bluuebunny/crossref_metadata_2025_split huggingface dataset:
Advancements in Rift Valley fever vaccines: a historical overview and prospects for next generation candidates
Authors: Alkan Cigdem , Jurado-Cobena Eduardo , Ikegami Tetsuro 
Published: November 2023

AbstractRift Valley fever (RVF) is a zoonotic viral disease transmitted by mosquitoes and causes abortion storms, fetal malformations, and newborn animal deaths in livestock ruminants. In humans, RVF can manifest as hemorrhagic fever, encephalitis, or retinitis. Outbreaks of RVF have been occurring in Africa since the early 20th century and continue to pose a threat to both humans and animals in various regions such as Africa, Madagascar, the Comoros, Saudi Arabia, and Yemen. The development of RVF vaccines is crucial in preventing mortality and morbidity and reducing the spread of the virus. While several veterinary vaccines have been licensed in endemic countries, there are currently no licensed RVF vaccines for human use. This review provides an overview of the existing RVF vaccines, as well as potential candidates for future studies on RVF vaccine development, including next-generation vaccines that show promise in combating the disease in both humans and animals.
An Open Science MRI Database of over 100 Synaesthetic Brains and Accompanying Deep Phenotypic Information
Authors: Racey Chris , Kampoureli Christina , Bowen-Hill Oscar , Bauer Mathilde , Simpson Ivor , Rae Charlotte , del Rio Magda , Simner Julia , Ward Jamie 
Published: November 2023

AbstractWe provide a neuroimaging database consisting of 102 synaesthetic brains using state-of-the-art 3 T MRI protocols from the Human Connectome Project (HCP) which is freely available to researchers. This database consists of structural (T1- and T2-weighted) images together with approximately 24 minutes of resting state data per participant. These protocols are designed to be inter-operable and reproducible so that others can add to the dataset or directly compare it against other normative or special samples. In addition, we provide a ‘deep phenotype’ of our sample which includes detailed information about each participant’s synaesthesia together with associated clinical and cognitive measures. This behavioural dataset, which also includes data from (N = 109) non-synaesthetes, is of importance in its own right and is openly available.
Mapping annual 10-m maize cropland changes in China during 2017–2021
Authors: Li Xingang , Qu Ying , Geng Hao , Xin Qi , Huang Jianxi , Peng Shuwen , Zhang Liqiang 
Published: November 2023

AbstractChina contributed nearly one-fifth of the world maize production over the past few years. Mapping the distributions of maize cropland in China is crucial to ensure global food security. Nonetheless, 10 m maize cropland maps in China are still unavailable, restricting the promotion of sustainable agriculture. In this paper, we collect numerous samples to produce annual 10-m maize cropland maps in China from 2017 to 2021 with a machine learning based classification framework. To overcome the temporal variations of plants, the proposed framework takes Sentinel-2 sequence images as input and utilizes deep neural networks and random forest as classifiers to map maize in a zone-specific way. The generated maps have an overall accuracy (OA) spanning from 0.87 to 0.95 and the maize-cultivated areas estimated by the maps are highly consistent with the records in statistical yearbooks (R2 varying from 0.83 to 0.95). To the best of our knowledge, this is the first annual 10-m maize maps across China, which largely facilitates the sustainable agriculture development in China dominated by smallholder farmlands.
MAPK signaling pathway-based glioma subtypes, machine-learning risk model, and key hub proteins identification
Authors: Liu Hengrui , Tang Tao 
Published: November 2023

AbstractAn early diagnosis and precise prognosis are critical for the treatment of glioma. The mitogen‑activated protein kinase (MAPK) signaling pathway potentially affects glioma, but the exploration of the clinical values of the pathway remains lacking. We accessed data from TCGA, GTEx, CGGA, etc. Up-regulated MAPK signaling pathway genes in glioma were identified and used to cluster the glioma subtypes using consensus clustering. The subtype differences in survival, cancer stemness, and the immune microenvironment were analyzed. A prognostic model was trained with the identified genes using the LASSO method and was validated with three external cohorts. The correlations between the risk model and cancer-associated signatures in cancer were analyzed. Key hub genes of the gene set were identified by hub gene analysis and survival analysis. 47% of the MAPK signaling pathway genes were overexpressed in glioma. Subtypes based on these genes were distinguished in survival, cancer stemness, and the immune microenvironment. A risk model was calculated with high confidence in the prediction of overall survival and was correlated with multiple cancer-associated signatures. 12 hub genes were identified and 8 of them were associated with survival. The MAPK signaling pathway was overexpressed in glioma with prognostic value.
Global and local meteoric water lines for δ17O/δ18O and the spatiotemporal distribution of Δ′17O in Earth’s precipitation
Authors: Terzer-Wassmuth Stefan , Araguás-Araguás Luis J. , Wassenaar Leonard I. , Stumpp Christine 
Published: November 2023

AbstractRecently, δ17O and its excess (Δ′17O) have become increasingly significant “triple-oxygen-isotope” indicators of distinctive hydrological processes in hydrology and climatology. This situation mirrors the research regarding δ18O and δ2H in the 1960s towards a solid theoretical base and a surge in application examples and field studies worldwide. Currently, systematic global measurements for δ17O in precipitation are still lacking. As a result, attempts have been made to define a Global δ17O/δ18O Meteoric Water Line (GMWL), often by using regional or local datasets of varying systematicity. Different definitions of the global reference slope (λref) for determining Δ′17O values have been proposed, by ongoing debate around a proposed consensus value of 0.528. This study used worldwide samples archived in the IAEA Global Network of Isotopes in Precipitation (GNIP) to (a) derive a δ17O/δ18O GMWL based on four-year monthly records from 66 GNIP stations, (b) formulate local δ17O/δ18O meteoric water lines (LMWL) for these stations’ areas, and (c) evaluate regional and seasonal variations of Δ′17O in precipitation. The GMWL for δ17O/δ18O was determined to be δ′17O = 0.5280 ± 0.0002 δ′18O + 0.0153 ± 0.0013, in keeping with the consensus value. Furthermore, our results suggested that using a line-conditioned 17O-excess is a viable alternative over the global λref in the context of regional hydrology and paleoclimatology interpretations; however, without challenging the global λref as such.
Comparative physiochemical and transcriptomic analysis reveals the influences of cross-pollination on ovary and fruit development in pummelo (Citrus maxima)
Authors: Wang Shaohua , Long Chunrui , Liu Hongming , Pan Li , Yang Shizao , Zhao Jun , Jiang Yan , Bei Xuejun 
Published: November 2023

Abstract‘Shuijingmiyou’ pummelo (SJ), one of the most popular fruits in Yunnan province of China, is of relatively low fruit shape (FS) quality. In this study, we compared the FS promoting effects of cross pollinations using pollens from seven pummelo varieties, and found that ‘Guanximiyou’ pummelo (GX) cross-pollination showed the best FS promoting effects on SJ fruits by shortening its fruit neck. To explore the underlying mechanism, physiochemical and transcriptomic differences between self- and cross-pollinated SJ ovaries (SJO and GXO) were investigated. Higher salicylic acid, gibberellin and indole acetic acid contents and superoxide dismutase, peroxidase and catalase activities, and lower polyphenol oxidase activity were determined in GXO compared with SJO. Enrichment analysis of the identified 578 differentially expressed genes (123 up-regulated and 455 down-regulated) in GXO showed that genes involved in solute transport, RNA biosynthesis, phytohormone action and cell wall organization were significantly enriched. The results obtained in this study will be helpful in understanding the influences of cross-pollination on pummelo ovary and fruit development, and can provide the basis for clarifying the underlying mechanism of cross-pollination improved fruit quality.
Adsorption and safe immobilization of Sr ions in modified zeolite matrices
Authors: Fayezi Mahya , Shiri-Yekta Zahra , Sepehrian Hamid , Heydari Mehran , Rahghoshay Mohammad , Zolghadri Samaneh 
Published: November 2023

AbstractIn the present study, an Iranian natural zeolite (Sabzevar region) was evaluated as a natural adsorbent for the elimination and immobilization of strontium ions from an aqueous solution. For improving the adsorption efficiency of strontium ion, the zeolite surface was modified by the Schiff base ligand of bis (2-hydroxybenzaldehyde)1,2-diaminoethane (H2L). The natural zeolite and zeolite/H2L were characterized using Fourier transform infrared spectroscopy (FT-IR), X-ray diffraction (XRD), X-ray fluorescence (XRF), BET and scanning electron microscope (SEM). Analysis of the natural zeolite showed that the zeolite is from the type of clinoptilolite and has a crystalline structure with the specific surface area 29.74 m2/g. The results showed that strontium adsorption onto modified zeolite increases compared to unmodified zeolite from 64.5% to 97.2% (at pH = 6). The effective parameters pH, adsorbent dosage, initial concentration of strontium ions, contact time, temperature, and interfering ions, were studied and optimized. The maximum adsorption efficiency was confirmed by modified zeolite and found to be 97.5% after 60 min of equilibrium time at pH 6, 0.05g as adsorbent dosage, and at 25 °C. Adsorption of strontium was confirmed by Langmuir model with maximum adsorption capacity of 10.31 mg/g. Kinetic studies showed that the adsorption of strontium ions on the adsorbent follows pseudo-second-order (PSO) model. Also, the thermodynamics of the adsorption process indicated that the adsorption of strontium on zeolite/H2L is an endothermic and spontaneous process, and the adsorption mechanism is a combination of physical and chemical adsorption. Finally, to manage the secondary waste generated from the adsorption process, strontium ions were immobilized in a zeolite structure. The results showed that the stabilization is well done with the thermal preparation process. After thermal treatment at 25–900 °C, modified zeolite satisfactorily retains strontium during back-exchange tests with NaCl solution. According to the results, the amount of strontium released from the adsorbent phase decreases from 52.6 to 1.6% with increasing heat treatment temperature.
Comparative transcriptome analysis of gene responses of salt-tolerant and salt-sensitive rice cultivars to salt stress
Authors: Fang Xin , Mo Junjie , Zhou Hongkai , Shen Xuefeng , Xie Yuling , Xu Jianghuan , Yang Shan 
Published: November 2023

AbstractSalt stress is one unfavorable factor of global climate change that adversely affects rice plant growth and yield. To identify novel salt-tolerant genes and new varieties of salt-tolerant rice, a better understanding of the molecular regulation mechanism of salt tolerance in rice is needed. In this study we used transcriptome analyses to examine changes in gene expression of salt-tolerant and salt-sensitive rice plants. The salt-tolerant cultivar HH11 and salt-sensitive cultivar IR29 were treated with 200 mM NaCl solution for 0 h, 6 h, 24 h and 48 h at the three leaf stage. Physiological parameters and transcriptome were measured and analyzed after each treatment. Activity of SOD and POD, as well as the MDA and protein content of the two rice cultivars generally increased with increasing time of exposure to NaCl. Meanwhile, the APX activity first increased, then decreased in both cultivars, with maximum values seen at 6 h for IR29 and at 24 h for HH11. The GR and GPX activity of HH11 were stronger than that of IR29 in response to salt stress. The H2O2 content first increased at 0–6 h, then decreased at 6–24 h, and then increased again at 24–48 h under salt stress. Compared with IR29, SOD, POD and APX activity of HH11 was more sluggish in response to salt stress, reaching the maximum at 24 h or 48 h. The MDA, H2O2 and proline content of HH11 was lower than that of IR29 under salt stress. Relative to untreated HH11 plants (0 h) and those exposed to salt for 6 h, 24 h, and 48 h (H0-H6, H0-H24 and H0-H48), 7462, 6363 and 6636, differentially expressed genes (DEGs), respectively, were identified. For IR29, the respective total DEGs were 7566, 6075 and 6136. GO and KEGG enrichment analysis showed that metabolic pathways related to antioxidative responses and osmotic balance played vital roles in salt stress tolerance. Sucrose and starch metabolism, in addition to flavonoid biosynthesis and glutathione metabolism, showed positive responses to salt stress. Expression of two SPS genes (LOC_Os01g69030 and LOC_Os08g20660) and two GST genes (LOC_Os06g12290 and LOC_Os10g38740) was up-regulated in both HH11 and IR29, whereas expression of LOC_Os09g12660, a glucose-1-phosphate adenylyltransferase gene, and two SS genes (LOC_Os04g17650 and LOC_Os04g24430) was up-regulated differential expression in HH11. The results showed that HH11 had more favorable adjustment in antioxidant and osmotic activity than IR29 upon exposure to salt stress, and highlighted candidate genes that could play roles in the function and regulation mechanism of salt tolerance in rice.
Applying self-powered sensor and support vector machine in load energy consumption modeling and prediction of relational database
Authors: Yang Dexian , Yu Jiong , He Zhenzhen , Li Ping , Du Xusheng 
Published: November 2023

AbstractThis study explores the analysis and modeling of energy consumption in the context of database workloads, aiming to develop an eco-friendly database management system (DBMS). It leverages vibration energy harvesting systems with self-sustaining wireless vibration sensors (WVSs) in combination with the least square support vector machine algorithm to establish an energy consumption model (ECM) for relational database workloads. Through experiments, the performance of self-sustaining WVS in providing power is validated, and the accuracy of the proposed ECM during the execution of Structured Query Language (SQL) statements is evaluated. The findings demonstrate that this approach can reliably predict the energy consumption of database workloads, with a maximum prediction error rate of 10% during SQL statement execution. Furthermore, the ECM developed for relational databases closely approximates actual energy consumption for query operations, with errors ranging from 1 to 4%. In most cases, the predictions are conservative, falling below the actual values. This finding underscores the high predictive accuracy of the ECM in anticipating relational database workloads and their associated energy consumption. Additionally, this paper delves into prediction accuracy under different types of operations and reveals that ECM excels in single-block read operations, outperforming multi-block read operations. ECM exhibits substantial accuracy in predicting energy consumption for SQL statements in sequential and random read modes, especially in specialized database management system environments, where the error rate for the sequential read model is lower. In comparison to alternative models, the proposed ECM offers superior precision. Furthermore, a noticeable correlation between model error and the volume of data processed by SQL statements is observed. In summary, the relational database ECM introduced in this paper provides accurate predictions of workload and database energy consumption, offering a theoretical foundation and practical guidance for the development of eco-friendly DBMS.
eRNA co-expression network uncovers TF dependency and convergent cooperativity
Authors: Lee Seungha Alisa , Kristjánsdóttir Katla , Kwak Hojoong 
Published: November 2023

AbstractEnhancer RNAs (eRNAs) are non-coding RNAs produced by transcriptional enhancers that are highly correlated with their activity. Using a capped nascent RNA sequencing (PRO-cap) dataset in human lymphoblastoid cell lines across 67 individuals, we identified inter-individual variation in the expression of over 80 thousand transcribed transcriptional regulatory elements (tTREs), in both enhancers and promoters. Co-expression analysis of eRNAs from tTREs across individuals revealed how enhancers are associated with each other and with promoters. Mid- to long-range co-expression showed a distance-dependent decay that was modified by TF occupancy. In particular, we found a class of “bivalent” TFs, including Cohesin, that both facilitate and isolate the interaction between enhancers and/or promoters, depending on their topology. At short distances, we observed strand-specific correlations between nearby eRNAs in both convergent and divergent orientations. Our results support a cooperative model of convergent eRNAs, consistent with eRNAs facilitating adjacent enhancers rather than interfering with each other. Therefore, our approach to infer functional interactions from co-expression analyses provided novel insights into the principles of enhancer interactions as a function of distance, orientation, and binding landscapes of TFs.
The urinary RNA atlas of patients with chronic kidney disease
Authors: Lv Li-Zhi 
Published: November 2023

AbstractChronic kidney disease (CKD) represents a significant global health burden. Currently employed CKD biomarkers are influenced by various factors and lack accuracy in reflecting early-stage renal fibrosis severity. Consequently, there is an urgent need for the identification of early, noninvasive CKD biomarkers. Urine, easily collectible and kidney-derived, has demonstrated potential as a diagnostic source for various kidney diseases by leveraging its RNA content. To address this, we obtained RNA-seq data pertaining to urinary RNAs from both CKD patients and healthy controls via the Gene Expression Omnibus database (GEO). The DEseq2 software was utilized to identify differentially expressed RNAs (DE-RNAs). To evaluate the overall accuracy of these DE-RNAs in urine, we performed Receiver Operating Characteristic analysis (ROC). Selected urinary RNAs were subsequently validated using reverse-transcription quantitative real-time Polymerase Chain Reaction (qRT-PCR) in conjunction with ROC analysis. Computational and experimental analyses revealed significant increases in miR-542-5p, miR-33b-5p, miR-190a-3p, miR-507, and CSAG4 within the urine of CKD patients, exhibiting high AUC values. In conclusion, our findings suggest that urinary RNAs hold promise as diagnostic biomarkers for CKD.
Data-driven prediction of the equivalent sand-grain roughness
Authors: Ma Haoran , Li Yuhao , Yang Xin , Ye Lili 
Published: November 2023

AbstractSurface roughness affects the near-wall fluid velocity profile and surface drag, and is commonly quantified by the equivalent sand-grain roughness $${k}_{s}$$

k
s

. It is essential to estimate $${k}_{s}$$

k
s

for accurate fluid dynamic problem modeling. While numerous roughness correlation formulas have been proposed to predict $${k}_{s}$$

k
s

in the fully rough regime, most of them are restricted to certain roughness types, with various geometric parameters considered in each case, leading to ongoing disagreements regarding its parameterization and lack of universality. In this study, a Particle Swarm Optimized Backpropagation (PSO-BP) method is proposed to predict $${k}_{s}$$

k
s

based on the selected surface parameters from previous DNS, LES, and experimental results for flow behavior over various surface roughness. The PSO-BP model’s ability to predict $${k}_{s}$$

k
s

in the fully rough region is evaluated and compared with both the existing roughness correction formulas as well as the traditional BP model. An optimized polynomial function is also proposed to serve as a ‘white box’ for predicting $${k}_{s}$$

k
s

. It turns out that the PSO-BP method has better performance in the evaluation metrics compared to other methods, yielding a Mean Absolute Error (MAE) of 0.0390, a Mean Squared Error (MSE) of 0.0026 and a Mean Absolute Percentage Error (MAPE) of 28.12%. This novel approach for estimating $${k}_{s}$$

k
s

has practical applicability and holds promise for improving the precision and efficiency of calculations related to equivalent sand-grain roughness, and thus provides more accurate and effective solutions for CFD and other engineering applications.
Evaluation of industrial ecology in the π-shaped curve area of China’s Yellow River based on the grey Lotka–Volterra model
Authors: Sun Yifang 
Published: November 2023

AbstractIndustrial ecology (IE) is the process of constructing industrial-ecological systems (IES) with the realization of the mutual benefits for industrial system (IS) and ecological system (ES). Therefore, the IE level depends on the IES development and the relationship between IS and ES. This paper calculated the development index of ES and IS to account for IES development and adopted the grey Lotka–Volterra to analyze the relationship between IS and ES. Choosing the π-shaped curve area in the Yellow River basin of China as the study area, this paper analyzed its IE level and influence factors from 2005 to 2019. Findings include: (1) The development level of IES in the Area presented significant spatial differentiation and could be classified into three levels. (2) IS and ES remained in the stage of isolated development or mutual restriction. (3) IE was found to be positively correlated with scientific innovation, economic development, openness degree, pollution control, and industrial structure while negatively correlated with urbanization, resource consumption, and government influence.
Recent changes in the climatological characteristics of daily contiguous rain areas over India
Authors: Bhowmick Mansi , Sahany Sandeep , Das Ananda Kumar 
Published: November 2023

AbstractThis study documents the climatological feature (1951–1980) and recent changes (1981–2020) in rainfall characteristics considering the observed nearly full spectrum of rain event sizes (daily contiguous rain area (CRA) events) in all seasons over India. It is found that the low frequency very large CRA (~synoptic scale) from monsoon season contributes ~50% of annual rainfall. However, the small-sized CRA (isolated thunderstorms) are the most frequent daily rain events (~70% of annual frequency) and hence are important for rain-fed agricultural practices. The well-documented widespread drying trend in the monsoon season has manifested in the annual rainfall trend but with reduced magnitude illustrating the compensatory effect from other seasons. Spatial aggregated annual statistics show that there is no significant change in rainfall amount and frequency of occurrence of rain events in the recent past compared to the base period. However, seasonally the pre-monsoon rainfall amount has increased significantly. Annually, the number of extremely heavy CRA (EHR) events have significantly increased by ~55% owing to a significant increase in pre-monsoon and monsoon rainfall. In all seasons, small-sized extremely heavy CRA has intensified substantially by 50–200% as compared to the base period. Additionally, the rain events from areal category large (~Mesoscale Convective Complexes (MCC)) have intensified in all seasons except winter. Thus, to decrease the uncertainty in rain-fed agricultural practices and better prediction of EHR to develop effective climate change mitigation strategies; process studies beyond monsoon season and processes other than synoptic scales are also required.