Miracle-dz/UniFAR-FTUs huggingface dataset:
Generalized Role for the Cerebellum in Encoding Internal Models: Evidence from Semantic Processing

The striking homogeneity of cerebellar microanatomy is strongly suggestive of a corresponding uniformity of function. Consequently, theoretical models of the cerebellum's role in motor control should offer important clues regarding cerebellar contributions to cognition. One such influential theory holds that the cerebellum encodes internal models, neural representations of the context-specific dynamic properties of an object, to facilitate predictive control when manipulating the object. The present study examined whether this theoretical construct can shed light on the contribution of the cerebellum to language processing. We reasoned that the cerebellum might perform a similar coordinative function when the context provided by the initial part of a sentence can be highly predictive of the end of the sentence. Using functional MRI in humans we tested two predictions derived from this hypothesis, building on previous neuroimaging studies of internal models in motor control. First, focal cerebellar activation–reflecting the operation of acquired internal models–should be enhanced when the linguistic context leads terminal words to be predictable. Second, more widespread activation should be observed when such predictions are violated, reflecting the processing of error signals that can be used to update internal models. Both predictions were confirmed, with predictability and prediction violations associated with increased blood oxygenation level-dependent signal in the posterior cerebellum (Crus I/II). Our results provide further evidence for cerebellar involvement in predictive language processing and suggest that the notion of cerebellar internal models may be extended to the language domain.
Relevant Pages in semantic Web Search Engines using Ontology

In general, search engines are the most popular means of searching any kind of information from the Internet. Generally, keywords are given to the search engine and the Web database returns the documents containing specified keywords. In many situations, irrelevant results are given as results to the user query since different keywords are used in different forms in various documents. The development of the next generation Web, Semantic Web, will change this situation. This paper proposes a prototype of relation-based search engine which ranks the page according to the user query and on annotated results. Page sub graph is computed for each annotated page in the result set by generating all possible combinations for the relation in the sub graph. A relevance score is computed for each annotated page using a probability measure. A relation based ranking model is used which displays the pages in the final result set according to their relevance score. This ranking is provided by considering keyword-concept associations. Thus, the final result set contains pages in the order of their constrained relevant scores.
Virtual Plant Tissue: Building Blocks for Next-Generation Plant Growth Simulation

Motivation: Computational modeling of plant developmental processes is becoming increasingly important. Cellular resolution plant tissue simulators have been developed, yet they are typically describing physiological processes in an isolated way, strongly delimited in space and time. Results: With plant systems biology moving toward an integrative perspective on development we have built the Virtual Plant Tissue (VPTissue) package to couple functional modules or models in the same framework and across different frameworks. Multiple levels of model integration and coordination enable combining existing and new models from different sources, with diverse options in terms of input/output. Besides the core simulator the toolset also comprises a tissue editor for manipulating tissue geometry and cell, wall, and node attributes in an interactive manner. A parameter exploration tool is available to study parameter dependence of simulation results by distributing calculations over multiple systems. Availability: Virtual Plant Tissue is available as open source (EUPL license) on Bitbucket (https://bitbucket.org/vptissue/vptissue). The project has a website https://vptissue.bitbucket. io.
Alcohol-induced Hyperlipidemia Is Ameliorated by Orally Administered DWP208, a Sodium Succinate Form of ZYM201

DWP208 is a sodium succinate form of ZYM-201 which is a triterpenoid glycoside isolated from Sanguisorba officinalis, a medicinal plant prescribed for various diseases, such as duodenal ulcers and bleeding in East Asian counties. We demonstrated that this compound is able to normalize the altered lipid metabolism induced by hyperglycemia and a high fat diet. In this study, we determined whether hyperlipidemic conditions induced with chronically treated alcohol can also be restored by DWP208. Similar to our previous results, orally administered DWP208 (1 to 10 mg/kg) also ameliorated the hyperlipidemia that was induced by alcohol. This compound reversed the alcohol-induced hyperlipidemia including (i) up-regulated hyperlipidemic parameters such as low-density lipoprotein (LDL), very low-density lipoprotein (VLDL), atherosclerotic index (AI), triglyceride, and total cholesterol, and (ii) down-regulated hyperlipidemic parameters such as absolute body weight, superoxide dismutase (SOD) activity, and high-density lipoprotein (HDL) in serum and liver. According to our data, the ameliorative activity of DWP208 is due to its indirect anti-oxidative activity as a result of which lipid peroxide and hydroxyl radical levels were reduced and the activity of SOD was enhanced. Therefore, our data strongly suggest that DWP208 can be used as a remedy against alcohol-induced hyperlipidemia.
An iterative approach to nonconvex QCQP with applications in signal processing

This paper introduces a new iterative approach to solve or to approximate the solutions of the nonconvex quadratically constrained quadratic programs (QCQP). First, this constrained problem is transformed to an unconstrained problem using a specialized penalty-based method. A tight upper-bound for the alternative unconstrained objective is introduced. Then an efficient minimization approach to the alternative unconstrained objective is proposed and further studied. The proposed approach involves power iterations and minimization of a convex scalar function in each iteration, which are computationally fast. The important design problem of multigroup multicast beamforming is formulated as a nonconvex QCQP and solved using the proposed method.
Reconciling system requirements and runtime behavior

This paper considers the problem of system deviations from requirements specifications. Such deviations may arise from lack of anticipation of possible behaviors of environment agents at specification time, or from evoking conditions in this environment. We discuss an architecture and a development process for monitoring system requirements at runtime to reconcile the requirements and the system's behavior. This process is deployed on three scenarios of requirements-execution reconciliation for the Meeting Scheduler system. The work builds on our previous work on goal-driven requirements engineering and on runtime requirements monitoring.
SWIPT in MISO full-duplex systems

This paper investigates a multiuser multiple-input singleoutput (MISO) full-duplex (FD) system for simultaneous wireless information and power transfer (SWIPT), in which a multiantenna base station (BS) simultaneously sends wirelessly information and power to a set of single-antenna mobile stations (MSs) using power splitters (PSs) in the downlink and receives information in the uplink in FD mode. In particular, we address the joint design of the receive PS ratio and the transmit power at the MSs, and the beamforming matrix at the BS under signal-to-interferenceplus- noise ratio (SINR) and the harvested power constraints. Using semidefinite relaxation (SDR), we obtain the solution to the problem with imperfect channel state information (CSI) of the selfinterfering channels. Furthermore, we propose another suboptimal zero-forcing (ZF) based solution by separating the optimization of the transmit beamforming vector and the PS ratio. Simulation results are provided to evaluate the performance of the proposed beamforming designs.
Throughput and outage for block-Markov encoding implementation with network coding for cooperative communications

In size constraint terminals like in cellular and sensor networks, cooperative communications have been proposed as one of the most efficient way to exploit the benefits of multiple antenna systems. The achievable rates and resulting diversity gains are dependent on information theoretic block-Markov coding. Practical implementation of this information theoretic code design with network coding, as an efficient and low cost option, has recently been proposed. In this paper, we further investigate the resulting benefits in terms of system throughput and outage probability. We also discuss the receiver structure to exploit the resulting cooperative network coding gains and the block-Markov coding in detail. The results show that network coding implementation of block-Markov coding provides considerable gains to cooperative communications
Designing for Reflective Practice in Legal Education

Including reflective practice in tertiary learning design is one way of working towards making effective learning possible for students. This article considers how elements of reflective practice in teaching delivery and assessment have been successful in satisfying principles of effective teaching in the context of the study of law at first year level. The article also critically considers, however, how some of the theoretical perspectives on reflective practice do not always resonate with the real learning experience of students, and makes suggestions in terms of addressing these issues, particularly in relation to assessment.
A UML profile for model-driven design of software defined radio applications

Model-driven design (MDD) is considered a very promising approach to cope with complex software applications such as software defined radio (SDR). This paper proposes a MDD approach for SDR applications. Our approach comprises: (1) DiplodocusDF, a domain-specific modelling language for telecommunication applications, which is based on UML. (2) The mechanism to transform DiplodocusDF models into C-language code ready for compilation, and (3) a runtime environment for the generated code. Moreover, the proposed UML profile is supported by Ttool, which is a framework for design exploration and formal verification at model level. We illustrate the potential of our methodology designing a SDR application.
Improved PCR Methods for Detection of African Rabies and Rabies-Related Lyssaviruses

ABSTRACT Eleven different lyssavirus species, four of which occur on the African continent, are presently recognized. These viruses cause rabies, the burden of which is highest in the developing world, where routine laboratory diagnosis is often not available. From an epidemiological and control perspective, it is necessary that diagnostic methods detect the diversity of lyssaviruses present in different regions of the world. A published and widely used heminested reverse transcription-PCR (hnRT-PCR) was evaluated for its ability to detect a panel of diverse African lyssaviruses. Due to the limitations experienced for this assay, an alternative hnRT-PCR was developed. The new assay was found to be accurate and sensitive in the detection of African lyssavirus RNA in a variety of clinical specimens. The assay was further adapted to a real-time PCR platform to allow rapid, one-step, quantitative, and single-probe detection, and an internal control for the verification of sample preparation was included. The limit of detection of the real-time PCR assay was 10 RNA copies per reaction, with inter- and intra-assay variability below 4%. Subsequently, in demonstrating utility, both assays were successfully applied to antemortem rabies diagnosis in humans. We believe that the quantitative real-time PCR assay could find application as a routine confirmatory test for rabies diagnosis in the future and that it will serve as a valuable research tool in the biology of African lyssaviruses. Alternatively, the hnRT-PCR assay can be used in laboratories that do not have access to expensive real-time PCR equipment for sensitive diagnosis of lyssaviruses.
Compressive sensing methods for radar cross section ISAR measurements

The compressive sensing algorithm BPDN applied to RCS ISAR measurements is investigated in this paper. It is used to acquire ISAR images from data sets that are incomplete if conventional back projection is used to process images. The aim of the study is to determine if the algorithm can be used to extract accurate RCS values for parts of the measured objects when there are azimuth angle gaps in the measured RCS data. It is determined that the method is limited by the noise level but accurate RCS levels can be determined even at relatively low signal to noise ratios.
World Wide Web: A Graph-Theoretic Perspective

The World Wide Web can be modeled as a directed graph in which a node represents a Web page and an edge represents a hyperlink. Currently, the number of nodes in this gigantic Web graph is estimated to be over four billion, and is growing at more than seven million nodes a day  without any centralized control. Recent studies suggest that despite its chaotic appearance, the Web is a highly structured digraph, in a statistical sense. The study of this graph can provide insight into Web algorithms for crawling, searching, and ranking Web resources. Knowledge of the graph-theoretic structure of the Web graph can be exploited for attaining efficiency and comprehensiveness in Web navigation as well as enhancing Web tools, e.g., better search engines and intelligent agents. In this proposal, we discuss various problems to be explored for understanding the structure of the WWW. Many research directions are identified such as Web caching, prevention of security threats, user-flow analysis, etc.
Cross-Tier Interference-Aware Scheduling for Heterogeneous Uplink Transmission

Heterogeneous deployment comprising overlays macrocell and small cells is a promising solution to enhance both system capacity and coverage. Nevertheless, the performance of heterogeneous networks uplink is severely degraded due by cross-layer interference, especially the interference that small cell suffers from the proximate macro UEs (MUEs). In this paper, we propose a Cross-Tier Interference-Aware (CTIA) scheduling scheme which exploits scheduling coordination and small cell spacial degree of freedom to mitigate the uplink interference. The system level simulations show that substantial throughput gains can be achieved with the proposed CTIA scheme and practical receivers. It is also suggested to properly balance between the capacity improvement achieved by the proposed method and the backhaul overhead consumption, which can be implemented by adapting the cooperating set size with a system-defined parameter.
Cloning and Characterization of ThSHRs and ThSCR Transcription Factors in Taxodium Hybrid ‘Zhongshanshan 406’

Among the GRAS family of transcription factors, SHORT ROOT (SHR) and SCARECROW (SCR) are key regulators of the formation of root tissues. In this study, we isolated and characterized two genes encoding SHR proteins and one gene encoding an SCR protein: ThSHR1 (Accession Number MF045148), ThSHR2 (Accession Number MF045149) and ThSCR (Accession Number MF045152) in the adventitious roots of Taxodium hybrid ‘Zhongshanshan’. Gene structure analysis indicated that ThSHR1, ThSHR2 and ThSCR are all intron free. Multiple protein sequence alignments showed that each of the corresponding proteins, ThSHR1, ThSHR2 and ThSCR, contained five well-conserved domains: leucine heptad repeat I (LHRI), the VHIID motif, leucine heptad repeat II (LHR II), the PFYRE motif, and the SAW motif. The phylogenetic analysis indicated that ThSCR was positioned in the SCR clade with the SCR proteins from eight other species, while ThSHR1 and ThSHR2 were positioned in the SHR clade with the SHR proteins from six other species. Temporal expression patterns of these genes were profiled during the process of adventitious root development on stem cuttings. Whereas expression of both ThSHR2 and ThSCR increased up to primary root formation before declining, that of ThSHR1 increased steadily throughout adventitious root formation. Subcellular localization studies in transgenic poplar protoplasts revealed that ThSHR1, ThSHR2 and ThSCR were localized in the nucleus. Collectively, these results suggest that the three genes encode Taxodium GRAS family transcription factors, and the findings contribute to improving our understanding of the expression and function of SHR and SCR during adventitious root production, which may then be manipulated to achieve high rates of asexual propagation of valuable tree species.
Primary Frequency Control Contribution From Smart Loads Using Reactive Compensation

Frequency-dependent loads inherently contribute to primary frequency response. This paper describes additional contribution to primary frequency control based on voltage-dependent noncritical (NC) loads that can tolerate a wide variation of supply voltage. By using a series of reactive compensators to decouple the NC load from the mains to form a smart load (SL), the voltage, and hence the active power of the NC load, can be controlled to regulate the mains frequency. The scope of this paper focuses primarily on reactive compensators for which only the magnitude of the injected voltage could be controlled while maintaining the quadrature relationship between the current and voltage. New control guidelines are suggested. The effectiveness of the SLs in improving mains frequency regulation without considering frequency-dependent loads and with little relaxation in mains voltage tolerance is demonstrated in a case study on the IEEE 37 bus test distribution network. Sensitivity analysis is included to show the effectiveness and limitations of SLs for varying load power factors, proportion of SLs, and system strengths.
Constrained Source-Based Morphometry Identifies Structural Networks Associated with Default Mode Network

We present constrained source-based morphometry (SBM), a multivariate semiblind data-driven approach, to explore a possible brain-wide structural network in both gray matter (GM) and white matter (WM) associated with the functional default mode network (DMN). With this approach, we utilize seed regions associated with the DMN as constraints on GM maps and derive a joint GM and WM structural network automatically through a multivariate data-driven approach. In this article, we first provide a simulation to validate the constrained SBM approach. The approach was then applied to structural magnetic resonance imaging and diffusion tensor imaging data obtained from 102 healthy controls. Regions that have consistently reported to be associated with the DMN were used to create an a priori mask that was integrated within an independent component analysis framework to derive the structural network associated with the DMN. We identified a set of GM and corresponding WM regions contributing to a structural network underlying the functional DMN. The GM regions consisted mainly of the precuneus, superior and medial frontal gyri, middle temporal gyrus, hippocampus, cuneus, and cerebellum. The WM regions included the cingulum, corpus callosum, corona radiata, association fibers, and middle cerebellar peduncle. Significant gender differences in the relationship between intelligence quotient (IQ) and the identified structural network were observed. Our findings suggest that the functional DMN is underpinned by a corresponding brain-wide structural network. The constrained SBM approach is additionally applicable to a wide variety of problems identifying structural networks from seed regions.
GPU-based fast signal processing for large amounts of snore sound data

Snore sound (SnS) data has been demonstrated to carry very important information for diagnosis and evaluation of sleep related breathing disorders with high prevalence, such as Primary Snoring and Obstructive Sleep Apnea (OSA) - a serious chronic sleep disorder with a big community. With the increasing number of collected SnS data from subjects, how to handle such large amount of data is a big challenge, and a huge opportunity for further study on optimally combining signal processing techniques with machine learning algorithms. In this study, we utilize the Graphics Processing Unit (GPU) to process a large amount of SnS data collected from hospitals in Germany (37 subjects, 38.34 hours, 15.10 GB). Experimental results prove that, our GPU-based platform significantly speeds up the audio processing for features extraction of SnS data, compared with the traditional Central Processing Unit (CPU) system.
Accelerating storage access by combining block storage with memory storage

Memory storage technologies, such as next generation non-volatile (NV) memory and battery backed NV-DIMM, are emerging. While they provide much higher performance than the current block storage devices, such as SSDs and HDDs, their capacities are limited. Such limitation makes it difficult to adapt memory storage for mass storage; thus, its uses have been limited. This paper proposes a method that combines block storage with memory storage and makes use of memory storage as cache of block storage. The proposed method effectively utilizes the high performance of memory storage and also provides the large capacity of block storage. Therefore, memory storage can be transparently used as a part of mass storage while its low overhead access can accelerate storage performance. The proposed method was implemented as a device driver of the Linux kernel. Its performance evaluation shows that it outperforms a bare SSD drive and a drive that combines memory storage and a SSD by the existing method.
New Approaches for Rhythmic Description of Audio Signals

The subject of this work is the study of how rhythmical description of music can be included in Music Information Retrieval works, but from a more musical point of view. The goal is to provide a suitable representation of rhythm and explore how useful it can be for many different applications. This new representation is based on the so called Rhythm Transform that transforms data from the time domain to a so called rhythm domain. This transformation has proved to give good results for automatic classification and similarity applications. The theoretical and computational issues of the Rhythm Transform are explained, and some results for specific applications are also shown.
Performance of Spatially-Coupled LDPC Codes and Threshold Saturation over BICM Channels

We study the performance of binary spatially-coupled low-density parity-check codes (SC-LDPC) when used with bit-interleaved coded-modulation (BICM) schemes. This paper considers the cases when transmission takes place over additive white Gaussian noise (AWGN)channels and Rayleigh fast-fading channels. The technique of upper bounding the maximum-a-posteriori (MAP) decoding performance of LDPC codes using an area theorem is extended for BICM schemes. The upper bound is computed for both the optimal MAP demapper and the suboptimal max-log-MAP (MLM) demapper. It is observed that this bound approaches the noise threshold of BICM channels for regular LDPC codes with large degrees. The rest of the paper extends these techniques to SC-LDPC codes and the phenomenon of threshold saturation is demonstrated numerically. Based on numerical evidence, we conjecture that the belief-propagation (BP) decoding threshold of SC-LDPC codes approaches the MAP decoding threshold of the underlying LDPC ensemble on BICM channels. Numerical results also show that SC-LDPC codes approach the BICM capacity over different channels and modulation schemes.