Miracle-dz/UniFAR-FTUs huggingface dataset:
Challenges and limitations of using autonomous instrumentation for measuring in situ soil respiration in a subarctic boreal forest in Alaska, USA

Subarctic and Arctic environments are sensitive to warming temperatures due to climate change. As soils warm, soil microorganisms break down carbon and release greenhouse gases such as methane (CH₄) and carbon dioxide (CO₂). Recent studies examining CO₂ efflux note heterogeneity of microbial activity across the landscape. To better understand carbon dynamics, our team developed a predictive model, Dynamic Representation of Terrestrial Soil Predictions of Organisms’ Response to the Environment (DRTSPORE), to estimate CO₂ efflux based on soil temperature and moisture estimates. The goal of this work was to acquire respiration rates from a boreal forest located near the town of Fairbanks, Alaska, and to provide in situ measurements for the future validation effort of the DRTSPORE model estimates of CO₂ efflux in cold climates. Results show that soil temperature and seasonal soil thaw depth had the greatest impact on soil respiration. However, the instrumentation deployed significantly altered the soil temperature, moisture, and seasonal thaw depth at the survey site and very likely the soil respiration rates. These findings are important to better understand the challenges and limitations associated with the in situ data collection used for carbon efflux modeling and for estimating soil microbial activity in cold environments.
NPK Fertilizer Requirements for Jatropha Zeyheri Indigenous Tea under Microplot Conditions

Effects of NPK fertilizer could have positive or negative effects in relation to growth of crops under certain environments, with minimum findings on how crops react to fertilizers under microplot conditions. Therefore, the objective of this study was to assess the effects of increasing NPK fertilizer rate on Jatropha zeyheri tea growth under microplot conditions. At two-leaf phase, J. zeyheri seedlings were transplanted into 25 cm diameter plastic pots. Each pot was filled with heated pasteurized sandy soil and Hygromix at 3:1 (v/v) ratio and placed in a spacing of 0.30 m × 0.30 m inter-and intra-row spacing. Six treatments constituting NPK fertilizer rates (0, 2, 4, 8, 16 and 32 g) were arranged in a randomized complete block design, with five replications. Treatments were initiated a week after transplanting, and 130 days after that, treatments had highly significant effects on leaf width, contributing 66% in TTV, whereas significant effects were reported on vine length, stem diameter, leaf length and dry root mass contributing 61, 67, 68 and 49% in TTV, respectively. NPK fertilizer rates did not affect chlorophyll content, NDVI, dry shoot mass, number of leaves and leaf area index. Jatropha zeyheri yield variables when exposed to increasing fertilizer rates displayed positive quadratic relations. Use of fertilizers had setbacks when applied inappropriately leading to inconsistent results. However, determining optimum fertilizer requirement for J. zeyheri was a strategical solution for inappropriate application. Jatropha zeyheri fertilizer requirements were optimized at 3.30 g fertilizer/plant, which shows that J. zeyheri requires a minimum amount of NPK fertilizer to stimulate growth.
Nets of conics

Segre's classification of pencils of quadrics is well known, and appears in standard texts such as (1), (2). By contrast, other linear systems of quadrics do not lend them-selves to a similar exhaustive treatment. Here we discuss the simplest case, that of nets of conics. The result is intrinsically interesting, and involves some pleasant geometry. As well as deriving a list of types, and enumerating their properties, we study the elementary geometrical properties of the partition of the space Ω of nets into equivalence classes (or strata). We work over the field ℝ of real numbers, after performing preliminary calculations over ℂ.
Isolation, Characterization and Heavy Metal Tolerance Capacity of Indigenous Fungi: A Case Study of Iron Mine Waste

Received March 05, 2015; Accepted June 23, 2015 Abstract: Rapid urbanization and industrialization without proper environmental planning lead to the discharge of toxic heavy metals into the environment. Biological related technologies may provide an alternative or addition to conventional methods for remediation of the contaminated sample. The current investigation was focused to study the fungal diversity of rhizosphere soil, overburden and tailings samples of the iron mining area of Barbil, Odisha, India. Fifteen fungal strains were isolated from collected sample using serial dilution technique and all the isolated strains were screened for metal tolerance assay. The degree of tolerance of fungi was measured by minimum inhibitory concentration in the presence of different concentration of iron. Tolerance analysis depicts that some are tolerant and sensitive. All isolated fungal strains were tolerant up to 600ppm but species of Aspergillus and Penicillium can tolerate up to 800 and 1000ppm, respectively. Hence, it can be act as a potential agent for bioremediation purpose.
Exploring pearl millet root system and its outcome for drought tolerance

Pearl millet plays an important role for food security in arid regions of Africa and India. Nevertheless, it lags far behind other cereals in terms of genetic improvement. Improving its root system could improve pearl millet tolerance to abiotic constraints (drought and low nutrient availability) and lead to a significant increase in production. The objective of this work is to characterize pearl system root system development in order to produce knowledge for breeding, mainly targeted on tolerance to drought stress occurring at the early growth stages.First, we described the dynamics of early pearl millet root system development and the anatomy of the different root types. This work revealed the existence of three anatomically distinct types for lateral roots. We also showed the existence of variability in primary root growth and lateral root density in a diversity panel derived from cultivated varieties, which opens the possibility to use this existing variability in root system breeding. Our study also revealed a large variability among the growth profiles of lateral roots.To further analyze this diversity, the growth rates of a large number of lateral roots were measured daily and a statistical model developed to classify these lateral roots into three main trends, according to their growth profiles. These three categories distinguish roots with high growth rate that keep on growing after the end of the experiment, roots with intermediate growth rates and roots with low growth rates that quickly stop growing. These different lateral root types are randomly distributed along the primary root and there seem to be no influence of root types on the intervals between successive lateral roots. The three growth types correspond, though imperfectly, to the three anatomical types evidenced in the first chapter. A similar work has been performed on maize, which was used to compare these two phylogenetically close cereals.Finally, we searched for genetic markers associated to primary root growth, a root trait potentially involved in early drought stress tolerance. A large panel of genetically fixed pearl millet inbred lines was phenotyped, confirming the presence of a large variability existing for this trait. These lines were then genotyped by sequencing. Analyses of association between phenotype and genotype are underway.This work provides a precise description of pearl millet root system that was little studied to date. Our data were used for parameterization and testing of functional structural plant models simulating root growth and water transport. The statistical tool developed for the characterization of the different lateral root growth types is an original approach that can be used on other cereals. Finally, results from our association study will reveal new information on the genetic control of root growth and open the way to marker assisted selection for root traits in pearl millet.
Food Selectivity in Juvenile Three-Spined Stickleback Gasterosteus aculeatus L. (Gasterosteidae) at Nursery Grounds in the White Sea

The spatial and temporal variability in the dietary preferences of juvenile three-spined stickleback Gasterosteus aculeatus were studied across the typical coastal habitats of Keret Archipelago, Kandalaksha Bay(the White Sea). The sampling of fish using a beach seine was conducted in the late July–early August period and in late August. Additionally, zooplankton samples were collected to conduct a quantitative assessment of the abundance of potential prey items. The similarity percentage (SIMPER) analysis was applied to the data obtained from the stomach content and revealed the five planktonic taxa most prominently contributing to the diet of juvenile sticklebacks. Among these, the copepod Temora longicornis was the most important prey item at marine sites, while Acartia longiremis dominated the diet of fish in the marine lagoon. The calculation of the selectivity index revealed that some taxa (such as A. longiremis) were always avoided by juvenile fish, whereas the selectivity of some taxa increased in late August. In general, juvenile sticklebacks demonstrated a pronounced individual variation in their selectivity, even when a particular prey item was selected positively during the whole period of study. Our data highlight that despite the predominant consumption of easily available prey by juvenile sticklebacks, they demonstrate taxonomic- and size-specific prey selectivity.
Modeling the Risk Factors of Undernutrition among Children below Five Years of Age in Uganda Using Generalized Structural Equation Models

Introduction: The prevalence of undernutrition among children below five years of age, in Uganda and the world over, remains very high. About 45% of all global deaths among children below five years of age are attributed to undernutrition. A number of studies using different statistical approaches affirm this effect, yet some factors indicate the influence of other factors within the system. This study, therefore, uses a method that demonstrates how different variables feed into each other. Aim: The aim of this study was to establish the major factors associated with an increased likelihood of undernutrition and the paths showing how these risk factors influence undernutrition. Methods: Data from the Uganda Demographic and Health Survey (UDHS, 2016) were used for this study. A sample of 4530 children, whose age, height, and weight measurements were recorded, was considered for this study. Additionally, the study used generalized structural equation models to identify the multifaceted natures and paths of the risk factors that influence undernutrition among children below five years of age. The study relied on the UNICEF 2020 conceptual framework to identify and analyze the direct and indirect effects of these risk factors of undernutrition. Results: From the perspective of a male child, having a perceived small size at birth, a low birth weight, being breastfed for less than 6 months, having no formal education from mothers, limited income-generating opportunities, a low wealth status, and notable episodes of diarrhea were among the key factors associated with an increased likelihood of undernutrition. The identified paths were as follows: (i) Having no education, as this was associated with limited working opportunities and a low income, which increases the likelihood of low household wealth status, hence increasing the chances of undernutrition. (ii) Exposure to a rural setting was associated with an increased likelihood of undernutrition through association with poor and or low employment levels within the rural areas. (iii) A shorter duration of breastfeeding was associated with children in urban areas, resulting in an increased likelihood of undernutrition. (iv) Children aged between 6 and 47 months had a higher likelihood of undernutrition. Conclusions: An approach that addresses and recognizes all these factors at different levels, along the established paths, should be implemented to effectively reduce undernutrition among children below five years of age.
Climate changes and trends over India

Based on the instrumental observations of over a century available in India, attempt is made to study if there is a clear-cut evidence of any climate change or trend over . India with particular reference to rainfall, surface temperature, atmospheric pressure and total ozone. The study concludes that while there are year to year random. fluctuations in these atmospheric variables and there are certain epochal increases and decreases in respect of rainfall and . surface temperature, . there appears to be no systematic climate charge or trend over India. There IS also no evidence of ozone depletion over India.
The ‘Pants-Sign’: A Predictor for Falling in People with Parkinson’s Disease?

Background: A history of falls is the most established predictor of future falls in people with Parkinson’s disease (PD). However, predicting a first fall remains challenging. Objective: To assess whether experiencing difficulties putting on pants while standing is a viable predictor of future falling, and specifically a first fall, in persons with PD. We define this ‘Pants-sign’ as people who resort to putting on their pants only while seated. Methods: 264 persons with PD were included. Information on the Pants-sign, history of falls, disease severity (MDS-UPDRS part III), freezing of gait (N-FOGQ > 0), cognitive function (MoCA), self-reported disability (Schwab & England scale), health-related quality of life (SF-12), Timed-Up-and-Go, and one-legged stance were determined at baseline and after one-year follow-up. The association between the Pants-sign and future falling was examined by univariate logistic regression analysis. A multivariate step-wise logistic regression with forward selection was employed to identify the strongest associations in the entire cohort and a sub-cohort of people without falls in the year prior to baseline. Results: The Pants-sign was univariably associated with a future fall (OR = 2.406, 95% CI [1.313–4.409], p = 0.004]), but was not an independent predictor in the multivariate logistic regression; predictors were higher MDS-UPDRS part III scores (OR = 1.088, 95% CI [1.056–1.121], p < 0.001] and history of falls (OR = 5.696, 95% CI [2.650–12.243], p≤0.001]. For the sub-cohort of people without falls in the previous year (n = 189), the Pants-sign was not associated with future falls. Conclusions: The Pants-sign is simple to assess and is associated with future falling in PD but is not an independent predictor.
Anthropocentrism and Microorganisms: Implications for Biosecurity

The world is changing: both a conventional and a vaccine passport are now needed to travel internationally. Mask mandates, and social distancing are the new norm in a rapidly changing society. These measures were put in place to control the spread of the highly infectious and often fatal Covid-19, caused by a viral agent, a microorganism, a zoonosis, and the cause of death for over 6 million people around the world. Considering this, maintaining biosecurity is important around the world to ensure public health. Biosecurity in New Zealand supposes that people including young people understand different pests and diseases that can harm public health. This qualitative study was conducted to gauge the biosecurity knowledge of 171 young people (14–15-year-olds). Young people were tested on their knowledge about biosecurity related plants, animals, and microorganisms. This paper reports specifically on the results of knowledge of microorganisms of young people. Results show that negative anthropocentric views dominate adolescents understanding of microorganisms and anthropomorphism is widely used to explain microorganism activity. An educational programme, targeted at developing a conceptual understanding about microorganisms starting at primary education may help develop a more educated global citizen, one versed in understanding the biology of microorganisms.
Predicting Nurse Turnover for Highly Imbalanced Data Using the Synthetic Minority Over-Sampling Technique and Machine Learning Algorithms

Predicting nurse turnover is a growing challenge within the healthcare sector, profoundly impacting healthcare quality and the nursing profession. This study employs the Synthetic Minority Over-sampling Technique (SMOTE) to address class imbalance issues in the 2018 National Sample Survey of Registered Nurses dataset and predict nurse turnover using machine learning algorithms. Four machine learning algorithms, namely logistic regression, random forests, decision tree, and extreme gradient boosting, were applied to the SMOTE-enhanced dataset. The data were split into 80% training and 20% validation sets. Eighteen carefully selected variables from the database served as predictive features, and the machine learning model identified age, working hours, electric health record/electronic medical record, individual income, and job type as important features concerning nurse turnover. The study includes a performance comparison based on accuracy, precision, recall (sensitivity), F1-score, and AUC. In summary, the results demonstrate that SMOTE-enhanced random forests exhibit the most robust predictive power in the classical approach (with all 18 predictive variables) and an optimized approach (utilizing eight key predictive variables). Extreme gradient boosting, decision tree, and logistic regression follow in performance. Notably, age emerges as the most influential factor in nurse turnover, with working hours, electric health record/electronic medical record usability, individual income, and region also playing significant roles. This research offers valuable insights for healthcare researchers and stakeholders, aiding in selecting suitable machine learning algorithms for nurse turnover prediction.
BoLA-DRB3 Polymorphism Associated with Bovine Leukemia Virus Infection and Proviral Load in Holstein Cattle in Egypt

Bovine leukemia virus (BLV) is the etiological agent of enzootic bovine leukosis, the most prevalent neoplastic disease of cattle worldwide. The immune response to BLV and disease susceptibility and resistance in cattle are strongly correlated with the bovine leukocyte antigen (BoLA)-DRB3 allelic polymorphism. BLV infection continues to spread in Egypt, in part because the relationships between BLV infection, proviral load in Egypt, and BoLA-DRB3 polymorphism are unknown. Here, we identified 18 previously reported alleles in 121 Holstein cows using a polymerase chain reaction sequence-based typing method. Furthermore, BoLA-DRB3 gene polymorphisms in these animals were investigated for their influence on viral infection. BoLA-DRB3*015:01 and BoLA-DRB3*010:01 were identified as susceptible and resistant alleles, respectively, for BLV infection in the tested Holsteins. In addition, BoLA-DRB3*012:01 was associated with low PVL in previous reports but high PVL in Holstein cattle in Egypt. This study is the first to demonstrate that the BoLA-DRB3 polymorphism confers resistance and susceptibility to PVL and infections of BLV in Holstein cattle in Egypt. Our results can be useful for the disease control and eradication of BLV through genetic selection.
Chemical Compositions of Essential Oil Extracted from Eight Thyme Species and Potential Biological Functions

Thymus is an herbaceous perennial or subshrub of the Lamiaceae family and is widely distributed worldwide. Essential oils extracted from thymus have attracted much attention, owing to their potential biological functions. Here, we evaluated the chemical compositions of eight thyme essential oils (TEOs) using gas chromatography mass spectrometry and assessed their antioxidant activity. The results showed that (1) the main components in eight TEOs were monoterpene hydrocarbons and oxygenated monoterpenes (84.26–92.84%), and the chemical compositions of the TEOs were affected by the specie factor; (2) eight TEOs could be divided into three groups (thymol-, geraniol-, and nerol acetate-types), and thymol was the main type; (3) eight TEOs had some common compounds, such as thymol and p-cymene, which were the main components in seven TEOs; (4) eight TEOs had antioxidant activity, and Thymus pulegioides, Thymus thracicus, and Thymus serpyllum EOs had stronger antioxidant activity than vitamin E (0.07–0.27 fold) at a concentration of 1 mg/mL, while Thymus quinquecostatus and Thymus longicaulis EOs had relatively weak antioxidant activity. In addition, three chemical type standards were used to evaluate potential roles in antibacterial and tumor therapy. The results showed that thymol had strong antibacterial activity against the growth of Escherichia coli and Staphylococcus aureus, and antimigratory activity for A549 cell. Overall, our results can provide a theoretical basis for further exploring the function of natural products from thyme essential oils.
Exploring the gut mycobiome: differential composition and clinical associations in hypertension, chronic kidney disease, and their comorbidity

Background Hypertension (HTN) and chronic kidney disease (CKD) pose significant global health challenges and often coexist, amplifying cardiovascular risks. Recent attention has turned to the gut mycobiome as a potential factor in their pathophysiology. Our study sought to examine the gut fungal profile in individuals with HTN, CKD, and the concurrent HTN+CKD condition, investigating its connections with serum cytokines, renal function, and blood pressure. Methods and materials We investigated three distinct participant groups: a cohort of 50 healthy controls (HC), 50 individuals diagnosed with HTN-only, and 50 participants suffering from both HTN and CKD (HTN+CKD). To facilitate our research, we gathered fecal and blood samples and conducted a comprehensive analysis of serum cytokines. Moreover, fungal DNA extraction was conducted with meticulous care, followed by sequencing of the Internal Transcribed Spacer (ITS) region. Results HTN+CKD patients displayed distinctive fungal composition with increased richness and diversity compared to controls. In contrast, HTN-only patients exhibited minimal fungal differences. Specific fungal genera were notably altered in HTN+CKD patients, characterized by increased Apiotrichum and Saccharomyces levels and reduced Candida abundance. Our correlation analyses revealed significant associations between fungal genera and serum cytokines. Moreover, certain fungal taxa, such as Apiotrichum and Saccharomyces, exhibited positive correlations with renal function, while others, including Septoria, Nakaseomyces, and Saccharomyces, were linked to blood pressure, particularly diastolic pressure. Conclusion Gut mycobiome dysbiosis in individuals with comorbid HTN and CKD differs significantly from that observed in HTN-only and healthy controls. The interactions between serum cytokines, renal function, and blood pressure emphasize the potential impact of the fungal microbiome on these conditions. Additional research is required to clarify the underlying mechanisms and identify therapeutic opportunities associated with mycobiome dysbiosis in HTN and CKD.