Miracle-dz/UniFAR-FTUs huggingface dataset:
Fully Automatic Segmentation of the Myocardium in Cardiac Perfusion MRI

Reduced myocardial perfusion is an important indicator for coronary artery diseases. To perform early diagnosis the myocardial perfusion needs to be quantified. For this the myocardium has to be segmented in all time steps of the image sequence. Manually identification of myocardial boundaries is a very time consuming and tedious task. Existing automatic methods ignore motion artifacts, assumes that the heart is located at the center of the images, or requires user interactions to select a region of interest (ROI) covering the heart. Therefore, a fully automatic segmentation method is introduced in this work. This method uses spatial and temporal information and deals with motion artifacts. The ROI covering the heart is located by a hierarchical pattern matching algorithm. Motion artifacts are minimized by image registration using mutual information. Estimation of characteristic intensity-time curves followed by pixel-wise classification and boundary extraction deliver the final segmentation. The proposed method was successfully evaluated for 10 out of 11 data sets.
Modeling Cantonese Pronunciation Variations for Large-Vocabulary Continuous Speech Recognition

This paper presents different methods of handling pronunciation variations in Cantonese large-vocabulary continuous speech recognition. In an LVCSR system, three knowledge sources are involved: a pronunciation lexicon, acoustic models and language models. In addition, a decoding algorithm is used to search for the most likely word sequence. Pronunciation variation can be handled by explicitly modifying the knowledge sources or improving the decoding method. Two types of pronunciation variations are defined, namely, phone changes and sound changes. Phone change means that one phoneme is realized as another phoneme. A sound change happens when the acoustic realization is ambiguous between two phonemes. Phone changes are handled by constructing a pronunciation variation dictionary to include alternative pronunciations at the lexical level or dynamically expanding the search space to include those pronunciation variants. Sound changes are handled by adjusting the acoustic models through sharing or adaptation of the Gaussian mixture components. Experimental results show that the use of a pronunciation variation dictionary and the method of dynamic search space expansion can improve speech recognition performance substantially. The methods of acoustic model refinement were found to be relatively less effective in our experiments.
Best Practices for Aero-Database CFD Simulations of Ares V Ascent

In support of NASA’s next generation heavy lift launch vehicle (HLLV), a simulation protocol has been developed to generate databases of the aerodynamic force and moment coefficients for HLLV ascent. The simulation protocol has been established and validated with a series of computational analyses that ensure best practices are achieved. Results of the sensitivity analyses using a full-scale Ares V flight vehicle are next applied in a validation study with three scaled-down Ares V wind tunnel test articles. Three independent computational fluid dynamic (CFD) flow solvers were included in the study. These included OVERFLOW, a viscous Reynolds Averaged Navier-Stokes (RANS) solver for structured overset grids, USM3D, a viscous RANS solver for unstructured tetrahedral grids, and Cart3D, an inviscid Euler solver using unstructured Cartesian grids and adjoint-based adaptive mesh refinement. First, a series of tests was independently performed for each applicable CFD code, including a grid convergence study and sensitivity studies of turbulence models and convective flux discretization methods. Once the proper grid resolution, physical models, and numerical parameters were determined for each of the codes, the process was continued with a code-to-code comparison. Each CFD code was applied to the Ares V flight vehicle at several points in the ascent trajectory, with all three codes obtaining consistent force and moment predictions. Finally, an extensive validation of the CFD approach was performed, in which the three codes were used to generate aero-databases of force and moment coefficients for three distinct Ares V wind tunnel test articles. These computations were performed concurrent to the experimental databases generated in the 14-inch wind tunnel at Marshall Space Flight Center (MSFC). Comparisons of the CFD results with the experimental data are reported and the viscous flow results compare well.
Venom Down Under: Dynamic Evolution of Australian Elapid Snake Toxins

Despite the unparalleled diversity of venomous snakes in Australia, research has concentrated on a handful of medically significant species and even of these very few toxins have been fully sequenced. In this study, venom gland transcriptomes were sequenced from eleven species of small Australian elapid snakes, from eleven genera, spanning a broad phylogenetic range. The particularly large number of sequences obtained for three-finger toxin (3FTx) peptides allowed for robust reconstructions of their dynamic molecular evolutionary histories. We demonstrated that each species preferentially favoured different types of α-neurotoxic 3FTx, probably as a result of differing feeding ecologies. The three forms of α-neurotoxin [Type I (also known as (aka): short-chain), Type II (aka: long-chain) and Type III] not only adopted differential rates of evolution, but have also conserved a diversity of residues, presumably to potentiate prey-specific toxicity. Despite these differences, the different α-neurotoxin types were shown to accumulate mutations in similar regions of the protein, largely in the loops and structurally unimportant regions, highlighting the significant role of focal mutagenesis. We theorize that this phenomenon not only affects toxin potency or specificity, but also generates necessary variation for preventing/delaying prey animals from acquiring venom-resistance. This study also recovered the first full-length sequences for multimeric phospholipase A2 (PLA2) ‘taipoxin/paradoxin’ subunits from non-Oxyuranus species, confirming the early recruitment of this extremely potent neurotoxin complex to the venom arsenal of Australian elapid snakes. We also recovered the first natriuretic peptides from an elapid that lack the derived C-terminal tail and resemble the plesiotypic form (ancestral character state) found in viper venoms. This provides supporting evidence for a single early recruitment of natriuretic peptides into snake venoms. Novel forms of kunitz and waprin peptides were recovered, including dual domain kunitz-kunitz precursors and the first kunitz-waprin hybrid precursors from elapid snakes. The novel sequences recovered in this study reveal that the huge diversity of unstudied venomous Australian snakes are of considerable interest not only for the investigation of venom and whole organism evolution but also represent an untapped bioresource in the search for novel compounds for use in drug design and development.
Multi-privacy biometric protection scheme using ensemble systems

Biometric systems use personal biological or behavioural traits that can uniquely characterise an individual but this uniqueness property also becomes its potential weakness when the template characterising a biometric trait is stolen or compromised. To this end, we consider two strategies to improving biometric template protection and performance, namely, (1) using multiple privacy schemes and (2) using multiple matching algorithms. While multiple privacy schemes can improve the security of a biometric system by protecting its template; using multiple matching algorithms or similarly, multiple biometric traits along with their respective matching algorithms, can improve the system performance due to reduced intra-class variability. The above two strategies lead to a novel, ensemble system that is derived from multiple privacy schemes. Our findings suggest that, under the worst-case scenario evaluation where the key or keys protecting the template are stolen, multi-privacy protection scheme can outperform a single protection scheme as well as the baseline biometric system without template protection.
Size and complexity among multicellular organisms

The diversity of specialized cell types (‘complexity’) is estimated for a wide range of multicellular organisms. Complexity increases with size, independently of phylogeny. This is interpreted in economic terms as the consequence of a greater degree of cooperative division of labour within larger entities. The rate of increase of complexity with size is less in the case of a cooperative division of labour (cell types within bodies) than in the analogous case of a competitive division of labour (species within communities). This is atttributed to the inutility of single specialized cells whose goods must be shared among all the many cells of a large organism. Major groups of organisms differ in complexity at given size: animals are more complex than plants, and phaeophytes are simpler than either.
Self Confidence Spillovers and Motivated Beliefs

Is success in a task used strategically by individuals to motivate their beliefs prior to taking action in a subsequent, unrelated, task? Also, is the distortion of beliefs reinforced for individuals who have lower status in society? Conducting an artefactual field experiment in India, we show that success when competing in a task increases the performers’ self-confidence and competitiveness in the subsequent task. We also find that such spillovers affect the self-confidence of low-status individuals more than that of high-status individuals. Receiving good news under Affirmative Action, however, boosts confidence across tasks regardless of the caste status.
Web-based GIS and spatial decision support system for watershed management

Geographic Information Systems (GIS) have been widely used for spatial data manipulation for hydrologic model operations and as a supporting tool to develop spatial decision support systems (SDSS). Information technologies, including GIS and the Internet, have provided opportunities to overcome many of the limitations of computer-based models in terms of data preparation and visualisation, and provide the possibility to create integrated SDSS. This paper examines the relationship between changes in GIS technology and watershed management SDSS. It also describes a conceptual web-based SDSS framework in terms of system components and data flow. A prototype watershed management web-based SDSS that utilises the conceptual framework is examined (URL: http://pasture.ecn.purdue.edu/~watergen/owls ). The SDSS uses web-GIS for watershed delineation, map interfaces and data preparation routines, a hydrologic model for hydrologic/water quality impact analysis and web communication programs for Internet-based system operation. The web-based SDSS can be helpful for watershed management decision-makers and interested stakeholders. The watershed management SDSS also provides insight into the role of GIS and information technologies in creating readily accessible and useable SDSS capabilities.
Chromatin fibers observed in situ in frozen hydrated sections. Native fiber diameter is not correlated with nucleosome repeat length

Chromatin fibers have been observed and measured in frozen hydrated sections of three types of cell (chicken erythrocytes and sperm of Patiria miniata and Thyone briareus) representing an approximately 20- bp range of nucleosomal repeat lengths. For sperm of the starfish P. miniata, it was possible to obtain images of chromatin fibers from cells that were swimming in seawater up to the moment of cryo- immobilization, thus providing a record of the native morphology of the chromatin of these cells. Glutaraldehyde fixation produced no significant changes in the ultrastructure or diameter of chromatin fibers, and fiber diameters observed in cryosections were similar to those recorded after low temperature embedding in Lowicryl K11M. Chromatin fiber diameters measured from cryosections of the three types of nuclei were similar, a striking contrast to the situation for chromatin isolated from these cell types, where a strong positive correlation between diameter and nucleosomal repeat length has been established. The demonstration of chromatin fibers in unfixed whole cells establishes an unequivocal baseline for the study of native chromatin and chromosome architecture. The significant differences between chromatin fibers in nucleo and after isolation supports a previous observation (P. J. Giannasca, R. A. Horowitz, and C. L. Woodcock. 1993. J. Cell Sci. 105:551-561), and suggests that structural studies on isolated material should be interpreted with caution until the changes that accompany chromatin isolation are understood.
A Platform for Streaming Push Notifications to Mobile Assessors

We present an assessment platform for gathering online relevance judgments for mobile push notifications that will be deployed in the newly-created TREC 2016 Real-Time Summarization (RTS) track. There is emerging interest in building systems that filter social media streams such as tweets to identify interesting and novel content in real time, putatively for delivery to users' mobile phones. In our evaluation design, all participants subscribe to the Twitter streaming API to identify relevant tweets with respect to a set of interest profiles. As the systems generate results, they are pushed in real time to our evaluation broker via a REST API. The broker then "routes" the tweets to assessors who have installed a custom app on their mobile phones. We detail the design of this platform and discuss a number of challenges that need to be tackled in this type of "Living Labs" setup. It is our goal that such an evaluation design will mitigate any issues that have arisen in traditional batch-style evaluations of this type of task.
Semirandom Models as Benchmarks for Coloring Algorithms

Semirandom models generate problem instances by blending random and adversarial decisions, thus intermediating between the worst-case assumptions that may be overly pessimistic in many situations, and the easy pure random case. In the Gn,p,k random graph model, the n vertices are partitioned into k color classes each of size n/k. Then, every edge connecting two different color classes is included with probability p = p(n). In the semirandom variant, G*n,p,k, an adversary may add edges as long as the planted coloring is respected. Feige and Killian prove that unless NP ⊆ BPP, no polynomial time algorithm works whp when np < (1 − e) ln n, in particular when np is constant. Therefore, it seems like G*n,p,k is not an interesting benchmark for polynomial time algorithms designed to work whp on sparse instances (np a constant). We suggest two new criteria, using semirandom models, to serve as benchmarks for such algorithms. We also suggest two new coloring heuristics and compare them with the coloring heuristics suggested by Alon and Kahale 1997 and by Bottcher 2005. We prove that in some explicit sense both our heuristics are preferable to the latter.
The Analytic Experience: Lectures from the Tavistock

There have been many expositions of psychoanalysis, but none so deeply rooted in clinical practice - both as it affects the patient, and even more as it affects the analyst. Neville Symington lectured to mental health professionals seconded to the Tavistock Centre; this book is the result of these lectures.
A Mixed Methods Investigation of Posttraumatic Growth in Young Adults Following Parental Divorce

The present study used a mixed methods design to examine factors contributing to posttraumatic growth (PTG) in 232 young adults who experienced parental divorce. Participants completed an online survey including measures of social support, religious coping, posttraumatic stress, and posttraumatic growth. Participants also responded to five open-ended questions related to their parents’ divorce. Multiple regression analysis demonstrated that perceived social support, intrinsic religiousness, and positive and negative religious coping contributed statistically significant variance to PTG. Qualitative data revealed themes of both pain and positive growth following parental divorce. Implications to assist children in the promotion of positive growth after parental divorce are discussed.
Cataloging Coding Sequence Variations in Human Genome Databases

Background With the recent growth of information on sequence variations in the human genome, predictions regarding the functional effects and relevance to disease phenotypes of coding sequence variations are becoming increasingly important. The aims of this study were to catalog protein-coding sequence variations (CVs) occurring in genetic variation databases and to use bioinformatic programs to analyze CVs. In addition, we aim to provide insight into the functionality of the reference databases. Methodology and Findings To catalog CVs on a genome-wide scale with regard to protein function and disease, we investigated three representative databases; the Human Gene Mutation Database (HGMD), the Single Nucleotide Polymorphisms database (dbSNP), and the Haplotype Map (HapMap). Using these three databases, we analyzed CVs at the protein function level with bioinformatic programs. We proposed a combinatorial approach using the Support Vector Machine (SVM) to increase the performance of the prediction programs. By cataloging the coding sequence variations using these databases, we found that 4.36% of CVs from HGMD are concurrently registered in dbSNP (8.11% of CVs from dbSNP are concurrent in HGMD). The pattern of substitutions and functional consequences predicted by three bioinformatic programs was significantly different among concurrent CVs, and CVs occurring solely in HGMD or in dbSNP. The experimental results showed that the proposed SVM combination noticeably outperformed the individual prediction programs. Conclusions This is the first study to compare human sequence variations in HGMD, dbSNP and HapMap at the genome-wide level. We found that a significant proportion of CVs in HGMD and dbSNP overlap, and we emphasize the need to use caution when interpreting the phenotypic relevance of these concurrent CVs. Combining bioinformatic programs can be helpful in predicting the functional consequences of CVs because it improved the performance of functional predictions.
Modelling of LF ground-wave propagation at short distances based on 2-D cylindrical-coordinate FDTD method

FDTD algorithm based on 2-D cylindrical-coordinate is used to investigate LF ground-wave propagation over lossy ground paths due to a vertical current element source at short distances. In this paper, 100 kHz LF signal is taken for an example and the numerical model is verified by comparing its results for LF propagation attenuation with corresponding data generated by the classical methods. The results of FDTD and theoretical formulas all agree very well. It demonstrates that the FDTD method can be used in the computation of LF ground-wave propagation. Since FDTD results include all effects of wave propagation, such as reflection, diffraction, surface wave excitation, and backscattering, it may make FDTD the technique of the future.
Enhancment of Grid Scheduling using Dyanamic Error Detection and Fault Tolerance

computational grid solve most of the problems that arise in many scientific application with the help of the heterogeneous resources which is spread across the distributed environment . The challenges that arise in such case of utilization of the resources and scheduling of jobs can be overcome by the techniques of error detection mechanisms . The early error detection mechanism collects the entire information about the resources which are available in the heterogeneous distributed environment. The resource information can be used during the allocation of jobs to that resources so that the job gets executed successfully without any failure in the resource. But the error detection mechanism also has its own drawbacks like the remote host server may be down ,file transfer services may not supported by the host ,there may be any malfunctionality in the service protocols and the hardware failure which occurs during data transfer also cannot be tackled in error rectification . To avoid this we introduce fault tolerance mechanism to overcome the difficulty.
Effective shared representations with Multitask Learning for Community Question Answering

An important asset of using Deep Neural Networks (DNNs) for text applications is their ability to automatically engineering features. Unfortunately, DNNs usually require a lot of training data, especially for highly semantic tasks such as community Question Answering (cQA). In this paper, we tackle the problem of data scarcity by learning the target DNN together with two auxiliary tasks in a multitask learning setting. We exploit the strong semantic connection between selection of comments relevant to (i) new questions and (ii) forum questions. This enables a global representation for comments, new and previous questions. The experiments of our model on a SemEval challenge dataset for cQA show a 20% of relative improvement over standard DNNs.
Applied LPV control exploiting the separation principle for the single axis positioning of an industrial manipulator

This paper describes the application of linear parameter varying (LPV) control design to the positioning control of the first axis of an industrial manipulator. The manipulator is modeled as a single flexible joint robot. The parameter dependency of the manipulator dynamics results from movements of the other axes. They determine the inertia that has to be moved by the first axis. The controller is designed via a mixed sensitivity weighting scheme for LPV control. Structural properties of the weighting scheme allow the application of the separation principle. By splitting the synthesis problem into an observer and a state feedback problem, the complexity of the convex optimization problem which has to be solved is greatly reduced. A multistage parameter optimization is employed to tune the control system. Finally, the design is compared to an output feedback PID and an ad-hoc gain-scheduled observer based PI state feedback controller on a real-time testbed with a KUKA standard industrial manipulator.
Evidence for a Mass Dependent Step-Change in the Scaling of Efficiency in Terrestrial Locomotion

A reanalysis of existing data suggests that the established tenet of increasing efficiency of transport with body size in terrestrial locomotion requires re-evaluation. Here, the statistical model that described the data best indicated a dichotomy between the data for small (<1 kg) and large animals (>1 kg). Within and between these two size groups there was no detectable difference in the scaling exponents (slopes) relating metabolic (E met) and mechanical costs (E mech, CM) of locomotion to body mass (M b). Therefore, no scaling of efficiency (E mech, CM/E met) with M b was evident within each size group. Small animals, however, appeared to be generally less efficient than larger animals (7% and 26% respectively). Consequently, it is possible that the relationship between efficiency and M b is not continuous, but, rather, involves a step-change. This step-change in the efficiency of locomotion mirrors previous findings suggesting a postural cause for an apparent size dichotomy in the relationship between E met and M b. Currently data for E mech, CM is lacking, but the relationship between efficiency in terrestrial locomotion and M b is likely to be determined by posture and kinematics rather than body size alone. Hence, scaling of efficiency is likely to be more complex than a simple linear relationship across body sizes. A homogenous study of the mechanical cost of terrestrial locomotion across a broad range of species, body sizes, and importantly locomotor postures is a priority for future research.