bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effect of synthetic conditions on the structure and magnetic properties of iron oxide nanoparticles in diethylene glycol medium
Authors: Nizamov Timur R. , Bordyuzhin Igor G. , Mogil’nikov Pavel S. , Abakumov Maxim A. , Shchetinin Igor V. , Savchenko Alexander G. 
Published: June 2024

Abstract

This paper presents a study on the influence of synthetic conditions on the structure and properties of hydrophilic iron oxide nanoparticles obtained by thermal decomposition in diethylene glycol. The phase composition of the nanoparticles was studied using X-ray diffraction analysis and Mössbauer spectroscopy. The mass content of the magnetic phase was determined by thermogravimetric analysis. Transmission electron microscopy was used to determine the sizes of the nanoparticles. The magnetic properties were measured using a vibration magnetometry and magnetic resonance imaging. X-ray diffraction revealed that all the obtained samples are of spinel structure (Fd-3m), specific to both magnetite and maghemite. Sample 60-2h is maghemite in terms of isomer shift (Is=0.353 ± 0.001 mm/s). With an increase in the synthesis time and concentration of iron (III) acetylacetonate, crystallite size changed from 1.8 ± 0.2 to 5.2 ± 0.5 nm, the mass fraction of non-volatile residue increased from 67.6 ± 0.1% to 85.9 ± 0.1%, the average size according to transmission electronic microscopy changed from 3.3 ± 0.8 to 3.8 ± 0.4 nm, and the saturation magnetization from 13.9 ± 0.3 to 83.3 ± 1.7 A•m2/kg. It was shown that the samples obtained using this synthesis method have high values of r2-relaxivity, up to 235 mM− 1•s− 1, which is usually uncharacteristic for iron oxide nanoparticles of this size range. The studied method for the synthesis of iron oxide nanoparticles is promising for use in creating T2 contrast agents for MRI.
­­Dynamics of rain-triggered lahars and destructive power inferred from seismo-acoustic arrays and time-lapse camera correlation at Volcán de Fuego, Guatemala.
Authors: Bosa Ashley R , Bejar Gustavo , Waite Gregory P. , Mock Jerry C. , Pineda Armando , Anderson Jacob F. 
Published: June 2024

Abstract

Lahars, or volcanic mudflows, are one of the most devastating natural, volcanic hazards. Deadly lahars, such as the one that occurred after the Nevado del Ruiz, Columbia eruption in 1985, in which at least 23,000 people tragically lost their lives, threaten the safety and well-being of humans, the economy, and the infrastructure of many of the communities living in the vicinity of volcanoes. Due to their complex flow behaviors, lahars remain a major challenge to those studying them. We present an analysis of several rain-triggered lahar events at Volcán Fuego in Guatemala using both seismic and infrasound monitoring to quantify both ground vibrations and low-frequency atmospheric sound waves associated with these mudflows. Geophysical data collected over this field campaign quantifies flow parameters such as velocities, stage and the frequency of these rain-triggered mudflows. Time-lapse imagery of lahar flows is compared with filtered seismo-acoustic signal characteristics to ascertain stage predictions and relationship to stage fluxes. Using random forest regression models, we establish moderate correlations (correlation coefficient modes 0.48–0.53) with statistical significance (p-value = 0.01–0.02) between energetics in the flows and respective stage. We observe that energetic thresholds exist when using infrasound to detect small lahars, likely due to storm noise and co-location of sensors to cameras. Compiling a catalog of rain-triggered lahar events in Volcán de Fuego’s drainages over a season permits a dataset amenable to statistical analysis. Our goal is the development of new-generation geophysical monitoring tools that will be capable of remote and real-time estimation of flow parameters.
GraphPCA: a fast and interpretable dimension reduction algorithm for spatial transcriptomics data
Authors: Yang Jiyuan , Wang Lu , Liu Lin , Zheng Xiaoqi 
Published: June 2024

Abstract

The rapid advancement of spatial transcriptomics technologies has revolutionized our understanding on cell heterogeneity and intricate spatial structures within tissues and organs. However, the high dimensionality and noise in spatial transcriptomic data present great challenges for downstream analyses. Here, we develop GraphPCA, a novel graph-constrained, interpretable, and quasi-linear dimension-reduction algorithm tailored for spatial transcriptomic data. GraphPCA leverages the strengths of graphical regularization and Principal Component Analysis (PCA) to extract low-dimensional embeddings of spatial transcriptomes that integrate location information in nearly linear time complexity. Through comprehensive evaluations on simulated data and multi-resolution spatial transcriptomic data generated from various platforms, we demonstrate the capacity of GraphPCA to enhance downstream analysis tasks including spatial domain detection, denoising, and trajectory inference. The computational efficiency and scalability of GraphPCA facilitate the development of GraphPCA_multi, a multi-slice extension of GraphPCA that effectively captures shared tissue structures across slices. GraphPCA_multi achieved more accurate spatial domain detection than its single-slice version and other competing methods in the field. The substantial power boost enabled by GraphPCA benefits various downstream tasks of spatial transcriptomic data analyses and provides more precise insights into transcriptomic and cellular landscapes of complex tissues.
Performance evaluation and analysis of scalable Raspberry Pi 4 Model B clusters
Authors: Liu Peng , Cao Xiaofan , Jia Yujiao 
Published: June 2024

Abstract

This study systematically investigates the performance scalability of Raspberry Pi 4 Model B clusters across various configura-tions. Leveraging the latest advancements in the Pi4B architecture, including improved processor performance, increased memory capacity, and enhanced network bandwidth, we explore Raspberry Pi clusters’ computational efficiency and cost-effectiveness. We use the High-Performance Linpack (HPL) benchmark to measure the clusters’ floating-point operations per second (FLOPS) across diverse node combinations and memory usage scenarios, examining cluster scalability andperformance thresholds. Our findings reveal a nuanced, nonlinear scaling behavior of performance with increasing cluster sizes. This paper contributes valuable insights for designing and optimizing Raspberry Pi clusters in scalable computing applications,offering a foundational perspective for future exploration in this rapidly evolving field.
Prevalence and Knowledge of modern contraceptives among married women in Kombo North District of The Gambia
Authors: Jatta Solomon PS , Badjie Mansour , Sreed Aswathy , Jassey Fatoumata 
Published: June 2024

Abstract

Background
The family planning services that are a part of reproductive health care give couples the chance to have the number of children they want with the proper spacing between each birth. Family planning is important for community socioeconomic advancement, public health, and resource conservation. It is the most economically impactful health and development intervention and has significant positive effects on women, communities, and nations as a whole. The study aimed at assessing married women's knowledge and prevalence of using contemporary contraceptives in the Kombo North District of The Gambia.
Methods: The study design was a descriptive hospital-based cross-section study design using the Maternal and Child Health clinics in the Gambia's Kombo North District. A total of two hundred and thirty-two randomly selected married women participants were recruited for the study.
A structured questionnaire was used to gather data from the participants. Univariate and bivariate analyses were used to analyze the data with the results presented using tables. IBM SPSS version 20.0 is used for data entry and analysis.
Results:
Ninety-three percent (93.1%) of married women used injectables with 6.9% used pills. The reasons for utilizing modern contraceptives were child spacing, prevention of unplanned pregnancy (78.9%), affordability and availability (18.4%), and suitability and reliability (4.9%). Two-thirds (65.1%) of the participants reported ever used family planning. However, 66% of the participants claimed to lack knowledge of family planning methods. Married women were able to identify only three family planning methods - Pills (58.2%), Injectable (78.9%), and Implants (9.5%).
Conclusion:
Married women showed some amount of understanding about using modern contraceptives even though the majority could only identify just three methods. The availability and acceptance of injectables and pills by married women and society may be a contributing factor to their use. Therefore, there is a need for more awareness creation to enable women to opt for other methods other than pills and injections.
Predicting Rice Blast (Pyriculariaoryzae) Severity Using Epidemiological Data with Advanced Regression Modeling Strategies
Authors: Arooj Saneela , Ahmad Salman , Ali Yasir , Ijaz Muhammad , Nawaz Muhammad , Shahzad Umbreen , Shah Adnan Noor , Ahmad Irfan , Ercisli Sezai , Ali Hayssam M. , Alsakkaf Waleed A. A. , Alomran Maryam M. 
Published: June 2024

Abstract

Rice blast is a detrimental disease widely prevalent in the world. Many disease predictive models have been developed for Rice blast disease (RBD) in different regions, but the disease prediction modeling in semi-arid areas is less characterized. Here, we focused on developing a disease predictive model (DPM) for rice blast disease (RBD) based on eight-year (2009–2016) environmental variables and their correlation with the RBD severity data, followed by validation with two-year (2017–2018) field trial data in a semi-arid region of Pakistan. Besides the correlation analysis, the model implied multiple linear regression analysis. The DPM indicated that five environmental variables maximum (Max) and minimum (Min) temperature, rainfall (RF), relative humidity (RH) and windspeed (WS), significantly contributed to the development of RBD during eight years. The obtained values of standard statistical indicators, coefficient of determination (R2) low standard error (SE) ≤ 10, and significance of F-distribution of regression statistics proved the effectiveness in predicting RBD for eight years. Furthermore, the criteria of root-mean square error (RMSE) and error (%) of 8 year data and observed data suggested a striking closeness between old and observed values of RBD severity, indicating the effective reliability of the model in both contexts. The analysis of 8 year DPM data showed that five environmental variables (max and min temps, RF, RH and WS) could cause up to 92% variability in RBD. Except for min temp, which showed a negative correlation suggesting a minor influence on disease development, the other four environmental factors exhibited a positive correlation with RBD severity, indicating the maximum contributing factors in disease development. The developed model helped us to predict the ranges of environmental factors, Max and Min temp 40–42°C and 22–24°C, RF 2-2.5 mm, RH 50–70%, and WS 9–11 Km/h, significantly favorable for RBD. The current prototype DPM of RBD has the potential for practical application if combined with a weather prediction system, which could be useful in developing rice blast disease warning system in the semi-arid zone of Punjab and predicting the appropriate time of the fungicidal sprays.
Trend Analysis of the Monthly and Annual Air Temperatures in Port-Said City (Egypt)
Authors: Dabbous Amna , El-Wakeel Yasser , El-Geziry Tarek 
Published: June 2024

Abstract

This study investigated variations in a long-term air temperature record in Port Said; to conclude the presence or absence of climate change in this important Egyptian city. The data collection spans 31 years, from 1991 to 2021. The research examined the homogeneity of the annual data, and the linear regression approach to specify the trend of air temperature variations throughout the study period. Moreover, the study investigated the trend significancy by using the Mann-Kendall test, the anomaly calculations and statistically specified the extreme air temperature events. Results revealed that the data were homogenous. Monthly mean air temperatures had increasing trends with varying rates, and the annual increasing trend had a rate of + 0.04°C/yr at 99% confidence level. A negative anomaly period existed only during the period 1991–1997, and as of 1998 the anomaly was always positive. The extreme air temperature times were precisely specified. Four extreme high and 12 extreme low monthly events were detected throughout the study period. The year 2010 (22.7°C) and the year 1991 (20.5°C) were determined as sole years of respectively extreme high and extreme low mean annual air temperatures. The research findings are regarded to be a trustworthy indicator of climate change in Port Said.
Assessing the contribution of genes involved in monogenic bone disorders to the etiology of atypical femoral fractures
Authors: Garcia-Giralt Natalia , Ovejero Diana , Grinberg Daniel , Nogues Xavier , Castañeda Santos , Balcells Susanna , Rabionet Raquel 
Published: June 2024

Abstract

Background
Recent studies suggested that genetic variants associated with monogenic bone disorders were involved in the pathogenesis of atypical femoral fractures (AFF). Here, we aim to identify rare genetic variants by whole exome sequencing in genes involved in monogenic rare skeletal diseases in 12 women with AFF and 4 controls without any fracture.
Results
Out of 33 genetic variants identified in women with AFF, eleven (33.3%) were found in genes belonging to the Wnt pathway (LRP5, LRP6, DAAM2, WNT1, and WNT3A). One of them was rated as pathogenic (p.Pro582His in DAAM2), while all others were rated as variants of uncertain significance according to ClinVar and ACMG criteria.
Conclusions
Osteoporosis, rare bone diseases, and AFFs may share the same genes, thus making it even more difficult to identify unique risk factors.
Analysis of conformable Fokas system in monomode optical fiber viathe modified Recatti equation mapping approach
Authors: Murad Muhammad Amin S. Murad , Omar Faraj M. 
Published: June 2024

Abstract

In the present paper, we apply modified generalized Riccati equation mapping method, whichresults in the successful derivation of numerous optical solutions for the conformable Fokas system.As a result, various optical solutions such as dark, singular, bright, and wave soliton solutionsare constructed. The novel optical soliton solutions derived in this study are depicted via contourgraphs, two-dimensional graphs, and three-dimensional surface plots. The physical significanceand dynamic nature of the optical solutions in the present conformable system through graphicalsimulations presented in multiple graphs are highlighted. The new optical soliton solutions holdpromise for applications in single-mode optical fibers. The Fokas method can be applied to modeland analyze the propagation of optical pulses through nonlinear fiber channels. To our knowledge,these solutions are original and have not been documented in existing literature. They hold promisefor applications in the field of nonlinear optics.
Novel early-onset Alzheimer-associated genes influence risk through dysregulation of glutamate, immune activation, and intracell signaling pathways
Authors: Cruchaga Carlos , Bradley Joseph , Western Daniel , Wang Ciyang , Fonseca Eder Lucio Da , Neupane Achal , Kurup Jiji , Ray NIcholas , Jean-Francois Melissa , Gorijala Priyanka , Bergmann Kristy , Budde John , Martin Eden , Pericak-Vance Margaret , Cuccaro Michael , Kunkle Brian , Morris John , Holtzman David , Perrin Richard , Naj Adam , Haines Jonathan , Schellenberg Gerard , Fernandez Victoria , Reitz Christiane , Beecham Gary , Consortium Alzheimer's Disease Genetics , ADRC Charles F. and Joanne Knight Alzheimer's disease research ce 
Published: June 2024

Abstract

Alzheimer Disease (AD) is a highly polygenic disease that presents with relatively earlier onset (≤70yo; EOAD) in about 5% of cases. Around 90% of these EOAD cases remain unexplained by pathogenic mutations. Using data from EOAD cases and controls, we performed a genome-wide association study (GWAS) and trans-ancestry meta-analysis on non-Hispanic Whites (NHW, NCase=6,282, NControl=13,386), African Americans (AA NCase=782, NControl=3,663) and East Asians (NCase=375, NControl=838 CO). We identified eight novel significant loci: six in the ancestry-specific analyses and two in the trans-ancestry analysis. By integrating gene-based analysis, eQTL, pQTL and functional annotations, we nominate four novel genes that are involved in microglia activation, glutamate production, and signaling pathways. These results indicate that EOAD, although sharing many genes with LOAD, harbors unique genes and pathways that could be used to create better prediction models or target identification for this type of AD
Comparative analysis of the profitability of major value-added activities along the pineapple value chain in Ghana
Authors: Boakye Kwaku , Salifu Iddrisu , Danso Hayford , Lee Yu-Feng 
Published: June 2024

Abstract

The purpose of this study was to analyze the profitability for sampled pineapple farmers, processors, and marketers in Ghana which will help evaluate how these actors optimize available resources to generate profits and achieve production efficiencies. It employed the descriptive survey while the interview schedules were used as the instruments for the data collection. A sample size of 320, 66, and 169 pineapple farmers, processors, and marketers was obtained respectively. Empirically, it revealed that pineapple production and processing were profitable whereas marketing was not. It rejected the null hypothesis identifying no significant difference in the profit share of the group actors and concluded that the profit share of each actor along the pineapple value chain is different. That is revenue, capital, and planting materials were the determinants of farmers’ profit; capital, pineapple fruits, and packaging materials were the predictors of the processors’ profit, while transportation, revenue, and loading and off-loading costs predict the profit of the marketer. The study recommended, among others, that NGOs and other partner agencies promote the pineapple industry in various ways in hopes of decreasing the country's poverty by providing the actors with credit facilities that will enhance their productivity, profitability, and sustainability.
Impact of the model structure and calibration strategy on baseflow modeling in the German low mountain range
Authors: Kissel Michael , Bach Michael , Schmalz Britta 
Published: June 2024

ABSTRACT

Baseflow is a vital component of the water balance. The fractured hard rock aquifers of the German low mountain range are in danger of increased water stress due to climate change because they react rapidly to deficits in precipitation and groundwater tables decline sharply. Therefore, simulation software must be able to model baseflow accurately. Three soil moisture simulation and two monthly factor-based baseflow models are evaluated using two calibration strategies. Models were calibrated to total flow (S1) or stepwise to baseflow and then total flow (S2). Results were not significantly different for total flow. Regarding baseflow, S2 proved significantly better with median values (S1 calibration, validation | S2 calibration, validation) of SSE (20.3, 20.3 | 13.5, 13.8), LnNSE (0.15, 0.17 | 0.47, 0.34), and PBIAS (27.8, 21.6 | 2.5, −0.8). Parallel linear reservoir proved best at modeling baseflow with a median SSE (S2: 6.1, 5.9), LnNSE (S2: 0.64, 0.71), and PBIAS (S2: 3.8, 3.8). The new modified monthly factor approach is a simple and robust alternative with SSE (13.0, 13.3), LnNSE (0.61, 0.61), and PBIAS (9.8, −8.6). The results are useful regarding selection of baseflow model structure and calibration strategy in low mountain ranges with fractured hard rock aquifers.
Climate-resilient urban drainage planning: An approach using a GIS-based SCS-CN model
Authors: Huq Md Habibul , Rahman Md Mafizur , Hasan G. M. Jahid 
Published: June 2024

ABSTRACT

Inexorable urbanization continues apace across the world and urban flooding in megacities is now frequently evidenced due to extreme rainfall events due to climate change (CC). Climate-resilient urban drainage planning is critical towards making sustainable cities or any new urbanization. This paper presents an approach through an insightful assessment of climate resilient urban drainage applying GIS-based Soil Conservation Service-Curve Number (SCS-CN) model of a new urban growth of megacity Dhaka, Bangladesh. A precise DEM (Digital Elevation Model) of the study area has been used for catchment delineation using ArcSWAT. Localized climate anomalies of rainfall of around 11% have been identified during monsoon from statistical downscaling and included in the cumulative rainfall event of 5 days. The effect of historical and CC-induced rainfall have been used to identify and map the peak discharges of sub-catchments considering the return period of 5-day cumulative rainfall for 10, 25, and 100 years of the urban catchment for both existing and future land-use scenarios accounting for the change in CN. The varying results of the peak discharges of the sub-catchments for resilient drainage planning is not only dependent on the increase in rainfall but also the combined response of the land-use and soil profile.
Seasonal distributions of Ti-containing NPs in the main tributaries of the Tamsuei River Basin in northern Taiwan
Authors: Chen Jou-An , Chen Yen-Tzu , Liu Chia-Hsin , Hwang Yaw-Huei 
Published: June 2024

ABSTRACT

This study aimed to characterize seasonal variations in Ti-containing nanoparticles in the Tamsuei River Basin, situated in northern Taiwan, using sp-ICPMS. The highest particulate mass concentrations were present in the Dahan River, 0.80 − 1.64 ng/mL and 5.65 − 9.94 ng/mL in the dry and wet seasons, respectively, whereas the lowest concentrations were observed in the Xindian River, 0.05 − 0.31 ng/mL and 0.34 − 1.92 ng/mL in the dry and wet seasons, respectively. The highest particulate number concentrations were found in the Keelung River, 170 × 103 − 231 × 103 part./mL in the dry season and 1,372 × 103 − 4,110 × 103 part./mL in the wet season, while the lowest ones presented in the Xindian River. Notably, both particulate mass and number concentrations were significantly elevated during the wet season compared with the dry season, exhibiting a general increase from upstream to downstream. Moreover, a higher proportion of Ti in particulate form was observed in all samples during the wet season. The most frequent sizes for particles present in the samples of the Dahan River were larger during the dry season, 60 − 72 nm, in contrast to the wet season, 38 − 52 nm. These findings suggest that local geology and land use patterns may contribute to variations in Ti-containing nanoparticle concentration distributions among different rivers, particularly during the wet season.