bluuebunny/crossref_metadata_2025_split huggingface dataset:
Monitoring of spatio-temporal glaciers dynamics in Bhagirathi Basin, Gharhwal Himalayas using remote sensing data
Authors: Sandhu Har Amrit Singh , Gusain Hemendra Singh , Arora Manoj , Cherubini Claudia , Singh Dhiraj Kumar , Tripathi Neeraj 
Published: May 2024

AbstractGlacier retreat represents a highly sensitive indicator of climate change and global warming. Therefore, timely mapping and monitoring of glacier dynamics is strategic for water budget forecasting and sustainable management of water resources. In this study, Landsat satellite images of 2000 and 2015 have been used to estimate area extent variations in 29 glaciers of the Bhagirathi basin, Garhwali Himalayas. ASTER DEM has been used for extraction of glacier terrain features, such as elevation, slope, area, etc. It is observed from the analysis that Bhagirathi sub-basin has a maximum glaciated area of ~ 35% and Pilang has the least with ~ 3.2%, whereas Kaldi sub-basin has no glacier. In this region, out of 29 glaciers, 25 glaciers have shown retreat, while only 4 glaciers have shown advancement resulting in a total glacier area loss of ~ 0.5%, while the retreat rate varies from ~ 0.06 m/yr to ~ 19.4 m/yr. Dokarni glacier has maximum retreat rate (~ 19.4 m/yr), whereas Dehigad has maximum advancing rate (~ 10.1 m/yr). Glaciers retreat and advance have also been analyzed based on terrain parameters and observed that northern and southern orientations have shown retreat, whereas the area change is highly correlated with glacier length. The study covers more than 65% of the total glaciated area and based on the existing literature represents one of the most exhaustive studies to cover the highest number of glaciers in all sub-basins of the Bhagirathi basin.
An alternative method for predicting internal friction angle of rock materials
Authors: Karakul Hasan , Ulusay Reşat 
Published: May 2024

AbstractThe shear strength properties of rock materials, cohesion and internal friction angle, are determined by carrying out tri-axial strength test on cylindrical core specimens in laboratory. But determination of these parameters by triaxial tests in accordance with standards and suggested methods, particularly for weak, fractured and weathered rocks is exteremely difficult and/or impossible due to difficulties related to preparation of test specimens suitable for this test. In addition, the tri-axial test requires high cost equipment and too much time for sample preparation and testing. In such cases, there is a need to precisely estimate the friction angle and estimation of rock shear strength properties using some indirect methods, as they are economical and easy to carry out. In this study, the traditional method, which is recommended to be used for the prediction of internal friction angle (ϕ) when triaxial test data is not available, was briefly assessed with its some limitations and an alternative method using theoretical tensile strength and uniaxial compressive strength to predict ϕ was proposed. Then the prediction performances of traditional and proposed methods were compared using a very large data set collected from published literature. The statistical reliability of the derived equations was assessed using F- and t-tests and according to the test results the prediction equations were found to be statistically reliable. The results indicated that the method proposed in this study using the theoretical tensile strength yields best predictions of ϕ when compared to those estimated from the traditional methods based on direct and Brazilian tensile strength values.
Teachers’ Beliefs and Practices to Support Emergent Literacy Development in Preschool Education: The Moderating Role of Continuous Training
Authors: Cadime Irene , Alves Diana , Mendes Sofia , Pinto Patrícia , Cruz Joana 
Published: May 2024

AbstractThe main goal of this study was to explore the relationship between emergent literacy beliefs and practices among Portuguese preschool teachers and to investigate the moderating role of experience and training (initial and continuous). The participants were 266 preschool teachers working in Portugal. The results indicate higher levels of holistic beliefs than technicist beliefs regarding emergent literacy. Practices aimed at promoting oral language and phonological awareness were reported as the most frequently used practices in the classroom. Teachers who had continuous training in emergent literacy had more holistic beliefs and performed more practices to promote children’s phonological awareness and knowledge of the relationship between oral and written language. Continuous training was also a significant moderator of the relationship between emergent literacy beliefs and practices. These findings highlight the importance of continuous training in fostering the use of quality research-based practices in the classroom.
Sand screen selection by sand retention test: a review of factors affecting sand control design
Authors: Khan Javed Akbar , Zainal Aimi Zahraa , Idris Khairul Nizam , Herman Angga Pratama , Cai Baoping , Maoinser Mohd Azuwan 
Published: May 2024

AbstractThe installation of sand screens in open-hole completions in the wellbore is crucial for managing sand production. The main reason for using standalone screens in open-hole completions is their relatively reduced operational complexity compared to other sand control technologies. However, directly applying the screen to the bottom of the hole can lead to an incorrect screen type selection, resulting in an unreliable sand control method. To address this issue, a sand retention test is conducted to evaluate the performance of a standalone screen before field installation. Nevertheless, current sand retention test setups encounter several challenges. These include difficulties in identifying minimum retention requirements, interpreting results in the context of field conditions, and replicating field-specific parameters. The existing sand retention test introduces uncertainties, such as inaccurately replicating field requirements, inconsistent selection of wetting fluids, flow rates, and channel formation, leading to variations in the choice of the optimal screen using this test. In response to these challenges, this study aims to review the sand retention test and propose an improved sand retention method to overcome these problems. The focus of this article is to provide an in-depth analysis of previous sand retention test setups, their contributions to characterizing sand screens, and the parameters utilized in determining test outcomes. Additionally, this review outlines a procedure to investigate the impact of different particle sizes on screen erosion. Key findings emphasize the importance of using high-quality materials, proper screen design to resist damage and erosion, achieving acceptable natural packing behind the screen, and considering factors such as geology, wellbore conditions, and installation techniques. The analysis reveals that a high quantity of finer and poorly sorted sand increases sand production. The study recommends performing a sand pack test closer to reservoir conditions for better evaluation. Premium sand screens demonstrate the highest retention capacity, followed by metal mesh and wire-wrapped screens. Additionally, geotextiles show potential for enhancing sand retention, and screen design affects erosion resistance and service life.
Case report. Emfysemateuze cystitis
Authors: Tijhof Esther H. , van der Fels Christa A. M. 
Published: May 2024

SamenvattingEmfysemateuze cystitis is een zeldzame aandoening van de blaas, met een relatief hoog mortaliteitspercentage. Er is geen richtlijn beschikbaar en er zijn weinig onderzoeken beschreven. Een 85-jarige patiënt wordt met deze aandoening gediagnosticeerd. Een adequate aanpak resulteert in een succesvolle behandeling.
Experimental Investigation and Classification of Wastewater Treatment Sludge as Pozzolan for Cement
Authors: Ekolu S. O. , Mudzanani P. , Mofokeng M. T. M. , Maiyana M. C. , Naghizadeh A. 
Published: May 2024

AbstractThis paper presents an investigation conducted to evaluate wastewater treatment sludge for potential use as a cement extender or pozzolan. Two varieties comprising the digested wastewater sludge (DWWS) and activated wastewater sludge (AWWS) materials, were finely ground then calcined at 750 °C for 30 min. Subsequently, the calcined sludge waste materials were blended with ordinary Portland cement CEM I 52.5 N at 0, 10, 20, 30% DWWS or AWWS, and used to prepare mortar mixtures at proportions of 1:3:0.61 cement to sand to water. Various tests were conducted including workability, compressive strength, pozzolanic activity with lime, drying shrinkage and alkali-silica reaction. It was found that both varieties of the sludge waste materials, once blended with CEM I at 20% DWWS or 20% AWWS, satisfied the ASTM C618 criteria for Class C pozzolan, and may be classified as CEM II /A-P 32.5 N,R cement type of EN 197-1/SANS 50197-1. The overall performance of DWWS was relatively better than that of AWWS.
Advancements in the application of metal oxide nanocatalysts for sustainable biodiesel production
Authors: Awogbemi Omojola , Ojo Ayotunde Adigun , Adeleye Samson Adedayo 
Published: May 2024

AbstractThe growing population and the unpalatable ecological impact of exploration and utilization of fossil-based fuels have resulted in increased demand for biofuel as an alternative fuel for engines and power generation. The global demand for biodiesel, a prominent member of the biofuels family, has continued to increase over the past decades with researchers devising various means to intensify cost-effective production. The use of metal oxide nanocatalysts is one of the feasible strategies to meet the increased demand for quality biodiesel. This study reviews the recent advances in the deployment of commonly used metal oxide nanoparticles such as MgO, CaO, TiO2, ZnO, and ZrO2 to accelerate sustainable biodiesel production. Converting conventional metal oxide heterogeneous catalysts into nanoparticles enhances the surface configuration, chemical and thermal stability, porosity, and crystallinity of the nanocatalysts. The deployment of metal oxide nanocatalysts hasten the transesterification reaction, reduces reaction temperature and time, and enhances biodiesel yield. Biodiesel synthesized with the aid of metal oxide nanoparticles is of impeccable quality and meets international standards. Notwithstanding the few challenges, the application of metal oxide nanoparticles as heterogeneous catalysts engenders sustainable biodiesel production and contributes to energy security. More innovative and collaborative studies are needed to reduce the ethical, economic, infrastructural, and environmental consequences of the usage of nanomaterials for sustainable biodiesel production.
A Multiscale Method for Two-Component, Two-Phase Flow with a Neural Network Surrogate
Authors: Magiera Jim , Rohde Christian 
Published: May 2024

AbstractUnderstanding the dynamics of phase boundaries in fluids requires quantitative knowledge about the microscale processes at the interface. We consider the sharp-interface motion of the compressible two-component flow and propose a heterogeneous multiscale method (HMM) to describe the flow fields accurately. The multiscale approach combines a hyperbolic system of balance laws on the continuum scale with molecular-dynamics (MD) simulations on the microscale level. Notably, the multiscale approach is necessary to compute the interface dynamics because there is—at present—no closed continuum-scale model. The basic HMM relies on a moving-mesh finite-volume method and has been introduced recently for the compressible one-component flow with phase transitions by Magiera and Rohde in (J Comput Phys 469: 111551, 2022). To overcome the numerical complexity of the MD microscale model, a deep neural network is employed as an efficient surrogate model. The entire approach is finally applied to simulate droplet dynamics for argon-methane mixtures in several space dimensions. To our knowledge, such compressible two-phase dynamics accounting for microscale phase-change transfer rates have not yet been computed.
Application Study on the Reinforcement Learning Strategies in the Network Awareness Risk Perception and Prevention
Authors: Xie Junwei 
Published: May 2024

AbstractThe intricacy of wireless network ecosystems and Internet of Things (IoT) connected devices have increased rapidly as technology advances and cyber threats increase. The existing methods cannot make sequential decisions in complex network environments, particularly in scenarios with partial observability and non-stationarity. Network awareness monitors and comprehends the network's assets, vulnerabilities, and ongoing activities in real-time. Advanced analytics, machine learning algorithms, and artificial intelligence are used to improve risk perception by analyzing massive amounts of information, identifying trends, and anticipating future security breaches. Hence, this study suggests the Deep Reinforcement Learning-assisted Network Awareness Risk Perception and Prevention Model (DRL-NARPP) for detecting malicious activity in cybersecurity. The proposed system begins with the concept of network awareness, which uses DRL algorithms to constantly monitor and evaluate the condition of the network in terms of factors like asset configurations, traffic patterns, and vulnerabilities. DRL provides autonomous learning and adaptation to changing network settings, revealing the ever-changing nature of network awareness risks in real time. Incorporating DRL into risk perception increases the system's capacity to recognize advanced attack methods while simultaneously decreasing the number of false positives and enhancing the reliability of risk assessments. DRL algorithms drive dynamic and context-aware response mechanisms, making up the adaptive network prevention component of the development. Predicting new threats and proactively deploying preventive measures, such as changing firewall rules, isolating compromised devices, or dynamically reallocating resources to reduce developing risks, is made possible by the system's ability to learn from historical data and prevailing network activity. The suggested DRL-NARPP model increases the anomaly detection rate by 98.3%, the attack prediction accuracy rate by 97.4%, and the network risk assessment ratio by 96.4%, reducing the false positive ratio by 11.2% compared to other popular methodologies.
Predictive capability of rough set machine learning in tetracycline adsorption using biochar
Authors: Balasubramanian Paramasivan , Prabhakar Muhil Raj , Liu Chong , Zhang Pengyan , Li Fayong 
Published: May 2024

AbstractMachine learning algorithms investigate relationships in data to deliver useful outputs. However, past models required complete datasets as a prerequisite. In this study, rough set-based machine learning was applied using real-world incomplete datasets to generate a prediction model of biochar’s adsorption capacity based on key attributes. The predictive model consists of if–then rules classifying properties by fulfilling certain conditions. The rules generated from both complete and incomplete datasets exhibit high certainty and coverage, along with scientific coherence. Based on the complete dataset model, optimal pyrolysis conditions, biomass characteristics and adsorption conditions were identified to maximize tetracycline adsorption capacity (> 200 mg/g) by biochar. This study demonstrates the capabilities of rough set-based machine learning using incomplete practical real-world data without compromising key features. The approach can generate valid predictive models even with missing values in datasets. Overall, the preliminary results show promise for applying rough set machine learning to real-world, incomplete data for generating biomass and biochar predictive models. However, further refinement and testing are warranted before practical implementation.
A numerical study on effect of liquefaction on ring footings during 2001 Bhuj earthquake at Kutch (Gujarat), India
Authors: Amin Milind , Singh Manendra 
Published: May 2024

AbstractLiquefaction, the temporary loss of strength in saturated sand causing it to behave like a liquid, leads to devastating consequences, including the settling, tilting, or collapsing of structures built on loose, saturated soil. The 2001 Bhuj earthquake witnessed extensive liquefaction in regions such as the Great Rann of Kutch, Banni Plains, Kandla, and Gulf of Kutch, resulting in substantial damage to various infrastructures, including bridges, docks, buildings, embankments, and dams. This study employs a finite element approach to analyse the behaviour of shallow foundations on liquefying subsoil in Kutch during the 2001 earthquake. The investigation focuses on ring footings with inner radii of 0.25 m, 0.5 m, and 0.75 m, as well as an outer radius of 1 m, alongside a circular foundation with a 1 m radius. Notably, the ring footing with a radius ratio of 0.5 exhibits the least settlement under static loads, underscoring that liquefaction-induced settlement for ring footings is significantly less than that for circular footings.
The effects of dairy on the gut microbiome and symptoms in gastrointestinal disease cohorts: a systematic review
Authors: Ní Chonnacháin Clíona , Feeney Emma L. , Gollogly Clare , Shields Denis C. , Loscher Christine E. , Cotter Paul D. , Noronha Nessa , Stack Roisin , Doherty Glen A. , Gibney Eileen R. 
Published: May 2024

Abstract
Bovine dairy foods provide several essential nutrients. Fermented bovine dairy foods contain additional compounds, increasing their potential to benefit gastrointestinal health. This review explores the effects of dairy consumption on the gut microbiome and symptoms in gastrointestinal disease cohorts. Human subjects with common gastrointestinal diseases (functional gastrointestinal disorders and inflammatory bowel disease) or associated symptoms, and equivalent animal models were included. A systematic literature search was performed using PubMed, Embase and Web of Science. The search yielded 3014 studies in total, with 26 meeting inclusion criteria, including 15 human studies (1550 participants) and 11 animal studies (627 subjects). All test foods were fermented bovine dairy products, primarily fermented milk and yogurt. Six studies reported increases in gastrointestinal bacterial alpha diversity, with nine studies reporting increases in relative Lactobacillus and Bifidobacterium abundance. Six studies reported increases in beneficial short-chain fatty acids, while three reported decreases. Gastrointestinal symptoms, specifically gut comfort and defecation frequency, improved in 14 human studies. Five animal studies demonstrated reduced colonic damage and improved healing. This review shows fermented bovine dairy consumption may improve gut microbial characteristics and gastrointestinal symptoms in gastrointestinal disease cohorts. Further human intervention studies are needed, expanding test foods and capturing non-self-reported gastrointestinal measures.
Small micro- and nanoplastic test and reference materials for research: Current status and future needs
Authors: Sørensen Lisbet , Gerace Mathias Hanson , Booth Andy M. 
Published: May 2024

Abstract
Environmental plastic pollution comprises partially degraded particles representing a continuum of sizes, shapes, polymer types and chemical compositions. Owing to their potential for biological uptake, small microplastic particles (sMP; <100 μm) and nanoplastics (NPs) are considered to be a potential risk to organisms. Understanding how sMPs and NPs behave in the environment, and how environmental matrices affect their detection, is fundamental to quantifying exposures, assessing hazards and understanding these risks. For this purpose, high-quality, well-characterised and environmentally relevant test and reference materials are crucial. The current lack of environmentally relevant sMP and NP reference materials has resulted in many studies applying commercially available spherical, homogenous and monodisperse particles, typically produced for specific purposes and without environmental relevance. There is a need for sMP and NP test/reference materials for fate and effects assessments and analytical protocol validation that more accurately represent the sMP and NP present in the environment. To date, feasible methods for producing relevant sMP and NP test materials in sufficient quantities for environmental fate and effects studies remain lacking. The current review provides an overview and comparison of the available methods, highlighting those that show the most promise for producing environmentally relevant sMP and NP with further development and optimisation.
Socioeconomic gradient in functional difficulties by domain among youth: evidence from Egypt
Authors: Metwally Soha 
Published: May 2024

AbstractThis study aims to measure inequalities in the distribution of functional difficulties and their different domains among youth aged 15–29 years in Egypt, according to selected socioeconomic characteristics (e.g. wealth quantiles and education level of the head of the household). The data come from the nationally representative survey, ‘Household Observatory Survey’, with 10,405 persons aged 15–29 years representing the study sample population. The survey identifies individuals with disabilities using the Washington Group Short questions. Inequalities in disability distribution have been measured by the concentration index (CI). The results indicate that functional difficulties have been concentrated among the poorest youth and households headed by illiterate persons. Rural areas have the highest concentration of disabilities among youth, with the lowest wealth and the lowest educational level of the head of the household. The CI suggests the existence of socioeconomic inequalities in all functional difficulties except for seeing difficulties. Understanding which factors more substantially contribute to inequalities is critical for advancing policies devoted to enhancing the quality of life for individuals with disabilities.