Miracle-dz/UniFAR-FTUs huggingface dataset:
When Agile Means Staying: A Moderated Mediated Model

ABSTRACT The design of software development methods focuses on improving task processes, including accommodating changing user requirements and accelerating product delivery. However, there is limited research on how the use of different software development methods impacts IT professionals’ perceptions of organizational mobility. Drawing on concepts from the agile development literature and job characteristics theory, we formulate a moderated mediation model explicating the mechanism and the condition under which agile development use exerts an influence on IT professionals’ intention to stay with their current employer. Specifically, we examine job satisfaction as mediating the effect of using agile development on the intention to stay as well as how the strength of the mediated relationship differs across firms. We test our hypotheses using a sample of 32,389 software developers. We find that job satisfaction fully mediates the effect of using agile development on the intention to stay. The strength of the mediation effect is significantly different for large and small firms.
Broad Host Range Xenotrophic Gene Transfer by Virus-Like Particles from a Hot Spring

The bactericidal effects of "Virus-like particles" ("ST-VLPs") derived from a sulphur-turf microbial mat consisting of the Aquificales bacterium, were examined using Escherichia coli AB1157 and Bacillus subtilis PS9 as recipients. The recipient population was reduced by up to one order of magnitude with transduction frequencies of between 10-3 and 10-4 per particle. Broad host range and xenotrophic behaviour imply that "ST-VLPs" do not fit the current concept of a "virus" with a narrow host range. Such novel VLPs would control the bacterial population, and genetically enhance biodiversity.
A Lightweight Cloud-Assisted Identity-Based Anonymous Authentication and Key Agreement Protocol for Secure Wireless Body Area Network

Recent advancements in ubiquitous technologies, such as an intelligible sensor, wireless communication, internet of things, and cloud computing have enabled the wearable devices to integrate with the wireless body area network (WBAN) for improving the patient's health remotely. Due to the resource-constraint nature of the WBAN, it provides limited services to the patients. Cloud technology has strengthened the WBAN potential by facilitating the storage and computation. However, due to the open nature of the cloud technology and wireless communication, these type of systems encounter several security issues. In this article, we propose an identity-based anonymous authentication and key agreement (IBAAKA) protocol for WBAN in the cloud-assisted environment, which achieves mutual authentication and user anonymity. In the security analysis, we show that under the well-known computational diffie-hellman assumption and random oracle model, the proposed IBAAKA scheme is provably secure, as well as achieves the required security properties. Further, it requires the least computational cost and comparable communication cost with the existing schemes.
Comparative anatomy and morphology of fertile complexes of Prumnopitys and Afrocarpus species (Podocarpaceae) as revealed by histology and NMR imaging, and their relevance to systematics

Fertile complexes (individual reproductive units of ovulate cones) of three Prumnopitys species and Afrocarpus falcatus (Podocarpaceae) were subjected to histological examination and non-destructive NMR imaging. The latter technique allowed the display, frame-by-frame analysis and electronic ‘dissection’ of internal structures such as the number and courses of vascular traces and resin canals and their morphology. Characters of these internal structures distinguished all three Prumnopitys species from each other and thus were shown to be taxonomically diagnostic. Fertile complexes of Prumnopitys andina and P. taxifolia were most similar, possessing simple vascular traces and few unbranched resin canals. Those of P. ferruginea were very different and possessed an interconnected network of resin ducts within the sarcotesta. These findings are congruent with relationships inferred from molecular phylogenetic studies, in which two subclades were recovered within Prumnopitys. The anatomy of the female fertile complexes of Afrocarpus falcatus was very distinct from all Prumnopitys species analysed. Its most distinctive feature was the existence of a complex network of radial vascular strands originating from within the outer layers of the sarcotesta and penetrating the inner layers of the fertile complex. The surface texture and morphology of the sclerotesta of the seed was also unique to each species. © 2004 The Linnean Society of London, Botanical Journal of the Linnean Society, 2004, 145, 295–316.
Recovery Rate of intestinal parasites using conventional methods in Ibadan, Nigeria

Five different techniques were used to diagnose all the 232 stool specimens that came into the Parasitology Department of University College Hospital, Ibadan for a period of six months. A prevalence of 25.0% was obtained in the study. Brine flotation recovered the highest number of parasites; 40 (69.0%), followed by formol ether concentration; 32 (55.2%), Katokatz recovered a total of 28 (48.3%) parasites, but could not recover any protozoan parasite, stoll technique recovered 22 (37.9%) parasites and wet preparation detected the least number of parasites; 12 (20.7%). There was a significant statistical difference among the techniques (χ 2 = 13. 63, P = 0.008). None of the methods could detect all the cases observed in the study alone, thus no single technique was satisfactory as none was equally applicable for trophozoites and cysts of protozoa, eggs or larvae of helminths. Brine flotation technique should be added to the routine diagnostic method (wet preparation), since it significantly detects both helminths and protozoa more than any of the other techniques. Nigerian Journal of Health and Biomedical Sciences Vol. 7 (1) 2008 pp. 42-46
Stator Current Vector Orientation-Based Backstepping Predictive Control of Torque Ripple Minimization for PMSM with consideration of Electrical Loss

Existing research studies on torque ripple suppression mostly ignore the electrical loss of PMSM. However, the electrical loss will not only decrease the operating efficiency but also adversely influence the suppression of torque ripple. This paper attempts to construct a unified framework to suppress torque ripple with consideration of electrical loss. Firstly, a dynamic mathematical model of PMSM under current vector orientation is established with a combination of electrical loss. The constraints that can achieve the control of both torque ripple and electrical loss for PMSM are derived. Then, on the basis of the backstepping control principle, a closed-loop I/f integrative control method under stator current vector orientation is proposed. Meanwhile, this paper also proposes a speed estimation algorithm of PMSM based on the least-squares method to realize wide-range speed identification and an online prediction algorithm for control parameters of backstepping control to enhance the stability of the motor in operation. Both simulations and experiments have been performed to verify the effectiveness of the proposed control method, and the results indicate that torque ripple is suppressed effectively, operating efficiency is significantly improved, and all variables are regulated to track their reference signals correctly and rapidly.
Dietary Diversity and Associated Health Status of Newly Diagnosed Type 2 Diabetic Patients in Jashore Region of Bangladesh

Background: Lack of adequate dietary diversity may contribute to the deterioration of health and nutritional status of newly diagnosed type 2 diabetes mellitus (T2DM) patients. This cross-sectional study was designed to assess the dietary diversity and related health status of 110 newly diagnosed T2DM patients. Methods: The diabetes history of the subjects was collected from the hospital’s e-database. IDDS (individual dietary diversity score) was measured based on the FFQ (food frequency questionnaire) according to the FAO guidelines for measuring household and individual dietary diversity. BMI (body mass index), FBG (fasting blood glucose) level, 2h-PG (two-hour plasma glucose) level, serum creatinine level, and any signs of macro and microvascular diseases were recorded. Results: The mean±SD of IDDS was moderate, 5.74±0.85. About half of the newly diagnosed diabetic patients consumed foods with high diversity. All respondents consumed starchy foods and about half of them did not consume any green leafy vegetables. Younger patients had a lower tendency to take high IDDS diets than the older. About half of individuals were overweight or obese. Higher IDDS and lower BMI, hypertension, serum creatinine, FBG, and 2-HPG were found among males than that of the females. Approximately 35% and 20% patients had microvascular and Current Research in Nutrition and Food Science www.foodandnutritionjournal. org ISSN: 2347-467X, Vol. 08, No. (2) 2020, Pg. 438-453 CONTACT Rajib Kanti Roy rk. roy_nft@just.edu. bd Department of Food and Nutrition Technology, Jashore University of Science and Technology, Jashore-7408, Bangladesh. © 2020 The Author(s). Published by Enviro Research Publishers. This is an Open Access article licensed under a Creative Commons license: Attribution 4.0 International (CC-BY). Doi: http://dx.doi. org/10.12944/CRNFSJ.8. 2.09 Article History Received: 19 October 2019 Accepted: 16 April 2020
A Redescription of the Eel Goby Trypauchenopsis (Gobiidae: Amblyopinae) with Comments on Relationships

The gobioid genus Trypauchenopsis and type species, T. intermedia, are redescribed based on examination of 485 specimens (including the holotype) from various localities in the Indo-West Pacific. The genus is unique in possessing forked middle radials of the ultimate dorsal- and anal-fin pterygiophores, no pleural ribs or only a single pleural rib on the ultimate precaudal vertebra, and caducous, cutaneous, short barbel-like processes scattered on the head. Two species that had been referred to the genus Taenioides (T. jacksoni and T. limicola) are now placed in the synonymy of Trypauchenopsis intermedia. Trypauchenopsis has often been confused with Taenioides or Brachyamblyopus; these three genera along with Gymnoamblyopus, Odontamblyopus, and Pseudotrypauchen are compared and characters to distinguish them are provided. The relationships of Trypauchenopsis to these genera are also discussed.
Characterization of the complete mitochondrial genome of Oriental reed warbler, Acrocephalus orientalis (Aves: Passeriformes), and a comparative analysis with other Sylviidae species

Abstract The complete mitochondrial genome of the Oriental reed warbler, Acrocephalus orientalis, which belongs to the family Sylviidae was determined. The complete mitochondrial genome has a length of 16,971 bp and consists of 13 protein-coding genes, 22 tRNA genes, 2 rRNA genes, and a control region. A. orientalis has a mitochondrial gene arrangement that is typical of vertebrates. Phylogenetic analysis using mitochondrial genomes of 11 related species revealed that A. orientalis is clustered with Acrocephalus scirpaceus and rooted with the other Sylviidae species. This mitochondrial genome provides an important resource for addressing taxonomic issues and studying molecular evolution.
Track: a Multi-Modal Deep Architecture for Head Motion Prediction in 360° Videos

Head motion prediction is an important problem with 360° videos, in particular to inform the streaming decisions. Various methods tackling this problem with deep neural networks have been proposed recently. In this article, we introduce a new deep architecture, named TRACK, that benefits both from the history of past positions and knowledge of the video content. We show that TRACK achieves state-of-the-art performance when compared against all recent approaches considering the same datasets and wider prediction horizons: from 0 to 5 seconds.
Accurate Screening of COVID-19 Using Attention-Based Deep 3D Multiple Instance Learning

Automated Screening of COVID-19 from chest CT is of emergency and importance during the outbreak of SARS-CoV-2 worldwide in 2020. However, accurate screening of COVID-19 is still a massive challenge due to the spatial complexity of 3D volumes, the labeling difficulty of infection areas, and the slight discrepancy between COVID-19 and other viral pneumonia in chest CT. While a few pioneering works have made significant progress, they are either demanding manual annotations of infection areas or lack of interpretability. In this paper, we report our attempt towards achieving highly accurate and interpretable screening of COVID-19 from chest CT with weak labels. We propose an attention-based deep 3D multiple instance learning (AD3D-MIL) where a patient-level label is assigned to a 3D chest CT that is viewed as a bag of instances. AD3D-MIL can semantically generate deep 3D instances following the possible infection area. AD3D-MIL further applies an attention-based pooling approach to 3D instances to provide insight into each instance’s contribution to the bag label. AD3D-MIL finally learns Bernoulli distributions of the bag-level labels for more accessible learning. We collected 460 chest CT examples: 230 CT examples from 79 patients with COVID-19, 100 CT examples from 100 patients with common pneumonia, and 130 CT examples from 130 people without pneumonia. A series of empirical studies show that our algorithm achieves an overall accuracy of 97.9%, AUC of 99.0%, and Cohen kappa score of 95.7%. These advantages endow our algorithm as an efficient assisted tool in the screening of COVID-19.
Relations between water content, potential and permeability in stems of conifers

Abstract. The influence of sapwood water content on the conductivity of sapwood to water was measured on stem sections of Pinus contorta. A reduction in relative water content from 100 to 90% caused permeability to fall to about 10% of the saturated value. Pressure–volume curves of branchwood and stem sapwood of Pinus contorta and Picea sitchensis have been analysed to define the tissue capacitance and the time constant and resistance for water movement between stored water and the functional xylem as functions of tissue water potential. Three phases in water loss were discernible. In the initial phase at high water potentials (> –0.5 MPa), the capacitance was large, the time constant long and the resistance to flow large in comparison with intermediate water potentials (−0.5 to −1.5 MPa). At still lower water potentials (−1.5 to −3.0 MPa), the time constant and resistance declined still further but the capacitance had a tendency to increase again, especially in the stemwood of Sitka spruce. Typical values in the second phase were for the time constant 5 s, for the resistance 4 × 10−13 N s m−5 and for the capacitance (change in relative water content per unit change in potential) 1×10−11 m3 Pa−1. These parameters define the availability of stored water and are being used in a dynamic model of water transport in trees.
Brief Survey on Attack Detection Methods for Cyber-Physical Systems

In recent years, cyber-physical systems (CPSs) have attracted intense attention due to their potential applications in many areas. However, the strong reliance on communication networks makes CPSs vulnerable to intentional cyberattacks. Therefore, a great number of attack detection methods have been proposed to enforce security of CPSs. In this article, various false data injection attack detection methods presented for CPSs are investigated and reviewed. According to the knowledge of control information, the controllers of CPSs are categorized as centralized and distributed controllers. Existing centralized attack detection approaches are discussed in terms of i) linear time-invariant systems, ii) actuator and sensor attacks, iii) nonlinear systems, and iv) systems with noise. Furthermore, the development of distributed attack detection is reviewed according to different decoupling methods. Some challenges and future research directions in the context of attack detection approaches are provided.
Combined Vector Based on Factorized Time-delay Neural Network for Text-Independent Speaker Recognition

Currently, the most effective text-independent speaker recognition method has turned to be extracting speaker embedding from various deep neural networks. Among them, the x-vector extracted from factorized time-delay neural network (F-TDNN) has been demonstrated to be among the best performance on recent NIST SRE evaluations. In our previous works, we have proposed combined vector (c-vector) and proved that the performance can be further improved by introducing phonetic information, which is often ignored in extracting x-vectors. By taking advantages of both F-TDNN and c-vector, we propose an embedding extraction method termed as factorized combined vector (fc-vector). In the NIST SRE18 CTS task, the EER and minDCF18 of fc-vector are 12.1% and 10.5% relatively lower than the x-vector, and 3.4% and 3.9% relatively lower than the c-vector, respectively.
Finding of a putative Lake Baikal endemic, Lindavia minuta, in distant lakes near the Arctic pole in Yakutia (Russia)

In the northern lakes of Yakutia, Vorota and Labynkyr, which are 2100 kilometres northeast of Lake Baikal, we found a putative Lake Baikal endemic, Lindavia minuta. Morphological analysis and non-metric multidimensional scaling showed that L. minuta populations from Yakutian and Transbaikalian lakes belong to the same (morpho) species. The possible dispersal history is discussed. The most probable hypothesis is that L. minuta was present in the Baikal basin during several Pleistocene glaciation cycles, and since Lake Baikal was previously connected to the River Lena, it is possible that there was a stable population of this species in the river, and that the river carried some cells to other suitable habitats. During glaciated periods, L. minuta could also have survived for longer periods in several ice dam lakes and possibly dispersed further north-east to the lakes in Yakutia.
Combustion Instability Monitoring through Deep-Learning-Based Classification of Sequential High-Speed Flame Images

In this study, novel deep learning models based on high-speed flame images are proposed to diagnose the combustion instability of a gas turbine. Two different network layers that can be combined with any existing backbone network are established—(1) An early-fusion layer that can learn to extract the power spectral density of subsequent image frames, which is time-invariant under certain conditions. (2) A late-fusion layer which combines the outputs of a backbone network at different time steps to predict the current combustion state. The performance of the proposed models is validated by the dataset of high speed flame images, which have been obtained in a gas turbine combustor during the transient process from stable condition to unstable condition and vice versa. Excellent performance is achieved for all test cases with high accuracy of 95.1–98.6% and a short processing time of 5.2–12.2 ms. Interestingly, simply increasing the number of input images is as competitive as combining the proposed early-fusion layer to a backbone network. In addition, using handcrafted weights for the late-fusion layer is shown to be more effective than using learned weights. From the results, the best combination is selected as the ResNet-18 model combined with our proposed fusion layers over 16 time-steps. The proposed deep learning method is proven as a potential tool for combustion instability identification and expected to be a promising tool for combustion instability prediction as well.
FORECASTING GYPSY MOTH DEFOLIATION WITH A GEOGRAPHICAL INFORMATION SYSTEM

Abstract In this study, we developed a series of logistic regression models for forecasting gypsy moth defoliation. The models were parameterized by using data collected over a small scaled 100m× 100m gridarea; the independent variables included egg mass density, male moth trap, previous year defoliation, and distance to the nearest cell which was defoliated in the previous year. We simulated the decision‐making by using these models; this method essentially simulated the application of current gypsy moth management decision‐making. The results indicated that these models can be more reliably applied to actual management decision.
Single Nucleotide Polymorphisms in the Chicken Mx gene at Position 2032 by Real-time Allele-specific PCR Melting-curve Analysis

Mx proteins are interferon-induced proteins with potent antiviral activities. A single nucleotide substitution at position 2032 of the Mx gene for position 631 of its protein from Ser to Asn is crucial for its antiviral activities in chickens. This study developed a real-time PCR based allelic discrimination method for the rapid genotyping of the chicken Mx gene G2032A SNP. The previously described allele-specific PCR was combined with real-time PCR melting curving analysis to genotype this Mx gene SNP from a small population of White Leghorn chickens, and the genotyping assay was confirmed by direct sequencing of PCR products. Our data demonstrate that the SNP at position 2032 of the Mx gene can be identified by the characteristic melting curve of the allele-specific fragments. This real-time PCR based SNP assay is rapid, sensitive and easy to perform compared with traditional PCR method which makes it suitable for large population analysis.
El Niño events, the lean versus fat scenario, and long-term guild dynamics of vertebrate predators in a South American semiarid ecosystem

Predator assemblages are complex systems in which asynchrony in the dynamics of resources and consumers, and the idiosyncratic perception of environmental conditions by the predators may obscure the detection of expected patterns. We disentangle the specific effects of these variables on the guild structure of a vertebrate predatory assemblage in a semiarid ecosystem of western South America. Over 16 years, this system faced dramatic fluctuations in prey availability associated with four El Nino events. After controlling for other sources of variation, we tested if increased resource availability is associated with higher niche overlaps, as expected from the lean/fat scenario. We determined the existence of two trophic guilds of predators (specialized mammal- eaters and omnivorous species with emphasis on arthropods) and found that they responded to increased produc- tivity both at the guild and whole assemblage levels. However, the population response of arthropod prey (almost simultaneous) and of different small mammal prey (delayed by 1 or 2 years) to productivity imposed a degree of asynchrony in prey availability and in the response of predators. This resulted in the between-guilds exchange of predator species depending on mammal prey scarcity or abundance. As a consequence, the observed pattern was an apparent lack of response at the assemblage level. Despite differences in the perception of prey levels by predators, we conclude that each one of them responded accordingly to theoretical predictions following a simple rule: if prey resources are not limiting, predators behave opportunistically converging over the most abundant resources, thus increasing niche overlap; if prey shortages occur, predators specialize on those prey resources that they gather most efficiently, thus lowering niche overlap; if resources become even scarcer, all predators converge again upon the few prey resources still available, thus increasing overlap - out of necessity.