bluuebunny/crossref_metadata_2025_split huggingface dataset:
Estimating sensible heat flux over bare soils using surface renewal and similarity theories for unstable cases
Authors: Castellvi Francesc , Agam Nurit 
Published: May 2024

Abstract

A model to estimate the sensible heat flux half-hourly (H) for bare soils was derived based on surface renewal (SR) and similarity (MOST) theories, involving the land surface temperature (LST) and low-frequency measurements (wind speed and the air temperature in half an hour), HSR-LST. The dataset included semi-arid and arid climates, where the optimal surface roughness length for momentum (zom), determined from the actual friction velocity (u*) and the measurement height, ranged between 0.68 and 6.1 mm. Fixing the parameter kB-1 (=ln⁡(zom/zoh ) , where z0h is the roughness length for heat) to 2 (traditional value under neutral conditions), a non-dimensional relationship for the SR parameters was proposed. The sensible heat flux estimates were evaluated using the root mean square difference (RMSD) over the mean actual sensible heat flux (HEC), (E =RMSD/(HEC) 100%) considering (as a rule of thumb) excellent, good and moderate for E values up to 25%, 30% and 35%, respectively. For different measurement heights (ranging from 0.5 m up to 20 m), HSR-LST was in excellent, good, and moderate agreement in 6, 3 and 13 cases, respectively. Three cases had E value ranging between 37% and 39%. The sensible heat flux estimates using MOST required calibration of zom and kB-1. It is concluded that HSR-LST method is more direct requiring the wind speed, the air temperature and the land surface temperature as input.
The comprehensive SARS-CoV-2 ‘hijackome’ knowledge base— reveals significant changes in host cell protein expression and activation by multiple SARS-CoV-2 variants
Authors: Varjosalo Markku , Huuskonen Sini , Liu Xiaonan , Redchuk Taras , Salokas Kari , Lundberg Rickard , Maljanen Sari , Belik Milja , Reinholm Arttu , Kolehmainen Pekka , Tripathi Garima , Laine Pia , Belanov Sergei , Auvinen Petri , Vartiainen Maria , Laine Larissa , Österlund Pamela , Julkkunen Ilkka , kakkola Laura 
Published: May 2024

Abstract

The continuous evolution of SARS-CoV-2 has led to the emergence of several variants of concern (VOCs) that significantly affect global health. This study aims to investigate how these VOCs affect host cells at proteome level to better understand the mechanisms of disease. To achieve this, we first analyzed the (phospho)proteome changes of host cells infected with Alpha, Beta, Delta, and Omicron BA.1 and BA.5 variants over time frames extending from 1 to 36 hours post-infection. Our results revealed distinct temporal patterns of protein expression across the VOCs, with notable differences in the (phospho)proteome dynamics that suggest variant-specific adaptations. Specifically, we observed enhanced expression and activation of key components within crucial cellular pathways such as the RHO GTPase cycle, RNA splicing, and ER-associated degradation (ERAD)-related processes. We further utilized proximity biotinylation Mass Spectrometry (BioID-MS) to investigate how specific mutation of these VOC influence viral-host protein interactions. Our comprehensive interactomics dataset uncovers distinct interaction profiles for each variant, illustrating on how specific mutations can change viral protein functionality. Overall, our extensive analysis provides a detailed proteomic profile of host cell for each variant, offering valuable insights into how specific mutations may influence viral protein functionality and impact therapeutic target identification. These insights are crucial for the design of new targeted interventions, aiming to enhance the efficacy of treatments against evolving SARS-CoV-2 variants.
Mathematical Modeling and CFD Analysis with Experimental Investigation of the Geometry of the Grooves Created with CO2 Laser on the Polycarbonate Plate
Authors: Canel Timur , Baglan Irem , Karabas Ogan 
Published: May 2024

Abstract

Mathematical modeling of micro-scale grooves was made on the polycarbonate plate. The micro-scale groove's surface and cross-section structure, created by scanning at a constant speed using a 30 W beam with a CO2 laser, was examined with a high-resolution optical microscope and the groove geometry was precisely measured. Using the data obtained from the measurements and the physical constants of the polycarbonate, mathematical modeling was made for the temperature distribution in two different directions. The Fourier Finite difference method was used to model the temperature distribution along the line on the polycarbonate surface. The experimental studies with 5 different laser beam powers were carried out again to prove the accuracy and validity of the model. Lateral temperature distribution on the surface of the material and vertical temperature distribution towards the depths of the material were investigated separately. The error rates between the proposed mathematical model and the experimental results are between 3.24 % and 8.44 %. Since the experimental results are in good agreement with the proposed model, it can be said that the proposed mathematical model is a reliable model. Moreover, the temperature distributions both in the lateral direction and vertically into the material were modeled with CFD-Computational Fluid Dynamics. The sources of the differences between the ignition, melting and glass transition temperature obtained from the CFD analysis and the actual temperature values were discussed.
Cell-Free Adipose Tissue Extracts: A Novel Approach to Downregulate TRPV1 for Rosacea Treatment
Authors: Zhou Liuyi , Chen Lulu , Li Ting , Wang Lu , Zhao Ye , Fu Zexin , Wu Sufan , Jin Tingting 
Published: May 2024

Abstract

Rosacea is a chronic inflammatory skin disease that typically affects the central facial area. Its main clinical symptoms include paroxysmal flushing, telangiectasia, and non-temporary erythema. Cell-free adipose tissue extracts (ATEs) are liquid components extracted from human adipose tissue that contain large amounts of growth factors. Despite the scar-reducing, anti-aging, and wound-healing effects of ATEs, the efficacy of ATEs in rosacea remains unknown. Therefore, the anti-rosacea effects of ATEs were investigated in LL37 cathelicidin-induced rosacea mice and capsaicin (CAP)-stimulated HaCaT keratinocytes. The in vitro results revealed that ATEs alleviated rosacea symptoms, such as erythema score, erythema area, transepidermal water loss, epidermal thickness, and telangiectasia upon downregulating TRPV1 and CD31 expression. Moreover, the up-regulated TRPV1 protein expression was also recovered by ATEs administration in vivo and in vitro. Meanwhile, ATEs demonstrated good biocompatibility. In summary, ATEs could be a potential therapeutic agent for rosacea by regulating inflammation and alleviating telangiectasia.
Lack of knowledge and training about antibiotic resistance among community pharmacists in Bangladesh: a cross-sectional study
Authors: Hossain Md. Jubayer , Shahariar Musab , Barsha Lamia Hasan Joarder , Shahjahan Muhibullah , Towhid Syeda Tasneem , Sheikh Md. Kamrul , Hasan Md. Mehedi , Rahaman Md Habibur , Sazid Md Shahnewaz 
Published: May 2024

Abstract

This study aimed to assess the current level of knowledge and impact of training among community pharmacists in Bangladesh regarding antibiotic resistance, and to explore the potential relationship between knowledge, training, and antibiotic dispensing practices. A cross-sectional study was conducted among community pharmacists practicing in Bangladesh, using a self-administered questionnaire. The questionnaire assessed the respondents' demographic information, knowledge and attitude towards antibiotic use and antibiotic resistance, and practices towards improving appropriate antibiotic use in community pharmacies. The results of the study showed that the majority of community pharmacists in Bangladesh lacked knowledge and training regarding antibiotic resistance. Only 8.4% of the respondents had adequate knowledge of antibiotic resistance, and 38% had received training on the topic. Furthermore, a significant relationship was found between the level of knowledge and training received by community pharmacists and their antibiotic dispensing practices. Pharmacists with higher levels of knowledge and training were more likely to appropriately dispense antibiotics. The findings of this study highlight the need for increased education and training regarding antibiotic resistance among community pharmacists in Bangladesh. This is crucial for improving antibiotic dispensing practices and for reducing the spread of antibiotic resistance. Policymakers and educators should collaborate to develop and implement training programs and continuing education courses for community pharmacists to improve their knowledge and skills in this area.
Protective effect of CGRP on acute pancreatitis: Based on metabolomics
Authors: Hu Jian-Xiong , Chen Ying-Kai , Chen Shi-Jun , Lin Yan-Ya , Chen Jun-Nian , Xie Ying , Zhao Cheng-Fei , Chen Cun-Rong 
Published: May 2024

Abstract

To study the mechanism of calcitonin gene-related peptide(CGRP) protecting acute pancreatitis based on metabolomics. 24 adult male rats were randomly divided into control group (Con), acute pancreatitis model group (AP), CGRP treatment group (CGRP + AP, abbreviated as CGRP) and CGRP antagonist(CGRP(8–37)) pretreatment group (preCGRP(8–37) + AP, abbreviated as CGRP37), with 6 rats in each group. After different interventions, pancreases of rats in each group were collected for pathological analysis, and serum was collected for metabolomics analysis. Pathological examination of the pancreas suggested that the inflammation of pancreatitis in AP group was significant, the inflammation of pancreatitis in CGRP group was significantly reduced, and the pancreatitis in CGRP37 group was aggravated. Metabolomics of rat serum suggested that the differences in metabolites in each group were mainly related to amino acid metabolism, coenzyme/vitamin metabolism, carbohydrate metabolism, lipid metabolism, digestive system and other metabolic pathways. According to the trend of metabolite changes, we found 6 differential metabolites that were significantly correlated with CGRP intervention, including L-Valine, 5-Aminopentanoic acid, 4-oxo-L-proline, L-glutamine, L-proline, and Ornithine, all of which were related to amino acid metabolism. CGRP can effectively protect acute pancreatitis, possibly by regulating amino acid metabolism to alleviate acute pancreatitis.
GIS-based Spatial Autocorrelation Queen Contiguity Order-One Analysis of the Renewable Energy Consumption and Production of African Countries with Economic and Environmental Indices
Authors: Gwani Alhaji Abdullahi , Kun Sek Siok 
Published: May 2024

Abstract

The worldwide undertaking to achieve sustainable energy solutions has emphasized the need to comprehend the patterns of renewable energy consumption (REP), and production (REC), and socioeconomic and environmental variables. This work utilizes geographic information system (GIS) methodologies and spatial autocorrelation analysis, specifically Queen contiguity order 1 (Q1), to examine the spatial pattern of renewable energy consumption across African nations. This research seeks to reveal regional patterns, detect clusters of comparable renewable energy consumption behaviors, and assess the economic and environmental consequences linked to these patterns, REP, REC, economic indicators, and environmental indices such as African countries' gross domestic product (GDP) and carbon dioxide emissions (CO2) using data from 57 countries from 1990 to 2020. This study measured the similarities of these variables between neighbouring nations using the Q1 spatial autocorrelation methodology. The findings show concentrated areas with high and low REP, REC, and GDP, revealing regional patterns and inequities. This study also analysed trends to determine the eco-nomic and environmental evolution as well as the REP and REC patterns. Additional related variables, including the ecological footprint (EF), economic complexity index (ECI), and global index (GI), were used in Moran’s I statistical analysis. These findings can help policymakers, researchers, and stakeholders establish strategies for sustainable energy, economic growth, and environmental protection across the continent. This multidisciplinary method uses GIS, spatial analysis, economics, and environmental elements to fully comprehend the complex relationships between the variables under investigation. Furthermore, the study recommends an econometric regression model approach to evaluate the link between these variables, with the hope that this technique will facilitate a more thorough understanding of the influence of renewable energy use on the economic and environmental welfare of African nations.
Knowledge-driven design of fluorinated ether electrolytes via a multi-model approach
Authors: Rajput Nav Nidhi , Atwi Rasha , Gribble Daniel , Nguyen Dan Thien , Song Minyung , Babbar Agrim , murugesan vijayakumar , Pol Vilas 
Published: May 2024

Abstract

Fluorinated ether solvents (FLS) can enhance the cycle life of Li-S batteries by mitigating the polysulfide shuttle effect. However, developing fluorinated electrolytes with reduced polysulfide solubility and uncompromised transport properties is underexplored. We integrate high-throughput density functional theory, molecular simulations, machine learning, and experimental analyses to explore ~1,000 FLS to be used as co-solvent with 1,3-dioxolane. Only 14 FLS in our library have been previously reported in Li-S literature. Through a rigorous screening process, we identify and test two new solvents which demonstrate reduced polysulfide solubility. One solvent exhibits electrochemical performance on par with the widely used 1,1,2,2-tetrafluoro-3-(1,1,2,2-tetrafluoroethoxy)propane (TTE) solvent, yet with superior electrolyte viscosity and ionic conductivity. Interpretable machine learning models indicate fluorination degree, steric effects on ether oxygen, and fluorine proximity to ether oxygen are crucial in dictating oxidation reactions and polysulfide solubility. This work not only introduces new promising co-solvents for Li-S batteries but also provides a framework for knowledge-driven electrolyte design.
Dendrometry, production and nutritional value of Mimosa caesalpiniifolia Benth. under monocrop and silvopastoral system
Authors: Izidro José Lypson Pinto Simões Izidro , de Mello Alexandre Carneiro Leão , Cunha Márcio Vieira da , Silva Valdson José da , Costa Suellen Brandão Miranda , Santos José Ronaldo dos , Carvalho Chrislanne Barreira de Macêdo , Santos Mércia Virgínia Ferreira dos , Costa Nivaldo Azevedo , Dubeux José Carlos Batista 
Published: May 2024

Abstract

Legumes have the potential to provide diverse ecosystem services, therefore, it is important to understand the quantitative and qualitative aspects of their development in different cropping systems. The objective of this study was to evaluate the dendrometric, productive characteristics and nutritional value of Mimosa caesalpiniifolia Benth. in monocrop and a silvopastoral system with signal grass, in Brazil. The treatments were distributed under a randomized block design and consisted of M. caesalpiniifolia monocrop system and silvopasture (signal grass + M. caesalpiniifolia). Evaluations were carried out every 56 days for two years. The data were analyzed using repeated measures over time using SAS on demand (2021) and the treatment means were compared using PDIFF with Tukey's test (P < 0.05). There was no effect of cropping systems (P > 0.05) on plant height (~ 5.2 m). The greatest values ​​for diameter at breast height (16.32 cm), basal diameter (20.54 cm), and dry matter production per plant (36 g DM plant− 1) were observed in the silvopasture system (P < 0.05). Forage mass was higher (P < 0.05) in the monocrop system compared to silvopasture (69 and 22 kg DM ha− 1, respectively) in the first year of evaluation. Total forage accumulation was greater in the monocrop system compared to silvopasture (383 vs. 116 kg DM ha− 1 year− 1) in the first year of evaluation. The nutritional value was not influenced (p < 0.05) by the cultivation systems in the first year of evaluation, however, higher content of CP (221 g kg− 1), ADF (449 g kg− 1), and IVDMD (383 g kg− 1) were observed in the rainy season, while the highest DM content (426 g kg− 1) occurred in the dry season. M. caesalpiniifolia showed good dendrometric characteristics in the silvopasture system. The silvopasture provides greater forage production per plant of M. caesalpiniifolia and better nutritional value of the forage than the legume monocrop.
Memristor: An Innovative Approach towards
Modern Electronics and its SPICE Model for Nonlinear Dopant Drift
Authors: Talukder Safwan , Rafid Md. Tahsin , Bhuiyan A.B.M. Noushad 
Published: May 2024

Abstract

Memristor is the fourth fundamental passive circuit element and a novel tool for modern electronics. While MOS transistors are the most important components in electronics, memristors will pave a new path towards more efficient electronic circuits with better performance. This paper studies the various models of memristors and proposes a model with new window function to overcome the latencies of previous models. We propose a Non Linear Ion Drift Model with a new window function that serves as a SPICE model to be simulated in computers to study and analyze the behavior of memristors. The proposed model surpasses the output values in terms of Current, Resistance and Maximum Power compared to other memristor models. We focused on these parameters with a view to ensure better efficiency from the proposed model. Our model achieved improvements of up to a double value in terms of current, compared to other models. The results demonstrate an efficient model that can be implemented as SPICE simulations of memristors for precise analysis of its behavior. The proposed method ensures the proper functioning of memristors that can be implemented in electronic circuits.
Enhancing Anxiety Diagnosis through ADABOOST-Assisted Decision-Level Fusion
Authors: Hosseini Seyedeh sara , Maghooli Keivan 
Published: May 2024

Abstract

Background: Humans naturally respond with anxiety to mental stress caused by a variety of circumstances. Anxiety impairs memory function and makes it difficult to learn and retain information. Additionally, sustaining high productivity while balancing life's stresses can be achieved through good anxiety and stress management. New
Method: This paper presents an effective technique for automatically classifying two anxiety levels: normal and anxious, using an analysis of EEG data. The EEG signals found in the DASPS database were utilized. This database includes 14-channel EEG recordings taken under normal and anxious settings from 23 individuals (10 male and 13 female, average age 30 years). Brain subbands were extracted from EEG signals using wavelet transform. Different features such as Hjorth coefficients, entropy, autoregressive, and energy were extracted. The feature vector was reduced by the PCA method, and the classification was carried out by the Adaboost classification method.
Results: The results demonstrate the effectiveness and efficiency of the proposed model in diagnosing anxiety, with an accuracy of 80.58%. Comparison with Existing Methods: Our study highlights the superior performance of the Adaboost method compared to other methods, showcasing its potential for accurate anxiety classification using EEG data.
Conclusions: In conclusion, the proposed method shows promise for automatic classification of anxiety levels using EEG data. By leveraging machine learning techniques and EEG analysis, our approach could contribute to improved anxiety diagnosis and stress management strategies.
Mathematical Modelling and Optimizing Design of Heliostat Field
Authors: Cheng Zijie , Zheng Ang 
Published: May 2024

Abstract

The heliostat field is a form of solar thermal power plant, and establishing a heliostat field is of great significance for reducing carbon emissions. This paper focuses on the mathematical modelling and optimization design problem of the heliostat field. For three different design scenarios, firstly, based on the data provided by the China Undergraduate Mathematical Contest in Modeling 2023, a geometric optical efficiency model is proposed to determine the annual average optical efficiency and output thermal power under specific heliostat field design parameters. Secondly, aiming at the optimal design parameters of the solar furnace field under the condition of rated annual average output thermal power is 60\(\text{M}\text{W}\), Particle Swarm Optimization (PSO) combing with efficiency model are utilized to determine the optimal design parameters of the heliostat field. Finally, this paper uses Quasi -Monte Carlo ray tracing (QMCRT) model to perform simulation, exploring how to obtain the optimal design parameters of the heliostat field with the goals of maximizing the output thermal power and ensuring high efficiency. On this basis, the influence of normal disturbances on the annual average output thermal power is further explored.
Optimization and development of an airfoil by Bezier curve through computational analysis
Authors: Vala Jignesh , Umathe Manisha , Patel D. K. , Panchal Hitesh 
Published: May 2024

Abstract

Airfoils play a pivotal role in the turbomachinery field, influencing energy efficiency in various applications, including aircraft design and fluid product blending. This research focuses on the optimization of airfoil shapes, aiming to design a new generalized airfoil with adjustable parameters through the application of Bezier curve theory. The investigation employs a combination of experimental techniques in a Low-Speed Open-Type Wind Tunnel and computational simulations using ANSYS Fluent as the flow solver. The study considers the existing C4 Profile and introduces a novel airfoil with varying angles of attack(A.O.A), ranging from 0 degrees to + 30 degrees in 5-degree increments. Steady-state simulations are conducted to solve Reynolds Averaged Navier-Stokes (RANS) Equations, utilizing the shear stress transport (SST) k-ω turbulence model and the Standard k-epsilon turbulence model as closure models, with a moderate turbulence intensity of 5%. The newly designed airfoil, referred to as the Circular arc cambered airfoil, is created using the Bezier curve theory, resulting in a generalized form with adjustable shape parameters. The research findings indicate that the Circular arc cambered airfoil exhibits superior aerodynamic efficiency, generating increased lift and reduced drag when compared to the conventional C4 Profile airfoil. This study contributes to the ongoing exploration of airfoil design optimization, offering insights into the potential enhancements achievable through Bezier curve-based adjustments in shape parameters.