Miracle-dz/UniFAR-FTUs huggingface dataset:
Devil is in the detail: behaviorally explicit habitat selection by the Critically Endangered great Indian bustard

Habitat management to accommodate ecological needs of threatened species can help abate biodiversity decline. Some species require contrasting microhabitats for different functions, and may prefer patches with ample, diverse microhabitats. We examined this problem for the Critically Endangered great Indian bustard Ardeotis nigriceps in 175 km2 breeding habitat in Kachchh, India. We developed behaviorally explicit resource selection functions (RSFs) by comparing used vs. available microhabitats using binomial generalized linear models that tested hypothesized habitat responses in an information theoretic framework. We identified suitable resource units based on fitted RSF values. We examined if availability of complementary resource units influenced density/usage at the patch level, using line transect distance sampling. Birds preferred agro-vegetation mixture, grassland, high fruit abundance and intermediate grazing density, and they avoided Prosopis thickets for foraging. They preferred moderately tall sward for day resting but shorter sward and less Prosopis for roosting. Nesting females preferred grasslands with relatively tall sward and abundant insects, while displaying males preferred grasslands with shorter sward, far from settlements. Thus, microhabitat selection differed between behaviors and differed from habitat availability. The RSF without behavioral segregation failed to capture these nuances and was non-informative for habitat management. Density/usage at the patch level was correlated with the availability of complementary microhabitats. Thus, protected area management to accommodate diverse life-history requirements may reduce species’ movements over large hostile landscapes and associated mortality. Overall, species requiring complementary microhabitats will benefit from management that promotes habitat heterogeneity. However, habitat use analysis based on behaviorally inexplicit occurrence cannot capture the habitat quality of such species.
Promoting Lactobacillus casei and Bifidobacterium adolescentis survival by microencapsulation with different starches and chitosan and poly L‐lysine coatings in ice cream

In this research, microencapsulation of the probiotics Lactobacillus casei ATCC 39392 and Bifidobacterium adolescentis ATCC 15703 was performed using calcium alginate, wheat, rice, and high-amylose corn (Hylon VII) starches along with chitosan and poly L-lysine coatings. The effect of microencapsulation on the survival and sensory properties of ice cream over 100 days at −30 °C was evaluated. Scanning electron and optical microscopy were employed to measure capsule size and morphology. The results suggested that the survival of probiotics is increased by microencapsulation. Coating the capsules with chitosan and poly L-lysine led to enhanced bacterial viability and an increase in the size of microcapsules. Among different starches, Hylon starch enhanced the survival of probiotics at low temperatures the most. Furthermore, the addition of probiotics in free and encapsulated states did not have a significant effect on the sensory properties, or pH levels of the final product during storage (p > .05). Practical applications Microencapsulation using various hydrocolloids is a commonly used method for enhancing probiotic survival in ice cream during the frozen storage. This study indicates that the microencapsulation of probiotics can enhance probiotic survival in ice cream after 100 days of storage at −30 °C. Chitosan and poly L-lysine coatings significantly improved the survival of encapsulated probiotics during the storage of ice cream. This improvement is attributed to the role of Hylon starch in creating more integrated microcapsule structure. Moreover, sensory evaluation of ice cream revealed that inoculation with the probiotic culture, in either the encapsulated or the free-state, had no significant effect on texture, color, flavor, taste, or general sensory characterization of ice cream during the storage period at −30 °C (p > .05).
Optimal and Heuristic Approaches to Modulo Scheduling With Rational Initiation Intervals in Hardware Synthesis

A well-known approach for generating custom hardware with high throughput and low resource usage is modulo scheduling, in which the number of clock cycles between successive inputs [the initiation interval (II)] can be lower than the latency of the computation. The II is traditionally an integer, but in this article, we explore the benefits of allowing it to be a rational number. A rational II can be interpreted as the average number of clock cycles between successive inputs. Since the minimum rational II can be less than the minimum integer II, higher throughput is possible; moreover, allowing rational IIs gives more options in a design-space exploration. We formulate rational-II modulo scheduling as an integer linear programming (ILP) problem that is able to find latency-optimal schedules for a fixed rational II. We also propose two heuristic approaches that make rational-II scheduling more feasible: one based on identifying strongly connected components in the data-flow graph, and one based on iteratively relaxing the target II until a solution is found. We have applied our methods to a standard benchmark of hardware designs, and our results demonstrate an average speedup with respect to II of $1.24\times $ in 35% of the encountered scheduling problems compared to state-of-the-art formulations.
Probability Calculation of Pollution Flashover on Insulators and Analysis of Environmental Factors

Insulator pollution flashover occurs frequently and is harmful to the power transmission and distribution network. But the randomness of the pollution flashover and the complex influencing factors make it difficult to be predicted. The objective of this paper is to study the mechanism of the discharging on insulator surfaces and design a the calculation method which derives flashover probability. By calculating the distorted electric field in the initial streamer discharge quantitatively and combining it with the equivalent circuit of the insulator surface, the initial discharge voltage is derived. By analyzing the change in power input and dissipation in the process of the arc discharge, we propose the criterion on arc development and extinction, and the critical flashover conductivity of the insulator is obtained. Based on the probability density function, the behavior of the factors on the critical flashover conductivity is described, and the probability of insulator pollution flashover is calculated under different environmental conditions. In the validation experiment, the measured initial discharge voltage and pollution flashover ratio are close to the calculated values. The methods proposed in this paper could be used in the quantitative calculation of the initial discharge voltage and the prevention of the pollution flashover on insulators.
Asteroid Observations from the Transiting Exoplanet Survey Satellite: Detection Processing Pipeline and Results from Primary Mission Data

The Transiting Exoplanet Survey Satellite (TESS) is a NASA Explorer-class mission designed for finding exoplanets around nearby stars. TESS image data can also serve as a valuable resource for asteroid and comet detection, including near-Earth objects (NEOs). In order to exploit the TESS image data for moving object detection and potential object discovery, our team has developed an image processing pipeline as part of the Lincoln Near-Earth Asteroid Research (LINEAR) program, sponsored by the NASA NEO Observations Program. The LINEAR-TESS pipeline is currently in operation and reporting asteroid observations to the Minor Planet Center. In this paper we discuss the algorithms and methodology utilized to push the limits of the astrometric accuracy and photometric sensitivity of the TESS instrument for asteroid detection without a priori information on the ephemerides of the objects, and report on observation statistics from the first two years of TESS mission data.
Optimization of Cellulase Production from Newly Isolated Bacillus sp. Y3

Cellulose, a major constituent of plant cell wall, is the most abundant biological polymer on earth. The use of various cellulolytic microorganisms for the bioconversion of cellulose into value added products has attracted a worldwide attention. Hence the present work was aimed to isolate new cellulase producing microorganisms and further to investigate the effect of nutritional and process parameters on cellulase production from selected isolated culture. Out of 20 cellulase producing bacterial strains isolated during the study, Y3 isolate was found to be best for the production of cellulase enzyme. This isolate was then characterized for its morphological and biochemical characters and identified as Bacillus sp. Y3. The effect of different parameters like carbon sources, nitrogen sources, temperature, pH, inoculum concentration and incubation time was monitored with selected strain for cellulase production. The maximum FPase and CMCase activity of Bacillus sp. Y3 was 6.84 IU/mL and 7.82 IU/ mL, respectively, when the basal media of pH 7 containing CMC (1%, w/v) and peptone (1%, w/v) was inoculated with 2% (v/v) inoculum and incubated at 37°C for 96 hours at 120 rpm. The FPase (6.84 IU/mL) and CMCase activity (7.82 IU/mL) obtained after optimization was much higher than FPase (1.97 IU/mL) and CMCase activity (2.48 IU/ mL) before optimization.
A Loop Gain-Based Technique for Online Bus Impedance Estimation and Damping in DC Microgrids

In modern dc microgrids, several feedback-controlled power electronic converters are connected to the common dc bus. Although the control loops of each individual converter are designed with good stability margins, the interconnection of multiple source and load converters can cause stability and performance concerns, due to potential interactions. Therefore, in order to ensure the desired dynamic performance of the interconnected power converter system, an interesting approach is to perform online stability monitoring of the dc bus, and to properly damp the dc bus impedance, which has been demonstrated to ensure system-level stability and performance. In order to accomplish that, this article first derives a representation of the dc bus impedance in terms of voltage (or droop) loop gain of the source-side converter. Second, under certain simplifying assumptions it provides an estimate for the peak value of bus impedance—an indicator of system dynamic behavior— based on the phase margin. Third, it proposes to continuously monitor the peak value of bus impedance by only injecting a single sinusoid in the voltage (or droop) loop. The monitored value can then be used to autotune the voltage regulator, in order to keep the bus impedance in a well-known allowable impedance region. The proposed monitoring and stabilization technique eliminates the need for the time consuming and memory intensive impedance measurement tasks. This technique is verified by simulation and experimental results on a laboratory prototype system of interconnected power converters.
Contribution of Chemical Methods to the Study of Nanostructure of Ultrafine and Amorphous Materials

Controlling the hydrolysis conditions of the solution TiOSO4•xH2SO4•yH2O, the h-TiO2 and A-TiO2 single phases were prepared in amorphous/crystalline state. With scanty structural and electron microscopy data, the unique capability of differential dissolution method was used to perform quantitative phase analysis of the samples and identify phases where two from them (TiO)(HSO4)0.4(OH)and TiO(OH)2 were found to be amorphous. New results were obtained that the amorphous TiO(OH)2 is transformed to ~ 5-nm crystallites TiO2-x•0.95H2O which then turned into ~ 3-nm crystallites TiO2•0.25H2O when drying the gels at 90°C. New structural models for the crystallites were proposed explaining differences in their chemical and thermal characteristics.
The Effect of Blended Learning on Student Learning Outcomes in Calculus Vector Course

Rapid development of technology has become an inseparable part of life. This poses a challenge for the world of education to be able to take advantage of technological developments in achieving educational goals. However, switching from a direct learning model to technology-based learning requires a lot of effort and money. However, this can be started with the Blended Learning Model. This study aims to analyse whether student learning outcomes are better with the application of Blended Learning using e-learning and to describe how student learning activities with the Blended Learning model. This type of research is a combination of quasy-experiment and descriptive research. The research data are the value of the midterm exam and the final semester test scores after the implementation of the learning Blended Learning model which will be analysed. Therefore, it can be compared students’ learning outcomes using the Blended Learning model with student learning outcomes with the conventional learning model. Based on the results of data analysis, it can be concluded that the N-gain test results obtained from the control class are better than the experimental class, which means that the use of the Blended Learning model is less effective in improving student learning outcomes in vector calculus subjects.
Correlation studies in seedling and reproductive stage salinity tolerance in rice (Oryza sativa L.) under salinity

Salinity is a major abiotic stress limiting rice productivity worldwide. The present study had 234 F2:3 population of a salt-tolerant donor Indra (MTU 1061) in the genetic background of Sri Druthi (MTU 1121) to elucidate the genetic basis of seedling and reproductive stage salinity tolerance. The F2:3 population were evaluated under salt stress at seedling stage (EC 6 &12 dSm-1) and reproductive stage (EC 6 & 12 dSm-1). At seedling stage, salt injury score had positive significant correlation with shoot Na+ concentration and Na/K ratio while it was negative & significant with K+ concentration, shoot length, root length and shoot dry weight. This indicated that homeostasis between Na+ and K+, plays a key role in the seedling stage tolerance to salt stress. In reproductive stage grain yield per plant play pivotal role for salinity tolerance comparative to remaining parameters such as number of spikelets, filled spikelets and unfilled spikelets. Results showed positive significant correlation of grain yield with days to flowering, number of total grains and productive tillers while it was negative significant with panicle length. The results of this study confirmed that salinity tolerance at the seedling and reproductive stages are independent to each other.
Spectral detection of nematodes in soybean at flowering growth stage using unmanned aerial vehicles

ABSTRACT: Soybean is one of the main crop species grown in the world. However, there is a decline in productivity due to the various types of stress, including the nematodes Heterodera glycines and Pratylenchus brachyurus. The objectives were to determine the best spectral band for detecting H. glycines and P. brachyurus at the beginning of flowering (R1). Soil and root sampling was conducted at nine sampling sites in each of the five nematode-infested regions, totaling 45 sampling points. Flights were made at all regions using Phantom 4 Advanced, Sequoia and 14-band customized Sentera. For H. glycines, the red spectral band best explained the variability on soil and root nematode counts as well as the second stage of juveniles in soil. For P. brachyurus, Sentera RedEdge best explained the variability in root nematode counts and Sequoia NIR best explained soil juveniles. A multiple linear regression model using spectral data for detecting P. brachyurus and H. glycines improved R² compared to simple linear regressions. At flowering growth stage (R1), soybean spectral reflectance was associated with the number of H. glycines and P. brachyurus on soil and roots using low-cost and multispectral sensors.
A Measurement Model of Value of Data for Decision Making in the Digital Era

: Despite burgeoning opportunities for data-driven decisions, research shows that decision makers are failing to make sense of data within a broader context of organisational change which presents the following pertinent questions: 1) How can decision makers measure the value of data by giving a holistic account? ; 2) How should the organisation-specific blending of machine and human rationality be factored in the measurement model? This study tackles these questions by proposing a novel approach that combines system dynamics and the ability to incorporate data science methods. In addition to a conceptual description, this paper also describes a feasibility test conducted on a small-scale prototype set in a supply chain context. The results show that the use of sophisticated models that have a local scope (‘locally rational’) might have unintended global consequences. It underscores the need for a holistic model in the decision makers’ toolkit providing the ability to run targeted simulations to assess digital investments.
The Mediating Role of Offline Political Participation in the Relationship Between Social Capital and Online Political Participation in Taiwan

This study aims to explore how bonding and bridging social capital in affecting online political participation through offline political participation. This study tests the mediating role of offline political participation in the relationship between two types of social capital and online participation, and examines the mobilization and reinforcement hypotheses by analyzing a nationally-representative adult sample in Taiwan. Results suggest that offline political participation mediates the relationship between two types of social capital and online participation. The findings provide more support for a resource reinforcement hypothesis rather than a mobilization hypothesis.
On gaps of clinical diagnosis of dementia subtypes: A study of Alzheimer’s disease and Lewy body disease

Introduction Alzheimer’s disease (AD) and Lewy body disease (LBD) are the two most common neurodegenerative dementias and can occur in combination (AD+LBD). Due to overlapping biomarkers and symptoms, clinical differentiation of these subtypes could be difficult. However, it is unclear how the magnitude of diagnostic uncertainty varies across dementia spectra and demographic variables. We aimed to compare clinical diagnosis and post-mortem autopsy-confirmed pathological results to assess the clinical subtype diagnosis quality across these factors. Methods We studied data of 1,920 participants recorded by the National Alzheimer’s Coordinating Center from 2005 to 2019. Selection criteria included autopsy-based neuropathological assessments for AD and LBD, and the initial visit with Clinical Dementia Rating (CDR) stage of normal, mild cognitive impairment, or mild dementia. Longitudinally, we analyzed the first visit at each subsequent CDR stage. This analysis included positive predictive values, specificity, sensitivity and false negative rates of clinical diagnosis, as well as disparities by sex, race, age, and education. If autopsy-confirmed AD and/or LBD was missed in the clinic, the alternative clinical diagnosis was analyzed. Findings In our findings, clinical diagnosis of AD+LBD had poor sensitivities. Over 61% of participants with autopsy-confirmed AD+LBD were diagnosed clinically as AD. Clinical diagnosis of AD had a low sensitivity at the early dementia stage and low specificities at all stages. Among participants diagnosed as AD in the clinic, over 32% had concurrent LBD neuropathology at autopsy. Among participants diagnosed as LBD, 32% to 54% revealed concurrent autopsy-confirmed AD pathology. When three subtypes were missed by clinicians, “No cognitive impairment” and “primary progressive aphasia or behavioral variant frontotemporal dementia” were the leading primary etiologic clinical diagnoses. With increasing dementia stages, the clinical diagnosis accuracy of black participants became significantly worse than other races, and diagnosis quality significantly improved for males but not females. Discussion These findings demonstrate that clinical diagnosis of AD, LBD, and AD+LBD are inaccurate and suffer from significant disparities on race and sex. They provide important implications for clinical management, anticipatory guidance, trial enrollment and applicability of potential therapies for AD, and promote research into better biomarker-based assessment of LBD pathology.
Is Suicide of Older Adults With Dementia Preventable? Evaluation of the Effect of Long-term Care Insurance System

Background: South Korea has the highest older adults’ suicide rate in the world. This study proposed a multifaceted policy to reduce the suicide risk among older adults with dementia by evaluating the effectiveness of the expanded long-term care insurance coverage.Methods: About 62,282 older adults with dementia were selected as study samples from the National Health Insurance Service’s “Older Adults Cohort DB (2002 to 2015). ” This study confirmed how the demographic characteristics, health status, and the long-term care services (LTCS) of older adults with dementia affect their suicide. Data analysis was conducted with the Kaplan-Meier, Cox-regression to represent the yearly survival curve from 2002 to 2015, and the suicide rate was identified by demographic characteristics, health status, and policy. Also, difference-in-differences (DID) estimation was conducted to analyze the effect of LTCS on suicide rates by comparing statuses before and after 2014.Results: The results revealed statistically significant differences in sex, activities of daily living, cognitive ability, caregivers, and use of LTCS (Log-rank test p<0.001). The suicide risk of older adults using LTCS was about 0.256 times lower than those who did not use it (p<.001), after adjusting controls. Regarding the policy effect of LTCS, their suicide rate increased after the expansion of dementia grade (OR=2.131, 95% CI=1.061-4.280) but was still lower among LTCS users than non-users (OR=0.296, 95% CI=0.183-0.478). The interaction term indicating whether older adults with dementia use LTCS after the expansion of dementia grade was not statistically significant. Conclusions: This study not only identified differences in suicide rates depending on the sex, ADL, and type of caregiver at the individual level, but also confirmed that national policies and long-term care services could protect their lives. It highlights the importance of national level management to prevent suicide among older adults with dementia and offers effective policy suggestions.