bluuebunny/crossref_metadata_2025_split huggingface dataset:
A global dataset of experimental intercropping and agroforestry studies in horticulture
Authors: Paut Raphaël , Garreau Léa , Ollivier Guillaume , Sabatier Rodolphe , Tchamitchian Marc 
Published: January 2024

AbstractIntercropping and agroforestry systems have been increasingly well studied and documented. Yet, so far, no dataset has provided a systematic synthesis of existing data on intercropping experiments in the specific field of horticulture. A systematic literature search was carried using search terms and applied to Web of Science. The resulting dataset includes data from field experiments published in 191 articles covering experiments worldwide, between 1982 and 2022. The selected experiments cover five continents and involved 118 different crop species. Through manual extraction of information from publications, the dataset includes (i) general information on the articles; (ii) experimental site soil and climate conditions; (iii) descriptions of intercropping designs; (iv) crop management practices; (v) measurements of sole crop and intercrop yields and (v) Land Equivalent Ratios. The dataset is arranged in an easily reusable spreadsheet with columns as variables (n = 45) and rows as treatment (n = 1544). The dataset is freely reusable and updateable. We expect that it will provide valuable information for statistical analysis, modeling and innovative farming system design based on intercropping.
CAS Landslide Dataset: A Large-Scale and Multisensor Dataset for Deep Learning-Based Landslide Detection
Authors: Xu Yulin , Ouyang Chaojun , Xu Qingsong , Wang Dongpo , Zhao Bo , Luo Yutao 
Published: January 2024

AbstractIn this work, we present the CAS Landslide Dataset, a large-scale and multisensor dataset for deep learning-based landslide detection, developed by the Artificial Intelligence Group at the Institute of Mountain Hazards and Environment, Chinese Academy of Sciences (CAS). The dataset aims to address the challenges encountered in landslide recognition. With the increase in landslide occurrences due to climate change and earthquakes, there is a growing need for a precise and comprehensive dataset to support fast and efficient landslide recognition. In contrast to existing datasets with dataset size, coverage, sensor type and resolution limitations, the CAS Landslide Dataset comprises 20,865 images, integrating satellite and unmanned aerial vehicle data from nine regions. To ensure reliability and applicability, we establish a robust methodology to evaluate the dataset quality. We propose the use of the Landslide Dataset as a benchmark for the construction of landslide identification models and to facilitate the development of deep learning techniques. Researchers can leverage this dataset to obtain enhanced prediction, monitoring, and analysis capabilities, thereby advancing automated landslide detection.
Drought Atlas of India, 1901–2020
Authors: Chuphal Dipesh Singh , Kushwaha Anuj Prakash , Aadhar Saran , Mishra Vimal 
Published: January 2024

AbstractIndia has been considerably affected by droughts in the recent past. Despite the considerable impacts of droughts on agriculture and water resources, long-term datasets to examine droughts and their consequences at appropriate spatial and temporal scales have been lacking in India. Datasets that provide drought information are mostly available for a short period and at coarser resolutions, therefore, these do not comprehend the information regarding the major droughts that occurred in the distant past at administrative scales of decision-making. To fill this critical gap, we developed the high-resolution (0.05°) and long-term monthly precipitation and temperature datasets for the 1901–2021 period. We used long-term high-resolution precipitation and temperature to estimate droughts using standardized precipitation and evapotranspiration index (SPEI). As SPEI considers the role of air temperature in drought estimation, it can be used to examine meteorological, agricultural, and hydrological droughts. Using high-resolution SPEI, we developed drought atlas for India (1901–2020) that can provide comprehensive information on drought occurrence, impacts, and risks in India.
Dynamical behavior of solitons of the (2+1)-dimensional Konopelchenko Dubrovsky system
Authors: Hussain A. , Parveen T. , Younis B. A. , Ahamd Huda U. M. , Ibrahim T. F. , Sallah Mohammed 
Published: January 2024

AbstractUtilizing nonlinear evolution equations (NEEs) is common practice to establish the fundamental assumptions underlying natural phenomena. This paper examines the weakly dispersed non-linear waves in mathematical physics represented by the Konopelchenko-Dubrovsky (KD) equations. The $$(G^\prime /G^2)$$

(

G
′

/

G
2

)

-expansion method is used to analyze the model under consideration. Using symbolic computations, the $$(G^\prime /G^2)$$

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′

/

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2

)

-expansion method is used to produce solitary waves and soliton solutions to the $$(2+1)$$

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-dimensional KD model in terms of trigonometric, hyperbolic, and rational functions. Mathematica simulations are displayed using two, three, and density plots to demonstrate the obtained solitary wave solutions’ behavior. These proposed solutions have not been documented in the existing literature.
Home-based monitoring of persons with advanced Parkinson’s disease using smartwatch-smartphone technology
Authors: Fay-Karmon Tsviya , Galor Noam , Heimler Benedetta , Zilka Asaf , Bartsch Ronny P. , Plotnik Meir , Hassin-Baer Sharon 
Published: January 2024

AbstractMovement deterioration is the hallmark of Parkinson’s disease (PD), characterized by levodopa-induced motor-fluctuations (i.e., symptoms’ variability related to the medication cycle) in advanced stages. However, motor symptoms are typically too sporadically and/or subjectively assessed, ultimately preventing the effective monitoring of their progression, and thus leading to suboptimal treatment/therapeutic choices. Smartwatches (SW) enable a quantitative-oriented approach to motor-symptoms evaluation, namely home-based monitoring (HBM) using an embedded inertial measurement unit. Studies validated such approach against in-clinic evaluations. In this work, we aimed at delineating personalized motor-fluctuations’ profiles, thus capturing individual differences. 21 advanced PD patients with motor fluctuations were monitored for 2 weeks using a SW and a smartphone-dedicated app (Intel Pharma Analytics Platform). The SW continuously collected passive data (tremor, dyskinesia, level of activity using dedicated algorithms) and active data, i.e., time-up-and-go, finger tapping, hand tremor and hand rotation carried out daily, once in OFF and once in ON levodopa periods. We observed overall high compliance with the protocol. Furthermore, we observed striking differences among the individual patterns of symptoms’ levodopa-related variations across the HBM, allowing to divide our participants among four data-driven, motor-fluctuations’ profiles. This highlights the potential of HBM using SW technology for revolutionizing clinical practices.
Evaluating the hidden potential of deashed biochar in mitigating salinity stress for cultivation of fenugreek
Authors: Huang Shoucheng , Huang Ping , Hareem Misbah , Tahzeeb-ul-Hassan Muhammad , Younis Uzma , Dawar Khadim , Fahad Shah , Salmen Saleh H. , Ansari Mohammad Javed , Danish Subhan 
Published: January 2024

AbstractSoil salinity, the second most prominent cause of land degradation after soil erosion, has posed a persistent challenge to agriculture. Currently, approximately 1 billion hectares of Earth's land surface, equivalent to 7%, are affected by salinity. While biochar has proven effective in mitigating salinity stress, the specific role of deashed biochar in salinity mitigation has not been thoroughly explored. Therefore, this study was conducted to investigate the impact of four levels of deashed biochar (0%, 0.4%, 0.8%, and 1.2%) on the growth and physiological attributes of Fenugreek under both non-saline conditions (2.54 dS/m EC) and salinity stress conditions (5.46 dS/m EC). The results revealed a notable enhancement in various parameters under salinity stress. Compared to the control, the application of 1.20% deashed biochar led to a significant increase in shoot fresh weight (30.82%), root fresh weight (13.06%), shoot dry weight (17.43%), root dry weight (33.44%), shoot length (23.09%), and root length (52.39%) under salinity stress. Furthermore, improvements in internal CO2 concentration (9.91%), stomatal conductance (15.49%), photosynthetic rate (25.50%), and transpiration rate (10.46%) were observed, validating the efficacy of 1.20% deashed biochar in alleviating salinity stress. The study also demonstrated a significant decrease in the activities of oxidative stress markers such as peroxidase (POD), superoxide dismutase (SOD), catalase (CAT), ascorbate peroxidase (APX), electrolyte leakage, and malondialdehyde (MDA). Simultaneously, there was an increase in the concentrations of essential nutrients, namely nitrogen (N), phosphorus (P), and potassium (K), in both shoot and root tissues. These findings collectively suggest that deashed biochar, particularly at a concentration of 1.20%, is recommended for achieving enhanced crop production under conditions of salinity stress.
Association study between genetic polymorphisms in MTHFR and stroke susceptibility in Egyptian population: a case–control study
Authors: El-khawaga Omali Y. , Al-azzawy Mohammed F. , El-Dawa Aliaa N. , ElSaid Afaf M. , Mustafa Wessam , Saad Mariam 
Published: January 2024

AbstractStroke is a major global disability cause, and genetic variables for multifactorial illnesses like stroke are crucial for precision medicine. The purpose of this study is to see if genetic variants in the MTHFR gene are associated with a higher risk of ischemic stroke among the Egyptian population. A case–control study was conducted at Mansoura University Hospital, involving 100 stroke patients and 150 healthy volunteers as the control group. Peripheral blood genomic DNA was isolated and single-nucleotide polymorphisms were genotyped using ARMS-PCR. The CT and TT genotypes of the C677T gene polymorphism exhibited substantial risks for having stroke disease [(OR 3.856; P ≤ 0.001); (OR 4.026; P ≤ 0.001), respectively]. The T allele was significantly more prevalent among patients compared to controls. (OR 2.517; (P = 0.001)). The over-dominant and dominant models demonstrated a substantial relationship between stroke groups at risk of developing stroke but not the Recessive model. An extensive connection was found between the MTHFR A1298C and stroke danger in three different inheritance models: dominant (CC + CA vs. AA), over-dominant (AA + CC vs AC), and allelic (C allele) (P < 0.001). A highly significant difference in blood pressure, total cholesterol, and triglycerides levels was found between patients and control. While there was no meaningful link discovered between genetic polymorphism with SBP, DBP, TG, LDL, VLDL among stroke group (P > 0.05 for each) except the CC genotype that was significantly associated with lower levels of TC and HDL when compared to CT + TT genotypes. The study evaluates a strong link among MTHFR mutations in genes and the probability to get stroke. The research significantly supports the use of MTHFR ((rs1801133) and (rs1801131) variations in stroke prediction.
Evaluating the impact of a short bout of stair-climbing on creative thinking in a between-subjects pretest posttest comparison study
Authors: Kawashima Chihiro , Chen Chong , Hagiwara Kosuke , Mizumoto Tomohiro , Watarai Mino , Koga Takaya , Higuchi Fumihiro , Fujii Yuko , Okabe Emi , Nakagawa Shin 
Published: January 2024

AbstractRecent studies have indicated potential links between short bouts of physical activity like stair-climbing and enhanced creative thinking. However, previous research featured limitations, such as using an uncommon 3 flights round-trip design and lacking baseline creative thinking evaluations. To rectify these limitations and build a more comprehensive understanding, the present study adopts a between-subjects pretest posttest comparison design to scrutinize the effects of ascending stair-climbing on both divergent and convergent thinking. 52 subjects underwent a pretest, followed by random assignment to one of four interventions: ascending stair-climbing for 2, 5, or 8 flights, or taking an elevator for 8 flights, before progressing to a posttest. The results revealed a notable improvement in convergent thinking, measured by the increased number of solved matchstick arithmetic problems (d = 1.165), for participants who climbed 2 flights of stairs compared to those who took the elevator. However, climbing 5 or 8 flights showed no such impact on convergent thinking, and stair-climbing, regardless of the number of flights, did not influence divergent thinking. These findings underscore the utility of brief stair-climbing as an accessible means to enhance convergent thinking in everyday settings, providing a nuanced insight into the relationship between physical activity and creative thinking processes.
Optimal water resource allocation considering virtual water trade in the Yellow River Basin
Authors: Wang Hao , Ma Tao 
Published: January 2024

AbstractWater can be redistributed physically and virtually. We explored water allocation optimization to mitigate water stresses by constructing a physical–virtual dual water system and optimizing the 1987 Yellow River water allocation scheme. We calculated the virtual water volume, identified the virtual in-basin, out-of-basin, and export water volumes, and compared the total regional water demand (i.e., combined physical and virtual water volumes) with regional water planetary boundaries to optimize basin water allocation schemes. Virtual water accounted for > 90% of the total regional demands, whereas physical flows did not significantly impact them. Moreover, allocation quotas for Qinghai and Inner Mongolia should be reduced by 0.113 and 1.005 billion m3, respectively, for sustainability. Furthermore, improving the efficiency of water-intensive sectors and limiting virtual water outflows from heavy industry to out-of-basin sectors are vital to water intensification. Increased attention should be directed toward physical–virtual water demands than the current focus on supply-oriented water allocation.
Polarization properties and Umov effect of human hair
Authors: Hamdoh Alaa , Miller Sawyer , Gao Yufei , Zou Yang , Smith Matthew , Jiang Linan , Pau Stanley 
Published: January 2024

AbstractThis study delves into the polarization properties of various hair colors using several techniques, including polarization ray tracing, full Stokes, and Mueller matrix imaging. Our analysis involved studying hair in both indoor and outdoor settings under varying lighting conditions. Our results demonstrate a strong correlation between hair color and the degree of linear polarization. Specifically, light-colored hair, such as white and blond, exhibits high albedo and low DoLP. In contrast, dark hair, like black and brown hair, has low albedo and high DoLP. Our research also revealed that a single hair strand displays high diattenuation near specular reflections but high depolarization in areas with diffuse reflections. Additionally, we investigated the wavelength dependency of the polarization properties by comparing the Mueller matrix under illumination at 450 nm and 589 nm. Our investigation demonstrates the impact of hair shade and color on polarization properties and the Umov effect.
Circulating cell-free DNA correlate to disease activity and treatment response of patients with radiographic axial spondyloarthritis
Authors: Peng Yun , Wu Yuanhui , Chen Shiju , Liu Yuan , Qian Hongyan , He Yan , Huang Heqing , Cai Meimei , Liu Wen , Shi Guixiu 
Published: January 2024

AbstractMicrodamage and its related inflammation contribute to the development of radiographic axial spondyloarthritis (r-axSpA). Inflammation and cell death in damaged tissues are associated with cell-free DNA (cfDNA) release. Here we investigated whether circulating cfDNA could be a potential biomarker for evaluating disease activity and treatment response in r-axSpA. Circulating cfDNA was detected in the discovery and validation cohort with 79 and 60 newly diagnosed r-axSpA patients respectively and 42 healthy controls using the Quant-iT PicoGreen dsDNA reagent and kit. As a result, cfDNA levels were significantly higher in r-axSpA patients compared with healthy controls in the discovery and validation cohort. Moreover, cfDNA levels were positively correlated with CRP, ASDAS-CRP and neutrophil counts. Additionally, non-steroid anti-inflammatory drugs (NSAIDs) combined with disease-modifying anti-rheumatic drugs or tumor necrosis factor inhibitors but not NSAIDs alone could reduce cfDNA levels. Moreover, a decrease of cfDNA levels after treatment was associated with an effective therapeutic response. Intriguingly, patients with higher levels of cfDNA at diagnosis responded better to combination therapy rather than NSAIDs. However, patients with lower levels of cfDNA displayed similar responses to combination or mono-NSAID treatment. In conclusion, circulating cfDNA levels showed a significant correlation with disease activity as well as treatment efficacy in patients with r-axSpA. Moreover, cfDNA at diagnosis might predict the response to different therapy. Consequently, cfDNA may serve as a useful biomarker of inflammation in r-axSpA.
Factors influencing sex ratio at birth in Krosno, Poland
Authors: Nieczuja-Dwojacka Joanna , Marchewka-Długońska Justyna , Budnik Alicja , Wojtowicz Patryk , Giemza Bogdan , Skrzypczyk Bożena , Zvarik Aneta 
Published: January 2024

AbstractThe secondary sex ratio (SSR) is a widely used descriptor that reflects the living conditions and health status during pregnancy. The aim of study was to assess the impact of maternal factors, season of birth, and air pollution with the heating season on the sex ratio at birth in the Subcarpathian population from the Krosno district, Poland. A retrospective study involving 11,587 births was occurred at the John Paul II Podkarpackie Province Hospital in Krosno between 2016 and 2020. Sex of the newborn, the season of their birth, as well as the maternal age, birth order, the interval between births, and the season of birth were analysed. Furthermore, the relationship between the SSR and the level of air pollution during the heating season was investigated. To determine the significance of differences in sex ratios, chi-square analysis and multifactorial regression were used, with a significance level set at p < 0.05. At the chi-square level, all the studied factors indicated a statistically significant relationship with the SSR. However, the regression model used shows that maternal age and birth order were the most important factors in shaping the SSR in the study group.
Renewable and high-purity hydrogen from lignocellulosic biomass in a biorefinery approach
Authors: Elsaddik Majd , Nzihou Ange , Delmas Guo-Hua , Delmas Michel 
Published: January 2024

AbstractUnprecedented efforts are being deployed to develop hydrogen production from bioresources in a circular economy approach, yet their implementation remains scarce. Today’s Challenges are associated with the shortage in the value chain, lack of large-scale production infrastructure, high costs, and low efficiency of current solutions. Herein, we report a hydrogen production route from cellulose pulp, integrating biomass fractionation and gasification in a biorefinery approach. Softwood sawdust undergoes formic acid organosolv treatment to extract cellulose, followed by steam gasification. High-purity hydrogen-rich syngas at a concentration of 56.3 vol% and a yield of 40 gH2/kgcellulose was produced. Char gasification offers the advantage of producing free-tar syngas reducing cleaning costs and mitigating downstream issues. A comprehensive assessment of mass and energy balance along the hydrogen value chain revealed an efficiency of 26.5% for hydrogen production, with an energy requirement of 111.1 kWh/kgH2. Optimizing solvent recovery and valorization of other constituents as added-value products in a biorefinery approach would further improve the process and entice its industrial takeoff.
Deep learning system for true- and pseudo-invasion in colorectal polyps
Authors: Yang Joe , Chen Lina , Liu Eric , Wang Boyu , Driman David K. , Zhang Qi , Ling Charles 
Published: January 2024

AbstractOver 15 million colonoscopies were performed yearly in North America, during which biopsies were taken for pathological examination to identify abnormalities. Distinguishing between true- and pseudo-invasion in colon polyps is critical in treatment planning. Surgical resection of the colon is often the treatment option for true invasion, whereas observation is recommended for pseudo-invasion. The task of identifying true- vs pseudo-invasion, however, could be highly challenging. There is no specialized software tool for this task, and no well-annotated dataset is available. In our work, we obtained (only) 150 whole-slide images (WSIs) from the London Health Science Centre. We built three deep neural networks representing different magnifications in WSIs, mimicking the workflow of pathologists. We also built an online tool for pathologists to annotate WSIs to train our deep neural networks. Results showed that our novel system classifies tissue types with 95.3% accuracy and differentiates true- and pseudo-invasions with 83.9% accuracy. The system’s efficiency is comparable to an expert pathologist. Our system can also be easily adjusted to serve as a confirmatory or screening tool. Our system (available at http://ai4path.ca) will lead to better, faster patient care and reduced healthcare costs.
Variability in proximate composition, phytochemical traits and antioxidant properties of Iranian agro-ecotypic populations of fenugreek (Trigonella foenum-graecum L.)
Authors: Bakhtiar Ziba , Hassandokht Mohammadreza , Naghavi Mohammad Reza , Mirjalili Mohammad Hossein 
Published: January 2024

AbstractFenugreek (Trigonella foenum-graecum L.) is a multi-use annual forage legume crop that is widely used in food products such as syrup, bitter run, curries, stew, and flavoring. In the present study, morphological traits, proximate composition (moisture, crude fibre, protein, fat, carbohydrate, and energy value), total phenol and total flavonoid contents, and antioxidant properties of 31 Iranian agro-ecotypic populations of the plant was investigated. Among the leaf and seed samples studied, the seeds exhibited the high ash (3.94 ± 0.12%), fat (7.94 ± 0.78%), crude fibre (10.3 ± 0.25%), protein (35.41 ± 1.86%), and carbohydrate (50.5 ± 1.90%) content. In general, more energy value (kcal/100 g) was also obtained from the seed (318.88 ± 1.78–350.44 ± 1.27) than leaf samples (45.50 ± 1.32–89.28 ± 0.85). Antioxidant activity and power of leaf samples were ranged from 67.95 ± 0.05‒157.52 ± 0.20 μg/ml and from 45.17 ± 0.01‒361.92 ± 0.78 μmol Fe+2 per g dry weigh, respectively. Positive linear correlations between antioxidant activity and total phenolic compounds were observed. A significant correlation between proximate composition (dependent variable) and some morphological features (independent variable) was observed. Considerable variability in the studied traits among the plant samples can be interestingly used in further food and production systems.