Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of intergroup contact and relative gratification vs. deprivation on prejudice on both sides of the U.S./Mexico status divide

A study in the U.S.–Mexican intergroup context examined how collective relative gratification (RG) versus deprivation affects the relationship between intergroup contact and interpersonal closeness and subtle prejudice towards an out‐group. Participants were Mexican university students in Mexico (N = 239) and non‐Mexican students in California (N = 90). As predicted, Mexicans experienced less gratification/higher relative deprivation (RD), and low quality intergroup contact and expressed lower interpersonal closeness and higher subtle prejudice than U.S. Americans. Differences between countries were larger amongst participants reporting higher RD. Second‐stage moderated mediation analysis showed that the mediating effects of contact between country and interpersonal closeness and subtle prejudice, respectively, were larger amongst participants who felt relatively gratified than those who felt relatively deprived. These findings underline the importance of recognizing the moderating effect of differences in the RG versus RD levels of minority and majority groups when anticipating the potential benefits of intergroup contact for prejudice reduction.
Analysis of the relevance between Vocational High School competencies and the needs of the industrial sector on Computer and Network Engineering Competencies

The curriculum applied in vocational schools aims to synchronize graduate competencies with the demands of the industrial sector on workforce competencies. This study aims to analyze the relevance of the 2013 Vocational High School curriculum on Computer and Network Engineering Competencies and the needs of the workforce in the Telecommunications Industry Sector. This research was conducted using quantitative descriptive methods. The study population was the Vocational High School and the Telecommunications Industry in West Java Province and DKI Jakarta. The sample is determined by purposive sampling technique for the Telecommunications Industry and saturated sampling for Vocational High Schools. Participants in this study were 6 respondents from the Vocational High School and 21 respondents from the Telecommunications Industry. The research instrument used was a questionnaire. The analysis technique used is recall and precision. The results showed a high relevance between Basic Competence in the field of computer and network engineering and the need for workforce in the telecommunications industry sector by 83.84%.
Inactivation of CaMIT1 Inhibits Candida albicans Phospholipomannan β-Mannosylation, Reduces Virulence, and Alters Cell Wall Protein β-Mannosylation*

Studies on Candida albicans phospholipomannan have suggested a novel biosynthetic pathway for yeast glycosphingolipids. This pathway is thought to diverge from the usual pathway at the mannose-inositol-phospho-ceramide (MIPC) step. To confirm this hypothesis, a C. albicans gene homologue for the Saccharomyces cerevisiae SUR1 gene was identified and named MIT1 as it coded for GDP-mannose:inositol-phospho-ceramide mannose transferase. Two copies of this gene were disrupted. Western blots of cell extracts revealed that strain mit1Δ contained no PLM. Thin layer chromatography and mass spectrometry confirmed that mit1Δ did not synthesize MIPC, demonstrating a role of MIT1 in the mannosylation of C. albicans IPCs. As MIT1 disruption prevented downstream β-1,2 mannosylation, mit1Δ represents a new C. albicans mutant affected in the expression of these specific virulence attributes, which act as adhesins/immunomodulators. mit1Δ was less virulent during both the acute and chronic phases of systemic infection in mice (75 and 50% reduction in mortality, respectively). In vitro, mit1Δ was not able to escape macrophage lysis through down-regulation of the ERK1/2 phosphorylation pathway previously shown to be triggered by PLM. Phenotypic analysis also revealed pleiotropic effects of MIT1 disruption. The most striking observation was a reduced β-mannosylation of phosphopeptidomannan. Increased β-mannosylation of mannoproteins was observed under growth conditions that prevented the association of β-oligomannosides with phosphopeptidomannan, but not with PLM. This suggests that C. albicans has strong regulatory mechanisms associating β-oligomannoses with different cell wall carrier molecules. These mechanisms and the impact of the different presentations of β-oligomannoses on the host response need to be defined.
Image SR-based NLM and DCNN improved IBP with cubic B-spline

ABSTRACT Image super-resolution (SR) techniques aim to estimate high-resolution (HR) image from low-resolution (LR) image. Existing SR method has slow convergence and recovery of high-frequency details are inaccurate. To overcome these issues, two algorithms have been proposed for image SR based on non-local means improved iterative back projection (NLM-IIBP), deep convolutional neural network improved iterative back projection (DCNN-IIBP) to produce high-resolution images with low noise, minimal blur by restoring high-frequency details. In NLM-IIBP denoised images have been interpolated using cubic B-spline interpolation and processed using IIBP based on guided bilateral method. NLM preserves the edges effectively, but does not consider high dimensional information and over smoothing during noise minimization. To further improve the resolution, NLM is replaced by DCNN. DCNN denoising method suppresses different noises at different noise levels. The proposed algorithms have been analysed and compared with existing approaches using various parameters to prove the effectiveness.
Nurses’ Satisfaction Related to Implementing Patient Acuity Tool-Based Assignment

Nurses’ assignment that based on patient acuity tool scores regulates the number of nurses on a shift according to the patients' needs, thus balancing nurses’ workload and enhancing nurses’ satisfaction with assignment. This study aimed at assessing nurses' satisfaction related to implementing of patient acuity tool-based assignment. Experimental posttest only design was used. This study was conducted in critical care units at the Menoufia University Hospitals in Shebin Elkom. Simple random sample of nurses was selected from the previous units that was divided equally into two groups: experimental group (n=89) and control group (n=89). Additionally, all first line managers of the same units were selected (n=33). Tools used for data collection included: (1): Nurses’ Satisfaction with the Methods of Assignment questionnaire (posttest only). (2): First line managers Opinion Sheet to measure their opinion regarding implementation of the acuity tool-based nurses’ assignment. Results of the current study revealed that the majority of nurses in the experimental group were satisfied with method of assignment that based on acuity scores after implementation of the program. Also, there was no statistically significant difference between nurses’ satisfaction in the experimental group and their personal data except regarding their educational level and years of experience that was highly statistical. In conclusion, implementation of Kidd et al., new patient acuity tool was effective in improving nurses’ satisfaction with assignment. Moreover, the highest percentage of first line managers agreed on implementation of the patient acuity- tool based assignment. Continuous incorporation of the patient acuity tool in nurses’ assignment and generalization in other nursing units is a significant implication to promote proper distribution of nursing shift assignments and better nurses’ satisfaction.
Listeria contamination at a poultry processing plant

A survey was made of Listeria contamination at a chicken processing plant with a two‐stage ‘hot’ enrichment procedure in conjunction with three selective plating media. Results from three separate visits indicated that carcasses acquired listerias mainly via contaminated surfaces and equipment. Whereas no listerias were detected on neck skin from freshly slaughtered birds or in the caeca, Listeria monocytogenes was isolated from 50% of oven‐ready carcasses prior to packaging. In further tests, some caecal samples yielded L. monocytogenes, but only after prolonged cold enrichment.
Emergency Notification Using Combination Algorithm with Recognition ECG Signal

Intensive Care Unit (ICU) Rooms usually have several detectors attached to each patient providing intensive care, and several processors control and interpret. If the processor detects an abnormality, the medical professional office will be alerted. Nevertheless, many patients with heart disease are concerned with day-to-day behaviors such as hard work, battle, exercise, shock, fight, and war. Become due to clinical depression and erectile impotence this induces anxiety and fear. The boundaries of your heart muscle and coronary strength are unclear. They want a warning that is quick and accurate before they lose control. We develop signal recognition for an algorithm that is very fast and accurate. It helps alert patients to avoid the operation of risk. Nevertheless, it is able to transfer information from the heartbeat network to the doctor's guidance system. The research would analyze the 200 signals from multiple ECG signals. Integration Component Diagnosis (ICD) is capable of extraordinary reliability of identification than the 17.10-41.93 average percentage of the Automata Matching Process which takes less time than the other 29.37 average percentage process and can alert within 12 seconds. It cannot be identified in a pattern other than without the detection of an ECG signal. In the experimental, the signal is used to distinguish 20 ECG signal patterns.
Size structure, not metabolic scaling rules, determines fisheries reference points

Impact assessments of fishing on a stock require parameterization of vital rates: growth, mortality and recruitment. For ‘data-poor’ stocks, vital rates may be estimated from empirical size-based relationships or from life-history invariants. However, a theoretical framework to synthesize these empirical relations is lacking. Here, we combine life-history invariants, metabolic scaling and size-spectrum theory to develop a general size- and trait-based theory for demography and recruitment of exploited fish stocks. Important concepts are physiological or metabolic scaled mortalities and flux of individuals or their biomass to size. The theory is based on classic metabolic relations at the individual level and uses asymptotic size W∞ as a trait. The theory predicts fundamental similarities and differences between small and large species in vital rates and response to fishing. The central result is that larger species have a higher egg production per recruit than small species. This means that density dependence is stronger for large than for small species and has the consequence that fisheries reference points that incorporate recruitment do not obey metabolic scaling rules. This result implies that even though small species have a higher productivity than large species their resilience towards fishing is lower than expected from metabolic scaling rules. Further, we show that the fishing mortality leading to maximum yield per recruit is an ill-suited reference point. The theory can be used to generalize the impact of fishing across species and for making demographic and evolutionary impact assessments of fishing, particularly in data-poor situations.
Accounting for Uncertainty in Estimates of Escapement Goals for Fraser River Sockeye Salmon Based on Productivity of Nursery Lakes in British Columbia, Canada

Abstract For certain populations of sockeye salmon Oncorhynchus nerka, spawner and recruit data are either absent or too limited to estimate escapement goals (target abundance of spawners). In some cases, scientists instead use data on productivity of nursery lakes; however, many such analyses have not accounted for uncertainties. We therefore extended a previously developed lake productivity method for estimating escapement goals (the photosynthetic rate (PR) model) by using a Bayesian statistical approach that takes several sources of uncertainty into account. Utilizing data for Fraser River, British Columbia, sockeye salmon stocks, we compared this Bayesian PR method with stock–recruitment analysis. In six of seven cases, probability distributions of spawner abundance goals from the Bayesian PR method were 27% narrower on average than those from the stock–recruitment method. In four of seven cases, the Bayesian PR method produced higher median estimates of target spawner abundance than did stock–recrui.
The Quality of Recovery after Dexamethasone, Ondansetron, or Placebo Administration in Patients Undergoing Lower Limbs Orthopedic Surgery under Spinal Anesthesia Using Intrathecal Morphine. A Randomized Controlled Trial

Intrathecal morphine is widely and successfully used to prevent postoperative pain after orthopedic surgery, but it is frequently associated with side effects. The aim of this study was to evaluate the effect of dexamethasone or ondansetron when compared to placebo to reduce the occurrence of these undesirable effects and, consequently, to improve the quality of recovery based on patient's perspective. Methods. One hundred and thirty-five patients undergoing lower extremity orthopedic surgery under spinal anesthesia using bupivacaine and morphine were randomly assigned to receive IV dexamethasone, ondansetron, or saline. On the morning following surgery, a quality of recovery questionnaire (QoR-40) was completed. Results. No differences were detected in the global and dimensional QoR-40 scores following surgery; however, following postanesthesia care unit (PACU) discharge, pain scores were higher in patients receiving ondansetron compared with patients who received dexamethasone. Conclusion. Neither ondansetron nor dexamethasone improves the quality of recovery after lower limbs orthopedic surgery under spinal anesthesia using intrathecal morphine.
The contribution of wind-wave energy at sea bottom to the modelling of rhodolith beds distribution in an off-shore continental shelf

The study aims to investigate the relationship between the presence of rhodolith beds and the effect on the shelf bottom boundary layer due to the action of surface wind waves. The study area is situated off-shore and north-west of Elba Island in the Western Mediterranean Sea, an area known to be characterized by rhodolith beds. A binomial logistic regression model is used in order to analyse the relationship between wind-wave energy at sea bottom, bathymetry and rhodolith bed occurrence. The results indicate a positive correlation between rhodolith bed occurrence and wave energy, while the relation with bathymetry is weaker in all the trials. The wave energy confidence interval associated to the rhodolith bed probability is also estimated, thereby informing on wind wave energy values required for the modelling of this particular benthic habitat in off-shore shelf areas.
Nuclear DNA content in Salmo fibvenl in Lake Posta Fibreno, Italy

The nuclear DNA content of Salmo fibreni, endemic to Lake Posta Fibreno, and of the sympatric Salmo trutta macrostigma, was evaluated using flow cytometric (FCM) analysis. The DNA content was 6-29 pg/nucleus for male and significantly greater at 6-41 pg/nucleus for female S, fibreni; and 6-37 pg/nucleus for male S, trutta macrostigma.
Detection of Brain Tumor in MRI Images Using Watershed and Threshold-Based Segmentation

—Brain Cells control all body organs including the critical ones where any disorder of these cells will directly cause other organs to malfunction and thus threatens human’s life. That is why the brain is considered the most crucial organ in the human body. Disorder of brain cells, appear as inflamed cells in the brain known as a tumor. The early detection of these tumorous cells will increase the possibility of curing disease in a short time. Magnetic Resonance Imaging (MRI) is now used for detection of brain tumor. Image processing and segmentation of the MRI images is now an emerging research field where several techniques have been developed for MRI segmentation and tumor detection like Fuzzy C-Means (FCM) and Support Vector Machine (SVM). In this paper, an efficient algorithm based on threshold segmentation technique, followed by some morphological operations is proposed. The quality of the MRI scanned image is enhanced at first, then threshold segmentation is applied to divide the pixels into different classes, then to detect the tumor part of the image with the highest intensity, morphological operators are applied.
Development of co‐dominant amplified polymorphic sequence markers for resistance of sunflower to downy mildew race 730

The inheritance of the reaction of sunflower to downy mildew was investigated using resistant and susceptible near isogenic lines (NILs) and their F 3 families. Resistance to race 730 was evaluated using the whole seedling inoculation technique. Seventy-three F 3 families were inoculated, among which 54 families were resistant and 19 susceptible, fitting a 3 : 1 segregation ratio. F 3 families were also studied using several PCR markers. Ten markers at the Pl6 locus, specific for the resistant line, also segregated in F 3 families with a 3 : 1 ratio. The same segregation ratio occurred for microsatellite haplotypes that resembled the resistant parent, and were amplified with ORS 166 and ORS 1043. The only common fragment that was observed between resistant and susceptible parental lines was one of the TIR-NBS-LRR resistance gene analogue markers, having a restriction site. Two co-dominant cleaved amplified polymorphic sequence (CAPS) markers were obtained. The mapping data indicate that several dominant markers and two CAPS markers, developed here, completely co-segregate with the Pl6 gene conferring resistance to race 730. CAPS markers will facilitate efficient marker-assisted selection for sunflower resistance to downy mildew race 730.
Summer dormancy and drought survival of Moroccan ecotypes of orchardgrass.

Summer dormancy improves drought survival and autumn recovery of perennial forage species in Mediterranean areas. Morocco has served as a source of germplasm for orchardgrass (Dactylis glomerata L.) breeding, but little is known of the incidence and variability of the summer dormancy trait in Moroccan orchardgrass germplasm. This paper characterizes summer dormancy and summer drought survival in Moroccan ecotypes of orchardgrass. Ten Moroccan ecotypes and the cultivar Kasbah were studied in the field in Guich experimental INRA, Rabat, Morocco. Two trials were conducted in irrigated (to test summer dormancy) and in rainfed conditions (to test drought survival after summer). Under irrigation, Moroccan ecotypes of orchardgrass and Kasbah were summer dormant. According to a summer dormancy index and a combination of physiological responses, most ecotypes and Kasbah were found completely dormant. A single ecotype was considered incompletely dormant. After intense first year summer drought, plant survival was correlated (P < 0.001) with water soluble carbohydrate (WSC) content and osmotic potential in immature leaf bases (r = 0.67 and 0.62, respectively). Two Moroccan ecotypes exhibited higher post-drought survival after summer drought (98%) than Kasbah (90%) (P < 0.01). After a second year with severe drought, an ecotype outyielded Kasbah for autumn recovery (P < 0.001). Moroccan germplasm exhibited good levels of dormancy and agronomic performance that would be desirable in breeding programs.
Smart feature extraction and classification of hyperspectral images based on convolutional neural networks

Hyperspectral satellite imagery (HSI) is an advanced technology for object detection because it provides a large amount of information. Thus, the classification of HSIs is very complicated, so the methods of reducing spectral or spatial information generally degrade the quality of classification. In order to solve this problem and guarantee faster and more efficient processing, we propose a smart feature extraction (SFE) and classification by convolutional neural network (2D-CNN) method made up of two parts. The first consists in reducing spectral information by a probabilistic method based on the Softmax function. The second is classification by processing batches of data in the proposed CNN network. The method was tested on two public hyperspectral images (Indian Pines and SalinasA) to prove its effectiveness in increasing classification accuracy and reducing computing time.
Antioxidant Activities of Jeju Wax Apple (Syzygium samarangense) and Safety of Human Keratinocytes and Primary Skin Irritation Test

This study analyzed the antioxidant activity, cell viability, and human skin primary irritation test using the hot-water extracts of the Syzygium samarangense. As a result of the recent warmer climate, tropical plants have flourished on Jeju Island, and S. samarangense is one of these plants known to have biological activities. In this study, the hot-water extract of S. samarangense leaf and branch was analyzed. Antioxidant activity was measured by DPPH (2,2-diphenyl-1-picrylhydrazyl) and ABTS (2,2′-azino-bis(3-ethyl-benzthiazoline-6-sulfonic acid)) assays, and the DMPD (dimethyl-4-phenylenediamine) radical scavenging activity, nitrite scavenging activity, ferrous-ion chelating activity, cupric reducing antioxidant capacity, reducing power assay, ferric reducing antioxidant power, total phenol content, and total flavonoid content were also measured. In addition, cell viability was measured by MTT assay in human keratinocyte cells (HaCaT), and the safety of the extract for use on the skin was evaluated in the human skin primary irritation test. The antioxidant activities, except DMPD radical scavenging activity and ferrous-ion chelating activity, were stronger in the branch extract than in leaf extract, and the total phenol and flavonoid contents were also higher in the branch extract. Slight irritation was observed in the human skin primary irritation test. However, it was possible to observe sufficient antioxidant capacity at a concentration lower than the concentration used in the irritation test; therefore, if the concentration of the extract is appropriately adjusted, this suggests that it is a possible natural material suitable for use in cosmetics.
A Pipeline for Adaptive Filtering and Transformation of Noisy Left-Arm ECG to Its Surrogate Chest Signal

The performance of a low-power single-lead armband in generating electrocardiogram (ECG) signals from the chest and left arm was validated against a BIOPAC MP160 benchtop system in real-time. The filtering performance of three adaptive filtering algorithms, namely least mean squares (LMS), recursive least squares (RLS), and extended kernel RLS (EKRLS) in removing white (W), power line interference (PLI), electrode movement (EM), muscle artifact (MA), and baseline wandering (BLW) noises from the chest and left-arm ECG was evaluated with respect to the mean squared error (MSE). Filter parameters of the used algorithms were adjusted to ensure optimal filtering performance. LMS was found to be the most effective adaptive filtering algorithm in removing all noises with minimum MSE. However, for removing PLI with a maximal signal-to-noise ratio (SNR), RLS showed lower MSE values than LMS when the step size was set to 1 × 10−5. We proposed a transformation framework to convert the denoised left-arm and chest ECG signals to their low-MSE and high-SNR surrogate chest signals. With wide applications in wearable technologies, the proposed pipeline was found to be capable of establishing a baseline for comparing left-arm signals with original chest signals, getting one step closer to making use of the left-arm ECG in clinical cardiac evaluations.