Miracle-dz/UniFAR-FTUs huggingface dataset:
Cohorts based custom models for rapid speaker and dialect adaptation

It is well known that speaker dependent acoustic models can achieve an error rate that is up to a factor of two smaller compared to well trained speaker independent acoustic models [1]. Thus, for improved accuracy, many modern dictation systems require the user to perform enrollment sessions to adapt the acoustic model of the system. In this paper, we present an approach that uses as few as three sentences from the test speaker to select N closest speakers (cohorts) from both the original training set and newly available training speakers to construct customized models. By using such an approach, our adaptation scheme can be updated online without reconfiguring anything that has been determined or calculated before, i.e. speaker independent model. When applying this approach to address dialectal differences, the cohort based user specific models constructed with 3 user sentences can obtain a lower error rate even when compared to user-adapted models based on 170 user sentences. On average, a relative error rate reduction of 22% was achieved.
Effect of Lesion Site on Serial Position During List Learning: A Study With The Cvlt

Successful learning of supraspan word lists such as the California Verbal Learning Test (CVLT) relies more on clustering strategies than rote learning, subserved by the frontal and temporal lobes. The authors studied the effect of word sequence in CVLT learning, in 15 patients with frontal (FLL) and 15 temporal (TLL) lesions, and 33 controls. Experimental measures were: number of clusters, number of first (FI), middle (MI) and last items (LI), in learning trials and in total immediate recall. FLL disclosed significantly lower FI along learning. Clusters were similar among groups. This difficulty is discussed according to the role of frontal lobes in learning and memory.
A Three-Phase Four-Wire Inverter Control Technique for a Single Distributed Generation Unit in Island Mode

A control technique is developed for a three-phase four-wire split DC bus inverter of a single distributed generation unit working in island mode. The control technique combines an inner discrete-time sliding mode controlled (DSMC) current loop and an outer robust servomechanism controlled voltage loop. The control algorithms are developed under stationary alphabeta0 (Clarke's) reference frame and a modified space vector pulsewidth modulation (MSVPWM) is proposed to implement the algorithm under Clarke's reference frame. The proposed technique achieves voltage regulation with low steady state error and low total harmonic distortion and fast transient response under various load disturbances. Meanwhile the usage of MSVPWM in a stationary alphabeta0 reference frame yields better transient performance under limited DC bus voltage compared to conventional uniformly sampled sine wave modulation in ABC reference frame. In this paper, besides the development and description of the algorithms, a series of discussions, analysis and studies are performed on the proposed control technique, including the L-C filter design issue, frequency domain closed-current-loop and closed-voltage-loop responses, and time domain simulations and experiments under various load conditions. All the analysis, simulations, and experiments demonstrate the effectiveness of the proposed control solution.
Performance evaluation of a pixellated Ge Compton camera

An ongoing project is being carried out to develop a high purity germanium (HPGe) Compton camera for medical applications. The Compton camera offers many potential advantages over the conventional gamma camera. The camera reported in this paper comprises two pixellated germanium detector planes housed 9.6 cm apart in the same vacuum housing. The camera has 177 pixels, 152 in the scatter detector and 25 in the absorption detector. The pixels are 4 × 4 mm2 with a thickness of 4 mm in the scatter detector and 10 mm in the absorption detector. Images have been taken for a variety of test objects including point sources, a ring source and a Perspex phantom. The measured angular resolution is 9.4° ± 0.4° for a 662 keV gamma-ray source at 3 cm. Due to the limited number of readout modules a multiple-view technique was used to image the source distributions from different angles and simulate the pixel arrangement in the full camera.
A review of the melatonin functions in zebrafish physiology

Melatonin is part of the evolutionary conserved highly functional network in vertebrates. It plays a central role in the adaptative behavior of the animal to the environment, including entrainment of daily and annual physiological rhythms, reproductive behavior, food intake, locomotor activity, growth, and breeding performance. In zebrafish, apart from its synchronizing capabilities, melatonin seems to have a major role in multiple physiological processes. Extensive knowledge of its genome and the identification of a series of genes with the same functions as those in humans, the relative ease of obtaining mutants, and the similarities between zebrafish and human pathologies make it an excellent experimental model organism of human diseases. Moreover, it is a common experimental species because of easy handling, breeding, and developmental control. Among other pathophysiologies, zebrafish are now used in studies of neurodegeneration and neurological diseases, endocrine diseases, behavior, muscular dystrophies, developmental alterations, circadian rhythms, and drugs screening. The purpose of this review was to update the current knowledge on the synthesis and biological functions of melatonin in zebrafish, keeping in mind its relevance not only in the physiology of the animal, but also in pathophysiological conditions.
Consistent Minimization of Clustering Objective Functions

Clustering is often formulated as a discrete optimization problem. The objective is to find, among all partitions of the data set, the best one according to some quality measure. However, in the statistical setting where we assume that the finite data set has been sampled from some underlying space, the goal is not to find the best partition of the given sample, but to approximate the true partition of the underlying space. We argue that the discrete optimization approach usually does not achieve this goal. As an alternative, we suggest the paradigm of "nearest neighbor clustering". Instead of selecting the best out of all partitions of the sample, it only considers partitions in some restricted function class. Using tools from statistical learning theory we prove that nearest neighbor clustering is statistically consistent. Moreover, its worst case complexity is polynomial by construction, and it can be implemented with small average case complexity using branch and bound.
Anomaly Detection based on Review Burstness and Ranking Fraud Discovery

Nowadays everyone is using smart phone. Many applications are in smart phone. To download an application user visit App store such as Google play store, Apple play store etc, then he or she is able to see the different application lists. User has no awareness about the application. So user looks at the list and download the application from App Store based on the mobile app rank. App developers use different ways to promote their Apps in order to get top position in App store for example, high rating and good reviews are given about the mobile app i.e. there is fraud behavior occur it. To detect fraud behavior first identify the active periods of mobile app, namely leading session of mobile apps. In the existing system the leading event and leading session of an app identified from the collected historical records. Then ranking based evidence, rating based evidence and review based evidence were collected from the historical records. These evidence score value is used to detect fraud behavior occur in the mobile app. In proposed system from the reviews of mobile app it identifies if it is a fake review or not.
Lack of Correlation between the Steady‐State Plasma Concentrations of Haloperidol and Risperidone

Both haloperidol and risperidone have been widely used in the treatment of schizophrenia. Because of wider therapeutic spectrum of risperidone, switching from haloperidol to risperidone is recommended in patients who do not sufficiently respond to haloperidol. The present study investigated the correlation between the steady‐state plasma concentrations of haloperidol and risperidone together with the effects of CYP2D6 status on the steady‐state kinetics of both drugs. Subjects were 22 schizophrenic inpatients. Eleven patients first received risperidone 6 mg/day and then haloperidol 12 mg/day, while the remaining 11 patients received these two treatments in the opposite sequence. The steady‐state plasma concentrations of risperidone, 9‐hydroxyrisperidone, haloperidol, and reduced haloperidol were measured after the subjects had been on the treatment for at least 2 weeks, and CYP2D6 genotypes were identified in all subjects. Neither the correlation between the steady‐state plasma concentrations of haloperidol and those of risperidone (r = 0.061, ns) nor the active moiety (sum of concentration of risperidone and 9‐hydroxyrisperidone) of risperidone (r = 0.141, ns) was significant. The mean (± SD) plasma concentration of risperidone in patients with mutated allele(s)forCYP2D6 was significantly higher than those without mutated allele (1.5 ± 0.7 vs. 8.5 ± 11.0, p<0.05), while such a tendency for haloperidol was not observed. The present study suggests that the steady‐state plasma concentration of risperidone is not predicted from that of haloperidol in the same individual, probably because of the much greater involvement of CYP2D6 in the metabolism of risperidone than in that of haloperidol.
Graph-based interpolation for DIBR-synthesized images with nonlocal means

Given texture and depth maps of a single reference viewpoint, one can synthesize a novel viewpoint image via depth-image-based rendering (DIBR) by mapping texture pixels from reference to virtual view. When the virtual viewpoint is much closer to the 3D scene than the reference view (camera movement in the z-dimension), objects close to the camera will enlarge in size in the virtual viewpoint image. An object's enlargement during DIBR means that its pixel samples in the reference view will be scattered to a larger spatial area, resulting in expansion holes. Following our previous work, we investigate the problem of expansion hole completion. We first assume a previously proposed method based on depth histogram is used to identify missing or erroneously translated pixels as expansion holes. We then propose a new graph-based interpolation technique to fill in expansion holes. Unlike our previous work, nonlocal but similar pixel patch information are incorporated into a new graph construction before a graph-based interpolation procedure with sparsity prior is executed, resulting in enhanced performance. Experimental results show that our new procedure of expansion hole filling can outperform inpainting procedure employed in VSRS 3.5 by up to 4.02 dB.
A parallel optimization method for stencil computation on the domain that is bigger than memory capacity of GPUs

The problem size of the stencil computation on GPU cluster is limited by the memory capacity GPUs, which is typically smaller than that of host memories. This paper proposes and evaluates parallel optimization method for stencil computation to achieve scalability, larger problem size than the memory capacity of GPUs and high performance. It uses 2D decomposition to achieve scalability over GPUs. Then it enables bigger sub-domain on each GPU to achieve bigger problem size. It applies temporal blocking method to improve memory access locality of stencil computation and reuses former result to solve redundant problem to get higher performance. Evaluation of stencil simulation on 3D domain shows that our new method for 7-point and 19-point on GPUs achieves good scalability which is 1.45 times and 1.72 times better than other methods on average.
Harvesting Fix Hints in the History of Bugs

In software development, fixing bugs is an important task that is time consuming and cost-sensitive. While many approaches have been proposed to automatically detect and patch software code, the strategies are limited to a set of identified bugs that were thoroughly studied to define their properties. They thus manage to cover a niche of faults such as infinite loops. We build on the assumption that bugs, and the associated user bug reports, are repetitive and propose a new approach of fix recommendations based on the history of bugs and their associated fixes. In our approach, once a bug is reported, it is automatically compared to all previously fixed bugs using information retrieval techniques and machine learning classification. Based on this comparison, we recommend top-{\em k} fix actions, identified from past fix examples, that may be suitable as hints for software developers to address the new bug.
Looking forward, looking back: capturing drought in flagrante delicto and uncovering its broader consequences for forest ecosystems.

The large-scale die-back and collapse of forest and woodland communities in recent decades has seen drought-induced tree mortality emerging as a prominent topic in the ecological and physiological literature. Against the spectre of a potential increase in the frequency and intensity of global change-type droughts and associated temperatures, it is argued that better understanding of the mechanisms driving plant mortality provides a basis for predicting how species may respond to future stresses associated with changing climates. Although it is tempting to try and isolate a primary mechanistic driver for tree mortality, the emerging picture is one of the complex interactions between multiple processes and stresses, often including biotic agents. In this issue of Tree Physiology , Gaylord et al. (2015) present an interesting retrospective examination of potential causes of mortality in Pinus–Juniper ecosystems. Their approach is akin to a forest post mortem, where the authors combined established methods in tree-ring analysis, stable isotope chemistry and xylem anatomy to disentangle the proximal (contributing) and ultimate (primary) causes of death among the victims (adult Pinus edulis trees) of an extreme drought ending in 2002. Gaylord et al. (2015) impli-cate the interactive effects of hydraulic dysfunction, carbon (C) metabolism and pest infestation, a conclusion consistent with a growing body of knowledge emphasizing the role of combined biotic and abiotic stressors in driving forest condition and tree death; see for example, Worrall et al. (2013), Jactel et al. (2012) or Jacquet
The Discourses of English Teaching.

Editors' Note: In the US increasingly we have seen both the federal and state governments intervening in education at the local level in terms both of curriculum and assessment. Beyond simple pronouncements on policy, lawmakers are mandating specific syllabi and measurement instruments. While such interference can cripple teacher and school initiative and set back more enlightened holistic approaches to the teaching of English, at least what legislation exists varies across a number of competing constituencies. In contrast, the British situation, with the current Thatcher government in power, recently has demonstrated a centralized effort to dismantle several generations of reform and attempts at educational equity and opportunity. In the following article, Peter Griffith, author of Literary Theory and the Teaching of English and Director of Professional Development in Education at the Open University, explores how the "growth model" of English remains vulnerable to attacks by the right because it has never clearly articulated its ideological and social agenda. By publishing this article we hope to encourage our readers to look more closely at the social consequences of the particular models of English instruction that they hold. This article is an attempt to define and analyze some of the features of the liberal approach to the teaching of English which has been such a significant feature of classroom practice in England and Wales during the past quarter of a century. My use of the word "significant" is intended to signal two things: the importance of this form of pedagogy as exemplary for, rather than always typical of, the profession during the period in question, and the fact that it now functions as a rallying point in the face of concerted state action to standardize and regulate the teaching of English. During the parliamentary year (1987-8) in which this article was written, a major education Bill was piloted through Parliament by the 191
Non-Preemptive Coflow Scheduling and Routing

As more and more data-intensive applications have been moved to the cloud, the cloud network has become the new performance bottleneck for cloud applications. To boost application performance, the concept of coflow has been proposed to bring application-awareness into the cloud network. A coflow consists of many individual data flows, and a coflow is completed only when all its component flows are transmitted. The network performance of a cloud application is dependent on the completion time of coflows, rather than the completion time of each individual flow. Existing coflow-aware optimization solutions employ flow preemption to reduce the completion time, which brings difficulty in practical implementation and non-negligible overhead. In this paper, we study the non-preemptive coflow scheduling and routing problem in the cloud network. We propose an offline optimization framework for coflow scheduling, as well as two subroutines for coflow routing using single-path routing and multi-path routing respectively. We also show that our proposed framework is easily extensible to the online scenario. Extensive evaluations show that the proposed solutions can greatly reduce coflow completion time compared to coflow-agnostic solutions, and are also computationally efficient.
Anti-biofilm activity of silver nanoparticles against different microorganisms

Biofilms confer protection from adverse environmental conditions and can be reservoirs for pathogenic organisms and sources of disease outbreaks, especially in medical devices. The goal of this research was to evaluate the anti-biofilm activities of silver nanoparticles (AgNPs) against several microorganisms of clinical interest. The antimicrobial activity of AgNPs was tested within biofilms generated under static conditions and also under high fluid shears conditions using a bioreactor. A 4-log reduction in the number of colony-forming units of Pseudomonas aeruginosa was recorded under turbulent fluid conditions in the CDC reactor on exposure to 100 mg ml−1 of AgNPs. The antibacterial activity of AgNPs on various microbial strains grown on polycarbonate membranes is reported. In conclusion, AgNPs effectively prevent the formation of biofilms and kill bacteria in established biofilms, which suggests that AgNPs could be used for prevention and treatment of biofilm-related infections. Further research and development are necessary to translate this technology into therapeutic and preventive strategies.
Montelukast as add-on therapy with inhaled corticosteroids alone or inhaled corticosteroids and long-acting beta-2-agonists in the management of patients diagnosed with asthma and concurrent allergic rhinitis (the RADAR trial).

OBJECTIVE To evaluate the effectiveness of montelukast as add-on therapy for patients diagnosed with asthma and concurrent allergic rhinitis who remain uncontrolled while receiving inhaled corticosteroid (ICS) monotherapy or ICS/long-acting beta-2-agonist (LABA) therapy in a community practice setting. DESIGN An eight-week, multicentre, open-label, observational study. Patients were 15 years of age or older and, while treated with an ICS or ICS/LABA, had allergic rhinitis and uncontrolled asthma symptoms by at least two criteria as per the Canadian Asthma Consensus Guidelines. The primary outcome measure was the percentage of patients with controlled asthma symptoms after eight weeks of treatment with montelukast 10 mg once daily added to ICS or ICS/LABA therapy. RESULTS In total, 1004 patients participated in the survey phase of the study. Of these patients, 319 continued in the treatment phase and 301 (94.4%) completed the eight-week assessment. At baseline, all patients had uncontrolled asthma symptoms based on the Canadian Asthma Consensus Guidelines; at the eight-week assessment, 229 patients (76.1%) achieved asthma control. According to the Asthma Control Questionnaire (as determined by scores of 0.75 or less), 164 patients (54.7%) achieved well-controlled asthma at week 8. The mean (+/- SD) Asthma Control Questionnaire score decreased from 2.03+/-0.80 to 0.92+/-0.80 (P<0.001) for all patients, representing a clinically significant improvement. A statistically and clinically significant reduction in the overall Mini Rhinitis Quality of Life Questionnaire score was achieved with a decrease from 2.57+/-1.20 to 1.12+/-1.00 (-1.45+/-1.35; P<0.001). Patient and physician satisfaction rates with montelukast add-on therapy were also significantly increased when compared with baseline treatment. CONCLUSION Montelukast add-on therapy is effective for managing asthma and allergic rhinitis symptoms in patients who were previously uncontrolled with ICS or ICS/LABA treatment.
Rapid free-space mapping from a single omnidirectional camera

Low-cost robots such as floor cleaners generally rely on limited perception and simple algorithms, but some new models now have enough sensing capability and computation power to enable Simultaneous Localisation And Mapping (SLAM) and intelligent guided navigation. In particular, computer vision is now a serious option in low cost robotics, though its use to date has been limited to feature-based mapping for localisation. Dense environment perception such as free space finding has required additional specialised sensors, adding expense and complexity. Here we show that a robot with a single passive omnidirectional camera can perform rapid global free-space reasoning within typical rooms. Upon entering a new room, the robot makes a circular movement to capture a closely-spaced omni image sequence with disparity in all horizontal directions. feature-based visual SLAM procedure obtains accurate poses for these frames before passing them to a dense matching step, 3D semi-dense reconstruction and visibility reasoning. The result is turned into a 2D occupancy map, which can be improved and extended if necessary through further movement. This rapid, passive technique can capture high quality free space information which gives a robot a global understanding of the space around it. We present results in several scenes, including quantitative comparison with laser-based mapping.
Neurovascular Coupling of the Posterior Cerebral Artery in Spinal Cord Injury: A Pilot Study

Purpose: To compare neurovascular coupling in the posterior cerebral artery (PCA) between those with spinal cord injury (SCI) and able bodied (AB) individuals. Methods: A total of seven SCI and seven AB were matched for age and sex. Measures included PCA velocity (PCAv), beat-by-beat blood pressure and end-tidal carbon dioxide. Posterior cerebral cortex activation was achieved by 10 cycles of (1) 30 s eyes closed (pre-stimulation), (2) 30 s reading (stimulation). Results: Blood pressure was significantly reduced in those with SCI (SBP: 100 ± 13 mmHg; DBP: 58 ± 13 mmHg) vs. AB (SBP: 121 ± 12 mmHg; DBP: 74 ± 9 mmHg) during both pre-stimulation and stimulation, but the relative increase was similar during the stimulation period. Changes in PCAv during stimulation were mitigated in the SCI group (6% ± 6%) vs. AB (29% ± 12%, P < 0.001). Heart rate and end-tidal carbon dioxide responded similarly between groups. Conclusions: Clearly, NVC is impaired in those with SCI. This study may provide a link between poor perfusion of the posterior cerebral region (containing the medullary autonomic centres) and autonomic dysfunction after SCI.