bluuebunny/crossref_metadata_2025 huggingface dataset:
Product Design Trends within the Footwear Industry: A Review
Authors: Firtikiadis Lazaros , Manavis Athanasios , Kyratsis Panagiotis , Efkolidis Nikolaos
Published: May 2024

Computer technology influences the capability to enhance the functionality of manufacturing and product design technologies. Innovations in computational design and digital manufacturing empower designers and manufacturers to create novel representations and algorithms for designing, analyzing, and planning the production of highly complicated products achievable through state-of-the-art technology. Various principles, including computational physics, geometric reasoning, and automated spatial planning, enable engineers to generate entirely new categories of products in the footwear industry. This study aims to review the methods and tools that have been published in the literature for the last twenty years, and provide a better understanding of the parameters, tools, and controls that contribute to the design and manufacturing processes of shoes. The main focus is on highlighting the product design-related trends within the footwear industry. A structured framework becomes apparent in the literature through the grouping and presentation of information. This framework facilitates drawing conclusions about the trends and existing needs derived from in-depth research in the field of footwear. Additionally, it reveals the upcoming methods and tools that will contribute to the enhancement and development of this emerging and promising industry sector. In conclusion, the categorization limitation within the footwear industry could serve as the foundation for exploring key areas to be analyzed further in other industries, for instance, in furniture, clothing, and packaging.
Next-Generation Healthcare: Artificial Intelligence Applications in Disease Management
Authors: Akbulut Sami , Colak Cemil
Published: May 2024

The quick and large development in the accumulation of medical data provides broad potential for the application of artificial intelligence technologies [...]
Filtered Saliva for Rapid and Accurate Analyte Detection for POC Diagnostics
Authors: Farsaeivahid Nadia , Grenier Christian , L. Wang Ming
Published: May 2024

Saliva has shown considerable promise as a diagnostic medium for point-of-care (POC) and over-the-counter (OTC) diagnostic devices due to the non-invasive nature of its collection. However, a significant limitation of saliva-based detection is undesirable interference in a sensor’s readout caused by interfering components in saliva. In this study, we develop standardized sample treatment procedures to eliminate bubbles and interfering molecules while preserving the sample’s target molecules such as spike (S) protein and glucose. We then test the compatibility of the pretreatment system with our previously designed SARS-CoV-2 and glucose diagnostic biosensing systems for detecting S protein and glucose in subject saliva. Ultimately, the effectiveness of each filter in enhancing biomarker sensitivity is assessed. The results show that a 20 mg nylon wool (NW) filter shows an 80% change in viscosity reduction with only a 6% reduction in protein content, making it an appropriate filter for the salivary S protein diagnostic system. Meanwhile, a 30 mg cotton wool (CW) filter is identified as the optimal choice for salivary glucose detection, achieving a 90% change in viscosity reduction and a 60.7% reduction in protein content with a minimal 4.3% reduction in glucose content. The NW pretreatment filtration significantly improves the limit of detection (LOD) for salivary S protein detection by five times (from 0.5 nM to 0.1 nM) and it reduces the relative standard deviation (RSD) two times compared to unfiltered saliva. Conversely, the CW filter used for salivary glucose detection demonstrated improved linearity with an R2 of 0.99 and a sensitivity of 36.6 μA/mM·cm2, over twice as high as unfiltered saliva. This unique filtration process can be extended to any POC diagnostic system and optimized for any biomarker detection, making electrochemical POC diagnostics more viable in the current market.
Classification of Diabetic Retinopathy Disease Levels by Extracting Spectral Features Using Wavelet CNN
Authors: Sundar Sumod , Subramanian Sumathy , Mahmud Mufti
Published: May 2024

Diabetic retinopathy (DR) arises from blood vessel damage and is a leading cause of blindness on a global scale. Clinical professionals rely on examining fundus images to diagnose the disease, but this process is frequently prone to errors and is tedious. The usage of computer-assisted techniques offers assistance to clinicians in detecting the severity levels of the disease. Experiments involving automated diagnosis employing convolutional neural networks (CNNs) have produced impressive outcomes in medical imaging. At the same time, retinal image grading for detecting DR severity levels has predominantly focused on spatial features. More spectral features must be explored for a more efficient performance of this task. Analysing spectral features plays a vital role in various tasks, including identifying specific objects or materials, anomaly detection, and differentiation between different classes or categories within an image. In this context, a model incorporating Wavelet CNN and Support Vector Machine has been introduced and assessed to classify clinically significant grades of DR from retinal fundus images. The experiments were conducted on the EyePACS dataset and the performance of the proposed model was evaluated on the following metrics: precision, recall, F1-score, accuracy, and AUC score. The results obtained demonstrate better performance compared to other state-of-the-art techniques.
Single-Cell RNA Sequencing Analysis Reveals Metabolic Changes in Epithelial Glycosphingolipids and Establishes a Prognostic Risk Model for Pancreatic Cancer
Authors: Ba Qinwen , Wang Xiong , Hu Hui , Lu Yanjun
Published: May 2024

Objective: Metabolic reprogramming serves as a distinctive feature of cancer, impacting proliferation and metastasis, with aberrant glycosphingolipid expression playing a crucial role in malignancy. Nevertheless, limited research has investigated the connection between glycosphingolipid metabolism and pancreatic cancer. Methods: This study utilized a single-cell sequencing dataset to analyze the cell composition in pancreatic cancer tissues and quantified single-cell metabolism using a newly developed computational pipeline called scMetabolism. A gene signature developed from the differential expressed genes (DEGs), related to epithelial cell glycosphingolipid metabolism, was established to forecast patient survival, immune response, mutation status, and reaction to chemotherapy with pancreatic adenocarcinoma (PAAD). Results: The single-cell sequencing analysis revealed a significant increase in epithelial cell proportions in PAAD, with high glycosphingolipid metabolism occurring in the cancerous tissue. A six-gene signature prognostic model based on abnormal epithelial glycosphingolipid metabolism was created and confirmed using publicly available databases. Patients with PAAD were divided into high- and low-risk categories according to the median risk score, with those in the high-risk group demonstrating a more unfavorable survival outcome in all three cohorts, with higher rates of gene mutations (e.g., KRAS, CDKN2A), increased levels of immunosuppressive cells (macrophages, Th2 cells, regulatory T cells), and heightened sensitivity to Acetalax and Selumetinlb. Conclusions: Abnormal metabolism of glycosphingolipids in epithelial cells may promote the development of PAAD. A model utilizing a gene signature associated with epithelial glycosphingolipids metabolism has been established, serving as a valuable indicator for the prognostic stratification of patients with PAAD.
Cross-Cultural Adaptation and Validation of the Portuguese Version of the SARC-F in Community-Dwelling Older Adults
Authors: Boteta-Gomes Margarida Isabel , Aibar-Almazán Agustín , Hita-Contreras Fidel , de Loureiro Nuno Eduardo Marques , Brandão-Loureiro Vânia Azevedo Ferreira
Published: May 2024

(1) Background: The goal of this study was to analyze the reliability and validity of the Portuguese version of the SARC-F in older adults. (2) Methods: A total of 100 participants (77.1 ± 7.36 years, 73% women) were included in the study. In a first phase, the Portuguese SARC-F was adapted following the standardized forward–backward translation procedure, and internal consistency as well as inter-rater and test–retest reliability of the Portuguese SARC-F were analyzed. Secondly, clinical validation was evaluated by comparing the SARC-F total score with five operational definitions of sarcopenia and with other sarcopenia-related measurements. Discriminant validity, with respect to low muscle mass and strength and physical function were analyzed. (3) Results: The Portuguese SAR-F showed acceptable internal consistency (Cronbach α = 0.82), excellent inter-rater reliability (total score), and substantial to excellent test–retest reliability (ICC = 0.891 for the total score). Specificity ranged from 72.5% (FNIH) to 73.4 (IGWS), and negative predictive values went from 91.8% (EWGSOP1) to 97.3% (FNIH), but low sensitivity and positive predictive value were observed. The Portuguese SARC-F showed a moderate ability to discriminate people with low muscle strength (AUC = 0.78) and gait speed (AUC = 0.89). (4) Conclusions: The Portuguese SARC-F is a valid and reliable tool for ruling out sarcopenia in community-dwelling older adults and can discriminate between people with low handgrip strength and gait speed.
Clinical Effectiveness of Ion-Releasing Restorations versus Composite Restorations in Dental Restorations: Systematic Review and Meta-Analysis
Authors: Arbildo-Vega Heber Isac , Cruzado-Oliva Fredy Hugo , Coronel-Zubiate Franz Tito , Luján-Valencia Sara Antonieta , Meza-Málaga Joan Manuel , Aguirre-Ipenza Rubén , Echevarria-Goche Adriana , Luján-Urviola Eduardo , Castillo-Cornock Tania Belú , Serquen-Olano Katherine , Farje-Gallardo Carlos Alberto
Published: May 2024

Background: To compare the clinical effectiveness of ion-releasing restorations (IRR) vs. composite resin (CR) in dental restorations. Methods: A systematic search was carried out from articles published until January 2024, in the biomedical databases: PubMed, Cochrane Library, Scielo, Scopus, Web of Science and Google Scholar. Randomized clinical trials were included, with a follow-up time greater than or equal to 1 year, without time and language limits and which reported the clinical effect of IRR compared to CR in dental restorations. The RoB 2.0 tool was used to assess the risk of bias of the included studies and the GRADEPro GDT tool was used to assess the quality of evidence and the strength of recommendation of the results. Results: The search yielded a total of 1109 articles. After excluding those that did not meet the selection criteria, 29 articles remained for the quantitative synthesis. The analysis found no statistically significant difference when comparing the dental restorations with IRRs or CRs. Conclusion: The literature reviewed suggests that there are no differences between the IRRs and CRs in dental restorations.
The Expression Patterns of Non-Coding RNAs in Periodontal Disease
Authors: Adamouli Dimitra , Marasli Chrysa , Bobetsis Yiorgos A.
Published: May 2024

During the last few decades there has been a growing interest in understanding the involvement of epigenetics in the pathogenesis and treatment of periodontal disease. Noncoding RNAs (ncRNAs), including microRNAs (miRNAs), long noncoding RNAs (lncRNAs), and circular RNAs (circRNAs), may serve as epigenetic modifiers affecting the expression of genes involved in the pathogenesis of inflammatory and autoimmune diseases. There is increasing evidence supporting the idea that the function of all three types of ncRNAs seems to be interdependent. LncRNAs can act as miRNA decoys, while circRNAs can act as miRNA sponges, leading to the re-expression of miRNA target genes. The purpose of this review is to evaluate the expression patterns of ncRNAs in periodontal disease. Studies demonstrate a positive correlation between miRNA expression and periodontitis; however, this cannot be claimed for lncRNAs and circRNAs, which appear to be differentially expressed in periodontitis patients. Several studies have also suggested utilizing ncRNAs as diagnostic and prognostic biomarkers in periodontitis, or even as potential therapeutic targets; Nevetheless, the evidence to support this is premature. Future well-designed research remains necessary to establish the functional role of ncRNAs in the evolution and progression of periodontal disease.
Self-Assessment in Reading Competence: Memory, Attention, and Inference
Authors: Jiménez Pérez Elena del Pilar , Vicente-Yagüe Jara María Isabel de , Gutiérrez-Fresneda Raúl , Cuadros Muñoz Roberto
Published: May 2024

There are many reading competence tests in Spanish on the market and available in institutions like libraries or universities; some are scientifically validated whereas others lack theoretical support. Among the users of the AECL (Asociación Española de Comprensión Lectora: Spanish Association for Reading Comprehension) platform, there is an increasing demand for an easy-to-use tool aimed at older teenagers and adults, so that people can become aware of their strengths and limitations in reading comprehension. After a review of the reading competence tests in which individuals’ own recognized limitations have been included, the self-perception of the three dimensions that constitute the backbone of the Self-Assessment in Reading Competence: Memory, Attention, and Inference (MAI) instrument, which is based, in a simplified way, on the guidelines of the validated TEECLED tool, is analyzed. In a sample of 360 university students, the MAI tool has been tested in parallel with the scientifically validated reading proficiency test ComLec. The results of the analysis of the multidimensional tool MAI show significant internal consistency in both the separate dimensions (attention, memory, and inference) and the global tool, and a correspondence in the results with the ComLec reading proficiency test through multiple regression analysis. In addition, among all the dimensions, attention to memory and inference stand out; this suggests that one of the causes of not understanding what is read may, in fact, be our lack of attention during the process and not a problem with an individual’s reading ability.
Study of Fixed Point Message Scheduling Algorithm for In-Vehicle Ethernet
Authors: Chen Jiaoyue , Zuo Qihui , Xu Yihu , Wu Yujing , Jin Wenquan , Xu Yinan
Published: May 2024

With the rapid development of advanced driver assistance systems (ADASs) and autonomous driving technology, in-vehicle networks are facing huge challenges in real-time operation and data loss. Traditional vehicle bus network systems such as LIN, CAN, and FlexRay are insufficient to meet the real-time requirements of intelligent connected vehicles. In-vehicle Ethernet meets the requirements of high reliability, low electromagnetic radiation, low power consumption, bandwidth allocation, low latency, and real-time synchronization of intelligent connected vehicles. In-vehicle Ethernet has become one of the trends in the next generation of in-vehicle network architecture. This research focuses on the delay problem existing in the real-time data transmission process of in-vehicle Ethernet, and innovatively proposes a fixed point message scheduling algorithm (FPMS) based on time-sensitive network (TSN) technology. By building an experimental platform based on the CANoe simulation tool, the high-efficiency message transmission performance of the fixed point message scheduling algorithm was verified. Experimental results show that the fixed point message scheduling algorithm proposed in this study improves message transmission efficiency by 66%, laying a solid foundation for improving the real-time and reliability performance of in-vehicle Ethernet.
Adaptive Mobility-Based IoT LoRa Clustering Communication Scheme
Authors: Mugerwa Dick , Nam Youngju , Choi Hyunseok , Shin Yongje , Lee Euisin
Published: May 2024

Long Range (LoRa) as a low-power wide-area technology is distinguished by its robust long-distance communications tailored for Internet of Things (IoT) networks. Because LoRa was primarily designed for stationary devices, when applied to mobile devices, they become susceptible to frequent channel attenuation. Such a condition can result in packet loss, higher energy consumption, and extended transmission times. To address these inherent challenges posed by mobility, we propose an adaptive mobility-based IoT LoRa clustering communication (AMILCC) scheme, which employs the 2D random waypoint mobility model, strategically partitions the network into optimal spreading factor (SF) regions, and incorporates an adaptive clustering approach. The AMILCC scheme is bolstered by a hybrid adaptive data rate (HADR) mechanism categorized into two approaches, namely intra-SF and inter-SF region HADRs, derived from the standard network-based ADR mechanism for stationary devices, to ensure efficient resource allocation for mobile IoT LoRa devices. Evaluation results show that, based on simulations at low mobility speeds of up to 5 m/s, AMILCC successfully maximizes the packet success ratio to the gateway (GW) by over 70%, reduces energy consumption by an average of 55.5%, and minimizes the end-to-end delay by 47.62%, outperforming stationary schemes. Consequently, AMILCC stands as a prime solution for mobile IoT LoRa networks by balancing the high packet success ratio (PSR) with reliability with energy efficiency.
Research on a Personalized Decision Control Algorithm for Autonomous Vehicles Based on the Reinforcement Learning from Human Feedback Strategy
Authors: Li Ning , Chen Pengzhan
Published: May 2024

To address the shortcomings of previous autonomous decision models, which often overlook the personalized features of users, this paper proposes a personalized decision control algorithm for autonomous vehicles based on RLHF (reinforcement learning from human feedback). The algorithm combines two reinforcement learning approaches, DDPG (Deep Deterministic Policy Gradient) and PPO (proximal policy optimization), and divides the control scheme into three phases including pre-training, human evaluation, and parameter optimization. During the pre-training phase, an agent is trained using the DDPG algorithm. In the human evaluation phase, different trajectories generated by the DDPG-trained agent are scored by individuals with different styles, and the respective reward models are trained based on the trajectories. In the parameter optimization phase, the network parameters are updated using the PPO algorithm and the reward values given by the reward model to achieve personalized autonomous vehicle control. To validate the control algorithm designed in this paper, a simulation scenario was built using CARLA_0.9.13 software. The results demonstrate that the proposed algorithm can provide personalized decision control solutions for different styles of people, satisfying human needs while ensuring safety.
Numerical Analysis of Dual Droplet Simultaneous Oblique Impact on a Water Film
Authors: Zhou Botong , Jin Zheyan , Yang Zhigang , Yu Lei
Published: May 2024

The simultaneous oblique impact of multiple droplets on a liquid film is an intricate phenomenon prevalent in diverse natural and industrial processes. However, previous studies have primarily focused on single droplet impact, while an in-depth understanding of the more complex multi-droplet scenario remains lacking. The current study aims to numerically investigate the simultaneous oblique impact of two droplets on a water film using a three-dimensional Volume of Fluid (VOF) model. The effects of the Weber number and the impact angle on the crown behavior are carefully analyzed. The results demonstrate that increasing the Weber number enhances the central uprising sheet height but has minor influences on the upstream crown radius and central sheet radius. In contrast, the increase in the impact angle leads to a decreased upstream crown radius and an increased central sheet radius, while the central sheet height remains relatively unaffected. In addition, the splashing threshold for the dual droplet impact cases is significantly lower than that of the single droplet impact cases due to the interactions between the adjacent crowns. The present results provide novel insights into the underlying physics and useful supports in developing predictive models for the intricate multi-droplet impact phenomenon.
Optimising Agricultural Waste Supply Chains for Sustainable Bioenergy Production: A Comprehensive Literature Review
Authors: Roudneshin Maryam , Sosa Amanda
Published: May 2024

One of the United Nations’ 17 Sustainable Development Goals is to “Ensure access to affordable, sustainable, and clean energy for all.” Additionally, the growing concerns about climate change and energy security have heightened the importance of exploring alternative energy sources to replace fossil fuels. The utilisation of agricultural waste for bioenergy production has acquired significant attention due to its potential to mitigate environmental impacts and provide renewable energy sources. However, the major obstacle to producing bioenergy is managing the supply chain while considering economic, environmental, and social factors in an optimal way. This paper presents a comprehensive overview of the literature on the management of agriculture waste supply chains, specifically related to the use of modelling and optimisation techniques for planning. The first section describes different stages of the supply chain and various technologies for converting biomass to bioenergy. This is followed by a synopsis of the literature reviewed based on decision levels, objective functions, modelling methodologies, and optimisation approaches. Finally, the review highlights limitations and gaps in current research and the areas with potential for further exploration.
The Influence of Injector Nozzle Diameter on High-Density and Lean Mixture Combustion in Heavy-Duty Diesel Engines
Authors: Liu Yize , Su Wanhua
Published: May 2024

In order to improve the fuel economy of heavy-duty diesel engines under high-load conditions, based on the combustion pathway model, it is proposed that the proportion of lean mixture with 0 < Φ < 1 is the most important spray characteristic affecting the overall diesel combustion process. Answering the question of how to increase the proportion of lean mixture inside the spray is the key to achieving the efficient and clean combustion of diesel engines. This paper investigated the mechanism of injector nozzle diameter on the in-cylinder air–fuel mixture and combustion process based on a high-density and lean mixture characteristic combustion strategy. The experimental results show that with an increase in nozzle diameter, the peak pressure and instantaneous heat release rate significantly increase, the combustion duration is shortened by about 20%, and the heat release becomes more concentrated. At 1200 rpm and IMEPg~2.3 MPa conditions, the indicated thermal efficiency increases by 1.3%, reaching a maximum of 51.5%. The numerical simulation results show that with the increase in nozzle diameter from 0.169 mm to 0.218 mm, the spray ejection momentum per unit time increases by 30%, the momentum transferred to the air by the spray increases, the oxygen transport process becomes more intense, and the air entrainment mass during the spray free development stage increases by 42%. The proportion of lean mixture inside the spray throughout the entire spray development process increases, resulting in an increase in the heat release rate of the lean mixture, making the overall combustion more intense and concentrated.
End-to-End Top-Down Load Forecasting Model for Residential Consumers
Authors: Parkash Barkha , Lie Tek Tjing , Li Weihua , Tito Shafiqur Rahman
Published: May 2024

This study presents an efficient end-to-end (E2E) learning approach for the short-term load forecasting of hierarchically structured residential consumers based on the principles of a top-down (TD) approach. This technique employs a neural network for predicting load at lower hierarchical levels based on the aggregated one at the top. A simulation is carried out with 9 (from 2013 to 2021) years of energy consumption data of 50 houses located in the United States of America. Simulation results demonstrate that the E2E model, which uses a single model for different nodes and is based on the principles of a top-down approach, shows huge potential for improving forecasting accuracy, making it a valuable tool for grid planners. Model inputs are derived from the aggregated residential category and the specific cluster targeted for forecasting. The proposed model can accurately forecast any residential consumption cluster without requiring any hyperparameter adjustments. According to the experimental analysis, the E2E model outperformed a two-stage methodology and a benchmarked Seasonal Autoregressive Integrated Moving Average (SARIMA) and Support Vector Regression (SVR) model by a mean absolute percentage error (MAPE) of 2.27%.
A Dual and Rapid RPA-CRISPR/Cas12a Method for Simultaneous Detection of Cattle and Soybean-Derived Adulteration in Goat Milk Powder
Authors: Wen Yuanjun , Huang Shuqin , Lei Hongtao , Li Xiangmei , Shen Xing
Published: May 2024

The adulteration of goat milk powder occurs frequently; cattle-derived and soybean-derived ingredients are common adulterants in goat milk powder. However, simultaneously and rapidly detecting cattle-derived and soybean-derived components is still a challenge. An efficient, high-throughput screening method for adulteration detection is needed. In this study, a rapid method was developed to detect the adulteration of common cattle-derived and soybean-derived components simultaneously in goat milk powder by combining the CRISPR/Cas12a system with recombinant polymerase amplification (RPA). A dual DNA extraction method was employed. Primers and crRNA for dual detection were designed and screened, and a series of condition optimizations were carried out in this experiment. The optimized assay rapidly detected cattle-derived and soybean-derived components in 40 min. The detection limits of both cattle-derived and soybean-derived components were 1% (w/w) for the mixed adulteration models. The established method was applied to a blind survey of 55 commercially available goat milk powder products. The results revealed that 36.36% of the samples contained cattle-derived or soybean-derived ingredients, which revealed the noticeable adulteration situation in the goat milk powder market. This study realized a fast flow of dual extraction, dual amplification, and dual detection of cattle-derived and soybean-derived components in goat milk powder for the first time. The method developed can be used for high-throughput and high-efficiency on-site primary screening of goat milk powder adulterants, and provides a technical reference for combating food adulteration.
Oak Leaves as a Raw Material for the Production of Alcoholic Fermented Beverages
Authors: Pencak Tomas , Dordevic Dani , Ćavar Zeljković Sanja , Tremlova Bohuslava
Published: May 2024

This study aimed to point out the possible use of oak leaves (Q. petraea) in the production of fermented alcoholic beverages. Parameters such as antioxidant capacity, total phenolic content, phenolics and sugars were determined using spectrophotometric and chromatographic methods. pH values were also determined, and in the final product with a fermentation length of 85 days, the alcohol content was determined and sensory analysis performed. The antioxidant capacity of the beverage was lower compared to the infusions before fermentation, and its highest values were recorded in the leaf samples, in which the highest values of phenolic compounds and the total phenolic content were also recorded. A decrease in the content of total phenolics was recorded with the increasing length of fermentation in beverage samples. However, the fermentation process had a positive effect on the contents of some phenolic substances such as catechin, gallic acid and gallocatechin. Sensory analysis showed a higher acceptability of the fermented beverage without the addition of orange, which could be caused by the higher sugar content in these samples. Oak leaves therefore represent a suitable raw material for the production of a fermented alcoholic beverage, without the need to enrich the taste with other ingredients.
Isolation and Evaluation of Erinacine A Contents in Mycelia of Hericium erinaceus Strains
Authors: Liu Mengchen , Liu Liangliang , Song Xiaoya , Zhou Yingjun , Peng Yuande , Xie Chunliang , Gong Wenbing
Published: May 2024

Hericium erinaceus has long been favored for its remarkable nutritional and health-promoting benefits, and erinacine A is the key component responsible for the neuroprotective properties of H. erinaceus. Establishing an efficient method for separating erinacine A from H. erinaceus and screening the erinacine A-enriched strains is crucial to maximizing its benefits. Herein, we first reported that high-speed counter current chromatography (HSCCC) is an effective method for separating high-purity erinacine A. Using a two-phase solvent system composed of n-hexane/ethyl acetate/methanol/water (4.5:5:4.5:5, v/v/v/v), erinacine A with a purity of over 95% was separated. Then, we evaluated the content and yield of erinacine A in the liquid-fermented mycelia of Hericium germplasms. Both the content and yield of erinacine A varied greatly among the surveyed strains. The significant effect of the strain on the erinacine A content and yield was revealed by an analysis of variance. The highest erinacine A content and yield were observed in the mycelia of a wild strain HeG, reaching 42.16 mg/g and 358.78 mg/L, which is superior to the current highest outcomes achieved using submerged cultivation. The isolation method established and the strains screened in this study can be beneficial for the scaling up of erinacine A extraction and nutraceutical development to industrial levels.
Geological and Geochemical Characterization of Variscan Pegmatites in the Sidi Bou Othmane District, Central Jebilet Province, Morocco
Authors: Wafik Amina , El Aouad Nouamane , Daafi Youssef , Morsli Yousra , Chniouar Marouane , Punturo Rosalda , Conte Aida Maria , Guglietta Daniela , Aba Sidi Wissale
Published: May 2024

The Sidi Bou Othmane (SBO) pegmatite district is situated in the Central Jebilet massif, Western Meseta domain, Morocco. The SBO district is hosted essentially in a volcano-sedimentary series composed of Late-Devonian Sarhlef shales. Pegmatite bodies crop out as dykes, which are oriented from N-S to E-W and are generally variably deformed with ductile and/or brittle structures with ante, syn- or post-kinematic criteria. Petrographic observations of pegmatite dykes show that feldspars (i.e., albite, microcline) are the most abundant mineral phases, followed by quartz and micas, with tourmaline and accessory minerals such as garnet, and zircon also featuring heavily, as well as secondary minerals such as clinochlore, sericite, and illite. The geochemical study of the SBO pegmatites indicates that they have mainly S-type granitic compositions, which are peraluminous granites with calc-alkalic affinities. The study of trace elements indicates that SBO pegmatites were formed in post-orogenic syn-collision context during the Variscan orogeny by the partial melting of argilliferous sediment. They can be ascribed to the muscovite-bearing pegmatite; moreover, they have good potential regarding ceramics. They also contain minerals, such as feldspar, which have been recently assessed as critical raw materials by the European Union.
An Orthopedic Healthcare Facility Governance Assessed with a New Indicator System
Authors: Moldovan Flaviu , Moldovan Liviu
Published: May 2024

Background and Objectives: A sustainability-oriented hospital governance has the potential to increase the efficiency of healthcare services and reduce the volume of expenses. The objective of this research is to develop a new complex tool for evaluating healthcare facility governance as a component of social responsibility, integrated into sustainability. Materials and Methods: We designed the research to develop the domains of a new reference framework for evaluating healthcare facility governance. The methodology for designing the indicators that make up the new reference framework consists of collecting and processing the most recent and relevant practices regarding the governance of healthcare facilities that have been reported by representative hospitals around the world. Results: We designed eight indicators that are brought together in the healthcare facility governance indicators matrix. They have descriptions and qualitative and quantitative rating scales with values from 0 to 5 that allow the degree of fulfillment to be quantified. The importance of the indicators is evaluated on a specific scale described qualitatively and quantitatively by values from 0 to 5. The values of the degree of achievement–importance couples of the indicators allow the development of improvement measures with priority according to the results revealed by the Eisenhower-type assessment diagram. Conclusions: Validation in practice of the system of indicators at an emergency hospital in an orthopedic profile highlighted the fact that they can be integrated into other national and international reference frameworks implemented in the hospital. The added value of the implementation consists of the facilitation of sustainable development and the orientation of health personnel, patients, and interested parties toward sustainability.
Exogenous Application of Melatonin on the Preservation of Physicochemical and Enzymatic Qualities of Pepper Fruit from Chilling Injury
Authors: Charoenphun Narin , Pham Nam Hoang , Rattanawut Jessada , Venkatachalam Karthikeyan
Published: May 2024

This study investigates the impact of melatonin (MT) treatment at varying concentrations (0, 25, 50, 75, 100 µmol L−1) on the post-harvest quality and shelf life of long green pepper fruits stored under low temperature for 28 days. Every 4 days, pepper fruits were examined for the chilling injury (CI) index, weight loss (WL), respiration rates, firmness, electrolyte leakage (EL), reactive oxygen species (ROS), malondialdehyde (MDA) levels, non-enzymatic antioxidant (NEA) content, antioxidant (AO) enzyme activity (superoxide dismutase (SOD), catalase (CAT), and peroxidases (PODs)), and cellular degrading enzymes (polygalacturonase (PG), pectin methylesterase (PME), phospholipase D (PLD), and lipoxygenase (LOX)). MT-treated samples exhibited delayed and reduced CI stress compared to controls, with higher exogenous MT concentrations (>50 µmol L−1) offering significant (p < 0.05) CI reductions. During storage, WL was notably mitigated by MT treatment in the tested samples compared to control samples. This study also demonstrated that MT-treated pepper fruits effectively decelerated respiration rates and consequently preserved pepper firmness. A higher concentration of MT-treated pepper fruits demonstrated a significantly (p < 0.05) lowered level of ROS and MDA while maintaining membrane stability, as evidenced by reduced EL. MT treatment with increasing concentration increased the levels of glutathione (GSH), glutathione disulfide (GSSG), ascorbic acid (AsA), dehydroascorbate (DHA), and total phenolic content (TPC) in the pepper fruits compared to control and thus significantly (p < 0.05) suppressed the ROS production (superoxide anion (O2•−) and hydrogen peroxide (H2O2) radicals) in the pepper fruits. Furthermore, AO enzymes such as SOD, CAT, and POD were also high in the pepper fruits that were treated with higher concentrations of MT (>50 µmol L−1). Additionally, the activities of cellular degrading enzymes (PG, PME, PLD, and LOX), which are linked to senescence and stress-induced physiological disorders, were also effectively regulated by MT-treated (>75 µmol L−1) pepper fruits. Overall, the application of MT at higher concentrations (>75 µmol L−1) demonstrated substantial benefits in preserving the quality and extending the shelf life of pepper fruits during cold storage.
Transplantation of Mesenchymal Stem Cells Derived from Old Rats Improves Healing and Biomechanical Properties of Vaginal Tissue Following Surgical Incision in Aged Rats
Authors: Ben Menachem-Zidon Ofra , Reubinoff Benjamin , Shveiky David
Published: May 2024

Pelvic floor dysfunction encompasses a group of disorders that negatively affect the quality of women’s lives. These include pelvic organ prolapse (POP), urinary incontinence, and sexual dysfunction. The greatest risk factors for prolapse are increased parity and older age, with the largest group requiring surgical intervention being post-menopausal women over 65. Prolapse recurrence rates following surgery were reported to be as high as 30%. This may be attributed to ineffective healing in the elderly. Autologous stem cell transplantation during surgery may improve surgical results. In our previous studies, we showed that the transplantation of bone marrow-derived mesenchymal stem cells (MSCs) from young donor rats improved the healing of full-thickness vaginal surgical incision in the vaginal wall of old rats, demonstrated by both histological and functional analysis. In order to translate these results into the clinical reality of autologous MSC transplantation in elderly women, we sought to study whether stem cells derived from old donor animals would provide the same effect. In this study, we demonstrate that MSC transplantation attenuated the inflammatory response, increased angiogenesis, and exhibited a time-dependent impact on MMP9 localization. Most importantly, transplantation improved the restoration of the biomechanical properties of the vagina, resulting in stronger healed vaginal tissue. These results may pave the way for further translational studies focusing on the potential clinical autologous adjuvant transplantation of MSCs for POP repair for the improvement of surgical outcomes.
Reduction in Hippocampal Amyloid-β Peptide (Aβ) Content during Glycine-Proline-Glutamate (Gly-Pro-Glu) Co-Administration Is Associated with Changes in Inflammation and Insulin-like Growth Factor (IGF)-I Signaling
Authors: Frago Laura M. , Burgos-Ramos Emma , Rodríguez-Pérez María , Canelles Sandra , Arilla-Ferreiro Eduardo , Argente Jesús , López Manuela G. , Barrios Vicente
Published: May 2024

Alzheimer’s disease (AD) is characterized by the deposition in the brain of senile plaques composed of amyloid-β peptides (Aβs) that increase inflammation. An endogenous peptide derived from the insulin-like growth factor (IGF)-I, glycine-proline-glutamate (GPE), has IGF-I-sensitizing and neuroprotective actions. Here, we examined the effects of GPE on Aβ levels and hippocampal inflammation generated by the intracerebroventricular infusion of Aβ25-35 for 2 weeks (300 pmol/day) in ovariectomized rats and the signaling-related pathways and levels of Aβ-degrading enzymes associated with these GPE-related effects. GPE prevented the Aβ-induced increase in the phosphorylation of p38 mitogen-activated protein kinase and the reduction in activation of signal transducer and activator of transcription 3, insulin receptor substrate-1, and Akt, as well as on interleukin (IL)-2 and IL-13 levels in the hippocampus. The functionality of somatostatin, measured as the percentage of inhibition of adenylate cyclase activity and the levels of insulin-degrading enzyme, was also preserved by GPE co-treatment. These findings indicate that GPE co-administration may protect from Aβ insult by changing hippocampal cytokine content and somatostatin functionality through regulation of leptin- and IGF-I-signaling pathways that could influence the reduction in Aβ levels through modulation of levels and/or activity of Aβ proteases.
The Impact of Input Types on Smart Contract Vulnerability Detection Performance Based on Deep Learning: A Preliminary Study
Authors: Aldyaflah Izdehar M. , Zhao Wenbing , Yang Shunkun , Luo Xiong
Published: May 2024

Stemming vulnerabilities out of a smart contract prior to its deployment is essential to ensure the security of decentralized applications. As such, numerous tools and machine-learning-based methods have been proposed to help detect vulnerabilities in smart contracts. Furthermore, various ways of encoding the smart contracts for analysis have also been proposed. However, the impact of these input methods has not been systematically studied, which is the primary goal of this paper. In this preliminary study, we experimented with four common types of input, including Word2Vec, FastText, Bag-of-Words (BoW), and Term Frequency–Inverse Document Frequency (TF-IDF). To focus on the comparison of these input types, we used the same deep-learning model, i.e., convolutional neural networks, in all experiments. Using a public dataset, we compared the vulnerability detection performance of the four input types both in the binary classification scenarios and the multiclass classification scenario. Our findings show that TF-IDF is the best overall input type among the four. TF-IDF has excellent detection performance in all scenarios: (1) it has the best F1 score and accuracy in binary classifications for all vulnerability types except for the delegate vulnerability where TF-IDF comes in a close second, and (2) it comes in a very close second behind BoW (within 0.8%) in the multiclass classification.
Decentralized Zone-Based PKI: A Lightweight Security Framework for IoT Ecosystems
Authors: El-Hajj Mohammed , Beune Pim
Published: May 2024

The advent of Internet of Things (IoT) devices has revolutionized our daily routines, fostering interconnectedness and convenience. However, this interconnected network also presents significant security challenges concerning authentication and data integrity. Traditional security measures, such as Public Key Infrastructure (PKI), encounter limitations when applied to resource-constrained IoT devices. This paper proposes a novel decentralized PKI system tailored specifically for IoT environments to address these challenges. Our approach introduces a unique “zone” architecture overseen by zone masters, facilitating efficient certificate management within IoT clusters while reducing the risk of single points of failure. Furthermore, we prioritize the use of lightweight cryptographic techniques, including Elliptic Curve Cryptography (ECC), to optimize performance without compromising security. Through comprehensive evaluation and benchmarking, we demonstrate the effectiveness of our proposed solution in bolstering the security and efficiency of IoT ecosystems. This contribution underlines the critical need for innovative security solutions in IoT deployments and presents a scalable framework to meet the evolving demands of IoT environments.
Diagnosis and Management of Fetal Arrhythmias in the Current Era
Authors: Killen Stacy A. S. , Strasburger Janette F.
Published: May 2024

Diagnosis and management of fetal arrhythmias have changed over the past 40–50 years since propranolol was first used to treat fetal tachycardia in 1975 and when first attempts were made at in utero pacing for complete heart block in 1986. Ongoing clinical trials, including the FAST therapy trial for fetal tachycardia and the STOP-BLOQ trial for anti-Ro-mediated fetal heart block, are working to improve diagnosis and management of fetal arrhythmias for both mother and fetus. We are also learning more about how “silent arrhythmias”, like long QT syndrome and other inherited channelopathies, may be identified by recognizing “subtle” abnormalities in fetal heart rate, and while echocardiography yet remains the primary tool for diagnosing fetal arrhythmias, research efforts continue to advance the clinical envelope for fetal electrocardiography and fetal magnetocardiography. Pharmacologic management of fetal arrhythmias remains one of the most successful achievements of fetal intervention. Patience, vigilance, and multidisciplinary collaboration are key to successful diagnosis and treatment.
Clinical Outcomes in Scleral Fixation Secondary Intraocular Lens with Yamane versus Suture Techniques: A Systematic Review and Meta-Analysis
Authors: Zhang Charles , Palka Charles , Zhu Daniel , Lai Daniel , Winokur Jules , Shwani Treefa , DeAngelis Margaret M. , Reynolds Andrew L.
Published: May 2024

Background: The purpose of the study is to compare the visual outcomes and complications of sutured scleral fixation (SSF), a traditional and conservative surgical approach, and the newer and faster Yamane technique for secondary intraocular lens placement. Methods: A literature search was performed on PubMed, Embase, and Scopus on studies published between 1 July 2017 to 29 September 2023. Outcomes analyzed included the final best corrected visual acuity (BCVA) between 3 and 12 months to assess the effectiveness of the procedure, post-operative month (POM) 1 BCVA to assess the speed of visual recovery, endothelial cell count (ECC), absolute refractive error, surgical duration, and complication rates. Additional subgroup analyses were performed based on surgeon experience with the technique. Single-surgeon studies had an average of 26 procedures performed, whereas multiple-surgeon studies averaged only 9 procedures performed; these were then used to delineate surgeon experience. A sample-size weighted mean difference (MD) meta-analysis was performed across all variables using RevMan 5.4.1; p < 0.05 was considered statistically significant. Results: Thirteen studies with 737 eyes were included: 406 eyes were included in the SSF group, and 331 eyes were included in the Yamane group. There was no significant difference in the final BCVA between groups in both the single-surgeon versus multiple-surgeon studies (MD = −0.01, 95% CI: [−0.06, 0.04], p = 0.73). In the single-surgeon studies, the BCVA at POM1 was significantly improved in the Yamane group compared to SSF (MD = −0.10, 95% CI: [−0.16, −0.04], p = 0.002). In the multiple-surgeon studies, there was no significant difference in BCVA at POM1 (MD = −0.06, 95% CI: [−0.16, 0.04], p = 0.23). The Yamane group had a shorter surgical duration than SSF in both single-surgeon and multiple-surgeon studies (MD = −24.68, 95% CI: [−35.90, −13.46], p < 0.0001). The ECC, refractive error, and complication rates did not significantly differ amongst all groups. Conclusions: The Yamane technique demonstrated similar long-term visual outcomes and complication rates to the traditional SSF. Visual recovery was significantly faster in the Yamane group in the single-surgeon studies. The operative times were shorter across all Yamane groups. Based on these findings, it is advisable to consider the Yamane technique as a viable, and perhaps preferable, option for patients requiring secondary IOL placement, alongside traditional SSF methods.