Miracle-dz/UniFAR-FTUs huggingface dataset:
Performance Estimation of Noisy Speech Recognition Considering the Accuracy of Acoustic Models

To ensure a satisfactory QoE (Quality of Experience) and facilitate system design in speech recognition services, it is essential to establish a method that can be used to efficiently investigate recognition performance in different noise environments. Previously, we proposed a performance estimation method using the PESQ (Perceptual Evaluation of Speech Quality) as a measure of speech distortion. However, there is the problem that the accuracy of acoustic models used for speech recognition affects the relationship between the recognition performance and the distortion value. To solve this problem, we propose a novel performance estimation method considering the accuracy of acoustic models. Experimental results confirmed that the proposed method gives accurate estimates of the recognition performance for different sets of acoustic models, when using the recognition error rate for clean speech as a measure of the accuracy of acoustic models.
Examining Sensorial Interfaces as the Stimuli for Remote Affective Communication

Current communication technologies have a significant role in satisfying social connection and networking, but have not yet been developed to entirely support interpersonal communication, especially in creating and maintaining intimacy and a sense of connection in an intimate relationship, specifically with young adult children and older parents. Under the emerging trend of ubiquitous computing, this research examines the possibility of creating new means for augmenting intimacy in remote affective communication between young adult children and older parents. From a small-targeted group, this exploratory study rooted in family communication activities and family life is exploring the possible themes, cues and artefacts that support family closeness but are missing in conventional communication (audio and video). By generating a group of concepts and new tools for remote family interaction, the findings of this thesis offer insights into new means of communication tools for supporting family connectedness.
Group–Difference Effect Sizes: Gauging the Practical Importance of Findings from Group–Experimental Research

Effect sizes are powerful tools for evaluating the practical importance of study findings that should be considered in the context of study characteristics such as participants, dependent variables, and comparison condition. In this article, we discuss how group–difference effect sizes are used to gauge the practical importance of group experimental studies. We first define different types of group–difference effect sizes and discuss how they can provide valuable information for research consumers. Second, we present guidelines for interpreting group–difference effect sizes. Third, we discuss important contextual variables that should be taken into account when interpreting group–difference effect sizes reported in the literature. Last, we provide two examples of how group–difference effect sizes have been used in the learning disabilities research base.
ReliNoC: A reliable network for priority-based on-chip communication

The reliability of networks-on-chip (NoC) is threatened by low yield and device wearout in aggressively scaled technology nodes. We propose ReliNoC, a network-on-chip architecture which can withstand failures, while maintaining not only basic connectivity, but also quality-of-service support based on packet priorities. Our network leverages a dual physical channel switch architecture which removes the control overhead of virtual channels (VCs) and utilizes the inherent redundancy within the 2-channel switch to provide spares for faulty elements. Experimental results show that ReliNoC provides 1.5 to 3 times better network physical connectivity in presence of several faults, and reduces the latency of both high and low priority traffic by 30 to 50%, compared to a traditional VC architecture. Moreover, it can tolerate up to 50 faults within an 8×8 mesh at only 10 and 40% latency overhead on control and data packets for PARSEC traces [24]. Synthesis results show that our reliable architecture incurs only 13% area overhead on the baseline 2-channel switch.
A LAMARCKIAN MODEL COMBINING LEVENBERG-MARQUARDT ALGORITHM AND A GENETIC ALGORITHM

We review the integration between the genetic and evolutionary techniques with artificial neural networks. A Lamarckian model is proposed based on genetic algorithms and artificial neural networks. The genetic algorithm evolves the population while the artificial neural network performs the learning process. The direct encoding scheme was used. This model was submitted to several data sets and provided good results, exhibiting superior robustness when compared with the LevenbergMarquardt and the Scaled Conjugate Gradient algorithms. It also achieved the best solutions in the regression problems.
Semantic representation for navigation in large-scale environments

Mimicking human navigation is a challenging goal for autonomous robots. This requires to explicitly take into account not only geometric representation but also high-level interpretation of the environment. In this paper, we demonstrate the capability to infer a route in a global map by using semantics. Our approach relies on an object-based representation of the world automatically built by robots from spherical images. In addition, we propose a new approach to specify paths in terms of high-level robot actions. This path description provides robots with the ability to interact with humans in an intuitive way. We perform experiments on simulated and real-world data, demonstrating the ability of our approach to deal with complex large-scale outdoor environments whilst dealing with labelling errors.
Identification of WOX Family Genes in Selaginella kraussiana for Studies on Stem Cells and Regeneration in Lycophytes

Plant stem cells give rise to all tissues and organs and also serve as the source for plant regeneration. The organization of plant stem cells has undergone a progressive change from simple to complex during the evolution of vascular plants. Most studies on plant stem cells have focused on model angiosperms, the most recently diverged branch of vascular plants. However, our knowledge of stem cell function in other vascular plants is limited. Lycophytes and euphyllophytes (ferns, gymnosperms, and angiosperms) are two existing branches of vascular plants that separated more than 400 million years ago. Lycophytes retain many of the features of early vascular plants. Based on genome and transcriptome data, we identified WUSCHEL-RELATED HOMEOBOX (WOX) genes in Selaginella kraussiana, a model lycophyte that is convenient for in vitro culture and observations of organ formation and regeneration. WOX genes are key players controlling stem cells in plants. Our results showed that the S. kraussiana genome encodes at least eight members of the WOX family, which represent an early stage of WOX family evolution. Identification of WOX genes in S. kraussiana could be a useful tool for molecular studies on the function of stem cells in lycophytes.
Capturing complex behaviour for predicting distant future trajectories

We put forth a system, to predict distant-future positions of multiple moving entities and index the forecasted trajectories, in order to answer predictive queries involving long time horizons. Today, the proliferation of mobile devices with GPS functionality and internet connectivity has led to a rapid development of location-based services, accounting for user mobility prediction as a key paradigm. Mobility prediction is already playing a major role in traffic management, urban planning and location-based advertising, which demand accurate and long time horizon forecasting of user movements. Existing prediction methodologies either use motion patterns or techniques based on frequently visited places for predicting the next move. However, when it comes to distant-future, human mobility is too complex to be represented by such statistical functions. Therefore, the existing techniques are not well suited to answer distant-future queries with a satisfactory level of accuracy. To tackle this problem, we introduce a novel spatial object, 'Representative Trajectory', which embodies the movements of users amongst their zones of interest. We propose means to empirically evaluate the quality of this object and dynamically adapt its extraction method based on user mobility behaviour. We rely on an inverted index to store the predicted trajectories that scales well with the number of moving entities. Our evaluation results show that the technique achieves more than 70% accurate predictions with the best extraction technique. This shows that longer query time horizons do not necessarily demand complex spatial indexing schemes, which have to be rebalanced as they grow and which is a constantly experienced problem while answering predictive queries.
QPLOT: A Quality Assessment Tool for Next Generation Sequencing Data

Background. Next generation sequencing (NGS) is being widely used to identify genetic variants associated with human disease. Although the approach is cost effective, the underlying data is susceptible to many types of error. Importantly, since NGS technologies and protocols are rapidly evolving, with constantly changing steps ranging from sample preparation to data processing software updates, it is important to enable researchers to routinely assess the quality of sequencing and alignment data prior to downstream analyses. Results. Here we describe QPLOT, an automated tool that can facilitate the quality assessment of sequencing run performance. Taking standard sequence alignments as input, QPLOT generates a series of diagnostic metrics summarizing run quality and produces convenient graphical summaries for these metrics. QPLOT is computationally efficient, generates webpages for interactive exploration of detailed results, and can handle the joint output of many sequencing runs. Conclusion. QPLOT is an automated tool that facilitates assessment of sequence run quality. We routinely apply QPLOT to ensure quick detection of diagnostic of sequencing run problems. We hope that QPLOT will be useful to the community as well.
Modified desegmentation technique in analysis of arbitrary shaped planar circuit

This article introduces a simple technique in two-dimensional multiport method for analysis of planar circuits. This technique is applicable to configurations which have been analyzed by desegmentation method with electric wall boundary condition at the removed parts. Analysis of planar circuits with metallic vias is performed faster and more accurate by this technique, because there is no need to make the curved electric wall boundary discrete. In addition, proposed method is numerically stable. Substrate integrated waveguide as a planar circuit is analyzed by this technique. Through comparison with related published literatures, the accuracy of proposed technique is confirmed.
On ergodic secrecy rate of multiuser MISO downlink wiretap channel

In this paper, we consider the problem of secure communication in multiuser downlink wiretap networks where there exist a base-station (BS) equipped with multiple antennas, multiple legitimate receivers and a passive eavesdropper. The transmitter simultaneously transmits an information signal and artificial noise (AN) separately to the intended receivers and the eavesdropper, in which way, the secrecy rate at the eavesdropper can be seriously degraded without thinking about it location. Different schemes are studied about the power allocation of the multiple antennas in the BS, namely the average power allocation scheme and the Water-filling scheme. And in the average power allocation scheme, Zero-forcing (ZF) pre-coding scheme is used at the BS to eliminate the internal interference of all the security users. We obtain an analytical closed form expression of an achievable ergodic secrecy rate and use it as the objective function to optimize the power allocation rate between the information signal and the AN in the two schemes.
Real-time pedestrian detection based on A hierarchical two-stage Support Vector Machine

This Paper presents an SVM (Support Vector Machine) based real-time pedestrian detection scheme for next-generation automotive vision applications. To meet the requirement of real-time detection with high accuracy, we designed the proposed system consisting of 2-stage hierarchical SVMs. In the proposed system, most of the input data are classified by the 1st stage linear SVM and only the inputs between positive and negative hyper-plane of the linear SVM are transferred to the 2nd stage non-linear SVM. This hierarchical 2-stage classifier can be suited for various systems via controlling the amount of data processed by the 2nd stage classifier, which trades off the detection accuracy and the required system resources. To make the proposed 2nd stage non-linear SVM further appropriate for various systems, a hyper-plane approximation technique by sample pruning has been adopted. By reducing the number of required SVs (Support Vectors) using this technique and controlling the amount of data processed via the 2nd stage classifier, high precision non-linear SVM can be employed in the proposed real-time pedestrian detection system. Simulations using HOG (Histogram of Oriented Gradient) features and Daimler pedestrian dataset show the proposed system provides highly accurate classification results under the real-time constraint of application.
Using Agents to Improve the Usability and Usefulness of the World-Wide Web

The World-Wide Web (WWW) has emerged as a new type of information space. Its lack of central control mechanisms leads to many interesting new features but at the same time has the potential danger that users can drown in irrelevant information. To address and overcome problems of global information spaces such as the WWW, we have designed and implemented a framework to integrate agents into the use of the WWW. The agents filter information, initiate communication, monitor events, and perform tasks. The agents rely on usage profiles to adapt their assistance to specific users. In this paper we describe the unique challenges of a WWW-type information space, present the design rationale and conceptual framework behind our work, and illustrate with scenarios the use of the system.
Anti-HMGB 1 Neutralizing Antibody Ameliorates Gut Barrier Dysfunction and Improves Survival after Hemorrhagic Shock

Trauma ranks fifth as a cause of death among people of all ages living in the United States, and it is the leading cause of death among people less than 45 years of age (1). In the United States, traumatic injuries result in approximately 100,000 deaths per year (1). Early deaths are secondary to exsanguination or overwhelming central nervous system injuries, whereas late deaths are secondary to sepsis and multiple organ system dysfunction syndrome (MODS) (2,3). Massive hemorrhage is a major risk factor for the development of MODS in trauma victims (4,5). Intestinal barrier dysfunction, manifested by increased mucosal permeability to hydrophilic macromolecules and/or increased bacterial translocation to mesenteric lymph nodes (MLN), occurs following hemorrhagic shock and resuscitation (HS/R) in rodents (6-13). These findings may have clinical implications, because increased intestinal permeability has been shown to be associated with an increased risk of complications, MODS, or even mortality in critically ill patients (14-17). The underlying mechanisms responsible for gut barrier dysfunction after HS/R are not fully understood, but increased production of certain proinflammatory mediators, such as IL-6 (11) or nitric oxide (18), may be involved. High-mobility group proteins are small DNA-binding proteins that serve an important role in transcriptional regulation (19). One of these proteins, HMGB1, has been identified as a lateacting mediator of lipopolysaccharide (LPS)-induced (20) or sepsis-induced (21) lethality in mice. Additional studies have documented that HMGB1 is a cytokinelike molecule that can promote TNF release from mononuclear cells (22). HMGB1 is actively secreted by immunostimulated macrophages (20,23-25) and enterocytes (26) and is also released by necrotic but not apoptotic cells (27). In 1999, Ombrellino and co-workers (28) described a patient with high circulating levels of HMGB1 following an episode of hemorrhagic shock, and Kim et al. (29) recently reported data supporting the view that HMGB1 contributes to the development of acute lung injury in mice subjected to HS/R. These data, along with results from our laboratory showing that exposure to HMGB1 increases the permeability of Caco-2 enterocyte-like monolayers in vitro (30), prompted to us to measure circulating HMGB1 levels in a cohort of adult
The KEGG databases at GenomeNet

The Kyoto Encyclopedia of Genes and Genomes (KEGG) is the primary database resource of the Japanese GenomeNet service (http://www.genome.ad.jp/) for understanding higher order functional meanings and utilities of the cell or the organism from its genome information. KEGG consists of the PATHWAY database for the computerized knowledge on molecular interaction networks such as pathways and complexes, the GENES database for the information about genes and proteins generated by genome sequencing projects, and the LIGAND database for the information about chemical compounds and chemical reactions that are relevant to cellular processes. In addition to these three main databases, limited amounts of experimental data for microarray gene expression profiles and yeast two-hybrid systems are stored in the EXPRESSION and BRITE databases, respectively. Furthermore, a new database, named SSDB, is available for exploring the universe of all protein coding genes in the complete genomes and for identifying functional links and ortholog groups. The data objects in the KEGG databases are all represented as graphs and various computational methods are developed to detect graph features that can be related to biological functions. For example, the correlated clusters are graph similarities which can be used to predict a set of genes coding for a pathway or a complex, as summarized in the ortholog group tables, and the cliques in the SSDB graph are used to annotate genes. The KEGG databases are updated daily and made freely available (http://www.genome.ad.jp/kegg/).
Startle modulation during emotional anticipation and perception.

The startle reflex is potentiated when anticipating emotional, compared to neutral, pictures. This study investigated the time course of reflex modulation during anticipation and the impact of informative cuing on picture perception. Colors were used to signal the thematic content of emotional and neutral scenes; blink response modulation was measured by presenting acoustic startle probes 3, 2, or 1 s before picture onset or 2 s after picture onset. During anticipation of neutral scenes, blink magnitude showed increasing attenuation as picture onset approached, consistent with a modality-directed vigilance account. Conversely, when anticipating emotional scenes, reflex magnitude did not change over time, and blinks elicited closest to picture onset were potentiated compared to neutral. During perception, the expected reflex potentiation for unpleasant pictures was not found, suggesting that cuing may dampen defensive activation.
Experimental implementation of MPPT for PV systems

Solar panel efficiency is an essential parameter in determining the cost of converting solar energy into electrical energy. This paper addresses a technique for maximizing energy extraction from photovoltaic (PV) solar systems using power electronic circuits to achieve maximum power point tracking. Design and implementation details are presented, illustrating the perturbation and observation algorithm based on DC-DC power converter. Simulations are done in Matlab/Simulink environments, and experimental implementation is conducted in a developed PV testbed. Analysis of the recorded results reveals the potential of the presented techniques in enhancing the efficiency of energy extraction from PV systems.
The CD8 and CD4 T-Cell Response against Kaposi's Sarcoma-Associated Herpesvirus Is Skewed Towards Early and Late Lytic Antigens

Kaposi's sarcoma-associated herpesvirus (KSHV) is causally related to Kaposi's sarcoma (KS), the most common malignancy in untreated individuals with HIV/AIDS. The adaptive T-cell immune response against KSHV has not been fully characterized. To achieve a better understanding of the antigenic repertoire of the CD8 and CD4 T-cell responses against KSHV, we constructed a library of lentiviral expression vectors each coding for one of 31 individual KSHV open reading frames (ORFs). We used these to transduce monocyte-derived dendritic cells (moDCs) isolated from 14 KSHV-seropositive (12 HIV-positive) and 7 KSHV-seronegative (4 HIV-positive) individuals. moDCs were transduced with up to 3 KSHV ORFs simultaneously (ORFs grouped according to their expression during the viral life cycle). Transduced moDCs naturally process the KSHV genes and present the resulting antigens in the context of MHC class I and II. Transduced moDCs were cultured with purified autologous T cells and the CD8 and CD4 T-cell proliferative responses to each KSHV ORF (or group) was assessed using a CFSE dye-based assay. Two pools of early lytic KSHV genes ([ORF8/ORF49/ORF61] and [ORF59/ORF65/K4.1]) were frequently-recognized targets of both CD8 and CD4 T cells from KSHV seropositive individuals. One pool of late lytic KSHV genes ([ORF28/ORF36/ORF37]) was a frequently-recognized CD8 target and another pool of late genes ([ORF33/K1/K8.1]) was a frequently-recognized CD4 target. We report that both the CD8 and CD4 T-cell responses against KSHV are skewed towards genes expressed in the early and late phases of the viral lytic cycle, and identify some previously unknown targets of these responses. This knowledge will be important to future immunological investigations into KSHV and may eventually lead to the development of better immunotherapies for KSHV-related diseases.
Generalized performance management of multi-class real-time imprecise data services

The intricacy of real-time data service management increases mainly due to the emergence of applications operating in open and unpredictable environments, increases in software complexity, and need for performance guarantees. In this paper we propose an approach for managing the quality of service of real-time databases that provide imprecise and differentiated services, and that operate in unpredictable environments. Transactions are classified into service classes according to their level of importance. Transactions within each service class are further classified into subclasses based on their quality of service requirements. In this way transactions are explicitly differentiated according to their importance and quality of service requests. The performance evaluation shows that during overloads the most important transactions are guaranteed to meet their deadlines and that reliable quality of service is provided even in the face of varying load and execution time estimation errors