Miracle-dz/UniFAR-FTUs huggingface dataset:
Infection Control Knowledge and Practices: Program Management in Labor Units According to Standard Infection Control Precautions in Northern Upper Egypt

Background: Birth-infection is known to be a major cause of maternal perinatal morbidity and mortality. Globally, it has been reported that better care during birth and labor, and newborns' care, as well, immediately after birth can avert up to 1.49 million maternal and newborn deaths and stillbirths. Infection Control is the most important field of concern in labor and delivery rooms. Aim: study the effect of an educational program on maternity nurses' knowledge and practices towards infection control in labor units according to standard infection control precautions. Subject & Methods: This study was conducted on 30 nurses worked in labor units of three hospitals in Fayoum city, Egypt. The method for data collection consists of а questionnaire based on standard infection control precautions. Checklists were used for 11 procedures to assess nurses' practices. Results: Nurses' knowledge and practices regarding infection control, according to standard infection control precautions, were poor. Statistically significant improvement in the maternity nurse's knowledge and practices after the implication of the program was found. The majority (87.0%) of nurses had expressed their satisfaction to participate with a high level of significant. Conclusion: Results indicate that prevention and control of infections aren't adequately applied in Fayoum hospitals. Therefore, after the program was implemented; all nurses reported higher scoring in both awareness and skills than before. The satisfactory score progressed while unsatisfactory one regressed. This is mirrored to the program's effect. Recommendations: Activate hospitals' infection control committees which should be combined with maternal death reviews, audits, training and feedback on infection rates in upper Egyptian Hospitals.
First records of soilborne Phytophthora species in Swedish oak forests

Thirty-two oak stands in southern Sweden, 27 with predominantly declining trees and five with a higher proportion of healthy trees were investigated regarding the presence of soilborne Phytophthora species. Phytophthora quercina , an oak-specific fine root pathogen, was isolated from rhizosphere soil samples in 10 of the 27 declining stands. Additionally, P. cactorum and P. cambivora were recovered from one stand each. No Phytophthora species were isolated from the healthy oak stands. The soil conditions at the sites from which Phytophthora spp. were recovered ranged from mesic sediments to moraines, with clayey to silty textures and with soil pH (BaCl2) between 3.5 and 5.0. The results show that P. quercina is geographically widespread in oak stands in southern Sweden and indicate that this pathogen may be one of the factors involved in oak decline in Northern Europe as has already been shown for western, Central and parts of southern Europe. (Less)
Influence of the pressure range on temperature coefficient of resistivity (TCR) for polysilicon piezoresistive MEMS pressure sensor

Sensitivity with respect to physical change of any type of sensor depends upon structure of the sensor and sensing material. If sensor is sensitive with more than single physical change (pressure or temperature etc) than sensitivity will get affected because of conflict in impact due to multiple physical parameters. Depending upon the designer’s intuition and experience, a variety of shapes of sensor had been proposed which can bear both the pressure and temperature. To understand the influence of temperature and pressure on the linearity and sensitivity, pressure sensors has been designed having 50 μm thick square diaphragm is being simulated and analyzed. The effect of pressure on Temperature Coefficient of Resistivity (TCR) of poly-silicon pressure sensor has been investigated in this paper. The stresses tempted in the piezoresistors and dislocation created in diaphragm have been studied using finite element method (FEM). The physical characteristics of sensor have been determined within the temperature range from 10 °C to 100 °C under the pressure range of 0 to 100 psi. It has been observed that TCR reduces with increasing pressure up to 30 psi, and beyond this pressure, the TCR begins to increase and thus the TCR shows the duality in nature. At 100 psi pressure, the calculated TCR for the diaphragm is found of the order of ∼7.7 × 10−3 (/°C). Thus, in conclusion, the pressure range ∼40–100 psi is recommended as the optimal range to achieve the better sensitivity. The temperature sensitivity of designed sensor has been found to be ∼0.10455 mV °C−1 while the pressure sensitivity of the proposed sensors which has been found to be 1.20051 mV psi−1. Hence, designed sensor can be used as both pressure and temperature sensing device incorporated into a single sensor.
ESTIMATION OF VOLATILITY FUNCTIONS IN JUMP DIFFUSIONS USING TRUNCATED BIPOWER INCREMENTS

In this article, we introduce and analyze a new methodology to estimate the volatility functions of jump diffusion models. Our methodology relies on the standard kernel estimation technique using truncated bipower increments. The relevant asymptotics are fully developed, allowing for the time span to increase as well as the sampling interval to decrease, and accommodate both stationary and nonstationary recurrent processes. We evaluate the performance of our estimators by simulation and provide some illustrative empirical analyses.
Effects of Gibberllin and Abscisic Acid on the Cortical Microtubule Orientation in Hypocotyl Cells of Light-Grown Cucumber Seedlings

Effects of gibberellin (GA4) and abscisic acid (ABA) on the orientation of cortical microtubules (MTs) in the epidermal and cortex cells of light-grown cucumber (Cucumis sativus L. cv Aonagajibai) hypocotyls were examined by immunofluorescence microscopy. MTs were observed in the 0-1 mm region (region A) and 3-4 mm region (region D) below the cotyledonary node. GA4 promoted and ABA inhibited hypocotyl elongation. In the control, the predominant pattern of MT arrangement in the tangential surface of epidermal cells (Ep-t) was oblique in region A and oblique/longitudinal in region D, while in the radial surface of epidermal cells (Ep-r), the MT arrangement was mostly transverse in both regions. The MT arrangement in the radial surface of cortex cells (C-r) was all transverse in both regions. GA4 increased transversely oriented MTs and decreased obliquely and longitudinally oriented MTs, whereas ABA increased obliquely and longitudinally oriented MTs and decreased transversely oriented MTs in Ep-t and Ep-r in both regions. ABA counteracted GA4-induced effects on MT orientation as well as elongation. The frequency of the occurrence of transverse MTs in Ep-t but not in Ep-r and C-r was found to be highly correlated to the growth rate of the hypocotyl, suggesting that the epidermis is the essential tissue that limits the growth of the hypocotyl.
Reproductive tissue banking : scientific principles

Utility of Viable Tissues Ex Vivo: Banking of Reproductive Cells and Tissues. Tissue Maturation in Vivo and in Vitro: Gamete and Embryo Ontogeny. Metabolic Support at Normothermia. Pharmacological Intervention in Vitro. Hypothermia and Mammalian Gametes. Fundamental Cryobiology of Mammalian Spermatozoa. The Cryobiology of Mammalian Oocyte. Cryopreservation of Multicellular Embryos and Reproductive Tissues. Genome Resource Banking: Impact on Biotic Conservation and Society. Implications of Tissue Banking for Human Reproductive Medicine. Subject Index.
Emerging functions of alphaherpesvirus genes

Abstract We know from complete sequencing of three alphaherpesvirus genomes that these large DNA viruses around 70 genes. In many cases little is known of gene function. Features of predicted amino acid sequences have given a number of clues to functions, mostly for enzymes and membrane-associated proteins. Genetic analyzes have very strikingly shown that over 30 genes are dispensable for virus growth in tissue culture. A variety of experimental approaches is giving information on many areas of gene function including control of gene expression, modulation of cell state, DNA replication, virion formation and structure and cell entry mechanisms.
Genome-Wide Identification and Characterization of Point Mutations in the SARS-CoV-2 Genome

Objectives Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged in Wuhan, China, in December 2019 and has been rapidly spreading worldwide. Although the causal relationship among mutations and the features of SARS-CoV-2 such as rapid transmission, pathogenicity, and tropism, remains unclear, our results of genomic mutations in SARS-CoV-2 may help to interpret the interaction between genomic characterization in SARS-CoV-2 and infectivity with the host. Methods A total of 4,254 genomic sequences of SARS-CoV-2 were collected from the Global Initiative on Sharing all Influenza Data (GISAID). Multiple sequence alignment for phylogenetic analysis and comparative genomic approach for mutation analysis were conducted using Molecular Evolutionary Genetics Analysis (MEGA), and an in-house program based on Perl language, respectively. Results Phylogenetic analysis of SARS-CoV-2 strains indicated that there were 3 major clades including S, V, and G, and 2 subclades (G.1 and G.2). There were 767 types of synonymous and 1,352 types of non-synonymous mutation. ORF1a, ORF1b, S, and N genes were detected at high frequency, whereas ORF7b and E genes exhibited low frequency. In the receptor-binding domain (RBD) of the S gene, 11 non-synonymous mutations were observed in the region adjacent to the angiotensin converting enzyme 2 (ACE2) binding site. Conclusion It has been reported that the rapid infectivity and transmission of SARS-CoV-2 associated with host receptor affinity are derived from several mutations in its genes. Without these genetic mutations to enhance evolutionary adaptation, species recognition, host receptor affinity, and pathogenicity, it would not survive. It is expected that our results could provide an important clue in understanding the genomic characteristics of SARS-CoV-2.
Processing and function of CFTR-ΔF508 are species-dependent

Mutations in the cystic fibrosis transmembrane conductance regulator (CFTR) cause cystic fibrosis. The most common mutation, a deletion of the phenylalanine at position 508 (ΔF508), disrupts processing of the protein. Nearly all human CFTR-ΔF508 is retained in the endoplasmic reticulum and degraded, preventing maturation to the plasma membrane. In addition, the F508 deletion reduces the activity of single CFTR channels. Human CFTR-ΔF508 has been extensively studied to better understand its defects. Here, we adopted a cross-species comparative approach, examining human, pig, and mouse CFTR-ΔF508. As with human CFTR-ΔF508, the ΔF508 mutation reduced the single-channel activity of the pig and mouse channels. However, the mutant pig and mouse proteins were at least partially processed like their wild-type counterparts. Moreover, pig and mouse CFTR-ΔF508 partially restored transepithelial Cl− transport to CF airway epithelia. Our data, combined with earlier work, suggest that there is a gradient in the severity of the CFTR-ΔF508 processing defect, with human more severe than pig or mouse. These findings may explain some previously puzzling observations in CF mice, they have important implications for evaluation of potential therapeutics, and they suggest new strategies for discovering the mechanisms that disrupt processing of human CFTR-ΔF508.
Scaling Laws for Multilingual Neural Machine Translation

In this work, we provide a large-scale empirical study of the scaling properties of multilingual neural machine translation models. We examine how increases in the model size affect the model performance and investigate the role of the training mixture composition on the scaling behavior. We find that changing the weightings of the individual language pairs in the training mixture only affect the multiplicative factor of the scaling law. In particular, we observe that multilingual models trained using different mixing rates all exhibit the same scaling exponent. Through a novel joint scaling law formulation, we compute the effective number of parameters allocated to each language pair and examine the role of language similarity in the scaling behavior of our models. We find little evidence that language similarity has any impact. In contrast, the direction of the multilinguality plays a significant role, with models translating from multiple languages into English having a larger number of effective parameters per task than their reversed counterparts. Finally, we leverage our observations to predict the performance of multilingual models trained with any language weighting at any scale, significantly reducing efforts required for language balancing in large multilingual models. Our findings apply to both in-domain and out-of-domain test sets and to multiple evaluation metrics, such as ChrF and BLEURT.
Vegetation changes in semi‐natural meadows after abandonment in coastal northern Finland

A research project on traditional cultural landscapes in coastal northern Finland provided the opportunity to compare presently managed meadow sites to a series of corresponding abandoned sites. Twenty-two grassland habitats. either grazed or mown, were studied to analyze differences between species compositions The data were classified with TWINSPAN and ordinated with Detrended Correspondence Analysis and Canonical Correspondence Analysis. The multivariate analysis recognized successfully habitats that are either presently used or differ considerably from the others by their moisture gradient although a few very coininon generalist species were present in almost every seral stage studied. The studied deviant habitats resemble most of the previously described vegetation types in northern Finland. Results suggest that drought can delay the invasion of tall broad-leaved species. The results also support the idea that abandoned meadows of corresponding moisture gradients begin to resemhle each other in later stages of succession. Multivariate methods can be used to determine the succession stages in grassland habitats and thus help to determine the urgency for restoration practices.
Effect of experimental hyperhomocysteinemia on plasma lipid profile, insulin sensitivity and paraoxonase 1 in the rat

Hyperhomocysteinemia (hHcy) is a well-known risk factor of cardiovascular diseases, however, the mechanism of its detrimental effect is incompletely understood. Some studies suggest that, paradoxically, hHcy may promote traditional risk factors such as hyperlipidemia. We examined the effect of experimental hHcy on plasma lipid profile, glucose and insulin concentrations as well as on high-density lipoprotein (HDL)-associated antiatherosclerotic enzyme, paraoxonase 1 (PON1). Hyperhomocysteinemia was induced by feeding male Wistar rats with diet enriched with methionine or diet enriched in methionine and deficient in folate, vitamin B6 and B12 for 8 weeks. These diets resulted in the 3.3- and 9.6-fold elevation of plasma Hcy, respectively. Plasma total and HDL-cholesterol, triglycerides and apolipoprotein A-I were similar in all groups. High-methionine diets had no effect on fasting plasma glucose but significantly increased fasting plasma insulin concentration indicating impaired ability of insulin to suppress hepatic glucose output. PON1 activity was unchanged in high methionine vitamin B-sufficient diet-fed rats, but was decreased by 30-40% toward various substrates in high methionine vitamin B-deficient diet-fed animals. The results indicate that hHcy has no effect on lipid metabolism, however, induces insulin resistance and, above certain Hcy level, PON1 deficiency. Impaired insulin signaling and reduced PON1 activity may contribute to detrimental effects of hHcy. Adipobiology 2012; 4: 77-84.
Evaluation of Pb, Zn and Cd focusing on IPI, PI and I geo in Sediments of Hashilan Wetland, Iran

ABSTRACT Investigation of heavy metals in the bed sediments of wetlands can be used as an appropriate index for determining environmental quality of wetlands. In this study, the concentration of lead (Pb), zinc (Zn) and cadmium (Cd) in sediments of 8 points in the Hashilan wetland was evaluated. Geo-accumulation index (I geo), input potential index (IPI) and pollution index (PI) calculated for bed sediments of the wetland. The I geo for Cd, Pb and Zn were obtained as −2.29 to −2.68, −0.86 to −1.15 and −1.77 to −2.12. The PIs for mentioned heavy metals were 0.1–0.3, 0.07–0.14 and 0.007–0.01; and the IPI were 0.19, 0.1 and 0.009, respectively. Based on the results, the concentration of heavy metals in this wetland is lower than international standards, and this wetland is classified as clean and pollution-free regions.
Thermal and Visual Imaging to Assist with Juvenile Idiopathic Arthritis Examination of the Knees

Juvenile idiopathic arthritis (JIA) causes inflammation of the joints, and it is frequently associated with their pain and stiffness. Its timely diagnosis is important to avoid its progressive damage to the bones and cartilage. Increases in the joint’s temperature and redness could be indicators of active JIA, hence their accurate quantification could assist with diagnosis. Thermal and visual images of the knees in 20 JIA participants (age: mean = 11.2 years, standard deviation = 2.3 years) were studied. The median temperature of knees with active inflammation was 3.198% higher than that of inactive knees. This difference, examined by a Wilcoxon signed-rank test, was statistically significant (p = 0.0078). In six out of the eight participants who had one active inflamed knee, thermal imaging identified the corresponding knee as warmer. In 16 out of 20 participants, the knee identified as warmer by thermal imaging was also identified as having a greater colour change by visual imaging as compared to their respective reference regions. The devised methods could accurately quantify the colour and temperature of the knees. It was concluded that thermal and visual imaging methods can be valuable in examining JIA. Further studies involving a larger number of participants and more detailed explorations would be needed prior to clinical application.
The Gender Gap in Tech & Competitive Work Environments? Field Experimental Evidence from an Internet-of-Things Product Development Platform

Many technology companies struggle to fill all their positions and to achieve gender parity in their ranks. One explanation for gender disparities is the possibility that men and women differ in their willingness to work under competitive organizational environments of tech firms. To investigate this question, this paper reports on a large platform-based field experiment in which 97,696 U.S. university-educated individuals were given the opportunity to join a tech-related product development activity. Individuals were randomly assigned to treatments emphasizing either competitive or collaborative interactions with other participants. We find that (1) in non-STEM fields, the competition treatment leads to a 27% drop in participation for females in comparison to males. However, in our main finding, (2) in STEM fields, we find no statistical differences in men and women’s responses to competition. The patterns are consistent with (3) men in non-STEM fields exhibiting overconfidence in their likelihood of succeeding under competition. We also find that, while participation in highest in STEM fields, (4) the ratio of female to male participation in a field is better predicted by whether the field is male- or female-dominated, than it is by whether it is a STEM field or not. We discuss theoretical interpretations and implications for organizations.
DINOISER: Diffused Conditional Sequence Learning by Manipulating Noises

While diffusion models have achieved great success in generating continuous signals such as images and audio, it remains elusive for diffusion models in learning discrete sequence data like natural languages. Although recent advances circumvent this challenge of discreteness by embedding discrete tokens as continuous surrogates, they still fall short of satisfactory generation quality. To understand this, we first dive deep into the denoised training protocol of diffusion-based sequence generative models and determine their three severe problems, i.e., 1) failing to learn, 2) lack of scalability, and 3) neglecting source conditions. We argue that these problems can be boiled down to the pitfall of the not completely eliminated discreteness in the embedding space, and the scale of noises is decisive herein. In this paper, we introduce DINOISER to facilitate diffusion models for sequence generation by manipulating noises. We propose to adaptively determine the range of sampled noise scales for counter-discreteness training; and encourage the proposed diffused sequence learner to leverage source conditions with amplified noise scales during inference. Experiments show that DINOISER enables consistent improvement over the baselines of previous diffusion-based sequence generative models on several conditional sequence modeling benchmarks thanks to both effective training and inference strategies. Analyses further verify that DINOISER can make better use of source conditions to govern its generative process.
Structure function tensor equations with triple decomposition

Abstract Exact budget equations are derived for the coherent and stochastic contributions to the second-order structure function tensor. They extend the anisotropic generalised Kolmogorov equations (AGKE) by considering the coherent and stochastic parts of the Reynolds stress tensor, and are useful for the statistical description of turbulent flows with periodic or quasi-periodic features, like, for example, the alternate shedding after a bluff body. While the original AGKE describe production, transport, inter-component redistribution and dissipation of the Reynolds stresses in the combined space of scales and positions, the new equations, called $\varphi$AGKE, contain the phase $\varphi$ as an additional independent variable, and describe the interplay among the mean, coherent and stochastic fields at the various phases. The newly derived $\varphi$AGKE are then applied to a case where an exactly periodic external forcing drives the flow: a turbulent plane channel flow modified by harmonic spanwise oscillations of the wall to reduce drag. The phase-by-phase action of the oscillating transversal Stokes layer generated by the forcing on the near-wall turbulent structures is observed, and a detailed description of the scale-space interaction among mean, coherent and stochastic fields is provided thanks to the $\varphi$AGKE.
Identification of Key Factors Affecting the Trophic State of Four Tropical Small Water Bodies

Due to their dimensions, small and shallow water bodies are more sensitive to changes in nutrient load, water flow, and human management. The four water bodies studied are small (area <0.01 km2), constantly supplied by a non-anthropogenic source of nutrients, and these water bodies present different trophic states: mesotrophic, eutrophic, and hyper-eutrophic. The objective of this study was to identify the key environmental factors that created differences in the trophic state of these adjacent shallow urban lakes by modeling chlorophyll-a (Chl a) through the application of the Partial Least Squares Regression (PLSR). The models (n = 36) explain 45.8–60.6% (R2), and predicts 39–52.9% (Q2) of the variance. Environmental variables were identified in the water bodies as critical factors of trophic state determination, water residence time (WRT), ions (e.g., Ca2+), and minerals as hydroxyapatite (HAP). These variables were related to processes that could improve trophic conditions, such as flushing and phosphorous precipitation. Conversely, N-NH3 concentration was associated with nutrient recycling, and found to be able to promote eutrophication.