bluuebunny/crossref_metadata_2025_split huggingface dataset:
Assessment of the WRF model in reproducing a flash-flood heavy rainfall event over Kosovo
Authors: Osmanaj Lavdim , Spiridonov Irena , Jakimovski Boro , Spiridonov Vlado 
Published: March 2024

Abstract
This research investigates the efficacy of the cloud-resolving Weather Research and Forecasting (WRF) model in reproducing convective cells associated with flash-flooding heavy rainfall near Peja, Northeast Kosovo, on June 24, 2023. Employing two distinct dynamical cores and a unique numerical setup for the Kosovo domain, numerical experiments were conducted. The study employed a triply nested WRF-ARW model with a high resolution of 3 km horizontal grid spacing, integrating conventional analysis data. Additionally, experiments using the WRF-NMM core with 3 km for a larger domain covering Southeast Europe and Kosovo domain were executed to simulate the specific event. The WRF model accurately simulated the initiation of isolated thunderstorms, convective band formation, cloud cluster, and squall line at the opportune time. While precipitation distribution was reasonably replicated, there was a slight underestimation in the amount. Hydrological analysis of precipitation, including river discharge rates provided from ECMWF ERA5 reanalysis, identified a unique storm category with intense precipitation production, registering an intensity of approximately 54.6 mm in one hour, leading to sudden flash flooding.
Development of Optimal L-PBF Process Parameters using an Accelerated Discrete Element Simulation Framework
Authors: Aarab Marwan , Dorussen Bram J.A. , Poelsma Sandra S. , Remmers Joris J.C. 
Published: March 2024

Abstract
Laser Powder Bed Fusion (L-PBF) has immense potential for the production of complex, lightweight, and high-performance components. Optimizing process parameters both for existing and new materials is crucial for maximizing the capabilities of the technique. Traditionally process parameter optimization involves a large amount of experimentation, which makes it a costly and time-consuming endeavor. An elegant improvement upon this is leveraging numerical simulations to find optimal process parameters. Current research mostly focuses on modeling single-line scans, most likely to maintain computational efficiency. Unfortunately, optimization of process parameters using this single-line geometry will lead to process parameter sets optimized for thin walls rather than bulk material.
In this work, we present a novel approach to optimizing bulk process parameters. The approach utilizes a discrete element simulation, with a ray tracing-modelled laser heat source, which significantly reduces the cost and time consumption in contrast to conventional optimization methods. The simulation is sped up by using GPU acceleration, enabling efficient simulation of multiple fully scanned layers. This will result in process parameters optimized for the bulk material rather than thin walls.
The practical use of the optimization method is demonstrated in a case study where optimal process parameters are developed for AlSi10Mg. The optimization entails just 5 days of computation time, which would have been at least 8 months without the GPU acceleration. Through experimental validation, it was found that the numerically optimized process parameters were indeed the highest quality, with an optical density of 99.91%.
Investigation on Low-Iodine Diet Implementation of Medical Staffs before 131I Therapy for Differentiated Thyroid Carcinoma
Authors: YI Yupin , HU Fengqiong , ZHU Yuquan , WU Youfeng 
Published: March 2024

Abstract
Objective: To explore the implementation of low-iodine diets among medical staff caring for patients with differentiated thyroid carcinoma prior to 131I therapy across 58 hospitals, and offer valuable insights for the development of guidelines on low-iodine diets.
Methods: Convenience sampling was utilized to conduct a survey among 163 medical staff members working in nuclear medicine departments across 58 tertiary hospitals using a self-designed questionnaire.
Results: Concerning the duration of the low-iodine diet prior to treatment, the medical staff's recommendations were as follows: 58.28% suggested 2–4 weeks, 31.29% recommended more than 4 weeks, 9.2% opted for 7–13 days, and 1.23% favored less than 1 week. Regarding the timing of resuming a normal diet, the respondents' recommendations ranged from immediately after treatment (1.84%) to 3 months post-treatment (8.58%), with intermediate recommendations of 2 hours (8.58%), 24–48 hours (14.11%), post-discharge (12.26%), and 1 month (42.94%).Furthermore, the surveyed medical staff unanimously recommended abstaining from seafood, with 90.8% also advising against the consumption of iodized salt, 91.41% recommending avoidance of iodine-containing medications, and 71.17% advising caution with moderately high-iodine foods. Notably, 75.46% of the medical staff evaluated patient compliance with the low-iodine diet. When patients failed to adhere to the diet preparation, 33.74% of healthcare workers chose to proceed with treatment. In terms of guidance sources, 96.93% of respondents relied on relevant guidelines, 66.26% referred to the literature, and 49.69% drew upon their clinical experience. During hospitalization, 58.28% of the medical staff continued to guide patients on the low-iodine diet, while only 8.59% provided such guidance after discharge. Notably, only 20.25% of the staff considered consulting the nutrition department.
Discussion: This study underscored substantial variations in the duration and selection criteria for low-iodine diets, which were linked to a scarcity of standardized evaluations. Consequently, there is an urgent need for further research to establish detailed, practical, accessible, comprehensive, and dependable implementation programs for low-iodine diets.
Eco-Friendly Synthesis of Mesoporous Silica Nanoparticles from Banana Peel Waste: A Comprehensive Study on Sustainable Waste Utilization and Advanced Material Development
Authors: M MONICA , J Irine , R Jayasree 
Published: March 2024

Abstract
The growing challenge of solid waste in various industries underscores the need for sustainable environmental solutions. This study focused on converting banana peel waste, a byproduct from the global banana industry, into valuable mesoporous silica nanoparticles (MSNs) through an eco-friendly approach. Musaceae peels, which are rich in nutrients and are abundant in Tamil Nadu, India, are often overlooked. In response to the demand for sustainable waste management, this study explored the transformation of Musaceae peel ash into silica using the sol-gel method. The synthesis process involves preparing Musaceae peel ash, extracting silica with a sodium silicate solution, and subsequent gelation, drying, and purification steps to obtain amorphous silica powder. Characterization analyses, including scanning electron microscopy (SEM), Fourier transform infrared (FTIR) spectroscopy and energy dispersive X-ray (EDX) spectroscopy, confirmed the successful synthesis of the mesoporous silica nanoparticles. EDX confirmed the elemental composition, FTIR revealed chemical groups on the nanoparticle surface, and SEM images showed a uniform particle morphology, indicating a well-crystallized nature and optimized adsorption capabilities. This eco-friendly approach not only addresses environmental challenges in waste disposal but also contributes to developing mesoporous silica nanoparticles from a biosource, with potential applications in various advanced fields. This study aimed to promote sustainable waste utilization and explore eco-conscious materials for diverse applications.
ZnO NPs Enhanced Photosynthetic Capacity, Promoted New Shoot Development, and Improved the Community Composition of Phyllosphere Epiphytic and Endophytic Microorganisms in Tea Plants
Authors: Chen Hao , Song Yujie , Wang Yu , Wang Huan , Ding Zhaotang , Fan Kai 
Published: March 2024

Abstract
Background
Nanotechnology holds revolutionary potential in the field of agriculture, with zinc oxide nanoparticles (ZnO NPs) demonstrating advantages in promoting crop growth. Photosynthesis is a key process in the growth and quality formation of tea plants, and phyllosphere microorganisms also have a significant impact on plant growth and health. However, the effects of ZnO NPs on the photosynthesis of tea plants, the sprouting of new shoots, and the community of phyllosphere microorganisms are not yet clear.
Results
This study investigated the photosynthetic physiological parameters of tea plants under the influence of ZnO NPs, the content of key photosynthetic enzymes such as RubisCO, chlorophyll content, chlorophyll fluorescence parameters, transcriptomes (leaves and new shoots), extensively targeted metabolomes (leaves and new shoots), mineral element content (leaves and new shoots), and the communities of epiphytic and endophytic microorganisms in the phyllosphere. The results indicated that ZnO NPs could enhance the photosynthesis of tea plants, upregulate the expression of some genes related to photosynthesis, increase the accumulation of photosynthetic products, promote the development of new shoots, and alter the content of various mineral elements in the leaves and new shoots of tea plants. Additionally, ZnO NPs improved the community composition of epiphytic and endophytic microorganisms in the phyllosphere of tea plants, inhibited potential pathogenic microorganisms, and allowed various beneficial microorganisms with potential growth-promoting properties to become dominant species.
Conclusion
This study demonstrates that ZnO NPs have a positive impact on the photosynthesis of tea plants, the sprouting of new shoots, and the community of phyllosphere microorganisms, which can improve the growth condition of tea plants. These findings provide new scientific evidence for the application of ZnO NPs in sustainable agricultural development and contribute to advancing research in nanobiotechnology aimed at enhancing crop yield and quality.
Effects of Three Exogenous Selenium on Rice Morphology, Photosynthesis, Antioxidant Enzyme System, and Identification of Selenium-Related Genes
Authors: Wu Wenjiang , Qi Deqiang , Chen Yalong , Wang Jiaqi , Zhao Wei , Niu Hongbin , Peng Ting , Zhao Quanzhi 
Published: March 2024

Abstract
Background: Selenium (Se) is an essential trace element that has various beneficial effects for human healthy. However, the effects of different selenium sources, treatment methods and concentrations on growth and development, photosynthetic characteristics and antioxidant capacity are still unclear in rice.
Results: In this study, three concentrations of three different selenium sources were performed in rice using two treatment methods, respectively. The results showed that selenium treatment can increase the plant height, the 1000 grain weight, the Se content of rice grain, and increased the organic selenium content of rice grain, especially. All the selenium treatments improved the photosynthetic indexes including net photosynthetic rate, transpiration rate, and stomatal conductance, decreased inter-cellular CO2 concentration. The activities of catalase (CAT), peroxidase (POD), superoxide dismutase (SOD), and glutathione reductase (GR), as well as the content of GSSG (Glutathione oxidized) were increased at different levels after Se treatments, while GSH (Glutathione) decreased. Totally, 32 DEGs related to selenium absorption/endocytosis (including six heat shock 70 kDa protein, one ACD), transport (including four ABC transporters, one SULTR, one LAST, one Inorganic phosphate transporter, one GlpT, one PHO, one PPT) and metabolism (including NAS1, NAS2, APS5, 3MST2, PPCS1, SAMDC and 8 protein kinases), 6 DEGs related to glutathione metabolic pathway (including one G6PD, four GSTs and one GSS), 69 transcription factors (including 19 AP2/ERF-ERFs, 9 MYBs, 9 WRKYs, 8 HSFs, 6 bHLHs, 5 GRASs, 4 NACs,3 B3-ARFs, 3 C2H2s and 3 bZIPs) were identified by RNA-Seq.
Conclusion: Our study indicated that exogenous selenium treatments could increase the 1000 grain weight, the Se content and the organic selenium content of rice grain by improving photosynthetic traits and antioxidant enzyme activities, especially sodium selenite. The expressions of the genes related to selenium metabolism indicated that foliar spraying can faster induce the response of Se treatment in rice than root irrigation. The results will provide an insight into the selenium enrichment of rice.
Protein-losing enteropathy as a new phenotype in atypical hemolytic uremic syndrome caused by CD46 gene mutation and recovery from chronic kidney failure by eculizumab treatment
Authors: Wang Chunyan , Chen Jing , Han Xinli , Sun Manqing , Fang Xiaoyan , Zhai Yihui , Miao Qianfan , Zhang Zhiqing , Tang Xiaoshan , Liu Jiaojiao , Dai Rufeng , Shen Qian , Xu Hong 
Published: March 2024

Abstract

Background: Atypical hemolytic uremic syndrome (aHUS) is a life-threatening thrombotic microangiopathies. Genetic defects in complement alternative pathway have been identified in 60-70% of aHUS individuals. Eculizumab is recommended as first-line therapy.
Methods: We collected clinical data of a pediatric aHUS case, who accompanied with protein-losing enteropathy (PLE). Genetic testing was performed. Related literatures of aHUS combined with PLE were reviewed.
Results: A 15-year-old Chinese girl was diagnosed with aHUS at 3.7-year- old, and suffered with five episodes, she showed completely resolved with plasma treatment. Severe gastrointestinal symptoms and hypoalbuminemia presented after first episode and protein-losing enteropathy (PLE) was diagnosed. A novel homozygous CD46 variant was identified and FACS showed significantly decreased CD46 expression. She presented a recent relapse with persistent GI symptoms and headache, and progressed to chronic kidney failure, peritoneal dialysis was initiated. Eculizumab was given after 8 months of last recurrence. Surprisingly, PLE was cured, Afterwards, dialysis could be discontinued, eGFR recovered to 44.8ml/min/1.73㎡.
Review of literatures indicated PLE with thrombosis was caused by CD55 variants with a mechanism of hyperactivation of complement system. We firstly reported an aHUS case with PLE caused by CD46 variants, both symptoms of PLE and aHUS improved significantly in our case and cases reported with CD55 variants treated with eculizumab, which indicates PLE as a new symptom of aHUS in our case with CD46 variants.
Conclusions: Our case expands phenotype of aHUS caused by CD46 mutation, and provide evidence of efficiency of eculizumab after a long chronic kidney failure phase.
Effect of MnSO4 concentration on the electrochemical performance of β-MnO2/3D graphene-carbon nanotube hybrids cathode for aqueous zinc-ion batteries
Authors: Jin Duolong , Dong Xiaoping , Xin Shenghai , Yang Liying , Liu Jiankai , Pang Qianran 
Published: March 2024

Abstract

Manganese-based cathode material has a wide range of applications in aqueous zinc-ion batteries, but its structural stability is poor. We can improve the microstructure of manganese-based cathode materials by simple mechanical ball milling methods, thus increasing the discharge capacity of batteries. However, the capacity of manganese-based cathode material batteries decreases rapidly during cycling, which is caused by the dissolution of manganese-based materials in the electrolyte. To ameliorate this problem, in this work, MnSO4 is pre-added to the ZnSO4 electrolyte, which can effectively inhibit the dissolution of the manganese-based material and maintain the conversion reaction inside the battery, providing better cycle life and higher discharge capacity. In addition, with the increase of MnSO4 additive concentration in a certain range, the discharge capacity and cycle life of the batteries were improved (the battery pre-added with 0.5 M MnSO4 solution had the highest reversible specific capacity of up to 521.91 mAh·g-1 at a current density of 100 mA·g-1 and 109.12 mAh·g-1 even at 1 A·g-1, the capacity retention rate remained at 83.8% after cycling for more than 8000 cycles), which provides an idea for the electrolyte regulation of aqueous zinc-ion batteries.
Global Dissipative Examination of Delayed Memristive Inertial Neural Networks with Uncertain Parameters
Authors: S Premalatha , M Shanmugapriya M , P Indumathi , S Santhosh Kumar 
Published: March 2024

Abstract
The present article addresses the discussion of dissipative examination of Dynamic Systems, namely Inertial Neural Networks with memristor, parameter uncertainity and delays such as time-varying, distributed. A suitable variable substitution is implemented to convert the inertial system to the first order differential system. Exploiting the concept of matrix measure and properties to the Lyapunov function, a sufficient criteria for dissipative of the dynamical system is achieved through a generalized Halanay Inequality. Concurrently, the globally attractive sets are extracted from the network system with bound. The derived results are new-fangled concerning the dynamical systems with the complex- the inertial and memristor term along with the mixed delays and parameter uncertainties. At the end, the numerical simulations are presented for the better clarification and testimonial of obtained dissipative criteria with pictorial representation.
BERT-BiLSTM-Attention model for sentiment analysis on Chinese stock reviews
Authors: Li Xiaoyan , Chen Lei , Chen Baoguo , Ge Xianlei 
Published: March 2024

Abstract
COVID-19 has produced significant fluctuations and impacts on the Chinese stock market, and the sentiment analysis of stock reviews is important for the study of economic recovery. Due to the lack of a large amount of labeled data in the existing Chinese stock review data, and the currently popular Bert model mostly failed to consider contextual information according to different contextual backgrounds when extracting features, resulting in the lack of contextual information in the modeled features. To address the above problems, this paper proposes an innovative Chinese stock review sentiment analysis model BERT-BiLSTM-Attention, which encodes the stock review text by BERT to enhance the semantic feature representation of the text, BiLSTM is then utilized to enhance the contextual information of the overall context of the review as well as the model’s comprehension of the text sequences, and then Attention mechanism is utilized to obtain important textual information and get the most effective information quickly. Experiments show that the model is effective in sentiment analysis of Chinese stock reviews, with an accuracy of 93.98%, It can be proved that the proposed model well enhances the performance of stock review text classification, and has a strong generalization ability, which can be used for sentiment analysis in many fields.
Stable Training of Normalizing Flows for High-dimensional Variational Inference
Authors: Andrade Daniel 
Published: March 2024

Abstract
Variational inference with normalizing flows (NFs) is an increasingly popular alternative to MCMC methods. In particular, NFs based on coupling layers (Real NVPs) are frequently used due to their good empirical performance. In theory, increasing the depth of normalizing flows should lead to more accurate posterior approximations. However, in practice, training deep normalizing flows for approximating high-dimensional posterior distributions is often infeasible due to the high variance of the stochastic gradients. In this work, we show that previous methods for stabilizing the variance of stochastic gradient descent can be insufficient to achieve stable training of Real NVPs. As the source of the problem, we identify that, during training, samples often exhibit unusual high values. As a remedy, we propose a combination of two methods: (1) soft-thresholding of the scale in Real NVPs, and (2) a bijective soft log transformation of the samples. We evaluate these and other previously proposed modification on several challenging target distributions, including a high-dimensional horseshoe logistic regression model. Our experiments show that with our modifications, stable training of Real NVPs for posteriors with several thousand dimensions is possible, allowing for more accurate marginal likelihood estimation via importance sampling. Moreover, we evaluate several common training techniques and architecture choices and provide practical advise for training NFs for high-dimensional variational inference.
Can Relative Abundance of Diatoms (RAD) Serve as an Indicator for the Water Quality Assessment in River-Connected Lakes? A Case Study at Dongting Lake
Authors: Yan Guanghan , Yin Xueyan , Wang Xing , Huang Mingsheng 
Published: March 2024

Abstract
Abstrat: In this study, 15 sampling sites were set up in Dongting Lake, a typical river-connected lake in China, to investigate water quality and phytoplankton in March, June, September and December from year 2017 to 2022. Seven diatom indices, including relative abundance of diatoms (RAD), percentage motile diatoms (PMD), generic diatom index (GDI), diatom quotient (DU), pollution tolerance index for diatoms (PTI), trophic diatom index (TDI), and Pampean diatom index (IDP), were selected to screen the adaptability of water quality assessment comparing with the Nemero index (NI). The monitoring results from 2017 to 2019 showed that the diatom density in Dongting Lake ranged from 0.7×104 to 85.5×104 ind./L, with a certain decreasing trend. The spatial and temporal changes of major water quality factors were obvious, and the ∑TLI ranged from 45.99 to 50.72, with an average value of 47.85, indicating that the overall condition of Dongting Lake was medium nutrition. Correlation analysis showed that PTI, Rad and PMD could represent the information of DU, GDI, TDI and IDP, and were significantly positively correlated with DO (p<0.01), while significantly negatively correlated with Cond, CODMn, BOD5, CODCr and ∑TLI (p<0.001). The index verification results from year 2020 to 2022 showed that PTI, RAD and PMD were all significantly positively correlated with P (p<0.001). Taking into account the data integrity of the index calculation (PMD would appear the phenomenon of zero value) and the difficulty degree (PTI index needs to calculate the tolerance value of diatoms to external stress), RAD was finally selected as the biological indicator for evaluating the water quality of Dongting Lake. The results of this study provide a new path or alternative method for water quality assessment of the river-connected lakes.