bluuebunny/crossref_metadata_2025 huggingface dataset:
Benchmarking RNA-Seq Aligners at Base-Level and Junction Base-Level Resolution Using the Arabidopsis thaliana Genome
Authors: Coxe Tallon , Burks David J. , Singh Utkarsh , Mittler Ron , Azad Rajeev K.
Published: February 2024

The utmost goal of selecting an RNA-Seq alignment software is to perform accurate alignments with a robust algorithm, which is capable of detecting the various intricacies underlying read-mapping procedures and beyond. Most alignment software tools are typically pre-tuned with human or prokaryotic data, and therefore may not be suitable for applications to other organisms, such as plants. The rapidly growing plant RNA-Seq databases call for the assessment of the alignment tools on curated plant data, which will aid the calibration of these tools for applications to plant transcriptomic data. We therefore focused here on benchmarking RNA-Seq read alignment tools, using simulated data derived from the model organism Arabidopsis thaliana. We assessed the performance of five popular RNA-Seq alignment tools that are currently available, based on their usage (citation count). By introducing annotated single nucleotide polymorphisms (SNPs) from The Arabidopsis Information Resource (TAIR), we recorded alignment accuracy at both base-level and junction base-level resolutions for each alignment tool. In addition to assessing the performance of the alignment tools at their default settings, accuracies were also recorded by varying the values of numerous parameters, including the confidence threshold and the level of SNP introduction. The performances of the aligners were found consistent under various testing conditions at the base-level accuracy; however, the junction base-level assessment produced varying results depending upon the applied algorithm. At the read base-level assessment, the overall performance of the aligner STAR was superior to other aligners, with the overall accuracy reaching over 90% under different test conditions. On the other hand, at the junction base-level assessment, SubRead emerged as the most promising aligner, with an overall accuracy over 80% under most test conditions.
Trichoderma atroviride Enhances Impatiens walleriana Hook. f Growth and Flowering in Different Growing Media
Authors: Traversari Silvia , Cardarelli Mariateresa , Brambilla Massimo , Cutini Maurizio , Burchi Gianluca , Fedrizzi Marco , Massa Daniele , Orlandini Alessandro , Cacini Sonia
Published: February 2024

Trichoderma spp. are widely reported to regulate plant growth by improving nutrient uptake, photosynthesis, and abiotic stress tolerance. However, their possible application for bedding plants is little explored, especially when comparing different growing media. Considering that coconut coir dust is finding broader application in the ornamental plants sector as a peat substitute, this work was aimed to test the combination of Trichoderma atroviride AT10 and coconut coir dust on Impatiens walleriana plants. Four treatments were tested as a mix of: (i) two growing media (70:30), peat:perlite or coconut coir dust:perlite; and (ii) the absence or presence of a T. atroviride treatment. At the end of the production cycle, the biomass and ornamental parameters, leaf pigments, nutrient content of the plant tissues, and Trichoderma abundance were assessed. The results revealed that T. atroviride can readily colonize coir, and the same positive effects of inoculum were found in plants grown on both substrates. The biostimulant effect of T. atroviride was observed as an increase in the aboveground biomass, number and weight of flowers, pigments and nutrient concentration, thereby improving the commercial quality of I. walleriana. Thus, T. atroviride has shown its potential in making bedding plant cultivation more sustainable and improving the yield and aesthetic parameters of plants grown on peat and coconut coir dust substrates.
Lap Shear Strength and Fatigue Analysis of Continuous Carbon-Fibre-Reinforced 3D-Printed Thermoplastic Composites by Varying the Load and Fibre Content
Authors: Saeed Khalid , Mcilhagger Alistair , Dooher Thomas , Ullah Jawad , Manzoor Faisal , Velay Xavier , Archer Edward
Published: February 2024

This study focuses on evaluating the fatigue life performance of 3D-printed polymer composites produced through the fused deposition modelling (FDM) technique. Fatigue life assessment is essential in designing components for industries like aerospace, medical, and automotive, as it provides an estimate of the component’s safe service life during operation. While there is a lack of detailed research on the fatigue behaviour of 3D-printed polymer composites, this paper aims to fill that gap. Fatigue tests were conducted on the 3D-printed polymer composites under various loading conditions, and static (tensile) tests were performed to determine their ultimate tensile strength. The fatigue testing load ranged from 80% to 98% of the total static load. The results showed that the fatigue life of the pressed samples using a platen press was significantly better than that of the non-pressed samples. Samples subjected to fatigue testing at 80% of the ultimate tensile strength (UTS) did not experience failure even after 1 million cycles, while samples tested at 90% of UTS failed after 50,000 cycles, with the failure being characterized as splitting and clamp area failure. This study also included a lap shear analysis of the 3D-printed samples, comparing those that were bonded using a two-part Araldite glue to those that were fabricated as a single piece using the Markforged Mark Two 3D printer. In summary, this study sheds light on the fatigue life performance of 3D-printed polymer composites fabricated using the FDM technique. The results suggest that the use of post-printing platen press improved the fatigue life of 3D-printed samples, and that single printed samples have better strength of about 265 MPa than adhesively bonded samples in which the strength was 56 MPa.
Valorisation of Sub-Products from Pyrolysis of Carbon Fibre-Reinforced Plastic Waste: Catalytic Recovery of Chemicals from Liquid and Gas Phases
Authors: Acha Esther , Gastelu Naia , Lopez-Urionabarrenechea Alexander , Caballero Blanca María
Published: February 2024

Waste carbon fibre-reinforced plastics were recycled by pyrolysis followed by a thermo-catalytic treatment in order to achieve both fibre and resin recovery. The conventional pyrolysis of this waste produced unusable gas and hazardous liquid streams, which made necessary the treatment of the pyrolysis vapours. In this work, the vapours generated from pyrolysis were valorised thermochemically. The thermal treatment of the pyrolysis vapours was performed at 700 °C, 800 °C and 900 °C, and the catalytic treatment was tested at 700 °C and 800 °C with two Ni-based catalysts, one commercial and one homemade over a non-conventional olivine support. The catalysts were deeply characterised, and both had low surface area (99 m2/g and 4 m2/g, respectively) with low metal dispersion. The thermal treatment of the pyrolysis vapours at 900 °C produced high gas quantity (6.8 wt%) and quality (95.5 vol% syngas) along with lower liquid quantity (13.3 wt%) and low hazardous liquid (92.1 area% water). The Ni–olivine catalyst at the lowest temperature, 700 °C, allowed us to obtain good gas results (100% syngas), but the liquid was not as good (only 58.4 area% was water). On the other hand, the Ni commercial catalyst at 800 °C improved both the gas and liquid phases, producing 6.4 wt% of gas with 93 vol% of syngas and 13.6 wt% of liquid phase with a 97.5 area% of water. The main reaction mechanisms observed in the treatment of pyrolysis vapours were cracking, dry and wet reforming and the Boudouard reaction.
Assessment of Degree of Conversion and Volumetric Shrinkage of Novel Self-Adhesive Cement
Authors: Ling Long , Chen Yulin , Malyala Raj
Published: February 2024

The degree of monomer conversion and polymerization shrinkage are two of the main reasons for potential adhesion failure between the tooth structure and the restoration substrate. To evaluate the degree of conversion and polymerization shrinkage of a newly developed self-adhesive resin cement, the degree of conversion (DC) was measured using FTIR under different activation modes, temperatures, and times. Volumetric shrinkage was tested using the AcuVol video imaging method. The experimental cement showed a higher DC than other cements under self-curing. The DC of the experimental cement was higher than that of other cements, except SpeedCem Plus under light curing. The experimental cement had a higher DC than other cements, except SpeedCem Plus in some conditions under dual curing. All self-adhesive cements had a higher DC at 37 °C than at 23 °C under self-curing, and there was no statistical difference between 23 °C and 37 °C under light curing. All self-adhesive cements showed a significantly higher DC at 10 min than at 5 min under self-curing. There was no statistical difference between 5 min and 10 min for most cements under dual curing. All self-adhesive cements statistically had the same volumetric shrinkage under light curing and self-curing. The newly developed self-adhesive resin cement exhibited a higher degree of conversion and similar volumetric shrinkage compared to these commercial self-adhesive resin cements.
An Approach to Testing Antivandal Composite Materials as a Function of Their Thickness and Striker Shape—A Case Study
Authors: Irzmańska Emilia , Mizera Kamila , Litwicka Natalia , Sałasińska Kamila
Published: February 2024

Our research material comprised antivandal fire-retardant hybrid composites modified with inorganic and organic fillers intended for application in public transport vehicles. This paper presents an approach to studying their impact strength as a function of the composite thickness (3 to 6 mm) and striker shape (hemispherical, semicylindrical, wedge-shaped) used in the experimental stand. Group A composites, made of single fabric layers (n = 5), were thinner and their impact strength was lower by 73% than that for Group B composites made of double fabric layers. Study results show an almost threefold improvement in impact strength for a thickness increase of as little as 0.3 mm. Statistical analysis (the Shapiro–Wilk test, p > 0.05) did not show any significant differences in the quantitative evaluation of changes (n = 3) on the surface of the examined materials caused by impacts with strikers of different shapes. In turn, a linear correlation (Shapiro-Wilk test, W = 0.0857, p = 0.022) was found between impact strength and the thickness of the studied materials. It was observed that appropriate arrangement of fabrics and powder fillers can lead to a different distribution of forces and energy absorbed by the tested material. A lower impact strength was observed for the composite which had powder fillers in its composition, which caused the formation of microvoids in the structure of the material and thus led to a weakening in their strength properties. An effect of the placement of the glass fabric layer in the composite on the results was also observed. Moreover, SEM evaluation of the composites revealed their layered structure and the impregnation of woven fabrics with resin.
Synergetic Mechanism of Multiple Industrial Solid Waste-Based Geopolymer Binder for Soil Stabilization: Optimization Using D-Optimal Mixture Design
Authors: Wang Xiaoli , Wang Xiancong , Fu Pingfeng , Lei Bolan , Shi Jinjin , Xu Miao
Published: February 2024

In order to improve the comprehensive utilization rate of industrial solid waste and the road quality, a novel low-carbon and environmental friendly soil stabilizer is proposed. In this study, steel slag (SS), carbide slag (CS), blast furnace slag (BFS), fly ash (FA), and desulfurized gypsum (DG) were used as raw materials to develop a multiple industrial solid waste-based soil stabilizer (MSWSS). The optimal mix ratio of the raw materials determined by D-optimal design was as follows: 5% SS, 50% CS, 15% BFS, 15% DG, and 15% FA. The 7-day unconfined compressive strength (UCS) of MSWSS-stabilized soil was 1.7 MPa, which was 36% higher than stabilization with ordinary portland cement (OPC) and met the construction requirements of highways. After 7 days of curing, the UCS of MSWSS-stabilized soil was significantly higher than that in the OPC group. X-ray powder diffraction (XRD), thermogravimetric analysis (TGA), and scanning electron microscopy (SEM) analysis indicated that the prominent hydration products were ettringite (AFt) and C-S-H gel. The results showed that an amount of AFt and C-S-H were formed in the initial stage of curing, resulting in a rapid improvement in early UCS. As the curing proceeded, the content of AFt and C-S-H increased constantly and grew intertwined with each other, which lead to the denser microstructure of stabilized soil and better mechanical strength.
How Would Structural Change in Electricity and Hydrogen End Use Impact Low-Carbon Transition of an Energy System? A Case Study of China
Authors: Zhang Nuobei , Li Zheng , Zheng Xiaoying , Liu Pei
Published: February 2024

Driven by global targets to reduce greenhouse gas emissions, energy systems are expected to undergo fundamental changes. In light of carbon neutrality policies, China is expected to significantly increase the proportion of hydrogen and electricity in its energy system in the future. Nevertheless, the future trajectory remains shrouded in uncertainty. To explore the potential ramifications of varying growth scenarios pertaining to hydrogen and electricity on the energy landscape, this study employs a meticulously designed bottom-up model. Through comprehensive scenario calculations, the research aims to unravel the implications of such expansions and provide a nuanced analysis of their effects on the energy system. Results show that with an increase in electrification rates, cumulative carbon dioxide emissions over a certain planning horizon could be reduced, at the price of increased unit reduction costs. By increasing the share of end-use electricity and hydrogen from 71% to 80% in 2060, the unit carbon reduction cost will rise by 17%. Increasing shares of hydrogen could shorten the carbon emission peak time by approximately five years, but it also brings an increase in peak shaving demand.
Novel Method on Mixing Degree Quantification of Mine Water Sources: A Case Study
Authors: Li Qizhen , Fan Gangwei , Zhang Dongsheng , Yu Wei , Zhang Shizhong , Fan Zhanglei , Fu Yue
Published: February 2024

After a mine water inrush occurs, it is crucial to quickly identify the source of the water inrush and the key control area, and to formulate accurately efficient water control measures. According to the differences in water chemical characteristics of four aquifers in the Fenyuan coal mine, the concentrations of K+~Na+, Ca2+, Mg2+, Cl−, SO42−, and HCO3− were taken as water source identification indexes. A decision tree classification model based on the C4.5 algorithm was adopted to visualize the chemical characteristics of a single water source and extract rules, and intuitively obtained the discrimination conditions of a single water source with Mg2+, Ca2+, and Cl− as important variables in the decision tree: Mg2+ < 39.585 mg/L, Cl− < 516.338 mg/L and Mg2+ ≥ 39.585 mg/L, Ca2+ < 160.860 mg/L. Factor analysis and Fisher discriminant theory were used to eliminate the redundant ion variables, and the discriminant function equations of the two, three, and four types of mixed water sources were obtained successively in turn. This paper puts forward MSE, RMSE, and MAE as the evaluation indexes of the water source mixing degree calculation models and obtains the ranking of the pros and cons of the mixed water source mixing degree calculation models. The results show that the minimum inscribed circle analytical method is the optimal model for the calculation of the mixing degree of two types of water sources, and the MSE, RMSE, and MAE are 0.17%, 4.13%, and 4.13%, respectively. The minimum inscribed circle clustering method is the optimal model for the calculation of the mixing degree of three types of water sources, and the minimum distance method is the optimal model for the calculation of the mixing degree of four types of water sources. The method of mine water source identification based on the decision tree C4.5 algorithm and mixing degree calculation has the characteristics of a simple calculation process, high efficiency, objective accuracy, and low cost, which can provide a scientific basis for the development of stope water control measures.
The Positive Association between Grit and Mental Toughness, Enhanced by a Minimum of 75 Minutes of Moderate-to-Vigorous Physical Activity, among US Students
Authors: Stamatis Andreas , Morgan Grant B. , Boolani Ali , Papadakis Zacharias
Published: February 2024

Drawing from the 2015 Gucciardi et al.’s mental toughness (MT) framework, this study examines the association between grit and MT in US college students, while considering the moderating role of at least 75 min of moderate-to-vigorous physical activity (MVPA) based on recommendations from the American College of Sports Medicine. We administered the Grit-S Scale and the Mental Toughness Index in two samples of a total of 340 US undergraduate student-athletes and graduate students. The Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies was employed to ensure internal validity, while statistical procedures including principal component analysis and regression models were utilized to analyze the collected data. A weighted component combining grit and the interaction between MVPA and grit significantly predicted MT, explaining 23% of its variability. Drawing from a specific conceptual framework, this study provides novel insights into the relationship between grit, engagement in at least 75 min of MVPA per week, and MT among US collegiate students. The findings support a positive association between grit, MVPA, and both MT and a specific component of MT, highlighting the significance of these factors in enhancing performance and suggesting potential implications for future research and practical applications in the field.
Love Thy Neighbor: Exploring Religious and Social Openness among Prospective Theologians in Germany and Turkey
Authors: Demmrich Sarah , Ağılkaya-Şahin Zuhal , Şenel Abdulkerim
Published: February 2024

Amidst increasing globalization and religious diversity, acknowledging and embracing openness towards religious and/or cultural others has become crucial for societal cohesion and international relations. Theological scholars, holding significant potential in mitigating inter-religious and intercultural prejudices, can play a pivotal role in addressing this challenge. However, it is acknowledged that theologians themselves may harbor such biases. This study, conducted within the framework of the Religious Openness Hypothesis, employed an online questionnaire among theology students, seen as future multipliers of religiosity, in Germany and Turkey (N = 513) using convenience sampling. The results reveal the consistent relation of religiosity to all forms of prejudice among German Christians, with a linked defense against secularism potentially leading to self-isolation and the protection of their own worldview against religious or cultural outgroups. In contrast, the (generally high) prejudice among Turkish Muslims appears to be rooted not primarily in religiosity or defense against secularism but in fundamentalism and, most likely, in other socio-cultural factors such as politics and education. For both subsamples, religiosity was positively linked with xenosophia, particularly when accounting for fundamentalism. The article concludes by proposing curriculum implications for universities and schools in both cultural contexts.
Historical Dynamic Mapping of Eucalyptus Plantations in Guangxi during 1990–2019 Based on Sliding-Time-Window Change Detection Using Dense Landsat Time-Series Data
Authors: Li Yiman , Liu Xiangnan , Liu Meiling , Wu Ling , Zhu Lihong , Huang Zhi , Xue Xiaojing , Tian Lingwen
Published: February 2024

Eucalyptus plantations are expanding rapidly in southern China owing to their short rotation periods and high wood yields. Determining the plantation dynamics of eucalyptus plantations facilitates accurate operational planning, maximizes benefits, and allows the scientific management and sustainable development of eucalyptus plantations. This study proposes a sliding-time-window change detection (STWCD) approach for the holistic characterization and analysis of eucalyptus plantation dynamics between 1990 and 2019 through dense Landsat time-series data. To achieve this, pre-processing was first conducted to obtain high-quality reflectance data and the monthly composite maximum normalized-difference vegetation index (NDVI) time series was determined for each Landsat pixel. Second, a sliding time window was used to segment the time series and obtain the NDVI change characteristics of the subsequent segments, and a sliding time window-based LandTrendr change detection algorithm was applied to detect the crucial growth or harvesting phases of the eucalyptus plantations. Third, pattern-matching technology was adopted based on the change detection results to determine the characteristics of the eucalyptus planting dynamics. Finally, we identified the management history of the eucalyptus plantations, including planting times, generations, and rotation cycles. The overall accuracy of eucalyptus identification was 90.08%, and the planting years of the validation samples and the planting years estimated by our algorithm revealed an apparent correlation of R2 = 0.98. The results showed that successive generations were mainly first- and second-generations, accounting for 75.79% and 19.83% of the total eucalyptus area, respectively. The rotation cycles of the eucalyptus plantations were predominantly in the range of 4–8 years. This study provides an effective approach for identifying eucalyptus plantation dynamics that can be applied to other short-rotation plantations.
Comparison and Synthesis of Precipitation Data from CloudSat CPR and GPM KaPR
Authors: Liang Yanzhi , Kou Leilei , Huang Anfan , Gao Haiyang , Lin Zhengjian , Xie Yanqing , Zhang Liguo
Published: February 2024

Employing different bands of radar to detect precipitation information in identical regions enables the acquisition of a more comprehensive precipitation cloud structure, thereby refining the continuity and completeness of precipitation measurements. This study first compared the coincident data from CloudSat W-band cloud profiling radar (CPR) and Global Precipitation Measurement Mission (GPM) Ka-band precipitation radar (KaPR) from 2014 to 2017, and then a synthesis of the radar reflectivity from CPR and KaPR was attempted to obtain a complete cloud and precipitation structure. The findings of the reflectivity comparisons indicated that the echo-top height identified by CPR is on average 3.6 to 4.2 km higher than that from KaPR, due to the higher sensitivity. Because of strong attenuation of CPR by liquid-phase particles, the reflectivity below the height of the melting layer usually shows an opposite gradient to KaPR with decreasing altitude. The difference in the near-surface rain rates of CPR and KaPR was found to be related to reflectivity gradients in the vertical direction, and the larger the reflectivity gradients, the greater the differences in near-surface rain rates. For better representing the complete vertical structure of precipitation clouds and improving the consistency of the reflectivity and precipitation rate, the radar reflectivity was weighted, synthesized from CPR and KaPR based on the gradient difference of the reflectivity from the two radars. We presented the synthesis results for a stratiform cloud and a deep convective case, and Spearman’s rank correlation coefficient (rs) between the GPM combined radiometer precipitation rate and the radar reflectivity was utilized to analyze the performance of the synthesis. The consistency between synthesized reflectivity and precipitation rate in the non-liquid phase was improved compared with KaPR, and the rs of the ice and mixed phases was increased by about 12% and 10%, respectively.
Extraction and Analysis of Grasshopper Potential Habitat in Hulunbuir Based on the Maximum Entropy Model
Authors: Zhang Yan , Dong Yingying , Huang Wenjiang , Guo Jing , Wang Ning , Ding Xiaolong
Published: February 2024

Grasshoppers have profound effects on both grassland ecosystems and livestock production. Despite commendable efforts made by China in grasshopper control, completely eradicating or preventing them still remains a distant prospect. This study aims to analyze the ecological distribution and patterns of grasshopper occurrences in order to provide more accurate monitoring techniques and preventive measures. By considering four types of environmental determinants—meteorology, vegetation, soil, and topography—we systematically identified 18 key influencing factors. These factors encompass various developmental stages of grasshoppers, including variables such as temperature, precipitation, vegetation coverage, vegetation type, soil moisture, soil salinity, soil type, and terrain characteristics. The MaxEnt model is employed in this study to comprehensively capture complex ecological interactions. Omission curves, Receiver Operating Characteristic curves (ROC curves), and the Area Under the Curve (AUC values) demonstrate the robustness and high accuracy of the MaxEnt model. Our research results indicate that meteorological factors are the primary influencing factors for the distribution of grasshoppers, surpassing the effects of vegetation, soil, and terrain. Precipitation and vegetation type emerge as key factors shaping their distributional patterns. Integrating the Sen-MK trend method, our findings identify the epicenter of damage primarily within the central, southern, and northeastern regions, notably affecting locales such as New Barag East County and the Ewenki Autonomous Banner. While their impact in 2012 was particularly severe, temporal trends indicate a decreasing risk of grasshoppers in specific regions, with escalated activity observed in other areas. The empirical insights from this study lay a solid foundation for the development of monitoring and control strategies concerning grasshoppers. Furthermore, the derived theoretical framework serves as a valuable foundation for future research endeavors addressing grasshopper infestations.
Rainfall Area Identification Algorithm Based on Himawari-8 Satellite Data and Analysis of its Spatiotemporal Characteristics
Authors: Chen Xingru , Letu Husi , Shang Huazhe , Ri Xu , Tang Chenqian , Ji Dabin , Shi Chong , Teng Yupeng
Published: February 2024

Real-time monitoring of rainfall areas based on satellite remote sensing is of vital importance for extreme rainfall research and disaster prediction. In this study, a new rainfall area identification algorithm was developed for the new generation of geostationary satellites with high spatial and temporal resolution and rich bands. As the main drivers of the rainfall process, the macro and micro physical properties of clouds play an important role in the formation and development of rainfall. We considered differences in the absorption capacity of the water vapor absorption channels in the infrared band and introduced a sensitivity difference of rainfall area in water vapor channels to construct a sensitive detection of the water vapor region. The results of this algorithm were evaluated using Global Precipitation Measurement (GPM) satellite products and CloudSat measurements in various scenarios, with hit rates of 70.03% and 81.39% and false alarm rates of 2.05% and 21.34%, respectively. Spatiotemporal analysis revealed that the types of upper clouds in the rainfall areas mainly consisted of deep convection, cirrostratus, and nimbostratus clouds. Our study provides supporting data for weather research and disaster prediction, as well as an efficient and reliable method for capturing temporal and spatial features.
Evaluation and Comparison of Reanalysis Data for Runoff Simulation in the Data-Scarce Watersheds of Alpine Regions
Authors: Wang Xiaofeng , Zhou Jitao , Ma Jiahao , Luo Pingping , Fu Xinxin , Feng Xiaoming , Zhang Xinrong , Jia Zixu , Wang Xiaoxue , Huang Xiao
Published: February 2024

Reanalysis datasets provide a reliable reanalysis of climate input data for hydrological models in regions characterized by limited weather station coverage. In this paper, the accuracy of precipitation, the maximum and minimum temperatures of four reanalysis datasets, the China Meteorological Assimilation Driving Datasets for the SWAT model (CMADS), time-expanded climate forecast system reanalysis (CFSR+), the European Centre for Medium-Range Weather Forecast Reanalysis (ERA). and the China Meteorological Forcing Dataset (CMFD), were evaluated by using data from 28 ground-based observations (OBs) in the Source of the Yangtze and Yellow Rivers (SYYR) region and were used as input data for the SWAT model for runoff simulation and performance evaluation, respectively. And, finally, the CMADS was optimized using Integrated Calibrated Multi-Satellite Retrievals for Global Precipitation Measurement (AIMERG) data. The results show that CMFD is the most representative reanalysis data for precipitation characteristics in the SYYR region among the four reanalysis datasets evaluated in this paper, followed by ERA5 and CFSR, while CMADS performs satisfactorily for temperature simulations in this region, but underestimates precipitation. And we contend that the accuracy of runoff simulations is notably contingent upon the precision of daily precipitation within the reanalysis dataset. The runoff simulations in this region do not effectively capture the extreme runoff characteristics of the Yellow River and Yangtze River sources. The refinement of CMADS through the integration of AIMERG satellite precipitation data emerges as a potent strategy for enhancing the precision of runoff simulations. This research can provide a reference for selecting meteorological data products and optimization methods for hydrological process simulation in areas with few meteorological stations.
Analysis and Quantification of the Distribution of Marabou (Dichrostachys cinerea (L.) Wight & Arn.) in Valle de los Ingenios, Cuba: A Remote Sensing Approach
Authors: Moreno Eduardo , Gonzalez Encarnación , Alvarez Reinaldo , Menendez Julio
Published: February 2024

Cuba is struggling with a growing environmental problem: the uncontrolled spread of the allochthonous weed species marabou (Dichrostachys cinerea) throughout the country. Over the last 70 years, marabou has become a formidable invasive species that poses a threat to Cuban biodiversity and agricultural productivity. In this paper, we present a free and affordable method for regularly mapping the spatial distribution of the marabou based on the Google Earth Engine platform and ecological surveys. To test its accuracy, we develop an 18-year remote sensing analysis (2000–2018) of marabou dynamics using the Valle de los Ingenios, a Cuban UNESCO World Heritage Site, as an experimental model. Our spatial analysis reveals clear patterns of marabou distribution and highlights areas of concentrated growth. Temporal trends illustrate the aggressive nature of the species, identifying periods of expansion and decline. In addition, our system is able to detect specific, large-scale human interventions against the marabou plague in the area. The results highlight the urgent need for remedial strategies to maintain the fragile ecological balance in the region.
Trends in Concentration and Flux of Total Suspended Matter in the Irrawaddy River
Authors: Zheng Zhuoqi , Wang Difeng , Fu Dongyang , Gong Fang , Huang Jingjing , He Xianqiang , Zhang Qing
Published: February 2024

Large rivers without hydrological data from remote sensing observations have recently become a hot research topic. The Irrawaddy River is among the major tropical rivers worldwide; however, published hydrological data on this river have rarely been obtained in recent years. In this paper, based on the existing measured the total suspended matter flux (FTSM) and discharge data for the Irrawaddy River, an inversion model of the total suspended matter concentration (CTSM) is constructed for the Irrawaddy River, and the CTSM and FTSM from 1990 to 2020 are estimated using the L1 products of Landsat-8 OLI/TIRS and Landsat-5 TM. The results show that over the last 30 years, the FTSM of the Irrawaddy River decreased at a rate of 3.9 Mt/yr, which is significant at the 99% confidence interval. An increase in the vegetation density of the Irrawaddy Delta has increased the land conservation capacity of the region and reduced the inflow of land-based total suspended matter (TSM). The FTSM of the Irrawaddy River was estimated by fusing satellite data and data measured at hydrological stations. The research method employed in this paper provides a new supplement to the existing hydrological data for large rivers.
Python Software Tool for Diagnostics of the Global Navigation Satellite System Station (PS-NETM)–Reviewing the New Global Navigation Satellite System Time Series Analysis Tool
Authors: Savchuk Stepan , Dvulit Petro , Kerker Vladyslav , Michalski Daniel , Michalska Anna
Published: February 2024

The time series of GNSS coordinates contain signals caused by the age-related movement of tectonic plates, the deformation of the Earth’s surface, as well as errors at different time scales from sub-daily tidal deformation to the long-term deformation of the surface load. Depending on the nature of the signal, specific approaches are used for both the visual interpretation and pre-processing of time series and their statistical analysis. However, none of the present software analyzes the nature of the residual errors but assumes their random nature and obedience to the classical normal distribution. One of the methods for analyzing the time series of coordinates with residual, unaccounted-for systematic errors is the non-classical error theory of measurements. The result of this work is a developed software solution for analyzing the time series of GNSS coordinates to test their normality, or in other words, to test whether a particular GNSS station is subject to the influence of small, unaccounted-for errors. Conclusions: After testing our software on four reference stations in Europe, we concluded that none of the chosen stations followed the normal law of distribution; thus, it is vital to perform such tests before conducting any experiments on the time series from reference stations.
The Use of Interactive Visualizations for Tracking Haplotypic Inheritance in Livestock
Authors: Selli Alana , Miller Stephen P. , Ventura Ricardo V.
Published: February 2024

Our objective was to harness the power of interactive visualizations by utilizing open-source tools to develop an efficient strategy for visualizing Single Nucleotide Polymorphism data within a livestock population, focusing on tracking the transmission of haplotypes. To achieve this, we simulated a realistic beef cattle population in order to obtain phased haplotypes and generate the necessary inputs for creating our visualizations. The visualization tool was built using Python and the Plotly library, which enables interactivity. We set out to explore three scenarios: trio comparison, visualization of grandparents, and half-sibling evaluation. These scenarios enabled us to trace the inheritance of genetic segments, identify crossover events, and uncover common regions within related and unrelated animals. The potential applications of this approach are significant, particularly for improving genomic selection in smaller breeding programs and farms, and it provides valuable insights for guiding more in-depth genomic region analysis. Beyond its practical applications, we believe this strategy can be a valuable educational tool, helping educators clarify complex concepts like Mendelian sampling and haplotypic diversity. Furthermore, we hope it will encourage livestock producers to adopt advanced technologies like genotyping and genomic selection, thereby contributing to the advancement of livestock genetics.
Novel near E-Field Topography Sensor for Human–Machine Interfacing in Robotic Applications
Authors: Skoraczynski Dariusz J. , Chen Chao
Published: February 2024

This work investigates a new sensing technology for use in robotic human–machine interface (HMI) applications. The proposed method uses near E-field sensing to measure small changes in the limb surface topography due to muscle actuation over time. The sensors introduced in this work provide a non-contact, low-computational-cost, and low-noise method for sensing muscle activity. By evaluating the key sensor characteristics, such as accuracy, hysteresis, and resolution, the performance of this sensor is validated. Then, to understand the potential performance in intention detection, the unmodified digital output of the sensor is analysed against movements of the hand and fingers. This is done to demonstrate the worst-case scenario and to show that the sensor provides highly targeted and relevant data on muscle activation before any further processing. Finally, a convolutional neural network is used to perform joint angle prediction over nine degrees of freedom, achieving high-level regression performance with an RMSE value of less than six degrees for thumb and wrist movements and 11 degrees for finger movements. This work demonstrates the promising performance of this novel approach to sensing for use in human–machine interfaces.
Interpreting Stroke-Impaired Electromyography Patterns through Explainable Artificial Intelligence
Authors: Hussain Iqram , Jany Rafsan
Published: February 2024

Electromyography (EMG) proves invaluable myoelectric manifestation in identifying neuromuscular alterations resulting from ischemic strokes, serving as a potential marker for diagnostics of gait impairments caused by ischemia. This study aims to develop an interpretable machine learning (ML) framework capable of distinguishing between the myoelectric patterns of stroke patients and those of healthy individuals through Explainable Artificial Intelligence (XAI) techniques. The research included 48 stroke patients (average age 70.6 years, 65% male) undergoing treatment at a rehabilitation center, alongside 75 healthy adults (average age 76.3 years, 32% male) as the control group. EMG signals were recorded from wearable devices positioned on the bicep femoris and lateral gastrocnemius muscles of both lower limbs during indoor ground walking in a gait laboratory. Boosting ML techniques were deployed to identify stroke-related gait impairments using EMG gait features. Furthermore, we employed XAI techniques, such as Shapley Additive Explanations (SHAP), Local Interpretable Model-Agnostic Explanations (LIME), and Anchors to interpret the role of EMG variables in the stroke-prediction models. Among the ML models assessed, the GBoost model demonstrated the highest classification performance (AUROC: 0.94) during cross-validation with the training dataset, and it also overperformed (AUROC: 0.92, accuracy: 85.26%) when evaluated using the testing EMG dataset. Through SHAP and LIME analyses, the study identified that EMG spectral features contributing to distinguishing the stroke group from the control group were associated with the right bicep femoris and lateral gastrocnemius muscles. This interpretable EMG-based stroke prediction model holds promise as an objective tool for predicting post-stroke gait impairments. Its potential application could greatly assist in managing post-stroke rehabilitation by providing reliable EMG biomarkers and address potential gait impairment in individuals recovering from ischemic stroke.
Template-Guided Hierarchical Multi-View Registration Framework of Unordered Bridge Terrestrial Laser Scanning Data
Authors: Xiong Guikai , Cui Na , Liu Jiepeng , Zeng Yan , Chen Hanxin , Huang Chengliang , Xu Hao
Published: February 2024

The registration of bridge point cloud data (PCD) is an important preprocessing step for tasks such as bridge modeling, deformation detection, and bridge health monitoring. However, most existing research on bridge PCD registration only focused on pairwise registration, and payed insufficient attention to multi-view registration. In addition, to recover the overlaps of unordered multiple scans and obtain the merging order, extensive pairwise matching and the creation of a fully connected graph of all scans are often required, resulting in low efficiency. To address these issues, this paper proposes a marker-free template-guided method to align multiple unordered bridge PCD to a global coordinate system. Firstly, by aligning each scan to a given registration template, the overlaps between all the scans are recovered. Secondly, a fully connected graph is created based on the overlaps and scanning locations, and then a graph-partition algorithm is utilized to construct the scan-blocks. Then, the coarse-to-fine registration is performed within each scan-block, and the transformation matrix of coarse registration is obtained using an intelligent optimization algorithm. Finally, global block-to-block registration is performed to align all scans to a unified coordinate reference system. We tested our framework on different bridge point cloud datasets, including a suspension bridge and a continuous rigid frame bridge, to evaluate its accuracy. Experimental results demonstrate that our method has high accuracy.
Body Part Pain Affects Subjective and Objective Handball Performance in Japanese Male National Athletes—Results of Short-Term Practical Monitoring of Athletes’ Conditions
Authors: Ogasawara Issei , Shindo Daichi , Fujiwara Kazuki , Suzuki Haruka , Ueno Yuki , Kato Hiroyuki , Takada Michihiro , Adachi Yusuke , Todoroki Manabu , Iwasaki Susumu , Okimoto Nobukazu , Nakata Ken
Published: February 2024

This short-term survey examined the effect of body part pain on subjective and objective handball performance in Japanese male national handball athletes. Fourteen athletes participated in this study. Assessments of pain in 10 body parts and subjective performance (concentration and satisfaction with body movement) were performed using a visual analog scale from 0 to 10 over four consecutive training days. Monitoring of heart rate and body acceleration during training was also performed to quantify the objective performance. Path analysis and linear mixed modeling were employed to assess the relationship between body pain scores and subjective/objective handball performance. Over the four days of the study period, the body part in which most athletes reported pain was the dominant shoulder (6 of 14 athletes), followed by the dominant knee, the dominant elbow, the dominant ankle joint, and the non-dominant ankle joint (3 of 14 athletes). The path analysis revealed that pain in the dominant elbow negatively correlated with concentration (standardized path coefficient = −0.644, p = 0.00), which was associated with satisfaction with body movement (standardized path coefficient = 0.704, p = 0.00). No significant effect of body pain on objective performance (heart rate and body acceleration) was found among the athletes in this study. The results suggested that the elite athletes were practicing with pain. Even if pain does not physically affect athletes’ objective performance, pain in the upper extremities, associated with the primary handball movement of throwing, may reduce the quality of practice by lowering athletes’ subjective performance.
Morpho-Physiological Assessment of Tomato and Bell Pepper in Response to Nutrient Restriction
Authors: Lisboa Lucas Aparecido Manzani , Galindo Fernando Shintate , Pagliari Paulo Humberto , Goncalves João Igor Ussifati Pessoa , Okazuka Matheus Haruichi , Cunha Matheus Luís Oliveira , de Figueiredo Paulo Alexandre Monteiro
Published: February 2024

The aim of this study was to investigate the morpho-physiological responses of tomato and bell pepper plants when specific nutrients were restricted. The study was conducted in a greenhouse under controlled environmental conditions and used hydroponic solution as the growth medium, with the nutrient solution being replaced as needed. Treatments consisted of a control treatment that included all nutrients at optimal concentrations and the suppression of magnesium (Mg), boron (B), zinc (Zn), and iron (Fe) for both tomato and bell pepper. The experimental design followed a completely randomized design, with a 2 (crops) × 5 (treatments) factorial scheme replicated four times. The results of this study showed that suppression of Fe had the most pronounced negative effect on the morphology and physiology of tomatoes and bell peppers and caused a reduction in parameters associated with gas exchange, leading to the development of interveinal chlorosis in the leaves. The suppression of Mg had the second most notable negative effects, with similar deficiency symptoms observed in the plant leaves as observed for the absence of Fe. While the suppression of B and Zn were less prominent compared to Fe and Mg, they still resulted in tissue malformation in the shoot apices and reductions in gas exchange and negatively impacted the morphological parameters evaluated. Therefore, our study provided important insights on how Mg, B, Zn, and Fe depletion affects tomato and bell pepper physiology and its impacts on tomato and bell pepper morphology.
Energy Labels and Consumer Attitudes: A Study among University Staff
Authors: Durmus Senyapar Hafize Nurgul , Duzgun Bilal , Boran Fatih Emre
Published: February 2024

This study investigates energy label awareness among Gazi University staff, exploring the influence of demographic factors on attitudes and perceptions. Using the Theory of Planned Behavior (TPB), the research examines individual attitudes, subjective norms, and perceived behavioral control in shaping energy efficiency awareness. A cross-sectional survey of academic and administrative staff reveals significant differences in awareness across demographic groups. Gender-specific variations in attitudes towards energy-efficient products are evident, with the greatest difference observed between female (M = 3.93, SD = 1.16) and male staff (M = 3.58, SD = 1.30) on Capacity (I-11) (Z = −2.805, p = 0.005 < 0.05). Education level also significantly influences awareness scores, particularly on the status symbol item (I-18) (χ2 = 24.543, p = 0.00 < 0.05). These findings, analyzed through Wilcoxon Rank Sum and Kruskal–Wallis Tests, provide nuanced insights into the demographic factors impacting energy label awareness. Interpretation of the findings on the complex relationship between demographic characteristics and energy label awareness with TPB provided valuable insights. The practical implications of the study highlight the imperative for tailored communication strategies and targeted interventions to raise awareness among different staff groups. By addressing these nuanced factors, the study significantly contributes to the development of effective energy policies, fostering a sustainable and energy-conscious academic community.