Miracle-dz/UniFAR-FTUs huggingface dataset:
Maternal stress and the ZIKV epidemic in Puerto Rico

ABSTRACT In the summer of 2016, we examined the impact of the ZIKV crisis on women’s experiences of perinatal stress in Puerto Rico. Twenty-two pregnant or recently postpartum women engaged in qualitative interviews designed to elicit experiences of stress and pregnancy. Three key themes emerged from the interviews: 1) ‘Every day I think that it was invented’: Skepticism of official messaging about ZIKV; 2) ‘I worried about mosquitoes all the time’: Fear of ZIKV-related birth defects; and 3) ‘What am I going to do? ’: ZIKV as a compounding maternal stressor. Public health ZIKV education campaigns inadvertently sent the message that attempting to avoid ZIKV was futile. In response, women focused on more immediate, tangible life stressors and questioned the anti-natalist objectives of Puerto Rican and US health authorities. Any public health messaging that recommends delaying or preventing pregnancy must consider how such messaging might be received in a post-sterilization society. Prioritizing preventive measures – such as removing standing water – is essential for building trust in this colonial context.
Attenuation of CCl4 Induced Oxidative Stress, Immunosuppressive, HepatorenalDamage by Fucoidan in Rats

The protective and therapeutic effects of fucoidan extract from Laminaria species against liver damage induced by CCl4 in rats was investigated by monitoring the serum level and hepatic m-RNA expression of TGFβ-1, liver and renal markers, as well as oxidative stress and antioxidant biomarker. Thirty six adult male albino rats were divided into 4 equal groups; one was used as a negative control while groups II, III, and IV administrated 0.1 mL/100 g body weight twice a week for 8 weeks with carbon tetrachloride (CCl4), fucoidan (400 mg/kgbw orally/day), and CCl4 plus fucoidan, respectively. Blood samples were collected at the end of experiment and sera were separated to evaluate serum levels and the hepatic m-RNA expression of transforming growth factor beta (TGFβ-1), tumor necrosis factor (TNF α), interferon gamma (IFN-γ.), interleukin (IL), Il-1β, IL-6 and IL-10, antioxidant markers, reduced glutathione (GSH), superoxide dismutase (SOD), catalase (CAT), glutathione peroxidase (GPx) and lipid peroxidation malondialdehyde (MDA) as well as selective biochemical markers of liver and kidney functions were estimated. The results of this investigation revealed that treatment with fucoidan improved elevated expression of liver TGF β-1, Il-1β, IL-6, TNF α and serum level of malnoaldehyde (MDA), total bilirubin (T. Bil), induced by CCl4 at 8th week post treatment. In addition to enhancing the antioxidant enzyme activities, GSH, GPx, CAT and SOD. Also, liver trransaminase (ALT, AST), alkaline phosphatase (ALP), reduced in fucoidan and CCl4 treated group. These results show that crude fucoidan has potential immunomodulatory, antioxidant and hepatoprotective effects against the hepatic damage induced by CCl4.
A Modified GAN for Compressed Sensing MRI

Magnetic resonance imaging is a commonly used diagnosis method in medicine. Most reconstruction methods are based on the compressed sensing theory, while it is inefficient and time-consuming. In recent years, deep neural networks have developed rapidly. GAN architecture has been widely used in various image tasks after published. This paper proposes a new MRI reconstruction method RISEGAN. The generator uses U-Net structure to extract multi-scale features in the down sampling and up sampling modules. Combined with the residual learning and squeeze excitation blocks, the mapping between the under sampled and the fully sampled image is established. Experiment results show that our method can finish reconstruction with premium quality. Evaluation indicators have also improved.
Visual Recognition Method Based on Hybrid KPCA Network

SUMMARY In this paper, we propose a deep model of visual recognition based on hybrid KPCA Network(H-KPCANet), which is based on the combination of one-stage KPCANet and two-stage KPCANet. The proposed model consists of four types of basic components: the input layer, one-stage KPCANet, two-stage KPCANet and the fusion layer. The role of one-stage KPCANet is to calculate the KPCA ﬁlters for convolution layer, and two-stage KPCANet is to learn PCA ﬁlters in the ﬁrst stage and KPCA ﬁlters in the second stage. After binary quantization mapping and block-wise histogram, the features from two di ﬀ erent types of KPCANets are fused in the fusion layer. The ﬁnal feature of the input image can be achieved by weighted serial combination of the two types of features. The performance of our proposed algorithm is tested on digit recognition and object classiﬁcation, and the experimental results on visual recognition benchmarks of MNIST and CIFAR-10 validated the performance of the proposed H-KPCANet.
Ranking Candidates: An Experiential Exercise in Personnel Selection

Personnel selection is a key topic in Human Resource Management (HRM) courses. Many selection exercises focus on management situations that are unfamiliar to students who are taking introductory HRM courses. In contrast, this exercise introduces students to the pre-interview steps in the personnel selection process by asking them to determine the knowledge, skills, and abilities of potential adjunct instructors for a future offering of an HRM course. Groups of students act as management teams to determine the suitability of four applicants. Tasks include determining desirable qualifications, and then developing and ranking selection criteria based on the job posting. Subsequently, each group reviews the resumes of the four applicants and ranks them based on their selection criteria. A plenary discussion follows, during which students compare their choices and provide their rationale for their rankings. A discussion based on key questions concludes the activity. The exercise may be conducted in class or online.
Comparison of Ensemble Machine Learning Methods for Automated Classification of Focal and Non-Focal Epileptic EEG Signals

This research presents the epileptic focus region localization during epileptic seizures by applying different signal processing and ensemble machine learning techniques in intracranial recordings of electroencephalogram (EEG). Multi-scale Principal Component Analysis (MSPCA) is used for denoising EEG signals and the autoregressive (AR) algorithm will extract useful features from the EEG signal. The performances of the ensemble machine learning methods are measured with accuracy, F-measure, and the area under the receiver operating characteristic (ROC) curve (AUC). EEG-based focus area localization with the proposed methods reaches 98.9% accuracy using the Rotation Forest classifier. Therefore, our results suggest that ensemble machine learning methods can be applied to differentiate the EEG signals from epileptogenic brain areas and signals recorded from non-epileptogenic brain regions with high accuracy.
Characterization of the wake behind a horizontal-axis wind turbine (HAWT) at very high Reynolds numbers

The wake of a three-bladed horizontal axis wind turbine was studied at aerodynamic conditions similar to what is experienced by commercially available turbines. Field relevant Reynolds numbers and tip speed ratios were obtained through the use of a high-pressure wind tunnel, at relatively low velocities. Measurements of the streamwise velocity were acquired through the use of the novel nano-scale thermal anemometry probe (NSTAP), which yields very high spatial and temporal resolution, enabling unattenuated turbulence measurements. Profiles of the mean velocity and turbulent fluctuations are presented, as they demonstrate important features of the wake development, such as wake recovery and tip vortex evolution. One dimensional energy spectra are also presented to provide details on the dominant flow features present in the wake. Reynolds number invariance is shown for mean velocity deficit and streamwise variance profiles for all downstream positions presented. Downstream evolution of streamwise variance profiles provides insight to the dynamic interactions between the tip and root vortex, such as their eventual coalescence. Spectral analysis show that the near wake flow-structures are dominated by the tip vortex, but that other larger structures are present as well, which may be related to the wake meandering phenomenon.
Assessment of Policies, Laws, and Regulations Affecting the Contraceptive Needs of Adolescents in the Democratic Republic of the Congo

Background: Poor regulation is a barrier to adolescents’ accessing family planning (FP) services. We aimed to assess policies, laws, and regulations according to the contraceptive needs of adolescents in the Democratic Republic of the Congo (DRC). Methods: A mixed method study was conducted in 74 structures, including 13 administrative structures and 61 facilities offering FP. Data were collected through semi-structured interviews and document review. Using a health policy analysis framework, we analyzed the types of policies; their availability at the delivery points; the actors and the context of the policy formulation process. The content of policies was analyzed on the basis of WHO recommendations to ensure respect for human rights in the provision of contraceptive information and services. Results: Of the policies targeting the sexual and reproductive health (SRH), 18 were mainly focused on the FP of which 5 were the standards and directives; 5 implementing documents; 3 guidelines; 3 laws and 2 policies. Twelve documents were classified “important” for the FP extension. However, a few targeted adolescents and were translated into operational instructions for providers. Of 9 WHO recommendations, one was fully and two partially integrated into FP policies. Adolescents and FP providers were less involved in the policy formulation process. Conclusion: The FP regulation remains problematic in the DRC. FP policies are unsuitable to adolescents’ expectation; they do not guarantee a secure and unrestricted access to FP services. The ministry of health should put in place evidence-based regulations to improve access to SRH services by adolescents.
Enhanced enzymatic activity exerted by a packed assembly of a single type of enzyme

In contrast to the dilute conditions employed for in vitro biochemical studies, enzymes are spatially organized at high density in cellular micro-compartments. In spite of being crucial for cellular functions, enzymatic reactions in such highly packed states have not been fully addressed. Here, we applied a protein adaptor to assemble a single type of monomeric enzyme on a DNA scaffold in the packed or dispersed states for carbonic anhydrase. The enzymatic reactions proceeded faster in the packed than in the dispersed state. Acceleration of the reaction in the packed assembly was more prominent for substrates with higher hydrophobicity. In addition, carbonic anhydrase is more tolerant of inhibitors in the packed assembly. Such an acceleration of the reaction in the packed state over the dispersed state was also observed for xylose reductase. We propose that the entropic force of water increases local substrate or cofactor concentration within the domain confined between enzyme surfaces, thus accelerating the reaction. Our system provides a reasonable model of enzymes in a packed state; this would help in engineering artificial metabolic systems.
Lecanicillium subprimulinum (Cordycipitaceae, hypocreales), a novel species from baoshan, yunnan

In this paper, we report a new asexual-morph taxon belonging to the family Cordycipitaceae (Hypocreales), which is associated with a sexual morph of an ophioceras-like taxon on submerged wood collected from Baoshan, Yunnan, China. Morphologically, this new taxon is similar to known asexual morphs of Lecanicillium and characterized by conidiophores arising from hyaline hyphae, with gregarious, ellipsoid to ovoid, aseptate conidia. Phylogenetic analyses of a combined LSU, SSU, tef 1-α and ITS sequence dataset positions our taxon in Cordycipitaceae and close to Lecanicillium sp. (CBS 639.85) and L. primulinum . Lecanicillium subprimulinum is introduced as a new species with support from molecular data .
Experimental assessment of the stress-sensitivity of combined elastic and electrical anisotropy in shallow reservoir sandstones

Seismic and electromagnetic properties generally are anisotropic, depending on the microscale rock fabric and the macroscale stress field. We have assessed the stress-dependent anisotropy of poorly consolidated (porosity of approximately 0.35) sandstones (broadly representative of shallow reservoirs) experimentally, combining ultrasonic (0.6 MHz P-wave velocity, [Formula: see text], and attenuation [Formula: see text]) and electrical resistivity measurements. We used three cores from an outcrop sandstone sample extracted at 0°, 45°, and 90° angles with respect to the visible geologic bedding plane and subjected them to unloading/loading cycles with variations of the confining (20–35 MPa) and pore (2–17 MPa) pressures. Our results indicate that stress field orientation, loading history, rock fabric, and the measurement scale all affect the elastic and electrical anisotropies. Strong linear correlations ([Formula: see text]) between [Formula: see text], [Formula: see text], and resistivity in the three considered directions suggest that the stress orientation similarly affects the elastic and electrical properties of poorly consolidated, high-porosity (shallow) sandstone reservoirs. However, resistivity is more sensitive to pore-pressure changes (effective stress coefficients [Formula: see text]), whereas P-wave properties provide simultaneous information about the confining (from [Formula: see text], with n slightly less than 1) and pore pressure (from [Formula: see text], with n slightly greater than 1) variations. We found n is also anisotropic for the three measured properties because a more intense and rapid grain rearrangement occurs when the stress field changes result from oblique stress orientations with respect to rock layering. Altogether, our results highlighted the potential of joint elastic-electrical stress-dependent anisotropy assessments to enhance the geomechanical interpretation of reservoirs during production or injection activities.
Fusarium oxysporum f. sp. cubense biocontrol mediated by Bacillus spp. in Prata-Anã banana

: The aim of this study was to evaluate the controlling effect of Bacillus spp. on Fusarium oxysporum f. sp. cubense (Foc) activity under greenhouse conditions. Two experiments were set up, with the first consisting of one Bacillus application on the substrate, with Foc addition seven days later; two Bacillus applications at a seven-day interval on the substrate and Foc application seven days after the last Bacillus application; and Bacillus applied to the substrate at the same time as Foc. After 14 days of incubation of the substrate infested with Foc and Bacillus , banana seedlings of the Prata-Anã cultivar were planted in tubes. In the second experiment, the application interval was the same as the pre-inoculation experiment, but with Fusarium inoculated first and then transferring bacteria to the substrate. The results of both experiments demonstrated that the Bacillus spp. application after the Fusarium installation, with and without time interval, proved to be the best biocontrol of this disease in Prata-Anã plants.
Diversity of teiid lizards from Gran Chaco and Western Cerrado (Squamata: Teiidae)

The Gran Chaco dry forest ecoregion corresponds to the southern portion of the South America diagonal belt of open formations, being one of the most threatened subtropical woodland savannas in the world. The area is still poorly known biologically and has been suffering with impressively high forest cover loss in the last 10 years. Integrating morphological and molecular data, we detected and describe a cryptic new species of lizard genus Ameivula endemic from the eastern part of this ecoregion, the called Humid Chaco. Ameivula apipensis sp nov. is characterised by a whitish brown vertebral stripe in adults and juveniles, a lateral field without ocelli and with overlapping spot, presence of an interfrontoparietal scale in 46.2% of the specimens, 12–17 femoral pores, an hemipenis without lateral sac, five xiphisternal ribs, and by a combination of meristic features as confirmed by discriminant analysis. The new species was recovered sister to a clade from Western Cerrado in our analysis, the first phylogenetic hypothesis for the Ameivula and Glaucomastix genera based on 1977 base pairs of three mitochondrial (12S, 16S and cyt‐b) and one nuclear (c‐mos) genes, including all the recognised species at the moment. Maximum parsimony and Bayesian inference recovered the monophyly of Ameivula and Glaucomastix with strong support. Reinforcing previous studies, our results suggest the presence of additional cryptic species in Ameivula from the Western Cerrado.
Quick Algorithms for Independent Vector Extraction and Analysis Based on Exact Newton-Raphson Optimization

We propose new algorithms for the joint blind extraction and analysis of independent vector/components in linear complex-valued instantaneous mixtures. An efficient parameterization of the mixing and de-mixing matrix is used, which enables us to derive algorithms for extraction based on the exact Newton-Raphson update rule. For the complete independent vector/component analysis, orthogonally constrained algorithms are run in parallel. In experiments, the proposed methods show fast and stable convergence that is competitive to the state-of-the-art algorithms. Moreover, our approach is applicable also to piecewise determined mixtures with constant separating vectors.
A Novel THz Differential Spectral Clustering Recognition Method Based on t-SNE

We apply time-domain spectroscopy (THz) imaging technology to perform nondestructive detection on three industrial ceramic matrix composite (CMC) samples and one silicon slice with defects. In terms of spectrum recognition, a low-resolution THz spectrum image results in an ineffective recognition on sample defect features. Therefore, in this article, we propose a spectrum clustering recognition model based on t-distribution stochastic neighborhood embedding (t-SNE) to address this ineffective sample defect recognition. Firstly, we propose a model to recognize a reduced dimensional clustering of different spectrums drawn from the imaging spectrum data sets, in order to judge whether a sample includes a feature indicating a defect or not in a low-dimensional space. Second, we improve computation efficiency by mapping spectrum data samples from high-dimensional space to low-dimensional space by the use of a manifold learning algorithm (t-SNE). Finally, to achieve a visible observation of sample features in low-dimensional space, we use a conditional probability distribution to measure the distance invariant similarity. Comparative experiments indicate that our model can judge the existence of sample defect features or not through spectrum clustering, as a predetection process for image analysis.
Findings Seminal Papers Using Data Mining Techniques

The aim of this contribution is to show the detection of seminal papers using data mining techniques. To achieve the objective of this research, Rapidminer Studio software and its data mining tools are used, based on data created with information extracted from Google Scholar and Scopus, in three different areas of knowledge. In this process, other softwares such as Microsoft Excel and Publish or Perish are used. Comparing the results obtained for the searches in Knowledge Management, Entrepreneurship and Marketing, it was obtained that there is no marked similarity between the sets of articles that were obtained in Google Scholar and Scopus. The values for the Similarity Index remained below 0.52%, similar between Knowledge Management and Entrepreneurship but decreasing for Marketing. The detection of outliers using Data Mining techniques and in particular using Rapidminer, allowed to determine the seminals papers for the three search terms analyzed and allowed to characterize these in the space, in Google Scholar and Scopus. It was shown that the seminal articles can be different if Google Scholar or Scopus is used. The results suggest determining for other search terms whether the trend found is maintained or not.
A Transfer Learning Method for Deep Networks with Small Sample Sizes

Transfer learning is that a machine learning model learns knowledge from more than one domain, and it is applied to the context of small sample size. Some of approaches concentrate on the correlation determination among all domains while some pay more attention on knowledge transfer among all domains. In this paper, on the basic of SVM with hinge loss, a new regularized transfer learning deep network with a specific regularization is proposed, in which a deep network learns high level representation with respect to the given samples. And a part of parameters in SVM are shared such that the similarity of data distribution can be well captured. Besides, a modified regularized SVM is exploited such that the gradient based method is feasible, which yields a parallel implementation of the proposed method. After that, in the experiment part, the comparison of our approach with state-of-the-art approaches manifests the competitive performance and the feasibility in classification.
Drilling operations for the South Pole Ice Core (SPICEcore) project

Abstract Over the course of the 2014/15 and 2015/16 austral summer seasons, the South Pole Ice Core project recovered a 1751 m deep ice core at the South Pole. This core provided a high-resolution record of paleoclimate conditions in East Antarctica during the Holocene and late Pleistocene. The drilling and core processing were completed using the new US Intermediate Depth Drill system, which was designed and built by the US Ice Drilling Program at the University of Wisconsin–Madison. In this paper, we present and discuss the setup, operation, and performance of the drill system.
CONJUGATIVE PLASMID-BORNE ANTIBIOTIC RESISTANCE GENES IN PSEUDOMONAS AEROGENOSA

A total of 6 isolates of P. aeruginosa were isolated from premature unit, oxygen administration room and blood of patients admitted in pediatric hospital in Sulaimani. The isolates were identified as P. aeruginosa according to the diagnostic keys. All isolates were tested for susceptibility towards 10 different antibacterial drugs and they exhibited multiresistant for several choice antibiotics (amikacin, ampicillin, carbencillin, chloramphenicol, cefotaxime, neomycin, and trimethoprimsulfamethoxazole), with varied susceptible to rifampicin, gentamicin, and tetracycline. Agarose gel electrophoresis showed two different plasmid bands in P. aeruginosa isolate which is resistant to 7 antibiotics. One of these bands was ranged between 41 to 45 kbp and identified as conjugative plasmid and it confirmed through conjugation process with E. coli. Transconjugants were selected on agar plate containing antibiotics (rifampicin, cefotaxime, and ampicillin) and was recovered at frequencies in range of 10 -5 -10 -6 per recipient. Data suggest that bacterial contamination of different units of pediatric hospital should be reduced or eliminated to minimize nosocomial infection risks related to transfer of antibiotic-resistant bacteria to other patients.