Miracle-dz/UniFAR-FTUs huggingface dataset:
Ratings of Speech Naturalness of Children Ages 8–16 Years

The focus of this cross-sectional study was the investigation of Speech Naturalness (speech that sounds normal or natural to the listener) of 60 normal speaking children and adolescents between the ages of 8 and 16 years. 26 naive adult listeners rated the naturalness of videotaped and computer-presented speech samples, using a 9-point-Likert rating scale (1: highly natural sounding speech and 9: highly unnatural sounding speech). The children and adolescents who participated as speakers were distributed among 5 age groups (8, 10, 12, 14, and 16 yr.) with 6 boys and 6 girls in each group. Each child demonstrated normal articulation, language, voice, and speech fluency skills. Age and sex comparisons indicated boys' and girls' speech was rated comparably; however, 8-yr. -olds' speech was rated as significantly less natural than those of 12-, 14-, and 16-yr. -olds. Preliminary ratings of Speech Naturalness for normal speaking children were presented. Suggestions for the clinical application of the findings as a target criterion in treatment programs with communicatively impaired children were suggested. Replication with a larger and more representative sample is in order.
Online human training of a myoelectric prosthesis controller via actor-critic reinforcement learning

As a contribution toward the goal of adaptable, intelligent artificial limbs, this work introduces a continuous actor-critic reinforcement learning method for optimizing the control of multi-function myoelectric devices. Using a simulated upper-arm robotic prosthesis, we demonstrate how it is possible to derive successful limb controllers from myoelectric data using only a sparse human-delivered training signal, without requiring detailed knowledge about the task domain. This reinforcement-based machine learning framework is well suited for use by both patients and clinical staff, and may be easily adapted to different application domains and the needs of individual amputees. To our knowledge, this is the first my-oelectric control approach that facilitates the online learning of new amputee-specific motions based only on a one-dimensional (scalar) feedback signal provided by the user of the prosthesis.
Understanding injury mechanisms: a key component of preventing injuries in sport

Anterior cruciate ligament (ACL) injuries are a growing cause of concern, as these injuries can have serious consequences for the athlete with a greatly increased risk of early osteoarthrosis. Using specific training programmes, it may be possible to reduce the incidence of knee and ankle injuries. However, it is not known which programme components are the key to preventing knee and ankle injuries or how the exercises work to reduce injury risk. Our ability to design specific prevention programmes, whether through training or other preventive measures, is currently limited by an incomplete understanding of the causes of injuries. A multifactorial approach should be used to account for all the factors involved-that is, the internal and external risk factors as well as the inciting event (the injury mechanism). Although such models have been presented previously, we emphasise the need to use a comprehensive model, which accounts for the events leading to the injury situation (playing situation, player and opponent behaviour), as well as to include a description of whole body and joint biomechanics at the time of injury.
What efficacy measures are clinically relevant and should be used in Cochrane Reviews of acute migraine trials? A viewpoint

Background Cochrane Reviews are methodologically of high quality but the clinical relevance of analysed efficacy measures (EMs) should also be assessed. Methods The clinical relevance of EMs used in one systematic Cochrane review of oral zolmitriptan for migraine headache was evaluated. Results The following EMs were used: pain free at two hours (30%), headache relief at two hours (60%), sustained pain free for 24 hours (19%) and sustained headache relief for 24 hours (39%). These EMs were also used in four other Cochrane reviews of acute migraine treatment. Of these EMs sustained headache relief for 24 h is not judged clinically relevant. Conclusion Pain free and sustained pain free are clinically relevant, but the responses are rather low, demonstrating that there is a need for improvement of acute drug treatment in migraine.
Collaborative Water Governance in the Colorado River Basin: Understanding Coalition Dynamics and Processes of Policy Change

As environmental policymaking and governance processes increasingly utilize collaborative approaches, evaluating whether these approaches are more effective than traditional, top-down governance is crucial. While generalized policy process theories often fail to capture the idiosyncrasies of collaborative approaches, emerging theories of collaborative governance are often too specific to apply in comparisons of multiple governance arrangements. In response, this paper proposes how the Advocacy Coalition Framework (ACF), a well-tested policy process framework, can be adapted to rigorously evaluate collaborative processes while retaining a common language and set of variables that facilitate comparisons of multiple governance approaches. Specifically, this paper develops hypotheses about the ACF’s key theoretical foci in the context of collaboration, and then provides a preliminary exploration of them using data from a multi-level collaborative environmental governance process. This study broadens the ACF’s applicability to collaborative contexts and introduces a new tool to the growing field of comparative policy process scholarship.
The roles of geography, climate and sexual selection in driving divergence among insect populations on mountaintops

Analysing the drivers of intraspecific variation and how reproductive barriers arise is an essential step to infer the mechanisms of biogeographic differentiation. In populations of a specialized alpine species, we explore the role of geography and climate in the divergence of genetic, morphological and acoustic characters, and analyse the functional consequences of variation on mate choice.
TimeML: Robust Specification of Event and Temporal Expressions in Text

In this paper we provide a description of TimeML, a rich specification language for event and temporal expressions in natural language text, developed in the context of the AQUAINT program on Question Answering Systems. Unlik em ost previous work on event annotation, TimeML capture st hree distinct phenomena in temporal markup: (1) it systematically anchors event predicates to a broad range of temporally denotating expressions; (2) it orders event expressions in text relative to one another, both intrasententially and in discourse; and (3) it allows for a delayed (underspecified) interpretation of partially determined temporal expressions. We demonstrate the expressiveness of TimeML for a broad range of syntactic and semantic contexts, including aspectual predication, modal subordination, and an initial treatment of lexical and constructional causation in text.
Improvement of speech intelligibility by reallocation of spectral energy

This report describes a method of speech modiﬁcation to improve the intelligibility of speech. The spectral energy is re-allocated by maintaining and emphasizing acoustical features important for speech perception. The method consists of three components: ﬂattening of the spectral tilt, enhancement of the spectral contrast, and holding of the low-frequency region. The results of this speech intelligibility test show that this method improves the speech intelligibility for all conditions of noise and SNR employed in the test
Effect of Deficit Irrigation During Growth Stages on Water Use Efficiency of Carrot Under El-Ismailia Conditions

Rationalization of irrigation water became a unique and necessary way to save the water used in sandy soil of Egypt. Scheduling the required irrigation water for each crop will help in minimizing the water lost during the growing season. Regulated deficit irrigation (RDI) is a strategy that applies less than the full replacement volume of water consumed by a plant, usually during a specific developmental stage. The key to the regulated deficit irrigation strategy is the timing of the deficit and the degree of the deficit applied to achieve a desired effect on the plant. Regulated deficit irrigation is water saving technology that is relatively inexpensive and easy to implement (Webber et al., 2007). When water deficit occurs during a specific crop development period, the yield response can vary depending on crop sensitivity at that growth stage. Therefore, timing the water deficit appropriately is a tool for Effect of Deficit Irrigation During Growth Stages on Water Use Efficiency of Carrot Under El-Ismailia Conditions
Algorithm 8 xx : a concise sparse Cholesky factorization package

The LDL software package is a set of short, concise routines for factorizing symmetric positive-definite sparse matrices, with some applicability to symmetric indefinite matrices. Its primary purpose is to illustrate much of the basic theory of sparse matrix algorithms in as concise a code as possible, including an elegant new method of sparse symmetric factorization that computes the factorization row-by-row but stores it column-by-column. The entire symbolic and numeric factorization consists of a total of only 53 lines of code. The package is written in C, and includes a MATLAB interface.
Fast Rotation Center Identification Methods for Video Sequences

Rotational motion can often be seen in video. However, comparatively little research has been done to investigate rotational motions in video, whose analysis could be useful. For example, if we can efficiently identify the rotation center of a spinning object, extraction and tracking of it can be made easier by grouping points moving at the same radial speed. It could also improve compression by synthesizing analyzed spin transitions, and help tracking of rotating objects. In this paper, we introduce a set of rotation center location methods using only the motion field constructed during video encoding, along with a few methods for improving their performances. These methods can be implemented using integer operations only. They are up to 1.81 times faster than the traditional circulation analysis method with little sacrifice in accuracy, and are not affected by asymmetric fields caused by translational motions.
ASSIMILATION OF PASSIVE MICROWAVE BRIGHTNESS TEMPERATURES FOR SNOW WATER EQUIVALENT ESTIMATION USING THE NASA CATCHMENT LAND SURFACE MODEL AND MACHINE LEARNING ALGORITHMS IN NORTH AMERICA

Title of dissertation: ASSIMILATION OF PASSIVE MICROWAVE BRIGHTNESS TEMPERATURES FOR SNOW WATER EQUIVALENT ESTIMATION USING THE NASA CATCHMENT LAND SURFACE MODEL AND MACHINE LEARNING ALGORITHMS IN NORTH AMERICA Yuan Xue, Doctor of Philosophy, 2017 Dissertation directed by: Assistant Professor Barton A. Forman Department of Civil and Environmental Engineering Snow is a critical component in the global energy and hydrologic cycle. It is important to know the mass of snow because it serves as the dominant source of drinking water for more than one billion people worldwide. To accurately estimate the depth of snow and mass of water within a snow pack across regional or continental scales is a challenge, especially in the presence of dense vegetations since direct quantification of SWE is complicated by spatial and temporal variability. To overcome some of the limitations encountered by traditional SWE retrieval algorithms or radiative transfer-based snow emission models, this study explores the use of a welltrained support vector machine to merge an advanced land surface model within a variant of radiance emission (i.e., brightness temperature) assimilation experiments. In general, modest improvements in snow depth, and SWE predictability were witnessed as a result of the assimilation procedure over snow-covered terrain in North America when compared against available snow products as well as ground-based observations. These preliminary findings are encouraging and suggest the potential for global-scale snow estimation via the proposed assimilation procedure.
Simple and Effective Type Check Removal through Lazy Basic Block Versioning

Dynamically typed programming languages such as JavaScript and Python defer type checking to run time. In order to maximize performance, dynamic language VM implementations must attempt to eliminate redundant dynamic type checks. However, type inference analyses are often costly and involve tradeoffs between compilation time and resulting precision. This has lead to the creation of increasingly complex multi-tiered VM architectures. This paper introduces lazy basic block versioning, a simple JIT compilation technique which effectively removes redundant type checks from critical code paths. This novel approach lazily generates type-specialized versions of basic blocks on-the-fly while propagating context-dependent type information. This does not require the use of costly program analyses, is not restricted by the precision limitations of traditional type analyses and avoids the implementation complexity of speculative optimization techniques. We have implemented intraprocedural lazy basic block versioning in a JavaScript JIT compiler. This approach is compared with a classical flow-based type analysis. Lazy basic block versioning performs as well or better on all benchmarks. On average, 71% of type tests are eliminated, yielding speedups of up to 50%. We also show that our implementation generates more efficient machine code than TraceMonkey, a tracing JIT compiler for JavaScript, on several benchmarks. The combination of implementation simplicity, low algorithmic complexity and good run time performance makes basic block versioning attractive for baseline JIT compilers.
Improving Wait Times and Patient Satisfaction in Primary Care

&NA; A strong and inverse relationship between patient satisfaction and wait times in ambulatory care settings has been demonstrated. Despite its relevance to key medical practice outcomes, timeliness of care in primary care settings has not been widely studied. The goal of the quality improvement project described here was to increase patient satisfaction by minimizing wait times using the Dartmouth Microsystem Improvement Curriculum (DMIC) framework and the Plan‐Do‐Study‐Act (PDSA) improvement process. Following completion of an initial PDSA cycle, significant reductions in mean waiting room and exam room wait times (p = .001 and p = .047, respectively) were observed along with a significant increase in patient satisfaction with waiting room wait time (p = .029). The results support the hypothesis that the DMIC framework and the PDSA method can be applied to improve wait times and patient satisfaction among primary care patients. Furthermore, the pretest–posttest preexperimental study design employed provides a model for sequential repetitive tests of change that can lead to meaningful improvements in the delivery of care and practice performance in a variety of ambulatory care settings over time.
Functional analysis of the sialic acid-binding adhesin SfaS of pathogenic Escherichia coli by site-specific mutagenesis

The gene coding for the sialic acid-specific adhesin SfaS produced by the S fimbrial adhesin (sfa) determinant of Escherichia coli has been modified by oligonucleotide-directed, site-specific mutagenesis. Lysine 116, arginine 118, and lysine 122 were replaced by threonine, serine, and threonine, respectively. The mutagenized gene clusters were able to produce S fimbrial adhesin complexes consisting of the S-specific subunit proteins including the adhesin SfaS. The mutant clones were further characterized by hemagglutination and by enzyme-linked immunoassay tests with antifimbria- and anti-adhesin-specific monoclonal antibodies, one of which is able to block S-specific binding (Moch et al., Proc. Natl. Acad. Sci. USA 84:3462-3466, 1987). The lysine-122 mutant clone was indistinguishable from the wild-type clone in these assays. Replacement of lysine 116 and arginine 118, however, abolished hemagglutination and resulted in clones which showed a weak (lysine 116) or a negative (arginine 118) reaction with the antiadhesin-specific antibody A1. We therefore suggest that lysine 116 and arginine 118 have an influence on binding of SfaS to the sialic acid residue of the receptor molecule. Substitution of arginine 118 by serine also had a negative effect on the amount of SfaS adhesin proteins isolated from the S fimbrial adhesin complex.
The increasing inefficiency of private health insurance in Canada

Although most health care in Canada is paid for publicly, private health insurance plays a major supporting role, particularly for prescription drugs, dental services and eye care. [1][1] Expenditures from private insurers totalled $22.7 billion in 2010, accounting for 11.7% of health care spending. [
Electrical substation inspection and intervention robot, field experiments

Aging infrastructures bring major challenges to electric utilities. Despite important resources invested in maintenance and replacement of assets, transmission networks continue to age. Substations day-to-day operations are consequently facing constraints due to personnel safety and security. Asset management is also becoming increasingly challenging. At the same time, recent advances in terrestrial mobile robotics, embedded computing, sensing and robotic manipulation allows for faster integration of subsystems into new robotic systems, at lower costs. Using robots in electrical substations has been studied and demonstrated by some utilities worldwide. Given this context and within a really short timeframe, a team of researchers at IREQ developed and field demonstrated a robot system that allows personnel to remotely accomplish multi-sensor inspections and live operations on numerous substation equipments. Robotic teleoperation therefore alleviates dangerous conditions for personnel and paves the way for valuable systematic inspection of equipments. The video shows various aspects of the system operated within substations.
A CENSUS OF STEINER TRIPLE SYSTEMS AND SOME RELATED COMBINATORIAL OBJECTS

A Steiner triple system of order v (STS(v)) is a set of triples, or blocks, constructed over a set of v points, such that every pair of distinct points occurs in a unique block. Previously, a complete classification of the STS(v) up to isomorphism was known only for v ≤ 15. In this work, we classify by computer search the next open case, v = 19. The classification proceeds in two stages. First, we construct an initial set of 25-block seed configurations. Then, using an algorithm for the exact cover problem, we determine all completions of the seeds to STS(19). Isomorph rejection on the STS(19) is carried out using the graph canonical labelling package nauty supplemented with a vertex invariant based on Pasch configurations. We conclude that there are 11,084,874,829 nonisomorphic STS(19) and study a number of their properties. In particular, the number of anti-Pasch STS(19) is 2,591 and the number of STS(19) with a nontrivial automorphism group is 164,758. We also develop an independent algorithm for classifying STS(19) with a prescribed group of automorphisms. We then use this algorithm to classify the STS(19) with a nontrivial automorphism group. The results obtained in this partial classification match those obtained in the main search. Finally, we show that the main classification algorithm can be used with minor modifications to classify certain related combinatorial structures, such as latin squares and one-factorizations of complete graphs. We estimate the performance of the algorithm in classifying one-factorizations of the complete graph on 12 vertices.
Classifying Very High-Dimensional and Large-Scale Multi-class Image Datasets with Latent-lSVM

We propose a new learning algorithm of latent local support vector machines (SVM), called Latent-lSVM for effectively classifying very-high-dimensional, large-scale multiclass image datasets. The common framework of image classification tasks using the Scale-Invariant Feature Transform method (SIFT), the Bag-of-visual-Words (BoW), leads to hard classification problem with thousands of dimensions, hundreds of classes. Our Latent-lSVM algorithm performs these complex tasks into two main steps. The first one is to use latent Dirichlet allocation (LDA) for assigning the image to some topics (clusters) with the corresponding probabilities. This aim is to reduce the number of classes, the number of datapoints in the cluster compared to the full dataset, followed by the second one: to learn a SVM model for each cluster to non-linearly classify the data locally. The numerical test results on eight real datasets show that the Latent-lSVM algorithm achieves very high accuracy compared to state-of-the-art algorithms. An example of its effectiveness is given with an accuracy of 97.87% obtained in the classification of fingerprint dataset having 5000 dimensions into 559 classes.
Clinical Evaluation of Patients with Spinal Cord Infarction in Mashhad, Iran

Background. Spinal Cord Infarction (SCI) is a rare and disabling disease. This hospital-based study was conducted for clinical evaluation of SCI patients in east of Iran. Methods. Consecutive SCI patients admitted in Ghaem hospital,Mashhad during 2006–2010 were enrolled in a prospective clinical study. Diagnosis of SCI was made by neurologists and radiologists. Demographic features, clinical syndrome, and Magnetic Resonance Imaging (MRI) findings were recorded. All of the patients underwent a standard battery of diagnostic investigations. All of the patients suspected to SCI had MRI of spinal cord at the symptomatic level of cord with a 0.5 Tesla generation, Philips NT Intra, Netherland equipment. An equal number of patients with Brain Infarction (BI) were randomly selected from our stroke registry data bank. Etiology and degree of disability were compared between these groups of patients. Results. Fourteen SCI patients (9 females, 5 males) with mean age 38.8 ± SD: 19.9 years were evaluated. Miscellaneous causes consisted 50% of etiologies in patients with SCI. Uncertain etiology, atherosclerosis, and cardioembolisms consisted 35.7%, 7.1%, and 7.1% of SCI causes, respectively. Distribution of etiologies was significantly different between SCI and BI patients, X 2 = 12.94, df = 3, P = . 003. Difference in mean disability score at acute phase of stroke was not significant between two studied groups, z = 1.54, P = . 057. Difference in mean changes of disability score at 90 days postevent was significant in two groups of patients, z = 2.65, P = . 019. Conclusion. SCI is a rare disease with poor recovery. Distribution of etiologies of SCI patients is quite different than of BI patients.
Obstruction degree: measuring concurrency in shared memory systems

This paper presents the notion of obstruction degree, a new metric for reasoning about the scalability of concurrent algorithms. Essentially, this simple metric gives an indication as to which of two concurrent algorithms is expected to scale better, as well as approximate the maximum number of processors up to which a concurrent algorithm is expected to scale. The scope of the metric is the arguably large class of concurrent algorithms obtained by augmenting sequential algorithms with locks (pessimistic), invalidation primitives (optimistic) or transactional memory. We illustrate the metric through various algorithms and we convey the accuracy of our scalability predictions through extensive experimental measures.
Non-ionizing radiation safety: radiofrequency radiation, electric and magnetic fields

The static, low-frequency and radiofrequency parts of the electromagnetic spectrum are used in various areas of human activity. Equipment utilizing this energy today is to be found in industry, medicine, commerce and private homes. The author provides a short survey of the biological effects and concentrates on the principal experimental and theoretical bases which allow the assessment of data on potential hazards to human health resulting from exposure to electromagnetic fields.