Miracle-dz/UniFAR-FTUs huggingface dataset:
Asynchronous factorisation of speaker and background with feature transforms in speech recognition

This paper presents a novel approach to separate the effects of speaker and background conditions by application of feature– transform based adaptation for Automatic Speech Recognition (ASR). So far factorisation has been shown to yield improvements in the case of utterance-synchronous environments. In this paper we show successful separation of conditions asynchronous with speech, such as background music. Our work takes account of the asynchronous nature of the background, by estimation of condition-specific Constrained Maximum Likelihood Linear Regression (CMLLR) transforms. In addition, speaker adaptation is performed, allowing to factorise speaker and background effects. Equally, background transforms are used asynchronously in the decoding process, using a modified Hidden Markov Model (HMM) topology which applies the optimal transform for each frame. Experimental results are presented on the WSJCAM0 corpus of British English speech, modified to contain controlled sections of background music. This addition of music degrades the baseline Word Error Rate (WER) from 10.1% to 26.4%. While synchronous factorisation with CMLLR transforms provides 28% relative improvement in WER over the baseline, our asynchronous approach increases this reduction to 33%. Index Terms: Speech recognition, adaptation, factorisation, asynchronous decoding
Healthy adult aging and decision-making:Is it all downhill from here?

As we age there are significant changes to our brain structure and cognitive functioning. There is a substantial body of literature exploring changes to memory and attention during healthy adult aging. There has been considerably less focus on the impact of aging on other areas of cognition, specifically, decision-making. This is surprising given that choices are ubiquitous in daily life across the lifespan. For example, older adults still face many significant decisions including those concerning finances in light of reduced income and choices about lifestyle factors in response to potential healthcare issues. Recently, the research community has increasingly shown appreciation of these issues and the literature on changes to decision-making function due to healthy aging is beginning to converge on key themes that are particularly telling in terms of how aging affects decision-making. The literature has focused predominantly on the negative effects of healthy aging on decision-making, particularly in terms of risk-processing. However, although fewer in number, some studies have identified age-related positive effects commonly attributed to an accumulation of ‘wisdom’ by the older adult. This review will provide an overview of the negative and positive changes to decision-making as we age and will, uniquely, converge these two streams of research and put forward the hypothesis that age-related changes in decision-making, underpinned by changes to the structure and function of the aging brain, underlie both positive and negative changes, the manifestation of which depends on choice context.
Recurrent neural network language model in mandarin voice input system

Over more than three decades, the development of automatic speech recognition (ASR) technology has made it possible for some intelligent query systems to use a voice interface. Specially, voice input system is a practical and interesting application of ASR. In this paper, we present our recent work on using Recurrent Neural Network Language Model (RNNLM) to improve the performance of our Mandarin voice input system. The Mandarin voice input system employs a two-pass strategy. In the first pass, a memory-efficient state network and a tri-gram language model are used to generate the word lattice from which the n-best list is extracted. And, in the second pass, we use a large 4-gram language model and RNNLM to re-rank the n-best list and then output the new best hypothesis. Experiments showed that it was very effective for RNNLM to be used in the n-best list re-score. Eventually, 10.2% relative reduction in word error rate (from 13.7% to 12.3%) was achieved on a voice search task, compared to the result of the first pass.
Sinfonia: a new paradigm for building scalable distributed systems

We propose a new paradigm for building scalable distributed systems. Our approach does not require dealing with message-passing protocols -- a major complication in existing distributed systems. Instead, developers just design and manipulate data structures within our service called Sinfonia. Sinfonia keeps data for applications on a set of memory nodes, each exporting a linear address space. At the core of Sinfonia is a novel minitransaction primitive that enables efficient and consistent access to data, while hiding the complexities that arise from concurrency and failures. Using Sinfonia, we implemented two very different and complex applications in a few months: a cluster file system and a group communication service. Our implementations perform well and scale to hundreds of machines.
3D Shape Classification Using Information Fusion

The intent of 3D-model classification is to find categories of similar objects according to their shapes. This task is a challenging and important problem in 3D-mining and shape processing. In this paper, we present a novel method to categorize 3D-objects based on view-based descriptors. The proposed method goes into two stages. The first stage corresponds to the training in which 3D-objects in the same category are processed and a set of representative 2D views is selected, The second stage corresponds to the labelling in which unknown objects are classified using a belief based classifier. The experimental results obtained on the Shrec07 datasets show that the system efficiently performs in categorizing 3D-models.
Developing a model of evacuation after an earthquake in Lebanon

This article describes the development of an agent-based model (AMEL, Agent-based Model for Earthquake evacuation in Lebanon) that aims at simulating the movement of pedestrians shortly after an earthquake. The GAMA platform was chosen to implement the model. AMEL is applied to a real case study, a district of the city of Beirut, Lebanon, which potentially could be stricken by a M7 earthquake. The objective of the model is to reproduce real life mobility behaviours that have been gathered through a survey in Beirut and to test different future scenarios, which may help the local authorities to target information campaigns.
Range image super-resolution via reconstruction of sparse range data

We propose a method for super-resolution of range image. Our approach leverages the interpretation of LR image as sparse samples on the HR grid. Based on this interpretation, we build upon a recent approach which reconstructs dense range images from sparse range data. We notice certain shortcomings of this approach and propose some improvements, particularly, to address the super-resolution problem. Our method only uses a single colour image in addition to the range observation in the super-resolution process. Using the proposed approach, we demonstrate super-resolution results for large factors (e.g. 4 and 8) with good localization and accuracy.
A "MICROTUBULE" IN PLANT CELL FINE STRUCTURE

This paper reports an electron microscope examination of the cortices of some plant cells engaged in wall formation. Previous studies of similar material fixed in OSO4 alone have disclosed discontinuities in the plasma membrane and other evidence of inadequate fixation. After glutaraldehyde, used as a fixative in this present study, the general preservation of cortical fine structure is greatly improved. This is shown, for example, by the first evidence of slender tubules, 230 to 270 A in diameter and of indeterminate length, in plant cells of this type. They have been found in the cortical regions of cells of two angiosperms and one gymnosperm, representing all the material so far studied following this method of fixation. The tubules are identical in morphology to those also observed here in the mitotic spindles of plant cells, except that the latter have a somewhat smaller diameter. It is noted that the cortical tubules are in a favored position to govern cytoplasmic streaming and to exert an influence over the disposition of cell wall materials. In this regard it may be of some significance that the tubules just beneath the surface of the protoplast mirror the orientation of the cellulose microfibrils of the adjacent cell walls.
Endo-β-N-acetylglucosaminidase forms N-GlcNAc protein aggregates during ER-associated degradation in Ngly1-defective cells

Significance In the endoplasmic reticulum (ER), N-glycans on glycoproteins play important roles in dictating the folding status of proteins by a sophisticated N-glycan–dependent protein quality control machinery. In this study we identified the dysregulation of ER-associated degradation (ERAD) in cells that were defective in the cytosolic deglycosylating enzyme, Ngly1. ERAD dysregulation was caused by an unexpected deglycosylating activity of endo-β-N-acetylglucosaminidase, another cytosolic deglycosylation enzyme, and this action resulted in the intracellular formation of protein aggregates. Our results clearly point to the critical role of N-glycans even in cytosolic events of the ERAD process by controlling the conformation/solubility of proteins. This study may also provide a potential mechanism for explaining the pathology of a human genetic disorder caused by mutations in the NGLY1 gene. The cytoplasmic peptide:N-glycanase (PNGase; Ngly1 in mice) is a deglycosylating enzyme involved in the endoplasmic reticulum (ER)-associated degradation (ERAD) process. The precise role of Ngly1 in the ERAD process, however, remains unclear in mammals. The findings reported herein, using mouse embryonic fibroblast (MEF) cells, that the ablation of Ngly1 causes dysregulation of the ERAD process. Interestingly, not only delayed degradation but also the deglycosylation of a misfolded glycoprotein was observed in Ngly1−/− MEF cells. The unconventional deglycosylation reaction was found to be catalyzed by the cytosolic endo-β-N-acetylglucosaminidase (ENGase), generating aggregation-prone N-GlcNAc proteins. The ERAD dysregulation in cells lacking Ngly1 was restored by the additional knockout of ENGase gene. Thus, our study underscores the functional importance of Ngly1 in the ERAD process and provides a potential mechanism underlying the phenotypic consequences of a newly emerging genetic disorder caused by mutation of the human NGLY1 gene.
Lehrstuhl für Informatik 10 ( Systemsimulation ) A Flexible Patch-Based Lattice Boltzmann Parallelization Approach for Heterogeneous GPU – CPU Clusters

Sustaining a large fraction of single GPU performance in parallel computations is considered to be the major problem of GPU-based clusters. We address this issue in the context of a lattice Boltzmann flow solver that is integrated in the WaLBerla software framework. Our multi-GPU implementation uses a block-structured MPI parallelization and is suitable for load balancing and heterogeneous computations on CPUs and GPUs. The overhead required for multi-GPU simulations is discussed in detail. It is demonstrated that a large fraction of the kernel performance can be sustained for weak scaling on InfiniBand clusters, leading to excellent parallel efficiency. However, in strong scaling scenarios using multiple GPUs is much less efficient than running CPU-only simulations on IBM BG/P and x86-based clusters. Hence, a cost analysis must determine the best course of action for a particular simulation task and hardware configuration. Finally we present weak scaling results of heterogeneous simulations conducted on CPUs and GPUs simultaneously, using clusters equipped with varying node configurations.
Group-by skyline query processing in relational engines

The skyline operator was first proposed in 2001 for retrieving interesting tuples from a dataset. Since then, 100+ skyline-related papers have been published; however, we discovered that one of the most intuitive and practical type of skyline queries, namely, group-by skyline queries remains unaddressed. Group-by skyline queries find the skyline for each group of tuples. In this paper, we present a comprehensive study on processing group-by skyline queries in the context of relational engines. Specifically, we examine the composition of a query plan for a group-by skyline query and develop the missing cost model for the BBS algorithm. Experimental results show that our techniques are able to devise the best query plans for a variety of group-by skyline queries. Our focus is on algorithms that can be directly implemented in today's commercial database systems without the addition of new access methods (which would require addressing the associated challenges of maintenance with updates, concurrency control, etc.).
Precoder design for AF cooperative systems with multiple wiretapping relays

This paper considers an amplify-and-forward (AF) cooperative system with multiple relays which may eavesdrop on the source signal without authorization. In conventional cooperative system where the relays are assumed trustworthy, the precoding design usually tends to optimize quality of the received signal at the relays. However, the considered system relies on the relays' assistance and requires to prevent source information eavesdropped by the relays. With this regard, we proposed that the destination transmits artificial noise to interfere the signal reception of wiretapping relays. The artificial noise can be fully eliminated at the destination with perfect channel information. We propose a precoder design for the cooperative system that aims to maximize the received SNR at the destination subject to constraining quality of received signal at the relays. It shows through simulation results that the proposed scheme is able to improve the secrecy capacity of the cooperative system with wiretapping relays effectively.
New Delhi Metallo – beta lactamase – 1 containing Enterobacteriaceae: Origin, Diagnosis, Treatment and Public health concern

One of the biggest problems associated with the antibiotic therapy is resistance. Recently published studies have revealed that enterobacteriaceae, like E. coli and Klebsiella, isolated from several Indian centers are resistant to many antibiotics including some highly potent antibiotics like carbapenems. It has been proposed that this resistance is because of a carbapenemase enzyme called NDM- 1 (New Delhi Metallo-betalactamase-1). This carbapenemase is class B carbapenemase also called metallolactamases as they require zinc at their active site. This enzyme is coded by a gene called bla - NDM -1 or gene NDM -1. NDM -1 containing enterobacteriaceae can be screened in laboratory by few techniques. Metallolactamase production can be detected by disk approximation test or Modified Hodge test and NDM -1 gene can be detected by polymerase chain reaction by the use of specific primer targeting the gene. Infections caused by such bacteria are associated with high morbidity and mortality. Two classes of antibiotics i.e., polymyxins (colistin) and glycylcyclines (tigecyclines), have shown in vitro activity against NDM -1 harboring enterobacteriaceae. The safety profile of both of these antibiotics is questionable. There is a need for active screening of microorganisms for NDM -1 and research should be directed towards the development of safe antibiotics for the treatment of these kinds of infections.
HashCache: Cache Storage for the Next Billion

We present HashCache, a configurable cache storage engine designed to meet the needs of cache storage in the developing world. With the advent of cheap commodity laptops geared for mass deployments, developing regions are poised to become major users of the Internet, and given the high cost of bandwidth in these parts of the world, they stand to gain significantly from network caching. However, current Web proxies are incapable of providing large storage capacities while using small resource footprints, a requirement for the integrated multi-purpose servers needed to effectively support developing-world deployments. Hash-Cache presents a radical departure from the conventional wisdom in network cache design, and uses 6 to 20 times less memory than current techniques while still providing comparable or better performance. As such, Hash-Cache can be deployed in configurations not attainable with current approaches, such as having multiple terabytes of external storage cache attached to low-powered machines. HashCache has been successfully deployed in two locations in Africa, and further deployments are in progress.
Corneal Ulcers in Two Children Wearing Paragon Corneal Refractive Therapy Lenses

Objectives. To report the development of corneal ulcers in two children wearing Paragon Corneal Refractive Therapy (CRT) lenses. Methods. Two case reports of children who developed corneal ulcers when fit with Paragon CRT contact lenses, which were worn nightly, are discussed. Each patient presented with a bacterial corneal ulcer after wearing CRT contact lenses for less than 6 months. In the first patient, Pseudomonas aeruginosa was identified as the causative organism. In the second patient, Haemophilus influenza was cultured from the ulcer. Results. Both patients were treated with intensive, fortified antibiotics with rapid resolution of the corneal ulcers and preservation of vision. No surgical intervention was required. Conclusions. Paragon CRT lenses have been approved for use in patients of all ages. When used in children, these lenses may present unique problems. The absolute incidence of bacterial corneal ulcers in patients with CRT lenses are unknown. Severe caution should be used before prescribing CRT lenses for children and informed consent should include potential sight-threatening corneal ulcers.
Forge: generating a high performance DSL implementation from a declarative specification

Domain-specific languages provide a promising path to automatically compile high-level code to parallel, heterogeneous, and distributed hardware. However, in practice high performance DSLs still require considerable software expertise to develop and force users into tool-chains that hinder prototyping and debugging. To address these problems, we present Forge, a new meta DSL for declaratively specifying high performance embedded DSLs. Forge provides DSL authors with high-level abstractions (e.g., data structures, parallel patterns, effects) for specifying their DSL in a way that permits high performance. From this high-level specification, Forge automatically generates both a naïve Scala library implementation of the DSL and a high performance version using the Delite DSL framework. Users of a Forge-generated DSL can prototype their application using the library version, and then switch to the Delite version to run on multicore CPUs, GPUs, and clusters without changing the application code. Forge-generated Delite DSLs perform within 2x of hand-optimized C++ and up to 40x better than Spark, an alternative high-level distributed programming environment. Compared to a manually implemented Delite DSL, Forge provides a factor of 3-6x reduction in lines of code and does not sacrifice any performance. Furthermore, Forge specifications can be generated from existing Scala libraries, are easy to maintain, shield DSL developers from changes in the Delite framework, and enable DSLs to be retargeted to other frameworks transparently.
Effectiveness and safety of poly (ADP-ribose) polymerase inhibitors in cancer therapy: A systematic review and meta-analysis

Poly (ADP-ribose) polymerase (PARP) inhibitors are a class of small-molecule drugs suppressing PARP enzymes activity, inducing the death of cells deficient in homologous recombination repair (HRR). HRR deficiency is common in tumor cells with BRCA gene mutation. Since their first clinical trial in 2003, PARP inhibitors have shown benefit in the treatment of HRR-deficient tumors. Recently, several randomized clinical trials (RCTs) have been conducted to investigate the potential benefit of administration of PARP inhibitors in cancer patients. However, the results remain controversial. To evaluate the efficiency and safety of PARP inhibitors in patients with cancer, we performed a comprehensive meta-analysis of RCTs. According to our study, PARP inhibitors could clearly improve progression-free survival (PFS), especially in patients with BRCA mutation. However, our study showed no significant difference in overall survival (OS) between the PARP inhibitors and controls, even in the BRCA mutation group. Little toxicity was reported in the rate of treatment correlated adverse events (AEs) in PARP inhibitor group compared with controls. In conclusion, PARP inhibitors do well in improving PFS with little toxicity, especially in patients with BRCA deficiency.
Risk Factors and Prediction of Stroke in a Population with High Prevalence of Diabetes: The Strong Heart Study

Background and Objective American Indians have a high prevalence of diabetes and higher incidence of stroke than that of whites and blacks in the U.S. Stroke risk prediction models based on data from American Indians would be of clinical and public health value. Methods and Results A total of 3483 (2043 women) Strong Heart Study participants free of stroke at baseline were followed from 1989 to 2010 for incident stroke. Overall, 297 stroke cases (179 women) were identified. Cox models with stroke-free time and risk factors recorded at baseline were used to develop stroke risk prediction models. Assessment of the developed stroke risk prediction models regarding discrimination and calibration was performed by an analogous C-statistic (C) and a version of the Hosmer-Lemeshow statistic (HL), respectively, and validated internally through use of Bootstrapping methods. Results Age, smoking status, alcohol consumption, waist circumference, hypertension status, an-tihypertensive therapy, fasting plasma glucose, diabetes medications, high/low density lipoproteins, urinary albumin/creatinine ratio, history of coronary heart disease/heart failure, atrial fibrillation, or Left ventricular hypertrophy, and parental history of stroke were identified as the significant optimal risk factors for incident stroke. Discussion The models produced a C = 0.761 and HL = 4.668 (p = 0.792) for women, and a C = 0.765 and HL = 9.171 (p = 0.328) for men, showing good discrimination and calibration. Conclusions Our stroke risk prediction models provide a mechanism for stroke risk assessment designed for American Indians. The models may be also useful to other populations with high prevalence of obesity and/or diabetes for screening individuals for risk of incident stroke and designing prevention programs.
Aircraft Emissions' Contributions to Organic Aerosols in a Regional Air Quality Model using the Volatility Basis Set

A framework that employs the Volatility Basis Set (VBS) within the Community Multiscale Air Quality Model (CMAQ) was applied to predict organic aerosol concentrations from aircraft emissions. This framework was further expanded to include the formation of secondary organic aerosols from semi and intermediate volatile organic compounds which are traditionally missing from emission inventories used in air quality models. Results indicated that CMAQ with VBS predicted similar total contributions to fine particulate matter compared to CMAQ without VBS but with variations in the composition of organic species.