bluuebunny/crossref_metadata_2025 huggingface dataset:
In Vitro Evaluation of DNA Damage Induction by Silver (Ag), Gold (Au), Silica (SiO2), and Aluminum Oxide (Al2O3) Nanoparticles in Human Peripheral Blood Mononuclear Cells
Authors: Babonaitė Milda , Striogaitė Emilija , Grigorianaitė Goda , Lazutka Juozas Rimantas
Published: July 2024

Nanoparticles (NPs) are increasingly applied in a wide range of technological and medical applications. While their use offers numerous benefits, it also raises concerns regarding their safety. Therefore, understanding their cytotoxic effects and DNA-damaging properties is crucial for ensuring the safe application of NPs. In this study, DNA-damaging properties of PVP-coated silver, silica, aluminum oxide (13 nm and 50 nm), and gold (5 nm and 40 nm) NPs in human peripheral blood mononuclear cells (PBMCs) were investigated. NPs‘ internalization and induction of reactive oxygen species were evaluated using flow cytometry. Cytotoxic properties were determined using a dual acridine orange/ethidium bromide staining technique while DNA-damaging properties were assessed using an alkaline comet assay. We observed that Ag, SiO2, and both sizes of Al2O3 NPs were efficiently internalized by human PBMCs, but only PVP-AgNPs (at 10–30 µg/mL) and SiO2 NPs (at concentrations > 100 µg/mL) induced significant DNA damage after a 24 h exposure. In contrast, the uptake of both sizes of gold nanoparticles was limited, though they were able to cause significant DNA damage after a 3 h exposure. These findings highlight the different responses of human PBMCs to various NPs, emphasizing the importance of their size, composition, and internalization rates in nanotoxicology testing.
Design and Evaluation of a Hypersonic Waverider Vehicle Using DSMC
Authors: Klothakis Angelos , Nikolos Ioannis K.
Published: July 2024

This work investigates the aerodynamic performance of a hypersonic waverider designed to operate at Mach 7, focusing on optimizing its design through advanced computational methods. Utilizing the Direct Simulation Monte Carlo (DSMC) method, the three-dimensional flow field around the specifically designed waverider was simulated to understand the shock wave interactions and thermal dynamics at an altitude of 90 km. The computational approach included detailed meshing around the vehicle’s critical leading edges and the use of three-dimensional iso-surfaces of the Q-criterion to map out the shock and vortex structures accurately. Additional simulation results demonstrate that the waverider achieved a lift–drag ratio of 2.18, confirming efficient aerodynamic performance at a zero-degree angle of attack. The study’s findings contribute to the broader understanding of hypersonic flight dynamics, highlighting the importance of precise computational modeling in developing vehicles capable of operating effectively in near-space environments.
Itch-Relieving Cosmetics
Authors: Han Ju Hee , Kim Hei Sung
Published: July 2024

This review aims to explore the evolving role of cosmetics in alleviating itch, transcending their traditional aesthetic function. With a focus on formulations enriched with natural oils and other bioactive components, we examine the efficacy and safety of various cosmetic ingredients designed to control itch. Highlighted are ingredients such as colloidal oatmeal, postbiotics, menthol, peppermint, cryosim-1, capsaicin, asivatrep, polidocanol, pramoxine hydrocholoride, and palmitoylethanolamide, which are recognized to reduce itch. Special attention is also given to phytochemicals that can modulate the Janus kinase/signal transducer and activator of transcription signaling pathway and carry the potential as an itch-relieving cosmetic ingredient. This review encompasses clinical studies that verify the itch relieving effect of these cosmetic ingredients. By integrating current scientific evidence, we aim to shed light on the potential of anti-itch cosmetics as an adjunct to standard itch treatment, thereby broadening our understanding of their role in dermatological care.
Endoscopic Grading and Sampling of Gastric Precancerous Lesions: A Comprehensive Literature Review
Authors: Tziatzios Georgios , Ziogas Dimitrios Ι. , Gkolfakis Paraskevas , Papadopoulos Vasilios , Papaefthymiou Apostolis , Mathou Nikoletta , Giannakopoulos Athanasios , Gerasimatos Gerasimos , Paraskeva Konstantina D. , Triantafyllou Konstantinos
Published: July 2024

Gastric cancer remains a disease with an ominous prognosis, while early gastric cancer has a good-to-excellent prognosis, with 5-year survival rates of up to 92.6% after successful endoscopic resection. In this context, the accurate identification of patients with established gastric precancerous lesions, namely chronic atrophic gastritis and intestinal metaplasia, is the first step in a stepwise approach to minimize cancer risk. Although current guidelines advocate for the execution of random biopsies to stage the extent and severity of gastritis/intestinal metaplasia, modern biopsy protocols are still imperfect as they have limited reproducibility and are susceptible to sampling error. The advent of novel imaging-enhancing modalities, i.e., high-definition with virtual chromoendoscopy (CE), has revolutionized the inspection of gastric mucosa, leading to an endoscopy-based staging strategy for the management of these premalignant changes in the stomach. Nowadays, the incorporation of CE-targeted biopsies in everyday clinical practice offers not only the robust detection of premalignant lesions but also an improvement in quality, by reducing missed diagnoses along with mean biopsies and, thus, the procedural costs and the environmental footprint. In this review, we summarize the recent evidence regarding the endoscopic grading and sampling of gastric precancerous lesions.
Seasonal Variability in Non-Structural Carbohydrate Content of Warm-Adapted Zostera noltei and Zostera marina Populations
Authors: Azcárate-García Tomás , Beca-Carretero Pedro , Hernández Ignacio , Brun Fernando G.
Published: July 2024

Non-structural carbohydrates (NSCs) are energetic compounds that can be accumulated in tissues and mobilized during periods of unfavorable conditions to maintain the biological functions of plants. The balance of these biochemical compounds is controlled by environmental factors such as temperature and irradiance. Zostera noltei and Zostera marina find one of their southern distribution limits in southern Spain, where relatively high seawater temperatures are reached during summer (23–24 °C). To better understand the effects of elevated temperatures on the concentration of NSCs, we conducted a seasonal study at Cadiz Bay, representing warm-adapted populations of these species. Our results showed a bimodal pattern in both species, with the highest NSC content observed in December and June, followed by a depletion in March and August. In addition, the NSC content observed in the leaves of Z. noltei (71.26 ± 30.77 mg g−1 dry weight) was higher than in the rhizomes and roots (52.14 ± 38.86 mg g−1 DW). The observed patterns suggest that these species accumulated NSCs to cope with periods of unfavorable environmental conditions. We also suggest that the limited concentration of NSCs in Z. noltei rhizomes and roots indicates that this population may be suffering physiological stress.
The Use of Insulin Pen Needles: The Italian Society of Metabolism, Diabetes, and Obesity (SIMDO) Consensus
Authors: Tonolo Giancarlo , DeMonte Ariella , Taras Maria Antonietta , Scorsone Alessandro , Tatti Patrizio , Pittui Battistina , Turco Salvatore , Trentin Riccardo
Published: July 2024

A correct injection technique is essential in order to ensure the effectiveness of insulin and to achieve good metabolic control, and the use of suitable needles is fundamental. Today, technological evolution has transformed insulin needles into innovative tools able to guarantee an effective and safe administration of insulin, to reduce local complications, such as lipodystrophies that are an obstacle to the effectiveness of the treatment itself, and to minimize the pain of the injection, a crucial factor in the acceptance of therapy and for compliance. The steering committee of the scientific society SIMDO has commissioned the scientific committee and some members of the board to draw up an official SIMDO point of view/consensus on the use of insulin needles. In this way, a group that has combined the experience gained in their field of expertise—diabetologists operating in the public and private sectors, nurses, psychologists, and patients—was set up. The aim is to give indications regarding insulin injection techniques, combining themes such as technology innovation, education in self-management, and psychological support for the patient into a unified approach based on the priority area of patient quality of life. The document will provide operational recommendations that integrate the directions regarding the standards of care for diabetes resulting from the most recent scientific acquisitions with the concept of quality at 360°, as it emerged from the point of view of all the operators involved, but with the patient’s interests as a central focal point.
Neonatal Outcomes after Maternal Biomarker-Guided Preterm Birth Intervention: The AVERT PRETERM Trial
Authors: Hoffman Matthew K. , Kitto Carrie , Zhang Zugui , Shi Jing , Walker Michael G. , Shahbaba Babak , Ruhstaller Kelly
Published: July 2024

The AVERT PRETERM trial (NCT03151330) evaluated whether screening clinically low-risk pregnancies with a validated maternal blood biomarker test for spontaneous preterm birth (sPTB) risk, followed by preventive treatments for those screening positive, would improve neonatal outcomes compared to a clinically low-risk historical population that had received the usual care. Prospective arm participants with singleton non-anomalous pregnancies and no PTB history were tested for sPTB risk at 191/7–206/7 weeks’ gestation and followed up with after neonatal discharge. Screen-positive individuals (≥16% sPTB risk) were offered vaginal progesterone (200 mg) and aspirin (81 mg) daily, with twice-weekly nurse phone calls. Co-primary outcomes were neonatal morbidity and mortality, measured using a validated composite index (NMI), and neonatal hospital length of stay (NNLOS). Endpoints were assessed using survival analysis and logistic regression in a modified intent-to-treat population comprising screen-negative individuals and screen-positive individuals accepting treatment. Of 1460 eligible participants, 34.7% screened positive; of these, 56.4% accepted interventions and 43.6% declined. Compared to historical controls, prospective arm neonates comprising mothers accepting treatment had lower NMI scores (odds ratio 0.81, 95% CI, 0.67–0.98, p = 0.03) and an 18% reduction in severe morbidity. NNLOS was shorter (hazard ratio 0.73, 95% CI, 0.58–0.92, p = 0.01), with a 21% mean stay decrease among neonates having the longest stays. Sensitivity analyses in the entire intent-to-treat population supported these findings. These results suggest that biomarker sPTB risk stratification and preventive interventions can ameliorate PTB complications in singleton, often nulliparous, pregnancies historically deemed low risk.
Using High-Resolution Vessel Wall Magnetic Resonance Images in a Patient of Intracranial Artery Dissection Related Acute Infarction
Authors: Lin Chia-Yu , Chen Hung-Chieh , Wu Yu-Hsuan
Published: July 2024

Acute ischemic stroke in young adults typically carries significant implications for morbidity, mortality, and long-term disability. In this study, we describe the case of a 34-year-old male with no prior medical history who presented with symptoms of right-sided weakness and slurred speech, suggesting an acute ischemic stroke. Initial CT angiography revealed an occlusion in the left M2 segment middle cerebral artery (MCA). The occlusion was successfully recanalized through emergent endovascular thrombectomy, which also identified a dissection as the cause of the stroke. Follow-up assessments at 3 days and three months, which included advanced vessel wall MRI, highlighted the critical role of intracranial artery dissection in strokes among young adults and provided essential images for ongoing evaluation.
Influence of Covariates on 18F-FDG PET/CT Diagnostic Accuracy for Liver Metastasis
Authors: Habouzit Vincent , Flaus Anthime , Phelip Jean-Marc , Grange Sylvain , Le Roy Bertrand , Grange Rémi , Prévot Nathalie
Published: July 2024

(1) Background: 18F-FDG PET/CT diagnostic accuracy for liver metastasis (LM) could be influenced by technical parameters, lesion size, and the patient’s covariates. This retrospective study aimed to evaluate these covariates’ impact on PET/CT sensitivity. (2) Methods: Consecutive patients with suspected LMs who underwent 18F-FDG PET/CT scans were included. PET/CT scans were interpreted visually. The reference standard integrated histopathological and imaging follow-up. Logistic regression modeling and average marginal predictions were used to calculate per-lesion diagnostic performance measures with cluster robust 95% confidence intervals and to assess the covariates’ impact on PET/CT sensitivity. (3) Results: We included 192 patients with 330 lesions. 18F-FDG PET/CT exhibited a per-lesion sensitivity, specificity, positive predictive value, and negative predictive value of 86%, 79%, 91%, and 69%, respectively. In multivariate analysis, TOF PET/CT exhibited a higher sensitivity than non-TOF PET/CT (91% vs. 78%, p = 0.02). Sensitivity was reduced for lesions < 10 mm compared to larger lesions (56% vs. 93%, p < 0.001). A 5 kg/m2 increase in BMI led to an average 5% sensitivity reduction (p < 0.001). Age, sex, blood glucose level below 11 mmol/L, and liver density did not significantly impact sensitivity (p > 0.05). (4) Conclusions: 18F-FDG PET/CT sensitivity might be reduced with non-TOF PET, lesions < 10 mm, and higher BMI.
Utilizing Esophageal Motility Tests in Diagnosing and Evaluating Gastroesophageal Reflux Disease
Authors: Yang Wangliu , Huang Yurong , He Lei , Chen Dongmei , Wu Sheng , Tian Yan , Zheng Juan , Yang Jie , Song Gengqing
Published: July 2024

Gastroesophageal reflux disease (GERD), a prevalent clinical condition, is often attributed to aberrant esophageal motility, leading to gastric content reflux and associated symptoms or complications. The rising incidence of GERD presents an escalating healthcare challenge. Endoscopic and esophageal reflux monitoring can provide a basis for the diagnosis of patients with gastroesophageal reflux disease, but when the diagnostic basis is at an inconclusive value, some additional supportive evidence will be needed. Advanced technology is the key to improving patient diagnosis, accurate assessment, and the development of effective treatment strategies. High-resolution esophageal manometry (HREM) and endoscopic functional lumen imaging probe (EndoFLIP) represent the forefront of esophageal motility assessment. HREM, an evolution of traditional esophageal manometry, is considered the benchmark for identifying esophageal motility disorders. Its widespread application in esophageal dynamics research highlights its diagnostic significance. Concurrently, EndoFLIP’s emerging clinical relevance is evident in diagnosing and guiding the treatment of coexisting esophageal motility issues. This review integrates contemporary research to delineate the contributions of HREM, EndoFLIP, and novel technologies in GERD. It examines their efficacy in facilitating an accurate diagnosis, differentiating similar gastrointestinal disorders, quantifying the extent of reflux, assessing the severity of the disease, forecasting patient responsiveness to proton pump inhibitor therapy, and guiding decisions for surgical interventions. The overarching aim is to deepen the understanding of GERD’s underlying mechanisms and advance the formulation of holistic, efficacious treatment approaches.
A Novel Hybrid Machine Learning-Based System Using Deep Learning Techniques and Meta-Heuristic Algorithms for Various Medical Datatypes Classification
Authors: Kadhim Yezi Ali , Guzel Mehmet Serdar , Mishra Alok
Published: July 2024

Medicine is one of the fields where the advancement of computer science is making significant progress. Some diseases require an immediate diagnosis in order to improve patient outcomes. The usage of computers in medicine improves precision and accelerates data processing and diagnosis. In order to categorize biological images, hybrid machine learning, a combination of various deep learning approaches, was utilized, and a meta-heuristic algorithm was provided in this research. In addition, two different medical datasets were introduced, one covering the magnetic resonance imaging (MRI) of brain tumors and the other dealing with chest X-rays (CXRs) of COVID-19. These datasets were introduced to the combination network that contained deep learning techniques, which were based on a convolutional neural network (CNN) or autoencoder, to extract features and combine them with the next step of the meta-heuristic algorithm in order to select optimal features using the particle swarm optimization (PSO) algorithm. This combination sought to reduce the dimensionality of the datasets while maintaining the original performance of the data. This is considered an innovative method and ensures highly accurate classification results across various medical datasets. Several classifiers were employed to predict the diseases. The COVID-19 dataset found that the highest accuracy was 99.76% using the combination of CNN-PSO-SVM. In comparison, the brain tumor dataset obtained 99.51% accuracy, the highest accuracy derived using the combination method of autoencoder-PSO-KNN.
Evaluation of Biomarkers of Bone Metabolism on Salivary Matrix in the Remodeling of Periodontal Tissue during Orthodontic Treatment
Authors: Cazzolla Angela Pia , Brescia Vincenzo , Lovero Roberto , Fontana Antonietta , Giustino Arcangela , Dioguardi Mario , Di Comite Maria Severa , Di Serio Francesca , Ciavarella Domenico , Crincoli Vito
Published: July 2024

The aim of this study was to evaluate changes in the concentration of N-terminal type I collagen extension pro-peptide (PINP), tartrate-resistant acid phosphatase (TRAcP), and parathyroid hormone-related protein (PTHrP) in saliva during orthodontic treatment in order to evaluate whether changes in bone turnover marker (BTM) concentration can help highlight the effects of orthodontic mechanical loading in the absence of clinical evidence of tooth movement in terms of tooth movement. Saliva samples from 25 apparently healthy young subjects (10 females and 15 males) were collected using Salivette® (Sarstedt) with cotton swabs and the concentrations of PTHrP, TRAcP 5b, and PINP were analyzed at time 0 (T1), 25 days (T2), and at 45 days (T3). Differences in the median value of biomarker levels between baseline T1 and follow-up of the different groups (T2 and T3) were assessed using the non-parametric Mann–Whitney U test. Trough concentrations of P1NP, PTHrP, and TRAcP were 0.80 µg/L, 0.21 ng/mL, and 0.90 U/L above the method LOD. The non-parametric Mann–Whitney U test confirmed a statistically significant difference in T1 versus concentrations of T2 and T3. All subjects evaluated had a statistically significant difference between T1 vs. T3. when compared with the specific critical difference (RCV) for the analyte The results obtained demonstrate that the evaluation of BTM changes in saliva can help the evaluation of orthodontic procedures and the monitoring of biomechanical therapy.
Granular Cities
Authors: Esquierro Leon , Da Silva Sergio
Published: July 2024

This study extends the concept of granularity from firms to cities, examining how large cities influence national economic dynamics beyond their relative size. By applying Zipf’s law, which describes the power law distribution of city sizes, we investigate the interplay between granularity and business cycles. Our aim is to test the granular hypothesis that large cities have a significant impact on the business cycle beyond their relative size. We analyze data from American and Brazilian cities between 2003 and 2019 assessing the granular residuals and their explanatory power. Our findings reveal that in the United States, the granular city size is three metropolitan areas or five counties when redefined. In Brazil, it equates to three municipalities. These results emphasize the substantial role large cities play in national economic fluctuations, suggesting that policy interventions that target infrastructure, education, and innovation in major urban centers could have widespread economic benefits. This paper’s contribution to the literature is to highlight a spatial component of granularity not considered so far.
The Moderating Effects of Gender and Study Discipline in the Relationship between University Students’ Acceptance and Use of ChatGPT
Authors: Elshaer Ibrahim A. , Hasanein Ahmed M. , Sobaih Abu Elnasr E.
Published: July 2024

The intensive adoption of ChatGPT by university students for learning has encouraged many scholars to test the variables that impact on their use of such AI in their learning. This study adds to the growing body of studies, especially in relation to the moderating role of students’ gender and their study discipline in their acceptance and usage of ChatGPT in their learning process. This study expanded the Unified Theory of Acceptance and Use of Technology (UTAUT) by integrating gender as well as study disciplines as moderators. The study collected responses from students in Saudi universities with different study disciplines and of different genders. The results of a structural model using Smart PLS showed a significant moderating effect of gender on the relationship between performance expectancy and ChatGPT usage. The results confirmed that the impact of performance expectancy in fostering ChatGPT usage was stronger in male than in female students. Moreover, social influence was shown to significantly affect males more than females in relation to ChatGPT usage. In addition, the findings showed that study discipline significantly moderates the link between social influence and ChatGPT usage. In the same vein, social influence significantly influences ChatGPT use in social sciences more than in applied sciences. Hence, the various implications of the study were discussed.
A Deep Learning-Based Intrusion Detection Model Integrating Convolutional Neural Network and Vision Transformer for Network Traffic Attack in the Internet of Things
Authors: Du Chunlai , Guo Yanhui , Zhang Yuhang
Published: July 2024

With the rapid expansion and ubiquitous presence of the Internet of Things (IoT), the proliferation of IoT devices has reached unprecedented levels, heightening concerns about IoT security. Intrusion detection based on deep learning has become a crucial approach for safeguarding IoT ecosystems. However, challenges remain in IoT intrusion detection research, including inadequate feature representation at the classifier level and poor correlation among extracted traffic features, leading to diminished classification accuracy. To address these issues, we propose a novel transformer-based IoT intrusion detection model, MBConv-ViT (MobileNet Convolution and Vision Transformer), which enhances the correlation of extracted features by fusing local and global features. By leveraging the high correlation of traffic flow, our model can identify subtle differences in IoT traffic flow, thereby achieving precise classification of attack traffic. Experiments based on the open datasets TON-IoT and Bot-IoT demonstrate that the accuracy of the MBConv-ViT model, respectively, 97.14% and 99.99%, is more effective than several existing typical models.
Influence of Performance Packages on Fuel Consumption and Exhaust Emissions of Passenger Cars and Commercial Vehicles under WLTP
Authors: Marchitto Luca , Costagliola Maria Antonietta , Berra Alessandra
Published: July 2024

The transportation sector is responsible for about 16% of worldwide greenhouse gas emissions. Despite efforts for a sensible reduction by means of new technologies’ development, the average age of a vehicle fleet is 12.3 years in the European Union. In light of this, actions aiming at improving the efficiency of circulating vehicles can prove effective in the short to mid-term. Introducing performance packages in standard fuels could allow a reduction in the CO2 emissions of whole vehicle fleets without any modification to powertrain. Such a kind of additive is generally used in premium fuels; deposit control additives can reduce or control the deposits at intake valves and at nozzle holes with benefits for the fuel efficiency and exhaust emissions. Further improvements in combustion phasing can be achieved with cetane/octane improver. This paper aims to assess the influence of two performance packages on the exhaust emissions and fuel consumption of five vehicles set to be as representative as possible of circulating Italian passenger cars and light commercial fleet vehicles (LCVs). Based on the literature datasets, three Euro 4 vehicles were selected with a mileage representative of each single vehicle class: two passenger cars (one spark ignition and one diesel) and an LCV. Further, two diesel Euro 6 vehicles, a passenger car and an LCV, were tested to investigate the effect of fuel additives on the combustion of vehicles compliant with current homologation regulation. Exhaust emissions and fuel consumption were experimentally estimated on a chassis dynamometer over a worldwide harmonized light vehicles test cycle (WLTC) in a climate-controlled laboratory. Each vehicle was preliminarily tested when running with base fuel, then a 3000 km clean-up stage was performed using the additive package. Finally, WLTC tests were repeated. Results demonstrated the efficiency of the performance packages with a reduction between 1.2% (diesel Euro 6 passenger car) and 8.1% (diesel Euro 4 passenger car) in fuel consumption. Similar trends were found for CO2 emissions. Further, a sensible reduction in THCs, CO and PM was found for each vehicle class.
Experimental Evaluation of the Robust Controllers Applied on a Single Inductor Multiple Output DC-DC Buck Converter to Minimize Cross Regulation Considering Parametric Uncertainties and CPL Power Variations
Authors: Saavedra Alvaro Christian Montaño , Barra Junior Walter , Medeiros Renan Landau Paiva de , Junior Carlos Roozembergh , Gomes Alan Sovano
Published: July 2024

This paper presents two control design strategies for voltage regulation in a single inductor dual-output DC-DC buck converter system. Based on a nominal multiple input multiple output plant model and performance requirements, both a Linear Quadratic Regulator and a Decoupled PI control law are designed to control the power converter system under parametric uncertainties such as voltage source variation, constant power load variation, and load resistance variation. Therefore, the converter can cascade operation, which may cause the undesired effects of voltage oscillation and reduce the system’s stability margin. The control performance was assessed under both the uncertainties of resistive loading and the power variation in a constant power load. A single inductor dual-output DC-DC buck converter board was developed for experimental tests. The experimental results show that the Linear Quadratic Regulator strategy, compared to the PI strategy, presented a robust performance in the presence of parametric uncertainties in the resistive load-bearing; however, it was sensitive to uncertainties due to the presence of constant power loads.
Powering the Future: Advanced Battery Management Systems (BMS) for Electric Vehicles
Authors: Krishna T. N. V. , Kumar Seelam V. S. V. Prabhu Deva , Srinivasa Rao Sunkara , Chang Liuchen
Published: July 2024

This paper introduces a novel approach for rapidly balancing lithium-ion batteries using a single DC–DC converter, enabling direct energy transfer between high- and low-voltage cells. Utilizing relays for cell pair selection ensures cost-effectiveness in the switch network. The control system integrates a battery-monitoring IC and an MCU to oversee cell voltage and ensure battery protection. A prototype circuit with twelve lithium-ion batteries demonstrates the method’s efficacy, achieving a remarkable balancing time of 48 min during charging with a maximum efficiency of 89.85%. Comparative analysis with other methods underscores the superior performance of the proposed balancing circuit in terms of balancing time and implementation cost. Furthermore, this paper delves into hardware aspects of battery management systems (BMSs) for electric vehicles and stationary applications. It offers an overview of prevailing concepts in state-of-the-art systems, aiding readers in assessing considerations essential for BMS design in various applications. The discussion includes examples of battery packs sourced from commercially available electric vehicles. Subsequently, the manuscript addresses implementation aspects concerning the measurement of critical physical variables such as voltage, current, and temperature, alongside balancing strategies.
Solar Window Innovations: Enhancing Building Performance through Advanced Technologies
Authors: Ghamari Mehrdad , Sundaram Senthilarasu
Published: July 2024

Building-integrated photovoltaic (BIPV) glazing systems with intelligent window technologies enhance building energy efficiency by generating electricity and managing daylighting. This study explores advanced BIPV glazing, focusing on building-integrated concentrating photovoltaic (BICPV) systems. BICPV integrates concentrating optics, such as holographic films, luminescent solar concentrators (LSC), Fresnel lenses, and compound parabolic concentrators (CPCs), with photovoltaic cells. Notable results include achieving 17.9% electrical efficiency using cylindrical holographic optical elements and crystalline silicon cells at a 3.5× concentration ratio. Dielectric CPCs showed 97.7% angular acceptance efficiency in simulations and 94.4% experimentally, increasing short-circuit current and maximum power by 87.0% and 96.6%, respectively, across 0° to 85° incidence angles. Thermochromic hydrogels and thermotropic smart glazing systems demonstrated significant HVAC energy savings. Large-area 1 m2 PNIPAm-based thermotropic window outperformed conventional double glazing in Singapore. The thermotropic parallel slat transparent insulation material (TT PS-TIM) improved energy efficiency by up to 21.5% compared to double glazing in climates like London and Rome. Emerging dynamic glazing technologies combine BIPV with smart functions, balancing transparency and efficiency. Photothermally controlled methylammonium lead iodide PV windows achieved 68% visible light transmission, 11.3% power conversion efficiency, and quick switching in under 3 min. Polymer-dispersed liquid crystal smart windows provided 41–68% visible transmission with self-powered operation.
Transforming CO2 into Synthetic Fuels: Modeling, Simulation, and Optimization Analysis of Methanol Production from Industrial Wastes
Authors: Kontou Vasiliki , Peppas Antonis , Kottaridis Sotiris , Politi Chrysa , Karellas Sotirios
Published: July 2024

Carbon capture and utilization (CCU) has emerged in recent years as a promising decarbonization solution for hard-to-abate industries. Compared to carbon capture and storage (CCS), CCU aims not for the storage of carbon dioxide (CO2) but for its use in the production of synthetic fuels, such as synthetic methanol (MeOH). Synthetic MeOH is produced through CO2 hydrogenation, utilizing green hydrogen (H2). Efficient use of CO2 and H2 feedstocks is essential to maximize the carbon reduction potential and energy efficiency of the process. This study performed an optimization analysis on a small-scale, containerized, and portable CO2 hydrogenation unit with a 5 kg MeOH/h production capacity goal, focusing on carbon conversion efficiency (CCE), MeOH yield, H2 consumption, and MeOH purity. The analysis was conducted using Aspen Plus V12. A single-pass model was used first to evaluate an initial reactor design. The reactor was then re-designed according to the results of the gas hourly space velocity (GHSV). The model was then expanded to include a recycling loop and the final reactor design was validated, aiming to maximize overall efficiency. The effects of the operational parameters including the reactor inlet temperature, reactor pressure, thermal fluid temperature, and condensation temperature were examined. The model was then further expanded to include the MeOH distillation process, and the effect of the distillation temperature was examined. The final product of the analysis was a fully-defined and optimized unit, achieving an 87.97% CCE and an 84.99% MeOH yield, consuming 1.11 kg H2/h for the production of 5.01 kg MeOH/h of 99.86 wt% purity. This study can provide valuable information and guidelines for designing small-scale, containerized, and portable CO2 hydrogenation units, which can serve as alternative solutions to address issues of H2 production and transportation related to large-scale installations.
Infodemiology and Infoveillance of the Four Most Widespread Arbovirus Diseases in Italy
Authors: Santangelo Omar Enzo , Provenzano Sandro , Vella Carlotta , Firenze Alberto , Stacchini Lorenzo , Cedrone Fabrizio , Gianfredi Vincenza
Published: July 2024

The purpose of this observational study was to evaluate the potential epidemiological trend of arboviral diseases most reported in Italy by the dedicated national surveillance system (ISS data) compared to searches on the internet, assessing whether a correlation/association between users’ searches in Google and Wikipedia and real cases exists. The study considers a time interval from June 2012 to December 2023. We used the following Italian search terms: “Virus Toscana”, “Virus del Nilo occidentale” (West Nile Virus in English), “Encefalite trasmessa da zecche” (Tick Borne encephalitis in English), and “Dengue”. We overlapped Google Trends and Wikipedia data to perform a linear regression and correlation analysis. Statistical analyses were performed using Pearson’s correlation coefficient (r) or Spearman’s rank correlation coefficient (rho) as appropriate. All the correlations between the ISS data and Wikipedia or GT exhibited statistical significance. The correlations were strong for Dengue GT and ISS (rho = 0.71) and TBE GT and ISS (rho = 0.71), while the remaining correlations had values of r and rho between 0.32 and 0.67, showing a moderate temporal correlation. The observed correlations and regression models provide a foundation for future research, encouraging a more nuanced exploration of the dynamics between digital information-seeking behavior and disease prevalence.
Integrating a Strategic Framework to Improve Health Education in Schools in South Tyrol, Italy
Authors: Wiedermann Christian J. , Rina Patrick , Barbieri Verena , Piccoliori Giuliano , Engl Adolf
Published: July 2024

This narrative review addresses the integration of health education into school curricula in South Tyrol, an Italian province with significant cultural and linguistic diversity. This review’s objective is to analyze current health education initiatives and propose a strategic framework to enhance school-based health education, aiming to improve student well-being post-pandemic. The review synthesizes global examples and recent local studies, highlighting the importance of comprehensive teacher training, mindfulness-based interventions, culturally sensitive health education, and community engagement. The key findings indicate that current health education programs in South Tyrol are insufficient to meet immediate public health needs, such as low vaccine uptake and mental health challenges exacerbated by the COVID-19 pandemic. The proposed strategic framework seeks to align educational strategies with the diverse needs of South Tyrol’s student population, thereby improving health literacy and behavior and strengthening the region’s public health infrastructure.
Research on a Vehicle-Mounted Emergency Communication System Using BeiDou Regional Short Message Communication (RSMC) for Firefighting Operations in Forest Areas without a Public Network
Authors: Xu Can , Sun Shufa , Zhou Yuan , Ding Zian
Published: July 2024

The low coverage of public networks in pristine forest areas prevents on-site firefighters from communicating directly with remote command centers during forest fires, reducing firefighting efficiency. In this study, we designed a vehicle-mounted emergency communication system Using BeiDou RSMC (Regional Short Message Communication) for firefighting operations in forest areas without a public network to establish a satellite communication network and Zigbee self-organizing network technology to establish a local self-organizing network. Beidou RSMC is a satellite communication service developed and operated independently by China, and its signals now cover the entire globe. The combination of these two components ensures emergency communication in the event of a fire in a forest area without public network coverage. The performance of the system was tested by simulating a fire, and it was able to establish a reliable communication link between the firefighters on the scene and the remote command center in the absence of a public network. The proposed system solves the emergency communication problem that arises when a fire occurs in a forest area without a public network, enabling the remote command center to monitor fire information and dispatch various resources in real time, thereby improving firefighting efficiency and reducing casualties.
Towards an Optimized Blockchain-Based Secure Medical Prescription-Management System
Authors: Ahmed Imen , Turki Mariem , Baklouti Mouna , Dammak Bouthaina , Alshahrani Amnah
Published: July 2024

This work introduces a blockchain-based secure medical prescription-management system seamlessly integrated with a dynamic Internet of Things (IoT) framework. Notably, this integration constitutes a pivotal challenge in the arena of resource-constrained IoT devices: energy consumption. The choice of a suitable blockchain consensus mechanism emerges as the linchpin in surmounting this hurdle. Thus, this paper conducts a comprehensive comparison of energy consumption between two distinct consensus mechanisms: Proof of Work (PoW) and Quorum-based Byzantine fault tolerance (QBFT). Furthermore, an assessment of the most energy-efficient algorithm is performed across multiple networks and various parameters. This approach ensures the acquisition of reliable and statistically significant data, enabling meaningful conclusions to be drawn about the system’s performance in real-world scenarios. The experimental results show that, compared to the PoW, the QBFT consensus mechanism reduced the energy consumption by an average of 5%. This finding underscores the significant advantage of QBFT in addressing the energy consumption challenges posed by resource-constrained IoT devices. In addition to its inherent benefits of privacy and block time efficiency, the Quorum blockchain emerges as a more sustainable choice for IoT applications due to its lower power consumption.
Assessing the Impact of Financial Technology Innovations on the Sustainable Profitability of Listed Commercial Banks in China
Authors: Wang Yueyao , Yu Xintong , Yao Qingyuan , Lu Yingnan , Che Wenjia , Jiang Jingang , Chen Sonia Chien-I
Published: July 2024

Commercial banks constitute a crucial segment of China’s financial system, and their efficient operation is directly linked to the development of other sectors within the national economy. The sustainable profitability of these banks is vital for maintaining the stability of China’s financial system. In the context of the current digital economy, it is of great theoretical and practical significance to conduct an in-depth analysis of the impact of financial technology (fintech) development on the sustainable profitability of commercial banks and its underlying mechanisms. Such research can promote the digital transformation of commercial banks, enhance risk supervision policies, and mitigate systemic financial risks. This study utilizes EViews software Version 13 to analyze annual data from 13 listed commercial banks in China over the period from 2011 to 2021. It examines the influence of fintech on the profitability of these banks, considering their unique characteristics and drawing insights from the existing literature on the mechanisms through which fintech affects bank profitability. Employing both a static panel fixed effects variable-intercept model and a dynamic panel generalized method of moments (GMM) model, the empirical findings indicate that fintech development significantly impacts the profitability of listed commercial banks.
A Comparative Study of Dairy and Non-Dairy Milk Types: Development and Characterization of Customized Plant-Based Milk Options
Authors: Silva Aline Rolim Alves da , Santelli Ricardo Erthal , Braz Bernardo Ferreira , Silva Marselle Marmo Nascimento , Melo Lauro , Lemes Ailton Cesar , Ribeiro Bernardo Dias
Published: July 2024

Plant-based milk has gained considerable attention; however, its high nutritional variation highlights the need for improved formulation designs to enhance its quality. This study aimed to nutritionally compare cow milk with plant-based milk produced from hazelnuts (H), Brazil nuts (BN), cashew nuts (CN), soybeans (S), and sunflower seeds (SS), and to perform physicochemical and technological characterization. The plant-based milk produced with isolated grains showed a nutritional composition inferior to that of cow milk in almost all evaluated parameters, protein content (up to 1.1 g 100 g−1), lipids (up to 2.7 g 100 g−1), color parameters, minerals, and especially calcium (up to 62.4 mg L−1), which were originally high in cow milk (up to 1030 mg L−1). However, the plant-based milk designed using a blend composition was able to promote nutritional enhancement in terms of minerals, especially iron (Fe) and magnesium (Mg), high-quality lipids (up to 3.6 g 100 g−1), and carbohydrates (3.4 g 100 g−1 using CN, BN, and S). The protein content was 1.3% compared to 5.7 in cow milk, and the caloric value of plant-based milk remained 32.8 at 52.1 kcal, similar to cow milk. Satisfactory aspects were observed regarding the shelf life, especially related to microbiological stability during the 11 d of storage at 4 °C. For the designed plant-based milk to be equivalent to cow milk, further exploration for optimizing the blends used to achieve better combinations is required. Furthermore, analyzing possible fortification and preservation methods to increase shelf life and meet the nutritional and sensory needs of the public would be interesting.
Food Protein Nanofibril Gels: From Conditions, Types and Properties to Applications
Authors: Guan Chen , Wang Changyuan , Fu Shixin
Published: July 2024

Many food proteins can be assembled into nanofibrils under pH conditions far from the isoelectric point and with a low ionic strength by heating them for a long period. These food protein nanofibrils (FPN) have outstanding functional and biological properties and are considered sustainable biomaterials in many fields. In this study, we review the recent developments in FPN gels and introduce the key factors in promoting food protein self-assembly in order to create functional gels. The major variables discussed are the morphology of nanofibrils, protein concentration, heating time, and the type and concentration of salts. We also highlight current advances in the formation and properties of different types of FPN gels. In addition, the various applications of FPN gels in bioactive and nutrient delivery, adsorbents for CO2 and toxic pollutants, cell scaffolding biomaterials, biosensors, and others are introduced and discussed.
Performance Analysis of Fully Intuitionistic Fuzzy Multi-Objective Multi-Item Solid Fractional Transportation Model
Authors: Almotairi Sultan , Badr Elsayed , Elsisy M. A. , Farahat F. A. , El Sayed M. A.
Published: July 2024

An investigation is conducted in this paper into a performance analysis of fully intuitionistic fuzzy multi-objective multi-item solid fractional transport model (FIF-MMSFTM). It is to be anticipated that the parameters of the conveyance model will be imprecise by virtue of numerous uncontrollable factors. The model under consideration incorporates intuitionistic fuzzy (IF) quantities of shipments, costs and profit coefficients, supplies, demands, and transport. The FIF-MMSFTM that has been devised is transformed into a linear form through a series of operations. The accuracy function and ordering relations of IF sets are then used to reduce the linearized model to a concise multi-objective multi-item solid transportation model (MMSTM). Furthermore, an examination is conducted on several theorems that illustrate the correlation between the FIF-MMSFTM and its corresponding crisp model, which is founded upon linear, hyperbolic, and parabolic membership functions. A numerical example was furnished to showcase the efficacy and feasibility of the suggested methodology. The numerical data acquired indicates that the linear, hyperbolic, and parabolic models require fewer computational resources to achieve the optimal solution. The parabolic model has the greatest number of iterations, in contrast to the hyperbolic model which has the fewest. Additionally, the elapsed run time for the three models is a negligible amount of time: 0.2, 0.15, and 1.37 s, respectively. In conclusion, suggestions for future research are provided.
Unary Operations on Homogeneous Coordinates in the Plane of a Triangle
Authors: Moses Peter J. C. , Kimberling Clark
Published: July 2024

Suppose that X is a triangle center with homogeneous coordinates (barycentric or trilinear) x:y:z. Eight unary operations discussed in this paper include u1(X)=(y−z)/x:(z−x)/y:(x−y)/z. For each ui, there exist, formally, two points, P and U, such that ui(P)=ui(U)=X. To such pairs of inverses are applied nine binary operations, each resulting in a triangle center. If L is a line, then formally, ui(L) is a cubic curve that passes through the vertices A,B,C. If L passes through the point 1:1:1 (the centroid or incenter, assuming that the coordinates are barycentric or trilinear), then the cubic is degenerate as the union of a parabola and the line at infinity. The methods in this work are largely algebraic and computer-dependent.
Factors Associated with Device, Internet and Videoconferencing Use Amongst Individuals with Moderate-to-Severe Traumatic Brain Injury
Authors: Chuah Sarah L. , Whiting Diane L. , Gates Thomas M. , Simpson Grahame K.
Published: July 2024

Videoconferencing (VC) has the potential to improve access to quality healthcare for individuals with traumatic brain injury (TBI) who require intensive and ongoing rehabilitation post-injury. Gaps in information and communication technology (ICT) use, access, and skills, however, may undermine equitable participation in remotely delivered healthcare and rehabilitation. This cross-sectional study sought to identify which demographic, injury-related, and psychological factors are associated with gaps in digital inclusion amongst individuals with a TBI. Between March 2020 and December 2023, 186 adults with a moderate-to-severe TBI who were aged 18–65 years and were within five years post-injury completed a range of self-report measures. The results demonstrated that most individuals with a moderate-to-severe TBI reported high levels of technology skills and access and used the internet from multiple devices daily. While injury severity was unrelated to technology use, this finding may reflect an overestimation of technology use amongst individuals with the most severe injuries, who were excluded from the study. Several demographic and psychological factors were found to predict VC readiness and are presented within a model to guide clinicians considering client suitability for VC rehabilitation. The current findings indicate that the use of VC in clinical settings following a moderate-to-severe TBI is feasible and suggest that individuals with a TBI may benefit from the greater provision of remotely delivered healthcare than is currently offered.