (Trigonella foenum-graecum L.) is a traditional medicinal plant for treating human diseases that is widely cultivated in many countries. However, the component and related metabolic pathways are still unclear. To understand the changes in expression of the component and related genes during seed development, this study employed metabolomic and transcriptomic analyses and integrative analysis to explore the metabolites and pathways involved in the growth of fenugreek. The antifungal activity of the fenugreek seeds was also analyzed. A total of 9499 metabolites were identified in the positive ion mode, and 8043 metabolites were identified in the negative ion mode. Among them, the main components were fatty acyls, prenol lipids, steroids, steroid derivatives, flavonoids, and isoflavonoids. Among these enriched pathways, the top 20 pathways were “flavone and flavonol biosynthesis”, “isoflavonoid biosynthesis”, and “flavonoid biosynthesis”. 3,7-Di-O-methylquercetin, flavonoids, pseudobaptigenin, isoflavonoids, methylecgonine, alkaloids, and derivatives were the most significantly upregulated metabolites. There were 38,137 differentially expressed genes (DEGs) identified via transcriptomic analysis. According to the KEGG pathway enrichment analysis, 147 DEGs were significantly enriched in “flavonoid biosynthesis”. Ten DEGs of the six key enzymes were found to be involved in three pathways related to flavonoid and alkaloid synthesis in fenugreek. The antifungal activity test revealed the inhibitory effect of the ethanol extract of fenugreek seeds on Alternaria tenuissima (Kunze)Wiltshire and Magnaporthe oryzae. These findings further prove that the use of botanical pesticides in fenugreek fruit has research value.
Spectrum of Mutations in PTPN11 in Russian Cohort
Authors: Orlova Anna , Guseva Daria , Demina Nina , Polyakov Aleksander , Ryzhkova Oksana
Published: March 2024

Noonan syndrome is a group of diseases with a similar clinical picture, consisting of 16 diseases caused by mutations in 15 genes. According to the literature, approximately half of all cases are attributed to Noonan syndrome type 1, NSML, caused by mutations in the PTPN11 gene. We analyzed 456 unrelated probands using a gene panel NGS, and in 206 cases, the cause of the disease was identified. Approximately half of the cases (107) were caused by variants in the PTPN11 gene, including three previously undescribed variants, one of which was classified as VOUS, and the other two as LP causative complex alleles. Frequent variants of the PTPN11 gene characteristics for Russian patients were identified, accounting for more than 38% (c.922A>G p.Asn308Asp, c.417G>C p.Glu139Asp, c.1403C>T p.Thr468Met) of all cases with mutations in the PTPN11 gene. A comparative characterization of frequent variants of the PTPN11 gene in different populations is shown. The most common features of Noonan syndrome in the studied sample were facial dysmorphisms and cardiovascular system abnormalities. A lower representation of patients with growth delay was observed compared to previously described samples.
Reframing the Refugee: Jenny Erpenbeck’s Compassionate Politics
Authors: Shaw Kristian
Published: March 2024

Countless polls, studies and surveys conducted prior to and following the 2016 UK Referendum on Membership of the European Union confirmed immigration to be the key emotive issue for not only the British electorate, but several Western European nations. By critiquing key pieces of EU legislation, Go, Went, Gone (2015) by Jenny Erpenbeck offers a humanising, caustic warning of the troubling politicisation of EU and non-EU migration in Germany, suggesting the ways by which literature can destabilise institutional optics of power and counteract myths surrounding the process of racial othering.
Effects of Diet on the Gut Bacterial Community of Aldrichina grahami (Diptera: Calliphoridae) across Developmental Stages
Authors: Li Zhen , Yue Chao , Ma Na , Yan Guanjie
Published: March 2024

The blowfly, Aldrichina grahami (Diptera: Calliphoridae), is a well-known forensically important insect. Basic data related to A. grahami have been well documented; but despite the pivotal role of gut microbes in various facets of insect biology, little is known about its gut microbiome. To investigate the gut bacterial community of A. grahami and explore its stability, diet and developmental stage were selected as the two variables. Larvae were reared on bovine liver, swine manure, and chicken manure, and high-throughput sequencing of the 1st, 2nd, and 3rd instar larvae and the newly emerged adults was performed. According to our results, the alpha diversity of the gut bacterial community did not significantly vary among different diets and developmental stages. Principal coordinate analysis revealed that the gut microbiome of A. grahami clustered together among different diets and developmental stages. The main phyla in the gut microbial community of A. grahami were Firmicutes and Proteobacteria, and the dominant genera were Vagococcus, Providencia, Lactobacillus, and Morganella. These findings characterized the gut microbiome of A. grahami and demonstrated that the gut bacterial community is fairly stable. The dominant genera Vagococcus, Providencia, Lactobacillus, and Morganella have the potential to serve as core microbiomes within the gut microbial community of A. grahami.
Enhancing Immune Response in Non-Small-Cell Lung Cancer Patients: Impact of the 13-Valent Pneumococcal Conjugate Vaccine
Authors: Smok-Kalwat Jolanta , Mertowska Paulina , Korona-Głowniak Izabela , Mertowski Sebastian , Niedźwiedzka-Rystwej Paulina , Bębnowska Dominika , Gosik Krzysztof , Stepulak Andrzej , Góźdź Stanisław , Roliński Jacek , Górecka Zofia , Siwiec Jan , Grywalska Ewelina
Published: March 2024

Background: Non-small-cell lung cancer (NSCLC) is one of the most frequently diagnosed diseases among all types of lung cancer. Infectious diseases contribute to morbidity and mortality by delaying appropriate anti-cancer therapy in patients with NSCLC. Methods: The study aimed to evaluate the effectiveness of vaccination with the 13-valent pneumococcal conjugate vaccine (PCV13) in 288 newly diagnosed NSCLC patients. The analysis of the post-vaccination response was performed after vaccination by assessing the frequency of plasmablasts via flow cytometry and by assessing the concentration of specific anti-pneumococcal antibodies using enzyme-linked immunosorbent assays. Results: The results of the study showed that NSCLC patients responded to the vaccine with an increase in the frequencies of plasmablasts and antibodies but to a lesser extent than healthy controls. The immune system response to PCV13 vaccination was better in patients with lower-stage NSCLC. We found higher antibody levels after vaccination in NSCLC patients who survived 5 years of follow-up. Conclusions: We hope that our research will contribute to increasing patients′ and physicians′ awareness of the importance of including PCV13 vaccinations in the standard of oncological care, which will extend the survival time of patients and improve their quality of life.
A Systemic Immune Inflammation Index and PD-L1 (SP142) Expression as a Potential Combined Biomarker of the Clinical Benefit of Chemo-Immunotherapy in Extensive-Stage Small-Cell Lung Cancer
Authors: Baek Jong-Min , Cha Hyungkeun , Moon Yeonsook , Kim Lucia , Kwak Seung Min , Park Eun Sun , Nam Hae-Seong
Published: March 2024

Background: No studies have identified combined biomarkers that may be more reasonable for the assessment of current chemo-immunotherapy in patients with extensive stage small-cell lung cancer (ES-SCLC). Methods: This study was conducted to investigate a combined biomarker with prognostic or predictive value in ES-SCLC. We determined the best independent prognostic biomarker among the four complete blood-count-derived inflammatory biomarkers (CBC-IBs). Subsequently, we analyzed the prognostic or predictive value of combining this independent CBC-IB with PD-L1 (SP142) expression. We prospectively assessed the SP142 analyses in tumor samples at diagnosis. Results: All in all, 55 patients with ES-SCLC were classified into four groups according to the systemic immune inflammation index (SII) (low/high) and SP142 (positive/negative). The best survival was observed in the low-SII/ SP142-positive group, whereas the worst survival was observed in the high-SII/SP142-negative group (p = 0.002). The combined SII-SP142 biomarker was better for predicting both survival and disease progression in patients with ES-SCLC. Conclusions: The combined SII-SP142 biomarker can be readily and universally obtained at a low cost in clinical practice, without requiring advanced genomics technology or specialized expertise. Although further studies are needed to confirm that the combined SII-SP142 biomarker is widely applicable, it should help clinicians to identify the best patients for combined chemotherapy with atezolizumab in ES-SCLC.
The Influence of Successful Treatment of Stress Urinary Incontinence and Pelvic Organ Prolapse on Depression, Anxiety, and Insomnia—A Prospective Intervention Impact Assessment Study
Authors: Kalata Urszula , Jarkiewicz Michał , Pomian Andrzej , Zwierzchowska Aneta Janina , Horosz Edyta , Majkusiak Wojciech , Rutkowska Beata , Barcz Ewa Monika
Published: March 2024

Introduction: The association between pelvic floor disorders (PFDs) and psychiatric conditions is an area of emerging interest. The causal direction of this relationship, however, remains ambiguous; it is unclear whether PFDs directly contribute to the deterioration of mental health or if pre-existing psychiatric conditions such as depression exacerbate the symptoms of PFDs. This study aimed to evaluate the effects of successful surgical treatment for stress urinary incontinence (SUI) and pelvic organ prolapse (POP) on symptoms of depression, anxiety, and insomnia. Materials and Methods: This investigation focused on patients who underwent successful surgical interventions for SUI and POP. Both subjective and objective symptoms of PFDs, along with psychiatric status, were assessed before and after the surgical procedures. Results: This study found that successful surgical treatment of SUI and POP led to a significant reduction in anxiety scores. Additionally, in patients with SUI, successful treatment was objectively associated with a decrease in the severity of insomnia. Alleviation of symptoms associated with the lower urinary tract, prolapse, and colorectal–anal region following POP surgery was correlated with improvements in depression and anxiety but not insomnia. Subjectively assessed improvements in SUI subjective symptoms were linked to reductions in the severity of depression, anxiety, and insomnia in patients who underwent anti-incontinence surgery. Conclusions: These findings suggest a potential cause-and-effect relationship between PFDs and certain psychiatric disorders, highlighting the importance of successful treatment of PFDs in mitigating symptoms of depression, anxiety, and insomnia.
Economic Cost of Rehabilitation with Robotic and Virtual Reality Systems in People with Neurological Disorders: A Systematic Review
Authors: Cano-de-la-Cuerda Roberto , Blázquez-Fernández Aitor , Marcos-Antón Selena , Sánchez-Herrera-Baeza Patricia , Fernández-González Pilar , Collado-Vázquez Susana , Jiménez-Antona Carmen , Laguarta-Val Sofía
Published: March 2024

Background: The prevalence of neurological disorders is increasing worldwide. In recent decades, the conventional rehabilitation for people with neurological disorders has been often reinforced with the use of technological devices (robots and virtual reality). The aim of this systematic review was to identify the evidence on the economic cost of rehabilitation with robotic and virtual reality devices for people with neurological disorders through a review of the scientific publications over the last 15 years. Methods: A systematic review was conducted on partial economic evaluations (cost description, cost analysis, description of costs and results) and complete (cost minimization, cost-effectiveness, cost utility and cost benefit) studies. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed. The main data sources used were PubMed, Scopus and Web of Science (WOS). Studies published in English over the last 15 years were considered for inclusion in this review, regardless of the type of neurological disorder. The critical appraisal instrument from the Joanna Briggs Institute for economic evaluation and the Consolidated Health Economic Evaluation Reporting Standards (CHEERS) were used to analyse the methodological quality of all the included papers. Results: A total of 15 studies were included in this review. Ten papers were focused on robotics and five on virtual reality. Most of the studies were focused on people who experienced a stroke. The robotic device most frequently used in the papers included was InMotion® (Bionik Co., Watertown, MA, USA), and for those focused on virtual reality, all papers included used semi-immersive virtual reality systems, with commercial video game consoles (Nintendo Wii® (Nintendo Co., Ltd., Kyoto, Japan) and Kinect® (Microsoft Inc., Redmond, WA, USA)) being used the most. The included studies mainly presented cost minimization outcomes and a general description of costs per intervention, and there were disparities in terms of population, setting, device, protocol and the economic cost outcomes evaluated. Overall, the methodological quality of the included studies was of a moderate level. Conclusions: There is controversy about using robotics in people with neurological disorders in a rehabilitation context in terms of cost minimization, cost-effectiveness, cost utility and cost benefits. Semi-immersive virtual reality devices could involve savings (mainly derived from the low prices of the systems analysed and transportation services if they are applied through telerehabilitation programmes) compared to in-clinic interventions.
The Clinical Utility of Lower Extremity Dual-Energy CT Angiography in the Detection of Bone Marrow Edema in Diabetic Patients with Peripheral Artery Disease
Authors: Floridi Chiara , Cacioppa Laura Maria , Valeri Tommaso , Rossini Nicolo , Rosati Marzia , Vento Vincenzo , Felicioli Alessandro , Macchini Marco , Candelari Roberto , Carotti Marina , Giovagnoni Andrea
Published: March 2024

(1) Background: Type 2 diabetes is a major cause of incidences and the progression of peripheral artery disease (PAD). Bone marrow edema (BME) is an important finding suggestive of underlying bone inflammation in non-traumatic diabetic patients with PAD. Our aim was to evaluate the presence, severity, and clinical implications of BME detected by virtual non-calcium application (VNCa) of dual-energy CT angiography (DE-CTA). (2) Methods: A consecutive series of 76 diabetic patients (55 men; mean age 71.6 ± 11.2 yrs) submitted to lower limb DE-CTA for PAD evaluation and revascularization planning, which were retrospectively analyzed. VNCa images were independently and blindly revised for the presence, location, and severity of BME by two radiologists with 10 years of experience. BME and non-BME groups were evaluated in terms of PAD clinical severity and 6-month secondary major amputation rate. (3) Results: BME was present in 17 (22%) cases, while 59 (78%) patients were non-BME. The BME group showed a significantly higher incidence of major amputation (p < 0.001) and a significantly higher number of patients with advanced clinical stages of PAD compared to the non-BME group (p = 0.024). (4) Conclusions: Lower limb DE-CTA with VNCa application is a useful tool in the detection of BME in diabetic patients with PAD, simultaneously enabling the evaluation of the severity and location of the arterial disease for revascularization planning. BME presence could be a marker of clinically severe PAD and a possible risk factor for revascularization failure.
Can Robotic Gait Training with End Effectors Improve Lower-Limb Functions in Patients Affected by Multiple Sclerosis? Results from a Retrospective Case–Control Study
Authors: Bonanno Mirjam , Maggio Maria Grazia , Ciatto Laura , De Luca Rosaria , Quartarone Angelo , Alibrandi Angela , Calabrò Rocco Salvatore
Published: March 2024

Background: Multiple sclerosis (MS) is characterized as a neurodegenerative condition possibly triggered by autoimmune mechanisms, impacting the entire central nervous system. In this context, neurorehabilitation plays a crucial role in every phase of the disease, aiming to restore and preserve motor functions in MS patients. In particular, robotic gait training (RGT) allows intensive, repetitive, and task-oriented training, which is pivotal in boosting neuroplastic processes. Thus, the primary aim of our study is to evaluate the effectiveness of innovative robotic gait training, using the G-EO system, on gait, functional abilities, and quality of life (QoL) in patients affected by MS. Secondly, we evaluated the effect of the robotic rehabilitation on lower-limb motor functioning, balance, sensation, and joint functioning. Methods: The study involved twenty MS patients, divided into two groups with comparable medical characteristics and rehabilitation training duration. The experimental group (EG) underwent robotic gait training with the G-EO system (n. 10), while the control group (CG) received traditional rehabilitation training (n. 10). Results: Both groups exhibited improvements in disability level (Functional Independence Measure), 10 m walking distance (10MWT), gait, and balance performance (Functional Ambulation Classification, Tinetti Scale). However, the EG demonstrated a more significant improvement. The G-EO system notably reduced spasticity in the lower limbs (Modified Ashworth Scale) exclusively in the EG. Discussion: This study suggests that the G-EO system could be a valuable tool for enhancing gait functions, including lower-limb movements, functional abilities, and QoL in individuals with MS.
Exploring the Potential of IL-4 and IL-13 Plasma Levels as Biomarkers in Atopic Dermatitis
Authors: Mitroi George G. , Pleșea Elena Leocadia , Mitroi George F. , Mitroi Mihaela Roxana , Neagoe Carmen Daniela , Ianoși Simona Laura
Published: March 2024

Atopic dermatitis (AD) is a persistent inflammatory skin condition that impacts individuals of various age groups, including both children and adults. Its pathophysiology involves allergens penetrating a disrupted epidermal barrier, triggering the dermal cells to produce pro-inflammatory cytokines and eliciting a T-cell-mediated immune response. Notably, interleukins (ILs), particularly interleukin 4 (IL-4) and interleukin 13 (IL-13), play a key role in AD pathogenesis. Therapies directed at inflammatory mechanisms, including Dupilumab, have demonstrated notable effectiveness in enhancing skin lesions, alleviating subjective symptoms, and improving the overall quality of life for individuals with AD. Despite therapeutic advances, assessing AD severity remains challenging. The commonly used tools, such as the SCORAD and DLQI scores, rely on subjective patient responses. Paraclinically, the search for universal biomarkers continues, with efforts to identify reliable indicators reflecting disease severity and treatment response. Various biomarkers, including Th2-related chemokines and cytokines, have been explored, but none have gained universal recognition for routine clinical use. This study aims to investigate the dynamics of the plasma levels of IL-4 and IL-13 during Dupilumab treatment and establish correlations between these ILs and disease severity, as measured using the SCORAD and DLQI scores. The ultimate endpoint is to determine whether IL-4 and IL-13 can serve as reliable biomarkers, assessing their correlation with patient-reported feelings and disease activity and potentially influencing their inclusion or exclusion as diagnostic elements in routine clinical practice.
Deep Learning Super-Resolution Technique Based on Magnetic Resonance Imaging for Application of Image-Guided Diagnosis and Surgery of Trigeminal Neuralgia
Authors: Hwang Jun Ho , Park Chang Kyu , Kang Seok Bin , Choi Man Kyu , Lee Won Hee
Published: March 2024

This study aimed to implement a deep learning-based super-resolution (SR) technique that can assist in the diagnosis and surgery of trigeminal neuralgia (TN) using magnetic resonance imaging (MRI). Experimental methods applied SR to MRI data examined using five techniques, including T2-weighted imaging (T2WI), T1-weighted imaging (T1WI), contrast-enhancement T1WI (CE-T1WI), T2WI turbo spin–echo series volume isotropic turbo spin–echo acquisition (VISTA), and proton density (PD), in patients diagnosed with TN. The image quality was evaluated using the peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM). High-quality reconstructed MRI images were assessed using the Leksell coordinate system in gamma knife radiosurgery (GKRS). The results showed that the PSNR and SSIM values achieved by SR were higher than those obtained by image postprocessing techniques, and the coordinates of the images reconstructed in the gamma plan showed no differences from those of the original images. Consequently, SR demonstrated remarkable effects in improving the image quality without discrepancies in the coordinate system, confirming its potential as a useful tool for the diagnosis and surgery of TN.
Phase Equilibrium Study of Rare Earth Oxide–Fluoride Salt System: A Review
Authors: Zhou Quan , Liao Jinfa , Liao Chunfa , Zhao Baojun
Published: March 2024

The applications of rare earth metals and alloys are becoming increasingly widespread and there is a strong market demand. Currently, most of the production enterprises adopt the fluoride–oxide system for electrolytic preparation of rare earth metals and alloys. The solubility of rare earth oxides in molten salt directly affects the selection of operational parameters in the electrolysis process. When the added amount of RE2O3 is less than its solubility, it leads to a decreased electrolytic efficiency. Conversely, an excessive amount of oxide is prone to settle at the bottom of the electrolytic cell, impeding smooth production. The RE2O3 solubility in the fluoride salt can be represented by the phase equilibrium of the RE2O3-REF3-LiF system. The isothermal lines in the primary phase field of rare earth oxide represent the solubility of the oxide in the fluoride salt at the corresponding temperature. This paper outlines the research methods and experimental results on the phase equilibria of the RE2O3-REF3-LiF system. The characteristics and existing problems in the current phase equilibrium study are analyzed. The solubility data of RE2O3 are expressed in the forms of ternary and pseudo-binary phase diagrams of the RE2O3-REF3-LiF system, providing theoretical guidance for the establishment of an accurate and reliable rare earth electrolysis system database and the optimization of electrolytic processes.
Pesticides: Unintended Impact on the Hidden World of Gut Microbiota
Authors: Ali Asghar , AlHussaini Khalid I.
Published: March 2024

A vast range of pesticides have been routinely employed for plant protection throughout the last few decades. Pesticides can enter non-target organisms in various ways, posing health hazards. Exposure to different environmental pollutants, including pesticides, can affect the human gut flora. Metabolites generated from the gut microbiota play an essential role in the host’s health by regulating metabolic homeostasis. A disruption in this equilibrium can lead to the emergence of numerous illnesses and their etiology. Pesticides have been shown in a few recent studies to harm the host’s gut microbiome. As a result, there is an urgent need to investigate the impact of pesticides on gut microbiota-mediated immunity. Metabolic alterations in the host may give a better understanding of pesticide-induced harm. This review highlights the potential consequences of pesticide exposure on gut microbiota composition and function, mainly focusing on how it might alter the production of secondary metabolites with potential downstream implications for host health.
Source Analysis and Contribution Estimation of Heavy Metal Contamination in Agricultural Soils in an Industrial Town in the Yangtze River Delta, China
Authors: Qi Chao , Xu Mingzuan , Liu Jiandong , Li Chuang , Yang Binbin , Jin Zhipeng , Liang Shengyue , Guo Bingyue
Published: March 2024

Farmland soil quality is a crucial determinant for agricultural productivity, food safety, and human well-being. Among the various contaminants, heavy metals have emerged as pervasive factors significantly impacting farmland quality, attracting widespread societal concern. In this study, we systematically applied multivariate statistical analysis, geostatistical methods, and the positive matrix factorization (PMF) source apportionment technique to elucidate the sources and contributions of eight heavy metals (Cd, Hg, As, Pb, Cr, Cu, Zn, Ni) in farmland soils within an industrialized town. Our findings reveal that Cd, Hg, Pb, and Zn exhibit pollution or enrichment in farmland soils compared to natural background levels, with Hg and Cd surpassing 164.3% and 50.2%, respectively. Notably, Zn demonstrates discernible point-source pollution. Source apportionment results highlight industrial point sources, coal combustion, and agriculture as the primary anthropogenic contributors to heavy metal contamination, with zinc-plating enterprises being the predominant industrial point sources. Addressing the specific issue of point-source pollution from Zn in industrial activities, further analysis establishes a correlation between soil Zn content and the distance from zinc-plating enterprises. Utilizing an atmospheric transport model, we observe that the impact of industrial activities on soil Zn is limited when the distance exceeds 1.5 km, emphasizing the importance of monitoring Zn pollution within areas less than 1.5 km. This study pioneers a progressive source apportionment approach, considering the origins of different heavy metals, pollution levels, distance factors, and the cost-effectiveness of environmental measures. The insights gained provide scientifically sound strategies for future decision making in environmental protection.
Ultra-Thin Ion Exchange Membranes by Low Ionomer Blending for Energy Harvesting
Authors: Jung Jaehoon , Choi Soyeong , Kang Ilsuk , Choi Kiwoon
Published: March 2024

Exploring the utilization of ion exchange membranes (IEMs) in salinity gradient energy harvesting, a technique that capitalizes on the salinity difference between seawater and freshwater to generate electricity, this study focuses on optimizing PVDF to Nafion ratios to create ultra-thin membranes. Specifically, our investigation aligns with applications such as reverse electrodialysis (RED), where IEMs facilitate selective ion transport across salinity gradients. We demonstrate that membranes with reduced Nafion content, particularly the 50:50 PVDF:Nafion blend, retain high permselectivity comparable to those with higher Nafion content. This challenges traditional understandings of membrane design, highlighting a balance between thinness and durability for energy efficiency. Voltage–current analyses reveal that, despite lower conductivity, the 50:50 blend shows superior short-circuit current density under salinity gradient conditions. This is attributed to effective ion diffusion facilitated by the blend’s unique microstructure. These findings suggest that blended membranes are not only cost-effective but also exhibit enhanced performance for energy harvesting, making them promising candidates for sustainable energy solutions. Furthermore, these findings will pave the way for advances in membrane technology, offering new insights into the design and application of ion exchange membranes in renewable energy.