Miracle-dz/UniFAR-FTUs huggingface dataset:
Bayesian inference, dysconnectivity and neuromodulation in schizophrenia.

This scientific commentary refers to ‘Estimating changing contexts in schizophrenia’, by Kaplan et al. (doi:10.1093/brain/aww095). The paper by Kaplan et al. in this issue of Brain addresses one of the most interesting questions in contemporary schizophrenia research: the role of uncertainty during perception (Kaplan et al. , 2016). Uncertainty enjoys much interest in schizophrenia research as it may provide a crucial link between core clinical symptoms of schizophrenia—aberrant perceptual inference (e.g. hallucinations) and abnormal beliefs (delusions)—and long-standing neurobiological findings that patients with schizophrenia display widespread alterations in structural and functional brain connectivity (dysconnectivity). These two cardinal features of schizophrenia have been integrated in disease theories, which have developed in three waves. A first influential proposal was that dysconnectivity in schizophrenia arises from abnormal regulation of NMDA receptor (NMDAR)-dependent transmission by neuromodulatory (dopaminergic and cholinergic) influences (Friston, 1998). Given the critical role of NMDARs for synaptic plasticity and myelination, this suggested that both neurodevelopmental aspects of schizophrenia ( cf . abnormal pruning of connections by altered experience-dependent plasticity) and structural dysconnectivity might arise from a primary disturbance of NMDAR-dependent plasticity due to aberrant neuromodulatory control. Second, these putatively abnormal NMDAR-neuromodulator interactions (NNI) were proposed to cause a central computational impairment in schizophrenia: abnormal hierarchical Bayesian inference in the cortex (Stephan et al. , 2006). This proposal was inspired by the notion that the brain constructs a hierarchical and probabilistic model of the world in order to infer the environmental causes of its sensory inputs (predictive coding), and by the increasingly discernible importance of NMDAR-neuromodulator interactions for implementing hierarchical Bayesian inference in the brain (Fig. 1). Under generic conditions, belief updates in Bayesian inference are driven by prediction errors (the difference between actual and predicted inputs) but, critically, weighted by how uncertain or precise both predictions and sensory inputs are. While …
Determinants and Reasons for Dropout in Swimming —Systematic Review

The present research aims to systematically review the determinants and reasons for swimming dropout. The systematic review was conducted through electronic searches on the Web of Knowledge and PsycInfo databases from 2 February to 29 July 2015, using the keywords dropout, withdrawal, motives, reasons, sport, framework-theories, motivation, swim*, review, attrition and compliance. Fifteen studies were found and six were fully reviewed and its data extracted and analysed. Most studies were undertaken in Canada and in the United States of America (USA), and one study was conducted in Spain. Most participants were female (65.74%), and the main reasons for dropout were ‘conflicts with their trainers’, ‘other things to do’, ‘competence improvements’ failure’, ‘parents, couples or trainers’ pressure’, ‘lack of enjoyment’ and ‘get bored’. This review contributes to the present knowledge on the understanding of dropout in swimming. However, it is necessary to continue researching on this topic, validating measurement instruments and studying the motivational processes related to dropout and persistence.
Complete Plastid Genome of the Brown Alga Costaria costata (Laminariales, Phaeophyceae)

Costaria costata is a commercially and industrially important brown alga. In this study, we used next-generation sequencing to determine the complete plastid genome of C. costata. The genome consists of a 129,947 bp circular DNA molecule with an A+T content of 69.13% encoding a standard set of six ribosomal RNA genes, 27 transfer RNA genes, and 137 protein-coding genes with two conserved open reading frames (ORFs). The overall genome structure of C. costata is nearly the same as those of Saccharina japonica and Undaria pinnatifida. The plastid genomes of these three algal species retain a strong conservation of the GTG start codon while infrequently using TGA as a stop codon. In this regard, they differ substantially from the plastid genomes of Ectocarpus siliculosus and Fucus vesiculosus. Analysis of the nucleic acid substitution rates of the Laminariales plastid genes revealed that the petF gene has the highest substitution rate and the petN gene contains no substitution over its complete length. The variation in plastid genes between C. costata and S. japonica is lower than that between C. costata and U. pinnatifida as well as that between U. pinnatifida and S. japonica. Phylogenetic analyses demonstrated that C. costata and U. pinnatifida have a closer genetic relationship. We also identified two gene length mutations caused by the insertion or deletion of repeated sequences, which suggest a mechanism of gene length mutation that may be one of the key explanations for the genetic variation in plastid genomes.
Cellular vacuolation induced by Clostridium perfringens epsilon‐toxin

The epsilon‐toxin of Clostridium perfringens forms a heptamer in the membranes of Madin–Darby canine kidney cells, leading to cell death. Here, we report that it caused the vacuolation of Madin–Darby canine kidney cells. The toxin induced vacuolation in a dose‐dependent and time‐dependent manner. The monomer of the toxin formed oligomers on lipid rafts in membranes of the cells. Methyl‐β‐cyclodextrin and poly(ethylene glycol) 4000 inhibited the vacuolation. Epsilon‐toxin was internalized into the cells. Confocal microscopy revealed that the internalized toxin was transported from early endosomes (early endosome antigen 1 staining) to late endosomes and lysosomes (lysosomal‐associated membrane protein 2 staining) and then distributed to the membranes of vacuoles. Furthermore, the vacuolation was inhibited by bafilomycin A1, a V‐type ATPase inhibitor, and colchicine and nocodazole, microtubule‐depolymerizing agents. The early endosomal marker green fluorescent protein–Rab5 and early endosome antigen 1 did not localize to vacuolar membranes. In contrast, the vacuolar membranes were specifically stained by the late endosomal and lysosomal marker green fluorescent protein–Rab7 and lysosomal‐associated membrane protein 2. The vacuoles in the toxin‐treated cells were stained with LysoTracker Red DND‐99, a marker for late endosomes and lysosomes. A dominant negative mutant of Rab7 prevented the vacuolization, whereas a mutant form of Rab5 was less effective. These results demonstrate, for the first time, that: (a) oligomers of epsilon‐toxin formed in lipid rafts are endocytosed; and (b) the vacuoles originating from late endosomes and lysosomes are formed by an oligomer of epsilon‐toxin.
The Use of the Ambiguity Decomposition in Neural Network Ensemble Learning Methods

We analyze the formal grounding behind Negative Correlation (NC) Learning, an ensemble learning technique developed in the evolutionary computation literature. We show that by removing an assumption made in the original work, NC can be seen to be exploiting the well-known Ambiguity decomposition of the ensemble error, grounding it in a statistics framework around the bias-variance decomposition. We use this grounding to find bounds for the parameters, and provide insights into the behaviour of the optimal parameter values. These observations allow us understand how NC relates to other algorithms, identifying a group of papers spread over the last decade that have all exploited the Ambiguity decomposition for machine learning problems. When taking into account our new understanding of the algorithm, significant reductions in error rates were observed in empirical tests.
Influence of surface roughness on pool boiling heat transfer

Experimental study of pool boiling heat transfer from the rough surface at pressure 1 bar, 5 bar and 10 bar is presented. Experiments are carried on 20 mm diameter copper sample at saturated condition of distilled water. Unidirectional scratches are made by different grit sandpaper. The surface roughness value Ra is varied from 0.106 μm to 4.03 μm. The effect of Ra on heat transfer at different pressure is reported. The variation in heat transfer coefficient with the heat flux for samples of different Ra is also examined. The predicted critical heat flux (CHF) by Kim’s model is found to in good agreement with present experimental values with mean absolute error of 12.06%.
Chip Scale Camera Module (CSCM) using Through-Silicon-Via (TSV)

No one doubts that Through Silicon Via (TSV) is one of the necessary technologies for three-dimensional integration of LSIs. Heterogeneous system integration is a good candidate for its application, which includes the “Vision Chip” [1]. TSV technology is applied to a CMOS imager sensor camera module for mobile handsets and successfully achieves a size reduction of 55% in volume and 36% in footprint, which we refer to as a Chip Scale Camera Module (CSCM). To the best of our knowledge, CSCM is the first mass-produced product using TSV technology.
iProbe : A Lightweight User-Level Dynamic Instrumentation Framework

Application tracing in production systems requires dynamic and flexible instrumentation mechanisms with lowoverhead. Tracing tools may be required to be started at anytime, and it can take potentially long time periods to collect enough information, but at the same time should not adversely affect service quality. Existing user-space code monitoring solutions are either inflexible developer-driven static instrumentation which require manual effort, or black-box dynamic instrumentation techniques which are flexible but have high overhead. To solve this problem, we introduce a new hybrid instrumentation technique for user-space code monitoring called iProbe, which is flexible and has low overhead. iProbe takes a novel 2-stage design, and offloads much of the dynamic instrumentation complexity to an offline compilation stage. It leverages standard compiler flags to introduce “place-holders” for hooks in the program executables. Then it utilizes an efficient userspace HotPatching mechanism which dynamically instruments the functions to be traced and enables execution of instrumented code in a safe and secure manner. We implemented iProbe as a dynamic application profiling framework. In its evaluation on micro-benchmarks and SPEC CPU2006 benchmark applications, the iProbe prototype achieved the instrumentation overhead an order of magnitude lower than existing state-of-the-art dynamic instrumentation tools like SystemTap and DynInst. We also built a hardware event profiling tool based on iProbe, and were able to obtain function-level hardware event breakdown on SPEC CPU2006 applications with controlled performance overhead (e.g., under 5%).
Evaluation of the expression pattern of rAAV2/1, 2/5, 2/7, 2/8, and 2/9 serotypes with different promoters in the mouse visual cortex

This study compared the expression pattern, laminar distribution, and cell specificity of several rAAV serotypes (2/1, 2/5, 2/7, 2/8, and 2/9) injected in the primary visual cortex (V1) of adult C57Bl/6J mice. In order to obtain specific expression in certain neuron subtypes, different promoter sequences were evaluated for excitatory cell specificity: a universal cytomegalovirus (CMV) promoter, and two versions of the excitatory neuron‐specific Ca2+/calmodulin‐dependent kinase subunit α (CaMKIIα) promoter, CaMKIIα 0.4 and CaMKIIα 1.3. The spatial distribution as well as the cell type specificity was immunohistochemically verified. Depending on the rAAV serotype used, the transduced volume expressing reporter protein differed substantially (rAAV2/5 ≫ 2/7 ≈ 2/9 ≈ 2/8 ≫ 2/1). Excitatory neuron‐specific targeting was promoter‐dependent, with a surprising difference between the 1.3 kb and 0.4 kb CaMKIIα promoters. While CaMKIIα 1.3 and CMV carrying vectors were comparable, with 78% of the transduced neurons being excitatory for CMV and 82% for CaMKIIα 1.3, the shorter CaMKIIα 0.4 version resulted in 95% excitatory specificity. This study therefore puts forward the CaMKIIα 0.4 promoter as the best choice to target excitatory neurons with rAAVs. Together, these results can be used as an aid to select the most optimal vector system to deliver transgenes into specific rodent neocortical circuits, allowing further elucidation of their functions. J. Comp. Neurol. 523:2019–2042, 2015. © 2015 Wiley Periodicals, Inc.
Evaluation of a generic quality of life instrument for early childhood caries-related pain.

OBJECTIVE This prospective study evaluated the reliability and validity of the Infant and Toddler Child Quality of Life Questionnaire (ITQOL) by comparing quality of life (QOL) of two groups of children afflicted with early childhood dental caries with a caries-free group. METHODS A convenience sample of 150 children divided into three groups (mean age [months] 51 +/- 15) was studied. Group I (OR) had extensive dental caries and were waiting for several months for treatment under general anesthesia. Group II were children who sought emergency services for acute odontogenic pain/abscess, and group III were children who were caries-free new patients. Parents/caretakers were administered the ITQOL, which assesses a child's physical, emotional and social well being from the parent/guardian's perspective. RESULTS The ITQOL had high success in item validity with good reliability. Significant differences in QOL were noted for scales of pain and discomfort, behavior and moods, global behavior, and impact on parental time (P <or= 0.05) among the three groups. No significant differences were noted for scales of growth and development, general health and impact on parents' emotional and mental health. CONCLUSIONS The ITQOL proved to be a useful instrument for characterizing QOL in this dental caries-afflicted sample. Overall, children with chronic and acute dental caries had a poorer QOL than caries-free children in areas of behavior, mood, pain and parental impact.
Real Time 3D Facial Movement Tracking Using a Monocular Camera

The paper proposes a robust framework for 3D facial movement tracking in real time using a monocular camera. It is designed to estimate the 3D face pose and local facial animation such as eyelid movement and mouth movement. The framework firstly utilizes the Discriminative Shape Regression method to locate the facial feature points on the 2D image and fuses the 2D data with a 3D face model using Extended Kalman Filter to yield 3D facial movement information. An alternating optimizing strategy is adopted to fit to different persons automatically. Experiments show that the proposed framework could track the 3D facial movement across various poses and illumination conditions. Given the real face scale the framework could track the eyelid with an error of 1 mm and mouth with an error of 2 mm. The tracking result is reliable for expression analysis or mental state inference.
Global Illumination using Imperfect Volumes

This paper introduces the concept of imperfect volumes, a fast one-pass point-based voxelization algorithm, and presents its applications to the global illumination problem. As often noted, diffuse indirect illumination has the characteristics of a low frequency function, consisting of smooth gradations. We exploit this by performing the indirect lighting computations on a rough approximation of the scene, the imperfect volume. The scene is converted on the fly to a dense point cloud, and each point is directly rendered to a volume texture, marking the corresponding voxel as occupied. A framebuffer reprojection scheme ensures that voxels visible to the main camera will get more points. Ray-marching is then used to compute the ambient occlusion or the indirect illumination of each voxel, and the results are stored using spherical harmonics. We demonstrate that the errors introduced by the imperfections in the volume are small and that our method maintains a high frame rate on scenes with high geometric complexity.
ADVANCED UMTS RECEIVER CHIP DESIGN USING VIRTUAL PROTOTYPING

Development of complex System on Chip (SoC) for modern communication systems has become more and more challenging. A designer has to bridge the gap between the requirements of the system at algorithmic level and its cycle true hardware description; the latter being synthesised for an Application Specific Integrated Circuit. This development requires numerous sub-steps, i.e., numerous intermediate descriptions on different abstraction levels of the same system. One of those levels can be an architecture level description implemented purely in software in form of a Virtual Prototype. This paper shows how Virtual Prototyping has been integrated in a design flow by a consistent design methodology and what advantages in terms of design efficiency have been gained.
Pupil and Iris Localization for Iris Recognition in Mobile Phones

Until now, iris recognition has been used in many fields. Recently, there have been attempts to adopt iris recognition technology for the security of mobile phones. For example, in case of bank transaction service by using a mobile phone, using a mobile phone can use high level of security based on iris recognition. In this paper, we propose a new pupil & iris segmentation method apt for the mobile environment. We find the pupil & iris at the same time, using both information of the pupil and iris. And we also use characteristic of the eye image. Experimental result shows that our algorithm has good performance in various images, which include motion or optical blurring, ghost, specular reflection and etc. from various environments for iris recognition system
Advanced Development of Certified OS Kernels

Abstract : The PI and his team at Yale have successfully developed (1) a clean - slate CertiKOS hypervisor kernel that runs on multicore platforms and supports Linux and ROS applications; (2) a new certified programming methodologies and tools that can verify contextual correctness, liveness, and security properties in a unified setting; (3) a fully verified single - core CertiKOS in Coq; (4) new semantics and logics for reasoning about information flow control with declassification, resource analysis, and fine-grained concurrent programs; and (5) new proof assistant language VeriML and Coq Ltac libraries.
Fibre-optic sensor development for process monitoring of epoxy resins

An investigation was undertaken to examine the performance of a Fresnel reflection sensor (FRS) incorporated into a differential scanning calorimeter (DSC) to track the cross-linking of epoxy resins. The initial design used a micrometer translation stage to lower the FRS through an orifice in the DSC platinum lid and onto the pan containing the sample. During exothermic cross-linking experiments, the resin refractive index and the heat evolved were measured simultaneously, allowing for direct comparison between the data. Combining the two measurement techniques produced a powerful hyphenated analytical procedure that demonstrated the feasibility of using the FRS for in-situ cure monitoring of epoxy resin systems. During the cross-linking of specified resins, the sensor revealed optical phenomena throughout the latter stages and was shown to be sensitive to the glass transition temperature, nano-particulate movement, nano-particulate concentration and phase separation. Therefore, the introduction of the FRS to the DSC provided valuable cross-linking information. A second modification to the DSC permitted the accommodation of an optical fibre probe, which facilitated simultaneous DSC/FRS/Fourier transform infrared spectroscopy (FTIRS) analysis. Good correlation between the cross-linking kinetics of an epoxy resin system was demonstrated using the hyphenated techniques and hence alleviated the issues of cross-correlation between individual experiments.
Hybrid duplex: a novel method to study the contractile function of heterogeneous myocardium.

In an earlier study, we experimentally mimicked the effects of mechanical interaction between different regions of the ventricular wall by allowing pairs of independently maintained cardiac muscle fibers to interact mechanically in series or in parallel. This simple physiological model of heterogeneous myocardium, which has been termed "duplex," has provided new insight into basic effects of cardiac electromechanical heterogeneity. Here, we present a novel "hybrid duplex," where one of the elements is an isolated cardiac muscle and the other a "virtual cardiac muscle. " The virtual muscle is represented by a computational model of cardiomyocyte electromechanical activity. We present in detail the computer-based digital control system that governs the mechanical interaction between virtual and biological muscle, the software used for data analysis, and working implementations of the model. Advantages of the hybrid duplex method are discussed, and experimental recordings are presented for illustration and as proof of the principle.
Integrated teleoperation and automation for nuclear facility cleanup

Purpose – The objective of this work was to demonstrate a novel approach to human machine interaction that seamlessly uses teleoperation and automation in a complex environment.Design/methodology/approach – This work leverages developments in the area of operational software Operational Software Components for Advanced Robotics (OSCAR), decision making, human‐machine interface, and motion planning. This demonstration uses a 17 degrees‐of‐freedom (DOF) dual arm robot that is equipped with modern tool changers, crash protectors, force‐torque sensors and electrical and pneumatic power at the tools. Four different end‐effector tools are also provided. These are electric grippers, electric rotary saw, electric drill, and a pneumatic spray gun. The system can be used both in teleoperation and automation mode. In teleoperation mode, the user has a choice of five different input devices. These are computer keyboard, spaceball and spacemouse, RSI manual controller and kraft force feedback controller. Automation is.
Functional and structural brain networks in epilepsy: What have we learned?

Brain functioning is increasingly seen as a complex interplay of dynamic neural systems that rely on the integrity of structural and functional networks. Recent studies that have investigated functional and structural networks in epilepsy have revealed specific disruptions in connectivity and network topology and, consequently, have led to a shift from “focus” to “networks” in modern epilepsy research. Disruptions in these networks may be associated with cognitive and behavioral impairments often seen in patients with chronic epilepsy. In this review, we aim to provide an overview that would introduce the clinical neurologist and epileptologist to this new theoretical paradigm. We focus on the application of a theory, called “network analysis,” to characterize resting‐state functional and structural networks and discuss current and future clinical applications of network analysis in patients with epilepsy.