bluuebunny/crossref_metadata_2025_split huggingface dataset:
Sustainability Analysis of Biogas as a Source of Energy in Rwanda
Authors: MAZIMPAKA Ezgad , NTAMBARA Boniface , Hortense Ingabire , Makokha Augustine B , Kiplakat Joseph 
Published: December 2023

Abstract
Rwanda has seen significant advancements in biogas installations, with a significant increase in households accessing biogas since 2012. However, rapid population growth has made it difficult to provide energy security due to energy deficit growth in both rural and urban areas. This study aimed to assess the sustainability of biogas as a source of energy in Rwanda, focusing on energy demand, supply profiles, and sustainability based on technical, environmental, social, and economic indicators. Data was collected from 600 biogas owners and local leaders who supported biogas production sensitization campaigns. The results showed that out of the 728.7GWh energy consumption, 42% was industrial consumption, and 51% was home-based consumption, with 67% of accessibility. The average temperature of 20°C was favorable for biogas digester functionality, leading to 97% of users being satisfied with its cooking efficiency. Biogas development and use increased social well-being by reducing CO emissions to about 7.01gCO/MJ. The reduction in firewood usage helped households and institutions reduce the cost of purchasing firewood by 30 to 80% per year. The study concludes that biogas energy in Rwanda has high levels of energy sustainability and potential for improving health and accessibility to affordable and clean energy to mitigate climate change. The government and Rwanda Energy Group should develop technical guidelines and policies to enhance biogas functionality and allocate budgets for upgrading existing infrastructures and initiating new biogas projects.
Power System Faults Analysis, Detection, and Localization in Underground Distribution and Transmission Networks by Deploying AI-based Matlab Model/Simulink.
Authors: Ntambara Boniface , Hortense Ingabire 
Published: December 2023

Abstract

Employing MATLAB/Simulink, this study designs and builds a fault-detecting and locating approaches for underground distribution and transmission networks. The suggested approach detects and locates faults through an AI-based waveform shift, which has become an established technique in electric power system investigations. MATLAB/Simulink 2019a was implemented to build and test the suggested method on underground distribution and transmission line models. The simulation results revealed that the developed fault detection and localization technique is capable of accurately detecting and locating faults on distribution and transmission lines. The method proposed can assist power system operators in swiftly locating the fault and taking the necessary procedures to restore power supply. Overall, this article is a valuable resource for increasing the reliability and efficiency of electricity transmission and distribution networks.
Sensorless BLDC motor Sliding Mode Control for Disturbance Rejection on Hand Held Motor Drive
Authors: Chang Peter I-Tsyuen , Lin Xin-You , Chen Yong-Kang 
Published: December 2023

Abstract
This research implemented a full sensor-less Sliding Mode Control (SMC) for a three phase Brushless Direct-Current (BLDC) motor for reduction on disturbance during motor operation. Instead of using hall sensors to provide motor speed feedback, this paper utilized the back counter-ElectroMotive Force (EMF), measured in the motor’s control circuitry, and through the zero-crossing characteristic induced from its operation, a full feedback disturbance rejection is implemented for BLDC motor speed regulation. Experimental results compared this SMC control voltage demonstrated a 30% improvement on recovery time, as well as 25% reduction to the maximum disturbance, along with the traditional PI controllers. A full system identification of the motor parameters are also validated rigorously before selection of the SMC parameters. This result brings benefit of a low cost, firmware only efficient BLDC controller algorithm, that is automated in the Embedded system, for disturbance rejection and can be applied to a vast array of products that entails BLDC motors.
Chemo-electro-mechanics of nanodefects in solid-state batteries: A phase-field simulation
Authors: Kamikawa Yuki , Amezawa Koji , Terada Kenjiro 
Published: December 2023

Abstract

Solid electrolytes (SEs) encompass various types of nanodefects, including grain boundaries (GBs) and nanovoids at the Li metal/SE interface, where lithium dendrite penetration has been extensively observed. Despite the importance of ion transport near GBs with different anisotropy and the combinatorial effects with interfacial nanovoids, a comprehensive understanding of these phenomena has remained elusive. This study develops an electro-chemo-mechanical phase-field model to elucidate how Li penetrates Li7La3Zr2O12 (LLZO) in the co-presence of GBs and interfacial nanovoids. The investigation unveils a GB-anisotropy-dependent behavior for Li-ion transport correlated with the presence of interfacial nanovoids. Notably, the Σ1 GB exhibits faster Li dendrite growth, particularly in the co-presence of interfacial nanovoids. The model quantitatively reveals whether interfacial electronic properties dominate Li deposit morphology and penetration, providing a strategy for designing stable Li/SE interfaces. These findings help prioritize approaches for optimally tailoring nanodefects and exploiting synergetic effects at the interface to prevent dendrite formation.
Social Media Influence on COVID-19 Vaccine Perceptions Among University Students: A Malawi Case Study
Authors: Folotiya Mervis , Ngoma Chimwemwe 
Published: December 2023

Abstract

Introduction
The global fight against the COVID-19 pandemic relies significantly on vaccination. The collective international effort has been massive, but the pace of vaccination finds hindrance due to supply and vaccine hesitancy factors. Understanding public perceptions, especially through the lens of social media, is important. This study investigates the impact of social media on COVID-19 vaccine perceptions among university students in Malawi.
Methodology
The study utilized a quantitative methodology and employed a cross-sectional study design to explore the relationship between social media dynamics and COVID-19 vaccine perceptions among 382 randomly sampled students at MUBAS. Data, collected by use of a Likert-scale questionnaire, was analyzed using IBM SPSS 20 for descriptive statistics and Pearson correlation tests.
Results and discussion
The findings reveal crucial correlations. Specifically, trust in online vaccine information shows a positive correlation (r = 0.296, p < 0.01) with active engagement in social media discussions. Conversely, a negative correlation surfaces concerning individuals' reactions to vaccine availability in Malawi (r = -0.026, p > 0.05), necessitating an exploration of influencing factors. The demographic overview underscores the need for tailored communication strategies, given the dominance of the 16 to 30 age group, representing 92.9% of respondents.
Conclusion
The identified correlations emphasize the need for careful communication strategies tailored to combat misinformation and enhance vaccine acceptance among the younger demographic in Malawi.
Predictive Modeling of Slope Stability Using Hybrid Machine Learning Approaches: PCA- GMM based WOA-XGBoost
Authors: Kamran Muhammad 
Published: December 2023

Abstract
Slope instability is a widespread environmental concern that affects all geographical regions. It is crucial to consider slope instability in mining, civil, tunnelling, and geotechnical engineering projects. A catastrophic event involving slope instability can lead to severe economic losses, casualties, and property damage. This study introduces the predictive modelling of slope stability using hybrid machine learning approaches. Firstly, a total of 404 events of slope stability were gathered using easily accessible input attributes. Secondly, principal component analysis (PCA) has been applied to reduce the dimension of the slope stability dataset. Thirdly, gaussian mixture model (GMM) was employed to categorize the PCA obtained dataset into distinct clusters. Fourthly, the parameters of extreme gradient boosting (XGBoost) were optimized using whale optimization algorithm (WOA). Lastly, the performance of the suggested model was assessed using several performance indices. The results indicate that the proposed hybrid PCA-GMM based WOA-XGBoost model exhibits the highest level of reliability. The proposed unsupervised-supervised machine learning method using a metaheuristic algorithm technique can considerably reduce slope-related disastrous incidents while rendering mining operations safer and more sustainable.
Alkaline pre-treatment enhances silicon release efficiency of silicon-rich biochar
Authors: Wu Duoji , Wei Zongqiang , Xia Lijia , Yuan Weiqi , Hu Zuwu , Wu Jianfu 
Published: December 2023

Abstract
Background and Aims
Silicon (Si) -accumulating plants alleviate the problem of low soil Si availability due to high weathering by absorbing labile Si from phytoliths in the soil. However, the efficient release of Si from Si-rich plant residues has not been well studied.
Methods
Rice husk and bamboo leaves were prepared and transformed into rice husk biochar (RHB), bamboo leaf biochar (BLB) and their alkali-modified biochar (ARHB, ABLB), which were then applied to highly weathered soils (high-available Si soil (HASi) and low-available Si soil (LASi)). Explore efficient Si release pathways and evaluate their potentials as efficient Si fertilizers.
Results
The first-order model demonstrated that the biochar Si pools were divided into rapidly-released Si pool C1 and slowly-released Si pool C2, and that alkali-modified biochar had higher Si solubilization capacity. A soil incubation experiment showed that available Si of the soils treated with alkali-modified biochar were significantly increased compared to those treated with original biochar, and this effect was more significant in LASi. In a rice growth pot experiment, biochar addition increased the grain, straw, and root Si concentration in LASi, with the effect being independent of amount added. However, for HASi, Si-rich biochar had no effect on straw Si concentration.
Conclusions
The alkaline pre-treatment of Si-rich biomass can improve its Si release efficiency, leading to increased labile Si content in the soil and improved soil Si availability. Therefore, alkali-modified Si-rich biochar can better sustain Si availability in soils characterized by high weathering and severe desilication.
Chloroplast-actin filaments decide the direction of chloroplast avoidance movement under strong light in Arabidopsis thaliana
Authors: wada masamitsu , Higa Takeshi , Kato Kaoru , Moritoki Nobuko , Nakai Tomonori , Nishino Yuri , Miyazawa Atsuo , Shibata Shinsuke , Mineyuki Yoshinobu 
Published: December 2023

Abstract
Chloroplast-actin (cp-actin) filaments are crucial for light-induced chloroplast movement, and appear in the front region of moving chloroplasts when visualized using GFP-mouse Talin. They are short and thick, exist between a chloroplast and the plasma membrane, and move actively and rapidly compared to cytoplasmic long actin filaments that run through a cell. The average period during which a cp-actin filament was observed at the same position was less than 0.5 sec. The average lengths of the cp-actin filaments calculated from those at the front region of the moving chloroplast and those around the chloroplast periphery after stopping the movement were almost the same, approximately 0.8 µm. Each cp-actin filament is shown as a dotted line consisting of 4-5 dots. The vector sum of cp-actin filaments in a moving chloroplast is parallel to the moving direction of the chloroplast, suggesting that the direction of chloroplast movement is regulated by the vector sum of cp-actin filaments. However, once the chloroplasts stopped moving, the vector sum of the cp-actin filaments around the chloroplast periphery was close to zero, indicating that the direction of movement was undecided. To determine the precise structure of cp-actin filaments under electron microscopy, Arabidopsis leaves and fern Adiantum capillus-veneris gametophytes were frozen using a high-pressure freezer, and observed under electron microscopy. However, no bundled microfilaments were found, suggesting that the cp-actin filaments were unstable even under high-pressure freezing.
Shape-Guided Detection: A joint network combining object detection and underwater image enhancement together
Authors: Yang Chao , Jiang Longyu , Li Zhicheng , Zhang Xinwen 
Published: December 2023

Abstract
Due to the poor quality of underwater images, they are usually not accurate when used for object detection. Most of the currently available solutions involve pre-processing, such as underwater image enhancement, to improve object detection accuracy. However, the pre-processing approach is to improve the subjective perception of the human eye, which does not necessarily improve the object detection performance and also consumes a lot of computational resources. Therefore, in this paper, we innovatively combine these two tasks and propose Shape-Guided Detection Network (SG Detection). We fuse underwater image enhancement and object detection into one network, where object detection can share clean features through joint learning, thus facilitating underwater object detection , and the object detection results will also guide the direction of underwater image enhancement. Meanwhile, in the SG Detection network, we embed the object shape prior features as a learnable module, and design the Shape Priori Enhancement module to achieve the full fusion and interaction between the prior features and local features. In addition, we innovatively adopt a combination of explicit and implicit constraint approach, which ultimately achieves high object detection accuracy. We have conducted extensive experiments on public available datasets, and we find that our approach achieves up to 10% mAP improvement in object detection performance and significantly increases the processing speed.
Controlling Behaviour of Transparency and Absorption in Three-Coupled Multiple Quantum Wells Via Spontaneously Generated Coherence
Authors: Mukherjee Rohit , Hazra Rohit , Borgohain Nitu 
Published: December 2023

Abstract
This article presents a coherent phenomenon called spontaneously generated coherence (SGC) under the regime of electromagnetically induced transparency (EIT) in a three-coupled multiple quantum wells. We demonstrate that the presence of SGC in these quantum wells lead to intriguing modifications in the transparency window within the absorption spectrum. At the same time, modification of the dispersive nature is also demonstrated which enables the feasibility of the system in diverse applications based on light propagation. The absorption and dispersion responses are found to be varied by the individual strength of the first and second control fields in presence as well as in absence of SGC in the EIT regime. The positional shifting of the transparency window and simultaneous modifications in the dispersive profiles by tuning the control field detunings of both the first and second control fields are also revealed. Some absorption and dispersion contours are illustrated for getting better insights into the modifications of the optical responses via SGC. Finally, by manipulating the strength of the SGC parameter, we observe the changes in the respective position of the transparency window and dispersion curve. It is expected that the current investigations will pave novel ways for innovative applications in quantum communications, and fabrication of advanced photonic devices.
Research on Copyright Protection of Live Broadcast Programs of Sports Events From the Perspective of Legal Interpretation
Authors: Li Lei , Sun Hui 
Published: December 2023

Abstract
the newly revised copyright law in 2021 has a significant impact on the protection of live sports programs. In the future, network real-time piracy can be regulated under the new law. However, there is still some room for improvement in the specific application of the new law of the coping legislative model. The definition of audio-visual works needs to be clarified, the scope of broadcasting right and information network communication right needs to be reconstructed, and the expansion explanation of broadcasting organization right needs to be clarified. The new "audio-visual works" in the amendment of the copyright law is essentially a subdivision of video products, which brings original video products into audio-visual works and endows them with complete copyright; For non original video products, the protection of adjacency rights will continue to be given, which can not only meet the practical needs of copyright protection for original producers under the development of video technology, but also fully consider the value of adjacency rights protection for traditional "mechanical" video products. Under the regulation of the new law, the protection of sports event live broadcast copyright and adjacent right to the mode of communication has been expanded to any form, reflecting the consistency of the legal system. Based on the legislative intention of implementing the principle of "technology neutrality" in this amendment, the copyright law should treat the use of works with basically the same implementation purpose and effect and only different communication technical means equally. Therefore, the live broadcast of sports events, whether wireless, wired or network, should be included in the regulation scope of "broadcasting right" in "broadcasting organization right".
Effect of interface on thermal conductivity of graphene- reinforced aluminum matrix composites
Authors: Yan Wang , Xiaoming Du , Siyu Li , Zhendong Sun 
Published: December 2023

Abstract
The thermal conductivity of graphene-reinforced aluminum-based composites was numerically investigated using the finite element method. Firstly, the influence of graphene content, morphology, and orientation on the thermal conductivity of the composite material was studied without interfaces. After obtaining the optimal parameters without interfaces, the effects of interface types and interface thickness were further investigated. The simulation results demonstrated that the thermal conductivity of the composite material improved with increasing graphene content and particle size. The thermal conductivity reached its maximum value when the orientation of the graphene was parallel to the direction of heat flow. When the thermal conductivity of the interface material was greater than that of the matrix, the thermal conductivity of the composite material increased more rapidly with increasing thickness. Conversely, when the thermal conductivity of the interface material was lower than that of the matrix, a smaller intrinsic thermal conductivity resulted in a faster decline in the thermal conductivity of the composite material with increasing thickness. This study reveals that the modification of graphene plays an important role in regulating the thermal conductivity of aluminum matrix composites.
EnsembleBBB: Enhanced accuracy in predicting drug blood-brain barrier permeability with a Machine Learning Ensemble model
Authors: Boulaamane Yassir , Maurady Amal 
Published: December 2023

Abstract
The blood-brain barrier (BBB) serves as a selective and semi-permeable barrier, crucial for maintaining homeostasis within the central nervous system. When developing drugs that act on the brain, understanding the permeability of compounds across the BBB is of utmost importance. However, succinctly formulating this consideration poses a challenge. Clinical experiments are the most accurate method for assessing BBB permeability, but they are time and cost consuming. Hence, computational methods have been explored as an alternative approach to predict BBB permeability. Nevertheless, the issue of accuracy has persistently plagued BBB permeability prediction models. To enhance the precision of BBB permeability prediction, we employed ensemble methods based on popular machine learning algorithms. Our models were trained using a dataset of 7,807 diverse compounds, each encoded with different molecular binary fingerprints. The predictive performance of the developed models was assessed and compared with the literature. We found out that Random Forest algorithm and MACCS fingerprints perform best. Notably, the ensemble model with MACCS fingerprints yielded an AUC of 0.95 in the testing set and a mean AUC of 0.94 in 5-fold cross validation. The applicability domain was evaluated using the William plot, which indicated that the MACCS dataset had the fewest outliers, while the PubChem dataset had the highest number of outliers. The most important features were calculated using the built-in features importance in Random Forest. Furthermore, our model achieved an impressive accuracy of 95% and an AUC of 0.92 in predicting BBB permeability of an external dataset used for benchmarking. This model holds significant promise for facilitating the screening of compounds based on their BBB permeability during the preliminary stages of drug development.
ARDL modeling using R software
Authors: Mestiri Sami 
Published: December 2023

Abstract
The goal of this paper is helping to apply ARDL models using the R software. We will cover its benefits, show how to use the packages and will make interesting recommendations for estimating models ARDL using R.
This paper presents the dynamac package for the statistical language R, demonstrating its main functionalities in a step by step guide.
JEL codes: C15, C88
Dissipation of Chlorantraniliprole, Fipronil and Deltamethrin Residues on Cabbage and Soil
Authors: akoijam romila , NINGOMBAM ARATI , SINGH H N , hanglem chinglemba , TELEM R S , sonia c , singh i m , laha ramgopal 
Published: December 2023

Abstract
The dissipation nature of chlorantraniliprole, fipronil and deltamethrin residues was studied on cabbage and soil. The insecticides such as chlorantraniliprole fipronil and deltamethrin, residues were sprayed as foliar application twice at an interval of 7 days with the recommended doses of deltamethrin (12.5 g a.i./ha), chlorantraniliprole (10 g a.i./ha) and fipronil (50 g a.i./ha). The samples were taken randomly before the application of insecticides and 1 hour after the second spray of insecticides. The repeatability and reproducibility of the residue analysis method of cabbage were found to be 0.30 to 4.50% and 1.84 to 2.39% respectively for all the insecticides whereas that of soil samples ranged from 0.54 to 3.84% and 1.56 to 2.87% respectively for repeatability and reproducibility. The residues were below the detectable limit for all the insecticides at harvest time. The residues of fipronil were found to be more persistent than those of chlorantraniliprole and deltamethrin. Fipronil was found to persist up to the 7th day with a residue of 0.01 mg kg− 1. However, the residues of chlorantraniliprole and deltamethrin persisted upto the 5th day i.e. 0.11 mg kg− 1 and 0.03 mg kg− 1 respectively. Observation revealed that the residues of chlorantraniliprole on the cabbage head dissipated over the course of time and an equally high degree of dissipation was observed. The residues of fipronil were also found to be persistent in soil upto 7th day (0.01 mg kg− 1) as compared to chlorantraniliprole and deltamethrin residues.