Miracle-dz/UniFAR-FTUs huggingface dataset:
The landscape genetics of yellow perch (Perca flavescens) in a large fluvial ecosystem

Landscape genetics is being increasingly applied to elucidate the role of environmental features on the population structure of terrestrial organisms. However, the potential of this framework has been little explored in aquatic ecosystems such as large rivers. Here, we used a landscape genetics approach in order to (i) document the population structure of the yellow perch (Perca flavescens) by means of genetic variation at microsatellite markers, (ii) assess to what extent the structure was explained by landscape heterogeneity, and (iii) interpret the relevance of interactions between genetics and landscape for management and conservation. Analysis of the genetic variation among 1715 individuals from 16 localities and distributed over 310 km in the freshwater section of the Saint Lawrence River (Québec, Canada) revealed a relatively modest level of genetic structuring (FST = 0.039). Application of the Monmonier's algorithm combining geographical and genetic information identified three zones of restricted gene flow defining four distinct populations. Physical barriers played a more important role on gene flow and genetic structure than waterway geographical distance. We found correlations between genetic differentiation and presence of distinct water masses in the sector of Lake Saint‐Louis (r = 0.7177, P = 0.0340) and with fragmentation of spawning habitats in the sector of Lake Saint‐Pierre (r = 0.8578, P = 0.0095). Our results support the treatment of four distinct biological units, which is in contrast with the current basis for yellow perch management. Finally, this study showed that landscape genetics is a powerful means to identify environmental barriers to gene flow causing genetic discontinuities in apparently highly connected aquatic landscapes.
Heterophyllin B Ameliorates Lipopolysaccharide-Induced Inflammation and Oxidative Stress in RAW 264.7 Macrophages by Suppressing the PI3K/Akt Pathways

Heterophyllin B (HB), an active cyclic peptide, is a compound existing in the ethyl acetate extract of Pseudostellaria heterophylla (Miq.) Pax and exhibited the activity of inhibiting the production of NO and cytokines, such as IL-1β and IL-6, in LPS-stimulated RAW 264.7 macrophages. In addition, HB suppressed the production of ROS and the apoptosis induced by LPS in RAW 264.7 macrophages. The underlying mechanism was investigated in the LPS-induced RAW 264.7 cells. The results showed that HB decreased the level of IL-1β and IL-6 expression by qRT-PCR analysis. HB up-regulated the relative ratio of p-AKT/AKT and p-PI3K/PI3K as indicated by western blot analysis. In summary, HB inhibited the LPS-induced inflammation and apoptosis through the PI3K/Akt signaling pathways and represented a potential therapeutic target for treatment of inflammatory diseases.
Recent Advances in Biosensor Development for Foodborne Virus Detection

Outbreaks of foodborne diseases related to fresh produce have been increasing in North America and Europe. Viral foodborne pathogens are poorly understood, suffering from insufficient awareness and surveillance due to the limits on knowledge, availability, and costs of related technologies and devices. Current foodborne viruses are emphasized and newly emerging foodborne viruses are beginning to attract interest. To face current challenges regarding foodborne pathogens, a point-of-care (POC) concept has been introduced to food testing technology and device. POC device development involves technologies such as microfluidics, nanomaterials, biosensors and other advanced techniques. These advanced technologies, together with the challenges in developing foodborne virus detection assays and devices, are described and analysed in this critical review. Advanced technologies provide a path forward for foodborne virus detection, but more research and development will be needed to provide the level of manufacturing capacity required.
A structure-factor least-squares refinement procedure for macromolecular structures using constrained and restrained parameters

A method of structure-factor least-squares refinement of constrained groups linked by distance restraints has been developed for the refinement of macromolecular structures. Each constrained group can have any number of variable dihedral rotation parameters within the group in addition to the rigid-body translational, rotational and thermal parameters. The matrix of normal equations may be either full or sparse and provision is made for solution by matrix inversion or the conjugate-gradient iterative method. This procedure has been successfully used for 3 A data and should be applicable even for lower-resolution data and especially for cases with a poorer data-per-atom ratio. The structure of yeast phenylalanine tRNA has been refined with this procedure from a starting crystallographic R value of 42% to a final R value of 25% with isotropic 'group" thermal parameters and 22% with isotropic atomic thermal parameters for 8207 independent reflections at 2.7 A resolution. The proper stereochemistry of bond distances, angles and van der Waals contacts for the restrained atoms was maintained within reasonable limits throughout the refinement. Although originally developed for nucleic acids, this procedure is directly applicable to the refinement of protein structures. In addition, a combination of applying distance restraints between groups and least-squares fitting of these groups to target coordinates has been used purely as an idealization process for imposing proper stereochemistry on an approximate model.
L1-Penalized Robust Estimation for a Class of Inverse Problems Arising in Multiview Geometry

We propose a new approach to the problem of robust estimation in multiview geometry. Inspired by recent advances in the sparse recovery problem of statistics, we define our estimator as a Bayesian maximum a posteriori with multivariate Laplace prior on the vector describing the outliers. This leads to an estimator in which the fidelity to the data is measured by the L∞-norm while the regularization is done by the L1-norm. The proposed procedure is fairly fast since the outlier removal is done by solving one linear program (LP). An important difference compared to existing algorithms is that for our estimator it is not necessary to specify neither the number nor the proportion of the outliers. We present strong theoretical results assessing the accuracy of our procedure, as well as a numerical example illustrating its efficiency on real data.
Translation, Validation, and Crosscultural Adaptation of the Hebrew Version of the Neck Disability Index

Study Design. The present study's design was translation and crosscultural validation of the Neck Disability Index (NDI). Objective. The aim of the study was to translate and culturally adapt the NDI into Hebrew language and to evaluate the psychometric properties of this version. Summary of Background Data. As yet, no Hebrew language neck pain and disability questionnaires exist. The NDI is widely used and validated among different patient populations with neck pain. Methods. The English version of the NDI was translated into Hebrew according to the published guidelines. A total of 100 patients with neck pain participated in the study. Inclusion criteria were age 18 years and older, neck pain, and ability to read and speak Hebrew. Exclusion criteria were cancer or suspected tumor, neck pain related to vertebral fracture, or neurological disease. Participants were asked to complete the NDI-Hebrew version (NDI-H), Numeric Pain Rating Scale (NPRS), and Patient-Specific Functional Scale (PSFS). Seventy-three patients completed the NDI-H twice in an interval of 2 days. Psychometric properties included test-retest reliability (intraclass correlation coefficient), internal consistency (Cronbach &agr;), convergent validity (Pearson correlation), and factor analysis. Results. The NDI-H demonstrated excellent test-retest reliability (intraclass correlation coefficient ranged from 0.827 to 0.929; Pv < 0.001). Cronbach &agr; value was excellent (0.855). A very good correlation was found between the NDI-H and NPRS scores (r = 0.611, P < 0.001) and a good correlation between the NDI-H and PSFS score (r = 0.417, P < 0.001). Factor analysis revealed a two-factor solution representing daily function and pain and symptoms. Conclusion. The NDI-H is a valid and reliable instrument to measure functional limitations and disability in Hebrew-speaking patients with neck pain. Level of Evidence: NA
Linear codes over Fq which are equivalent to LCD codes

Linear codes with complementary duals (abbreviated LCD) are linear codes whose intersection with their dual are trivial. When they are binary, they play an important role in armoring implementations against side-channel attacks and fault injection attacks. Non-binary LCD codes in characteristic 2 can be transformed into binary LCD codes by expansion. In this paper, we introduce a general construction of LCD codes from any linear codes. Further, we show that any linear code over $\mathbb F_{q} (q>3)$ is equivalent to an Euclidean LCD code and any linear code over $\mathbb F_{q^2} (q>2)$ is equivalent to a Hermitian LCD code. Consequently an $[n,k,d]$-linear Euclidean LCD code over $\mathbb F_q$ with $q>3$ exists if there is an $[n,k,d]$-linear code over $\mathbb F_q$ and an $[n,k,d]$-linear Hermitian LCD code over $\mathbb F_{q^2}$ with $q>2$ exists if there is an $[n,k,d]$-linear code over $\mathbb F_{q^2}$. Hence, when $q>3$ (resp.$q>2$) $q$-ary Euclidean (resp. $q^2$-ary Hermitian) LCD codes possess the same asymptotical bound as $q$-ary linear codes (resp. $q^2$-ary linear codes). Finally, we present an approach of constructing LCD codes by extending linear codes.
Energy requirements of women of reproductive age.

BACKGROUND The energy requirements of women have been based on total energy expenditure (TEE) derived from the factorial approach or as multiples of basal metabolic rate (BMR). OBJECTIVE This study was designed to reevaluate the energy requirements of healthy, moderately active underweight, normal-weight, and overweight women of reproductive age. DESIGN The energy requirements of 116 women [n = 13 with a low body mass index (BMI), n = 70 with a normal BMI, and n = 33 with a high BMI] were estimated from TEE measured by the doubly labeled water method. Twenty-four-hour EE and BMR were measured by room respiration calorimetry, activity EE was estimated from nonbasal EE as TEE - BMR, and physical activity level was calculated as TEE/BMR. Body composition was derived from a multicomponent model. Fitness, strength, and physical activity level were assessed, and fasting serum indexes were measured. RESULTS Energy requirements differed among the low-BMI (8.9 +/- 0.9 MJ/d), normal-BMI (10.1 +/- 1.4 MJ/d), and high-BMI (11.5 +/- 1.9 MJ/d) groups (P = 0.02-0.001, all pairwise comparisons). Major predictors of BMR, 24-h EE, and TEE were weight, height, and body composition; minor predictors were fasting metabolic profile and fitness. Fat-free mass and fat mass accounted for the differences in EE seen between the BMI groups. The mean physical activity level of 1.86 suggested that the multiples of BMR used to estimate energy requirements have been underestimated. CONCLUSION Recommended energy intakes for healthy, moderately active women of reproductive age living in industrialized societies should be revised on the basis of TEE.
Generating Functional Analysis of Iterative Sparse Signal Recovery Algorithms with Divergence-Free Estimators

Approximate message passing (AMP) is an effective iterative sparse recovery algorithm for linear system models. Its performance is characterized by the state evolution (SE) which is a simple scalar recursion. However, depending on a measurement matrix ensemble, AMP may face a convergence problem. To avoid this problem, orthogonal AMP (OAMP), which uses de-correlation linear estimation and divergence-free non-linear estimation, was proposed by Ma and Ping. They also provide the SE analysis for OAMP. In their SE analysis, the following two assumptions were made: (i) The estimated vector of the de-correlation linear estimator consists of i.i. d. zero-mean Gaussian entries independent of the vector to be estimated and (ii) the estimated vector of the divergence-free non-linear estimator consists of i.i. d. entries independent of the measurement matrix and the noise vector. In this paper, we derive a simple scalar recursion to characterize iterative sparse recovery algorithms with divergence-free estimators without such assumptions of independence of messages by using the generating functional analysis (GFA), which allows us to study the dynamics by an exact way in the large system limit.
Relationship between life qualities of adolescents and dysmenorrhoea

Objective: In this study, it is aimed to investigate the relationship between life qualities of adolescents who have dysmenorrhoea and do not have in the menstrual period and symptoms. Study Design: This study is a school-based cross-sectional. The search universe consists of the adolescent students (N=1752, between the ages of 13-19 years) from two girl in schools Central Anatolia Region. The study group consists of these students (n=1462) who were at the school in February-June in the year of 2013, had menstrual cycles during last one year, accepted to participate in the study and filled the forms used in the search completely. Method: Data were obtained with a survey form which were improved by the researchers in the result of literature investigation and had 25 questions about socio-demographic and menstrual properties, a VAS pain scale and a life quality scale. Results: Prevalence of dysmenorrhea was found 69.3% in the adolescents who were participated in the survey. 67.0% of the students with dysmenorrhea said that their daily lives were affected by the pain. The average of VAS score was found higher in the students who said that they affected compared to the students who said that they did not affect (p:0.000). The average of VAS score was also found higher in the students who cannot go to school because of dysmenorrhea compared to ones who can go to school (p:0.000). Furthermore, when the average scores were calculated in all sub-domains of SF: an average of 36 points life quality scale, the average scores of the students with dysmenorrhea was found lower according to ones with non-dysmenorrhea (p:0.00). Conclusion: It is said that dysmenorrhoea in the adolescent periods more common than it was considered and it has been also negatively affected the quality of life and the continuity of social life.
Regularization and Applications of a Network Structure Deep Image Prior

Finding a robust image prior is one of the fundamental challenges in image recovery problems. Many priors are based on the statistics of the noise source or assumed features (e.g. sparse gradients) of the image. More recently, priors based on convolutional neural networks have gained increased attention, due to the availability of training data and flexibility of a neural network-based prior. Here, we present results for an entirely novel neuralnetwork based image prior that was introduced in [18], known as a network structure deep image prior. We test the effect of regularization on convergence of the network structure prior, and apply this prior to problems in deconvolution, denoising, and single-pixel camera image recovery. Our results show that regularization does not improve the convergence properties of the network. The performance for improving deconvolution results and single-pixel camera image recovery are also poor. However, the results for denoising are comparable to baseline methods, achieving a strong PSNR for several test images. We believe with further work, this method can be readily applied to similar computational imaging problems such as inpainting and demosaicking.
Pattern Matching Image Compression: Algorithmic and Empirical Results

We propose a non-transform image compression scheme based on approximate 1D pattern matching, called pattern matching image compression (PMIC). The main idea behind it is a lossy extension of the Lempel-Ziv data compression scheme in which one searches for the longest prefix of an uncompressed image that approximately occurs in the already processed image. This main algorithm is enhanced with several new features such as searching for reverse approximate matching, recognizing sub-strings in images that are additively shifted versions of each other, introducing a variable and adaptive maximum distortion level D, and so forth. These enhancements are crucial to the overall quality of our scheme and their efficient implementation leads to algorithmic issues of interest in their own right. Both algorithmic and experimental results are presented. Our scheme turns out to be competitive with JPEG and wavelet compression for good quality graphical images. We also review related theoretical results.
Semi-hierarchical based motion estimation algorithm for the Dirac video encoder

Having fast and efficient motion estimation is crucial in today's advance video compression technique since it determines the compression efficiency and the complexity of a video encoder. In this paper, a method which we call semi-hierarchical motion estimation is proposed for the Dirac video encoder. By considering the fully hierarchical motion estimation only for a certain type of inter frame encoding, complexity of the motion estimation can be greatly reduced while maintaining the desirable accuracy. The experimental results show that the proposed algorithm gives two to three times reduction in terms of the number of SAD calculation compared with existing motion estimation algorithm of Dirac for the same motion estimation accuracy, compression efficiency and PSNR performance. Moreover, depending upon the complexity of the test sequence, the proposed algorithm has the ability to increase or decrease the search range in order to maintain the accuracy of the motion estimation to a certain level.
Enhanced ow visualisation of complex aerodynamic phenomena using automatic stream surface seeding with application to the BLOODHOUND SSC

This application paper describes a novel, cluster-based, semi-automatic, stream surface placement strategy for structured and unstructured computational fluid dynamics (CFD) data, tailored towards a specific application: The BLOODHOUND jet and rocket propelled land speed record vehicle. An existing automatic stream surface placement algorithm(8), is extensively modified to cater for large unstructured CFD simulation data. The existing algorithm uses hierarchical clustering of velocity and distance vectors to find potential stream surface seeding locations. This work replaces the hierarchical clustering algorithm, designed to work with small regular grids, with a K-means clustering approach suitable for large unstructured grids. Modifications are made to the seeding curve construction algorithm, improving the smoothness and distribution of the discretised curve in complex cases. A new distance function is described which allows the user to target particular characteristics Received 5 March 2015; revised 24 September 2015; accepted 24 September 2015. 548 April 2016 The Aeronautical Journal of simulation data. The proposed algorithm reduces the required memory footprint and computational requirement compared to previous work(8). The performance and effectiveness of the proposed algorithm is demonstrated, and CFD domain expert evaluation is provided describing the value of this approach.
Inverse relation between dietary intake of naturally occurring plant sterols and serum cholesterol in northern Sweden.

BACKGROUND Plant sterols are bioactive compounds, found in all vegetable foods, which inhibit cholesterol absorption. Little is known about the effect of habitual natural dietary intake of plant sterols. OBJECTIVE We investigated the relation between plant sterol density (in mg/MJ) and serum concentrations of cholesterol in men and women in northern Sweden. DESIGN The analysis included 37 150 men and 40 502 women aged 29-61 y, all participants in the Västerbotten Intervention Program. RESULTS Higher plant sterol density was associated with lower serum total cholesterol in both sexes and with lower LDL cholesterol in women. After adjustment for age, body mass index (in kg/m(2)), and (in women) menopausal status, men with high plant sterol density (quintile 5) had 0.15 mmol/L (2.6%) lower total serum cholesterol (P for trend = 0.001) and 0.13 mmol/L (3.1%) lower LDL cholesterol (P = 0.062) than did men with low plant sterol density (quintile 1). The corresponding figures for women were 0.20 mmol/L (3.5%) lower total serum cholesterol (P for trend < 0.001) and 0.13 mmol/L (3.2%) lower LDL cholesterol (P for trend = 0.001). CONCLUSIONS The present study is the second epidemiologic study to show a significant inverse relation between naturally occurring dietary plant sterols and serum cholesterol. To the extent that the associations found truly mirror plant sterol intake and not merely a diet high in vegetable fat and fiber, it highlights the importance of considering the plant sterol content of foods both in primary prevention of cardiovascular disease and in the dietary advice incorporated into nutritional treatment of patients with hyperlipidemia.
Strongly Exchange Coupled Core|Shell Nanoparticles with High Magnetic Anisotropy: A Strategy toward Rare-Earth-Free Permanent Magnets

Antiferromagnetic(AFM)|ferrimagnetic(FiM) core|shell (CS) nanoparticles (NPs) of formula Co0.3Fe0. 7O|Co0.6Fe2. 4O4 with mean diameter from 6 to 18 nm have been synthesized through a one-pot thermal decomposition process. The CS structure has been generated by topotaxial oxidation of the core region, leading to the formation of a highly monodisperse single inverted AFM|FiM CS system with variable AFM-core diameter and constant FiM-shell thickness (∼2 nm). The sharp interface, the high structural matching between both phases, and the good crystallinity of the AFM material have been structurally demonstrated and are corroborated by the robust exchange-coupling between AFM and FiM phases, which gives rise to one among the largest exchange bias (H E) values ever reported for CS NPs (8.6 kOe) and to a strongly enhanced coercive field (H C). In addition, the investigation of the magnetic properties as a function of the AFM-core size (d AFM), revealed a nonmonotonous trend of both H C and H E, which display a maxi.
Sequential Monte Carlo for Bayesian Computation

Summary Sequential Monte Carlo (SMC) methods are a class of importance sampling and resampling techniques designed to simulate from a sequence of probability distributions. These approaches have become very popular over the last few years to solve sequential Bayesian inference problems (e.g. Doucet et al. 2001). However, in comparison to Markov chain Monte Carlo (MCMC), the application of SMC remains limited when, in fact, such methods are also appropriate in such contexts (e.g. Chopin (2002); Del Moral et al. (2006)). In this paper, we present a simple unifying framework which allows us to extend both the SMC methodology and its range of applications. Additionally, reinterpreting SMC algorithms as an approximation of nonlinear MCMC kernels, we present alternative SMC and iterative self-interacting approximation (Del Moral & Miclo 2004; 2006) schemes. We demonstrate the performance of the SMC methodology on static and sequential Bayesian inference problems.