bluuebunny/crossref_metadata_2025_split huggingface dataset:
Development of a New Tool to Simultaneously Measure Soil Permeability and CO2 Concentration as Important Parameters for Geogenic Radon Potential Assessment
Authors: Janik Miroslaw , Gomez Christopher , Kodaira Satoshi , Grzadziel Dominik 
Published: August 2024

Abstract

This study assessed the geogenic radon potential using PECAME, an innovative tool designed to simultaneously measure soil permeability and CO2 concentration -- two key parameters for understanding radon transport in soil. Comparative field studies using the RADON-JOK device in various geological settings in Japan and Poland demonstrate the effectiveness of PECAME. These studies reveal a strong correlation between PECAME and RADON-JOK, with an R2 value of 0.87. Since the soil radon concentration and permeability were measured simultaneously, the geogenic radon potential was calculated. Most measured points fall within the low to medium radon index zones, with two exceptions near active faults located in the high zone. Therefore, permeability and CO2 measurements using PECAME may facilitate further research in Japan to develop a comprehensive geogenic radon potential map.
Coal–gangue sound recognition using hybrid multi–branch CNN based on attention mechanism fusion in noisy environments
Authors: Song Qingjun , Hao Wenchao , Song Qinghui , Jiang Haiyan , Li Kai , Sun Shirong 
Published: August 2024

Abstract

The coal–gangue recognition technology plays an important role in the intelligent realization of fully mechanized caving face and the improvement of coal quality. Although great progress has been made for the coal–gangue recognition in recent years, most of them have not taken into account the impact of the complex environment of top coal caving on recognition performance. Herein, a hybrid multi–branch convolutional neural network (HMBCNN) is proposed for coal–gangue recognition, which based on improved Mel Frequency Cepstral Coefficients (MFCC) as well as Mel spectrogram, and attention mechanism. Firstly, the MFCC and its smooth feature matrix are input into each branch of one–dimensional multi–branch convolutional neural network, and the spliced features are extracted adaptively through multi–head attention mechanism. Secondly, the Mel spectrogram and its first–order derivative are input into each branch of the two–dimensional multi–branch convolutional neural network respectively, and the effective time–frequency information is paid attention to through the soft attention mechanism. Finally, at the decision–making level, the two networks are fused to establish a model for feature fusion and classification, obtaining optimal fusion strategies for different features and networks. A database of sound pressure signals under different signal–to–noise ratios and equipment operations is constructed based on a large amount of data collected in the laboratory and on–site. Comparative experiments and discussions are conducted on this database with advanced algorithms and different neural network structures. The results show that the proposed method achieves higher recognition accuracy and better robustness in noisy environments.
An Inclusive agri-food systems transformation pathway for India
Authors: Singh Vartika , Das Prantika , Stevanovic Miodrag , Jha Chandan , Bodirsky Benjamin , Beier Felicitas , Humpenöder Florian , Leip Debbora , Chen David , Crawford Michael , von Jeetze Patrick , Bacca Edna Molina , Soergel Bjoern , Springmann Marco , Dietrich Jan , Popp Alexander , Ghosh Ranjan Kumar , Lotze-Campen Hermann 
Published: August 2024

Abstract

Although India has transformed from a food scarce to a food self-sufficient nation, the challenges of nutrition security, regional inequalities, and unsustainable agricultural practices persist. Existing policies lack an integrated vision for and implementation of holistic food system changes. This study undertakes a food system assessment for India using a global food system modelling framework, evaluating 23 food system measures on 14 indicators across dimensions of health, environment, inclusion, and economy. The food system measures include healthy diets, biosphere protection, agriculture management, equitable livelihood, and external reforms. Results indicate that 13 out of 14 indicators including nutrition and environmental outcomes improve due to synergistic effects driven by coordinated interventions, reducing trade-offs among the four dimensions of the food system. While progress is observed in most health and environmental indicators, challenges such as rising obesity and nitrogen pollution persist. Our attempt to quantify the dynamics of India’s food system under different scenarios enables understanding the trade-offs across dimensions. The comprehensive and forward-looking food system outcomes that this study elucidates aid in the identification of pivotal intervention points and facilitate strategizing policies for transformative changes.
Echo State Networks for modeling turbulent convection
Authors: Ghazijahani Mohammad Sharifi , Cierpka Christian 
Published: August 2024

Abstract

Turbulent Rayleigh-Bénard convection (RBC) is one of the very prominent examples of chaos in fluid dynamics with significant relevance in nature. Meanwhile, Echo State Networks (ESN) are among the most fundamental machine learning algorithms suited for modeling sequential data. The current study conducts reduced order modeling of the experimental RBC. The ESN successfully models the flow qualitatively. Even for this highly turbulent flow, it is challenging to distinguish predictions from the ground truth. The statistical convergence of the ESN goes beyond the velocity values and is represented in secondary aspects of the flow dynamics, such as spatial and temporal derivatives and vortices. Finally, ESN’s main hyperparameters show values for best performance in strong relation to the flow dynamics. These findings from both the fluid dynamics and computer science perspective set the ground for future informed design of ESNs to tackle one of the most challenging problems in nature: turbulence.
Modeling and Control of Quasi-Z-Source Interleaved Boost DC-DC Converter
Authors: Rashid Reza , Baghramian Alfred , Mojallali Hamed 
Published: August 2024

Abstract

In this article, the modeling and control of the Quasi-Z-Source Interleaved Boost Converter (QZIBC) that can be used in fuel cell vehicles is presented. We have already presented the QZIBC and in order to complete our research and design a suitable controller for it, we started modeling and preliminary investigation of the closed loop response of this converter. For this, first the state matrices of the small signal model of the converter are obtained by using the state space averaging method and then the transfer functions of the output voltage to input voltage and the output voltage to duty cycle (controlling input) are obtained using the Leverrier’s method, which is used to calculation of the transfer functions of high-order converters. The QZIB converter is modeled with the operation point characteristics of 120 W output power, 12 V input voltage, 60 V output voltage and 0.4 duty cycle and its open-loop and closed-loop responses have been evaluated. Also, the closed loop control of this converter has been done using a PI controller which shows very good performance in transient and steady state modes.
Particleboard Surface Optimization for High Quality Laminating with Decor Paper
Authors: Kursun Coskun , Onat Saadettin Murat , Kelleci Orhan , Köksal Süheyla Esin 
Published: August 2024

Abstract

In this study, it was aimed to determine optimum wood content in the particleboard (PB). This issue is important for the protection of forest resources. PBs were produced with two densities (520 and 560 kg/m3), three surface layer (SL) ratios (28%, 30%, and 32%), and two sanding end-thicknesses (17,8 mm and 18,0 mm). PBs were laminated with decor paper (DP) using a hot press (190°C, 35 kg/cm2). It was determined the optimum SL ratio, board density, and sanding tolerance with minimum wood content. Manufacturers have focused on low-density PB production, which can be achieved by consuming less wood. However, various problems occur when laminating surfaces with low-density boards. In this study, the optimal board density, thickness, and SL ratio were investigated. The GRAY multi-criteria decision-making method (MCDM) was used to determine the particleboard with optimum properties. Characterizations of PBs were carried out by physical and mechanical analyses. After the PB surfaces were laminated with DP, abrasion resistance (AR), scratch resistance (SR), porosity (PO), and stain resistance (ST) analyses were performed. According to the results, as the SL increased, PBs density increased, but thickness swelling ( TS) and water absorption (WA) decreased. The thickness after sanding did not cause a significant change in the TS and WA. The internal bond (IB) strength increased 32% and the surface strength (SS) increase 38% when the density was increased.
Trusting in Times of the COVID-19 Crisis: Workplace and Government Trust and Depressive Symptoms among Healthcare Workers
Authors: Basic Djordje , Czepiel Diana , Ven Els van der , Hoek Hans W. , Moro Maria Francesca , McCormack Clare , Carta Mauro Giovanni , Šeblová Dominika , Susser Ezra , Mascayano Franco , Martinez-Ales Gonzalo , Šeblová Jana , Barathie Josleen Al , Karam Elie G , Silva Andréa Tenório Correia da , Ouali Uta , Gureje Oye , Ayinde Olatunde , Afolabi Oyeyemi , Olaopa Olusegun , Burrone María Soledad , Durand-Arias Sol , Ramírez Dorian E. , Solís-Soto Maria Teresa , Flores Jorge Ramírez , Alvarado Ruben , Isahakyan Anna , Alnasser Lubna A. , Nishi Daisuke , Asaoka Hiroki , Balalian Arin A. , Basagoitia Armando , Lindert Jutta , Santaella-Tenorio Julian , Sapag Jaime Camilo 
Published: August 2024

Abstract

Purpose
Previous research has highlighted the negative impact of the COVID-19 pandemic on healthcare workers' (HCWs) mental health, yet protective factors remain underexplored. Emerging studies emphasize the importance of trust in government and interpersonal relationships in reducing COVID-19 infections and fostering positive attitudes toward vaccines. This study investigates the relationship between HCWs' trust in the workplace and government and depressive symptoms during the COVID-19 pandemic.
Methods
The COVID-19 HEalth caRe wOrkErS (HEROES) study surveyed 32,410 HCWs from 22 countries, including both clinical and non-clinical staff. Participants completed the Patient Health Questionnaire-9 (PHQ-9) and ad-hoc questions assessing their trust in the workplace and government. Logistic regression and multilevel models were employed to examine the association between trust levels and depressive symptoms.
Results
High levels of trust in the workplace (OR = 0.72 [0.68, 0.76]) and government (OR = 0.72 [0.69, 0.76]) were associated with lower odds of depressive symptoms, with significant between-country variation in these associations.
Conclusions
Despite substantial cross-country variation, HCWs with higher trust in the workplace and government had approximately 28% lower odds of experiencing depressive symptoms during the COVID-19 pandemic compared to their counterparts with lower trust levels. Promoting trust in the workplace and government may help mitigate the adverse effects of future crises on HCWs' mental health.
Faprication of Palladium Nanoparticles Decorated Reduced Graphene Oxide as a Highly Active and Stable Electrocatalyst
Authors: Ahmed Nada Sami , Azizi Orchideh , El-Boher Arik , Bok Sangho 
Published: August 2024

Abstract

The present research provides novel evidence that the galvanostatic deposition of palladium nanoparticles (Pd NPs) onto a conductive substrate, specifically reduced graphene oxide (RGO), leads to a successful new form of electrocatalysis. These flexible electrodes are synthesized using electrochemical techniques that decorate RGO with both Pd nanoparticles and the PdII complex. The one-step electrochemical deposition from various types of electrolytes was demonstrated. Morphological and structural analyses revealed that Pd NPs can be efficiently, with remarkable stability and activity, electrochemically decorated on the surface of RGO using a Pd NP suspension electrolyte. In addition, electrochemical deposition from PdII complex resulted in a very high density of Pd decorated on the surface of RGO sheets. Several electrocatalytic properties are demanded in this study, which include excellent electrocatalytic activity, uniform dispersion of small Pd nanoparticles over the electrode surface, and high stability combined with flexibility.
Developing an Air Quality Index Model Predictor
Authors: Malakouti Seyed Matin , Menhaj Mohammad Bagher , Suratgar Amir Abolfazl 
Published: August 2024

Abstract

Pollutants and particles have a dynamic character, are highly volatile, and exhibit a high degree of temporal and spatial fluctuation, making it challenging to forecast air quality accurately. On the other hand, the ability to model, forecast, and monitor air quality is becoming more critical, particularly in metropolitan areas. This is because air pollution has significantly impacted the environment and human health. In this paper, we employ extra tree, random forest, Linear Discriminant Analysis, K Neighbors, Logistic regression, and ensemble [random forest, extra tree] machine learning methods to classify the air quality of India from 2015 to 2020. The presented results demonstrate that ensemble [random forest, extra tree] allows us to classify daily AQI (Air Quality Index) for all India's cities accurately.
The Probability of the May 2024 Solar Superstorm
Authors: Elvidge Sean , Themens David 
Published: August 2024

Abstract

In May 2024, a series of coronal mass ejections (CMEs) resulted in the first 'severe' (G4-level) geomagnetic storm watch in nearly 20 years. This event evolved into a significant space weather event, including an 'extreme' (G5) geomagnetic storm, moderate (S2) solar radiation storm, and strong (R3) radio blackout. The widespread visibility of auroras at unusually low latitudes attracted global media attention. Using extreme value theory (EVT), this study estimates the return periods for the May 2024 storm based on several geomagnetic indices. The results indicate that while the storm's magnitude was a 1-in-12.5-year event, its duration was a 1-in-41-year event. This discrepancy highlights the storm's unusual longevity compared to its intensity. Updated EVT analyses incorporating recent data refine these return period estimates, providing critical insights into the frequency of such extreme space weather events.
Pollen dispersal pattern from the mediterranean shrub Cistus ladanifer L. to its congener C. laurifolius L.: ecological and conservation implications
Authors: Carrió Elena , Pérez Álvaro D. 
Published: August 2024

Abstract

Gene flow between congeners in natural systems can have important consequences for the species involved. Cistus ladanifer plays a significant role in natural ecosystems and is also considered a valuable source of natural resources. The objective of this study is to investigate the pollen dispersal pattern from this species to its congener, Cistus laurifolius. To this end, an analysis of pollen analog dispersal (using fluorescent dye) was conducted in a mixed population of both species. The pollen dispersal pattern of C. ladanifer to C. laurifolius was estimated, and the relationship between the dispersal distance and the distance from the pollen analog source of C. ladanifer plants was investigated. The results showed the ability of C. ladanifer to pollinate C. laurifolius. Cistus laurifolius plants closer to the particle emission source provided by C. ladanifer individuals received a greater amount of pollen analogs (fluorescent dye) on their stigmas than those farther away. Most of the detected pollen analogs (80%) dispersed within 60 meters of the donor plants. The evidence of pollen transfer from C. ladanifer to C. laurifoliushighlights the importance of studying pollen dispersal patterns in species that are potential candidates for exploitation and use as new crops. This is crucial to avoid impacts on populations of other wild congeners.
Knowledge, Attitude, and Practice Towards Diabetes Mellitus Tmong Chiro Town Population, Eastern Ethiopia
Authors: Wolde Wondimagegn , Atle Daniel , Girma Dechasa , Hailu Samuel 
Published: August 2024

Abstract

Background: Diabetes mellitus is a metabolic disorder of multiple etiological factors characterized by chronic hyperglycemia with disturbance of carbohydrate metabolism. It can play the vital role in the cause of morbidity and mortality through continued clinical consequence and mortality. Therefore good knowledge of diabetes mellitus prevention and management is necessary in promoting care and enhancing good therapeutic outcomes.
Objective:To assess the knowledge, attitude, practice and associated factors among general population regarding diabetes mellitus in Chiro town, Estern Ethiopia, august 01 to October 30, 2023.
Methods: Cross-sectional study design was conducted on 764 subjects from Augeust 01 to December 30, 2023. A pre-tested structured questionnaire was used to collect the socio-demographic information of the study participants. Data was enterd into Statstical Package for social science , checked for completeness and analyzed. The characteristics of the study population were summarized using descriptive statistics, frequency and percentage.
Result: The study revealed that 98% of respondents had heard of diabetes, with 80% correctly identifying it as a condition of high blood sugar and 25% recognizing inadequate insulin action as a characteristic. Additionally, 65.57% demonstrated good knowledge of diabetes, 60% had a positive attitude towards diabetes management, and 35.4% reported good practices. Despite these insights, misconceptions persisted, such as 25% believing diabetes is caused by a curse. Regular exercise and non-smoking were common positive practices, but only 10.4% regularly checked their blood sugar levels.
Conclusion and recommendation: This study highlights high diabetes awareness (98%) but incomplete understanding, with only 25% recognizing inadequate insulin action. Mixed perceptions about diabetes management and significant gaps in prevention practices underscore the need for targeted educational programs, emphasizing the treatability of diabetes, regular monitoring, and healthier lifestyle choices. Enhanced awareness of comprehensive diabetes care, including proper medication use and physical activity, is crucial.
Has Scale Sustained Its Value as an Important Element in Map-making in the Age of Geospatial Technology? Unveiling Grid Method for Area Measurement
Authors: Dhawale Nideshkumar , Patel Hemlata , Dhorde Amit 
Published: August 2024

Abstract

With respect to the age of analog cartography, the levels of detail of a particular region or feature are generally shown at an accurate scale, where the graphical representation of the scale correctly matches the level of classification used in those maps. Currently, many researchers are using geospatial techniques to extract information at different levels of classification of a particular region at a particular map scale. However, little attention has been given to the correlation between the classification level and scale during map composition, whereby the graphical representation of the scale on the final composed map is mostly erroneously depicted. In the modern era, most geographic information system (GIS) software has built-in default scales, which researchers normally prefer to use as such software without changing it. In such a situation, the question arises whether the scale has sustained its value as an important element in map making in the age of geospatial technology. The present study has tried to address this question while alarming all the researchers, especially geographers, are attempting to develop an accurate scale for a given level of classification. This study not only proposes the use of a Graticule/Grid method for area measurement but also establishes a relationship between scale and graticule extension, the contour interval, the spatial resolution of satellite images and the level of classification, which are displayed on a particular scale. The study tried to calculate the total area of Maharashtra using the Graticule method which resulted in an area of 307148.69 km2 which is closer to the actual area (307713 km2) of Maharashtra.
Modulating effective lymphatic drainage in aortic adventitia has anti-atherosclerotic effects: a new mechanism of FOXC2 to improve lymphatic endothelial cells inflammatory damage
Authors: Wu Hongfei , Bao Youli , Li Zhenglong 
Published: August 2024

Abstract

Atherosclerosis is a chronic multifactorial cardiovascular disease. The disruption of lymphatic drainage function, which is induced by inflammatory damage to lymphatic endothelial cells (LECs), plays an essential role in atherosclerosis. However, the detailed regulatory mechanisms remain largely unknown. Since FOXC2 has become a major regulator of lymphatic vessel development and maturation, we explored the possibility that FOXC2 contributes to lymphatic drainage and atherosclerosis. Herein, we identified FOXC2 mitigates atherosclerosis by restoring efficiently lymphatic drainage via regulating LECs inflammatory responses. Atherosclerosis leds to aortic lymphatic drainage dysfunction, and an down-regulation of FOXC2 expression in the aorta, especially in aortic adventitia, and an inhibition of the biological activity of FOXC2. FOXC2 overexpression improved the aortic lymphatic drainage function which led to reducing the accumulation of inflammatory factors in aortic adventitia, lymph nodes and lymphatic fluid. However, disruption of lymph flow by left carotid artery ligation abrogated the beneficial effects by FOXC2 overexpression on atherosclerosis. Western blot and co-immunoprecipitation experiment revealed that TRAF2 as a key downstream target in TNF-α-induced LECs inflammatory damage. FOXC2 overexpression down-regulated TRAF2, inhibited interaction of TNF-α with TRAF2, reduced the inflammatory damage to LECs, and restored LECs functions, which promoted the function of lymphatic drainage. FOXC2 knockout aggravated TNF-α-induced LECs inflammatory damage, TRAF2 up-regulation, and increased TNF-α interaction with TRAF2. Collectively, we have demonstrated that FOXC2 serves a central role in the atherogenesis induced by lymphatic drainage dysfunction.