bluuebunny/crossref_metadata_2025 huggingface dataset:
Gender equality in South African higher education: A scholarly analysis of the National Development Plan
Authors: Sokani Andile
Published: December 2024

This study offers a thorough examination of South Africa's National Development Plan (NDP), emphasising its dedication to advancing gender equality in higher education. Notwithstanding constitutional assurances of equality, considerable gender discrepancies endure in South African higher education institutions (HEIs), with women encountering institutional obstacles that impede their entry and achievement. The research utilises a systematic review approach, consolidating current academic literature to discern the problems and opportunities related to the NDP's gender equality objectives. Critical findings indicate that structural obstacles, including socio-cultural views and financial limitations, substantially hinder women's engagement in higher education. The under-representation of women in leadership positions within higher education institutions fosters a cycle of inequity, as cultural beliefs and institutional regulations frequently neglect the distinct problems encountered by female students. The investigation underscores the necessity of employing an intersectional approach to comprehend the intricacies of gender inequality in higher education. This study emphasises the importance of executing targeted interventions and unified national policies to cultivate an inclusive educational environment that empowers women and corresponds with the overarching objectives of sustainable development. By resolving these difficulties, South Africa can advance towards genuine gender equality in its higher education system, thereby fostering national development and social progress.
Conflict resolution in indigenous communities: A social work perspective
Authors: Alpha Rakgwata Phoke , Tumelo Sekgobela
Published: December 2024

Indigenous communities possess rich traditions of conflict resolution rooted in their cultural values, collective decision-making, and community involvement. However, the imposition of Western legal frameworks and colonial histories has often disrupted these practices, leading to increased tensions and unresolved conflicts. This study explored conflict resolution within Indigenous communities, emphasizing the role of social work in facilitating culturally appropriate processes. The study employed a qualitative approach, incorporating interviews with Indigenous leaders, social workers, and community members, alongside a review of relevant literature on traditional practices and social work interventions. Social workers play a crucial role as facilitators, helping to navigate tensions and bridging gaps between traditional practices and contemporary needs. Challenges include a lack of cultural competency and the need for ongoing community engagement. The integration of Indigenous knowledge systems into conflict resolution practices enhance outcomes and foster healing. Social workers prioritize cultural humility and active listening, ensuring that Indigenous voices lead the resolution process. By supporting the reclamation of traditional conflict resolution methods and advocating for culturally sensitive practices, social workers empowered Indigenous communities, promote resilience, and facilitate more effective conflict resolution. This perspective underscores the necessity of collaboration, respect, and recognition of Indigenous sovereignty in all social work interventions.
Building farming resilience to climate change through social assistance in South-Eastern Zimbabwe
Authors: Ndhlovu Emmanuel
Published: December 2024

Agriculture is the major source of livelihood and income for about 80% of the Zimbabwean population. However, in recent decades, climate change, political standoffs, hyperinflation, and an energy crisis have held the sector hostage. Policy and academic scholarship have mainly focused on reforming agricultural policies. Studies on the diagnostic potential of non-contributory social assistance in increasing resilience and recovery from shocks are limited. Focusing on south-eastern Zimbabwe, this article identifies climate change-related farming challenges. It explores how social assistance, cash transfers and material transfers, in particular, can generate the resilience of smallholder farmers to climate change. The article utilised mixed methods research data collected between June and December 2022. The study shows increased use of improved inputs, increased farm output and asset ownership, risk coping and non-farm investment, household income, food security, and production capabilities. The results provide a sufficient empirical rationale for promoting social assistance and smallholder agriculture interactions. It shows how social assistance interventions generate multiplier effects in smallholder farming. The government should normalise the increasing demand for smallholder farming products to promote agriculture through social protection.
Pengaruh Pertumbuhan Ekonomi, Suku Bunga, Inflasi, dan Perpajakan terhadap Investasi di Indonesia: Analisis Periode 2003-2022
Authors: Ariyadi Ridho , Yunani Ahmad , Sopiana Yunita
Published: December 2024

The purpose of this study is to examine how taxes, interest rates, inflation, and economic growth affect investment in Indonesia. The variables analyzed included economic growth, interest rates, inflation, and taxes in relation to investment in Indonesia. The study used time series data from 2003 to 2022 and applied quantitative analysis, focusing on measurable data presented through equations, tables, and other formats. The empirical findings indicate that interest rates and economic growth both have a positive and significant impact on investment. While taxes also show a positive impact, their effect is not statistically significant. In contrast, inflation has a negative impact on investment. These findings may provide valuable insights for policymakers in formulating strategies to promote investment in Indonesia.
Analysis of Regional Financial Capabilities and Independence and Their Effect on Economic Growth in Bali Province in 2019–2021
Authors: Diputra Gde Indra Surya
Published: December 2024

While financial independence and regional economic growth have been recognized as key factors in public sector success, there is limited understanding of the specific dynamics in Bali Province, especially during the pandemic period of 2019-2021. This knowledge gap hinders an accurate evaluation of regional financial capability and independence, as well as their impact on Bali's economic growth. Thus, the purpose of this study was to analyze and describe the impact of regional financial capacity and independence on economic growth in Bali during 2019-2021. A quantitative descriptive research design was employed, using multiple linear regression analysis at a 95% confidence level (p<0.05). The results showed that both regional financial capacity and independence had a significant effect on economic growth in Bali. The analysis indicates that the regional financial independence ratio during 2019-2021 was low, showing an instructive relationship pattern. Meanwhile, the regional financial capacity ratio, though relatively limited, showed a positive relationship pattern. Additionally, fiscal decentralization and economic growth were found to negatively affect Bali’s poverty rate from 2003 to 2011. Overall, regional financial capacity and independence were shown to have a significant impact on the region’s economic growth. Further research is needed to explore the predisposing factors that affect economic growth, both external and internal
Analisis Pengaruh Sektor Keuangan terhadap Inflasi di Indonesia
Authors: Andini Natasya Putri , Pasaribu Esti
Published: December 2024

This research aims to determine the influence of the Indonesian financial sector on inflation. The research used data collected from secondary sources, such as Bank Indonesia, the Federal Reserve Bank of St. Louis, and Investing.com. The independent variables in this study were the Composite Stock Price Index, JIBOR, and bond yield, while the dependent variable included inflation. Vector Autoregression (VAR) or Vector Error Correction Model (VECM) was employed as the research method. The findings showed that inflation was positively and significantly impacted by the Composite Stock Price Index over the long run. Conversely, JIBOR significantly and negatively impacted inflation over the long run. In contrast, bond yield had no effect on inflation. Overall, inflation was positively and significantly affected by the Composite Stock Price Index, JIBOR, and bond yield when considering the short term.
A SYSTEMATIC REVIEW OF RESEARCH ON SOFT SKILLS FOR EMPLOYABILITY
Authors: Villegas Christian
Published: December 2024

Science mapping was utilized in this systematic review of research to analyze the body of knowledge on soft skills for employability.  ​​The research review selected high impact articles, charted the "intellectual structure", and recorded the volume, development rate, and geographical spread of this literature. Forty-five English-language, Scopus-indexed documents that were published between 2013 and 2023 made up the database of this review.  The review revealed that the documents on soft skills for employability has slightly grown over the recent years with an average of 6 documents published in each year of 2017 to 2021.  The field was mostly dominated by scholars from Europe and Asia. Four "schools of thought" were identified through author co-citation analysis as the "intellectual structures” of soft skills for employability.  These are: Soft Skill Development of Students, Employers’ Expectations on Graduates, Key Soft Skills, and Measuring Employability. Analysis of the document content resulted in the conclusion that there is a clear agreement in the literature that employability and career preparedness are difficult notions that cannot be simply defined, quantified, or put into practice.  A significant gap between the demands of the actual world and our educational system in terms of soft skills has been determined.  The research recommends "skillfying the syllabus" or "skillification" in order to guarantee that soft skills are taught in the curriculum.
TRENDS IN ARTIFICIAL INTELLIGENCE-INFUSED ENGLISH LANGUAGE LEARNING: A COMPREHENSIVE BIBLIOMETRIC AND CONTENT REVIEW
Authors: Wahyuni Sri , Hidayanto Pancoro Setyo Putro Nur , Efendi Anwar
Published: December 2024

Notwithstanding the increase in research on artificial intelligence-infused English language learning, several issues remain inadequately addressed. Thus, this paper provides a systematic review and analyzes previous studies to pinpoint fruitful knowledge gaps and outline approaches for future research directions. Two approaches, bibliometric and descriptive content analysis, were employed in this study. Firstly, we extracted data for bibliometric analysis from the Scopus database, covering publications from 1996 to 2024. The findings show that the topic peaked in 2024, with 107 articles published. China was the most cited country, with 1.215 citations, and the most productive country, with 327 articles. The International Journal of Emerging Technologies in Learning published the majority of the articles. The research theme evolved to emphasize English learning and student involvement through mobile learning. We applied descriptive content analysis to selected papers published between 2014 and 2024. Theoretically, the findings suggest that addressing knowledge gaps can enhance the integration of artificial intelligence in English language learning. Empirically, the mixed studies used descriptive statistics collected through observation and questionnaires, with a medium sample size selected through random sampling, a commonly used research design. These approaches can potentially expand the scholarly literature on this subject.
Does Agricultural Environmental Regulation Improve Green Production Efficiency of Cotton?
Authors: Zhao Xiaodi , Wu Qingjun , Sun Yue
Published: December 2024

Based on the panel data of 12 major cotton-producing provinces in China from 2000 to 2021, the green total factor productivity of cotton is calculated and decomposed by super efficiency EBM-GML index. On this basis, FGLS model is used to analyze the impact of environmental regulation on cotton GTFP and its mechanism. The results show that: First, the cotton GTFP in China has been rising in the undulation during the sample period, with an annual rate of 1.5%, and it is mainly driven by the green technology progress, with the deterioration of scale efficiency the main restricting factor. Secondly, agricultural environmental regulation contributes to improve the cotton GTFP. With the strengthening of environmental regulation, government increases the agricultural scientific research investments, which stimulates the innovation and improves the green production efficiency of cotton. Thirdly, there is a nonlinear reversed U-shaped relationship between agricultural environmental regulation and the cotton’s GTFP. Since the intensity of environmental regulation in each major cotton-producing province in China has not hit the optimal value yet, we recommend local governments to institute flexible environmental regulation policies that adapt more closely to each region to promote the green development of cotton industry.
Integrating IoT with Adaptive Beamforming for Enhanced Urban Sensing in Smart Cities
Authors: Enahoro Sunday , Ekpo Sunday C. , Uko Mfonobong , Elias Fanuel , Alabi Stephen
Published: December 2024

The exponential growth of Internet of Things (IoT) devices in smart city environments presents significant challenges, including spectrum congestion, interference, energy inefficiency, and scalability. To address these issues, we propose SmartBeam+, a novel adaptive beamforming algorithm designed to optimize communication performance in dense IoT networks. SmartBeam+ dynamically adjusts beamforming weights using real-time Channel State Information (CSI) to maximize the Signal-to-Interference-and-Noise Ratio (SINR), minimize Bit Error Rate (BER), and suppress interference effectively. Extensive simulations compare SmartBeam+ with conventional algorithms such as Zero-Forcing (ZF), MVDR, and LMS, across key performance metrics: SINR, BER, energy efficiency, reliability, throughput, and latency. Results show that SmartBeam+ consistently achieves superior performance, with SINR values ranging from 20 dB to 13 dB, BER as low as 0.0001, and 30 dB interference suppression. SmartBeam+ maintains 20 bps/W energy efficiency and achieves a reliability of 92%, significantly outperforming other methods, especially under high node density and interference levels. Furthermore, network lifetime is prolonged up to 90 hours, and latency is reduced to as low as 5 ms, making SmartBeam+ ideal for time-sensitive applications such as disaster management and urban sensing. These results highlight SmartBeam+ as a scalable, energy-efficient, and robust solution for next-generation IoT networks in smart cities.
Application of pseudoinfectious viruses in transient gene expression: combining efficient expression with regulatory compliance
Authors: Zauatbayeva Gulzat , Kulatay Tolganay , Ingirbay Bakytkali , Shakhmanova Zhanar , Keyer Viktoriya , Zaripov Mikhail , Zhumabekova Maral , Shustov Alexandr V.
Published: December 2024

Transient gene expression (TGE) is commonly employed for protein production, but its reliance on plasmid transfection makes it challenging to scale up. An alternative TGE method is presented, utilizing pseudoinfectious alphavirus as an expression vector. Pseudoinfectious viruses (PIV) and a replicable helper construct were derived from the genome of the Venezuelan equine encephalitis virus. The PIV carries a mutant capsid protein that prevents packaging into infectious particles, while the replicable helper encodes a wild-type capsid protein but lacks other viral structural proteins. Although PIV and the helper cannot independently spread infection, their combination results in increased titers in cell cultures, enabling easier scale-up of producing cultures. The PIV-driven production of a model protein outperforms that of alphavirus replicon vectors or simple plasmid vector. Another described feature of the expression system is the modification to immobilized metal affinity chromatography (IMAC) allowing purification of His-tagged recombinant proteins from conditioned medium in the presence of substances that can strip metal from the IMAC columns. The PIV-based expression system allows for the production of milligram quantities of recombinant proteins in static cultures, without the need for complex equipment such as bioreactors, and complies with regulatory requirements due to its distinction from common recombinant viruses.
EvoBagNet: Efficient Ensemble Bagging Learning Model Enhanced with Evolutionary Algorithm in IT Stock Prediction
Authors: Bashir Umar , Singh Kuljeet , Mansotra Vibhakar , Khanday Akib Mohi Ud Din , Neshat Mehdi
Published: December 2024

The rapid economic growth in recent years has led to a surge in stock market participation, necessitating accurate stock price prediction to mitigate investment risks and maximize returns. However, stock price’s dynamic nature and intrinsic volatility pose significant challenges to traditional statistical and machine learning (ML) models, which often struggle with overfitting, poor robustness, and limited generalization. To address these challenges, this study introduces EvoBagNet, an evolutionary Bagging ensemble learning model specifically designed for robust and high-accuracy stock price prediction. The proposed framework integrates nine state-of-the-art ML techniques, encompassing tree-based methods, neural networks, and both boosting and bagging ensemble approaches, applied to recent datasets from nine prominent IT sector companies. Extensive experimentation was conducted using multiple train-test split ratios to evaluate the scalability and adaptability of the models under diverse scenarios. The performance of EvoBagNet was assessed against six evaluation metrics, revealing its superior accuracy and robustness compared to alternative models. EvoBagNet demonstrated exceptional prediction accuracy across all datasets, achieving performance scores of 97.0%±0.7, 98.3%±0.5, 97.3%±0.8, 97.4%±0.6, 97.0%±1.0, 98.6%±0.4, 98.8%±0.4, 91.7%±1.2, and 98.4%±0.3 for Tech Mahindra, Mindtree, Infosys, Wipro, TCS, Mphasis, L&T Tech, HCL, and Coforge, respectively. These results highlight EvoBagNet’s potential as a powerful tool for stock price forecasting, offering significant implications for informed investment strategies and financial decision-making. This study underscores EvoBagNet’s effectiveness in addressing the limitations of traditional ML models, paving the way for its application in dynamic and high-stakes financial markets.
Cheese Whey, Buttermilk and Dairy Wastewater to Promote Mixotrophic Metabolism in Arthrospira (Spirulina) platensis: Effect on Biomass Composition, Phycocyanin Content, and Fatty Acids Methyl Ester Profile
Authors: Baraldi Luca , Usai Luca , Torre Serenella , Fais Giacomo , Casula Mattia , Dessi Debora , Nieri Paola , Concas Alessandro , Lutzu Giovanni Antonio
Published: December 2024

This study explores the mixotrophic cultivation of Arthrospira platensis using dairy byproducts, specifically scotta whey (SW), buttermilk wastewater (BMW), and dairy wastewater (DWW), to promote biomass production and enhance the composition of bioactive compounds. By assessing various concentrations (1%, 2%, and 4% v v-1) of these byproducts in a modified growth medium, the research aims to evaluate their effect on A. platensis growth, phycocyanin (C-PC) content, and fatty acid methyl ester (FAME) profiles. The results show that the optimal biomass production was achieved with 2% scotta and dairy wastewater, reaching maximum concentrations of 3.30 g L⁻¹ and 3.19 g L⁻¹, respectively. Mixotrophic cultivation led to increased C-PC yields, especially in buttermilk and dairy wastewater treatments, highlighting the potential for producing valuable pigments. Additionally, the FAME profiles indicated minimal changes compared to the control, with oleic and γ-linolenic acids being dominant in mixotrophic conditions. These findings support the viability of utilizing dairy byproducts for sustainable A. platensis cultivation, contributing to a circular bio-economy while producing bioactive compounds of nutritional and commercial interest.
Robust and Long-Lasting Immunity and Protection in Mice Induced by Lipopolyplex-Delivered mRNA Vaccines Expressing the Prefusion Protein of Respiratory Syncytial Virus
Authors: Shan Xuchang , Han Ruiwen , Cheng Xueting , Bing Jialuo , Qi Zhenyong , Sun Shucai , Wang Tangqi , Chu Qiaohong , Deng Yao , Zhai Desheng , Tan Wenjie
Published: December 2024

Objectives: Respiratory syncytial virus (RSV) is the leading cause of lower respiratory tract infections in infants and children. mRNA vaccines based on the lipopolyplex (LPP) platform have been previously reported, but they remain unapplied in RSV vaccine development. In this study, we developed a novel LPP-delivered mRNA vaccine that expresses the respiratory syncytial virus prefusion protein (RSV pre-F) to evaluate its immunogenicity and protective effect in a mouse model. Methods: We synthesised mRNAs with gene modification for RSV pre-F and prepared mRNA vaccines using the LPP delivery platform, named as RSV pre-F LPP-mRNA. RSV pre-F protein expression in mRNA vaccines was characterized in vitro. Then we evaluated the effects of the immune response and protection of this mRNA vaccine in mice until to 24 weeks post-vaccination. Results: Following the booster immunisation, robust and long-lasting RSV F-specific IgG antibodies were detected in the serum of mice. which exhibited Th1/Th2 balanced IgG response and cross-neutralising antibodies against different subtypes (RSV A2, B18537, and clinical isolate hRSV/C-Tan/BJ 202301), with a clear dose-response relationship observed. RSV F-specific IgG antibodies were maintained in the mice for an extended period, lasting up to 18 weeks post-immunisation. Concurrently, multifunctional RSV F-specific CD8+T cells (IFN–γ, IL-2, TNF- α) were detected in mice. After the RSV A2 challenge, RSV pre-F LPP-mRNA vaccine led to significant reduction of viral replication, while reduced pathological damage was observed in lung tissue. Conclusions: The LPP-delivered mRNA vaccine expressing RSV pre-F induces a robust and long-lasting immune response and protection, indicating good prospects for further development and application.
A Methodological Framework for Assessing Overtourism in Insular Territories – Case Study Santorini Island, Greece
Authors: Leka Akrivi , Lagarias Apostolos , Stratigea Anastasia , Prekas Panayiotis
Published: December 2024

This paper aims at addressing sustainability concerns in vulnerable insular territories. Such concerns are due to the rising overtourism phenomenon that affects islands at a rapidly escalating pace; and renders sustainable local development of these outstanding areas – from a natural and cultural viewpoint – at stake. Towards this end, this work capitalizes on current literature and attempts to structure a methodological framework and a respective set of indicators’ groups that are capable of assessing dimensions of overtourism in each single tourism destination, thus providing evidence-based and more robust guidelines for articulating policy decisions that can remedy incidents of overtourism. The proposed methodological framework follows a place-based approach and combines tourism demand and supply data with environmental, social, economic and spatial data and respective indicators for assessing tourism density and intensity of each destination’s tourism pattern and related multi-dimensional impacts. Validation of both the proposed framework and indicators’ groups is conducted in Santorini Island, Greece, i.e., an island that lies at top positions of many lists of destinations, marked as suffering by overtourism. Results show that Santorini Island is confronted with severe overtourism impacts, which are highly affecting its identity, productive model and spatial pattern, while endangering its natural and cultural wealth.
Revolutionizing Cardiology: The Role of Artificial Intelligence in Echocardiography
Authors: Maturi Bhanu , Dulal Subash , Ibrahim Atif , Ramakrishna Manasa , Chinta Viswanath , Nanda Navin C. , Sharma Ashwini , Ravipati Harish
Published: December 2024

Artificial Intelligence (AI) in echocardiography represents a transformative leap in the realm of cardiology, refining diagnostic accuracy and mitigating human error. AI, often erroneously equated with robotics or automation, transcends mere mechanical operations. It encompasses the capacity of machines to emulate human decision-making processes and problem-solving abilities, augmenting rather than replacing human expertise. In echocardiography, AI has emerged as a pivotal tool, enhancing consistency and precision, elements crucial in cardiac diagnostics.
Echocardiography is indispensable in the diagnosis of cardiovascular diseases, but it is traditionally hampered by operator-dependent variability and subjective interpretation. AI intervenes here, offering high-precision automation in echocardiographic analysis. This encompasses several key phases: from image acquisition and standard view classification to cardiac chamber segmentation, structural quantification, and functional assessment. AI algorithms have demonstrated expertise-level accuracy in these domains, notably in identifying cardiac conditions such as cardiomyopathies.
The incorporation of AI into echocardiography tackles inherent challenges like variance in image capture and analysis. AI's prowess in machine learning (ML), a crucial subset of AI, specifically enhances image interpretation in echocardiography. This advancement is significant given echocardiography's reliance on the operator's subjective expertise, a reliance more pronounced than in other imaging modalities such as computed tomography (CT), nuclear imaging, and magnetic resonance imaging (MRI). AI technologies, through automated and consistent interpretations, promise to reshape echocardiographic diagnostics.
This review delves into ML's role in augmenting echocardiographic image analysis and diagnostic performance. It also examines the existing literature, highlighting AI's value in echocardiography and its potential to elevate patient care. In summary, AI's integration into echocardiography marks a pivotal shift, offering enhanced diagnostic capabilities and heralding a new era in cardiovascular care.
10-Year Evaluation of Ventilator-Associated Pneumonia (VAP) According to Initial Empiric Treatment. A Retrospective Analysis Using Real-World Data Automatically Obtained from the Clinical Information System
Authors: Rodríguez Alejandro , Berrueta Julen , Páez Carolina , Huertas Ronny , Marotta Marco , Claverias Laura , Gómez Josep , Trefler Sandra , Gómez- Bertomeu Frederic F. , Guerrero-Torres María Dolores , Pardo-Granell Sergio , Picó-Plana Ester , Selles-Sánchez Alicia , Candel Francisco Javier , Martín-Loeches Ignacio , Bodí María
Published: December 2024

Background: The aim of our study is to investigate variations in crude ICU mortality among patients with ventilator-associated pneumonia (VAP) over the past decade. We also wish to identify associated risk factors, evaluate changes in the aetiology, and assess the incidence and impact of inappropriate empirical antibiotic treatment (IEAT). Methods: We conducted a retrospective, observational, single-centre study over a 10-year period (2014-2024), including critically ill patients who developed VAP. The population was divided into three periods: P1) from 2014 to 2018 (pre-covid-19); P2) from 2019 to 2021 (covid-19); and P3) from 2022 to 2024 (post-covid-19). Binary logistic regression was used to identify which variables were independently associated with ICU mortality. Results: A total of 220 patients were included in the study (P1=47, P2=96 and P3=77 patients). The most prevalent microorganisms identified were P. aeruginosa, Klebsiella spp. and S.aureus. Significant variations in etiology were not observed over the years. The incidence of IEAT was 4.5%, with no observed differences between the study periods. Crude ICU mortality was 33.6%, with higher rates observed in IEAT (40% vs. 33.3%, p=0.73). In patients with AEAT, there was a significant decrease in crude mortality over the years from 42.2% in P1 to 22.2% in P3 (p<0.001). Age (OR=1.04; 95% CI=1.01-1.08) and P2 (OR=2.8; 95% CI=1.1-7.4) were found to be independently associated with an increased risk of mortality. Conversely, lower risk of death was associated with mean arterial pressure (OR=0.94; 95% CI=0.69-0.99) and the use of syndromic respiratory panel (OR=0.23; 95% CI=0.07-0.68). Conclusion: A reduction in crude VAP mortality over the years was observed, with no change in the aetiology or rate of IEAT. The implementation of protocols using respiratory syndromic panels could be a measure to implement to reduce VAP mortality.
New Terpenoids and Lignans from Phyllanthus acidus Fruits with Antioxidant Activity
Authors: Xin Ying , Xu Jia , Li Na , Yang Li-Ying , Zhu Hong-Tao , Zhang Ying-Jun
Published: December 2024

The fruits of Phyllanthus acidus, rich in various secondary metabolites and possessing significant antioxidant activity, have been consumed widely by many Southeast Asian people, including the Thai, Vietnamese, Burmese, Laotians, Cambodians. The extensive investigation on the chemical constituents of the fresh fruits led to the isolation and identification of 17 compounds including four new compounds (1-4). Their structures were elucidated on the basis of the extensive spectroscopic analyses. The absolute configurations of 1, 3, 4 were determined by comparison of their experimental electric circular dichroism (ECD) curves with references and calculated ECD spectra. Notably, the known lignan 13 and phenylpropanoid 15 showed obvious ABTS+ radical scavenging activities with IC50 values of 203.7 and 232.9 uM, respectively, which are comparable to the positive control, Trolox (IC50 = 176.5 ± 2.0 uM). The results indicated that P. acidus fruits can be a promising sources of antioxidant food supplement.
Sputter Deposition and Nanoindentation of FeNiCoCrCu High Entropy Alloy coating: A Molecular Dynamics Study
Authors: Anand Sriram , Yedla Natraj , Karthik Vaduganathan
Published: December 2024

High entropy alloys are being increasingly investigated for their excellent combination of properties like strength, ductility, and significant low temperature fracture toughness. In the present work, the quinary equiatomic FeNiCoCrCu alloy is studied for its sputter deposition over a [001] nickel substrate using molecular dynamics simulations, described by the embedded atom method. The influence of annealing on the mechanical properties of the HEA coating is studied using nanoindentation with a virtual spherical indenter of diameter 25Å to an indentation depth of 25Å. The alloy is observed to undergo Transformation Induced Plasticity (TRIP) deformation – with activation and annihilation of stacking faults.
Dynamic Optimization of Transportation Networks in Logistics Using Long Short-Term Memory Neural Networks
Authors: Wang Junbo , Li Xinshi
Published: December 2024

The optimisation of transportation networks is of paramount importance in the context of logistics systems. In the face of changing demand and environmental conditions, the dynamic optimisation of these networks represents a crucial means of improving logistics efficiency and reducing operating costs. This study proposes a dynamic optimisation model of a logistics and transportation network based on a Long Short-Term Memory (LSTM) neural network. Building on the existing model, our scheme combines LSTM networks, attention mechanisms, and reinforcement learning to capture time-dependent and dynamic behaviour in the network, thereby improving the ability to predict future demand and transportation delays. A hybrid architectural approach has been introduced to enhance the adaptability of LSTM networks in terms of adjusting routing decisions and network configurations in real time. Furthermore, the model is optimised through a multi-objective optimisation framework that balances travel time, cost, and congestion. The experimental results demonstrate that the proposed model exhibits superior performance compared to the traditional optimization method in dynamic routing tasks across a range of logistics scenarios.
The Eyes: A Source of Information for Detecting Deepfakes
Authors: Tchaptchet Elisabeth , Tagne Elie Fute , Acosta Jaime , Kamhoua Charles A. , Rawat Danda B.
Published: December 2024

Nowadays, the phenomenon of Deepfake is crucial as it enables the creation of extremely realistic images capable of deceiving anyone, thanks to deep learning tools based on Generative Adversarial Networks (GANs). These images are used as profile pictures on social media with the intent to sow discord and perpetrate scams on a global scale. In this study, we demonstrate that these images can be identified through various imperfections present in the synthesized eyes, such as the irregular shape of the pupil and the difference between the corneal reflections of the two eyes. These defects result from the absence of physical and physiological constraints in most GAN models. We have developed a two-level architecture capable of detecting these fake images. This approach begins with an automatic segmentation method for the pupils to verify their shape, as real image pupils naturally have a regular shape, typically round. Next, for all images where the pupils are not regular, the entire image is analyzed to verify the reflections. This step involves passing the facial image through an architecture that extracts and compares the specular reflections of the corneas of the two eyes, assuming that the eyes of real people observing a light source should reflect the same thing. Our experiments with a large dataset of real images from the Flickr-FacesHQ and CelebA datasets, as well as fake images from StyleGAN2 and ProGAN, show the effectiveness of our method. Our approach maintains good stability of physiological properties during deep learning, making it as robust as some single-class deepfake detection methods. The results of the tests on the selected datasets demonstrate higher accuracy compared to other methods.
Laryngeal Papillomatosis
Authors: Levinson Jared , Karle William Edward
Published: December 2024

Laryngeal papillomatosis and recurrent respiratory papillomatosis are caused by the human papillomavirus. It is characterized by papillomatous growths and is the most common benign disease of the larynx. Juvenile onset RRP is characterized by more aggressive disease compared to adult onset RRP. Patients often require frequent surgical procedures, with an increasing shift towards office-based treatment. A variety of surgical and adjuvant medical therapies are available with mixed responses. New targeted therapies and vaccines are currently under investigation as potential adjuncts in the management.
New Sparkling Wines from Traditional Grape Varieties and Indigenous Yeasts: Focusing on Wine Identity to Address the Industry's Crisis
Authors: Basile Teodora , Debiase Giambattista , Mazzone Francesco , Scarano Leonardo , Cardone Maria Francesca , Marsico Antonio Domenico
Published: December 2024

In recent years, there has been a noticeable decline in wine consumption. This trend can be attributed to a shift in consumer preferences towards alcoholic alternatives such as beer and fruit-based mixed drinks. What sets wine apart from these alternatives is its unique identity, is its perceived identity: a combination of brand, heritage, and terroir. The origin and production details of wine significantly influence consumer’s purchasing decisions. In this study, we have produced new sparkling wines using either commercial or native yeast strains along with traditional Italian grape varieties. This approach preserves the unique character of the region, represented by the typical grape varieties, and incorporates the concept of “microbial terroir,” which is linked to the indigenous yeasts. The wines produced have been analyzed for conventional parameters such as pH, titratable acidity, volatile acidity, alcohol content, and residual sugar, as well as for their aromatic profile through GC-MS analysis. To evaluate the acceptance of the wines, a sensory analysis was conducted, and NIR spectra were collected to identify the factors influencing their preferences. The positive reception of these innovative sparkling wines was connected to their chemical composition, offering valuable insights for the future production of similar products.
Tracing the Origin of the Genetic Code to Dipeptide Sequences in Proteomes
Authors: Wang Minglei , Aziz M Fayez , Caetano-Anollés Gustavo
Published: December 2024

The safekeeping of the genetic code has been entrusted, for the most part, to interactions between aminoacyl-tRNA synthetases and their cognate tRNA. In a previous phylogenomic study, chro-nologies of RNA substructures, protein domains and dipeptide sequences uncovered the early emergence of an ‘operational’ code in the acceptor arm of tRNA prior to the implementation of the 'standard' genetic code in the anticodon loop of the molecule. This history likely originated in synthetase urzymes capable of aminoacylation and peptide bond formation, but was driven by episodes of molecular co-evolution and recruitment that promoted flexibility and folding of pri-mordial proteins. Here, we show that dipeptide sequences offer deep time insight into the chro-nology of code emergence. A phylogeny describing the evolution of the repertoire of 400 canonical dipeptides reconstructed from an analysis of 4.3 trillion dipeptide sequences across 1,561 prote-omes revealed the overlapping temporal emergence of dipeptides containing Leu, Ser and Tyr, followed by those containing Val, Ile, Met, Lys, Pro, and Ala, all of which supported the opera-tional RNA code. Our study uncovers a hidden evolutionary link between a protein code of di-peptides – arising from the structural demands of emerging proteins – and an early operational code shaped by co-evolution, editing, catalysis and specificity.
Viscoelastic, Shape Memory, and Fracture Characteristics of 3D Printed Photosensitive Epoxy-Based Resin Under the Effect of Hydrothermal Ageing
Authors: Alsaadi Mohamad , Sebaey Tamer A , Hinchy Eoin P. , McCarthy Conor T. , Lima Tielidy A. de M. de , Portela Alexandre , Devine Declan M
Published: December 2024

The use of 3D printed polymers and their composites as shape memory materials in various smart engineering applications has raised the demand for such functionally graded sustainable materials. This study aims to investigate the viscoelastic, shape memory, and fracture toughness properties of the epoxy-based ultraviolet (UV)-curable resin. A UV-based DLP (Digital Light Processing) printer was employed for the 3D printing (3DPg) epoxy-based structures. The effect of the hydrothermal accelerating ageing on the various properties of the 3D printed (3DPd) components was examined. The viscoelastic performance in terms of storage modulus, loss modulus, and glass transition temperature (Tg) was evaluated. The shape memory behaviour in terms of shape fixity and shape recovery results were determined using dynamic mechanical thermal analysis (DMTA). DMTA is used to reveal the molecular mobility performance through three different regions, i.e., glass region, glass transition region, and rubbery region. The shape-changing region (Within the glass transition region) between the Tg value from the loss modulus and the Tg value from the tan delta was analysed. The temperature-memory behaviour was investigated for flat and circular 3DPd structures to achieve sequential deployment. The critical stress intensity factor values of the single-edge notch bending (SENB) specimens have been explored for different crack inclination angles to investigate mode I (opening) and mixed-mode I/III (Opening and tearing) fracture toughness. This investigation study can be employed to create highly complex shape memory 3DPd durable structures that can be reconfigured multiple times under large deformation.
Balneotherapy as a Complementary Intervention for Stress and Cortisol Reduction: Findings from a Randomized Controlled Trial
Authors: Rapolienė Lolita , Rapolis Dovydas , Bredelytė Aelita , Taletavičienė Giedrė , Fioravanti Antonella , Martinkėnas Arvydas
Published: December 2024

Background: In our modern era, stress has become a pervasive challenge, affecting individuals across all ages and backgrounds. Acute or chronic stress and elevated cortisol levels, are known to impair neurological function and hinder rehabilitation outcomes. Therefore, effective treatment methods that reduce stress, enhance mental health, and promote overall well-being are urgently needed. This study aimed to evaluate the seasonal effects of balneotherapy on distress, salivary cortisol, and integrative outcomes. Methods: A multicenter, randomized controlled, single-blinded parallel-group trial was conducted in 2023 across six medical spa centers in Lithuania. Participants with stress intensity >3 points (VAS) underwent combined natural resource-based therapies over a 1- to 2-week treatment period. Outcomes were assessed using the General Symptom Distress and Arizona Integrative Outcomes scales, along with salivary cortisol measurements. Results: The results demonstrated a significant reduction in distress intensity by 1–3.5 points (VAS), with winter interventions showing greater efficacy compared to other seasons. Participants also experienced an increase in well-being by up to 3 points (VAS), improved stress management by up to 1.9 points (VAS), and a reduction in salivary cortisol levels by 0.9 units following winter-based treatments. Conclusions: Our study provides robust evidence for the stress-reducing effects of balneotherapy, particularly highlighting the enhanced efficacy of winter interventions. These findings are especially relevant for neurological rehabilitation, where stress reduction and improved autonomic regulation can support neuroplasticity, recovery processes, and overall quality of life. This research offers valuable insights for developing holistic, seasonally optimized strategies to aid stress management and promote neurological health.
Intra-Tumoral Lymphocytic Infiltration Is Associated with Favorable Prognosis in Suboptimal Surgery in High-Grade Serous Ovarian Carcinoma
Authors: Harada Hiroshi , Hachisuga Toru , Harada Yoshikazu , Shibahara Mami , Murakami MIdori , Nuratdinova Fariza , Higami Shota , Tohyama Atsushi , Kinjo Yasuyuki , Ueda Taeko , Kurita Tomoko , Matsuura Yusuke , Nakayama Toshiyuki , Yoshino Kiyoshi
Published: December 2024

Background: Immunoreactive (IR) subtype is one of the subtypes of high-grade serous ovarian carcinoma (HGSOC) with intra-tumoral lymphocytic infiltration. A positive prognostic correlation between IR subtype and R0 + optimal surgery has been reported. This study investigates the prognostic significance of the tumor-infiltrating lymphocytes (TILs) in the suboptimal surgery group of HGSOCs. Methods: After reviewing 318 malignant ovarian tumors detected in our database between 2000 and 2017, 74 HGSOCs with supplemental p53 immunostaining were selected. Differences in progression-free survival (PFS) and overall survival (OS) between the 2 groups of the IR subtype and the other subtypes were investigated. Based on pathological findings, HGSOCs were divided into 2 groups: those with or without abundant TILs. Results: Abundant TILs were detected in 17 cases of HGSOC (22.9%). Clinicopathological characteristics including age, CA125, FIGO stage, and residual disease did not show significant differences between the 2 groups. Lymph node metastasis was more common in the IR subtype group (p=0.04). In the suboptimal surgery group, the 5-year PFS and OS (Kaplan-Meier estimates) in cases with (n=10) or without (n=21) abundant TILs were 10% and 0% (P=0.097) and 70% and 28.5% (P=0.012), respectively. The median time (range) to OS in cases with or without abundant TILs were 58 (34-81) months and 39 (22-55) months, respectively. Multivariate analysis in OS showed significant differences in TILs. Conclusions: Abundant intra-tumoral lymphocytic infiltration is an independent and favorable prognostic indicator for the suboptimal surgery group in HGSOCs, and is associated with treatment response via cancer immunity.
Cybersecurity Risks from Vulnerable Electronics in Illicit Streaming Devices
Authors: Watters Paul A
Published: December 2024

Illicit Streaming Devices (ISDs) are proliferating globally, offering unauthorized access to digital content but exposing significant vulnerabilities in their electronic and software configurations. This study investigates the electronic architecture and operational security risks inherent in ISDs, focusing on their susceptibility to exploitation as malware vectors and botnet components. A vulnerability assessment identified critical flaws, including outdated firmware, insecure communication protocols, and weak system defenses. Additionally, malware analysis of associated consumer applications revealed that nearly half contained malicious code, enabling remote device control and integration into command-and-control infrastructures. These vulnerabilities expose consumer networks and broader digital ecosystems to advanced threats, including distributed denial-of-service (DDoS) attacks. The study emphasizes the importance of addressing hardware and firmware security at the design stage and advocates for stricter regulatory standards and consumer awareness to mitigate the cybersecurity risks posed by these compromised electronic systems.
Discovery of a Novel Multitarget Analgesic Through an In Vivo-guided Approach
Authors: Zhen Guo , Do Nayeon , Manh Nguyen Van , Ha Hee-Jin , Kim Hee , Kim Hyunsoo , Choi Kwanghyun , Ann Jihyae , Lee Jeewoo
Published: December 2024

Pain is a multifaceted condition influenced by peripheral, central, immune, and psychological factors. Targeting multiple pathways provides a holistic approach, enhancing efficacy, minimizing side effects, and reducing tolerance compared to single-target drugs. This study utilized an in vivo-guided approach to discover a novel multitarget analgesic, identifying compound 29 from a new scaffold (3) inspired by the pharmacophores of opiranserin and vilazodone. Analog screening in the formalin test identified compound 29 as a lead candidate for further study. Compound 29 demonstrated high potency in the formalin model, with an ED50 of 0.78 mg/kg in the second phase and a concentration-dependent trend in the first phase. In the spinal nerve ligation (SNL) neuropathic pain model, it exhibited dose-dependent analgesic effects, increasing withdrawal thresholds by 24% and 45% maximum possible effect (MPE) at 50 and 100 mg/kg, respectively. Mechanistic studies revealed that its analgesic activity is primarily driven by strong triple uptake inhibition, particularly at DAT and SERT, combined with high-affinity 5-HT2A receptor antagonism. Pharmacokinetic studies in rats showed intraperitoneal administration provided a 5-fold increase in exposure and a 2-fold improvement in stability compared to oral administration. It also displayed high blood-brain barrier permeability, indicating suitability for CNS drugs. In vitro, compound 29 was nontoxic to HT-22 cells but exhibited potential hERG inhibition and strong CYP3A4 inhibition with minimal effects on other isozymes. In conclusions, compound 29 is a potent, multitarget analgesic discovered through an in vivo-guided approach. Ongoing optimization aims to mitigate side effects and further enhance its therapeutic profile.