bluuebunny/crossref_metadata_2025 huggingface dataset:
All You Need to Know About TACE: A Comprehensive Review of Indications, Techniques, Efficacy, Limits, and Technical Advancement
Authors: Lanza Carolina , Ascenti Velio , Amato Gaetano Valerio , Pellegrino Giuseppe , Triggiani Sonia , Tintori Jacopo , Intrieri Cristina , Angileri Salvatore Alessio , Biondetti Pierpaolo , Carriero Serena , Torcia Pierluca , Ierardi Anna Maria , Carrafiello Gianpaolo
Published: January 2025

Transcatheter arterial chemoembolization (TACE) is a proven and widely accepted treatment option for hepatocellular carcinoma and it is recommended as first-line non-curative therapy for BCLC B/intermediate HCC (preserved liver function, multifocal, no cancer-related symptoms) in patients without vascular involvement. Different types of TACE are available nowadays, including TAE, c-TACE, DEB-TACE, and DSM-TACE, but at present there is insufficient evidence to recommend one TACE technique over another and the choice is left to the operator. This review then aims to provide a comprehensive overview of the current literature on indications, types of procedures, safety, and efficacy of different TACE treatments.
Enhancing the Toughness of Composite Cold-Formed Steel Beams with ECC and Different Stiffener Arrangements and Shapes
Authors: Nawar Mahmoud T. , Silem Ola A. , Ibrahim Ishac , Maaly Hassan M. , Ibrahim Yasser E.
Published: January 2025

This study investigates the toughness and load capacity of various innovative beam configurations of cold-formed steel beams (CFSB) using both ordinary concrete slabs and engineered cementitious composite (ECC) slabs. A finite element analysis with ABAQUS 20 was conducted on double-channel, sigma, G, and omega sections, both with and without inverted lips, as well as the effects of L, channel, and trapezoidal stiffeners and length-to-depth ratios. The double-omega section with ordinary concrete achieved the highest first peak load of 365.2 kN and a toughness increase of 181.1%. Inverted lips enhanced toughness in the double-G and sigma sections, with increases of 156.9% and 158.3%, respectively. Among ECC configurations, the double-omega section with ECC3 slab reached 387.4 kN and a toughness increase of 199.5%. Thinner ordinary concrete sections (70 mm and 90 mm) negatively impacted toughness, emphasizing the need for adequate thickness. Trapezoidal stiffeners also improved toughness. These findings highlight the importance of geometrical design and material selection in optimizing CFSB performance, offering valuable insights for future design practices.
Impact of a Long-Term Home-Based Rehabilitation Program on Quality of Life, Balance, and Autonomy in Adults with Disabilities
Authors: Barria Patricio , Andrade Asterio , Yelincic Alejandro , Córdova Bessié , Covarrubias-Escudero Felipe , Cifuentes Carlos , Appelgren-Gonzalez Juan
Published: January 2025

Background: Rehabilitation is a critical process for enhancing functionality, independence, and quality of life in individuals with disabilities. Grounded in the biopsychosocial model, it addresses physical, emotional, and social dimensions through personalized, evidence-based interventions. By integrating standardized assessments and continuous evaluation, rehabilitation has the potential to promote recovery and support active participation in society. Objectives: This study evaluated the impact of a long-term, multidisciplinary, home-based rehabilitation program on quality of life, balance, and functional autonomy in adults with neuromusculoskeletal disabilities. Methods: A total of 559 participants received individualized interventions from a team of physical therapists, occupational therapists, psychologists, and other health professionals. Functional independence, balance, depressive symptoms, and quality of life were assessed using the Barthel Index, Berg Balance Scale, Beck Depression Inventory, and SF-36 questionnaire, respectively. Results: A longitudinal analysis comparing pre- and post-intervention outcomes revealed statistically significant improvements (p < 0.001) across all metrics. The Barthel Index median increased from 85 to 90 points, indicating greater functional independence, while the Berg Balance Scale improved from 39 to 47 points, reflecting reduced fall risk. Depressive symptoms decreased, with Beck Depression Inventory scores dropping from 12 to 9, and both physical and mental health components of the SF-36 showed marked enhancements. Conclusions: These findings demonstrate the program’s effectiveness in addressing both physical and emotional needs, emphasizing the value of extended, personalized, home-based care in improving health, autonomy, and overall quality of life for individuals with disabilities. This study underscores the potential of multidisciplinary approaches to support long-term rehabilitation in diverse populations.
Emergence and Development of a News Hate Cycle About Immigrants: The Case of Immigrants Transferred from the Canary Islands to the Spanish Mainland
Authors: Martínez Pilar Rodriguez , Villanueva Antonia Sánchez , Campos Pilar Rios , Joya Lucía Martinez , Sánchez Antonio Jesús Segura , Espinosa Joaquín Jaime Sánchez , Lirola Francisco Villegas , Berlanga Maria Carmen López
Published: January 2025

In this article, we present the findings of research focused on the emergence and development of an immigration-related news hate cycle in Spain. During the period from 24 to 29 October 2023, there was an unusual increase in social media posts about the Spanish government’s transfer of immigrants from the Canary Islands to the Spanish mainland. Based on the monitoring of 918 posts collected through AI media-monitoring software (Determ d.o.o), our study identify how hate speech against immigrants was generated and spread. In particular, we aim to identify the main actors and influencers involved in its creation, dissemination, and transformation, and how these actors manipulate interpretative frameworks by introducing arguments about a supposed comparative grievance between the Spanish people and immigrants in order to foment hatred and strengthen attitudes of rejection towards immigrants, presenting them as invaders, criminals, and terrorists. In this news cycle, hate speech reaches its peak when the press of trustworthy information echoes the disinformation. The analysis of the actors involved and the temporal sequence on social media and websites reveals how they achieve this. It also allows us to develop tools to counter the spread of hate speech.
Cultivating Slow Curating in Times of Acceleration
Authors: Semedo Alice , Dicuonzo Fabiana
Published: January 2025

This paper introduces key ideas and issues in the changing debates on heritage practices and sustainability. It draws attention to the capacities of heritage to activate and unfold new meanings and increase the resilience of territories and landscapes—namely depopulated ones—through slow curating processes. We will argue that slow curating processes cultivate ‘slower’ ways of knowing, act as seedbeds of emergence and as catalysts to transformation that recuperate the pieces of a fragmented territory while also helping to re-locate its existence—its past, its present and its future—in balance with and within a constellation of living networks. Through heritage criticality, we will investigate territory interpretation and intervention examples that adopt disruptive, cross-, inter-, and trans-disciplinary approaches, including artistic, architectural, urban, performative, and curatorial practice, as effects and methods of slow curating taken as a public activity. We will pay special attention to its production contexts (reasons, subjects…), to what and how resonance dispositions and axes are produced within these non-linear public acts, and how the co-presence of past and the future is extended so heritage public acts may engender new forms—of knowledge, being…—and become a resource for current times.
A Comparative Study of Two WAAM Patterns for Structures with Grid Fin Characteristics
Authors: Xian Guo , Pan Jingbang , Li Qingshan
Published: January 2025

As a critical component of rocket systems, the grid fin is widely applied in the aerospace industry. Compared to traditional manufacturing methods and other additive manufacturing (AM) techniques, wire arc additive manufacturing (WAAM) is more advantageous in its time and cost efficiency, especially when it is utilized in the large-scale production of components. Given the significant effect of the welding strategies on the quality of manufactured parts, we investigated two distinct WAAM printing orientations, horizontal, or lie (L), and perpendicular, or stand (S), using a small-scale model. The feasibility of these two printing approaches was evaluated by analyzing the surface quality, microstructure, and mechanical properties at the junctions of the grid fin. Furthermore, a finite element analysis (FEA) was adopted to simulate and analyze the main factors, including the temperature distribution, deformation, and stress profiles at the welding joints, in both AM strategies. The integrated approach adopted in this study provides important insights for optimizing the application of WAAM in grid fin manufacturing. In summary, our results indicate that while the L mode is easily manufacturable and exhibits stable properties, the S mode holds significant market potential if its welding parameters are optimized.
Tissue Paper Softness: A Comparison Between Different Experimental Assessment Approaches
Authors: Mendes António de O. , Vieira Joana C. , Carta Ana M. , Curto Joana M. R. , Amaral Maria E. , Costa Ana P. , Fiadeiro Paulo T.
Published: January 2025

In this work, four different experimental assessment approaches, namely, the Tissue Softness Analyzer (TSA), a Subjective Evaluation (SUB), the Kawabata Evaluation System (KES), and an Optical System (OPT), were used for the evaluation of softness on a set of 29 different tissue paper products. After processing and the interpretation of the results given by each one of the used methods, a procedure was implemented in the current work to make a comparison between them. The procedure consists in tracking the position of the tissue paper products on a ranking table, regardless of what values were obtained through each one of the four used methods independently. This comparison revealed to be very useful in determining the differences verified between methods allowing to conclude which ones were the least and the most concordant, and, at the same time, enabling us to identify interesting cases of tissue paper products on the set that caught our attention for their distinctive characteristics.
Theoretical Study of Pentacoordinated Lanthanide Single-Ion Magnets via Ab Initio Electronic Structure Calculation
Authors: Wang Yu-Xi , Wang Yu-Fei , Yin Bing
Published: January 2025

A theoretical study, based on ab initio electronic structure calculation, is performed in a group of 16 pentacoordinate Dy-SIMs. Theoretical results provide a reasonable explanation of the observed SMM performance based on a concise criterion, i.e., the co-existence of long τQTM and high Ueff. To have the desired electronic structure favoring good SMM performance, the contribution from the equatorial coordinating atoms might be even more important than that from the axial coordinating atoms. Widening the axial ∠O–Dy–O might be a probable way to improve the SMM performance of pentacoordinated Dy-SIMs. Starting from existing systems, a rigid-scan type exploration indicates the possibility of Ueff higher than 1600 K.
Identification of Interactive Genetic Loci Linked to Insulin Resistance in Metabolic Syndrome—An Update
Authors: Elfaki Imadeldin , Mir Rashid , Elnageeb Mohamed E. , Hamadi Abdullah , Alharbi Zeyad M. , Bedaiwi Ruqaiah I. , Javid Jamsheed , Alrasheed Tariq , Alatawi Dalal , Alrohaf Basmah M. , Abunab Mohammed K. , Muqri Turki Ahmed
Published: January 2025

Metabolic syndrome is a metabolic disorder characterized by hypertension, dyslipidemia, impaired glucose tolerance, and abdominal obesity. Impaired insulin action or insulin resistance initiates metabolic syndrome. The prevalence of insulin resistance is increasing all over the world. Insulin resistance results in the defective metabolism of carbohydrates and lipids, in addition to low-grade chronic inflammation. Insulin resistance is associated with metabolic syndrome, which is a risk factor for a number of pathological conditions, such as Type 2 diabetes (T2D), cardiovascular disease (CVD), nonalcoholic fatty liver disease (NAFLD), and polycystic ovarian syndrome (PCOS). Genome-wide association studies have increased our understanding of many loci linked to these diseases and others. In this review, we discuss insulin resistance and its contribution to metabolic syndrome and these diseases. We also discuss the genetic loci associated with them. Genetic testing is invaluable in the identification and stratification of susceptible populations and/or individuals. After susceptible individuals and/or populations have been identified via genetic testing or screening, lifestyle modifications such as regular exercise, weight loss, a healthy diet, and smoking cessation can reduce or prevent metabolic syndrome and its associated pathologies.
Effect of Relocation, Social Housing Changes, and Diarrhea Status on Microbiome Composition of Juvenile Cynomolgus Macaques (Macaca fascicularis)
Authors: McGrew Keely , de Oca Nicole Monts , Kosten Therese A.
Published: January 2025

Social housing changes are likely stressful and can be associated with diarrhea, the most common health problem noted in captive macaque populations. Diarrhea may reflect a negative shift in the gut flora (“gut dysbiosis”). This study reported on changes in the gut microbiome composition of juvenile primates (Macaca fascicularis) that experienced a change in social housing and exhibited diarrhea. A matched-case–control design was utilized to compare fecal samples from gut-unhealthy animals to healthy counterparts (n = 61). Baseline samples from recently imported animals were collected during routine sedation events. When an animal experienced a housing change, the entire cohort was monitored for diarrhea. Post-relocation samples were collected from animals that exhibited diarrhea and from their matched controls. Samples were assessed via 16S rRNA next-generation sequencing for a microbiome analysis and by ELISA for cortisol levels. Fecal cortisol levels did not differ between groups or across time points. Alpha diversity increased after relocation and differed by sex with males demonstrating a greater change in alpha diversity (p < 0.01). Although exhibiting diarrhea did not affect alpha diversity levels, it was associated with increased beta diversity (p < 0.05). Understanding how the microbiome may be affected by relocation will help guide prevention strategies such as the use of specific probiotics to reduce the incidence of diarrhea.
Bacteriophages: A Challenge for Antimicrobial Therapy
Authors: Segundo-Arizmendi Nallelyt , Arellano-Maciel Dafne , Rivera-Ramírez Abraham , Piña-González Adán Manuel , López-Leal Gamaliel , Hernández-Baltazar Efren
Published: January 2025

Phage therapy, which involves the use of bacteriophages (phages) to combat bacterial infections, is emerging as a promising approach to address the escalating threat posed by multidrug-resistant (MDR) bacteria. This brief review examines the historical background and recent advancements in phage research, focusing on their genomics, interactions with host bacteria, and progress in medical and biotechnological applications. Additionally, we expose key aspects of the mechanisms of action, and therapeutic uses of phage considerations in treating MDR bacterial infections are discussed, particularly in the context of infections related to virus–bacteria interactions.
Data Mining Models in Prediction of Vancomycin-Intermediate Staphylococcus aureus in Methicillin-Resistant S. aureus (MRSA) Bacteremia Patients in a Clinical Care Setting
Authors: Chen Wei-Chuan , Wang Jiun-Ling , Chang Chi-Chuan , Lin Yusen Eason
Published: January 2025

Vancomycin-intermediate Staphylococcus aureus (VISA) is a multi-drug-resistant pathogen of significant clinical concern. Various S. aureus strains can cause infections, from skin and soft tissue infections to life-threatening conditions such as bacteremia and pneumonia. VISA infections, particularly bacteremia, are associated with high mortality rates, with 34% of patients succumbing within 30 days. This study aimed to develop predictive models for VISA (including hVISA) bacteremia outcomes using data mining techniques, potentially improving patient management and therapy selection. We focused on three endpoints in patients receiving traditional vancomycin therapy: VISA persistence in bacteremia after 7 days, after 30 days, and patient mortality. Our analysis incorporated 29 risk factors associated with VISA bacteremia. The resulting models demonstrated high predictive accuracy, with 82.0–86.6% accuracy for 7-day VISA persistence in blood cultures and 53.4–69.2% accuracy for 30-day mortality. These findings suggest that data mining techniques can effectively predict VISA bacteremia outcomes in clinical settings. The predictive models developed have the potential to be applied prospectively in hospital settings, aiding in risk stratification and informing treatment decisions. Further validation through prospective studies is warranted to confirm the clinical utility of these predictive tools in managing VISA infections.
Characterization of Broad Spectrum Bacteriophage vB ESM-pEJ01 and Its Antimicrobial Efficacy Against Shiga Toxin-Producing Escherichia coli in Green Juice
Authors: Park Eun Jeong , Lee Seungki , Na Jong Beom , Kim Ye Bin , Lee Kee Man , Park Seon Young , Kim Ji Hyung
Published: January 2025

Shiga toxin-producing Escherichia coli (STEC) infections have increased in humans, animals, and the food industry, with ready-to-eat (RTE) food products being particularly susceptible to contamination. The prevalence of multidrug-resistant strains has rendered the current control strategies insufficient to effectively control STEC infections. Herein, we characterized the newly isolated STEC phage vB_ESM-pEJ01, a polyvalent phage capable of infecting Escherichia and Salmonella species, and assessed its efficacy in reducing STEC in vitro and food matrices. The phage, belonging to the Tevenvirinae, exhibits effective bacteriolytic activity, a short latent period, large burst size, and stability under a broad pH range and moderate temperatures. Moreover, the phage demonstrated strong anti-biofilm efficacy even at low concentrations. Genomic analysis revealed that the phage was similar to the well-characterized RB49 phage (T4-like phage) but possesses distinct host-specificity-related genes that potentially contribute to its extensive host range. The efficacy of phage vB_ESM-pEJ01 was evaluated in artificially STEC-inoculated green juice samples, where it significantly reduced STEC and the abundance of Shiga toxin-producing genes at 4 and 25 °C. Therefore, these results suggest that the polyvalent phage vB_ESM-pEJ01 is a promising biocontrol agent for foodborne pathogens in RTE foods such as fresh juices.
Influence of Phosphate Marinades on the Quality and Flavor Characteristics of Prepared Beef
Authors: Wang Wanqi , Zeng Maomao , Chen Qiuming , Wang Zhaojun , He Zhiyong , Chen Jie
Published: January 2025

Phosphate has been widely used in beef to improve processing characteristics such as tenderness and water-holding capacity. However, the effects of phosphates on the quality and especially the flavor of beef are not well understood. This study investigated the influence of eight different phosphate marinade solutions on the quality and flavor of prepared beef. The results revealed that the thawing loss in the control group was 11.47%, and NaCl with sodium hexametaphosphate (SYCP) had the lowest thawing loss, with a value of 2.13%, which was reduced by 81.43% as compared to the control group. The shear force of the control group was 3.85 kg, and the shear work was 10.03 kg. The best tenderness was recorded in the NaCl with sodium hexametaphosphate (SYST) group, which had a shear force of 1.14 kg and shear work of 3.34 kg. The incorporation of phosphates suppressed fat oxidation and increased the total free amino acid content. Additionally, the levels of certain key volatile flavor compounds, particularly those associated with fat oxidation, such as hexanal, heptanal, octanal, and nonanal, were reduced. In terms of sensory evaluation, juiciness, flavor, tenderness, and overall acceptability in the treatment group were significantly increased (p < 0.05). Overall, the results indicate that adding phosphates can enhance the quality of processed beef, inhibit lipid oxidation, and improve sensory evaluation.
Microwave and Steam Processing: A Novel Approach to Modifying the Characteristics of Reconstituted Whole Wheat Flour and Dough
Authors: Liu Xuhua , Sun Qiangqiang , Yan Rong , Wang Yaqing , Wang Junying , Yang Liping , Zhai Ligong
Published: January 2025

To reduce the adverse effects of bran on whole wheat flour products. In this study, seven reconstituted whole wheat flours were prepared and used to determine the effects of microwave and steam treatment on bran. We aimed to understand the effect of modification treatment on the properties of reconstituted whole wheat flour and dough. Treatment with whole wheat flour had a significant impact on the color, solubility, and swelling. As the cooking time increased, the initial temperature (To), peak temperature (Tp), and final temperature (Tc) of pasting and enthalpy (Hp) decreased. The combination of microwave and steam modification increased water absorption and stabilization time, leading to improved fermentation performance and cooking stability of the dough. The modified whole wheat flour and dough exhibited a significant decrease in crystallinity, possibly due to the degradation of the crystalline and amorphous regions of the starch granules during heat treatment. Upon modification treatment, the spiral β-turn structure was transformed into an irregular curled and β-sheet structure, and the β-sheet ratio increased significantly (p < 0.05). The modification of bran through microwave treatment (700 W for 30 s) followed by steam treatment (10 min) enhanced the processing performance of reconstituted whole wheat flour, offering substantial potential for the development of novel products and the optimization of industrial production efficiency.
Purine but Not Pyrimidine De Novo Nucleotide Biosynthesis Inhibitors Strongly Enhance the Antiviral Effect of Corresponding Nucleobases Against Dengue Virus
Authors: Bonnac Laurent F. , Dreis Christine D. , Rai Madhu , Geraghty Robert J.
Published: January 2025

Every year, dengue virus affects hundreds of millions of individuals worldwide. To date, there is no specific medication to treat dengue virus infections. Nucleobases, the base of a nucleoside without ribose, are understudied as potential treatments for viral infections. Antiviral nucleobases are converted in infected cells to their corresponding nucleoside triphosphate active form. Importantly, the conversion of nucleobases to their active nucleotide form and their antiviral effect can be enhanced when combined with de novo nucleotide biosynthesis inhibitors. In this work, we evaluated seven purine and pyrimidine nucleobases alone or combined with six purine or pyrimidine de novo nucleotide biosynthesis inhibitors, including novel prodrugs. Our study revealed that while a strong potentiation of purine nucleobases by purine de novo nucleotide biosynthesis inhibitors was observed, the pyrimidine nucleobases were not potentiated by pyrimidine de novo nucleotide biosynthesis inhibitors, possibly highlighting a significant difference between the modulation of purine versus pyrimidine de novo pathways and their impact on nucleobase potentiation. Most significant antiviral effects and potentiation were observed for Favipiravir, T-1105, and ribavirin nucleobases combined with purine nucleotide de novo synthesis inhibitors. These results are significant because drug combinations may solve the limited efficacy observed for some antiviral nucleobase drugs such as Favipiravir.
Diet Quality and Caloric Accuracy in AI-Generated Diet Plans: A Comparative Study Across Chatbots
Authors: Kaya Kaçar Hüsna , Kaçar Ömer Furkan , Avery Amanda
Published: January 2025

: Background/Objectives: With the rise of artificial intelligence (AI) in nutrition and healthcare, AI-driven chatbots are increasingly recognised as potential tools for generating personalised diet plans. This study aimed to evaluate the capabilities of three popular chatbots—Gemini, Microsoft Copilot, and ChatGPT 4.0—in designing weight-loss diet plans across varying caloric levels and genders. Methods: This comparative study assessed the diet quality of meal plans generated by the chatbots across a calorie range of 1400–1800 kcal, using identical prompts tailored to male and female profiles. The Diet Quality Index-International (DQI-I) was used to evaluate the plans across dimensions of variety, adequacy, moderation, and balance. Caloric accuracy was analysed by calculating percentage deviations from requested targets and categorising discrepancies into defined ranges. Results: All chatbots achieved high total DQI-I scores (DQI-I > 70), demonstrating satisfactory overall diet quality. However, balance sub-scores related to macronutrient and fatty acid distributions were consistently the lowest, showing a critical limitation in AI algorithms. ChatGPT 4.0 exhibited the highest precision in caloric adherence, while Gemini showed greater variability, with over 50% of its diet plans deviating from the target by more than 20%. Conclusions: AI-driven chatbots show significant promise in generating nutritionally adequate and diverse weight-loss diet plans. Nevertheless, gaps in achieving optimal macronutrient and fatty acid distributions emphasise the need for algorithmic refinement. While these tools have the potential to revolutionise personalised nutrition by offering precise and inclusive dietary solutions, they should enhance rather than replace the expertise of dietetic professionals.
Morphological and Chemical Changes in the Hemolymph of the Wax Moth Galleria mellonella Infected by the Entomopathogenic Fungus Conidiobolus coronatus
Authors: Boguś Mieczysława Irena , Kaczmarek Agata , Wrońska Anna Katarzyna , Drozdowski Mikołaj , Siecińska Lena , Mokijewska Ewelina , Gołębiowski Marek
Published: January 2025

Hemolymph enables communication between organs in insects and ensures necessary coordination and homeostasis. Its composition can provide important information about the physiological state of an insect and can have diagnostic significance, which might be particularly important in the case of harmful insects subjected to biological control. Galleria mellonella Linnaeus 1758 (Lepidoptera: Pyralidae) is a global pest to honey bee colonies. The hemolymph of its larvae was examined after infection with the soil fungus Conidiobolus coronatus (Constantin) Batko 1964 (Entomophthorales). It was found that after one hour of contact with the fungus, the volume of the hemolymph increased while its total protein content decreased. In larvae with a high pathogen load, just before death, hemolymph volume decreased to nearly initial levels, while total protein content and synthesis (incorporation of 35S-labeled methionine) increased. The hemolymph polypeptide profile (SDS-PAGE followed by autoradiography) of infected insects was significantly different from that of healthy larvae. Hemocytes of infected larvae did not surround the fungal hyphae, although they encapsulated small foreign bodies (phase contrast microscopy). Infection had a negative effect on hemocytes, causing oenocyte and spherulocyte deformation, granulocyte degranulation, plasmatocyte vacuolization, and hemocyte disintegration. GC-MS analysis revealed the presence of 21 compounds in the hemolymph of control insects. C. coronatus infection caused the appearance of 5 fatty acids absent in healthy larvae (heptanoic, decanoic, adipic, suberic, tridecanoic), the disappearance of 4 compounds (monopalmitoylglycerol, monooleoylglycerol, monostearin, and cholesterol), and changes in the concentrations of 8 compounds. It remains an open question whether substances appearing in the hemolymph of infected insects are a product of the fungus or if they are released from the insect tissues damaged by the growing hyphae.
Islam and the Pan-Abrahamic Problem
Authors: Sijuwade Joshua R.
Published: January 2025

This article aims to formulate a philosophical problem that is grounded upon the Pan-Abrahamic nature of early Islam, focusing on the implications that this has for understanding the identity of the contemporary Islamic community. This philosophical problem—termed the Pan-Abrahamic Problem—is structured around the examination of Prophet Muhammad’s leadership and the inclusivity of the early Islamic community, as proposed by Fred Donner in the form of the Pan-Abrahamic Thesis. The formulation of this philosophical problem is presented through the lens of the philosophical criteria of continuity and connectedness of aims (doctrine) and organisation, as proposed by Richard Swinburne. This philosophical problem will, thus, offer a challenge against traditional exclusivist narratives within Islam, ultimately aiming to emphasise the inclusive and pluralistic foundation of the religion and the significance of this for the contemporary Islamic identity.
Non-Intrusive Monitoring of Vital Signs in the Lower Limbs Using Optical Sensors
Authors: Simões Joana , Oliveira Regina , Costa Florinda M. , Teixeira António , Leitão Cátia , Correia Pedro , Silva Ana Luísa M.
Published: January 2025

Invisible health monitoring is currently a topic of global interest within the scientific community. Sensorization of everyday objects can provide valuable health information without requiring any changes in people’s routines. In this work, a feasibility study of photoplethysmography (PPG) acquisition in the lower limbs for continuous and real-time monitoring of the vital signs, including heart rate (HR) and respiratory rate (RR), is presented. The proposed system uses two MAX30102 sensors to obtain PPG signals from the back of the thigh. As proof of concept, tests were conducted in 17 volunteers (age group between 22 and 40 years old, twelve females and five males), and the results were compared to those of reference sensors. A Pearson correlation coefficient of r = 0.92 and r = 0.77 and a mean difference of 1.2 bpm and 0.9 rpm for HR and RR, respectively, were obtained between the developed system and reference. System accuracies of 95.9% for HR and 91.3% for RR were achieved, showing the system viability for vital sign monitoring of the lower limbs.
A Combined Frame Difference and Convolution Method for Moving Vehicle Detection in Satellite Videos
Authors: Luo Xin , Li Jiatian , A Xiaohui , Deng Yuxi
Published: January 2025

To address the challenges of missed detections caused by insufficient shape and texture features and blurred boundaries in existing detection methods, this paper introduces a novel moving vehicle detection approach for satellite videos. The proposed method leverages frame difference and convolution to effectively integrate spatiotemporal information. First, a frame difference module (FDM) is designed, combining frame difference and convolution. This module extracts motion features between adjacent frames using frame difference, refines them through backpropagation in the neural network, and integrates them with the current frame to compensate for the missing motion features in single-frame images. Next, the initial features are processed by a backbone network to further extract spatiotemporal feature information. The neck incorporates deformable convolution, which adaptively adjusts convolution kernel sampling positions, optimizing feature representation and enabling effective multiscale information integration. Additionally, shallow large-scale feature maps, which use smaller receptive fields to focus on small targets and reduce background interference, are fed into the detection head. To enhance small-target feature representation, a small-target self-reconstruction module (SR-TOD) is introduced between the neck and the detection head. Experiments using the Jilin-1 satellite video dataset demonstrate that the proposed method outperforms comparison models, significantly reducing missed detections caused by weak color and texture features and blurred boundaries. For the satellite-video moving vehicle detection task, this method achieves notable improvements, with an average F1-score increase of 3.9% and a per-frame processing speed enhancement of 7 s compared to the next best model, DSFNet.
Novel Class-AB Operational Amplifier for Compact and Energy-Efficient Wake-Up Sensor Systems
Authors: AlShammary Hussam
Published: January 2025

This paper presents a novel rail-to-rail Class-AB operational amplifier tailored for wake-up systems in motion sensor applications. By addressing limitations in free Class-AB designs, such as large inrush current, unstable bias conditions, and area ineffiiency, the proposed design achieves a gain of 59 dB and unity gain frequency of 550 kHz driving a 5 pF load. The inrush current is reduced from 1 mA to 7 µA, increasing the battery life. The layout area is reduced by 53% compared to the free Class-AB design, making it highly suitable for compact implementations. Operating at a low power consumption of 2 µW with a 1.8 V supply, the amplifier achieves a Signal-to-Noise-and-Distortion Ratio (SNDR) of 22 dB. These advancements demonstrate the potential of the design for energy-efficient analog front-end solutions in IoT and portable systems.
A Parallel Image Denoising Network Based on Nonparametric Attention and Multiscale Feature Fusion
Authors: Mao Jing , Sun Lianming , Chen Jie , Yu Shunyuan
Published: January 2025

Convolutional neural networks have achieved excellent results in image denoising; however, there are still some problems: (1) The majority of single-branch models cannot fully exploit the image features and often suffer from the loss of information. (2) Most of the deep CNNs have inadequate edge feature extraction and saturated performance problems. To solve these problems, this paper proposes a two-branch convolutional image denoising network based on nonparametric attention and multiscale feature fusion, aiming to improve the denoising performance while better recovering the image edge and texture information. Firstly, ordinary convolutional layers were used to extract shallow features of noise in the image. Then, a combination of two-branch networks with different and complementary structures was used to extract deep features from the noise information in the image to solve the problem of insufficient feature extraction by the single-branch network model. The upper branch network used densely connected blocks to extract local features of the noise in the image. The lower branch network used multiple dilation convolution residual blocks with different dilation rates to increase the receptive field and extend more contextual information to obtain the global features of the noise in the image. It not only solved the problem of insufficient edge feature extraction but also solved the problem of the saturation of deep CNN performance. In this paper, a nonparametric attention mechanism is introduced in the two-branch feature extraction module, which enabled the network to pay attention to and learn the key information in the feature map, and improved the learning performance of the network. The enhanced features were then processed through the multiscale feature fusion module to obtain multiscale image feature information at different depths to obtain more robust fused features. Finally, the shallow features and deep features were summed using a long jump join and were processed through an ordinary convolutional layer and output to obtain a residual image. In this paper, Set12, BSD68, Set5, CBSD68, and SIDD are used as a test dataset to which different intensities of Gaussian white noise were added for testing and compared with several mainstream denoising methods currently available. The experimental results showed that this paper’s algorithm had better objective indexes on all test sets and outperformed the comparison algorithms. The method in this paper not only achieved a good denoising effect but also effectively retained the edge and texture information of the original image. The proposed method provided a new idea for the study of deep neural networks in the field of image denoising.
Exact Inference for Random Effects Meta-Analyses for Small, Sparse Data
Authors: Gronsbell Jessica , McCaw Zachary R. , Regis Timothy , Tian Lu
Published: January 2025

Meta-analysis aggregates information across related studies to provide more reliable statistical inference and has been a vital tool for assessing the safety and efficacy of many high-profile pharmaceutical products. A key challenge in conducting a meta-analysis is that the number of related studies is typically small. Applying classical methods that are asymptotic in the number of studies can compromise the validity of inference, particularly when heterogeneity across studies is present. Moreover, serious adverse events are often rare and can result in one or more studies with no events in at least one study arm. Practitioners remove studies in which no events have occurred in one or both arms or apply arbitrary continuity corrections (e.g., adding one event to arms with zero events) to stabilize or define effect estimates in such settings, which can further invalidate subsequent inference. To address these significant practical issues, we introduce an exact inference method for random effects meta-analysis of a treatment effect in the two-sample setting with rare events, which we coin “XRRmeta”. In contrast to existing methods, XRRmeta provides valid inference for meta-analysis in the presence of between-study heterogeneity and when the event rates, number of studies, and/or the within-study sample sizes are small. Extensive numerical studies indicate that XRRmeta does not yield overly conservative inference. We apply our proposed method to two real-data examples using our open-source R package.
Sustainability of Key Proteins in Plant-Based Meat Analogs Production: A Worldwide Perspective
Authors: Romão Bernardo , Sommo Maximiliano , Zandonadi Renata Puppin , de Holanda Maria Eduarda Machado , Borges Vinicius Ruela Pereira , Saraiva Ariana , Raposo António
Published: January 2025

The market for plant-based analogs for meat is growing exponentially. In addition to motivations related to the search for health benefits, the consumption of such products is justified by the sustainability of their production since the use of non-renewable resources and the emission of polluting gases is lower than their animal-origin equivalents. However, little information regarding the global panorama of the sustainability of plant-based meat analogues is available, mainly due to the diffuse distribution of food matrices used across the planet. In this sense, this narrative review aimed to describe the state of the art regarding the use of resources and sustainability of the inputs used as protein sources in the manufacture of plant-based meat analogues. From the review carried out, it was possible to observe that the biggest problem in producing these plant-based alternatives lies in using inputs that are not native to the countries where the products are marketed, especially in the case of South American countries. Ingredients widely used in the production of these analogues find better cultivation conditions in the northern hemisphere, as in the case of lentils, peas and chickpeas; thus, South American markets depend on imports, reducing the sustainability of the products.
Digital Economy, R&D Resource Allocation, and Convergence of Regional Green Economy Efficiency
Authors: Yi Guodong , Gao Juan , Yuan Wentao , Zeng Yan , Liu Xiang
Published: January 2025

We looked into the ways in which the digital economy helps to speed up the convergence of environmentally responsible economic efficiency across China’s regions by facilitating the flow and optimization of R&D resources. We measured the mobility of R&D capital and personnel across 30 provinces in China from 2001 to 2022 using a gravity model, assessed the efficiency of green economic using the SBM method, and determined the influence of the digital economy by the use of a fixed-effects model. (1) We identified the σ convergence (the absolute gap between per capita income or per capita economic efficiency levels of different economies gradually decreasing over time) and β convergence (the negative correlation between the rate of economic efficiency increase among various economies or regions and their initial level of economic efficiency) characteristics of green economic efficiency, discovering that the digital economy has sped up the process of convergence of environmentally responsible economic efficiency in regional areas. (2) We found a latecomer advantage in the convergence of China’s green economic efficiency, along with the advancement of the digital economy; that is, the green economic efficiency more quickly converged in less developed regions and regions with fewer resources. (3) The digital economy is able to accelerate the convergence of regional green economy efficiency through the use of internal mechanisms such as the efficient flow of research and development factors and the reasonable allocation of those factors. By identifying the impact of the digital economy on the gaps in regional green economic efficiency from the new perspective of the flow and allocation of R&D elements, this study contributes to the existing body of literature. It also provides new information regarding the ways in which the digital economy is driving the development of China’s green economy. We offer policy suggestions based on our findings to assist regions in achieving a balance between the digital economy and industrial development through the utilization of resources that are specific to the location.
Water Requirements for Hydrogen Production: Assessing Future Demand and Impacts on Texas Water Resources
Authors: Lin Ning , Arzumanyan Mariam , Rodriguez Calzado Edna , Nicot Jean-Philippe
Published: January 2025

Hydrogen is emerging as a critical component in the global energy transition, providing a low-carbon alternative for sectors such as industry and transportation. This paper aims to comprehensively address water usage in hydrogen production by exploring the water demands of different production methods and their implications for water management, particularly in Texas. Key variables influencing water consumption are identified, and potential water demands under different hydrogen market scenarios are estimated. Using spatial analysis, regions where hydrogen production may stress local water resources are identified, alongside policy recommendations for sustainable water use.
The Impact of Green Spaces on Workplace Creativity: A Systematic Review of Nature-Based Activities and Employee Well-Being
Authors: Charisi Varvara , Zafeiroudi Aglaia , Trigonis Ioannis , Tsartsapakis Ioannis , Kouthouris Charilaos
Published: January 2025

Workplace mental health is a critical social issue with significant human and economic costs, making its sustainable management essential for long-term well-being and productivity. Nature-based interventions (NBIs) offer a promising cost-effective approach to enhancing employee creativity and well-being. This paper systematically reviewed NBIs—such as outdoor exercise, green space engagement, and nature-centered activity—and their effects on workplace creativity, subjective well-being, and mental health. Following the PRISMA guidelines, a comprehensive search of PubMed, PsycINFO, Scopus, and Google Scholar yielded 508 studies published from 2017 to 2024. Seven studies met our inclusion criteria, involving real workplace settings, NBIs as primary interventions, and clear comparison groups. Analysis covered study design, sample size, intervention type, and outcomes, focusing on creativity and well-being. Risk of bias was assessed using the Cochrane Bias Risk Tool and the ROBIN-I tool. Results were grouped into five themes: mental health metrics, cognition and creativity, rehabilitation and regeneration, job and life satisfaction, and physiological outcomes. Findings highlighted the positive impact of NBIs on mental health and creativity, though results for other outcomes were mixed. Methodological variability and potential bias limited the strength of conclusions. Future research should prioritize large-scale, methodologically rigorous trials aligned with contemporary theories on workplace environments and creativity.
Research on Urban Sustainability Based on Neural Network Models and GIS Methods
Authors: Zhang Chunxia , Yu Shuo , Zhang Junxue
Published: January 2025

Ecologically sustainable urban design plays a pivotal role in mitigating climate change. This study develops an indicator group consisting of urban ecological emergy, land use change, population density, ecological services, habitat quality, enhanced vegetation index, carbon emissions, and carbon storage to assess urban sustainability. By leveraging a dataset from 2000 to 2020, we employ a neural network to predict emergy sustainability indicators over a time series, projecting the sustainable status of Xuzhou City from 2020 to 2050. The findings indicate that urbanization has led to significant changes in land use, population distribution, ecological service patterns, habitat quality degradation, vegetation fragmentation, and fluctuating carbon dynamics. Cropland constitutes the predominant land type (90.6%), followed by built-up land (8.49%). The neural network predictions suggest that Xuzhou City’s sustainable status is subject to volatility (15–20%), with stability expected only as the city matures into a developed urban area. This research introduces a novel approach to urban sustainability analysis and provides insights for policy development aimed at fostering sustainable urban growth.
Competition and Cooperation in Ride-Sharing Platforms: A Game Theoretic Analysis of C2C and B2C Aggregation Strategies
Authors: Hou Li , Geng Shidao , Kong Wenjie
Published: January 2025

The aggregation of ride-sharing platforms has forced traditional ride-sharing platforms to decide whether to join or leave these emerging platforms. This study presents a stylized model analyzing the demand, supply, and profit of two self-operated platforms, C2C platforms (such as DiDi and Uber) and B2C platforms, considering aggregation platform awareness and commissions. The study investigates the conditions under which the self-operated platforms should employ the entry strategy based on the optimization method and Cournot game theory, as well as exploring the reasons why self-operated platforms choose to withdraw after joining. The results show that in order to avoid competition, B2C platforms adopt an entry strategy, while C2C platforms adopt a non-entry strategy. Only during the off-peak period, when the awareness of the aggregation platform is very high and the level of competition between the two types of platforms is very intense, will both types of platforms adopt an entry strategy, but C2C platforms may experience a significant loss of market share, leading to a decline in social welfare. Furthermore, even if the self-operated platform chooses to withdraw, social welfare will still increase if the two self-operated platforms adopt the best strategy. The study contributes to sustainable development by promoting efficient resource allocation, reducing redundant competition, and improving overall market efficiency, thereby fostering a more sustainable urban transportation system.