Miracle-dz/UniFAR-FTUs huggingface dataset:
The Increase of Lactobacillus Species in the Gut Flora of Newborn Broiler Chicks and Ducks Is Associated with Weight Gain

Background A bacterial role in the obesity pandemic has been suspected based on the ingestion of probiotics that can modify the gut flora. The objective of our study was to determine if increased Lactobacillus sp. in the gut flora of newborn broiler chicks and ducks could result in weight gain increase. Methodology Female broiler chicks (Gallus gallus domesticus) and ducks (Anas platyrhynchos domestica) were separated into one control and two experimental groups, and inoculated once or twice with 4×1010 Lactobacillus spp. per animal in PBS, or with PBS alone. Fecal samples were collected before and at 24 hours, 2, 4, 8, 16 and 30 days after the inoculation. DNA was extracted from the stools, and qPCR assays were performed on a MX3000™ system for the detection and quantification of Lactobacillus sp. , Bacteroidetes and Firmicutes, using a quantification plasmid. Animals were measured and sacrificed 60 days after the beginning of the experiment, and livers were collected and measured. Principal Findings Chicks inoculated once and twice with Lactobacillus weighed 10.2% (p = 0.0162) and 13.5% (p = 0.0064) more than the control group animals, respectively. Similarly, ducks inoculated once and twice weighed 7.7% (p = 0.05) and 14% (p = 0.035) more than those in the control group, respectively. Liver mass was also significantly higher in inoculated animals compared to the control group. Inoculation with Lactobacillus sp. increased the DNA copies of Lactobacillus spp. and Firmicutes in the stools. Bacteroidetes remained stable, and only the second Lactobacillus sp. inoculation significantly decreased its population in chicks. The ratio of DNA copies of Firmicutes to those of Bacteroidetes increased to as much as 6,4 in chicks and 8,3 in ducks. Conclusions Differences in the intestinal microbiota may precede weight increase, as we found that an increase of Lactobacillus sp. in newborn ducks and chicks preceded the development of weight gain.
Autonomous dynamic driving control of wheeled mobile robots

We propose a novel control framework to enable nonholonomic wheeled mobile robots (WMRs) to autonomously drive in an environment with the speed fast enough so that the dynamics effect (e.g., Coriolis effect) is not negligible, yet, still less than a certain threshold to prevent slippage at the wheels. For this, instead of the Newtonian vehicle modeling, we adopt Lagrange-D'Alembert formulation, which then allows us to explicitly relate the system's state/control with the constraint force, so that we can predict/detect possibility of a given motion's violating the no-slip condition. We present a scheme to generate a no-slip/collision-free timed-trajectory for the WMRs using this Lagrange-D'Alembert formulation. We also propose a backstepping-based control law, which enables the WMR to track the generated trajectory while respecting its nonholonomic constraints. Experiment, using a modified commercial radio-controlled car, is performed to verify the theory.
Securing Legacy C Applications Using Dynamic Data Flow Analysis

Most attacks on networks and information systems consist of exploits of software vulnerabilities. Even safe programming languages are not immune to problems such as Structured Query Language (SQL) injection, cross-site scripting, or other information flow-related vulnerabilities. While current technological and educational efforts seek to ensure the security of future applications, millions of lines of existing software must be secured as we work to defend our national infrastructure. What is needed is an automatic and scalable method that identifies and traps runtime exploits and that can update existing software as security policies evolve. This article presents ongoing research on an approach to securing legacy C applications, while remaining applicable to future problems and languages.
Square Root Unscented Kalman Filters for State Estimation of Induction Motor Drives

This paper investigates the application, design, and implementation of the square root unscented Kalman filter (UKF) (SRUKF) for induction motor (IM) sensorless drives. The UKF uses nonlinear unscented transforms (UTs) in the prediction step in order to preserve the stochastic characteristics of a nonlinear system. The advantage of using the UT is its ability to capture the nonlinear behavior of the system, unlike the extended Kalman filter (EKF) that uses linearized models. The SRUKF implements the UKF using square root filtering to reduce computational errors. We discuss the theoretical aspects and implementation details of the SRUKF for IM drives. Experimental results for a direct-torque-controlled drive are presented for a wide speed range of operation, with focus on low-speed performance. A comparison with the conventional EKF and the UKF is included. Our results show that the SRUKF is a viable and powerful tool for IM state estimation.
A Field Too Crowded? How Measures of Market Structure Shape Nonprofit Fiscal Health

This article explores how various dimensions of market structure, often used to measure organizational crowding, affect the fiscal health of nonprofit organizations. Using 2011 National Center for Charitable Statistics (NCCS) nonprofit sector data, our findings generally support population ecology’s model of a curvilinear relationship between density and days of spending. However, we also find that single dimensions of market structure do not fully capture the effects of market competition. Increasing density has a negative effect on the fiscal health of organizations in markets in which resources are more evenly distributed among actors, whereas increasing density of organizations has a positive effect on organizational fiscal health in markets in which resources are less evenly distributed among actors. These results are sensitive to different specifications of fiscal health and field of nonprofit activity.
Personalized medicine in diabetes: the role of ‘omics’ and biomarkers

Personalized medicine, otherwise called stratified or precision medicine, aims to better target intervention to the individual to maximize benefit and minimize harm. This review discusses how diabetes aetiology, pathophysiology and patient genotype influence response to or side effects of the commonly used diabetes treatments. C‐peptide is a useful biomarker that is underused to guide treatment choice, severe insulin deficiency predicts non‐response to glucagon‐like peptide‐1 receptor agonists, and thiazolidinediones are more effective in insulin‐resistant patients. The field of pharmacogenetics is now yielding clinically important results, with three examples outlined: sulphonylurea sensitivity in patients with HNF1A maturity‐onset diabetes of the young; sulphonylurea sensitivity in patients with Type 2 diabetes with reduced function alleles at CYP2C9, resulting in reduced metabolism of sulphonylureas; and severe metformin intolerance associated with reduced function organic cation transporter 1 (OCT1) variants, exacerbated by drugs that also inhibit OCT1. Genome‐wide approaches and the potential of other ‘omics’, including metagenomics and metabolomics, are then outlined, highlighting the complex interacting networks that we need to understand before we can truly personalize diabetes treatments.
Master in Computer Vision and Artificial Intelligence Report of the Master Project Option : Computer Vision Perceptual Organization for Text Extraction in Natural Scenes

The automated understanding of textual information in natural scenes is an important problem to solve for the Computer Vision and Document Analysis community. In this Thesis we approach the problem of text detection and extraction from an anthropocentric point of view, arguing that the Gestalt grouping laws, as a primary process in the human vision system, is something inherent in the complex cognitive task of reading. Our research hypothesis is therefore that placing Perceptual Organization at the heart of the task of Text Extraction in Natural Scenes will help increasing the performance obtained by current state of the art methods. We present a new method for text extraction in natural scenes inspired by the Perceptual Organization Theory. The method combines two di erent clustering techniques in a single parameter-free clustering procedure. This Perceptual Organization Clustering is totally independent of the language or script in which text appears, can deal with any kind of font types and sizes, and is not constrained to horizontally aligned text. The obtained results in several experiments on the ICDAR2003 dataset give rise interesting conclusions in the context of perceptual grouping of text components and achieve su cient success to warrant further development.
FTCloud: A Component Ranking Framework for Fault-Tolerant Cloud Applications

Cloud computing is becoming a mainstream aspect of information technology. The cloud applications are usually large-scale, complex, and include a lot of distributed components. Providing highly reliable cloud applications is a challenging and critical research problem. To attack this challenge, we propose FTCloud which is a component ranking based framework for building fault-tolerant cloud applications. FTCloud employs the component invocation structures and the invocation frequencies to identify the significant components in a cloud application. An algorithm is proposed to automatically determine optimal fault tolerance strategy for these significant components. The experimental results show that by tolerating faults of a small part of the most significant components, the reliability of cloud application can be greatly improved.
The effects of client attachment styles and therapeutic alliance on treatment outcome

The purpose of this study was to evaluate changes in symptoms of psychological distress and psychological well-being in clients being seen at a community mental health center as a function of the strength of the clienttherapist working alliance and of the client's attachment to the therapist. It was anticipated that Secure attachment styles and strong working alliances would be associated with positive treatment outcomes (i.e., decreases in symptoms of psychological distress and increases in psychological well­ being) over the course of therapy. It was also expected that Dismissing and Preoccupied attachment styles would be associated with negative treatment outcomes (i.e., little or few decreases in symptoms of psychological distress and little or few increases in psychological well-being) over the course of therapy. The results of this study were all in the expected direction. Positive outcomes were associated with Secure attachment styles and strong working alliances while negative outcomes were associated with Dismissing and Preoccupied attachment styles. However, probably due to sample size (N=13), few of these associations reached statistical significance. These findings suggest that the, quality of the,therapeutic relationship, including the client's ability to form a
Exome sequencing identifies mutations in the gene TTC7A in French-Canadian cases with hereditary multiple intestinal atresia

Background Congenital multiple intestinal atresia (MIA) is a severe, fatal neonatal disorder, involving the occurrence of obstructions in the small and large intestines ultimately leading to organ failure. Surgical interventions are palliative but do not provide long-term survival. Severe immunodeficiency may be associated with the phenotype. A genetic basis for MIA is likely. We had previously ascertained a cohort of patients of French-Canadian origin, most of whom were deceased as infants or in utero. The goal of the study was to identify the molecular basis for the disease in the patients of this cohort. Methods We performed whole exome sequencing on samples from five patients of four families. Validation of mutations and familial segregation was performed using standard Sanger sequencing in these and three additional families with deceased cases. Exon skipping was assessed by reverse transcription-PCR and Sanger sequencing. Results Five patients from four different families were each homozygous for a four base intronic deletion in the gene TTC7A, immediately adjacent to a consensus GT splice donor site. The deletion was demonstrated to have deleterious effects on splicing causing the skipping of the attendant upstream coding exon, thereby leading to a predicted severe protein truncation. Parents were heterozygous carriers of the deletion in these families and in two additional families segregating affected cases. In a seventh family, an affected case was compound heterozygous for the same 4bp deletion and a second missense mutation p.L823P, also predicted as pathogenic. No other sequenced genes possessed deleterious variants explanatory for all patients in the cohort. Neither mutation was seen in a large set of control chromosomes. Conclusions Based on our genetic results, TTC7A is the likely causal gene for MIA.
Anaerobic Biotransformation of Aromatic and Polycyclic Aromatic Hydrocarbons in Soil Microcosms: A Review

Industrial activities introduce a wide variety of xenobiotic aromatic compounds into the biosphere. These aromatic and polycyclic aromatic compounds find their way into anaerobic marine and freshwater sediments, saturated aquifers, and waterlogged soils where neither their impact on carbon flow nor their propensity to persist is clearly understood. Although some halogenated aromatic compounds are degraded via anaerobic pathways, anaerobic transformation of aromatics remains limited to a small range of chemicals. This paper reviews anaerobic transformation processes for aromatic compounds, particularly polycyclic aromatic hydrocarbons (PAHs) in soil microcosms. A simplified pathway of PAH biotransformation and a conceptual pathway of PAH degradation under different redox-conditions are presented.
A Content Based Image Watermarking Scheme Resilient to Geometric Attacks

— Multimedia security is an incredibly significant area of concern. The paper aims to discuss a robust image watermarking scheme, which can withstand geometric attacks. The source image is initially moment normalized in order to make it withstand geometric attacks. The moment normalized image is wavelet transformed. The first level wavelet transformed image is segmented into blocks if size 8x8. The product of mean and standard and standard deviation of each block is computed. The second level wavelet transformed image is divided into 8x8 blocks. The product of block mean and the standard deviation are computed. The difference between products in the two levels forms the watermark. The watermark is inserted by modulating the coefficients of the mid frequencies. The modulated image is inverse wavelet transformed and inverse moment normalized to generate the watermarked image. The watermarked image is now ready for transmission. The proposed scheme can be used to validate identification cards and financial instruments. The performance of this scheme has been evaluated using a set of parameters. Experimental results show the effectiveness of this scheme.
Where does Afghanistan fit in China’s grand project? A content analysis of Afghan and Chinese news coverage of the One Belt, One Road initiative

One Belt, One Road is a political and economic initiative developed by China to revive ancient trade routes in an effort to encourage international trade. One Belt, One Road will increase China’s economic reach but also promises to improve the political and economic standards of countries involved in the program. The initiative holds transformative opportunities for Afghanistan, as the country continues to experience political and economic instability. One Belt, One Road, though is met with differing perspectives, where critics of the initiative point toward China’s exploitative desires. Through content analysis of China’s People’s Daily and Global Times as well as Afghanistan’s Khaama Press, this article suggests China and Afghanistan’s involvement in the One Belt, One Road initiative is rooted in vastly different interests.
Nearly Optimal Preconditioned Methods for Hermitian Eigenproblems Under Limited Memory. Part II: Seeking Many Eigenvalues

In a recent companion paper, we proposed two methods, GD+k and JDQMR, as nearly optimal methods for finding one eigenpair of a real symmetric matrix. In this paper, we seek nearly optimal methods for a large number, nev, of eigenpairs that work with a search space whose size is O(1), independent from nev. The motivation is twofold: avoid the additional O(nevN) storage and the O(nevN) iteration costs. First, we provide an analysis of the oblique projectors required in the Jacobi-Davidson method and identify ways to avoid them during the inner iterations, either completely or partially. Second, we develop a comprehensive set of performance models for GD+k, Jacobi-Davidson type methods, and ARPACK. Based both on theoretical arguments and on our models we argue that any eigenmethod with O(1) basis size, preconditioned or not, will be superseded asymptotically by Lanczos type methods that use O(nev) vectors in the basis. However, this may not happen until nev > O(1000). Third, we perform an extensive set of experiments with our methods and against other state-of-the-art software that validate our models and confirm our GD+k and JDQMR methods as nearly optimal within the class of O(1) basis size methods.
The Ineffectiveness and Inadequacies of International Instruments in Combatting and Ending the Transboundary Movement of Hazardous Wastes and Environmental Degradation in Africa

Despite the fact that international instruments prohibit such activities, recent recurrent incidents involving the transboundary movement of hazardous wastes on the African continent highlight their inadequacies and ineffectiveness of international law in solving this problem. Despite some noticeable milestones achieved by the Bamako Convention, its shortcomings are conspicuous. In addition, the ban on transboundary movement of hazardous wastes is simply one dimension of the bigger problem faced by (many poor) African countries: poor management of the environment that ranges from water and air pollution, poor disposal of wastes, improper and inadequate treatment of domestically generated hazardous wastes, congestion, noise, and dumping. These international instruments deal with only a dimension of the problem faced by African states. It is argued that additional measures must be taken to complement these efforts. Such measures include the enactment of strong laws and policies, education of the masses and a virile civil society.
DockerPolicyModules: Mandatory Access Control for Docker containers

The wide adoption of Docker and the ability to retrieve images from different sources impose strict security constraints. Docker leverages Linux kernel security facilities, such as namespaces, cgroups and Mandatory Access Control, to guarantee an effective isolation of containers. In order to increase Docker security and flexibility, we propose an extension to the Dockerfile format to let image maintainers ship a specific SELinux policy for the processes that run in a Docker image, enhancing the security of containers.
Towards Robust and Automated Head Pose Estimation : Elastic Energy Model( BIOMETRICS AND ITS APPLICATIONS)

Pose estimation is an important part in human face recognition because head rotations will significantly affect the recognition accuracy. However, automated and accurate pose determination still remains an unsolved problem in the research community. In this paper, we propose a novel Elastic Energy Model to tackle this problem, which employs statistical energy contributions of a set of feature points on an input face. It can avoid over-trusting selected anchor points, providing a robust solution to the imprecise feature localization problem that is inevitable in practical applications with cluttered backgrounds. As a general configuration, this model can be easily implemented and extended to other non-rigid objects. Its effectiveness and robustness in automated head pose estimation are investigated in our experiments.
Cosmic statistics of statistics

The errors on statistics measured in finite galaxy catalogues are exhaustively investigated. The theory of errors on factorial moments by Szapudi & Colombi is applied to cumulants via a series expansion method. All results are subsequently extended to the weakly non-linear regime. Together with previous investigations this yields an analytic theory of the errors for moments and connected moments of counts in cells from highly non-linear to weakly non-linear scales. For non-linear functions of unbiased estimators, such as the cumulants, the phenomenon of cosmic bias is identified and computed. Since it is subdued by the cosmic errors in the range of applicability of the theory, correction for it is inconsequential. In addition, the method of Colombi, Szapudi & Szalay concerning sampling effects is generalized, adapting the theory for inhomogeneous galaxy catalogues. While previous work focused on the variance only, the present article calculates the cross-correlations between moments and connected moments as well for a statistically complete description. The final analytic formulae representing the full theory are explicit but somewhat complicated. Therefore we have made available a fortran program capable of calculating the described quantities numerically (for further details e-mail SC at colombi@iap.fr). An important special case is the evaluation of the errors on the two-point correlation function, for which this should be more accurate than any method put forward previously. This tool will be immensely useful in the future for assessing the precision of measurements from existing catalogues, as well as aiding the design of new galaxy surveys. To illustrate the applicability of the results and to explore the numerical aspects of the theory qualitatively and quantitatively, the errors and cross-correlations are predicted under a wide range of assumptions for the future Sloan Digital Sky Survey. The principal results concerning the cumulants ξ¯, Q3 and Q4 is that the relative error is expected to be smaller than 3, 5 and 15 per cent, respectively, in the scale range of 1–10 h−1 Mpc; the cosmic bias will be negligible.
The fitness costs of adaptation via phenotypic plasticity and maternal effects

Summary 1. Phenotypes are often environmentally dependent, which requires organisms to track environmental change. The challenge for organisms is to construct phenotypes using the most accurate environmental cue. 2. Here, we use a quantitative genetic model of adaptation by additive genetic variance, within- and transgenerational plasticity via linear reaction norms and indirect genetic effects respectively. 3. We show how the relative influence on the eventual phenotype of these components depends on the predictability of environmental change (fast or slow, sinusoidal or stochastic) and the developmental lag s between when the environment is perceived and when selection acts. 4. We then decompose expected mean fitness into three components (variance load, adaptation and fluctuation load) to study the fitness costs of within- and transgenerational plasticity. A strongly negative maternal effect coefficient m minimizes the variance load, but a strongly positive m minimises the fluctuation load. The adaptation term is maximized closer to zero, with positive or negative m preferred under different environmental scenarios. 5. Phenotypic plasticity is higher when s is shorter and when the environment changes frequently between seasonal extremes. Expected mean population fitness is highest away from highest observed levels of phenotypic plasticity. 6. Within- and transgenerational plasticity act in concert to deliver well-adapted phenotypes, which emphasizes the need to study both simultaneously when investigating phenotypic evolution.