Miracle-dz/UniFAR-FTUs huggingface dataset:
Midtrimester microbial DNA variations in maternal serum of women who experience spontaneous preterm birth

Abstract Objectives: To evaluate if midtrimester maternal serum contains microbial DNA and whether it differs between women with spontaneous preterm birth (SPTB) and those delivering at term. Study design: In this retrospective case–control study, we identified 20 healthy nulliparas with SPTB at 24–33 weeks of a nonanomalous singleton in 2014. Each case was matched by race/ethnicity to a control delivering at 39–40 weeks. Serum samples, collected at 15–20 weeks and stored at −80 C, were thawed and DNA extracted. PCR with primers targeting the 16S rDNA V4 region were used to prepare an amplicon library, sequenced using Illumina MiSeq, and analyzed using quantitative insight into microbial ecology (QIIME). Taxonomy was assigned using Ribosomal Database program (RDP) Classifier (threshold 0.8) against a modified Greengenes database. Differences in number of observed species, microbial alpha-diversity and beta-diversity, and taxa level analyses were undertaken. Results: All 40 samples were included. Women with SPTB had more unique observed species (p = .046) and higher mean alpha-diversity by Shannon index (but not Chao1 or Simpson) (p = .024). Microbial composition was different between groups by Bray–Curtis clustering (p = .03) but not by weighted (p = .13) or unweighted Unifrac (p = .11). Numerous taxa in the Firmicutes, Proteobacteria, and Actinobacteria phyla differed between groups (p < .05). Conclusions: SPTB is associated with distinct microbial DNA changes detected in midtrimester maternal serum.
Plant and Soil Metal Concentrations in Serpentine Soils and Their Influence on the Diet of Extensive Livestock Animals

Grazing circuits and resources consumed differ strongly throughout the year and within a territory. For this reason, animals’ diet composition, as well as their exposure to metals, is variable. No studies have been performed on how habitat use affects the metal concentrations to which sheep and goats reared in serpentine soil areas are exposed.The aim of the present study was to investigate the metal exposure of grazing animals raised in a serpentine soil area of the north-east of Portugal, taking into account the spatial distribution of metal concentrations in soils and plants.The habitat use and foraging behaviour of six flocks of sheep and goats were studied. The concentrations of Ca, Mg, Mn, Cr and Ni were determined in the soils and plant species most consumed by those animals.The highest Mg, Mn, Cr and Ni concentrations were found in the soils of the ultramafic complex. Ni concentrations above the recommended threshold for agricultural soils (30 μg/g) were found in some sites. A positive correlation between Ni concentration in soils and plants was found (0.634). Ni concentrations higher than 10 µg/g were found in some samples of the following plant species:Sorghum × drummondii(Steud.) Millsp. & Chase,Quercus rotundifoliaLam. ,Cytisus multiflorus(L’Hér.) Sweet,Cistus ladaniferL. andErica scopariaL. Significant differences (p ≤ 0.05) in metal concentrations of the plants most consumed by each flock were observed.Grazing circuits have an important role in the metal exposure of animals raised in this serpentine soil area.
Litho-Aware Machine Learning for Hotspot Detection

In this paper, we propose a novel methodology for machine learning-based hotspot detection that uses lithography information to build support vector machine (SVM) during its learning process. Unlike previous studies that use only geometric information or require a post-optical proximity correction (OPC) mask, this proposed method utilizes detailed optical information but bypasses post-OPC mask by sampling latent image intensity and uses those points to train an SVM model. The results suggest high accuracy and low false alarm, and faster runtime compared with methods that require a post-OPC mask.
Inbound e-marketing using neural network based visual and phonetic user experience analytics

Inbound marketing is the process of attracting the probable customers to a business before they have any intention to become customers. An effective method for inbound marketing is creation of a positive psychological business environment to attract the customers. A significant portion of traditional business environment is moving online and the new business environment is the company website. One of the major elements in online inbound marketing is the website address and the website logo, which are the first factors of brand personality that the visitor to the company website encounters when looking up the website in a search engine. In this paper, a framework for inbound e-marketing using visual and phonetic user experience analytics is proposed. The popular websites are studied and the relationship between website page views and the English phonetic construction of the website address and its logo are analyzed. For demonstrating the relationship between the website logo and name and its appeal to the customers, the proposed model is trained by a neural network. The proposed model is capable to predict website page views based on the company logo and the website address. The experimental results show that the proposed framework is capable of recommending the strategy for inbound marketing for online business and services with high accuracy.
Construction of deep resolution and retrieval platform for large scale scientific and technical literature

In the three aspects of information retrieval, scientific paper evaluation, revealing the knowledge structure evolution, citation analysis plays a vital role. With the appearance of full-text literature repositories, Citation analysis entered the 4 Era-full-text citation analysis age. However There is no Chinese full-text literature database. Secondly, in the two key points of citation content analysis, the citation topic analysis and the citation sentiment analysis are still lack of effective methods especially for Chinese literature. These have greatly restricted the research and application of full text citation analysis in Chinese Literature. In this project, our basic idea is: Through the study of establish a set of effective research for Chinese large-scale literature citation content analysis two key research points and efficient method for the analysis Chinese full citation analysis based on data, to enhance the effectiveness of citation analysis in our country in the field of science and technology. The main research topics include: (1) Studying the methods of real-time construction of standardized Data Set for citation content analysis based on spark. (2) A scientific and technical literature retrieval platform based on Citation content is proposed. In order to improve the research efficiency of science and technology in China and to improve the accuracy of sci-tech literature searching, the full text citation analysis is promoted.
Parallax-Tolerant Image Stitching Based on Robust Elastic Warping

Image stitching aims at generating high-quality panoramas with the lowest computational cost. In this paper, we propose a parallax-tolerant image stitching method based on robust elastic warping, which could achieve accurate alignment and efficient processing simultaneously. Given a group of point matches between images, an analytical warping function is constructed to eliminate the parallax errors. Then, the input images are warped according to the computed deformations over the meshed image plane. The seamless panorama is composed by directly reprojecting the warped images. As an important complement to the proposed method, a Bayesian model of feature refinement is proposed to adaptively remove the incorrect local matches. This ensures a more robust alignment than existing approaches. Moreover, our warp is highly compatible with different transformation types. A flexible strategy of combining it with the global similarity transformation is provided as an example. The performance of the proposed approach is demonstrated using several challenging cases.
A hybrid GA — Interval linear programming implementation for microgrid relay coordination considering different fault locations

This paper proposes hybrid Genetic Algorithm (GA) — Interval Linear Programming (ILP) approach to optimal relay coordination problem for microgrids. Relay coordination in microgrids is complex because of varied and bidirectional fault currents because of the existence of Distributed Generation (DG). Overcurrent relays are the feasible and economic choice of protection for meshed distribution systems. The coordinated relay settings must account for various possible fault scenarios in both grid connected and isolated microgrid modes of operation. Inadequate fault current levels from grid connected to the isolated mode are the major cause of protection miscoordination. This paper systematically formulates the relay coordination problem for microgrids as a linear interval optimization problem and introduces a new method of solution using hybrid GA — ILP method. The challenge in using GA to find the optimum in less number of iterations and the feasibility of ILP method to include various fault scenarios as “uncertain but bounded” intervals are combined to find the optimal overcurrent relay settings. The results show the effectiveness of proposed method. The programming is done using optimization tool box available in Matlab.
Changes in sexual behaviors following diagnosis with HIV: patterns and correlates among people living with HIV (PLHIV) in China

ABSTRACT Effective secondary prevention of HIV infections requires knowledge about changes in sexual behaviors after diagnosis among people living with HIV (PLHIV), yet there is a dearth of literature assessing gender-specific patterns and correlates of such changes among heterosexual PLHIV in China. Data used in the current study were derived from a cross-sectional survey conducted from 2012 to 2013 among 1212 heterosexual sexually active PLHIV in Guangxi, China. Most participants reduced sexual frequency (71.2%), reduced or maintained the same number of sexual partners (96.6%), and increased or maintained same frequencies of condom use (80.6%). Gender difference was found in changes in sexual frequency, but not in the number of sexual partners or condom use. For males, decrease in sexual frequency was associated with having no desire to have children (OR = 2.03, 95% CI 1.20, 3.44), being virally suppressed (OR = 0.27, 95% CI 0.079, 0.94), and social support (OR = 1.44, 95% CI 1.06, 1.96). Health promoting behaviors in condom use (i.e., increased or maintained same frequencies of condom use) for males was associated with being 45 years of age or older (OR = 0.35, 95% CI 0.21, 0.61), having an HIV-negative main partner (OR = 1.80, 95% CI 1.11, 2.92), and physical health-related quality of life (OR = 1.02, 95% CI 1.00, 1.04). For females, decrease in sexual frequency was associated with having no desire to have children (OR = 1.58, 95% CI 1.01, 2.47). Health promoting behaviors in condom use for females was associated with having an HIV-negative main partner (OR = 3.24, 95% CI 1.63, 6.45) and social support (OR = 0.75, 95% CI 0.57, 0.99). Future intervention efforts need to target PLHIV who need extra support in making health-improvement efforts and to facilitate gender-specific behavioral changes in sexual risk reduction after HIV diagnosis.
Liver Perfusate Natural Killer Cells From Deceased Brain Donors and Association With Acute Cellular Rejection After Liver Transplantation: A Time-to-Rejection Analysis

Background The ability to predict which recipients will successfully complete their posttransplant clinical course, which is crucial for liver transplant (LT) programs. The assessment of natural killer (NK) cell subset determined by flow cytometry from a monocentric series of consecutive liver perfusates could help identify risk factors portending adverse LT outcomes. Methods Liver perfusates were collected during the back-table surgical time after the procurement procedures for donors after brain death. Lymphocytic concentrations and phenotypes were matched with donors after brain death characteristics and indications, timing, surgical techniques, outcomes, and biopsy-proven acute cellular rejections (ACRs) in 46 adult recipients who underwent LT between 2010 and 2014 at our institute. Cox regression models were used to study relevant risk factors in order to estimate hazard ratios for episodes of rejection after LT. Results Percentage of NK cells was significantly associated with donor age (P = 0.05) and the percentage of NK T cellular subset (P = 0.001). The length of follow-up after LT was 41.0 ± 20.9 months, and 11 (23.9%) recipients experienced biopsy-proven ACR. At time-to-rejection proportional regression analysis, a cutoff value of 33.7% was optimal, with a sensitivity of 1, specificity of 0.57, and positive and negative predictive values of 0.42 and 1, respectively. The liver perfusate NK cell subset was strongly associated with biopsy-proven ACR (hazard ratio, 10.7; P = 0.02). Conclusions Liver perfusate cytofluorimetric phenotyping may contribute as a targeted preoperative tool to predict the risk of ACR, and as clinical test in translational studies that aim to improve donor allograft procurement and transplant outcomes.
Optimizing DSP Cores Using Design Transformation [Hardware Matters]

Reusable digital signal processing (DSP) intellectual property (IP) cores play a crucial role in numerous domains, including consumer electronics. However, optimizing DSP cores is crucial for the reduction of design area, delay, power, and so forth [1], [2]. Though several optimization techniques using evolutionary algorithms have been proposed, they incur design overhead and exploration time [1], [2].
Impact of system parameters and controller gain on the stability of a multi-terminal DC grid

The impact of the system parameters and controller gain on the dynamic and steady state behavior of the multi-terminal direct current (MTDC) system is discussed using small signal model. The small signal model (SSM) of VSC is derived including controllers and measurement filters and it is also validated with non-linear detailed switched model in PSCAD simulator. The SSM of DC grid and VSCs are augmented into single SSM to study the stability of the MTDC system. The limitation of the PLL gain caused by the strength of AC grid (short circuit ratio) is illustrated using eigenvalues analysis. This analysis is done for different control scheme as well as operating mode. The range of stable region for different SCR and loads are checked by varying the PLL gain. The effect of the controller gain on the AC resonance is also discussed in this paper. As the VSC terminals are increased, the DC resonance appears and its impact on the bandwidth of the direct voltage controller is explained briefly.
A Hierarchical SDN Architecture for Ultra-Dense Millimeter-Wave Cellular Networks

To cope with the tremendous growth in mobile data traffic, ultra-dense networks (UDNs) will be deployed in the future cellular network. Meanwhile, the enormous amount of available spectrum in millimeter-wave (mmWave) bands can be also exploited to increase the wireless link capacity. In accordance with these trends, this article introduces a novel hierarchical software-defined networking (SDN) architecture to facilitate the deployment of UDNs with both microwave base stations and mmWave access points. Aimed at reducing the cost of computational complexity and signaling overhead, the novel SDN architecture employs a semi-distributed design approach by configuring two levels of controllers: the centralized superior SDN controller and the localized subordinate SDN controller. Some practical challenges posed by the characteristics of mmWave transmissions, such as high propagation loss, channel blockage, and directional beamforming, are also discussed. To deal with such challenges, we then propose several important network operations for the hierarchical SDN, including dynamic subordinate SDN management, mobility management, and user-centric design. We finally provide simulation results to demonstrate the performance advantages of our proposals.
Neighborhood Disorder, Social Support, and Outcomes Among Violence-Exposed African American Women

Intimate partner violence (IPV) against women, particularly those living in poverty who have multiple marginalized identities, is a significant public health issue. IPV is associated with numerous mental health concerns including depression, hopelessness, and suicidal behavior. The present study examined the ecological determinants of these mental health outcomes in a high-risk sample of 67 low-income, African American women survivors of IPV. Based on an ecological framework that conceptualizes individuals as nested in multiple, interactive systems, we examined, longitudinally, the main and interactive effects of self-reported neighborhood disorder and social support from family members and friends on participants’ mental health (i.e., self-reported depressive symptoms, hopelessness, and suicide intent). In multiple regression analyses, neighborhood disorder interacted with social support from family members to predict depressive symptoms and hopelessness over time. Neighborhood disorder also interacted with social support from friends to predict hopelessness and suicide intent over time. High levels of social support buffered against the dangerous effects of neighborhood disorder on depressive symptoms, hopelessness, and suicide intent; at low levels of social support, there was no significant association between neighborhood disorder and those mental health outcomes. Neighborhood disorder and social support did not yield significant main effects. These findings underscore the importance of interventions that target individuals, families, and communities (e.g., community empowerment programs). Group interventions may also be important for low-income, African American women survivors of IPV, as they can help survivors establish and strengthen relationships and social support.
Prevalence and Long‐Term Survival After Coronary Artery Bypass Grafting in Women and Men With Heart Failure and Preserved Versus Reduced Ejection Fraction

Background Heart failure (HF) with reduced ejection fraction (rEF) is a widely regarded prognosticator after coronary artery bypass grafting. HF with preserved ejection fraction (pEF) accounts for up to half of all HF cases and is associated with considerable morbidity and mortality in hospitalized cohorts. However, HFpEF outcomes have not been elucidated in cardiac surgical patients. We investigated the prevalence and outcomes of HFpEF and HFrEF in women and men following coronary artery bypass grafting. Methods and Results We conducted a retrospective cohort study in Ontario, Canada, between October 1, 2008, and March 31, 2015, using Cardiac Care Network and Canadian Institute of Health Information data. HF is captured through a validated population‐based database of all Ontarians with physician‐diagnosed HF. We defined pEF as ejection fraction ≥50% and rEF as ejection fraction <50%. The primary outcome was all‐cause mortality. Analyses were stratified by sex. Mortality rates were calculated using Kaplan–Meier method. The relative hazard of death was assessed using multivariable Cox proportional hazard models. Of 40 083 patients (20.6% women), 55.5% had pEF without HF, 25.7% had rEF without HF, 6.9% had HFpEF, and 12.0% had HFrEF. Age‐standardized HFpEF mortality rates at 4±2 years of follow‐up were similar in women and men. HFrEF standardized HFpEF mortality rates were higher in women than men. Conclusions We found a higher prevalence and poorer prognosis of HFpEF in women. A history of HF was a more important prognosticator than ejection fraction. Preoperative screening and extended postoperative follow‐up should be focused on women and men with HF rather than on rEF alone.
Analysis of the dynamic response of pump-turbine runners-Part I: Experiment

When in operation, pump-turbine runners have to withstand large pressure pulsations generated by the rotor-stator interaction. The analysis of the dynamic behavior of these structures is necessary to avoid damage. For this analysis a realistic model of the runner is necessary. When the runner is submerged in water and inside the casing, its dynamic response is greatly affected. The added mass effects of the surrounding fluid and the proximity of the head-cover and bottom-cover may reduce the natural frequencies. The frequency reduction produced by the added mass effects and the influence of the boundary conditions has to be known for a safe design of the runner. In this paper an experimental investigation on the dynamic response of a model runner is presented. A reduced scale model of a pump-turbine was tested outside and inside the casing with different boundary conditions. For the excitation of the runner at different frequencies piezoelectric patches were used. The response was measured with miniature accelerometers located in several positions inside the runner. From the measurements the natural frequencies and mode-shapes of the runner were calculated using EMA. The influence of the added mass and of the boundary conditions is presented and discussed.
Soft Prioritized Network Coding in Multiple Access Relay Networks

We propose soft prioritized network coding techniques that provide a variable quality of service (QoS) to different nodes in multiple access relay networks. The basic idea is to exclude the low priority nodes in the network encoder when their channel gains towards the destination are below a threshold or above a threshold, and vary the threshold to provide a variable QoS. The proposed techniques can provide a soft-level prioritized service to different nodes depending on their assistance needs. They are a natural generalization of current prioritized network coding techniques which can provide only a hard-level (fixed) prioritized service. We derive the probability of decoding error for the prioritized and non-prioritized nodes in Rayleigh flat fading channel with path loss and additive white Gaussian noise taking into account the channel estimation error.
Age and gender classification from ear images

In this paper, we present a detailed analysis on extracting soft biometrie traits, age and gender, from ear images. Although there have been a few previous work on gender classification using ear images, to the best of our knowledge, this study is the first work on age classification from ear images. In the study, we have utilized both geometric features and appearance-based features for ear representation. The utilized geometric features are based on eight anthropometric landmarks and consist of 14 distance measurements and two area calculations. The appearance-based methods employ deep convolutional neural networks for representation and classification. The well-known convolutional neural network models, namely, AlexNet, VGG-16, GoogLeNet, and SqueezeNet have been adopted for the study. They have been fine-tuned on a large-scale ear dataset that has been built from the profile and close-to-profile face images in the Multi-PIE face dataset. This way, we have performed a domain adaptation. The updated models have been fine-tuned once more time on the small-scale target ear dataset, which contains only around 270 ear images for training. According to the experimental results, appearance-based methods have been found to be superior to the methods based on geometric features. We have achieved 94% accuracy for gender classification, whereas 52% accuracy has been obtained for age classification. These results indicate that ear images provide useful cues for age and gender classification, however, further work is required for age estimation.