bluuebunny/crossref_metadata_2025_split huggingface dataset:
Improved Exponential Type Ratio Estimator in Double Sampling for Stratification
Authors: Gupta Anurag , Tailor Rajesh , Barod Nitu 
Published: September 2023

Abstract
The objective of this research is to develop a chain-ratio-type exponential estimator in order to estimate the finite population mean in double sampling for stratification. An estimator for population mean has been constructed based on the concept of chain-ratio estimators given by Chand (1975). The constructed estimator is compared to the standard unbiased estimator, as well as the estimators of Ige and Tripathi (1987) and Tailor et al. (2014), and conditions are shown to yield better results in terms of efficiency. To support the theoretical results the study has been done on both natural as well as simulated populations.
AMS Subject Classification: 62DO5
Trichoderma viride based seed biopriming strategies for quality seedling production in East Indian Sandalwood
Authors: Satheesan Anjali , CM Jijeesh , TK Kunhamu , AV Santhoshkumar , V Jamaludheen , Settu Krishnamoorthi , Athikkayi Arshad , Nageri Fasilkhan 
Published: September 2023

Abstract

Seed biopriming is one of the cheapest, eco-friendly, and proven seed enhancement techniques to obtain better germination and seedling performance in many crops. Sandal (Santalum album L) seeds, in general, have poor and staggered germination which leads to difficulty in nursery management. In this study, the impact of plant growth-promoting fungi Trichoderma viride on the germination and seedling growth of sandal was studied. Fresh mature sandal seeds were procured from the Nachivayal Reserve Forest, Marayur Sandal Division, Kerala, India. The experiment was conducted in two factorial CRD with concentrations of T. viride (25, 50, 75 and 100%) and duration of treatment (1, 2, 3, 4, 6 and 8 days) as factors. The effect of post priming storage (periods one day and one week) was also studied. The application of T. viride improved the germination and seedlings performance of S. album. The highest germination was obtained on biopriming at 100% concentration for 3 days (82.72%) for one week, followed by 100% concentration for 1 day (73.3%) for storage of one day. Post priming storage studies indicated that the storage of bioprimed seeds (100% for 3 days) for one week recorded better seedling growth. Hence, we recommend the biopriming of sandal seeds with T. virideat 100% for 3 days stored for one week for the quality seedling production of sandal in the nursery.
Automatic quantification of TSR as a prognostic marker for pancreatic cancer.
Authors: Vendittelli Pierpaolo , Bokhorst John-Melle , Smeets Esther , Kryklyva Valentyna , Brosens Lodewijk , Verbeke Caroline , Litjens Geert 
Published: September 2023

Abstract
Purpose
This study aims to introduce an innovative multi-step pipeline for automatic tumorstroma ratio (TSR) quantification as a potential prognostic marker for pancreatic cancer, addressing the limitations of existing staging systems and the lack of commonly used prognostic biomarkers.
Methods
The proposed approach involves a deep-learning-based method for the automatic segmentation of tumor epithelial cells, tumor bulk, and stroma from whole-slide images (WSIs). Models were trained using five-fold cross-validation and evaluated on an independent external test set. TSR was computed based on the segmented components. Additionally, TSR’s predictive value for six-month survival on the independent external dataset was assessed.
Results
Median Dice (inter-quartile range (IQR)) of 0.751(0.15) and 0.726(0.25) for tumor epithelium segmentation on internal and external test sets, respectively. Median Dice of 0.76(0.11) and 0.863(0.17) for tumor bulk segmentation on internal and external test sets, respectively. TSR was evaluated as an independent prognostic marker, demonstrating a cross-validation AUC of 0.61 ± 0.12 for predicting six-month survival on the external dataset.
Conclusion
Our pipeline for automatic TSR quantification offers promising potential as a prognostic marker for pancreatic cancer. The results underscore the feasibility of computational biomarker discovery in enhancing patient outcome prediction, thus contributing to personalized patient management.
Technical optimization of spatially resolved single-cell transcriptomic datasets to study clinical liver disease.
Authors: Rocque Brittany , Guion Kate , Singh Pranay , Bangerth Sarah , Pickard Lauren , Bhattacharjee Jashdeep , Eguizabal Sofia , Weaver Carly , Chopra Shefali , Zhou Shengmei , Kohli Rohit , Sher Linda , Ekser Burcin , Emamaullee Juliet A. 
Published: September 2023

Abstract
Single cell and spatially resolved ‘omic’ techniques have enabled deep characterization of clinical pathologies that remain poorly understood, providing unprecedented insights into molecular mechanisms of disease. However, transcriptomic platforms are costly, limiting sample size, which increases the possibility of pre-analytical variables such as tissue processing and storage procedures impacting RNA quality and downstream analyses. Furthermore, spatial transcriptomics have not yet reached single cell resolution, leading to the development of multiple deconvolution methods to predict individual cell types within each transcriptome ‘spot’ on tissue sections. In this study, we performed spatial transcriptomics and single nucleus RNA sequencing (snRNASeq) on matched specimens from patients with either histologically normal or advanced fibrosis to establish important aspects of tissue handling, data processing, and downstream analyses of biobanked liver samples. We observed that tissue preservation technique impacts transcriptomic data, especially in fibrotic liver. Deconvolution of the spatial transcriptome using paired snRNASeq data generated a spatially resolved, single cell dataset with 24 unique liver cell phenotypes. We determined that cell-cell interactions predicted using ligand-receptor analysis of snRNASeq data poorly correlated with celullar relationships identified using spatial transcriptomics. Our study provides a framework for generating spatially resolved, single cell datasets to study gene expression and cell-cell interactions in biobanked clinical samples with advanced liver disease.
“We and malaria are already friends, becoming one,” A qualitative study on malaria risk perception in Eastern Indonesia
Authors: Ayuandini S. , Tobing F. , Jupp D. , Halim D.F , Kenangalem E. , Sumiwi Maria Endang , Prameswari Helen Dewi , Theodora Minerva , Dewi Riskha Tiara Puspa , Supriyanto Dedy , Kurnia Bayu , Shetye Mrunal , Ndoen Ermi , Onishi Yuka 
Published: September 2023

Abstract
Background
Despite the Government of Indonesia’s success in eliminating malaria in 372 out of 514 districts in 2022, the disease is still highly prevalent in Eastern Indonesia. In 2021, 95% of the total malaria cases in Indonesia were reported from Papua, West Papua and Nusa Tenggara Timur (NTT) provinces. In the context of the persistence of malaria in these areas, there is an increased recognition that malaria elimination will require an understanding of the social determinants of malaria prevention and treatment, informed by local context and local practice.
Methods
This study is based on qualitative data collected through participatory community assessment and participatory barrier analysis implemented through an adapted immersion approach. For the adapted immersion, researchers immersed themselves in the communities during the day and early evening over a period of 5 days. Researchers gathered insights through informal conversations, discussions using visual tools, and direct observation. The study was conducted in 4 districts of high endemic areas across Papua, West Papua, and Sumba Islands in NTT.
Results
The study highlights how people’s perception of the disease in high malaria endemic areas affects their health behaviors in dealing with malaria infection, particularly in their decision making for early testing, adherence to malaria treatment, and practices taken to prevent mosquito bites.
Conclusions
People in high-endemic areas of Eastern Indonesia perceived malaria as inseparable from their daily lives and with little link to mosquitos. These views underpinned behaviors that hindered the effectiveness of malaria programs, including delays in malaria testing, low adherence to malaria treatment, and inconsistent practices to prevent mosquito bites or control mosquitos. The effectiveness of public health interventions that aim to eliminate malaria in Eastern Indonesia may be improved by addressing these behaviors and underlying beliefs.
Research on the forecast of emergency supplies for major public health emergencies
Authors: Zhu Xiaoxin , Wen Zhimin , Regan David , Zhu Wenlong 
Published: September 2023

Abstract

An adequate provision of medical supplies is critical in the battle against pandemics, such as the ongoing one against COVID-19. This paper proposes a generalized analysis based on the fluctuation period of emergency material demand, constructing a combined forecasting model of time series and support vector machines. The daily demand of specific protective masks donated by the Wuhan COVID-19 Epidemic Prevention and Control Headquarters in the period from February 1 to March 16, 2020 is predicted through the use of data from the Wuhan Red Cross. Compared with traditional linear time series forecasting models, the proposed forecasting model sees its accuracy increased by 37.55%, with the relative errors of MAE, MSE and MAPE being respectively reduced by 37.57%, 60.88% and 37.86%. It transpires that the combined model is able to make full use of the potential information implied in the original data. The decision-making process provides a reference point for the forecast of the demand of medical emergency materials in future major public health emergencies.
Differential Short-term and Long-term Metabolic and Cytokine Responses to Infection of Severe Fever with Thrombocytopenia Syndrome Virus
Authors: zhang zhiyi , Hu Yafei , Zheng Xiang , Chen Cairong , Zhao Yishuang , Lin Haijiang , He Na 
Published: September 2023

Abstract

Introduction
Severe fever with thrombocytopenia syndrome (SFTS) is an emerging infectious disease caused by the SFTS bunyavirus (SFTSV), which has a wide geographic distribution. The primary clinical manifestations of SFTS are fever and thrombocytopenia, with multiorgan failure being the leading cause of death. While most patients recover with treatment, little is known about the potential long-term metabolic effects of SFTSV infection.
Objectives
The aim of this study was to light on dysregulated metabolic pathways and cytokine responses following SFTSV infection, which pose significant risks to the short-term and long-term health of affected individuals.
Methods
In this study, we used untargeted metabolomics to obtain the relative abundance of plasma metabolites from 14 SFTS patients, 18 IgG positive healthy controls and 20 IgG negative healthy controls, respectively, using ultrahigh-performance liquid chromatography-mass spectrometry (UHPLC-MS). Additionally, the concentrations of 12 cytokines were quantified through mean fluorescence intensity (MFI) measurements.
Results and Conclusion
We screened 122 long-term metabolites and 108 short-term metabolites by analytical comparison and alalyzed their correlations with 12 cytokines. Glycerophospholipid metabolism (GPL) was identified as significant short-term metabolic pathway suggesting that the activation of GPL might be linked to the self-replication of SFTSV, whereas pentose phosphate pathway and alanine, aspartate, and glutamate metabolism were indicated as significant long-term metabolic pathways playing a role in combating long-standing oxidative stress in the patients. Furthermore, we propose that α-ketoglutarate could serve as a dietary supplement to protect recovering SFTS patients, potentially providing a new perspective for the treatment of SFTS patients.
Semi-field evaluation of aquatic predators for the control of Anopheles funestus in rural south-eastern Tanzania
Authors: Mahenge Herieth H. , Muyaga Letus L. , Nkya Joel D. , Kafwenji Andrew D. , Mwalugelo Yohana A. , Kahamba Najat F. , Ngowo Halfan S. , Kaindoa Emmanuel W. 
Published: September 2023

Abstract

Introduction:
Biological control is a promising alternative or complementary approach for controlling vector populations in response to the spread of insecticide resistance in malaria vectors. This study evaluated the efficacy of three selected potential predators on the density and fitness parameters of Anopheles funestus larvae in rural Tanzania.
Methods
Common predator families (Aeshnidae, Coenagriondae, and Notonectidae) and An. funestus group larvae were collected from natural aquatic habitats in rural south-eastern Tanzania. Predators were starved for 12hours while An. funestus larvae were given fish food before starting the experiment. Anopheles funestus larvae were placed into artificial habitats containing predators, exposing them to potential predation. The number of surviving An. funestus larvae was counted every 24hours. An emergence trap was placed at the top of artificial habitats to capture emerging mosquitoes. Emerged mosquitoes were monitored until they died. Female wings were measured and used as a proxy for body size. Generalized linear mixed models (GLMM) with binomial variates at 95% CI and Cox proportional hazard models were used to assess the proportion of dead mosquitoes and the daily survival determined.
Results
There were significant differences in the number of emerged mosquitoes between the treatment and control groups (p < 0.001). Thus, all predator species played a significant role in reducing the density of An. funestus mosquitoes (P < 0.001). Furthermore, these predators had notable effects on the fitness parameters and survival of emerged mosquitoes (P < 0.001). Among the three predators studied, Coenagrionidae were most efficient followed by Notonectidae, with Aeshnidae being the least efficient.
Conclusion
Selected aquatic predators have the potential to reduce the survival and density of Anopheles funestus larvae. They might eventually be included within an integrated malaria vector control strategy, ultimately leading to a reduction in malaria transmission.
A novel CaCO 3 -embedded carbon cathode for highly energy-efficient Li–O 2 batteries
Authors: Kang Inhan , Kang Jungwon 
Published: September 2023

Abstract
Rechargeable Li‒O2 batteries have attracted considerable attention owing to their high specific energy density compared to those of other lithium secondary batteries. However, the high charging overpotential remains one of the challenges for the application of Li-O2 batteries in specific energy storage systems. To solve this problem, various catalyst materials such as metal/metal oxides (Pt, Au, MnO2, CuO, etc.) have been developed. In this study, a new CaCO3 catalyst embedded in carbon is investigated for the first time for a nonaqueous Li‒O2 battery application. The overpotential of the Li‒O2 cell containing the CaCO3-embedded carbon cathode decreases by ~ 6.5% on an average over 40 cycles.
Nasal ciliary beating controlled by carbonic anhydrase IV and Na+/HCO3- co-transport under an extremely low CO2 condition (air)
Authors: Okamoto Shota , Yasuda Makoto , Kawaguchi Kotoku , Yasuoka Kasane , Kikukawa Yumi , Asano Shinji , Inui Taka-aki , Hirano Shigeru , Inui Toshio , Marunaka Yoshinori , Nakahari Takashi 
Published: September 2023

Abstract
Ciliated human nasal epithelial cells (c-hNECs) express the bicarbonate transport metabolon (BTM) consisting of carbonic anhydrase (CA) IV, Na+/HCO3- cotransporter (NBC) and CAII. This study demonstrated that the BTM rapidly and selectively transports HCO3- into c-hNECs resulting in a high intracellular pH (pHi) in c-hNECs. Applying a CO2/HCO3--free solution decreased ciliary beat frequency (CBF) at a high pHi, at which the CA-mediated reaction synthesized H+ from CO2 produced by the metabolism. An NH4+ pulse also gradually decreased CBF and pHi following to immediate their increases in c-hNECs. Inhibition of NBC by S0859 decreased CBF and pHi, and the effects of the CO2/HCO3--free solution on CBF were reversed in c-hNECs pretreated with S0859 (i.e. it transiently increased CBF). Ciliated human bronchial epithelial cells (c-hBECs), pHi in which was lower than that in c-hNECs, expressed CAII and NBC but not CAIV. In c-hBECs, the CO2/HCO3--free solution transiently increased CBF and pHi and the NH4+ pulse increased and plateaued CBF and pHi. Inhibition of NBC by S0859 did not decrease CBF and pHi in c-hBECs. Based on these observations, in c-hNECs, the interactions between CAIV and NBC play a key role to accelerate the HCO3- influx, acceleration of which increase pHi to an extremely high value. This novel mechanism keeping a high pHi maintains an adequate CBF in c-hNECs in the air (0.04% CO2).
Spatial structures of different particles in helicon plasma
Authors: Zhang Zun , Zhang Jikun , Sun Yuzhe 
Published: September 2023

Abstract
The spatial structures of different particles (high-energy electron excited ionic and low-energy electron excited neutral particles) in both discharge and plume plasmas of a helicon source have been characterized. These two different populations show different intensity jumps and growth rates with increasing RF input powers. Filters of 480 nm band pass and 600 nm high pass have been used to distinguish these two populations. Results show that the plasmas are generated from both ends of the antenna and transmitted to the middle of the antenna to form an axial particle path. When the wave mode reaches, the axial particle path is formed. The radial distribution of the high-energy electrons is highly concentrated on the center line while that of the low-energy electrons is relatively uniform. The axial distribution of the high-energy electrons is asymmetric, that is the maximum density is located on the one end of the antenna. The reversed magnetic field could reverse their axial distributions. In the plume plasma, the high-energy electrons are highly directional and expand further axial distances compared with the low-energy electrons. The most probable energies of ions derived from the RFEA remain almost the same with an average value of 45 eV. But the IEDF shapes and the relative ion densities change greatly at 700W. It is believed that the IEDFs and ion density jumps are more likely related to the high-energy electron density jumps.
Explore the effect of size stratification of datasets on software faults proneness prediction performance
Authors: Alshehri Yasser , Alshehri Yasser 
Published: September 2023

Abstract
Size is one of the significant factors associated with bugs, and it has been used to predict software faults. We believe that stratifying software files based on size can play an essential role in improving prediction performance. This study explores the effect of size by stratifying our sample based on each unit’s size and distributing software units in multiple stratified groups based on an equal distribution approach. We stratified the Eclipse Europa project and Derby project files, and we reported the performance of each stratified group and compared them. We used two popular classifiers, decision tree J48 and random forest, to implement this experiment. These classifiers presented similar results on the same group of files. The results indicated that predicting faults with large files is significantly better than predicting those with small files. Furthermore, the files of large groups provide reliable and more stable performance. Finally, we resampled all the stratified groups of the two projects to explore if this can impact the performance. We found that the resampling has no impact on the performance of algorithms using the Europa dataset. However, the effect was significant when the Derby project was used.
Machine learning for uncertainty quantification in climate precipitation prediction over South America
Authors: Monego Vinicius , Anochi Juliana , Velho Haroldo Campos 
Published: September 2023

Abstract

In recent times, machine learning algorithms have found applications in various fields. Nice results have been obtained by employing these algorithms, including precipitation climate prediction. Precipitation is a key meteorological variable in South America, related to the intense rainfall under different climate seasons. For Brazil, the importance is beyond agriculture, civil defense, and tourism, because most part of the electric energy is produced by hydroelectric power plants. The inputs are some meteorological variables (wind fields, temperature, and precipitation from the previous month). Decision tree is the approach applied for monthly precipitation prediction, as implemented in the Light Gradient Boosting Machine (LightGBM) framework, after the prediction, another important issue is to quantify how good is the forecasting, in other words, it is important to estimate the predictability -- or uncertainty quantification to the prediction. Therefore, two decision trees were designed to estimate the precipitation and the prediction uncertainty over South America. Optimal hyperparameters for the machine learning tools were determined by Optuna optimizer. Data from the years January-1980 up to December-2017 were addressed for algorithms training, while the years 2018 and 2019 were used for testing. Very good results were obtained for precipitation prediction, with uncertainty maps calculated for all South America territory.
Gut microbiota and spinal stenosis: a two-sample Mendelian randomization study
Authors: Chen Ding-Qiang , Xu Wen-Bin , Xiao Ke-Yi , Que Zhi-Qiang , Feng Jin-Yi , Sun Nai-Kun , Cai Di-Xin , Rui Gang 
Published: September 2023

Abstract
Background
Whether the gut microbiota (GM) affects the progress of spinal stenosis is unclear. Accordingly, we explored the link between intestinal microbiota and spinal stenosis by a two-sample Mendelian randomization (MR) research.
Methods
The genome-wide association studies (GWAS) data about intestinal microbiota (the MiBioGen) and spinal stenosis (the FinnGen biobank) were obtained. The major analytical strategy was the inverse variance weighting (IVW) approach. To test the credibility of estimates of causality, we conducted a variety of tests, which included consistency, heterogenicity, pleiotropy analyses, and sensitivity analysis. For appraising the underlying reverse causality, we additionally carried out a reverse MR analysis.
Results
Among the 196 GM taxa, the IVW results confirmed that class-Gammaproteobacteria (P = 0.004), genus-Eubacteriumrectalegroup (P = 0.012), genus-Eubacteriumruminantiumgroup (P = 0.034), genus-Oxalobacter (P = 0.011), genus-Ruminiclostridium5 (P = 0.013) and order-Clostridiales (P = 0.042) were correlated with spinal stenosis based on Finngen GWAS. No pleiotropy or heterogeneity were found. Exposure-outcome effects for the six gut microbial taxa remained significant after instrumental variables with confounding effects were excluded.
Conclusion
We proved the causative connection between intestinal flora and spinal stenosis and opened up a novel insight into the management of spinal stenosis: aimed modulation of dysbiosis of particular bacterial taxa to protect against spinal stenosis.