Miracle-dz/UniFAR-FTUs huggingface dataset:
The Effect of the Addition of Fruit Powders on the Quality of Snacks with Jerusalem Artichoke during Storage

The aim of the study was to evaluate the physical, chemical and sensory properties of novel snacks gained from pellets composed of Jerusalem artichoke flour with the addition of cranberry, chokeberry and blackcurrant juice powders (after extrusion) fried or microwaved during 5-week storage. In ready-to-eat snacks stored in climatic chamber, the moisture content, texture, colour, total polyphenols content and antioxidant capacity, while in fat fraction of fried snacks—peroxide and acid values were examined. Overall sensory attributes were monitored as well. It was indicated that an addition of fruit powders increased the content of total polyphenols (on average by 40%) and improved the antioxidant capacity of snacks obtained. The products with fruit powders exhibited more attractive colour, while their texture was harder (when cranberry and chokeberry powders were added) in comparison with the control sample. Snacks with fruit powders addition showed better storage stability, what was especially important in the case of fried snacks where oxidative deterioration is most significant. The best effect was observed when chokeberry or black currant powders were used as additives. Replacing frying by microwaving as expansion method allowed to obtain snacks with acceptable sensory attributes and good quality during storage.
Syddansk Universitet Interaction between prenatal pesticide exposure and a common polymorphism in the PON 1 gene on DNA methylation in genes associated with cardio-metabolic disease risk an exploratory study

Background: Prenatal environmental conditions may influence disease risk in later life. We previously found a geneenvironment interaction between the paraoxonase 1 (PON1) Q192R genotype and prenatal pesticide exposure leading to an adverse cardio-metabolic risk profile at school age. However, the molecular mechanisms involved have not yet been resolved. It was hypothesized that epigenetics might be involved. The aim of the present study was therefore to investigate whether DNA methylation patterns in blood cells were related to prenatal pesticide exposure level, PON1 Q192R genotype, and associated metabolic effects observed in the children. Methods: Whole blood DNA methylation patterns in 48 children (6–11 years of age), whose mothers were occupationally unexposed or exposed to pesticides early in pregnancy, were determined by Illumina 450 K methylation arrays. Results: A specific methylation profile was observed in prenatally pesticide exposed children carrying the PON1 192R-allele. Differentially methylated genes were enriched in several neuroendocrine signaling pathways including dopamine-DARPP32 feedback (appetite, reward pathways), corticotrophin releasing hormone signaling, nNOS, neuregulin signaling, mTOR signaling, and type II diabetes mellitus signaling. Furthermore, we were able to identify possible candidate genes which mediated the associations between pesticide exposure and increased leptin level, body fat percentage, and difference in BMI Z score between birth and school age. Conclusions: DNA methylation may be an underlying mechanism explaining an adverse cardio-metabolic health profile in children carrying the PON1 192R-allele and prenatally exposed to pesticides.
Pharmacologic Approaches to Glycemic Treatment : Standards of Medical Care in Diabetes d 2019

The American Diabetes Association (ADA) “Standards of Medical Care in Diabetes” includes ADA’s current clinical practice recommendations and is intended to provide the components of diabetes care, general treatment goals and guidelines, and tools to evaluate quality of care.Members of theADAProfessional Practice Committee, a multidisciplinary expert committee, are responsible for updating the Standards of Care annually, or more frequently as warranted. For a detailed description of ADA standards, statements, and reports, as well as the evidence-grading system for ADA’s clinical practice recommendations, please refer to the Standards of Care Introduction. Readerswhowish to comment on the Standards of Care are invited to do so at professional.diabetes. org/SOC.
MOBBING IN A CROSS-SECTIONAL NATIONAL SAMPLE: The Turkish Case

In this empirical study we examined mobbing settings and outcomes with a data set from a cross-sectional occupational sample collected in ten cities in Turkey (N=853). The prevalence of mobbing in this sample was 23%, while victimization was 17% only. The most frequent aggressive behaviors were threats to the victim’s personal and occupational reputation such as having been denied a praise or promotion, having had one's contributions ignored by others, having been given unreasonable workloads above competence or simple and meaningless work below competence. Perpetrators were mostly superiors. Analyses revealed that oppressive management was the most influential factor for mobbing in work environment.
Analysis of abrasion rates in concrete surfaces of hydraulic structures

Abrasion of water-exposed surfaces in hydraulic structures can impose devastating defects in these surfaces leading to larger costs of rehabilitation and maintenance. One of the possible solutions is the improvement of concrete quality. Generally, several factors govern the abrasion resistance of hydraulic concrete. In the present study, previous experimental works, which carried out depending on the ASTM C 1138 test method, were collected, studied and analyzed precisely in order to estimate the effect of several factors that related with concrete quality on the abrasion rate of concrete. The results showed that the selection of cement type, inclusion of fibers, addition of silica fume and the election of the proper concrete type have the most effective influence among the remaining studied factors on the abrasion rate reduction.
Assessing and mitigating impact of time delay attack: a case study for power grid frequency control

Recent attacks against cyber-physical systems (CPSes) show that traditional reliance on isolation for security is insufficient. This paper develops efficient assessment and mitigation of an attack's impact as a system's built-in mechanisms. We focus on a general class of attacks, which we call time delay attack, that delays the transmissions of control data packets in a linear CPS control system. Our attack impact assessment, which is based on a joint stability-safety criterion, consists of (i) a machine learning (ML) based safety classification, and (ii) a tandem stability-safety classification that exploits a basic relationship between stability and safety, namely that an unstable system must be unsafe whereas a stable system may not be safe. The ML addresses a state explosion problem in the safety classification, whereas the tandem structure reduces false negatives in detecting unsafety arising from imperfect ML. We apply our approach to assess the impact of the attack on power grid automatic generation control, and accordingly develop a two-tiered mitigation that tunes the control gain automatically to restore safety where necessary and shed load only if the tuning is insufficient. Extensive simulations based on a 37-bus system model are conducted to evaluate the effectiveness of our assessment and mitigation approaches.
Shape Matching and Color Segmentation Based Traffic Sign Detection System

An automatic traffic sign detection system detects traffic signs from within images captured by an imaging sensor, and assists the driver to properly operate the vehicle. The idea presented here is through pixel value detection for hazard traffic signs containing red color background, computing in range regions and finally shape matching to choose the most appropriate traffic sign candidates to be drawn on the screen. The experimental result showed that, by comparing with the similar color segmentation based techniques, the proposed system has a higher accuracy of traffic sign detection rate with a lower computational time. Streszczenie. W artykule opisano system automatycznego rozpoznawania znakow drogowych na podstawie sygnalu czujnika obrazu. System rozpoznaje znaki na czerwonym tle, dopasowuje odpowiedni znak i wyświetla go na ekranie. Automatyczny system rozpoznawania znakow drogowych bazujący na dopasowaniu ksztaltu i segmentacji koloru.
Non-similar radiative bioconvection nanofluid flow under oblique magnetic field with entropy generation

Motivated by exploring the near-wall transport phenomena involved in bioconvection fuel cells combined with electrically conducting nanofluids, in the present article, a detailed analytical treatment using homotopy analysis method (HAM) is presented of non-similar bioconvection flow of a nanofluid under the influence of magnetic field (Lorentz force) and gyrotactic microorganisms. The flow is induced by a stretching sheet under the action of a oblique magnetic field. In addition, nonlinear radiation effects are considered which are representative of solar flux in green fuel cells. A second thermodynamic law analysis has also been carried out for the present study to examine entropy generation (irreversibility) minimization. The influence of magnetic parameter, radiation parameter and bioconvection Rayleigh number on skin friction coefficient, Nusselt number, micro-organism flux and entropy generation number (EGN) is visualized graphically with detailed interpretation. Validation of the HAM solutions with published results is also included for the non-magnetic case in the absence of bioconvection and nanofluid effects. The computations show that the flow is decelerated with increasing magnetic body force parameter and bioconvection Rayleigh number whereas it is accelerated with stronger radiation parameter. EGN is boosted with increasing Reynolds number, radiation parameter and Prandtl number whereas it is reduced with increasing inclination of magnetic field.
Histopathological Changes in Kidney of Hatched Chicks on Exposure to Vapors of Different Concentration of Embalming Fluid during Incubation

The study is aimed at observation of any teratogenic /adverse effects upon histology of the chick kidney when exposed to two different embalming fluid vapors containing different concentrations of formalin during their incubation period (21 days). 100 fresh fertilized eggs of Gallus gallusdomesticus were taken and divided in to three groups. group I contained 20 eggs as control group, not exposed to any embalming fluid but allowed to incubate and hatch in normal conditions. Group II and group III having 40 eggs each were exposed to vapors of embalming fluid containing 106 mmol/lt of formalin and 53mmol/litre of formalin respectively. The hatchability rate of Group I, II and III was 60%, 42.5% and 52.5% respectively. On dissecting the kidney of all 3 groups, no gross pathological changes were observed but on histopathological examination following pathological changes were observed. Glomerular enlargement, glomerular congestion, mesangial proliferation and increased bowman’s space were maximum in group II followed by Group III. tubular changes like cystic dialatation and cloudy swelling in Proximal convoluted tubules were observed in group II and III but more prevalent in group II (17.64% and 41.17% respectively) . Diffused necrosis in group II was seen in 58.82% of cases while focal necrosis was observed in 38.09% cases in group III. Therefore it is concluded that embalming fluid containing more concentrations of formalin is nephrotoxic even in vapors form.
Grain protein content and its association with the NAC-protein genes HvNAM 1 and HvNAM 2 in Nordic barley

Hunger is a problem faced by many people all over the world, and as the population grows, so does the need for food such as cereals. Because of this, the need for food with higher protein and nutrient content will be increasingly important. NAM-B1, a NAC-protein gene in wheat, has been shown to control the grain protein content and nutrient values, as well as senescence. In barley, two orthologs of this gene have been found, HvNAM1 and HvNAM2. This study focuses on Nordic barley accessions and how haplotypes of HvNAM1 and HvNAM2 correlate to the GPC and nutrient content. No correlations between the different haplotypes of the HvNAM genes and the nutrient content and GPC were found. No differences in nutrient content and GPC were found in Nordic accessions originating from Sweden, Norway, Finland, or Denmark, nor were differences found for improvements status groups or for six-row barley and two-row barley. The Nordic accessions were shown to generally have high GPC when compared to control groups Karl and Lewis. However, even if the results of this study indicate that the HvNAM genes do not have major effects on the nutrient contents or GPC, Nordic barley might still be good material for plant improvement. Other factors such as other genes, environmental effects, and gene expression should therefore be investigated.
Direct dating of Fe oxide-(Cu-Au) mineralization by U/Pb zircon geochronology

We present results for direct dating of Fe oxide-(Cu-Au) (iron oxide, copper, gold—IOCG) mineralization by U/Pb zircon geochronology. Constraining the timing of mineralization has important geodynamic implications for the processes involved in the genesis of these types of deposits and the tectonic evolution of rocks associated with these deposits. Hydrothermal zircon crystals were separated from four IOCG-type ore deposits associated with the Lyon Mountain Granite in the Adirondack Mountains, United States. Zircon grains from these low-Ti magnetite deposits reveal at least two periods of mineralization; one episode ca. 1039 Ma and a second between ca. 1015 and 1000 Ma. Previous age determinations of these deposits were constrained by the age of the altered host granitoids, and the assumption that Fe mineralization was directly related to pluton emplacement. Zircon crystals extracted from the ore yield ages that show that ore mineralization was episodic and younger than pluton emplacement.
Using an Artificial Lexicon and Eye Movements to Examine the Development and Microstructure of Lexical Dynamics

It is well known that the time course of lexical access is shaped by the number and nature of potential competitor items in the lexicon. While research has outlined the macrostructure of lexical processing (e.g., that during spoken word recognition, lexical candidates similar to the input are activated and compete for recognition), many questions remain about the microstructure (how exactly is the competitor set defined? ) and dynamics (what is the time course of lexical competition? ) of lexical processing, as well as their development as words are learned. Here, we begin to address these issues with a study in which participants learned to recognize words from a lexicon of novel names associated with novel shapes. Each item in the lexicon (e.g., /pibo/) had two potential competitors (e.g., /pibu/ and /dibo/). Half of the words were presented more frequently than the other half during training. This allowed us to examine the development of competition effects with experience. An eye tracker provided an on-line measure of the items being considered for recognition. The results indicate that lexical competition effects among newly-learned items develop quickly.
Effects of Topography on Tree Community Structure in a Deciduous Broad-Leaved Forest in North-Central China

Topography strongly influences the compositional structure of tree communities and plays a fundamental role in classifying habitats. Here, data of topography and 16 dominant tree species abundance were collected in a fully mapped 25-ha forest plot in the Qinling Mountains of north-central China. Multivariate regression trees (MRT) were used to categorize the habitats, and habitat associations were examined using the torus-translation test. The relative contributions of topographic and spatial variables to the total community structure were also examined by variation partitioning. The results showed the inconsistency in association of species with habitats across life stages with a few exceptions. Topographic variables [a + b] explained 11% and 19% of total variance at adult and juvenile stage, respectively. In contrast, spatial factors alone [c] explained more variation than topographic factors, revealing strong seed dispersal limitation in species composition in the 25-ha forest plot. Thus, the inconsistent associations of species and habitats coupled with high portion of variation of species composition explained by topographic and spatial factors might suggest that niche process and dispersal limitation had potential influences on species assemblage in the deciduous broad-leaved forest in north-central China.
Modelling chlorine wall decay in a full-scale water supply system

ABSTRACT The use of adequate decay models for simulating chlorine residuals can effectively aid in chlorine management in water supply systems. In this paper, wall decay in a full-scale water supply system is assessed and modelled using the traditional first-order (FO) model and the recent EXPBIO model. The EXPBIO model was successfully implemented in EPANET-MSX for the first time and predicted chlorine residuals with high accuracy. However, in the tested conditions (chlorine residuals ≥0.55 mg/L and small wall decay rates), the FO and the EXPBIO models described chlorine wall decay with similar accuracy. The results suggest that in systems of large diameter pipes and of high disinfectant concentrations, the simpler FO model can be used for the modelling of chlorine residuals without significant loss of accuracy. Further research is needed to identify in which conditions (chlorine levels, wall decay rates) the EXPBIO model performance may exceed that of the FO model.
Putting the “Me” in endorsement: Understanding and conceptualizing dimensions of self-endorsement using intelligent personal assistants

Self-endorsement—depicting the “self” as an endorser of a brand—represents a potentially powerful advertising strategy made possible by new media. This experiment tests the hypothesis that receiving brand recommendations from an intelligent personal assistant believed to be tailored to one’s own characteristics and consumer interests yields higher brand attitude and purchase intention toward the (self-endorsed) brand than receiving brand recommendations from a typical, but not self-tailored, intelligent personal assistant. Because endorsement is a well-known and highly effective advertising strategy, this is a high bar. We present evidence for self-referencing as an underlying mechanism, and perceived interactivity and identification as boundary conditions of self-endorsing. Consumers may show skepticism toward advertising but may not know how to be skeptical of themselves. As consumers outsource their tasks and decisions to new artificial intelligence (AI)-driven devices, they will need to be attentive to new media biases that threaten productive use of these devices.
Parton distribution functions and constraints on the intrinsic charm content of the proton using the Brodsky-Hoyer-Peterson-Saka approach

In this work, a new set of parton distribution functions taking into account the intrinsic charm (IC) contribution is presented. We focus on the impact of the EMC measurements on the large $x$ charm structure function as the strongest evidence for the intrinsic charm when combined with the HERA, SLAC and BCDMS data. The main goal of this paper is the simultaneous determination of the intrinsic charm probability ${P}_{c{\bar c/p}}$ and strong coupling $\alpha_s$. This allows us to study the interaction of these two quantities as well as the influence on the PDFs in the presence of IC contributions. By considering $\alpha_s$ which can be fix or free parameter from our QCD analysis, we find that although there is not a significant change in the extracted central value of PDFs and their uncertainties, the obtained value of ${P}_{c{\bar c/p}}$ change by factor 7.8\%. The extracted value of ${P}_{c{\bar c/p}}$ in the present QCD analysis is consistent with the recent reported upper limit of $1.93\%$, which is obtained for the first time from LHC measurements. We show the intrinsic charm probability is sensitive to the strong coupling constant and also the charm mass. The extracted value of the strong coupling constant $\alpha_s(M_Z^2) = 0.1191 \pm 0.0008$ at NLO is in good agreement with world average value and available theoretical models.
Spatial Variability of Selected Soil Attributes under Agricultural Land Use System in a Mountainous Watershed, Ethiopia.

In the Ethiopian Highlands, research projects were often measuring soil attributes of spatially structured point data but soil variability at a watershed scale is not clearly defined. This study was conducted to assess the correlation among selected soil attributes and to illustrate the spatial pattern and dependence of neighboring observations. The 53.7 km2 study watershed was divided into a 500 m by 500 m square grid using arcgis and at the center of each grid soil samples from 0 to 25 cm depth were collected within 184 locations. The descriptive statistics revealed available phosphorous (AP) had the largest coefficient of variation (CV = 104) while pH was the least variable. There was a positive link between elevation and SOC whereas bulk density (ρd) and pH indicated an inverse relationship with elevation and SOC. The value for nugget/sill of ρd, pH and elevation are less than 0.25, and depicts that it has strong spatial autocorrelation. The value for nugget/ sill of SOC, and TN found between 0.25 and 0.75, and indicate that they have moderate spatial autocorrelation. With regard to AP, the value for nugget/sill is more than 0.75, which displays a weak spatial autocorrelation. Semivariograms of ρd, pH and elevation were best fitted to Gaussian model whereas SOC, TN and AP were best fitted to exponential function. Generally, the study verified that soil measurements taken at the given scale through regular sampling interval were adequate to capture the spatial dependence of numerous initial soil assessments in the study watershed.
Malware Detection Based on Deep Learning of Behavior Graphs

The Internet of Things (IoT) provides various benefits, which makes smart device even closer. With more and more smart devices in IoT, security is not a one-device affair. Many attacks targeted at traditional computers in IoT environment may also aim at other IoT devices. In this paper, we consider an approach to protect IoT devices from being attacked by local computers. In response to this issue, we propose a novel behavior-based deep learning framework (BDLF) which is built in cloud platform for detecting malware in IoT environment. In the proposed BDLF, we first construct behavior graphs to provide efficient information of malware behaviors using extracted API calls. We then use a neural network-Stacked AutoEncoders (SAEs) for extracting high-level features from behavior graphs. The layers of SAEs are inserted one after another and the last layer is connected to some added classifiers. The architecture of the SAEs is 6,000-2,000-500. The experiment results demonstrate that the proposed BDLF can learn the semantics of higher-level malicious behaviors from behavior graphs and further increase the average detection precision by 1.5%.