bluuebunny/crossref_metadata_2025 huggingface dataset:
Simulation of Shale Gas Reservoir Production Considering the Effects of the Adsorbed Water Layer and Flow Differences
Authors: Yuan Hua , Liu Jianyi , Ding Qunchao , Jiang Lu , Liu Zhibin , He Wenting , Wen Yimin
Published: November 2024

Accurately describing the behavior of a gas-water two-phase flow in shale gas reservoirs is crucial for analyzing production dynamics in the field. Current research generally lacks consideration of the differences in physical properties and adsorption characteristics between the oleophilic organic matrix and the hydrophilic inorganic matrix. This study considers the organic matrix system as a single-phase gas flow, while the inorganic matrix and fracture systems involve a gas-water two-phase flow. Taking into account the impact of the adsorbed water layer on permeability at the surface of nanoscale pores in an inorganic matrix, the model comprehensively incorporates multiple mechanisms such as adsorption-desorption, the slippage effect, and Knudsen diffusion in the organic matrix and clay minerals. A multiscale gas-water two-phase comprehensive flow model for shale gas reservoirs has been established, and the results of the numerical model were validated against commercial software and actual field data. Simulation results over 1000 days indicate that early production from gas wells is primarily supplied by fractures, whereas free gas or desorbed gas from inorganic and organic matrices gradually contributes to the flow during the middle and later stages of production. As the Langmuir pressure and volume in the organic matrix and clay minerals increase, so does the corresponding gas production. The adsorbed water layer on the surface of inorganic nanopores reduces permeability, leading to a decrease in single-well cumulative gas production by 8.41%. The impact of the adsorbed water layer on gas production cannot be overlooked. The simulation method proposed in this study provides theoretical support for analyzing the gas-water two-phase flow behavior in shale gas reservoirs.
Enhancing Pereskia aculeata Mill. Cultivation with LED Technology: A Sustainable Approach
Authors: Silva Nayara Vieira , Lemes Ailton Cesar , Silva Fabiano Guimarães , Dário Bruno Matheus Mendes , Jesus Jenifer Ribeiro de , Sousa Tainara Leal de , Fernandes Sibele Santos , Egea Mariana Buranelo
Published: November 2024

Using light-emitting diode (LED) in plant production optimizes growth with higher energy efficiency, reduces carbon footprint and resource consumption, and promotes more sustainable agriculture. However, the plants’ growth characteristics and biochemical composition may vary depending on the light’s wavelength, spectrum, and intensity. Therefore, LEDs as a light source have become a promising choice for improving cultivation efficiency, as they can modulate the spectrum to meet the needs of plants. Pereskia aculeata is a plant species from the cactus family with high protein, vitamins, minerals, and fiber. The objective of this study was to evaluate the effect of LED lighting on the cultivation of P. aculeata and its influence on biometric color and physicochemical aspects. Two treatments were carried out without the addition of artificial light: one inside the greenhouse (C-ins) and the other outside the greenhouse (C-out), and four treatments with LEDs in different spectral bands: monochromatic red (600–700 nm) (Red), monochromatic blue (400–490 nm) (Blue), white (400–700 nm) (White), and blue–red (1:1) (Blue–Red). The biometric characteristics and the color of the leaves collected from the different treatments were evaluated. After this, the leaves were dried, ground, and evaluated. The physicochemical and thermal characteristics, bioactive compounds, and antioxidant activity of the leaves from each treatment were described. The biometric characteristics were intensified with red LED, and the color of the leaves tended toward green. The dried yield was around 50%, except for C-out treatment. Regarding nutritional characteristics, the highest protein (29.68 g/100 g), fiber (34.44 g/100 g), ash (20.28 g/100 g), and lipid (3.44 g/100 g) contents were obtained in the treatment with red light. The red treatment also intensified the content of chlorophyll a (28.27 µg/L) and total carotenoids (5.88 µg/g). The blue treatment intensified the concentration of minerals and provided greater thermal stability. Regarding bioactive properties, the cultivation of P. aculeata inside the greenhouse favored the concentration of phenolic compounds and a greater antioxidant capacity. Therefore, the quality of light for P. aculeata demonstrates that the length of red and blue light corroborates the development of the plant through the wavelength absorbed by the leaves, favoring its characteristics and planting in closed environments.
A State-of-the-Art Review of Fracture Toughness of Silicon Carbide: Implications for High-Precision Laser Dicing Techniques
Authors: Fan Zhiqiang , Zhang Jiaxin , Wang Zhuoqun , Shan Chong , Huang Chenguang , Wang Fusheng
Published: November 2024

Silicon carbide (SiC) stands out for its remarkable hardness, thermal stability, and chemical resistance, making it a critical material in advanced engineering applications, particularly in power electronics, aerospace, and semiconductor industries. However, its inherent brittleness and relatively low fracture toughness pose significant challenges during precision manufacturing processes, particularly during the laser stealth dicing—a pivotal process for wafer separation. This review provides a comprehensive analysis of the fracture toughness of SiC, exploring its dependence on microstructural factors, such as grain size, fracture mode (transgranular vs. intergranular), and toughening mechanisms, including the crack deflection and bridging. The effects of temperature and mechanical anisotropy on the fracture resistance of SiC are discussed. Particular attention is given to how SiC’s low fracture toughness and brittle nature affect the controlled crack propagation critical to the dicing process. The review synthesizes key experimental findings from various fracture-toughness measurement techniques, highlighting their relevance for optimizing the laser processing parameters. By linking the fracture mechanics of SiC to its performance in laser stealth dicing, this review provides critical guidance for enhancing the process, ensuring greater efficiency and reliability in SiC wafer separation for advanced technologies.
Circularity and Digitalisation in German Textile Manufacturing: Towards a Blueprint for Strategy Development and Implementation
Authors: Wiegand Tina , Wynn Martin
Published: November 2024

Textile and clothing (T&C) production and consumption have been steadily increasing for many years, accompanied by significant resource consumption, waste generation, and environmental impact. Germany holds a pivotal position in the industry, both within the EU and globally, as a leading producer, importer, and exporter of T&C. The circular economy (CE) concept has emerged as a promising solution to address the industry’s negative impacts by emphasising the reduction, reuse, and recycling of resources across the value chain. Digital technologies (DTs) are increasingly recognised as key enablers and facilitators of this transition, promoting both efficiency and circularity in manufacturing processes. However, the extent to which these are implemented in the German T&C industry remains largely underexplored. This study seeks to investigate the role of DTs in advancing CE practices within German T&C manufacturing. Employing process mapping and technology profiling, this research adopts an inductive, qualitative approach based on primary interview data to explore three key areas: (1) current CE practices, (2) the deployment of supportive DTs, and (3) the challenges in implementing the CE and DTs. The findings reveal that CE adoption is set to accelerate among T&C manufacturers, driven by regulatory compliance and market pressures, with DTs playing a critical role in enabling this transition. This study proposes a new operational framework designed to facilitate the shift towards a more circular textile sector, aligning with the ambitious goals of the European Union and broader environmental and societal objectives.
Innovative and Efficient Three-Dimensional Design Strategies for Optimizing the Industrial Production of Knitted Footwear
Authors: Hinojo Pérez Juan José , Valdés-Martínez Júlia , Juan-Fernandez Blanca , Calabuig-Barbero Eduardo , Gomez-Hernández José Francisco
Published: November 2024

Three-dimensional knitted uppers for footwear enhance ergonomic properties and fit compared to conventional flat panels. The knitting process for these elements represents a bottleneck in footwear production because flat-knitting machines must knit the uppers individually, which limits production capacity. This study explores ways to optimize knitting processes for 3D uppers. The focus is on reducing production time while maintaining product quality, ensuring a precise fit, and minimizing material waste. A series of experiments conducted on a base sneaker model implemented techniques to streamline knitting operations. These techniques were later adapted to other footwear types, including ankle boots, loafers, and sandals, to meet the unique requirements of each design. These optimizations include replacing traditional operations, such as overlocking or stitch decreases, with more efficient methods, such as open loops, as well as eliminating costly-to-manufacture elements. The results show significant reductions in production time while maintaining the fit and functional integrity of the uppers. These findings demonstrate both the technical feasibility and economic impact of these optimizations, offering valuable insights for the large-scale adoption of knitting technology in the footwear industry.
Forecasting CO2 Emissions in India: A Time Series Analysis Using ARIMA
Authors: M. Hrithik P. , Rehman Mohd Ziaur , Dar Amir Ahmad , Wangmo A. Tashi
Published: November 2024

This study evaluates the capability of the ARIMA (Auto Regressive Integrated Moving Average) to predict CO2 emissions in India using data from 1990 to 2023, addressing a critical need for accurate forecasting amid various economic and environmental uncertainties. It is observed that ARIMA yields high accuracy with respect to the prediction, and hence, it is reliable for environmental forecasting. These predictions give policymakers evidence-based information to aid in implementing sustainable climate policies within India. To ensure reliable predictions, the study methodology utilizes the Box–Jenkins approach, which encompasses model identification, estimation, and diagnostic checking. The initial step in the study is the Augmented Dickey–Fuller (ADF) test, which assesses data stationarity as a prerequisite for precise time series forecasting. Model selection is guided by the Akaike Information Criterion (AIC), which balances prediction accuracy with model complexity. The efficiency of the ARIMA model is assessed by comparing the actual observed values to the predicted CO2 emissions and the results demonstrate ARIMA’s effectiveness in forecasting India’s CO2 emissions, validated by statistical measures that confirm the model’s robustness. The value of the present study lies in its focused assessment of the relevance of the ARIMA model to the specific environmental and economic context of India, with actionable insight for policymakers. This study enhances prior research by incorporating a focused approach to data-driven policy formulation that increases climate resilience. The establishment of a reliable model for the forecasting of CO2 will aspire to support informed decision making in environmental policy and help India move forward toward sustainable climate goals. This study only serves to highlight the applicability of ARIMA in terms of environment-based forecasting and permits further emphasis on how much this method can be a useful data-based tool in climate planning.
From the Mouths of Babes: Lessons in Making a Joyful Noise unto the Lord
Authors: Wong Deborah Ann
Published: November 2024

How do infants praise the Lord? While we cannot say definitively how this is so, exploring this idea—particularly in the context of intergenerational worship and formation—offers rich theological insights. Scripture declares, “Out of the mouth of babes and nursing infants, you have perfected praise” (Matthew 21:16; Psalm 8:2, NKJV), suggesting that (1) infants indeed praise God, and (2) their praise is perfected by Him. Rather than dismissing this as purely metaphorical, this article draws on St. Augustine’s concept of the jubilus, a song with no intelligible words, to explore how infants’ babbling might be seen as a form of praise and worship, and what we might learn from it if it is thus seen. The article concludes by demonstrating how this reflection on infants’ praise might challenge us to reevaluate and enrich our approaches to Contemporary Praise & Worship and intergenerational formation.
Liberal Citizenship Through the Prism of Shia Jurisprudence: Embracing Fundamental over Partial Solutions
Authors: Fakhkhar Toosi Javad
Published: November 2024

This article explores the compatibility of liberal citizenship with Twelver Shia jurisprudence, a topic previously analyzed from the perspective of Sunni schools, most notably in the extensive research of Andrew F. March. This study confronts the challenges of reconciling liberal citizenship with Islamic jurisprudence, as highlighted in March’s work, through the lens of Shia legal thought. Rather than aiming to critique or review March’s research, this article considers his work solely as a representative example addressing the topic from the perspective of Sunni jurisprudence. This approach provides readers with a fundamental contrast, illuminating the unique insights that emerge from examining the subject within the framework of Shia jurisprudence. Unlike Sunni jurisprudence, which addresses these issues case-by-case by reviewing relevant Quranic and narrational sources, Twelver Shia jurisprudence offers a more foundational resolution. Owing to the belief in the occultation of the twelfth Imam and its implications for the implementation of Islamic law, Shia scholars have advanced theories such as the theory of obstruction (insidād) and the suspension of the social and political dimensions of Sharia. These theories effectively narrow the scope of Sharia, allowing for the acceptance of laws from non-Islamic states and circumventing potential conflicts with liberal citizenship in the absence of the twelfth Imam.
Performance of Different Macrophytes and Support Media in Constructed Wetlands for High Turbidity Reduction from Mine Spoil Rainwater
Authors: Gomes Paula Cristine Silva , Rochinha Isabela da Silva Pedro , Paiva Marllus Henrique Ribeiro de , Santiago Aníbal da Fonseca
Published: November 2024

Surface runoff in mining areas transports dissolved and suspended particles into water bodies, known as mine spoil rainwater, contributing to increases in turbidity. The aim of this study was to evaluate the effectiveness of horizontal flow wetlands, free water surface (FWS), and subsurface flow (HSSF) in reducing turbidity >1500 NTU from a synthetic mine spoil rainwater. Macrophytes, support media, hydraulic retention time (HRT), and hydraulic loading rate (HLR) were analyzed. The HSSF T. domingensis in gravel #1 achieved a 99% reduction for 4-day HRT, with residual turbidity of 7 ± 3 NTU for 27.43 L m−2 d−1 HLR. The FWS P. stratiotes achieved a 99% reduction for 6-day HRT, with residual turbidity of 11 ± 5 NTU for 36.53 L m−2 d−1 HLR. P. stratiotes free root structures promoted interception of suspended colloidal particles, resulting in a better performance. The dense root structure of T. domingensis spreading through the pores of the substrate provided better efficiency than N. humboldtiana. However, N. humboldtiana proved to be promising as a native species. The use of small granulometry alkaline support media (9 to 19 mm) was highlighted. Therefore, this research proves the efficiency of constructed wetlands in reducing high turbidity and provides optimized parameters for this technology application.
The Role of Credit Consortia in the Financial Structure of Sardinian Companies During the SARS-CoV-2 Crisis
Authors: Desogus Marco , Sergi Enrico , Zedda Stefano
Published: November 2024

In this paper, we analyzed the role of credit consortia in supporting SMEs of the Italian region of Sardinia around and during the SARS-CoV-2 pandemic crisis. Credit consortia (or credit guarantee schemes) are financial companies whose institutional role is to support small firms needing bank lending who are individually weak in the bank–firm relationship. Credit consortia are particularly relevant in Italy, where they mitigate credit restrictions for SMEs by supplying guarantees to the bank, allowing for partial coverage of potential losses, providing peer-monitoring activity, and collectively negotiating more favorable interest rates and other conditions with banks. During the SARS-CoV-2 pandemic, credit consortia had a crucial role in supporting Sardinian SMEs with guarantees and obtaining government financial support. The evolution of Sardinian companies’ financial structures during the SARS-CoV-2 pandemic shows that the confidi-supported firms have low capitalization and are financially fragile yet capable of good returns. The liquidity provided by the government during the pandemic loosened these constraints, boosting the available liquidity, which translated, in short, into higher investment and higher sales. The demographics of Sardinian companies in 2019–2022 and the volumes of loans and savings showed a strengthening of debt capital payments, increased collections, and a progressive improvement of the Sardinian companies’ net financial positions.
A Snapshot of Factors Associated with the Severity of Crashes Involving Physically Impaired Drivers
Authors: Bhuiya Md Musfiqur Rahman , Adanu Emmanuel Kofi , Jones Steven , Okafor Sunday , Liu Jun
Published: November 2024

Drivers with physical and/or mental impairments face many driving challenges. However, not many studies have been carried out to understand the factors that contribute to crashes involving these drivers and how these factors influence their crash outcomes. This study aims to address this gap in the road safety literature. The study uses historical crash data from the State of Alabama for at-fault physically impaired drivers and utilizes a random parameter with heterogeneity in a mean modeling approach to account for unobserved heterogeneity. The model estimation results reveal that in rural areas, driving over the speed limit, the time of crash being between 6.00 p.m. and 11.59 p.m., younger drivers, employed and distracted drivers were associated with severe injuries. Minor injury crashes are found to be associated with female drivers, state roads and residential areas. Finally, property-damage-only crashes are more associated with weekdays, driving under the influence of alcohol or drugs, a road with left curvature, driving too fast for the road conditions and intersections. The results obtained provide a foundation for the adoption of targeted countermeasures to improve highway safety for physically impaired drivers and all road users in general.
Racialized Representations of Migrants by the Local Police in Chile
Authors: Doña-Reveco Cristián , Bonhomme Macarena , Zúñiga Liza
Published: November 2024

In this article, we explore the racialized construction of migrants by the Carabineros, the Chilean national police. Based on a qualitative case study, we show that the representations of Latin American and Caribbean migrants by members of this institution are racialized and mostly framed on ideas of a historically constructed superiority. Drawing on interviews with police personnel from different units in Santiago, Chile, we show how the historical state racist policies on migration and systemic institutional racism are embedded in the Carabineros’ discourse, who represent the state and law in their everyday interactions with migrants. Historically, this institution continues to be a strongly hierarchical and militarized police force, whose mission has been to defend territorial integrity and the moral, socio-historical, and cultural national identity, as well as to uphold the most important values of the so-called Chilenidad. We argue that the Chilean police frame their racialized representations of Latin American and Caribbean migrants within systemic institutional racism and socio-historical tropes, particularly from racialized, class, and moral perspectives that reproduce anti-immigrant sentiments and illustrate the ways in which migrants have been historically criminalized and treated in everyday life.
Overview of Sustainable Water Treatment Using Microbial Fuel Cells and Microbial Desalination Cells
Authors: Farahani Hamed , Haghighi Mostafa , Behvand Usefi Mohammad Mahdi , Ghasemi Mostafa
Published: November 2024

Global water scarcity and pollution are among the most severe challenges, affecting the lives of over 2.2 billion people and leading to a projected water demand that will exceed supply by 40% by 2030. Even though reverse osmosis and thermal desalination are commonly adopted water governance solutions, with energy consumption rates reaching up to 10 kWh/cubic meter of water, they remain economically unfeasible for most countries. Therefore, with rapid population growth and industrialization, high operation costs further limit the adoption of the traditional water treatment technologies. However, microbial fuel cells (MFCs) and microbial desalination cells (MDCs) are an innovative solution due to their ability to treat wastewater, desalinate water, and generate bioelectricity simultaneously. The recent advancements in MFCs have enabled the achievement of over 3 W/m2 of power density, while desalination efficiencies in MDCs have surpassed 63%, reducing total energy consumption by more than 40% when compared to traditional methods. The innovative use of electrode materials, like graphene and carbon nanotubes, has led to a 40% faster electron transfer rate, further increasing the efficiency of energy recovery. Moreover, the innovative integration of artificial intelligence (AI) and machine learning (ML) optimized MFCs and MFC operations, leading to a cost reduction of up to 20% through the real-time monitoring of PMDCs. The main challenges, such as the high capital costs and membrane fouling, were also considered, with the system scalability being the recurring concern. Thus, the current reports suggest that MFCs and MDCs would reduce wastewater treatment costs by 30% if applied on a large scale in the future.
Does Market Integration Improve Air Quality: A Study Based on Spatial Models
Authors: Li Zining , Li Congxin
Published: November 2024

Studying the impact and mechanism of market integration on air quality is significant for promoting continuous improvement of air quality and green development. This article selects panel data from provinces in China from 2014 to 2021, uses a dynamic spatial lag model to test market integration’s impact on air quality empirically, and further tests spatio-temporal heterogeneity through geographically and temporally weighted regression (GTWR). The research results indicate that overall, both commodity market integration and capital market integration have improved air quality, while labor market integration has worsened air quality. There are temporal dynamic effects and spatial spillover effects on air quality. There is spatial heterogeneity in the regression coefficients of commodity market integration, labor market integration, and capital market integration.
The Contribution of Off-Takers to Sustainable Agricultural Cluster Businesses
Authors: Mulyana Asep , Masduki Teten , Muizu Wa Ode Zusnita , Febrianti Tri , Triski Dara Sagita
Published: November 2024

The agricultural sector is a cornerstone of many developing economies, supporting millions of livelihoods, contributing significantly to GDP, and ensuring food security and social stability. This study explores the crucial role of off-takers in enhancing the resilience and sustainability of agricultural clusters. Through predetermined purchase agreements, off-takers offer market certainty, stabilize income for smallholder farmers, and provide essential support in capital access, technical assistance, and technology adoption. Employing a Systematic Literature Review (SLR) method and secondary data analysis, along with a case study focusing on an agricultural cluster in West Java, Indonesia, this research highlights how off-takers contribute to price stability, promote entrepreneurial skills among farmers, and foster social entrepreneurship. The findings emphasize the importance of building strategic partnerships between farmers, off-takers, and government entities to strengthen agricultural competitiveness, support sustainable rural economies, and ensure food security. Practical recommendations are provided for policymakers and stakeholders to optimize off-taker engagement in agricultural clusters, thereby fostering thriving agricultural ecosystems and economic prosperity in rural communities.
Future Installation, Production and Global Trade of Clean Energy Technologies
Authors: Hembach-Stunden Katharina , Banning Maximilian , Becker Lisa , Lutz Christian , Matschoss Patrick , Klann Uwe , Horst Juri
Published: November 2024

While transitioning to clean energy technologies offers countries economic advantages, the risk of “low carbon leakage” arises if production shifts to more favorable locations. We conducted a scenario analysis to examine potential shifts in production and trade patterns of clean energy technologies. Our novel empirical approach combines the global macroeconometric model GINFORS-E with a newly developed gravity trade model and integrates a socio-political analysis based on a Multi-Level Perspective (MLP) framework, innovatively augmented by quantifiable indicators. The MLP-analysis defines the expansion paths of clean energy technologies in an alternative scenario, allowing us to incorporate political and social dynamics into our analysis. The baseline scenario is based on announced pledges. For established technologies like photovoltaics, we observe minimal shifts in global trade shares as production capacities approach their limits, signaling market saturation. Conversely, emerging technologies like hydrogen electrolyzers display greater shifts, highlighting potential for market disruption and increased risk of low carbon leakage. While adopting clean technologies in individual countries lead to sector-specific changes, broader macroeconomic impacts appear constrained by existing market structures and path dependencies. Sensitivity analyses suggest that component-specific price changes influence trade and production. Expanding our approach to additional technologies and countries remains challenging due to data limitations.
The Impact of Financial Inclusion and Digitalization on CO2 Emissions: A Cross-Country Empirical Analysis
Authors: Le Vu Linh Toan , Pham Khanh Duy
Published: November 2024

This research investigates the influence of financial inclusion and digitalization on carbon dioxide (CO2) emissions by analyzing a sample of 38 countries from 2006 to 2020. For our analysis, we use the SGMM method and fixed-effect panel threshold models. Financial inclusion and digitalization are measured using newly constructed indices derived from principal component analysis. Despite some variations in specific details, the overall trend in the relationship among CO2 emissions, financial inclusion, and digitalization remains consistent across high-income and low- and middle-income countries. Our findings reveal that financial inclusion has a significant and non-linear impact on CO2 emissions. Conversely, digitalization is found to reduce CO2 emissions significantly. Furthermore, the threshold models indicate that the impact of financial inclusion on CO2 emissions varies depending on the levels of financial inclusion and digitalization. The influence of financial inclusion on CO2 emissions is lower at higher levels of financial inclusion and digital technology, and vice versa. Our findings have implications for policymakers who seek to develop economic policies for sustainable development. By adopting policies that promote digital technologies, policymakers can enhance financial inclusion and economic growth and reduce CO2 emissions.
Enhancing Well-Being at Population Level: A Case Study on Romania
Authors: Cârstea Vlad Gabriel , Iordache Ana Maria Mihaela , Ionescu Alexandru , Grigore Nela Ramona , Coculescu Cristina
Published: November 2024

The concept of well-being is multifaceted, influenced by a range of factors, including economic, social, perceptual, and personal, and varies considerably between individuals, countries, and continents. The objective of this research paper is to achieve an efficient grouping of countries according to several indicators that measure overall happiness. The indicators utilized in this study, derived from the World Happiness Report, are as follows: Life Ladder, Log GDP (Gross Domestic Product) per capita, Social Support, Healthy Life Expectancy at Birth, Freedom to Make Life Choices, Generosity, Perceptions of Corruption, Positive Affect, and Negative Affect. Consequently, following the identification, filtering, and collection of data on the countries in the study, cluster analysis, discriminant analysis, and neural network training were employed to obtain a classification of the countries into heterogeneous groups with a minimum error rate. Finally, for Romania, scenarios and policies were developed to facilitate ascent from the initial class to a class with a superior level of well-being.
Certain Geometrical Properties and Hardy Space of Generalized k-Bessel Functions
Authors: Aktaş İbrahim , Cotîrlâ Luminiţa-Ioana
Published: November 2024

In this paper, we study certain geometric properties such as the starlikeness of order ζ and the convexity of order ζ of the generalized k-Bessel function. In addition, we establish several requirements for the parameters so that the generalized k-Bessel function belongs to some subclasses of analytic functions. Furthermore, as an application of the geometric properties, we establish certain results concerning the Hardy spaces of the generalized k-Bessel function. On the other hand, we present some corollaries concerning the classical Bessel function Jρ and the modified Bessel function Iρ. To support our geometric results, we present some specific examples of functions that map the open unit disk onto the symmetric domains with respect to the real axis.
Aflatoxin Contamination of Various Staple Foods from Angola and Mozambique
Authors: Matusse Cláudio , Lucamba Zelda , Bila João , Macuamule Custódia , Sampaio Ana , Afonso Sandra , Venâncio Armando , Rodrigues Paula
Published: November 2024

Aflatoxins constitute a significant risk in staple foods produced in African countries. This research aimed to analyze the total aflatoxin (AFT) contamination of various staple foods in Angola and Mozambique. A total of 233 samples of corn, peanuts, beans, rice, and cassava flour collected from farmers or local markets from the province of Cuanza Sul, Angola, and the provinces of Gaza and Inhambane, South Mozambique, were analyzed for the presence of AFT using the lateral flow strip method via AgraStrip® Pro WATEX® (Romer). The results showed that, from all matrices, the highest incidence and level of AFT were found in corn produced in Mozambique, with medians ranging from 6.5 to 66.5 µg/kg, with the samples showing values as high as 9200 µg/kg. Levels higher than the maximum admissible levels recommended by the Codex Alimentarius Commission for cereals and pulses (15 µg/kg) were observed in up to 90% of the corn samples, depending on the province. Corn produced in Angola showed lower amounts of AFT, with medians ranging from 1.2 to 7.7 µg/kg. Considering the maximum admissible levels for AFT recommended by the European Commission and the Codex Alimentarius Commission for cereals and pulses, the level of AFT contamination in staple food produced and consumed in the studied provinces is high and constitutes a public health risk for the population. Therefore, risk mitigation strategies are urgently needed.
Radio Spectrum Observations and Studies of the Solar Broadband Radio Dynamic Spectrometer (SBRS)
Authors: Huang Jing , Tan Baolin
Published: November 2024

Solar radio spectral observation is one of the essential approaches for solar physics research, which helps us study the plasma dynamics in the solar atmosphere. The Solar Broadband Radio Dynamic Spectrometer (SBRS) started observing the Sun at Huairou Solar Observing Station in Beijing, China, in 1999. It has obtained a large amount of high-quality observation data of solar radio dynamic spectra in the centimeter–decimeter wavelengths (1.10–7.60 GHz). In particular, the observations with high-temporal resolution of millisecond and high-frequency resolution of MHz display plenty of superfine structures in the dynamic spectrum, which provide crucial information on the radiation process of various radio bursts. We review the past history of solar radio spectral observation and scientific results of SBRS. It is meaningful and will undoubtedly help us inspire new ideas for future research. The understanding of the basic plasma processes in solar plasma could also promote the development of solar physics, astrophysics, and space weather. To broaden the observation frequency range, we propose a new spectrometer at millimeter wavelengths (20–100 GHz) with ultra-wideband and high time–frequency resolution to study the physical processes in the solar transition region. This will open a new window for solar physics research and will provide crucial observational evidence for exploring a series of major issues in solar physics, including coronal heating, solar eruptions, and the origin of solar winds.
Predictive Efficacy of Dual Therapies Combining Integrase Strand Transfer Inhibitors with Second-Generation Non-Nucleoside Reverse Transcriptase Inhibitors Following HIV-1 Treatment Failure in Cameroon: Implications for the Use of a Long-Acting Therapeutic Strategy in Low- and Middle-Income Countries
Authors: Gouissi Anguechia Davy-Hyacinthe , Bouba Yagai , Semengue Ezechiel Ngoufack Jagni , Ka’e Aude Christelle , Takou Désiré , Ambe Chenwi Collins , Beloumou Grace , Nka Alex Durand , Basseck Wome Ulrich Roland , Santoro Maria Mercedes , Ceccherini-Silberstein Francesca , Chatté Adawaye , Montesano Carla , Cappelli Giulia , Colizzi Vittorio , Ndjolo Alexis , Mbanya Dora , Ndembi Nicaise , Perno Carlo-Federico , Fokam Joseph
Published: November 2024

Dual therapies (DT) combining integrase strand transfer inhibitors (INSTIs) with second-generation non-nucleoside reverse transcriptase inhibitors (2nd-Gen-NNRTIs) offer new possibilities for HIV treatment to improve adherence. However, drug resistance associated mutations (RAMs) to prior antiretrovirals may jeopardize the efficacy of DT. We herein describe the predicted efficacy of DT combining INSTIs + 2nd-Gen-NNRTI following treatment failure among Cameroonian patients. We genotyped the HIV-1 pol gene using Sanger sequencing and assessed acquired RAMs to NNRTIs and INSTIs in patients failing treatment from March 2019 to December 2023. Drug susceptibility was interpreted using Stanford HIVdb v9.5, and statistical analyses were performed using SPSS v22. Of 130 successfully genotyped participants (median age (IQR): 38 (27–46) years; 59.2% female), 92.3% had RAMs to NNRTIs and 1.5% to INSTIs. Prevailing RAMs were Y181C (32.3%) among NNRTIs and R263K (0.7%) among INSTIs. Among 2nd-Gen-NNRTIs, etravirine, doravirine and rilpivirine had 43.85%, 41.54% and 38.46% genotypic sensitivity, respectively. Among INSTIs, we found 97.69% efficacy for dolutegravir/bictegravir, 96.15% for cabotegravir and 92.31% for elvitegravir/raltegravir. The overall predictive efficacy of DT was lower among participants who failed 1st-Gen-NNRTI (p < 0.001); with etravirine + dolutegravir/bictegravir combination showing the highest score (43.8%). Conclusively, DT combining INSTIs + 2nd-Gen-NNRTIs might be suboptimal in the context of previous ART failure, especially with NNRTI-based treatment in low- and middle-income countries. The general data clearly indicate that without resistance testing, it is nearly impossible to use long-acting dual therapies in previously failing patients.
Serological Evidence of Hantavirus in Bats from the Brazilian Atlantic Forest: An Investigation of Seroreactivity and Cross-Reactivity of Neotropical Bat Samples Using Nucleoproteins of Rodent- and Bat-Borne Hantaviruses
Authors: Rangel Caroline Lacorte , Fontes Silvia da Silva , Silva Marcus Vinicius de Mattos , Fernandes Jorlan , Mansur Janaina Figueira , Vilar Emmanuel Messias , da Costa-Neto Sócrates Fraga , Novaes Roberto Leonan Morim , Cordeiro-Estrela Pedro , Moratelli Ricardo , de Lemos Elba Regina Sampaio , Borges Ronaldo Mohana , Rodrigues-da-Silva Rodrigo Nunes , Oliveira Renata Carvalho de
Published: November 2024

Hantaviruses are zoonotic pathogens associated with severe human diseases such as hemorrhagic fever with renal syndrome and hantavirus pulmonary syndrome. Despite the extensive study of rodent-borne hantaviruses, research on bat-associated hantaviruses remains limited. This study aimed to investigate the seroprevalence and cross-reactivity of neotropical bat samples with rodent- and bat-associated recombinant hantavirus nucleoproteins (rNPs) to improve hantavirus surveillance in the Brazilian Atlantic Forest. The studied bat population consisted of 336 blood samples collected over nearly a decade in five Brazilian states (Bahia, Rio de Janeiro, Santa Catarina, Paraná, and Minas Gerais). Antibodies were detected using IgG ELISA assays with rNPs from bat-borne Mobatvirus xuansonense (XSV) and Loanvirus brunaense (BRNV) and the rodent-borne hantaviruses Orthohantavirus andesense (ANDV) and Orthohantavirus seoulense (SEOV). Results indicated a higher seroprevalence for the BRNV rNP (36.6%) compared to ANDV (7.4%), SEOV (5.7%), and XSV (0.6%). The high sensitivity of the BRNV rNP and the cross-reactivity observed with the ANDV rNP, the main protein used for serological tests in the Americas, indicates that BRNV rNP is a better antigen for the accurate detection of antibodies against hantaviruses in Brazilian bats. These findings underscore the presence of unknown hantaviruses antigenically similar to BRNV in Brazilian bat populations and highlight the urgent need for identifying better antigens for comprehensive hantavirus monitoring in bats.
Integrating Interpretability in Machine Learning and Deep Neural Networks: A Novel Approach to Feature Importance and Outlier Detection in COVID-19 Symptomatology and Vaccine Efficacy
Authors: Jacob Khoury Shadi , Zoabi Yazeed , Scheinowitz Mickey , Shomron Noam
Published: November 2024

In this study, we introduce a novel approach that integrates interpretability techniques from both traditional machine learning (ML) and deep neural networks (DNN) to quantify feature importance using global and local interpretation methods. Our method bridges the gap between interpretable ML models and powerful deep learning (DL) architectures, providing comprehensive insights into the key drivers behind model predictions, especially in detecting outliers within medical data. We applied this method to analyze COVID-19 pandemic data from 2020, yielding intriguing insights. We used a dataset consisting of individuals who were tested for COVID-19 during the early stages of the pandemic in 2020. The dataset included self-reported symptoms and test results from a wide demographic, and our goal was to identify the most important symptoms that could help predict COVID-19 infection accurately. By applying interpretability techniques to both machine learning and deep learning models, we aimed to improve understanding of symptomatology and enhance early detection of COVID-19 cases. Notably, even though less than 1% of our cohort reported having a sore throat, this symptom emerged as a significant indicator of active COVID-19 infection, appearing 7 out of 9 times in the top four most important features across all methodologies. This suggests its potential as an early symptom marker. Studies have shown that individuals reporting sore throat may have a compromised immune system, where antibody generation is not functioning correctly. This aligns with our data, which indicates that 5% of patients with sore throats required hospitalization. Our analysis also revealed a concerning trend of diminished immune response post-COVID infection, increasing the likelihood of severe cases requiring hospitalization. This finding underscores the importance of monitoring patients post-recovery for potential complications and tailoring medical interventions accordingly. Our study also raises critical questions about the efficacy of COVID-19 vaccines in individuals presenting with sore throat as a symptom. The results suggest that booster shots might be necessary for this population to ensure adequate immunity, given the observed immune response patterns. The proposed method not only enhances our understanding of COVID-19 symptomatology but also demonstrates its broader utility in medical outlier detection. This research contributes valuable insights to ongoing efforts in creating interpretable models for COVID-19 management and vaccine optimization strategies. By leveraging feature importance and interpretability, these models empower physicians, healthcare workers, and researchers to understand complex relationships within medical data, facilitating more informed decision-making for patient care and public health initiatives.
Progress of Measles and Rubella Surveillance in the Context of Measles Elimination in the WHO Eastern Mediterranean Region, 2019–2022
Authors: Farid Muhammad , Fahmy Kamal , Ghoniem Amany , Sharifuzzaman Md , Hasan Quamrul , Crowcroft Natasha , O’Connor Patrick
Published: November 2024

In 2015, the 62nd session of the Regional Committee [RC] of the Eastern Mediterranean Region [EMR] endorsed the Eastern Mediterranean Vaccine Action Plan 2016–2020 (EMVAP) that included postponement of the measles elimination target to before 2020. However, the EMR does not have a regional rubella control or elimination goal. We reviewed the progress of measles and rubella surveillance in context of measles elimination in the Eastern Mediterranean Region during 2019–2022. We compiled data on coverage, reported cases, surveillance indicators, incidence, and genotypes. We conducted an age-cohort analysis to estimate the size of the susceptible population using coverage and SIAs coverage data. We reviewed the dossiers of countries that applied to the Regional Verification Commission [RVC] for the verification of measles and rubella elimination. Between 2019 and 2022, the regional coverage of the vaccine against measles and rubella was stable at 83% for the first dose [MCV1] and increased from 75% to 78% for the second dose [MCV2] after a dip during COVID-19. In the EMRO, eighteen countries are using MR (measles–rubella) and/or measles–mumps–rubella (MMR) vaccines and four are using measles vaccines. The reported regional measles incidence per 1,000,000 was 23.3 in 2019, decreased to 7.4 in 2020, and re-increased to 50 in 2022, with two main genotypes–D8 and B3–in circulation. Both genotypes are considered to be actively circulating in eighteen countries, with different circulating variants of each genotype. There were no genotyping data available from four countries. Measles and rubella surveillance indicators deteriorated in the region. The number of susceptible individuals exceeded one birth cohort in nine of the 22 countries. In 2019–2022, Bahrain, Egypt, Iran, and Oman were verified to have eliminated measles and rubella. While four countries eliminated measles and rubella and another five progressed toward measles and rubella elimination, however, immunity gaps and reported incidence increased in eleven countries. Countries approaching elimination need to prepare verification dossiers, while others need to increase their routine coverage, conduct follow-up campaigns, and improve surveillance. Submission of progress reports to the RVC will measure progress toward the goal.
Changes in Gut Microbiota in Peruvian Cattle Genetic Nucleus by Breed and Correlations with Beef Quality
Authors: Quilcate Carlos , Estrada Richard , Romero Yolanda , Rojas Diorman , Mamani Rolando , Hañari-Quispe Renán Dilton , Aliaga Mery , Galindo Walter , Vásquez Héctor V. , Maicelo Jorge L. , Arbizu Carlos I.
Published: November 2024

This study evaluated the gut microbiota and meat quality traits in 11 healthy female cattle from the Huaral region of Peru, including 5 Angus, 3 Braunvieh, and 3 F1 Simmental × Braunvieh. All cattle were 18 months old and maintained on a consistent lifelong diet. Meat quality traits, including loin area, fat thickness, muscle depth, and marbling, were assessed in vivo using ultrasonography. Fecal samples were collected for microbiota analysis, and DNA was extracted for 16S and 18S rRNA sequencing to characterize bacterial, fungal, and protist communities. Significant correlations were observed between microbial genera and meat traits: Christensenellaceae R-7 and Alistipes were positively associated with marbling and muscle area, while Rikenellaceae RC9 showed a negative correlation with fat thickness. Among fungi, Candida positively correlated with marbling, while Trichosporon was negatively associated with muscle depth. For protists, Entodinium negatively correlated with fat thickness and marbling. Alpha diversity varied by breed, with Angus showing greater bacterial diversity, and beta diversity analyses indicated a strong breed influence on microbial composition. These findings suggest that microbial composition, shaped by breed and dietary consistency, could serve as an indicator of meat quality, offering insights into gut microbiota’s role in optimizing cattle production.