Miracle-dz/UniFAR-FTUs huggingface dataset:
Plant-Species Diversity Correlates with Genetic Variation of an Oligophagous Seed Predator

Several characteristics of habitats of herbivores and their food-plant communities, such as plant-species composition and plant quality, influence population genetics of both herbivores and their host plants. We investigated how different ecological and geographic factors affect genetic variation in and differentiation of 23 populations of the oligophagous seed predator Lygaeus equestris (Heteroptera) in southwestern Finland and in eastern Sweden. We tested whether genetic differentiation of the L. equestris populations was related to the similarity of vegetation, and whether there was more within-population genetic variation in habitats with a high number of plant species or in those with a large population of the primary food plant, Vincetoxicum hirundinaria. We also tested whether genetic differentiation of the populations was related to the geographic distance, and whether location of the populations on islands or on mainland, island size, or population size affected within-population genetic variation. Pairwise FST ranged from 0 to 0.1 indicating low to moderate genetic differentiation of populations. Differentiation increased with geographic distance between the populations, but was not related to the similarity of vegetation between the habitats. Genetic variation within the L. equestris populations did not increase with the population size of the primary food plant. However, the more diverse the plant community the higher was the level of genetic variation within the L. equestris population. Furthermore, the level of genetic variation did not vary significantly between island and mainland populations. The effect of the population size on within-population genetic variation was related to island size. Usually small populations are susceptible to loss of genetic variation, but small L. equestris populations on large islands seemed to maintain a relatively high level of within-population genetic variation. Our findings suggest that, in addition to geographic and species-specific ecological factors, the plant community affects population genetic structure of oligophagous herbivores.
Fast noise tracking based on recursive smoothing of MMSE noise power estimates

We consider estimation of the noise spectral variance from speech signals contaminated by highly nonstationary noise sources. In each time frame, for each frequency bin, the noise variance estimate is updated recursively with the minimum mean-square error (MMSE) estimate of the current noise power. For the estimation of the noise power, a spectral gain function is used, which is found by an iterative data-driven training method. The proposed noise tracking method can accurately track fast changes in noise level (up to about 10 dB/s). When compared to the minimum statistics method for various noise sources in a speech enhancement system, improvements in segmental signal-to-noise ratio of more than 1 dB are obtained.
Local and Regional Scale Genetic Variation in the Cape Dune Mole-Rat, Bathyergus suillus

The distribution of genetic variation is determined through the interaction of life history, morphology and habitat specificity of a species in conjunction with landscape structure. While numerous studies have investigated this interplay of factors in species inhabiting aquatic, riverine, terrestrial, arboreal and saxicolous systems, the fossorial system has remained largely unexplored. In this study we attempt to elucidate the impacts of a subterranean lifestyle coupled with a heterogeneous landscape on genetic partitioning by using a subterranean mammal species, the Cape dune mole-rat (Bathyergus suillus), as our model. Bathyergus suillus is one of a few mammal species endemic to the Cape Floristic Region (CFR) of the Western Cape of South Africa. Its distribution is fragmented by rivers and mountains; both geographic phenomena that may act as geographical barriers to gene-flow. Using two mitochondrial fragments (cytochrome b and control region) as well as nine microsatellite loci, we determined the phylogeographic structure and gene-flow patterns at two different spatial scales (local and regional). Furthermore, we investigated genetic differentiation between populations and applied Bayesian clustering and assignment approaches to our data. Nearly every population formed a genetically unique entity with significant genetic structure evident across geographic barriers such as rivers (Berg, Verlorenvlei, Breede and Gourits Rivers), mountains (Piketberg and Hottentots Holland Mountains) and with geographic distance at both spatial scales. Surprisingly, B. suillus was found to be paraphyletic with respect to its sister species, B. janetta–a result largely overlooked by previous studies on these taxa. A systematic revision of the genus Bathyergus is therefore necessary. This study provides a valuable insight into how the biology, life-history and habitat specificity of animals inhabiting a fossorial system may act in concert with the structure of the surrounding landscape to influence genetic distinctiveness and ultimately speciation.
High-Pressure Device for Fluid Extraction from Porous Materials: Application to Cement-Based Materials

A high-pressure device, reaching an axial pressure of 1000 MPa, intended to the extraction of the pore solution of rigid and slightly porous materials, has been developed to improve the efficiency of extraction. This paper gives an application of fluid extraction from mortars made with Portland cement. It includes an experimental study of the performance of the apparatus, and an analysis of the results in terms of efficiency of extraction, repeatability of measurement, and effect of the squeezing pressure on the pore solution composition. Results shows that: (1) the squeezing efficiency using our apparatus is higher than those found in the literature; (2) the measurement uncertainty ranges between 1.5% and 14%; (3) no significant effect of pressure (up to 1000 MPa) is observed for concentrations of Ca, Na, K, and Si. This paper suggests conducting extraction at 1000 MPa, especially on old concrete or concrete made with low W/C ratios.
Grounding Gene Mentions with Respect to Gene Database Identifiers

We describe our submission for task 1B of the BioCreAtIvE competition which is concerned with grounding gene mentions with respect to databases of organism gene identifiers. Several approaches to gene identification, lookup, and disambiguation are presented. Results are presented with two possible baseline systems and a discussion of the source of precision and recall errors as well as an estimate of precision and recall for an organism-specific tagger bootstrapped from gene synonym lists and the task 1B training data.
Curve Clustering with Spatial Constraints for Analysis of Spatiotemporal Data

In this paper we present a new approach for curve clustering designed for analysis of spatiotemporal data. Such kind of data contains both spatial and temporal patterns that we desire to capture. The proposed methodology is based on regression and Gaussian mixture modeling and the novelty of the herein work is the incorporation of spatial smoothness constraints in the form of a prior for the data labels. This enables the proposed model to take into account the underlying property of spatiotemporal data that spatially adjacent data points most likely should belong to the same cluster. A maximum a posteriori Expectation Maximization (MAP-EM) algorithm is used for learning this model. We present numerical experiments with simulated data where the ground truth is known in order to assess the value of the introduced smoothness constraint, and also with real cardiac perfusion MRI data. The results are very promising and demonstrate the value of the proposed constraint for analysis of such data .
Edge detection in SAR images using phase stretch transform

In this work a novel approach to edge detection on Synthetic Aperture Radar (SAR) images is introduced. The proposed method uses an optics inspired transform which emulates the diffraction of an image through a medium with nonlinear dispersive properties. The experimental results show that the output of the introduced Phase Stretch Transform (PST) in conjunction with further morphological operations can be effectively used for image edge detection.
Hyperspectral Remote Sensing Image Subpixel Target Detection Based on Supervised Metric Learning

The detection and identification of target pixels such as certain minerals and man-made objects from hyperspectral remote sensing images is of great interest for both civilian and military applications. However, due to the restriction in the spatial resolution of most airborne or satellite hyperspectral sensors, the targets often appear as subpixels in the hyperspectral image (HSI). The observed spectral feature of the desired target pixel (positive sample) is therefore a mixed signature of the reference target spectrum and the background pixels spectra (negative samples), which belong to various land cover classes. In this paper, we propose a novel supervised metric learning (SML) algorithm, which can effectively learn a distance metric for hyperspectral target detection, by which target pixels are easily detected in positive space while the background pixels are pushed into negative space as far as possible. The proposed SML algorithm first maximizes the distance between the positive and negative samples by an objective function of the supervised distance maximization. Then, by considering the variety of the background spectral features, we put a similarity propagation constraint into the SML to simultaneously link the target pixels with positive samples, as well as the background pixels with negative samples, which helps to reject false alarms in the target detection. Finally, a manifold smoothness regularization is imposed on the positive samples to preserve their local geometry in the obtained metric. Based on the public data sets of mineral detection in an Airborne Visible/Infrared Imaging Spectrometer image and fabric and vehicle detection in a Hyperspectral Mapper image, quantitative comparisons of several HSI target detection methods, as well as some state-of-the-art metric learning algorithms, were performed. All the experimental results demonstrate the effectiveness of the proposed SML algorithm for hyperspectral target detection.
Plasmonics for Laser Beam Shaping

This paper reviews our recent work on laser beam shaping using plasmonics. We demonstrated that by integrating properly designed plasmonic structures onto the facet of semiconductor lasers, their divergence angle can be dramatically reduced by more than one orders of magnitude, down to a few degrees. A plasmonic collimator consisting of a slit aperture and an adjacent 1-D grating can collimate laser light in the laser polarization direction; a collimator consisting of a rectangular aperture and a concentric ring grating can reduce the beam divergence both perpendicular and parallel to the laser polarization direction, thus achieving collimation in the plane perpendicular to the laser beam. The devices integrated with plasmonic collimators preserve good room-temperature performance with output power comparable to that of the original unpatterned lasers. A collimator design for one wavelength can be scaled to adapt to other wavelengths ranging from the visible to the far-IR regimes. Plasmonic collimation offers a compact and integrated solution to the problem of laser beam collimation and may have a large impact on applications such as free-space optical communication, pointing, and light detection and ranging. This paper opens up major opportunities in wavefront engineering using plasmonic structures.
Abstractive Tabular Dataset Summarization via Knowledge Base Semantic Embeddings

This paper describes an abstractive summarization method for tabular data which employs a knowledge base semantic embedding to generate the summary. Assuming the dataset contains descriptive text in headers, columns and/or some augmenting metadata, the system employs the embedding to recommend a subject/type for each text segment. Recommendations are aggregated into a small collection of super types considered to be descriptive of the dataset by exploiting the hierarchy of types in a pre-specified ontology. Using February 2015 Wikipedia as the knowledge base, and a corresponding DBpedia ontology as types, we present experimental results on open data taken from several sources--OpenML, CKAN and data.world--to illustrate the effectiveness of the approach.
Milk kefir: nutritional, microbiological and health benefits

Abstract Kefir is fermented milk produced from grains that comprise a specific and complex mixture of bacteria and yeasts that live in a symbiotic association. The nutritional composition of kefir varies according to the milk composition, the microbiological composition of the grains used, the time/temperature of fermentation and storage conditions. Kefir originates from the Caucasus and Tibet. Recently, kefir has raised interest in the scientific community due to its numerous beneficial effects on health. Currently, several scientific studies have supported the health benefits of kefir, as reported historically as a probiotic drink with great potential in health promotion, as well as being a safe and inexpensive food, easily produced at home. Regular consumption of kefir has been associated with improved digestion and tolerance to lactose, antibacterial effect, hypocholesterolaemic effect, control of plasma glucose, anti-hypertensive effect, anti-inflammatory effect, antioxidant activity, anti-carcinogenic activity, anti-allergenic activity and healing effects. A large proportion of the studies that support these findings were conducted in vitro or in animal models. However, there is a need for systematic clinical trials to better understand the effects of regular use of kefir as part of a diet, and for their effect on preventing diseases. Thus, the present review focuses on the nutritional and microbiological composition of kefir and presents relevant findings associated with the beneficial effects of kefir on human and animal health.
Endocrine Treatment-Related Symptoms and Patient Outcomes in Breast Cancer: A Meta-Analysis

Purpose An association between endocrine treatment-related symptoms and breast cancer recurrence has been suggested previously; however, conflicting results have been reported. We performed a meta-analysis of published studies to clarify this relationship. Methods We systematically searched PubMed, Embase, Scopus, and the Cochrane database for studies investigating the association between endocrine treatment-related symptoms and patient survival. Random-effects meta-analysis was conducted with recurrence rate as the primary outcome. Results Out of 7,713 retrieved articles, six studies were included. In patients who received endocrine treatment, the presence of any endocrine treatment-related symptom was found to be associated with a lower recurrence rate in comparison to an absence of any symptoms (hazard ratio [HR], 0.76; 95% confidence interval [CI], 0.66–0.87). This relationship persisted in patients presenting with only vasomotor or only musculoskeletal symptoms (HR, 0.74, 95% CI, 0.63–0.87; HR, 0.69, 95% CI, 0.55–0.86, respectively). At both time-points of symptom evaluation (3 months and 12 months), patients with endocrine treatment-related symptoms had a lower recurrence rate (HR, 0.74, 95% CI, 0.66–0.84; HR, 0.79, 95% CI, 0.69–0.90, respectively). This association was also significant in pooled studies including patients with and without baseline symptoms (HR, 0.73, 95% CI, 0.54–0.99; HR, 0.76, 95% CI, 0.69–0.85, respectively). Conclusion Endocrine treatment-related symptoms are significantly predictive of lower recurrence rate in breast cancer patients, regardless of the type of symptoms, time-point of evaluation, or inclusion of baseline symptoms. These symptoms could be biomarkers for the prediction of long-term responses to endocrine treatment in patients with breast cancer.
Alginate bead fabrication and encapsulation of living cells under centrifugally induced artificial gravity conditions

This study presents a novel method for the direct, centrifugally induced fabrication of small, Ca2+-hardened alginate beads at polymer-tube micronozzles. The bead diameter can arbitrarily be adjusted between 180–800 µm by the nozzle geometry and spinning frequencies between 5–28 Hz. The size distribution of the main peak features a CV of 7–16%, only. Up to 600 beads per second and channel are issued from the micronozzle through an air gap towards the curing agent contained in a standard lab tube (‘Eppi’). Several tubes can be mounted on a ‘flying bucket’ rotor where they align horizontally under rotation and return to a vertical position as soon as the rotor is at rest. The centrifugally induced, ultra-high artificial gravity conditions (up to 180 g) even allow the micro-encapsulation of alginate solutions displaying viscosities up to 50 Pa s, i.e. ∼50 000 times the viscosity of water! With this low cost technology for microencapsulation, HN25 and PC12 cells have successfully been encapsulated while maintaining vitality.
Spatially Resolved and Quantitative Analysis of VISTA/PD-1H as a Novel Immunotherapy Target in Human Non–Small Cell Lung Cancer

Purpose: Determine the localized expression pattern and clinical significance of VISTA/PD-1H in human non–small cell lung cancer (NSCLC). Experimental Design: Using multiplex quantitative immunofluorescence (QIF), we performed localized measurements of VISTA, PD-1, and PD-L1 protein in 758 stage I–IV NSCLCs from 3 independent cohorts represented in tissue microarray format. The targets were selectively measured in cytokeratin+ tumor epithelial cells, CD3+ T cells, CD4+ T-helper cells, CD8+ cytotoxic T cells, CD20+ B lymphocytes and CD68+ tumor-associated macrophages. We determined the association between the targets, clinicopathological/molecular variables and survival. Genomic analyses of lung cancer cases from TCGA were also performed. Results: VISTA protein was detected in 99% of NSCLCs with a predominant membranous/cytoplasmic staining pattern. Expression in tumor and stromal cells was seen in 21% and 98% of cases, respectively. The levels of VISTA were positively associated with PD-L1, PD-1, CD8+ T cells and CD68+ macrophages. VISTA expression was higher in T-lymphocytes than in macrophages; and in cytotoxic T cells than in T-helper cells. Elevated VISTA was associated with absence of EGFR mutations and lower mutational burden in lung adenocarcinomas. Presence of VISTA in tumor compartment predicted longer 5-year survival. Conclusions: VISTA is frequently expressed in human NSCLC and shows association with increased tumor-infiltrating lymphocytes, PD-1 axis markers, specific genomic alterations and outcome. These results support the immunomodulatory role of VISTA in human NSCLC and suggests its potential as therapeutic target. Clin Cancer Res; 24(7); 1562–73. ©2017 AACR.
A model for the interaction of the G3‐subdomain of Geobacillus stearothermophilus IF2 with the 30S ribosomal subunit

Bacterial translation initiation factor IF2 complexed with GTP binds to the 30S ribosomal subunit, promotes ribosomal binding of fMet‐tRNA, and favors the joining of the small and large ribosomal subunits yielding a 70S initiation complex ready to enter the translation elongation phase. Within the IF2 molecule subdomain G3, which is believed to play an important role in the IF2‐30S interaction, is positioned between the GTP‐binding G2 and the fMet‐tRNA binding C‐terminal subdomains. In this study the solution structure of subdomain G3 of Geobacillus stearothermophilus IF2 has been elucidated. G3 forms a core structure consisting of two β‐sheets with each four anti‐parallel strands, followed by a C‐terminal α‐helix. In line with its role as linker between G3 and subdomain C1, this helix has no well‐defined orientation but is endowed with a dynamic nature. The structure of the G3 core is that of a typical OB‐fold module, similar to that of the corresponding subdomain of Thermus thermophilus IF2, and to that of other known RNA‐binding modules such as IF2‐C2, IF1 and subdomains II of elongation factors EF‐Tu and EF‐G. Structural comparisons have resulted in a model that describes the interaction between IF2‐G3 and the 30S ribosomal subunit.
Layered Scene Models from Single Hazy

This paper describes the construction of a layered scene model, based on a single hazy image that has sufficient depth variation. A depth map and radiance image are estimated by standard dehazing methods. The radiance image is then segmented into a small number of clusters, and a corresponding scene plane is estimated for each. This provides the basic structure of a layered scene model, without the need for multiple views, or image correspondences. We show that problems of gap filling and depth blending can be addressed systematically, with respect to the layered depth structure. The final models, which resemble cardboard ‘pop-ups’, are visually convincing. An implementation is described, and subjective depth preferences are tested in a psychophysical experiment.
A cross-sectional survey of physical strains among offshore wind farm workers in the German exclusive economic zone

Objectives To assess the physical strains of employees in the German offshore wind industry, according to job type and phase of the wind farm (under construction or operation). Design Web-based cross-sectional survey. Setting Offshore wind farm companies operating within the German exclusive economic zone. Participants Male workers with regular offshore commitments and at least 28 days spent offshore in the past year (n=268). Outcome measures Physical strains (eg, climbing, noise, working overhead, with twisted upper body or in confined spaces, vibration, heavy lifting, humidity, odours). Results The most frequently mentioned physical strain was ’climbing’ with 63.8% of the respondents reporting to be always or frequently confronted with climbing and ascending stairs during offshore work. Work as a technician was associated with a greater exposition to noise, vibrations, humidity, cold, heat, chemical substances, lifting/carrying heavy loads, transport of equipment, working in non-ergonomic positions and in cramped spaces, as well as climbing. Indeed, statistical analyses showed that, after adjusting for phase of the wind farm, age, nationality, offshore experience, work schedule and type of shift, compared with non-technicians, working as a technician was associated with more frequently lifting/carrying of heavy loads (OR 2.58, 95% CI 1.58 to 4.23), transport of equipment (OR 2.06 95% CI 1.27 to 3.33), working with a twisted upper body (OR 2.85 95% CI 1.74 to 4.69), working overhead (OR 2.77 95% CI 1.67 to 4.58) and climbing (OR 2.30 95% CI 1.40 to 3.77). Working in wind farms under construction was strongly associated with increased and decreased exposure to humidity (OR 2.32 95% CI 1.38 to 3.92) and poor air quality (OR 0.58 95% CI 0.35 to 0.95), respectively. Conclusions Workers on offshore wind farms constitute a heterogeneous group, including a wide variety of occupations. The degree of exposure to detrimental physical strains varies depending on the type of job. Technicians are more exposed to ergonomic challenges than other offshore workers.