Miracle-dz/UniFAR-FTUs huggingface dataset:
The risk for psychiatric disorders in relatives of schizophrenic and control probands: a comparison of three independent studies

Background. Although replication is the heart of science, psychiatric geneticists rarely have the opportunity to replicate findings, especially more than once. Methods. This article reviews results from three independent family studies of schizophrenia on which one of us conducted diagnostic reviews: the Danish Adoption Study (DAS), the Iowa 500 non-500 family study (IFS), and the Roscommon Family Study (RFS). We utilized DSM-III or DSM-III-R criteria and meta-analysis techniques. Results. The odds ratios (OR) in personally interviewed, first degree biological relatives of schizophrenic and matched control probands for schizophrenia, other non-affective psychoses (ONAP), schizotypal personality disorder (SPD), unipolar affective illness (UPAI), bipolar affective illness (BPAI), and anxiety disorders were homogeneous across studies. For alcoholism, ORs were significantly heterogeneous. Schizophrenia, SPD and ONAP strongly aggregated in relatives of schizophrenic probands with decreasing common OR estimates of 16·2, 5·0 and 4·0, respectively. The common OR for anxiety disorders was 1·1, indicating no familial co-aggregation. For UPAI and BPAI, the common ORs exceeded unity (1·3 and 1·9, respectively), although only the former was statistically significant. Conclusions. Schizophrenia strongly aggregates in families and shares familial factors with SPD and ONAP but not anxiety disorders. The familial factors of aetiological importance for schizophrenia and affective illness may be weakly related. With the exception of alcoholism, the patterns of psychiatric disorders in relatives of schizophrenic and control probands in these three studies were sufficiently similar that, despite their methodological differences, they can probably be viewed as replications of one another.
Enhancing voxel carving by capture volume calculations

Many multi camera based approaches on dense volumetric 3d reconstruction depend on the correctly chosen often manually defined reconstruction volume and a reliable foreground/background segmentation process. We present an algorithm to automatically calculate the 3d polyhedron of the reconstruction volume seen by all cameras of a calibrated multi camera setup by utilizing the calibration data. The information from this polyhedron can not only be used to define the reconstruction volume but also to improve the reconstruction process significantly in terms of runtime and/or quality of reconstruction as presented in the evaluation section, in which the algorithm has been successfully tested on real life data.
GlobPlot: exploring protein sequences for globularity and disorder

A major challenge in the proteomics and structural genomics era is to predict protein structure and function, including identification of those proteins that are partially or wholly unstructured. Non-globular sequence segments often contain short linear peptide motifs (e.g. SH3-binding sites) which are important for protein function. We present here a new tool for discovery of such unstructured, or disordered regions within proteins. GlobPlot (http://globplot.embl.de) is a web service that allows the user to plot the tendency within the query protein for order/globularity and disorder. We show examples with known proteins where it successfully identifies inter-domain segments containing linear motifs, and also apparently ordered regions that do not contain any recognised domain. GlobPlot may be useful in domain hunting efforts. The plots indicate that instances of known domains may often contain additional N- or C-terminal segments that appear ordered. Thus GlobPlot may be of use in the design of constructs corresponding to globular proteins, as needed for many biochemical studies, particularly structural biology. GlobPlot has a pipeline interface--GlobPipe--for the advanced user to do whole proteome analysis. GlobPlot can also be used as a generic infrastructure package for graphical displaying of any possible propensity.
Assortative mating and persistent reproductive isolation in hybrids

Significance Understanding the processes that generate or breakdown reproductive isolation between species is essential to understanding evolution. Assortative mating mediates reproductive isolation between species, but its dynamics in natural populations are poorly understood. Here we show that strong assortative mating maintains reproductive isolation in a natural hybrid population following an initial breakdown when the hybrid population formed, and strongly shaped the genetic structure of this population over ∼25 generations. Intriguingly, although in the wild these mate preferences result in nearly 100% of matings occurring between similar genotypes, this barrier breaks down in the laboratory. Our results highlight the importance of assortative mating in shaping hybrid population evolution and imply that short-term breakdown in assortative mating can have long-term evolutionary consequences. The emergence of new species is driven by the establishment of mechanisms that limit gene flow between populations. A major challenge is reconciling the theoretical and empirical importance of assortative mating in speciation with the ease with which it can fail. Swordtail fish have an evolutionary history of hybridization and fragile prezygotic isolating mechanisms. Hybridization between two swordtail species likely arose via pollution-mediated breakdown of assortative mating in the 1990s. Here we track unusual genetic patterns in one hybrid population over the past decade using whole-genome sequencing. Hybrids in this population formed separate genetic clusters by 2003, and maintained near-perfect isolation over 25 generations through strong ancestry-assortative mating. However, we also find that assortative mating was plastic, varying in strength over time and disappearing under manipulated conditions. In addition, a nearby population did not show evidence of assortative mating. Thus, our findings suggest that assortative mating may constitute an intermittent and unpredictable barrier to gene flow, but that variation in its strength can have a major effect on how hybrid populations evolve. Understanding how reproductive isolation varies across populations and through time is critical to understanding speciation and hybridization, as well as their dependence on disturbance.
Novel Antigen Identification Method for Discovery of Protective Malaria Antigens by Rapid Testing of DNA Vaccines Encoding Exons from the Parasite Genome

ABSTRACT We describe a novel approach for identifying target antigens for preerythrocytic malaria vaccines. Our strategy is to rapidly test hundreds of DNA vaccines encoding exons from the Plasmodium yoelii yoelii genomic sequence. In this antigen identification method, we measure reduction in parasite burden in the liver after sporozoite challenge in mice. Orthologs of protective P. y. yoelii genes can then be identified in the genomic databases of Plasmodium falciparum and Plasmodium vivax and investigated as candidate antigens for a human vaccine. A pilot study to develop the antigen identification method approach used 192 P. y. yoelii exons from genes expressed during the sporozoite stage of the life cycle. A total of 182 (94%) exons were successfully cloned into a DNA immunization vector with the Gateway cloning technology. To assess immunization strategies, mice were vaccinated with 19 of the new DNA plasmids in addition to the well-characterized protective plasmid encoding P. y. yoelii circumsporozoite protein. Single plasmid immunization by gene gun identified a novel vaccine target antigen which decreased liver parasite burden by 95% and which has orthologs in P. vivax and P. knowlesi but not P. falciparum. Intramuscular injection of DNA plasmids produced a different pattern of protective responses from those seen with gene gun immunization. Intramuscular immunization with plasmid pools could reduce liver parasite burden in mice despite the fact that none of the plasmids was protective when given individually. We conclude that high-throughput cloning of exons into DNA vaccines and their screening is feasible and can rapidly identify new malaria vaccine candidate antigens.
Extrinsic Calibration of Camera Networks Using a Sphere

In this paper, we propose a novel extrinsic calibration method for camera networks using a sphere as the calibration object. First of all, we propose an easy and accurate method to estimate the 3D positions of the sphere center w.r. t. the local camera coordinate system. Then, we propose to use orthogonal procrustes analysis to pairwise estimate the initial camera relative extrinsic parameters based on the aforementioned estimation of 3D positions. Finally, an optimization routine is applied to jointly refine the extrinsic parameters for all cameras. Compared to existing sphere-based 3D position estimators which need to trace and analyse the outline of the sphere projection in the image, the proposed method requires only very simple image processing: estimating the area and the center of mass of the sphere projection. Our results demonstrate that we can get a more accurate estimate of the extrinsic parameters compared to other sphere-based methods. While existing state-of-the-art calibration methods use point like features and epipolar geometry, the proposed method uses the sphere-based 3D position estimate. This results in simpler computations and a more flexible and accurate calibration method. Experimental results show that the proposed approach is accurate, robust, flexible and easy to use.
Antimicrobial susceptibility of 103 strains of Haemophilus ducreyi isolated in Johannesburg

Of 103 strains of Haemophilus ducreyi isolated in Johannesburg, 96 produced beta-lactamase and were resistant to penicillin and ampicillin. Most strains showed resistance to tetracycline, sulfisoxazole, and sulfamethoxazole. All isolates were susceptible to rifampin, erythromycin, and cefoxitin, moderately susceptible to trimethoprim-sulfamethoxazole (1:19) and minocycline, and somewhat less susceptible to doxycycline.
Image-Based Mosaics: An Variable Construction Method

Image-based mosaic which transfers cells of a target image with a group of tile images preserving the whole appearance of the target image is a Non-Photo realistic Rendering (NPR) technique. a general mosaic algorithm includes cell partition and image database searching for tile images which look most similar with the cell images. in this paper, a target image is partitioned into different size cells with a Quad Tree method and then selected tile images from a very small Self-Organizing Map clustered database fill the cells. the cell partition and tile image selections are processed in a variable manner to generate different mosaics without losing aesthetic effect.
Managing Distributed, Shared L2 Caches through OS-Level Page Allocation

This paper presents and studies a distributed L2 cache management approach through OS-level page allocation for future many-core processors. L2 cache management is a crucial multicore processor design aspect to overcome non-uniform cache access latency for good program performance and to reduce on-chip network traffic and related power consumption. Unlike previously studied hardware-based private and shared cache designs implementing a "fixed" caching policy, the proposed OS-micro architecture approach is flexible; it can easily implement a wide spectrum of L2 caching policies without complex hardware support. Furthermore, our approach can provide differentiated execution environment to running programs by dynamically controlling data placement and cache sharing degrees. We discuss key design issues of the proposed approach and present preliminary experimental results showing the promise of our approach
Increased TNF-α/IFN-γ/IL-2 and Decreased TNF-α/IFN-γ Production by Central Memory T Cells Are Associated with Protective Responses against Bovine Tuberculosis Following BCG Vaccination

Central memory T cell (Tcm) and polyfunctional CD4 T cell responses contribute to vaccine-elicited protection with both human and bovine tuberculosis (TB); however, their combined role in protective immunity to TB is unclear. To address this question, we evaluated polyfunctional cytokine responses by CD4 T cell effector/memory populations from bacille Calmette–Guerin (BCG) vaccinated and non-vaccinated calves by flow cytometry prior to and after aerosol challenge with virulent Mycobacterium bovis. Polyfunctional cytokine expression patterns in the response by Tcm, effector memory, and effector T cell subsets were similar between BCG-vaccinated and M. bovis-infected calves, only differing in magnitude (i.e., infected > vaccinated). BCG vaccination, however, did alter the kinetics of the ensuing response to virulent M. bovis infection. Early after challenge (3 weeks post-infection), non-vaccinates had greater antigen-specific interferon-γ (IFN-γ)/tumor necrosis factor-α (TNF-α) and lesser IFN-γ/TNF-α/IL-2 responses by Tcm cells than did vaccinated animals. Importantly, these differences were also associated with mycobacterial burden upon necropsy. Polyfunctional responses to ESAT-6:CFP10 (antigens not synthesized by BCG strains) were detected in memory subsets, as well as in effector cells, as early as 3 weeks after challenge. These findings suggest that cell fate divergence may occur early after antigen priming in the response to bovine TB and that memory and effector T cells may expand concurrently during the initial phase of the immune response. In summary, robust IFN-γ/TNF-α response by Tcm cells is associated with greater mycobacterial burden, while IFN-γ/TNF-α/IL-2 response by Tcm cells are indicative of a protective response to bovine TB.
Diverse Soft Real-Time Processing in an Integrated System

The simple notion of soft real-time processing has fractured into a spectrum of diverse soft real-time types with a variety of different resource and time constraints. Schedulers have been developed for each of these types, but these are essentially point solutions in the space of soft real-time and no detailed unified definition of soft real-time has previously been provided that includes all types of soft realtime processing. We present a complete real-time taxonomy covering the spectrum of processes from best-effort to hard real-time. The taxonomy divides processes into nine classes based on their resource and timeliness requirements and includes four soft real-time classes, each of which captures a group of soft real-time applications with similar characteristics. We exploit the different features of each of the soft real-time classes to integrate all of them into a single scheduler together with hard real-time and best-effort processes and present results demonstrating their performance
Electron transport in high aspect ratio semiconductor nanowires and metal-semiconductor interfaces

We are facing variability problems for modern semiconductor transistors due to the fact that the performances of nominally identical devices in the scale of 10∼100 nm could be dramatically different attributed to the small manufacturing variations. Different doping strategies give statistical variations in the number of dopant atom density ND in the channel. The material size gives variations in wire diameter dW . And the immediate environment of the material leads to an additional level of variability. E.g. vacuum-semiconductor interface causes variations in surface state density Ds, metal-semiconductor interface causes variations in Schottky barrier and dielectric semiconductor interface induces dielectric confinement at small scales. To approach these variability problems, I choose Si-doped GaAs nanowires as an example. I investigate transport in Si-doped GaAs nanowire (NW) samples contacted by lithographically patterned Gold-Titanium films as function of temperature T . I find a drastically different temperature dependence between the wire resistance RW , which is relatively weak, and the zero bias resistance RC , which is strong. I show that the data are consistent with a model based on a sharp donor energy level slightly above the bottom of the semiconductor conduction band and develop a simple method for using transport measurements for estimates of the doping density after nanowire growth. I discuss the predictions of effective free carrier density neff as function of the surface state density Ds and wire size dW . I also describe a correction to the widely used model of Schottky contacts that improves thermodynamic consistency of the Schottky tunnel barrier profile and show that the original theory may underestimate the barrier conductance under certain conditions. I also provide analytical calculations for shallow silicon dopant energy in GaAs crystals, and find the presence of dielectrics (dielectric screening) and free carriers (Coulomb screening) cause a reduction of ionization energy and shift the donor energy level ED upward, accompanying conduction band EC shift downward due to band gap narrowing for doped semiconductor material. The theoretical results are in a reasonable agreement with previous experimental data. I also find that when the material reduces to nanoscale, dielectric confinement and surface depletion compete with both Coulomb screening and dielectric screening that shift the donor level ED down towards the band gap. The calculation should be appropriate for all types of semiconductors and dopant species. To my parents Shuyuan and Huiping. I hope that this achievement will realize the dream that you had for me all those many years ago when you chose to give me the best education you could.
A nanoliter rotary device for polymerase chain reaction

Polymerase chain reaction (PCR) has revolutionized a variety of assays in biotechnology. The ability to implement PCR in disposable and reliable microfluidic chips will facilitate its use in applications such as rapid medical diagnostics, food control testing, and biological weapons detection. We fabricated a microfluidic chip with integrated heaters and plumbing in which various forms of PCR have been successfully demonstrated. The device uses only 12 nL of sample, one of the smallest sample volumes demonstrated to date. Minimizing the sample volume allows low power consumption, reduced reagent costs, and ultimately more rapid thermal cycling.
Impact of severity of a child's chronic condition on the functioning of two-parent families.

OBJECTIVE To examine the impact of the severity of a child's chronic condition on family functioning from the perspectives of mothers and fathers and to compare their reports with the functioning of families with healthy children. METHODS Mothers and fathers in two-parent families of 160 infants and 102 pre-adolescents with a wide range of chronic health conditions (noncategorical approach) completed standard self-report inventories. RESULTS The families of children with chronic conditions functioned as well or better compared with normative data for families with healthy children. The only significant differences between mothers' and fathers' reports of family functioning were a greater negative impact on role performance reported by mothers of infants and pre-adolescents and a great negative impact on affective expression reported by fathers of pre-adolescents. CONCLUSIONS Overall, very little of the variance in family functioning was explained by severity of the child's chronic condition in this sample of middle-class, two-parent families.
Improving the Cluster Efficiency on Sea Level Rise Dataset using Data Discretization

Rising sea levels, an effect of global warming, is a cause of concern and it is likely to affect the developing countries. With respect to the data set published for research at the World Bank, clustering a data mining technique is applied to detect the most likely to be affected regions. When tested with the k-Means clustering technique, the result of the clustering process reveals a lot of imperfections; this research analyzes the use of data discretization to improve the quality of the clustering process.
Learning and generalization of complex tasks from unstructured demonstrations

We present a novel method for segmenting demonstrations, recognizing repeated skills, and generalizing complex tasks from unstructured demonstrations. This method combines many of the advantages of recent automatic segmentation methods for learning from demonstration into a single principled, integrated framework. Specifically, we use the Beta Process Autoregressive Hidden Markov Model and Dynamic Movement Primitives to learn and generalize a multi-step task on the PR2 mobile manipulator and to demonstrate the potential of our framework to learn a large library of skills over time.
Nonlinear Formulation of Flexible-Link Robots Based on Finite Element Approach

This paper presents a nonlinear formulation to model flexible-link robots based on finite element approach. To derive nonlinear dynamic equations of the flexible-link robot, links are modeled by some finite elements, and Lagrange’s principle is used for dynamic modeling. A local coordinate system is attached to each link and the local displacement of an arbitrary point is formulated based on nodal coordinates and shape functions of beam element. Then by a transformation matrix, total displacement of the robot is presented. Finally the nonlinear dynamic model of the system is developed and formulated.
Exploring Large Virtual Environments by Thoughts Using a BrainComputer Interface Based on Motor Imagery and High-Level Commands

Braincomputer interfaces (BCI) are interaction devices that enable users to send commands to a computer by using brain activity only. In this paper, we propose a new interaction technique to enable users to perform complex interaction tasks and to navigate within large virtual environments (VE) by using only a BCI based on imagined movements (motor imagery). This technique enables the user to send high-level mental commands, leaving the application in charge of most of the complex and tedious details of the interaction task. More precisely, it is based on points of interest and enables subjects to send only a few commands to the application in order to navigate from one point of interest to the other. Interestingly enough, the points of interest for a given VE can be generated automatically thanks to the processing of this VE geometry. As the navigation between two points of interest is also automatic, the proposed technique can be used to navigate efficiently by thoughts within any VE. The input of this interaction technique is a newly-designed self-paced BCI which enables the user to send three different commands based on motor imagery. This BCI is based on a fuzzy inference system with reject options. In order to evaluate the efficiency of the proposed interaction technique, we compared it with the state of the art method during a task of virtual museum exploration. The state of the art method uses low-level commands, which means that each mental state of the user is associated with a simple command such as turning left or moving forward in the VE. In contrast, our method based on high-level commands enables the user to simply select its destination, leaving the application performing the necessary movements to reach this destination. Our results showed that with our interaction technique, users can navigate within a virtual museum almost twice as fast as with low-level commands, and with nearly half the commands, meaning with less stress and more comfort for the user. This suggests that our technique enables efficient use of the limited capacity of current motor imagery-based BCI in order to perform complex interaction tasks in VE, opening the way to promising new applications.