bluuebunny/crossref_metadata_2025 huggingface dataset:
Machine Learning-Driven Prediction of Brain Age for Alzheimer's Risk: APOE4 Genotype and Gender Effects
Authors: Woods Carter , Xing Xin , Khanal Subash , Lin Ai-Ling
Published: August 2024

Background: Alzheimer's disease (AD) is a leading cause of dementia, significantly influenced by the Apolipoprotein E4 (APOE4) gene and gender. This study aims to use machine learning (ML) algorithms to predict brain age and assess AD risk by considering the effects of APOE4 genotype and gender.

Methods: We collected brain volumetric MRI data and medical records from 1100 cognitively unimpaired individuals and 602 AD patients. We applied three ML regression models—XGBoost, Random Forest (RF), and Linear Regression (LR)—to predict brain age. Additionally, we introduced two novel metrics, Brain Age Difference (BAD) and Integrated Difference (ID), to evaluate model performance and analyze the influence of APOE4 genotype and gender on brain aging.

Results: AD patients displayed significantly older brain ages compared to their chronological ages, with BADs ranging from 6.5 to 10 years. The RF model outperformed both XGBoost and LR in terms of accuracy, delivering higher ID values and more precise predictions. Comparing APOE4 carriers with non-carriers, the models showed enhanced ID values and consistent brain age predictions, improving overall performance. Gender-specific analyses indicated slight enhancements, with models performing equally well on both genders. It indicates that APOE4 may be a more robust predictor of brain age than gender.

Conclusion: Robust ML models for brain age prediction can be pivotal in the early detection of AD risk via MRI brain structural imaging, especially for APOE4 carriers. Such early identification may facilitate timely preventive interventions for AD.
3D Organoid Models in Cancer Immunotherapy: Bioengineering Approach for Personalized Treatment
Authors: Noorintan Syarifah Tiara , Angelius Chelsie , Torizal Fuad Gandhi
Published: August 2024

Recent advances in organoid technology have revolutionized cancer biology and thera-peutic interventions, offering personalized immunotherapy treatment. Organoids, three-dimensional cell cultures derived from patient tumors, accurately replicate the tumor microenvi-ronment, providing unprecedented insights into tumor-immune interactions and therapeutic re-sponses. In this literature-based study, we discuss various culture methods for the diverse appli-cations of organoids in cancer immunotherapy, including drug screening, personalized treatment strategies, and mechanistic studies. Additionally, we address the technological challenges asso-ciated with these methods and propose potential future solutions to accelerate the development of novel immunotherapeutic approaches. This review highlights the transformative potential of or-ganoid models in advancing preclinical cancer immunotherapy modeling, screening, and evalua-tion, paving the way for more effective and personalized cancer treatments.
The Association of Adolescent Internalizing and Externalizing Behavior Problems and Prospective Self with Alcohol and Marijuana Use
Authors: De Geronimo Francesca G , Stoddard Sarah A , Huntley Edward D , Keating Daniel P
Published: August 2024

Adolescent alcohol and marijuana use pose significant developmental risks. This study examined internalizing and externalizing problems as risk factors and prospective self as a protective factor in relation to alcohol and marijuana use. Self-report data were collected from a diverse sample (N = 2017) of 15-17-year-olds using the Youth Self Report (YSR) for behavior issues and Prospective Self, a factor derived variable reflecting future orientation, resistance to peer influence, and academic aspirations. Participants reported on 15 health risk behaviors, including alcohol and marijuana use. Weighted linear regressions evaluated associations between risk and protective factors and substance use. Model 1 included sociodemographic covariates. Model 2 added risk and protective factors, and Model 3 included interactions of internalizing and externalizing behaviors with prospective self. Results indicated higher externalizing behavior was linked to increased alcohol and marijuana use, while higher prospective self and internalizing behavior were linked to reduced alcohol use. Higher prospective self was associated with less marijuana use. Interaction terms were largely non-significant, except for the interaction between prospective self and internalizing behavior, where higher internalizing problems and high prospective self were linked to increased marijuana use. Findings highlight the importance of prospective self, especially at clinically elevated levels of behavior problems, and suggest further exploration of the unexpected positive association between internalizing behavior and prospective self with marijuana use.
Identifying Potential Therapeutic Targets in Long COVID Related Inflammatory, Coagulation, Mitochondrial, and Oxidative Stress Pathways through In Silico Approach
Authors: Kumar Suresh , Anak Sigai Philemon Telajan
Published: August 2024

Long COVID, characterized by persistent symptoms lasting from weeks to several months following initial infection with Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), significantly impacts individuals' quality of life and poses a potential long-term burden on global healthcare systems. Clinical manifestations of Long COVID are diverse, affecting multiple systems including respiratory, cardiovascular, neurological, and gastrointestinal. While the precise mechanisms underlying Long COVID remain unclear, emerging evidence suggests involvement of various bodily pathways. This study employs bioinformatics tools to investigate the mechanisms of Long COVID and identify potential drug targets associated with key pathways, including inflammation, cytokines, immune response, coagulation, mitochondrial function, oxidative stress, and autonomic dysfunction. Tools such as the National Center for Biotechnology Information (NCBI) database, PubChem, UniProt, and iGEMDOCK were utilized for pathway analysis and molecular docking. The analysis aimed to identify drug molecules that may interact with target proteins to regulate or inhibit pathway activity, yielding several potential drug candidates for further investigation.
Cost-Effectiveness Analysis of Pneumococcal Vaccine in the Pediatric Population: A Systematic Review
Authors: Vo Nam Xuan , Pham Huong Lai , Bui Uyen My , Ho Han Tue , Bui Tien Thuy
Published: August 2024

Pneumococcal disease, caused by Streptococcus pneumoniae is the leading cause of high mortality in children worldwide. The tremendous direct cost of hospital admissions and significant indirect costs from productivity loss contributed considerably to the economic burden, with vaccination being the only efficient way against the illness. Our study aims to summarize the cost-effectiveness of the pneumococcal conjugate vaccine (PCV) implemented in the pediatric population. Employing online databases from Pubmed, Embase, and Medline, we looked for economic evaluation from 2018 until March 2024. The Incremental Cost-Effectiveness Ratios (ICER) and Quality-Adjusted-Life-Years (QALY) were the primary outcomes for measuring PCV's cost-effectiveness. A 28-item CHEERS 2022 checklist was applied to assess the quality of collected studies. Of the 16 papers found, 9/16 discussed the lower-valent vaccine (PCV13, PCV10) and 7/16 examined the higher-valent vaccine. (PCV20, PCV15). PCV13 and PCV10 required more cost and generated more QALY compared to no vaccination. Both PCV15 and PCV20 averted substantial healthcare costs and yielded greater quality of life than PCV13. Additionally, PCV20 was a dominant strategy compared to PCV15. Utilizing PCV13 is a very cost-effective option compared to not getting vaccinated. Transitioning from PCV13 to PCV20 would result in higher QALY gain and more cost-saving than switching to PCV15.
A Roadmap for NF ISAC in 6G: A Comprehensive Overview and Tutorial
Authors: Hakimi Azar , Galappaththige Diluka , Tellambura And Chintha
Published: August 2024

Near-field (NF) integrated sensing and communication (ISAC) has the potential to revolutionize future wireless networks. It enables simultaneous communication and sensing operations on the same radio frequency (RF) resources using a shared hardware platform, maximizing resource utilization. NF-ISAC systems can improve communication and sensing performance compared to traditional far-field (FF) ISAC systems by employing the unique propagation characteristics of NF spherical waves with an additional distance dimension. Despite its potential, the NF-ISAC literature covers just a few specialized topics. A comprehensive survey encompassing all aspects of NF-ISAC systems has thus far been lacking. To this end, this paper systematically explores the prodigious potential of NF-ISAC technology. Specifically, an in-depth analysis of both NF and FF systems is provided, investigating their applicability in communication and sensing scenarios. Various channel model scenarios for NF and FF are discussed, emphasizing their distinguishing features. The advantages and philosophies of ISAC are further explored, opening opportunities to investigate both narrow-band and wide-band systems within NF ISAC. Case studies and simulation examples for each NF-ISAC design philosophy are provided to gain deeper insights into these system designs. An extensive literature review of existing NF-ISAC studies is conducted, exploring various methodologies, potentials, prospects, and conclusions. Finally, prospective research areas, remaining challenges, and applications of future NF-ISAC systems are discussed.
Papers in and Papers out of the Spotlight: Comparative Bibliometric and Altmetrics Analysis of Biomedical Reports with and without News Media Stories
Authors: Chaleplioglou Artemis
Published: August 2024

For decades, the discoverability and visibility of a paper relied on the readership of the academic journal where the publication was issued. The public's increasing interest in scientific research, particularly in biomedicine, has led news media outlets to play a significant role in disseminating scientific advances. This investigation, which explores the potential impact of news media stories on the citations and altmetrics of a paper, was conducted with thoroughness and rigour. A total of 2020 open access biomedical research papers, all published in the same year, 2015, and in journals with an impact factor between 10 and 14, were investigated. The papers were split into two groups based on the sole criterion of receiving or not receiving news media coverage. Papers with news media coverage accounted for 44% of the total. They received, on average, 60% more citations, 104% more blogs, 150% more X posts, 106% more Facebook reports, 40% more Wikipedia references, 85% more videos, and 51% more Mendeley readers than papers without news media coverage. The correlation between news media outlets and increased citations and altmetrics is evident. However, the broader societal impact of news media coverage, in terms of bringing scientific matters or discoveries to the public eye, appears to be more robust when compared to the reactions of the scientific community.
Deep Learning in Finance: Time Series Prediction
Authors: Muhammed Abdulkabir , Olaosun Korede Samuel , Popoola Seyi James , Byers Joe
Published: August 2024

The purpose of this project is to explore the potential of Long Short-Term Memory (LSTM), a type of recurrent neural network (RNN), as a tool for making directional predictions for assets. The focus will be on using LSTM for classifying up/down moves in stock indices, stocks, and FX rates (EUR/USD). Various financial ratios, advanced technical indicators, and volatility estimators will be used as features to enhance the predictive power of the model. Incorporating credit spreads and news indicators can also improve the model. The advantage of LSTM is its ability to handle sequences of arbitrary length, which means that longer time frames such as 5-day, 10-day, or 1-week returns can be used for prediction. Before using RNNs, exploratory data analysis (EDA) will be performed to understand the underlying patterns in the data. This may include dimensionality reduction techniques such as autoencoding, self-organizing maps, or decision tree regression. The results of the EDA will be used to guide the selection of features for the LSTM model. It is important to note that long memory and stationarity are common characteristics of time series data, such as interest rates or economic indicators. Power-law autocorrection, Hurst exponent fractional, or Markov processes may be used to model these data. Predicting 5-day, 10-day returns for equities or 1-week, 1-month returns for financial factors presents two challenges. First, a large amount of data is required, typically 7–10 years of data. Second, positive autocorrelation in the 5-day or 10-day returns in equity time series must be isolated.
Investigation of the Effect of Spray Dryer Encapsulation on Oleuropein from Olive Leaf Extracts Prepared at Two Different pH Levels
Authors: Tarchi Ines , Yangui Thabèt , Pop Oana Lelia , Simon Elemér , Vodnar Dan Cristian , Ranga Florica , SZABO Katalin , Suharoschi Ramona , Aït-Kaddour Abderrahmane , Bouaziz Mohamed
Published: August 2024

This study employed High-Performance Liquid Chromatography coupled with Diode Array De-tector and Mass Spectrometry (HPLC-DAD-MS) to characterize bioactive compounds in olive leaf extracts. The analysis revealed a diverse metabolic profile, predominantly composed of tyrosol, flavonoids, and hydroxycinnamic acid. The antioxidant activity of the extracts demonstrated their efficacy, with variations observed between neutral and acidic pH conditions. Encapsulation was explored as a preservation method, successfully maintaining the integrity of phenolic compounds in both liquid and powdered forms. All four extracts have an undeniable antimicrobial effect. Moreover, the antibacterial activity tested on E. coli ATCC 25922 and S. aureus ATCC 25923 strains significantly improved post-encapsulation, particularly for the acidic pH extract. The findings suggest that encapsulation can potentially conserve and/or enhance the antimicrobial activity of olive leaf extract, paving the way for developing functional products with improved shelf life and nutritional properties. Further investigations are recommended to elucidate underlying mecha-nisms and optimize encapsulation processes to maximize the benefits of olive leaf extract in di-verse applications.
Improving the Decision-Making for Sustainable Demolition Waste Management by Combining a BIM-Based Life Cycle Sustainability Assessment Framework and Hybrid MCDA Approach
Authors: Han Dongchen , Rajabifard Abbas
Published: August 2024

Increasing efforts have been devoted to promoting sustainable demolition waste management (DWM) from a life cycle-thinking perspective. To this end, facilitating sustainability-oriented de-cision-making for DWM planning requires a sustainability assessment framework for assessing multifaceted criteria. This study develops a BIM-based DWM sustainability assessment ap-proach to facilitate the life cycle assessment (LCA) and decision-making by coupling the enriched IFC model with hybrid Multi-Criteria Decision-Aiding (MCDA) methods using Dynamo visual scripting. To streamline the data-intensive LCA process, this study enriched the BIM properties and accommodated them into the LCA data template to enhance data interoperability, thus achieving seamless data transfer. Moreover, hybrid MCDA methods are integrated into the deci-sion-making workflow for DWM scenario ranking. A pilot study is employed to verify the ap-plicability of the decision-aiding framework. The results unveil that the sustainability score ascended with the recycling rate. The optimal DWM alternative with the highest recycling rate yields the highest sustainability score at 91.63. Conversely, a DWM alternative reflecting the ‘status quo’ in China’s recycling industry has the lowest score at 8.37, significantly lower than the baseline scenario with a 50% recycling rate. It is worth noting that the ‘growth curve’ of the sustainability score continuously flattens as the target recycling rate escalates. The increment in recycling rate from the “Australian standard” scenario to the optimal scenario is 18.4%, while the sustainability score merely increases by 2.3%, signal-ling that the former scenario arrived at an optimum point for maximising the cost-efficiency of DWM under the predefined framework and contexts.
Impacts of Spatiotemporal and COVID-19 Factors on Bike-Share Ride Duration in Detroit
Authors: Zahertar Anahita , Lavrenz Steven
Published: August 2024

[3:46 PM] Anahita Zahertar
This research explores the factors influencing bikeshare usage durations in the Detroit Metropolitan Area over two years, focusing on spatial, temporal, and COVID-19-related variables. Using a fully parametric hazard-based duration model with random parameters, we address data heterogeneity and uncover how different conditions affect bikeshare trips. Our findings reveal that a) intense environmental factors such as high traffic stress, poor weather, and high COVID-19 risk levels are associated with shorter trip durations b) in contrast, supportive initiatives like memberships, an affordable $5 Access Pass, a free one-month pass during the pandemic, and the introduction of new stations have been more likely to encourage longer rides c) furthermore, the study examines how variables like gym closures due to the pandemic, evening hours, and the addition of new stations, which were set as random variables in our model, exhibit both positive and negative relationships with ride durations. A key finding is the 20-minute mark in ride durations, which helps understand user behaviors and trip purposes. This insight aids urban planning by suggesting strategic bike station placements to enhance bikeshare system efficiency and meet diverse community needs. This study not only deepens our understanding of urban mobility dynamics but also underscores the effectiveness of adaptive strategies in promoting sustainable urban transportation.
Edge Integration of Artificial Intelligence into Wireless Smart Sensor Platforms for Railroad Bridge Impact Detection
Authors: Lawal Omobolaji , V.Shajihan Shaik Althaf , Mechitov Kirill , Spencer Jr. Billie F.
Published: August 2024

Of the 100,000 railroad bridges in the United States, 50% are over 100 years old. Many of these bridges do not meet the minimum vertical clearance standards, making them susceptible to impacts from over-height vehicles. Impacts can cause structural damage and unwanted disruption to railroad bridge services; rapid notification of the railroad authorities is crucial to ensure that the bridges are safe for continued use and to affect timely repairs. Therefore, researchers have developed approaches to identify these impacts to railroad bridges. Some recent approaches use machine learning to more effectively identify impacts from the sensor data. Typically, the collected sensor data is transmitted to a central location for processing. However, the challenge with this centralized approach is that the transfer of data to a central location can take considerable time, which is undesirable for time-sensitive events like impact detection that require rapid assessment and response to potential damage. To address the challenges posed by the centralized approach, this study develops a framework for edge implementation of machine learning predictions on wireless smart sensors. Wireless sensors are used because of their ease of installation and lower costs compared to their wired counterparts. The framework is implemented on the Xnode wireless smart sensor platform, thus bringing artificial intelligence models directly to the sensor nodes and eliminating the need to transfer data to a central location for processing. This framework is demonstrated using data obtained from events on a railroad bridge near Chicago; results illustrate the efficacy of the proposed edge computing framework for such time-sensitive structural health monitoring applications.
The Potential Use of Arsenic Trioxide in the Treatment of Systemic Lupus Erythematosus
Authors: Mok Tsz Ching , Mok Chi Chiu
Published: August 2024

Arsenic trioxide (ATO) is now part of the standard regimen for the treatment of newly diagnosed and relapsed acute promyelocytic leukaemia. The availability of an oral form of ATO has greatly reduced the incidence of cardiotoxicity as compared to intravenous administration. Increasing evidence suggests that ATO has anti-inflammatory properties that may be useful for the treatment of autoimmune diseases. These include the modulation of Treg cell activation, Th1/Th2 and Th17/Treg balance, depletion of activated T cells and plasmacytoid dendritic cells, and influence of B cell differentiation, leading to reduced autoantibody and cytokine production. ATO has also been shown to induce apoptosis of activated fibroblast-like synoviocytes through generation of reactive oxygen species and alter the gut microbiota in collagen-induced arthritis. Despite the emergence of newer treatment modalities, the treatment of systemic lupus erythematosus (SLE), especially refractory manifestations, remains a challenge, owing to the paucity of effective biological and targeted therapies that are devoid of adverse effects. Oral ATO is an attractive option for the treatment of SLE because of the lower cost of production, convenience of administration and reduced cardiotoxicity. This article summarizes the anti-inflammatory mechanisms of ATO and its potential application in the treatment of SLE.
Evaluating Burn Severity and Post-Fire Woody Vegetation Regrowth in the Kalahari Using UAV Imagery and Random Forest Algorithms
Authors: Gillespie Madeleine , Okin Gregory S. , Meyer Thoralf , Ochoa Francisco
Published: August 2024

Accurate fire severity mapping is essential for understanding the impacts of wildfires on vegetation dynamics in arid savannas. The frequent wildfires in these biomes often cause topkill, where vegetation experiences above-ground combustion, but the below-ground root structures survive, allowing for subsequent regrowth post-burn. Investigating post-fire regrowth is crucial for maintaining ecological balance, elucidating fire regimes, and enhancing the knowledge base of land managers regarding vegetation response. This study examined the relationship between bush fire severity and post-burn coppicing/regeneration events of woody vegetation in the Kalahari Desert of Botswana. Utilizing UAV-derived RGB imagery combined with a Random Forest (RF) classification algorithm, we aimed to enhance the precision of burn severity mapping at a fine spatial resolution. Our research focused on a 1 km2 plot within the Modisa Wildlife Reserve, extensively burnt by the Kgalagadi Transfrontier Fire of 2021. The UAV imagery, captured at various intervals post-burn, provided detailed orthomosaics and canopy height models, facilitating precise land cover classification and burn severity assessment. The RF model achieved an overall accuracy of 79.5% and effectively identified key burn severity indicators, including green vegetation, charred grass, and ash deposits. Our analysis revealed a >50% probability of woody vegetation regrowth in high severity burn areas six months post-burn, highlighting the resilience of these ecosystems. This study demonstrates the efficacy of low-cost UAV photogrammetry for fine scale burn severity assessment and provides valuable insights into post-fire vegetation recovery, thereby aiding land management and conservation efforts in savannas.
Altered Expression of C4BPA and CXCL1 Genes in the Endometrium of Patients with Recurrent Implantation Failure after In Vitro Fertilization and Thin Endometrium
Authors: Kurmanova Gaukhar , Ashirbekov Yeldar , Kurmanova Almagul , Mamedaliyeva Nagima , Moshkalova Gaukhar , Anartayeva Gaini , Salimbayeva Damilya , Tulesheva Aidana
Published: August 2024

Nowadays recurrent implantation failure (RIF) after invitro fertilization is common problem that reproductive specialists usually faced. The phenomenon of thin endometrium in RIF patients has yet not completely understood and properly treated. This study aimed to reveal significantly dysregulated selected genes expression between RIF patients with thin endometrium and fertile women. Endometrial samples were collected in the implantation window days (LH+7 – LH+10) of the natural menstrual cycle from RIF patients (n=20) and fertile women (n=14). Ten genes were chosen as target genes regarding their possible relations with the implantation process. Endometrial gene expression levels showed differences in RIF samples compared to fertile samples. The significant downregulation was observed for CXCL1 (p=0.005) and C4BPA (p=0.03) genes. There was no statistically significant difference between the RIF groups and the fertile group in the expression of 8 genes: CXCL8, HPRT1, MMP10, INFG, VEGFB, HAND2, IL15 and TNC (p>0.05). The use of a combination of two markers (C4BPA + CXCL1) allows for good discrimination of RIF patients from fertile women (AUC 0.806).
Efficient Bio-Based Insulation Panels Produced from Eucalyptus Bark Waste
Authors: Fuentealba Cecilia , Segovia César , Pradena-Miquel Mauricio , César Andrés Gabriel
Published: August 2024

Traditional thermal insulation panels consume large amounts of energy during production and emits pollutants into the environment. To mitigate this impact, the development of bio-based materials is an attractive alternative. In this context, the characteristics of the Eucalyptus fiber bark (EGFB) make it a candidate for insulation applications. However, more knowledge about the manufacturing process and in-service performance is needed. The present study characterized the properties that determinate the in-service behaviour of the EGFB insulation panel. The assessment involved two different manufacturing process. The results indicated that the hot plates and the saturated steam injection manufacturing system can produce panels with similar theoretical and bulk density. The thermal conductivity fluctuated between 0.064 and 0.077 W/m.K, which indicated good insulation. Furthermore, the values obtained for thermal diffusivity and water vapor transmission properties are comparable with other commercially available panels. To guarantee a good in-service performance, the panels need to be treated with flame retardant and antifungal additive. The good performance of the panel is relevant because bio-based Eucalyptus bark panels generate less CO2 eq and require less energy consumption compared to traditional alternatives, contributing to the sustainability of the forestry and the construction industry.
Growth, Photosynthesis and Yield Responses of Common Wheat to Foliar Application of Methylobacterium symbioticum under Decreasing Chemical Nitrogen Fertilization
Authors: Valente Francesco , Panozzo Anna , Bozzolin Francesco , Barion Giuseppe , Bolla Pranay Kumar , Bertin Vittorio , Potestio Silvia , Visioli Giovanna , Wang Yu , Vamerali Teofilo
Published: August 2024

Current agriculture intensifies crop cultivation to meet food demand, leading to unsustainable use of chemical fertilizers. This study investigates a few physiological and agronomic responses of common wheat following the inoculation with plant growth-promoting bacteria to reduce nitrogen inputs. A field trial was conducted in 2022-23, in Legnago (Verona, Italy) on Triticum aestivum var. LG-Auriga comparing full (180 kg ha-1) and reduced (130 kg ha-1) N doses, both with and without foliar application at end tillering of the N-fixing bacterium Methylobacterium symbioticum. Biofertilization did not improve shoot growth, while it seldom increased root length density in the arable layer. It delayed leaf senescence, prolonged photosynthetic activity, amplified stomatal conductance and PSII efficiency under reduced N dose. Appreciable ACC-deaminase activity of such bacterium disclosed augmented nitrogen retrieval and reduced ethylene production, explaining ameliorated stay-green. Yield and testing weight were unaffected by biofertilization, while both glutenin-to-gliadin and HMW-to-LMW ratios increased together with dough tenacity. It is concluded that Methylobacterium symbioticum can amplify nitrogen metabolism at reduced nitrogen dose, offering a viable approach to reduce chemical fertilization under suboptimal growing conditions for achieving a more sustainable agriculture. Further research over multiple growing seasons and soil types is necessary to corroborate these preliminary observations.
Balancing Nets and Lives: A Socio-Ecological Analysis of Sustainable Fisheries in the Gulf of Mannar
Authors: Saha Deepanjana , Suresh Devarajulu Kumar , Krishnan Pandian , Mukherjee Rajdeep
Published: August 2024

The Gulf of Mannar, a UNESCO World Biosphere Reserve, faces severe overfishing and habitat degradation threats. In this study, we investigate the pivotal role of ecosystem services in sustaining local livelihoods and overall well-being. By conducting a comprehensive survey of 480 respondents across two districts, we gathered extensive data on demographics, livelihoods, fishing practices, reliance on ecosystem services, and community management participation. The analysis reveals a critical dependence on the Gulf's resources (income, food security, traditions) with gender disparities (men fish, women in pre/post-harvest), but fishing is only allowed in the 10km buffer zone (not the core zone). The findings emphasize the promise of community-based strategies, such as Marine Protected Areas and reviving co-management committees, for achieving sustainable fisheries management. However, we also identify gaps, including the need for more nuanced well-being indicators and improved models for community management participation. To address these challenges, we advocate for sustainable fishing practices, tackling social inequities, especially gender disparities in resource access and decision-making, and investing in healthcare, education, and social safety nets for fishing communities. Promoting alternative livelihoods can alleviate pressure on fish stocks, and empowering local communities through capacity building and community-based management initiatives is crucial for ensuring the long-term sustainability of both the Gulf of Mannar ecosystem and the well-being of its dependent communities. This multifaceted approach holds significant promise for balancing ecological health with human prosperity.
Healthcare Resilience in Saudi Arabia: The Interplay of Occupational Safety, Staff Engagement, and Resilience
Authors: Qassim Amal Abdulmajeed , Abedelrahim Selma Sidahmed
Published: August 2024

This research investigates the relationships between occupational health and safety (OHS), staff resilience (SR), staff engagement (SE), and organizational resilience (HOR) within Saudi Arabian hospitals. Employing a quantitative, cross-sectional design, data were collected from 127 administrative staff members working in both public and private hospitals in Saudi Arabia. Using SmartPLS to test the hypothesized relationships and mediation effects, the findings reveal that OHS significantly impacts both SR and SE, and SR significantly influences HOR. Additionally, SE significantly affects HOR. The study also confirms a partial mediation effect of SE and SR in the relationship between OHS and HOR. The model demonstrates substantial explanatory power for HOR, SE, and SR. These results underscore the critical role of OHS in fostering a resilient healthcare environment by enhancing staff engagement and resilience. The study’s implications highlight the importance of targeted interventions to improve OHS practices, promoting overall hospital resilience in alignment with Saudi Arabia’s Vision 2030.
Prediction of Dielectric Constant in Series of Polymers by Quantitative Structure-Property Relationship (QSPR)
Authors: Ascencio Medina Estefania , He Shan , Daghighi Amirreza , Iduoku Kweeni , Casanola-Martin Gerardo M. , Arrasate Sonia , Gonzalez-Diaz Humerto , Rasulev Bakhtiyor
Published: August 2024

The dielectric constant (ε) reflects the ability of a material to align and orient electrical dipoles within its structure in response to an externally applied electric field; the greater the polarizability of molecules, the greater the value of dielectric constant. In this study a data set of 86 polymers was investigated to develop a structure-property quantitative relations (QSPR) model to predict the dielectric constant in polymers. An initial set of 1273 descriptors was used to select a best set of descriptors and to construct two machine learning models with Gradient Boosting Regressor (GB_A and GB_B). The best performing model (GB_A) with 8 descriptors, exhibited a performance of (R2train) = 0.938 and (R2test) = 0.802. The models were internally validated by 5 folds cross-validation, demonstrating robustness. Additionally, using the Accumulative Local Effect (ALE) technique, we analyzed the relationship between the 8 descriptors involved and the impact of these descriptors to dielectric constant of polymers.
Intercellular Adhesion Molecule 1 (ICAM-1): An Inflammatory Regulator with Potential Implications in Ferroptosis and Parkinson’s Disease
Authors: Miller Matthew R , Landis Harold E , Miller Robert E , Tizabi Yousef
Published: August 2024

Intercellular adhesion molecule 1 (ICAM-1/CD54), a transmembrane glycoprotein, has been considered as one of the most important adhesion molecules during leukocyte recruitment. It is encoded by the ICAM1 gene and plays a central role in inflammation. It’s crucial role in many inflammatory diseases such as ulcerative colitis and rheumatoid arthritis are well established. Given that neuroinflammation, underscored by microglial activation, is a key element in neurodegenerative diseases such as Parkinson’s disease (PD), we investigated whether ICAM-1 has a role in this progressive neurological condition and if so, elucidate the underpinning mechanisms. Specifically, we were interested in potential interaction between ICAM-1, glial cells and ferroptosis, an iron-dependent form of cell death that has recently been implicated in PD. We conclude that there exist direct and indirect (via glial cells and T cells) influences of ICAM-1 on ferroptosis and that further elucidation of these interactions can suggest novel intervention for this devastating disease.
Biomass Utilization for Energy Generation in Post-Disaster Scenarios: The Case of Puerto Rico
Authors: Abniel Machín
Published: August 2024

Puerto Rico's geographic and climatic conditions render it highly susceptible to natural disasters, particularly hurricanes. The devastation caused by Hurricane Maria in 2017 highlighted the fragility of the island's centralized energy infrastructure, which led to prolonged power outages and severe disruptions in essential services. This review explores the potential of biomass energy to enhance resilience in post-disaster scenarios, focusing on Puerto Rico as a case study. Biomass energy, derived from organic materials like agricultural residues, woody biomass, and municipal solid waste, offers a renewable and locally sourced power solution that can be rapidly deployed. Key biomass conversion technologies, including direct combustion, gasification, anaerobic digestion, and pyrolysis, are examined for their applicability and benefits in emergency energy provision. The implementation of biomass-powered microgrids in Puerto Rico, such as those by Casa Pueblo and Arensis, demonstrates the feasibility and effectiveness of decentralized energy systems in disaster recovery. These microgrids provide reliable power to critical infrastructure, reduce dependence on fossil fuels, and support waste management efforts. The review also discusses ongoing research and development in advanced biomass technologies, such as second-generation biofuels, algae-based biomass, and biomass-to-hydrogen conversion, which can further enhance energy efficiency and sustainability. Additionally, the economic, environmental, and social impacts of biomass energy are evaluated, highlighting its role in job creation, waste reduction, emission control, and community resilience. Policy recommendations include streamlining permitting processes, enhancing financial incentives, developing feedstock supply chains, and incorporating biomass into disaster recovery plans. The findings suggest that integrating biomass energy into Puerto Rico’s energy strategy can significantly improve its capacity to respond to and recover from natural disasters, promoting long-term sustainability and resilience.
Optimizing Additive Manufacturing with Computer Vision to Enhance Material Efficiency and Structural Stability
Authors: Ali Musaddiq Al , Shimoda Masatoshi , Naguib Marc
Published: August 2024

This study presents a novel approach combining computer vision with topology optimization for additive manufacturing. Using specialized photogrammetry software, we capture high-resolution images of the design domain to create precise 3D models through detailed scanning. These models are converted into STL file format and remeshed using an adaptive algorithm within COMSOL 5.3 Multiphysics, managed by a custom MATLAB 2023. This integration allows optimal mesh resolution and accuracy in analyses. We applied this method to design a concrete pillar for 3D printing, aiming for a 75% volume reduction to enhance material efficiency and stability, crucial for extraterrestrial environments. The design, scanned with a 360-degree camera array, informed the MATLAB-based topology optimization process. Combining MATLAB’s optimization algorithms with COMSOL’s meshing and finite element solver solver, we explored material-efficient configurations. The results show significant volume reduction, particularly in the central design area, optimizing material use while maintaining structural stability. The optimization algorithm demonstrated rapid, stable convergence to near-optimal solutions within about 20 iterations, highlighting the method’s efficiency and robustness in complex design optimization.
Analysis of the Rolling Phenomenon of a Reduced-Diameter Wheel for Freight Wagons, as a Function of Operating Factors
Authors: Pellicer David S. , Larrodé Emilio
Published: August 2024

This paper shows the development of a numerical analysis model which enables the calculation of the life of a reduced-diameter wheel used for freight wagons as a function of its operating factors. Reduced-diameter wheels are being increasingly used for combined transport applications and they can be arranged in a wide range of bogies and operated very differently. Due to the uniqueness of this type of wheels, their life has hardly been analyzed so far. To properly construct the numerical analysis model, it has been necessary to study the rolling phenomenon in-depth, tackle the main problems arising in the vehicle – track interaction and set the relations amongst them. Once the rail-wheel interaction model was built, it was used to calculate the life of an ordinary-diameter wheel, a medium-diameter wheel and a reduced-diameter wheels under the same conditions and compare them. In this way, it is possible to know how long the life of a reduced-diameter wheel is compared to that of an ordinary-diameter one and also the evolution of the life depending on the diameter. The root causes responsible for this evolution can be explained thanks to the comprehension of the rolling phenomenon provided by the full analytical work.
Temperature Measurement during Cryogenic Cooling of a Metal Object under Static Conditions
Authors: Chodór Jarosław , Żurawski Łukasz
Published: August 2024

In machining, there is a constant effort to achieve the expected roughness of the machined surface while maintaining the life of the cutting tool during its operation. The methods used for extending machinability characteristics can be applied due to cooling and lubrication. One of the latest, but not new, targeted cooling techniques have become cryogenic treatment, which uses substances that exhibit extremely low-temperature values of about 123 K. This is a very environmentally friendly technique compared to the current standardized cooling and lubricating fluids. The main task of such cooling is to change the properties of the workpiece so that it exhibits the properties of a brittle material. Bringing the workpiece structure in this way can result in easier material separation through the chip. In the article, the obtained test results can approximate the behavior of various materials during cryogenic cooling.
HIV-Induced Modulation of TREM2 Expression Is Reversed by Cannabidiol: Implications for Age-Related Neuropathogenesis in People with HIV
Authors: Avalos Bryant , Kulbe Jacqueline R , Ford Mary , Laird Anna Elizabeth , Walter Kyle , Mante Michael , Florio Jazmin , Boustani Ali , Chaillon Antoine , Schlachetzki Johannes , Sundermann Erin , Volsky David , Rissman Robert A , Ellis Ronald , Letendre Scott , Iudicello Jennifer , Fields Jerel Adam
Published: August 2024

(1) Background: Triggering receptor expressed on myeloid cells 2 (TREM2) is involved in neu-roinflammation and HIV-associated neurocognitive impairment (NCI). People with HIV (PWH) using cannabis exhibit lower inflammation and neurological disorders. We hypothesized TREM2 dysfunction mediates HIV neuropathogenesis and can be reversed by cannabinoids. (2) Methods: EcoHIV-infected wildtype (WT) and TREM2R47H mutant mice were used to study HIV's impact on TREM2 and behavior. TREM2 and related gene expressions were examined in mono-cyte-derived macrophages (MDMs) from PWH (n=42) and people without HIV (PWoH; n=19) with varying cannabis use via RNA sequencing and qPCR. Differences in membrane-bound and soluble TREM2 (sTREM2) were evaluated using immunocytochemistry (ICC) and ELISA. (3) Results: EcoHIV increased immature and C-terminal fragment forms of TREM2 in WT mice but not in TREM2R47H mice, with increased IBA1 protein in TREM2R47H hippocampi, correlating with worse memory test performance. TREM2 mRNA levels increased with age in PWoH but not PWH. Cannabidiol (CBD) treatment increased TREM2 mRNA alone and with IL1β. RNA-seq showed upregulation of TREM2-related transcripts in cannabis-using PWH compared to naïve controls. IL1β increased sTREM2 and reduced membrane-bound TREM2, effects partially re-versed by CBD. (4) Conclusions: These findings suggest HIV affects TREM2 expression modu-lated by cannabis and CBD, offering insights for therapeutic strategies.
Rugby Union Match Injury Surveillance in Portuguese Top-Tier Competition
Authors: Lopes Nuno Pinto de Sousa , Cruz-Ferreira António Miguel , Torres Lima Diana Freitas , Silva Marta Amaral , Santiago Luiz Miguel
Published: August 2024

Objective: To report time-loss match injuries in Portugal’s “Divisão de Honra” (Portuguese First Tier) 2022/23 season focusing on injury incidence, injury burden, anatomical region and type of injury. Methods: A cohort prospective observational study was conducted. Data was collected through an online form sent for every team medical department categorizing player position, injury type, location and severity. Injury incidence and burden were calculated per 1000-player-match-hours. Results: The overall injury incidence was 54.4 injuries per 1000 player-match-hours (CI95% 30.3-96.2). Forwards had a higher incidence comparing to backs. Lower limbs were the most affected location (52% of the injuries). Sprain/ligaments injuries were the most common type of injury followed by muscle injuries. Discussion: The injury incidence was higher than what is reported in amateur competitions and lower than professional ones. Injury severity was similar to other studies. Our study suggests a lower injury burden compared to other semi-professional and elite leagues. Further research with broader participation and training injury data is needed.
A Holistic Approach Tackling E-waste Management Using Ontology
Authors: Tarek Ahmed , Laviano Francesco , Fino Debora , Rubertelli Francesca , Toscano Claudio
Published: August 2024

Electronic waste generation has been following a continuously rising trend. With electronics containing a myriad of materials some of which are hazardous, toxic, extremely rare or precious combined with more stringent legislative laws which encourage the reuse and optimised recycling of the materials included in e-waste, the need for a holistic approach is inevitable. Such an approach should not only identify the materials found in the various types of e-waste and their respective quantities but also needs to highlight the possible handling techniques and their respective impacts and associated hazards whether to the environment or human health. Performing such a task manually would be exasperating and costly while requiring extensive resources which might not be met with a justifiable economic gain; thus, the use of the advancement in computational sustainability to draw a complete picture and aid in an informed decision-making process is crucial. The e-waste ontology developed in this paper is one way of addressing the problem since it covers the treatment domain, the hazard and the materials contained within the different types of e-waste. The ontology developed can be used directly from the protégé software or by embedding it into a developed Decision Support System.
Switching from Cigarettes to Heated Tobacco Products in Japan – Potential Impact on Health Outcomes and Associated Health Care Costs
Authors: Mahlich Joerg , Kamae Isao
Published: August 2024

Background: Health expenditure in Japan is rising due to an ageing society while simultaneously pressure is mounting to increase spending in other areas such as defense, all in the context of a stagnating economy. Easing pressures on the health care sector through smoking-related cost reductions could thus be a cornerstone to mitigate the looming fiscal threat. Public health policy has encouraged cessation, but this approach has seen limited success. Focusing on cessation alone therefore may not be a sustainable policy strategy and other, new solutions need to be found to reduce smoking-related costs.
Methods: Using a status-quo simulation based on hospital resources data derived from the Japanese Ministry of Health, Labour and Welfare, we examine the impact of heated tobacco products (HTPs) on the prevalence of four smoking attributable diseases (chronic obstructive pulmonary disease (COPD), ischemic heart disease (IHD), stroke and lung cancer) and related direct health care costs. Base case scenario assumes a switching rate from combustible smokers to HTPs of 50%. A risk reduction rate of 70% was applied. A sensitivity analysis was performed to determine the impact of parameter changes on output.
Results: Our results indicate that 50% of smokers switching to use HTPs instead of combustible tobacco products could reduce the number of patients of the four smoking attributable diseases considered by 12 million cases equivalent to 454 billion JPY in savings. Prefectures located in the north and south of Japan would benefit most.
Conclusion: Considering the heterogeneous prevalence rates across population groups and prefectures, a one-size-fits-all, centralized approach to tobacco control is not effective. Health authorities should strategically use multiple interventions to address smoking related health risks and costs. Switching to HTPs should be encouraged in parallel to smoking cessation, and educational efforts should aim to increase the awareness on health risks, especially among younger people.