Miracle-dz/UniFAR-FTUs huggingface dataset:
Frame based system combination and a comparison with weighted ROVER and CNC

In this paper we present a novel ASR system combination technique able to combine systems producing word graphs of different structure and with different segmentations. The new method is based on the definition of a time frame-wise word error cost function in a minimum Bayes risk framework. In contrast to confusion network combination (CNC), it preserves both the word graph structure and the word boundaries. First experimental results are presented on the European Parliament Plenary Sessions (EPPS) task for European Spanish and British English. The new approach to system combination is compared to both ROVER and CNC. In addition, we also apply datadriven weighting schemes for all system combination approaches addressed in this work. For the experiments presented, a variety of internal systems as well as an additional external system were combined.
Electronic Dietary Intake Assessment (e-DIA): Comparison of a Mobile Phone Digital Entry App for Dietary Data Collection With 24-Hour Dietary Recalls

Background The electronic Dietary Intake Assessment (e-DIA), a digital entry food record mobile phone app, was developed to measure energy and nutrient intake prospectively. This can be used in monitoring population intakes or intervention studies in young adults. Objective The objective was to assess the relative validity of e-DIA as a dietary assessment tool for energy and nutrient intakes using the 24-hour dietary recall as a reference method. Methods University students aged 19 to 24 years recorded their food and drink intake on the e-DIA for five days consecutively and completed 24-hour dietary recalls on three random days during this 5-day study period. Mean differences in energy, macro-, and micronutrient intakes were evaluated between the methods using paired t tests or Wilcoxon signed-rank tests, and correlation coefficients were calculated on unadjusted, energy-adjusted, and deattenuated values. Bland-Altman plots and cross-classification into quartiles were used to assess agreement between the two methods. Results Eighty participants completed the study (38% male). No significant differences were found between the two methods for mean intakes of energy or nutrients. Deattenuated correlation coefficients ranged from 0.55 to 0.79 (mean 0.68). Bland-Altman plots showed wide limits of agreement between the methods but without obvious bias. Cross-classification into same or adjacent quartiles ranged from 75% to 93% (mean 85%). Conclusions The e-DIA shows potential as a dietary intake assessment tool at a group level with good ranking agreement for energy and all nutrients.
A Clustering Approach Using Cooperative Artificial Bee Colony Algorithm

Artificial Bee Colony (ABC) is one of the most recently introduced algorithms based on the intelligent foraging behavior of a honey bee swarm. This paper presents an extended ABC algorithm, namely, the Cooperative Article Bee Colony (CABC), which significantly improves the original ABC in solving complex optimization problems. Clustering is a popular data analysis and data mining technique; therefore, the CABC could be used for solving clustering problems. In this work, first the CABC algorithm is used for optimizing six widely used benchmark functions and the comparative results produced by ABC, Particle Swarm Optimization (PSO), and its cooperative version (CPSO) are studied. Second, the CABC algorithm is used for data clustering on several benchmark data sets. The performance of CABC algorithm is compared with PSO, CPSO, and ABC algorithms on clustering problems. The simulation results show that the proposed CABC outperforms the other three algorithms in terms of accuracy, robustness, and convergence speed.
When Will They Learn? An Accountability Theory Perspective On The Effects Of Board Of Director Decision Monitoring On Ceo Learning

This paper contributes to the management literatures on board of director effectiveness and strategic cognition by developing a conceptual model that describes how the nature of the decision monitoring pressures that CEOs face from their boards of directors will influence their ongoing abilities to learn about the complex strategic issues facing their firms. Our model highlights the contingent nature of the effects of board decision monitoring on CEO learning. We identify a range of conditions under which board decision monitoring will be less likely to promote learning by CEOs, and may actually interfere with executive learning.
Water vapor budget of the Indian monsoon depression

Estimations by previous studies show that a minor amount of the Indian monsoon rainfall is contributed by Indian monsoon depressions (IMDs). In contrast, other studies found that approximately half of the summer monsoon rainfall in the northern Indian subcontinent is generated by IMDs. IMDs occur an average of six times during the summer season and provide a crucial water source to the agricultural activity over this region. The large disparity in the estimation of the IMD contribution to the Indian rainfall by previous studies requires a more accurate water vapor budget analysis of the IMD with quality data. For this reason, a composite analysis of the IMD is performed using the ERA-40 reanalysis and four precipitation data sets (the Global Precipitation Climatology Project, the Tropical Rainfall Measuring Mission, the GEOS precipitation index at the Goddard Space Flight Center and surface station observations) for the period of 1979–2002. Important findings of this study are: (i) about 45–55% of the total Indian rainfall is produced by the IMD; (ii) the rainfall maximum in the west’south-west sector of IMDs is largely maintained by convergence of atmospheric water vapor flux. The convergence of water vapor flux is largely coupled with the lower-tropospheric divergent circulation. Thus, the IMD water vapor budget is modulated by the 30–60 and 10–20 d monsoon modes through changes of water vapor convergence/divergence. The magnitude of this modulation on the IMD water vapor budget is close to a quarter of the summer-mean water vapor budget over the Bay of Bengal and north-eastern India.
Joint Optimization of Hidden Conditional Random Fields and Non Linear Feature Extraction

We describe an hybrid model that combines deep neural networks (DNN) for nonlinear feature extraction and hidden conditional random fields (HCRF), i.e. conditional random fields with hidden states. The model is globally trained though joint optimization of HCRF and DNN parameters. To deal with this highly non convex optimization criterion, we propose a multi-step training which aims at providing a good initialization before the final joint optimization of all parameters. We investigate then the discriminative power of these models with respect to the architecture of the DNN, and compare our models to HMM and HCRF based algorithms on the IAM database.
The simple fool's guide to population genomics via RNA‐Seq: an introduction to high‐throughput sequencing data analysis

High‐throughput sequencing technologies are currently revolutionizing the field of biology and medicine, yet bioinformatic challenges in analysing very large data sets have slowed the adoption of these technologies by the community of population biologists. We introduce the ‘Simple Fool's Guide to Population Genomics via RNA‐seq’ (SFG), a document intended to serve as an easy‐to‐follow protocol, walking a user through one example of high‐throughput sequencing data analysis of nonmodel organisms. It is by no means an exhaustive protocol, but rather serves as an introduction to the bioinformatic methods used in population genomics, enabling a user to gain familiarity with basic analysis steps. The SFG consists of two parts. This document summarizes the steps needed and lays out the basic themes for each and a simple approach to follow. The second document is the full SFG, publicly available at http://sfg.stanford. edu, that includes detailed protocols for data processing and analysis, along with a repository of custom‐made scripts and sample files. Steps included in the SFG range from tissue collection to de novo assembly, blast annotation, alignment, gene expression, functional enrichment, SNP detection, principal components and FST outlier analyses. Although the technical aspects of population genomics are changing very quickly, our hope is that this document will help population biologists with little to no background in high‐throughput sequencing and bioinformatics to more quickly adopt these new techniques.
Secure Error-Free Steganography for JPEG Images

The typical model of steganography has led the prisoners' problem, in which two persons attempt to communicate covertly without alerting the warden, that is, only the receiver knows the existence of the message sent by the sender. One available way to achieve this task is to embed the message in an innocuous-looking medium. In this paper, we propose a variation of the Quantization Index Modulation (QIM) for solving the prisoners' problem. We also propose a theorem to show that the error of mean intensity value of an image block caused by JPEG compression is bounded. The proposed method embeds the messages to be conveyed by modifying the mean intensity value, and the resulting stego-image can be stored in the JPEG format with a low quality setting. Besides, a specific pattern caused by using the QIM embedding method is also identified, and this pattern will be removed using the proposed embedding method. Experimental results and the proposed theorem show that the hidden message is error-free against the JPEG distortion under the quality setting as low as 25. Furthermore, the existence of the hidden message is not only visually imperceptible but also statistically undetectable.
Challenges and prospects of food science and technology education: Nepal's perspective

Food science and technology education has been running since four decades in Nepal. There is a very slow improvement in the profession. The job opportunities have always been threatened by insiders and outsiders. Academic institutions, government agencies, and food industries themselves are responsible for the quality of food science professionals. Novel and practical methods of teaching should be followed. The government and private organizations should facilitate the recruitment of food technologists. Constant prodding needs to be done for the establishment of a Council with more authority that could monitor all bodies associated with food science professionals.
Efficient large scale distributed matrix computation with spark

Matrix computation is the core of many massive data-intensive analytical applications such mining social networks, recommendation systems and nature language processing. Due to the importance of matrix computation, it has been widely studied for many years. In the Big Data ear, as the scale of the matrix grows, traditional single-node matrix computation systems can hardly cope with such large data and computation. Existing distributed matrix computation solutions are still not efficient enough, or have poor fault tolerance and usability. In this paper, we propose Marlin, an efficient distributed matrix computation library which is built on top of Spark. Marlin contains several distributed matrix operation algorithms and provides high-level matrix computation primitives for users. In Marlin, we proposed three distributed matrix multiplication algorithms for different situations. Based on this, we designed an adaptive model to choose the best approach for different problems. Moreover, to improve the computation performance, instead of naively using Spark, we put forward some optimizations including taking advantage of the native linear algebra library, reducing shuffle communication and increasing parallelism. Experimental results show that Marlin is over an order of magnitude faster than R (a widely-used statistical computing system) and the existing distributed matrix operation algorithms based on MapReduce. Moreover, Marlin achieves comparable performance to the specialized MPI-based matrix multiplication algorithm SUMMA but uses a general dataflow engine and gains common dataflow features such as scalability and fault tolerance.
Providing predictable streaming performance in mobile video streaming

Much work has been done to improve the performance of video streaming over mobile data networks. The widespread adoption of HTTP/TCP for video streaming further complicates the problem as TCP's own dynamics add even more fluctuations to the already unpredictable network bandwidth. Not surprisingly, none of the existing video bit-rate selection algorithms can achieve consistent or predictable streaming performance in the presence of wide network bandwidth fluctuations. This work tackles this problem by developing a new model to capture the statistical correlations between streaming performance, video bit-rate selection, and past TCP throughput data. Based on a novel post-streaming rate analysis technique, the proposed model can be used to predict the streaming performance of future video sessions at any given video bit-rate choices. This not only enables content providers to control the quality-of-service for streaming users, but also to ensure consistent streaming performance for users with widely different access bandwidths.
Distributed Many-to-Many Mapping Algorithm in the Hypercube Network

Server-client mapping is one of the most frequently encountered problems in nearly all the distributed systems, but is usually solved in ad-hoc manner in favor of quick implementation. To facilitate improved design of distributed applications, this paper addresses the issue of many-to-many node mapping in the hypercube. One can imagine that there exists a set of servers containing the data and a large number of clients requesting the data. The problem addressed in this paper is how to match the servers to clients so that the network loads are minimized. In this paper, we present a distributed many-to-many node mapping algorithm which allows scaling the network to very large size. Through simulation, we show that it has performance advantages in a number of areas. First, it reduces the level of congestion at the bottleneck link. Second, it consumes less network resources in terms of the total number of links used and bandwidth usage.
Extended LTA, TNF, LST1 and HLA Gene Haplotypes and Their Association with Rubella Vaccine-Induced Immunity

BACKGROUND Recent studies have suggested the importance of HLA genes in determining immune responses following rubella vaccine. The telomeric class III region of the HLA complex harbors several genes, including lymphotoxin alpha (LTA), tumor necrosis factor (TNF) and leukocyte specific transcript -1 (LST1) genes, located between the class I B and class II DRB1 loci. Apart from HLA, little is known about the effect of this extended genetic region on HLA haplotypic backgrounds as applied to immune responses. METHODOLOGY/PRINCIPAL FINDINGS We examined the association between immune responses and extended class I-class II-class III haplotypes among 714 healthy children after two doses of rubella vaccination. These extended haplotypes were then compared to the HLA-only haplotypes. The most significant association was observed between haplotypes extending across the HLA class I region, ten-SNP haplotypes, and the HLA class II region (i.e. A-C-B-LTA-TNF-LST1-DRB1-DQA1-DQB1-DPA1-DPB1) and rubella-specific antibodies (global p-value of 0.03). Associations were found between both extended A*02-C*03-B*15-AAAACGGGGC-DRB1*04-DQA1*03-DQB1*03-DPA1*01-DPB1*04 (p = 0.002) and HLA-only A*02-C*03-B*15-DRB1*04-DQA1*03-DQB1*03-DPA1*01-DPB1*04 haplotypes (p = 0.009) and higher levels of rubella antibodies. The class II HLA-only haplotype DRB1*13-DQA1*01-DQB1*06-DPA1*01-DPB1*04 (p = 0.04) lacking LTA-TNF-LST1 SNPs was associated with lower rubella antibody responses. Similarly, the class I-class II HLA-only A*01-C*07-B*08-DRB1*03-DQA1*05-DQB1*02-DPA1*01-DPB1*04 haplotype was associated with increased TNF-alpha secretion levels (p = 0.009). In contrast, the extended AAAACGGGGC-DRB1*01-DQA1*01-DQB1*05-DPA1*01-DPB1*04 (p = 0.01) haplotype was found to trend with decreased rubella-specific IL-6 secretion levels. CONCLUSIONS/SIGNIFICANCE These data suggest the importance of examining both HLA genes and genes in the class III region as part of the extended haplotypes useful in understanding genomic drivers regulating immune responses to rubella vaccine.
Fungal iron biomineralization in río tinto

Although there are many studies on biomineralization processes, most of them focus on the role of prokaryotes. As fungi play an important role in different geological and biogeochemical processes, it was considered of interest to evaluate their role in a natural extreme acidic environment, Rio Tinto, which has a high level of fungal diversity and a high concentration of metals. In this work we report, for the first time, the generation of iron oxyhydroxide minerals by the fungal community in a specific location of the Tinto basin. Using Transmission Electron Microscopy (TEM) and High Angle Angular Dark Field coupled with Scanning Transmission Electron Microscopy (HAADF-STEM) and Energy-Dispersive X-ray Spectroscopy (EDX), we observed fungal structures involved in the formation of iron oxyhydroxide minerals in mineralized sediment samples from the Rio Tinto basin. Although Rio Tinto waters are supersaturated in these minerals, they do not precipitate due to their slow precipitation kinetics. The presence of fungi, which simply provide charged surfaces for metal binding, favors the precipitation of Fe oxyhydroxides by overcoming these kinetic barriers. These results prove that the fungal community of Rio Tinto participates very actively in the geochemical processes that take place there.
Cryptanalysis of Syverson's Rational Exchange Protocol

The notion of rational exchange introduced by Syverson in 1998 is a particularly interesting alternative when an efficient scheme for fair exchange is required but the existence of a trusted third party simply cannot be assumed. A rational exchange protocol cannot provide true fairness, but it ensures that rational –i.e. self-interested– parties would have no reason to deviate from the protocol. In this paper, we identify some weaknesses in Syverson’s rational exchange protocol which were neither detected by the original author nor by subsequent analysis. After presenting some attacks, we indicate how the scheme should be modified to overcome these vulnerabilities. We also provide a formal analysis of our enhancement using BAN logic.
Quick Finding of Network Video Stream

Network video technology develops quickly in recent years and the applications of network video are various. The effectively managing of the application based on network video is necessary for network flow management, network security, etc. and finding video stream from the network flow is the precondition and foundation. This paper analyzes the characteristics of the video stream packets, and draws a conclusion that each network video stream type can be labeled uniquely by one characteristic string, based on which, we can find video streams in network flow easily. The experiment results show that the method is able to find network video streams accurately.
Mobile Surfing Pattern Analysis over Time and Location on a Big Access Record

The fast increasing WAP usage makes mobile-Internet a more and more important part of citizens' Internet life. As it is critical to mobile service market and city management, identifying surfing patterns of subgroups of mobile Internet users over time and based on locations will creates great value in Mobile Internet business and smart city management. In this paper, the author firstly examined the variation of surfing access, download and upload flow based on time and locations in which significantly and stable accessing peaks is found and verified. To detect the surfing behavior by individuals, the author traced the variation of surfing accessing over time and the variation of location of accessing and present them visually. The author finally obtained several surfing patterns that can precisely fit smaller subgroup of Mobile Internet users by hypothesis testing experiment.
Case Study in Simulated Concurrent Development and Evolution: Investigating the Theme Approach

AOSD aims at improving key software engineering properties (such as traceability, comprehensibility, and evolvability) through the separation and modularization of crosscutting concerns. The majority of AOSD research focuses on individual software engineering activities (such as implementation or requirements) in isolation. One exception to this trend is the Theme approach of Clarke and colleagues, which considers the derivation of implementations from requirements through design. Evidence is currently meagre for or against the claims of this approach. This paper describes a case study involving the development and evolution of a benchmark system to evaluate these claims. Alternative decisions are examined to consider whether one or more feasible development processes exist in applying Theme. Lessons learned from the study are discussed for their generalizability to other scenarios.
Identification of a Family of Sorting Nexin Molecules and Characterization of Their Association with Receptors

ABSTRACT Sorting nexin 1 (SNX1) is a protein that binds to the epidermal growth factor (EGF) receptor and is proposed to play a role in directing EGF receptors to lysosomes for degradation (R. C. Kurten, D. L. Cadena, and G. N. Gill, Science 272:1008–1010, 1996). We have obtained full-length cDNAs and deduced the amino acid sequences of three novel homologous proteins, which were denoted human sorting nexins (SNX2, SNX3, and SNX4). In addition, we identified a presumed splice variant isoform of SNX1 (SNX1A). These molecules contain a conserved domain of ∼100 amino acids, which was termed the phox homology (PX) domain. Human SNX1 (522 amino acids), SNX1A (457 amino acids), SNX2 (519 amino acids), SNX3 (162 amino acids), and SNX4 (450 amino acids) are part of a larger family of hydrophilic molecules including proteins identified in Caenorhabditis elegans andSaccharomyces cerevisiae. Despite their hydrophilic nature, the sorting nexins are found partially associated with cellular membranes. They are widely expressed, although the tissue distribution of each sorting nexin mRNA varies. When expressed in COS7 cells, epitope-tagged sorting nexins SNX1, SNX1A, SNX2, and SNX4 coimmunoprecipitated with receptor tyrosine kinases for EGF, platelet-derived growth factor, and insulin. These sorting nexins also associated with the long isoform of the leptin receptor but not with the short and medium isoforms. Interestingly, endogenous COS7 transferrin receptors associated exclusively with SNX1 and SNX1A, while SNX3 was not found to associate with any of the receptors studied. Our demonstration of a large conserved family of sorting nexins that interact with a variety of receptor types suggests that these proteins may be involved in several stages of intracellular trafficking in mammalian cells.
Universal Interfacing Circuit for Resistive-Bridge Sensors

A universal interfacing circuit for resistive-bridge sensing elements and bridge-output-to-frequency and/or duty cycle converters is described in this paper. It is based on a simple, cost effective three-point measuring technique and does not require any additional active components. The designed IC has been realized in a standard CMOS technology as a low power Application Specific Integrated Processor (ASIP). The active supply current at operating voltage +4.5 V and clock frequency 20 MHz is not more than 9.5 mA The circuit has been tested with a strain gauges bridge emulator and differential pressure resistive bridge sensor SX30GD2.