bluuebunny/crossref_metadata_2025 huggingface dataset:
Effectiveness and Safety of SYSADOAs Used in Eastern and Western Regions for the Treatment of Knee Osteoarthritis: A Systematic Review and Meta-Analysis of Randomized Controlled Trials—SYSADOAs Are Effective and Safe for Knee OA
Authors: Park Yong-Beom , Kim Jun-Ho
Published: February 2025

Background and Objective: According to international guidelines, glucosamine and chondroitin, regarded as slow-acting drugs for osteoarthritis (SYSADOAs), have been first-line treatments for knee osteoarthritis (OA); however, their efficacies remain controversial. Additionally, the efficacies of plant extract cocktails, SKI306X, and its newer formulation, SKCPT, have not been well investigated. To evaluate the effectiveness and safety of symptomatic slow-acting drugs for osteoarthritis (SYSADOAs) in patients with knee OA. Materials and Methods: Electronic databases were systematically searched to identify randomized controlled trials (RCTs) assessing the effectiveness and safety of SYSADOAs, including chondroitin sulfate, glucosamine sulfate, and SKCPT/SKI306X. The outcomes included pain relief, functional improvements, and safety profiles. The outcome measurements were compared between the treatment and control groups, including placebo and non-placebo groups, within and after 3 months of follow-up. Results: Analysis of 21 RCTs showed significantly greater improvement in pain relief in the treatment group compared with the placebo group both within (standard mean difference [SMD], 0.38; 95% confidence interval [CI], 0.18–0.57; p < 0.001) and after 3 months of follow-up (SMD, 0.22; 95%CI, 0.03–0.42 p = 0.023). The treatment group also showed significantly greater functional improvements regardless of follow-up. Pain and functional improvement did not differ significantly between the treatment and non-placebo groups. Regarding the safety profile, the risk ratios did not differ significantly between the treatment and control groups, including the placebo and non-placebo subgroups. Conclusions: Glucosamine, chondroitin, and SKCPT/SKI306X improved the pain and function and were non-inferior to pharmacologic drugs for up to 12 months. These findings support the clinical use of these SYSADOAs to treat knee OA. Level of Evidence: Therapeutic Level II.
Etching: The Art of Semiconductor Micromachining
Authors: Romano Lucia
Published: February 2025

Etching makes a pattern design a real 3D object [...]
An Implementation of a Crime-Safety-Map Application Based on a Safety Index
Authors: Hong Seong-Cho , Kim Svetlana , Ihm Sun-Young
Published: February 2025

This paper presents the development of a crime-safety-map application and a safety index using the heatmap and geofence methods. The need for a tool that can satisfy safety needs has become more important than ever due to society’s growing fear of crime. One way to satisfy the general public’s safety needs is by informing them of crime data and the safety level of the surrounding environment, but it is not disclosed by law enforcement agencies. Therefore, this study focused on crime prevention through environmental design for developing a user-friendly, open to the public crime-safety-map application. Data from the Republic of Korean Open Government Data Portal’s nationwide safety and crime related data were used and the application was designed using Android Studio. The developed application visualizes the characteristic of the surrounding environment and can also inform crime safety level through a heatmap and the geofence technique. This application can reduce the general public’s fear of crime and crime incidents by informing and warning them about the crime prone areas.
The Influence of Dietary Patterns on Polycystic Ovary Syndrome Management in Women: A Review of Randomized Controlled Trials with and Without an Isocaloric Dietary Design
Authors: Choi Yeonjeong , Kang Kyeonghoon , Je Minkyung , Lee Young-Min , Kim Yoona
Published: February 2025

Polycystic ovary syndrome (PCOS) is an endocrine disorder that causes cardiometabolic and reproductive disorders in women of reproductive age. Women with PCOS are more likely to have obesity, type 2 diabetes mellitus, and cardiovascular disease. There is an inconclusive consensus on which dietary modification could be most effective in PCOS prevention and treatment. This review aimed to examine the effects of diverse dietary patterns on PCOS in women according to randomized controlled trials (RCTs) with and without an isocaloric dietary design. A literature search was performed in the PubMed®®/MEDLINE®® database up to 14 November 2024. A total of 21 RCTs were reviewed after screening the records, including 15 RCTs with a calorie-restricted dietary design and 6 RCTs with a non-calorie-restricted dietary design. This review found beneficial effects of the calorie-restricted Dietary Approaches to Stop Hypertension (DASH) diet on weight loss and glucose control in women with PCOS in four RCTs with an isocaloric dietary design. The calorie-restricted low-glycemic index (GI) diets from three RCTs and high-protein diets from four RCTs with an isocaloric dietary design showed no significant differences in anthropometric parameters, glucose control, lipids, and gonadal parameters compared with the control diet in women with PCOS. Non-calorie-restricted low-carbohydrate diets from four RCTs with an isocaloric dietary design showed similar results to the calorie-restricted low-GI diets and high-protein diets. However, the existing number of RCTs is insufficient to conclude the association between dietary patterns and PCOS in women. Further, well-designed dietary intervention studies are needed to assess the role of dietary patterns in PCOS beyond calorie restriction.
Fraction of Genome Altered, Age, Microsatellite Instability Score, Tumor Mutational Burden, Cancer Type, Metastasis Status, and Choice of Cancer Therapy Predict Overall Survival in Multiple Machine Learning Models
Authors: Mestrallet Guillaume
Published: February 2025

Background/Objectives: The accurate prediction of overall survival (OS) in cancer patients is crucial for personalized treatment strategies. Methods: In this study, we developed machine learning models to predict OS by integrating clinical and mutational features from a cohort of 25,508 cancer patients. Key features included tumor mutational burden (TMB), microsatellite instability (MSI), fraction of genome altered (FGA), copy number alterations (CNA), age, sex, race, cancer type, and metastasis status. Results: We applied multiple Random Forest, Gradient Boosting, and Ensemble models, achieving an accuracy of 74% for overall survival status, and a C-Index of 0.76 using the Random Survival Forest model. Importantly, FGA, age, MSI score, TMB, cancer type, and metastasis status were identified as major predictors of OS across all models. We also integrated treatment data from 16,603 patients, demonstrating that therapies like platinum, carboplatin, and taxanes are associated with differences in survival predictions, with some therapeutic regimens showing minimal impact. Conclusions: Our findings highlight the potential of using machine learning to predict OS by incorporating both clinical and mutational features. These models offer a promising approach for improving patient outcomes and could be further validated in prospective studies for clinical use.
Exploration of Challenges and Opportunities for Good Pharmacy Practices in Bangladesh: A Qualitative Study
Authors: Chakma Nantu , Ali Sunjida Binta , Islam Md. Saimul , Momtaz Tanisha , Farzana Noshin , Amzad Raian , Khan Sharful Islam , Khan Md. Iftakhar Hassan , Azad Abul Kalam , Babar Zaheer-Ud-Din , Naheed Aliya
Published: February 2025

Background: In 2015, the Directorate General of Drug Administration (DGDA) of Bangladesh accredited model pharmacies (MPs) to enhance the quality of pharmacy services across the country. We examined the challenges and opportunities for pharmacists in MPs, and also explored the perspectives of the pharmacy stakeholders for improving good pharmacy practices (GPPs) in Bangladesh. Methods: In-depth interviews (IDIs) were conducted with graduate pharmacists (Grade A) and diploma pharmacists (Grade B) recruited from a few selected MPs that were included in a previous study. Key informant interviews (KIIs) were conducted with the government and non-government stakeholders who were involved in pharmacy regulations and practices. Trained qualitative researchers conducted IDIs and KIIs using interview topic guides under relevant themes developed by the study investigators. Results: Between February and March 2021, nine Grade A and six Grade B pharmacists and nine government and non-government stakeholders were interviewed. The key challenges, as well as demotivational factors, for Grade A pharmacists were reported to be multiple responsibilities, inadequate salary, poor social status, an unfavorable working environment, long working hours, a lack of recognition, and low respect for their profession. However, Grade B pharmacists expressed job satisfaction, primarily due to working opportunities in reputable pharmacies and learning opportunities. The stakeholders reported a high operation cost of the MPs, a shortage of trained pharmacists, poor salary structures, and a lack of public awareness about the critical roles of the pharmacists in healthcare to be challenges of retaining Grade A pharmacists at the MPs. Addressing the challenges of the pharmacists and revising compensation packages along with strengthening monitoring systems would be important for improving GPPs at the MPs. Conclusions: This study has demonstrated that specifying the roles of the pharmacists, offering competitive packages, conducive working hours, and professional recognition would be imperative for the retention of trained pharmacists at MPs. Implementing regulatory standards and monitoring performance would enhance good pharmacy practices in Bangladesh.
Optically Referenced Microwave Generator with Attosecond-Level Timing Noise
Authors: Yan Lulu , Ruan Jun , Zhang Pan , Rao Bingjie , Li Mingkun , Du Zhijing , Zhang Shougang
Published: February 2025

Microwave sources based on ultrastable lasers and optical frequency combs (OFCs) exhibit ultralow phase noise and ultrahigh-frequency stability, which are important for many applications. Herein, we present a microwave source that is phase-locked to an ultrastable continuous-wave laser, with a relative frequency instability of 7 × 10−16 at 1 s. An Er:fiber-based OFC and an optic-to-electronic converter with low residual noise are employed to confer optical frequency stability on the 9.6 GHz microwave signal. Instead of using the normal cascaded Mach–Zehnder interferometer method, we developed a microwave regeneration method for converting optical pulses into microwave signals to further suppress the additional noise in the optic-to-electronic conversion process. The microwave regeneration method employs an optical-to-microwave phase detector based on a fiber-based Sagnac loop to produce the error signal between a 9.6 GHz dielectric resonator oscillator (DRO) and the OFC. The 9.6 GHz microwave (48th harmonic of the comb’s repetition rate) signal with the frequency stability of the ultrastable laser was achieved using a DRO that was phase-locked to the optical comb. Preliminary evaluations showed that the frequency instability of the frequency synthesizer from the optical to the 9.6 GHz microwave signal was approximately 2 × 10−15 at 1 s, the phase noise was −106 dBc Hz−1 at 1 Hz, and the timing noise was approximately 9 as Hz−1/2 (phase noise approx. −125 dBc Hz−1). The 9.6 GHz signal from the photonic microwave source exhibited a short-term relative frequency instability of 2.1 × 10−15 at 1 s, which is 1.5 times better than the previous results.
Encapsulation Efficiency of Electrosprayed Glucose Oxidase Capsules: Effect of the Drying Technique
Authors: Rentería-Ortega Minerva , Perea-Flores María de Jesús , Peña-Barrientos Alberto , Barrios-Francisco Rigoberto , Rojas-Candelas Liliana Edith , Calderón-Domínguez Georgina
Published: February 2025

Glucose oxidase (GOX) is widely used in bakery applications to improve dough rheology and bread quality. However, its direct addition to formulations limits its functionality due to premature enzymatic activity. This study used electrospraying to encapsulate GOX using chia mucilage and sodium alginate as biopolymeric wall materials. Three drying methods—critical point drying (CPD), Lyophilization/freeze-drying (LC), and oven drying (OD)—were compared to evaluate their impact on encapsulation efficiency (EE), enzymatic activity retention, and microstructural integrity. Our findings reveal that CPD preserved the porous structure of the microcapsules, minimizing enzymatic leakage and yielding the highest EE (70%). In contrast, LC induced ice crystal formation, disrupting the polymer network and leading to a moderate EE (27.43%), whereas OD resulted in extensive capsule shrinkage, causing significant enzyme loss (57.1%). The release kinetics of GOX during mixing were best described by the Korsmeyer–Peppas model (R2 = 0.999), indicating a non-Fickian diffusion mechanism influenced by polymer relaxation. These results demonstrate that drying technique selection plays a crucial role in encapsulated enzymes’ stability and release behavior, providing new insights for optimizing enzyme delivery in bakery applications.
Development of Novel Mussel-Shell-Derived CaO-Based Transition Metal Catalysts for Efficient Microwave-Assisted Biodiesel Production
Authors: Al Alwan Basem , Alamri Shahd , El Jery Atef , Shah Mumtaj , Sahlabji Taher
Published: February 2025

This study introduces an innovative way to use calcium oxide (CaO) derived from mussel shells as a catalyst support for biodiesel production. Several transition metals, including Ni, Ag, Mo, Co, and W were loaded on the aforementioned support to synthesize mono-metallic and bi-metallic catalysts using the wet impregnation method. Microwave technology was utilized to accelerate reactions and improve efficiency. Characterization techniques such as BET, SEM/EDX, and XRD confirmed the successful incorporation of metals into the catalyst structure. The prepared catalysts, Mussel(Ni), Mussel(Ni-W), Mussel(Ni-Ag), Mussel(Ni-Mo), and Mussel(Ni-Co), were evaluated to investigate the catalytic performance for biodiesel production from corn oil under different conditions such as microwave powers, catalyst loadings, reaction times, and methanol-to-oil ratios. The combination of mussel-derived catalysts with microwave technology resulted in reduced reaction times and 100% selectivity under conditions of 1.5% catalyst loading, 10 min reaction time, and a methanol-to-oil ratio of 15:1, showcasing the synergistic effects of transition metals. This study highlights the potential of mussel-shell-derived catalysts as a cost-effective and sustainable solution for biodiesel production. By reducing reliance on conventional methods, these findings contribute to clean energy advancements and offer a scalable, environmentally friendly pathway for renewable fuel synthesis.
Push-Out Bond Strength of Different Luting Cements Following Post Space Irrigation with 2% Chitosan: An In Vitro Study
Authors: Rifaat Shimaa , Rahoma Ahmed , Alharbi Hind Muneer , Kazim Sawsan Jamal , Aljuaid Shrouq Ali , Alakloby Basmah Omar , Farooqi Faraz A. , Taymour Noha
Published: February 2025

Background: The optimum bond strength of glass fiber posts can be compromised; it has not yet been established which final irrigant, when used in combination with luting cement, can improve this bond strength. Objectives: This study assessed the effectiveness of 2% chitosan as a final irrigant in combination with different types of luting cement used to improve the bond strength of glass fiber posts bonded to root canal-treated teeth. Methods: Thirty single-rooted anterior teeth were collected and sectioned 2 mm above the most incisal point of the cementoenamel junction. After root canal filling, post spaces were prepared and irrigated in Group I using 17% EDTA for 3 min and in Group II using 2% chitosan for 3 min. Each group was divided into three subgroups: Fiber posts were cemented in subgroup A with Fuji II Cement (resin-reinforced glass ionomer cement), in subgroup B with RelyX Unicem (self-adhesive resin cement), and in subgroup C with Metacem Refill (total-etch resin cement). Push-out bond strength (N) for each sample was measured using a universal testing machine, and the failure mode was assessed with a stereomicroscope at 30× magnification. The fiber post’s morphological structure was analyzed through scanning electron microscopy. Statistical analysis included one-way ANOVA followed by Tukey’s post hoc test in the case of significant differences between the groups. p-Values less than 0.05 were considered statistically significant. Results: This study found no statistically significant difference between using 17% EDTA and 2% chitosan as the final irrigant before post placement (p > 0.05). RelyX Unicem cement showed significant bonding strength when used with 2% chitosan in the coronal, middle, and apical thirds (p = 0.009, p = 0.02, p = 0.01, respectively). Conclusions: Chitosan at 2% can be considered a good alternative to 17% EDTA when used as a final irrigant for the post space.
Narrowband Radar Micromotion Targets Recognition Strategy Based on Graph Fusion Network Constructed by Cross-Modal Attention Mechanism
Authors: Zhang Yuanjie , Gao Ting , Xie Hongtu , Liu Haozong , Ge Mengfan , Xu Bin , Zhu Nannan , Lu Zheng
Published: February 2025

In the domain of micromotion target recognition, target characteristics can be extracted through either broadband or narrowband radar echoes. However, due to technical limitations and cost constraints in acquiring broadband radar waveform data, recognition can often only be performed through narrowband radar waveforms. To fully utilize the information embedded within narrowband radar waveforms, it is necessary to conduct in-depth research on multi-dimensional features of micromotion targets, including radar cross-sections (RCSs), time frequency (TF) images, and cadence velocity diagrams (CVDs). To address the limitations of existing identification methodologies in achieving accurate recognition with narrowband echoes, this paper proposes a graph fusion network based on a cross-modal attention mechanism, termed GF-AM Net. The network first adopts convolutional neural networks (CNNs) to extract unimodal features from RCSs, TF images, and CVDs independently. Subsequently, a cross-modal attention mechanism integrates these extracted features into a graph structure, achieving multi-level interactions among unimodal, bimodal, and trimodal features. Finally, the fused features are input into a classification module to accomplish narrowband radar micromotion target identification. Experimental results demonstrate that the proposed methodology successfully captures potential correlations between modal features by incorporating cross-modal multi-level information interactions across different processing stages, exhibiting exceptional accuracy and robustness in narrowband radar micromotion target identification tasks.
RACR-ShipDet: A Ship Orientation Detection Method Based on Rotation-Adaptive ConvNeXt and Enhanced RepBiFPAN
Authors: Zhong Jiandan , Liu Lingfeng , Song Fei , Li Yingxiang , Xue Yajuan
Published: February 2025

Ship orientation detection is essential for maritime navigation, traffic monitoring, and defense, yet existing methods face challenges with rotational invariance in large-angle scenarios, difficulties in multi-scale feature fusion, and the limitations of traditional IoU when detecting oriented objects and predicting objects’ orientation. In this article, we propose a novel ship orientation detection (RACR-ShipDet) network based on rotation-adaptive ConvNeXt and Enhanced RepBiFPAN in remote sensing images. To equip the model with rotational invariance, ConvNeXt is first improved so that it can dynamically adjust the rotation angle and convolution kernel through adaptive rotation convolution, namely, ARRConv, forming a new architecture called RotConvNeXt. Subsequently, the RepBiFPAN, enhanced with the Weighted Feature Aggregation module, is employed to prioritize informative features by dynamically assigning adaptive weights, effectively reducing the influence of redundant or irrelevant features and improving feature representation. Moreover, a more stable version of KFIoU is proposed, named SCKFIoU, which improves the accuracy and stability of overlap calculation by introducing a small perturbation term and utilizing Cholesky decomposition for efficient matrix inversion and determinant calculation. Evaluations using the DOTA-ORShip dataset demonstrate that RACR-ShipDet outperforms current state-of-the-art models, achieving an mAP of 95.3%, representing an improvement of 5.3% over PSC (90.0%) and of 1.9% over HDDet (93.4%). Furthermore, it demonstrates a superior orientation accuracy of 96.9%, exceeding HDDet by a margin of 5.0%, establishing itself as a robust solution for ship orientation detection in complex environments.
A Survey on ML Techniques for Multi-Platform Malware Detection: Securing PC, Mobile Devices, IoT, and Cloud Environments
Authors: Ferdous Jannatul , Islam Rafiqul , Mahboubi Arash , Islam Md Zahidul
Published: February 2025

Malware has emerged as a significant threat to end-users, businesses, and governments, resulting in financial losses of billions of dollars. Cybercriminals have found malware to be a lucrative business because of its evolving capabilities and ability to target diverse platforms such as PCs, mobile devices, IoT, and cloud platforms. While previous studies have explored single platform-based malware detection, no existing research has comprehensively reviewed malware detection across diverse platforms using machine learning (ML) techniques. With the rise of malware on PC or laptop devices, mobile devices and IoT systems are now being targeted, posing a significant threat to cloud environments. Therefore, a platform-based understanding of malware detection and defense mechanisms is essential for countering this evolving threat. To fill this gap and motivate further research, we present an extensive review of malware detection using ML techniques with respect to PCs, mobile devices, IoT, and cloud platforms. This paper begins with an overview of malware, including its definition, prominent types, analysis, and features. It presents a comprehensive review of machine learning-based malware detection from the recent literature, including journal articles, conference proceedings, and online resources published since 2017. This study also offers insights into the current challenges and outlines future directions for developing adaptable cross-platform malware detection techniques. This study is crucial for understanding the evolving threat landscape and for developing robust detection strategies.
The Phytochemical Profile and Antioxidant and Gastroprotective Effects of Three Varieties of Chenopodium quinoa Willd. Sprouts Cultivated in Peru
Authors: Enciso-Roca Edwin Carlos , Arroyo-Acevedo Jorge Luis , Común-Ventura Pablo Williams , Tinco-Jayo Johnny Aldo , Aguilar-Felices Enrique Javier , Ramos-Meneses Mahomi Bertha , Carrera-Palao Rosa Elizabeth , Herrera-Calderon Oscar
Published: February 2025

Chenopodium quinoa sprouts possess a superior nutritional profile relative to conventional quinoa seeds, which is mainly attributable to their germination process. Sprouting quinoa is able to preserve its substantial nutritional value while enhancing its bioavailability and digestibility. The aim of this study was to evaluate the gastroprotective effects of hydroalcoholic extracts of three varieties of quinoa sprouts (pasankalla, yellow maranganí, and black coito). The chemical compounds were determined using LC-MS (Liquid Chromatography–Mass Spectrometry). Antioxidant activity was determined using two analytical methods, 2,2-diphenyl-1-picrylhydrazyl (DPPH) and 2,2′-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid) (ABTS). To evaluate the gastroprotective effects of these hydroalcoholic extracts in Holtzman male rats, a gastric lesion was induced with 96% ethanol after the administration of the hydroalcoholic extract of the three varieties of C. quinoa sprouts. Our phytochemical analysis results reveal the presence of amino acids (valine, leucine, isoleucine, phenylalanine, tryptophane, proline, tyrosine, and arginine, among others) and their derivatives, organic acids, monosaccharides, lipids, nucleobases/nucleosides, steroids, triterpene saponins, and coumarins. The pasankalla, yellow maranganí, and black coito varieties exhibited antioxidant capacities of 36.70, 32.32, and 34.63 µmol Trolox equivalent (TE)/mg of extract for the DPPH radical and 56.61, 41.56, and 52.09 µmol TE/mg of extract for the ABTS radical, respectively. The percentage of antisecretory efficiency at a dose of 500 mg/kg for the pasankalla, yellow maranganí, and black coito varieties was 34.13%, 30.67%, and 26.67%, respectively, and the anti-ulcer effect, expressed as a percentage of inhibition of ulcer formation, was 74.7%, 67.4%, and 69.5%, respectively. In contrast, the groups treated with ranitidine and sucralfate exhibited percentages of 59.0% and 67.4%, respectively. The pasankalla quinoa exhibits more significant antioxidant activity and a stronger gastroprotective effect compared to the other varieties examined in this study. In conclusion, the hydroalcoholic extracts of the three varieties of C. quinoa sprouts exhibited a gastroprotective effect, and the pasankalla variety at a dose of 500 mg/kg exhibited a stronger protective effect on the gastric mucosa of the rats.
Study on the Influence of the Ecological Environment on the Subjective Well-Being of Farmers Around Nature Reserves: Mediating Effects Based on Environmental Cognition
Authors: Chen Ke , Cao Boyang , Pan Xinning , Wang Yang , He Dan
Published: February 2025

Improving the subjective well-being of farmers is the goal of rural revitalization. Based on the data from a survey of 956 farmers from 44 villages in six nature reserves in Liaoning province and the least squares regression model, this paper studies the impact of ecological environment quality on the subjective well-being of farmers around nature reserves and analyzes the mediating role of environmental cognition in the impact of ecological environment quality on the well-being of farmers around nature reserves. The results show that in terms of ecological environment quality, both the natural environment and the social environment have a significant positive impact on the subjective well-being of farmers around nature reserves. For every 1% improvement in the following aspects, the subjective well-being of rural households increases as follows: air quality: 25%, soil and vegetation conditions: 46%, wildlife population: 27%, medical service facilities: 23%, basic living facilities: 30%, environmental beautification facilities: 33%. Environmental cognition plays a mediating role between ecological environment quality and farmers’ subjective well-being. The influence of the natural environment and social environment on the subjective well-being of farmers outside nature reserves is higher than that inside nature reserves. This paper enriches the research on subjective well-being to a certain extent, analyzes the mechanism of the ecological environment’s influence on farmers’ subjective well-being, and provides theoretical reference for further improving farmers’ subjective well-being and promoting ecological civilization construction.
Deep Learning-Based Exposure Asymmetry Multispectral Reconstruction from Digital RGB Images
Authors: Liang Jinxing , Hu Xin , Zhou Wensen , Xiao Kaida , Wang Zhaojing
Published: February 2025

Multispectral reconstruction is an important way to acquire spectral images with a high spatial resolution as snapshots. Current deep learning-based multispectral reconstruction models perform well under symmetric conditions, where the exposure of training and testing images is consistent. However, further research has shown that these models are sensitive to exposure changes. When the exposure symmetry is not maintained and testing images are input into the multispectral reconstruction model under different exposure conditions, the reconstructed multispectral images tend to deviate from the real ground truth to varying degrees. This limitation restricts the robustness and applicability of the model in practical scenarios. To address this challenge, we propose an exposure estimation multispectral reconstruction model of EFMST++ with data augmentation and optimized deep learning architecture, where Retinex decomposition and a wavelet transform are introduced into the proposed model. Based on the currently available dataset in this field, a comprehensive comparison is made between the proposed and existing models. The results show that after the current multispectral reconstruction models are retrained using the augmented datasets, the average MRAE and RMSE of the current most advanced model of MST++ are reduced from 0.570 and 0.064 to 0.236 and 0.040, respectively. The proposed method further reduces the average MRAE and RMSE to 0.229 and 0.037, with the average PSNR increasing from 27.94 to 31.43. The proposed model supports the use of multispectral reconstruction in open environments.
Research on Value Co-Creation Evolution Mechanism of Cross-Border Cooperation in Intelligent Connected Vehicle Industry
Authors: Tang Jinhuan , Chen Yiming , Zhao Dan , Ji Shoufeng
Published: February 2025

With the continuous development of information and communication technology, “software-defined vehicle” has become the trend of the times. The intelligent connected vehicle (ICV) is becoming a new direction for the development of the automotive industry. Nevertheless, the absence of cooperative innovation in the ICV sector, the dispersal of industrial chain resources, and the absence of enduring and consistent cooperation pose significant obstacles to value co-creation. Therefore, this paper constructs a value co-creation evolutionary game model of the innovation ecosystem of the ICV industry with the automotive enterprise, an intelligent automotive solution provider and the government as players, and applies prospect theory to optimize the tripartite evolutionary game. The payment matrix is established, the expected revenue is analyzed for each player’s strategies, and the replication dynamic equation and evolutionary stability strategy are analyzed. Finally, the theoretical research is validated through numerical simulation. The aim is to promote value co-creation by analyzing the co-evolution mechanism of various stakeholder strategies in the ICV innovation ecosystem. The results show the following: (1) The best evolutionary stability strategy is the positive cross-border cooperation between the automotive enterprise and the intelligent automotive solution provider, while the government gradually does not provide subsidies. (2) The government’s subsidy support should be controlled within an appropriate range. If the subsidy is too great, the marginal effect of incentives will gradually weaken. (3) The players’ willingness to integrate across borders can be enhanced by a higher level of trust and resource complementarity between the automotive enterprise and intelligent automotive solution provider. Also, liquidated damages and opportunity loss can effectively prevent the occurrence of negative integration behaviors. (4) The greater the risk attitude coefficient and risk aversion coefficient of the automotive enterprise and intelligent automotive solution provider, the more conducive they are to the occurrence of positive integration behavior.
Unexpected Pediatric Cluster of Enterovirus C105, Verona, Italy
Authors: Pomari Elena , Malagò Simone , Ferrari Guglielmo , Romano Greta , Mori Antonio , Matucci Andrea , Feletti Rebecca , Bonetti Paolo , Baldanti Fausto , Castilletti Concetta , Piralla Antonio
Published: February 2025

In an epidemiologic investigation of Enterovirus (EV) infections in a Verona hospital, September 2022–September 2024, we detected EV-C105 in six pediatric patients with upper respiratory symptoms between March and May 2023. The primary objective was to describe the local incidence of EV cases. The secondary objective was to perform Sanger’s genomic characterization and the whole-genome sequencing (WGS) of EV-C105. The proportion of positive EV results was calculated based on routine molecular method testing. An available cohort of 114 underwent Sanger sequencing, and the six EV-C105 were characterized with WGS. Overall, 96% EV results were from the upper respiratory tract. The total proportion of positives in children was 83%. Out of the typed 114, 90% were Rhinoviruses and 9%, EVs. Notably, six pediatric cases were EV-C105, placing together in a unique cluster with 99% of nucleotides belonging to the European lineage with the highest Average Nucleotide Identity, including EV-C104, EV-C109, and EV-C118. Our data describes the first cluster indicating that EV-C105 incidence may be higher than previously estimated. However, a limitation for affirming this hypothesis is the lack of a more in-depth epidemiological investigation on a larger case series with the possibility of including data from coordinated laboratories.
China’s Urban–Rural and Trade Inequality in Water Footprint
Authors: Liu Gang , Li Yonghua
Published: February 2025

The economic inequalities impede the equal distribution of water among various household groups, potentially leading to inequal access to this vital resource. By integrating a multi-regional input–output model with household expenditure, we investigate the water footprint (WF) for ten income groups in each of the provinces and evaluate water inequality among regions, households, and expenditure categories comprehensively. Our findings reveal significant disparities in water footprints, with urban households exhibiting nearly three times the WF of rural residents. Wealthier eastern provinces show higher per capita consumption-based WFs compared to the less developed western regions. The interregional trade exacerbates water inequality because water-intensive goods are produced in less developed regions and are being consumed in more developed provinces. This study underscores the importance of targeted policies to address water inequality, achieve sustainable water management, and promote equitable water use in the face of increasing water demand and supply imbalances.
Mapping Groundwater-Dependent Vegetation Zones: Application of GIS and Multicriteria Analysis with Field Validation
Authors: Rodríguez Osmel Abreu , Arumí José Luis , Urrutia Roberto
Published: February 2025

Wetlands with shallow water tables allow the development of groundwater-dependent vegetation, which is fundamental to the functioning and conservation of these ecosystems. Despite their importance, only 8% of the wetland area in Chile is protected. The lack of specific research on regions such as the center-south of the country hinders the protection and effective management of these ecosystems. This study presents an economical and practical methodology for mapping phreatophytic vegetation zones in a wetland in south-central Chile, using geographic information systems (GIS) and field validation. Through a literature review, five predictor parameters of the relationship between groundwater and vegetation in wetlands were selected. Using a multi-criteria analysis based on these five selected parameters, a map was generated to identify areas of high influence of groundwater on vegetation, which allowed the definition of ten zones to identify the type of vegetation and validate the methodology. The results indicated that 100% of the selected areas presented conditions of soil moisture and phreatophytic vegetation. Fourteen species were identified, of which nine are phreatophytes, corroborating that the parameters selected for mapping are indicators of areas where the existing vegetation depends on groundwater. It was demonstrated that the applied methodology offers a solid and accessible tool to map and identify the relationship between groundwater and vegetation in wetlands, generating valuable information that provides visibility to these ecosystems for better management and conservation.
A Novel Reconstruction Model for the Underwater Sound Speed Field Utilizing Ocean Remote Sensing Observations and Argo Profiles
Authors: Liu Yuhang , Li Ming , Li Hongchen , Wang Penghao , Liu Kefeng
Published: February 2025

The sound speed in the ocean has a considerable impact on the characteristics of underwater acoustic propagation. The swift gathering of the underwater three-dimensional (3D) sound speed field is essential for target detection, underwater acoustic communication, and navigation. Currently, the reconstruction of the underwater sound speed utilizing satellite remote sensing data of the sea surface has emerged as a significant area of research. However, dynamic activities within the ocean result in varying degrees of perturbation in the sound speed structure. Relying solely on sea surface information will restrict the accuracy of sound speed reconstruction. In response to this issue, by utilizing multi-source satellite remote sensing data alongside Argo profiles, we first implemented the random forest (RF) algorithm to establish the statistical mapping relationship from the sea surface temperature (SST), sea level anomaly (SLA), and absolute dynamic topography (ADT) to the density, and thus, reconstructed a 3D density field. Subsequently, based on the sea surface environmental information, we introduced the underwater vertical density as a novel input for sound speed calculations and proposed a new model for 3D sound speed field reconstruction (RF-SDR). The experimental results indicate that utilizing both the sea surface environmental variables and underwater density as inputs yielded an average root-mean-square error (RMSE) of 1.51 m/s for the reconstructed sound speed, along with an average mean absolute error (MAE) of 0.85 m/s. Following the incorporation of density into the reconstruction inputs, the two error metrics exhibited reductions of 31% and 35%, respectively. And the proposed RF-SDR model demonstrated a reduction in the RMSE by 36% and in the MAE by 43% when compared with the commonly utilized single Empirical Orthogonal Function regression (sEOF-r) method. Furthermore, simulations of the sound propagation with both the reconstructed sound speed and Argo sound speed demonstrated a high degree of consistency in the computed acoustic propagation losses. The correlation coefficients consistently exceeded 0.7, thereby reinforcing the validity of the reconstructed sound speed.
Operating Condition Recognition Based Fuzzy Power-Following Control Strategy for Hydrogen Fuel Cell Vehicles (HFCVs)
Authors: Yu Yingxiao , Wang Kun , Fan Yukun , Tang Xiangyu , Huang Minghao , Bao Junjie
Published: February 2025

To reduce hydrogen consumption by hydrogen fuel cell vehicles (HFCVs), an adaptive power-following control strategy based on gated recurrent unit (GRU) neural network operating condition recognition was proposed. The future vehicle speed was predicted based on a GRU neural network and a driving cycle condition recognition model was established based on k-means cluster analysis. By predicting the speed over a specific time horizon, feature parameters were extracted and compared with those of typical operating conditions to determine the categories of the parameters, thus the adjustment of the power-following control strategy was realized. The simulation results indicate that the proposed control strategy reduces hydrogen consumption by hydrogen fuel cell vehicles (HFCVs) by 16.6% with the CLTC-P driving cycle and by 4.7% with the NEDC driving cycle, compared to the conventional power-following control strategy. Additionally, the proposed strategy effectively stabilizes the battery’s state of charge (SOC).
USE OF ADSORPTION REFRIGERATION EQUIPMENT IN THE BUILDING'S AIR CONDITIONING SYSTEM
Authors: Lukyanov Vasily , Sultanguzin Ildar , Bo-Dakkah Baydaa , Kurzanov Sergey , Yavorovsky Yuriy
Published: February 2025

Adsorption cooling is a promising area in the field of modern cooling technologies. The research presented in the article is aimed at studying adsorption cooling in order to provide moderate cold for indoor air conditioning, as well as at developing a scientific basis for experimental testing of a refrigeration unit. The paper describes in detail the principle of operation of adsorption cooling. Silica gel is used as an adsorbent, and water is used as a refrigerant. The advantage of adsorption cooling is the use of environmentally friendly refrigerants such as water. The article deals with theoretical aspects of heat and mass transfer processes in the adsorbent layer. Based on the analysis existing developments in the field of solar-powered adsorption conditioning are suggested as recommendations for future research in this area. The creation of autonomous solar-energy refrigeration units using a new generation of adsorption thermal transformers is an important step towards solving the problem of energy saving. Important priorities are to improve the design of devices of such installations and search for new working pairs of devices. The use of solar energy reduces the cost of operating the plant. Autonomy and simple design ensure the reliability and ease of use of such systems.
Oxidative stress in semen of infertile men: the related factors
Authors: Nguyen Dac Nguyen , Le Minh Tam , Cao Ngoc Thanh
Published: February 2025

Objectives: Objectives: This study aimed to determine the relationship between oxidative stress measured by oxidation-reduction potential (ORP) and semen analysis results in infertile cases, along with factors associated with ORP levels.

Methods: This cross-sectional study included 150 men from infertile couples as determined by WHO guidelines. General characteristics, including age, disease history, smoking and drinking habits, semen analysis, sperm chromatin dispersion assay (SCD), and ORP, were evaluated for all subjects.

Results: The average age of participants was 34.32 ± 5.43 years old. The mean value of ORP was 0.98 ± 0.90 mV/106 sperm/mL. Patients with a history of smoking and mumps were associated with increased ORP in semen (p = 0.025 and p = 0.035, respectively). Additionally, high BMI patients also had higher ORP results.

Conclusion: Infertile men with a history of smoking and a history of mumps increased oxidative stress in semen. Elevated BMI was also a risk factor for oxidative stress in semen. Oxidative stress could be a factor that affects negatively sperm quality

Key words: semen analysis, oxidative stress, oxidation-reduction potential
Research on identification of some common Staphyloccoci species on healthy human skin using biological methods
Authors: Vo Dai Hoc , Duong Thi Ngoc Mai , Tran Dinh Binh
Published: February 2025

Background and objectives: Research on identification of some common Staphyloccoci species on healthy human skin at the University of Medicine and Pharmacy, Hue University with the aim of using biological methods to biologically identify and survey the distribution of S. aureus, S. epidermidis and S. saprophyticus on healthy human skin.

Subjects and methods: Cross-sectional descriptive study of the results of isolation by routine bacterial culture at the Department of Microbiology, Hue University Hospital.

Results: Identification of staphylococci on healthy human skin by biological methods on 249 staphylococci strains, of which S. aureus had 11 strains (4.4%), S. epidermidis had 128 strains accounting for 51.4%, S. saprophyticus had 74 strains accounting for 36.6% and other CoNS had 36 strains accounting for 14.5%. The biological identification method with Gram staining, catalase, coagulase, mannitol fermentation, hemolysis and novobiocin susceptibility testing for the diagnosis of staphylococci, in particularly, the two important tests, coagulase and novobiocin resistance are the most important to identify S. aureus, S. epidermidis and S. saprophyticus which does not require high equipment requirements, is not technically demanding, and can give results quite quickly (possibly within 36 - 48 hours).

Conclusion: Biological methods can be used to identify some staphylococci species to meet the needs of microbiological diagnosis at the district level.

Key words: Identification, biology, S. aureus, S. epidermidis and S. saprophyticus.
Gestão e retenção de talentos na era digital no setor da saúde
Authors: Santos Fernanda Maria de Almeida , Bajouco Helena , Rebelo Paulo Alexandre Pinto Portugal
Published: February 2025

A gestão de talentos no setor da saúde enfrenta desafios significativos num contexto de transformação tecnológica e digitalização crescente. Este artigo analisa as condições atuais de gestão de talentos, com foco na retenção de jovens profissionais e no desenvolvimento de competências digitais. Baseado numa análise documental e num questionário estruturado, o estudo identifica barreiras como a insuficiência de políticas de formação contínua, a falta de feedback regular e a ausência de planos de carreira personalizados. Os resultados apontam para a necessidade de estratégias integradas que combinem formação, flexibilidade laboral e mentorias cruzadas, de forma a promover a motivação e a retenção de talentos no setor da saúde.
Biomimética na melhoria da dispersão de sementes da Bertholletia excelsa na Amazônia
Authors: Benedito Lucas Henrique , Foppa Janecler
Published: February 2025

Este artigo acadêmico aborda o papel fundamental desempenhado pela cutia (Dasyprocta spp.)   na dispersão de sementes de castanha-do-Pará (Bertholletia excelsa) em ecossistemas tropicais da América do Sul, com uma atenção especial na região amazônica.  A castanha-do-Pará é uma espécie de árvore produtora de sementes comestíveis, altamente valorizadas por suas propriedades nutricionais e econômicas.  A cutia, por sua vez, é um pequeno roedor que habita essas áreas tropicais e tem uma estreita relação ecológica com a castanheira-do-Pará.   O estudo analisa como a cutia desempenha um papel central na dispersão das sementes da castanha-do-Pará, promovendo a regeneração da espécie vegetal e a manutenção da biodiversidade na floresta amazônica através do uso da tecnologia e biomimética.
IDENTIFICACIÓN DE LAS CONTRIBUCIONES CIENTÍFICA SOBRE ECOSISTEMA DIGITAL PARA EMPRENDEDORES
Authors: Ojeda Beltrán Adelaida , Botero Quintero Silvana María , Jiménez Quintero Rafael Antonio
Published: February 2025

El objetivo propuesto en esta investigación surge de la necesidad de conocer la producción científica sobre ecosistema digital. Este proyecto investigativo se aborda desde una metodología mixta se presenta en una primera fase de forma cuantitativa, utilizando como fuente de información la producción científica indexada en la base de datos SCOPUS. En una segunda fase se presenta la interpretación de los datos mediante un estudio ciencionométrico, utilizando parámetros bibliométricos que permitieron el tratamiento de documentos indexados, esto permitió describir la evolución de la actividad científica, los países e instituciones activos, autores más productivos y los principales temas investigados con el objetivo de determinar el estado y describir la evolución de la literatura en este campo. En una tercera fase se aplicó la técnica de análisis de contenido mediante la utilización del Software VOSviewer versión 1.6.13. Entre los resultados más relevantes, derivado del análisis de concurrencia de términos y su respectiva representación gráfica, se evidencia un aumento importante en la cantidad de investigaciones, baja interacción entre las redes de colaboración de los autores, presencia de investigadores e instituciones latinoamericanas en producción con alto impacto, así como la existencia de nuevas oportunidades de desarrollo para investigaciones futuras.