Miracle-dz/UniFAR-FTUs huggingface dataset:
SDL - with applications from protocol specification

Part 1 Introduction: application area the benefits of a specification language the use of a specification language about this book. Part 2 Overview of the language: specification, type and instance system instance behaviour system instance structure system specification structure abstract data type representation forms. Part 3 Basic SDL: hierarchical specifications system specification block specification process specification extended processes (using data) process communication creating and terminating processes other SDL process concepts comment shorthands a complete SDL example. Part 4 Structural concepts: channel partitioning procedure service signal refinement. Part 5 Additional concepts: macro option signal list declaration label and join continuous signal enabling condition import/export viewing variables nondeterminism. Part 6 General lexical and syntax rules: lexical rules visibility and naming rules. Part 7 Abstract data types: partial type specifications conditional equations error inheritance generators infix operators ordering name class literal default assignment predefined sorts predefined generators. Part 8 Interpretation model: interpretation of a system specification interaction with the environment dynamic semantics. Part 9 Protocol specification with SDL: the OSI basic reference model basic approach - the vertical view of protocols alternative approach - the horizontal view of protocols the inres system generic OSI specifications.
Discovering multilingual concepts from unaligned web documents by exploring associated images

The Internet is experiencing an explosion of information presented in different languages. Though written in different languages, some articles implicitly share common concepts. In this paper, we propose a novel framework to mine cross-language common concepts from unaligned web documents. Specifically, visual words of images are used to bridge articles in different languages and then common concepts of multiple languages are learned by using an existing topic modeling algorithm. We conduct cross-lingual text classification in a real-world data set using the mined multilingual concepts from our method. The experiment results show that our approach is effective to mine cross-lingual common concepts.
Cerebral Oxygen Delivery and Consumption During Evoked Neural Activity

Increases in neural activity evoke increases in the delivery and consumption of oxygen. Beyond observations of cerebral tissue and blood oxygen, the role and properties of cerebral oxygen delivery and consumption during changes in brain function are not well understood. This work overviews the current knowledge of functional oxygen delivery and consumption and introduces recent and preliminary findings to explore the mechanisms by which oxygen is delivered to tissue as well as the temporal dynamics of oxygen metabolism. Vascular oxygen tension measurements have shown that a relatively large amount of oxygen exits pial arterioles prior to capillaries. Additionally, increases in cerebral blood flow (CBF) induced by evoked neural activation are accompanied by arterial vasodilation and also by increases in arteriolar oxygenation. This increase contributes not only to the down-stream delivery of oxygen to tissue, but also to delivery of additional oxygen to extra-vascular spaces surrounding the arterioles. On the other hand, the changes in tissue oxygen tension due to functional increases in oxygen consumption have been investigated using a method to suppress the evoked CBF response. The functional decreases in tissue oxygen tension induced by increases in oxygen consumption are slow to evoked changes in CBF under control conditions. Preliminary findings obtained using flavoprotein autofluorescence imaging suggest cellular oxidative metabolism changes at a faster rate than the average changes in tissue oxygen. These issues are important in the determination of the dynamic changes in tissue oxygen metabolism from hemoglobin-based imaging techniques such as blood oxygenation-level dependent functional magnetic resonance imaging (fMRI).
General sound classification and similarity in MPEG-7

We introduce a system for generalised sound classification and similarity using a machine-learning framework. Applications of the system include automatic classification of environmental sounds, musical instruments, music genre and human speakers. In addition to classification, the system may also be used for computing similarity metrics between a target sound and other sounds in a database. We discuss the use of hidden Markov models for representing the temporal evolution of audio spectra and present results of testing the system on classification and retrieval tasks. The system has been incorporated into the MPEG-7 international standard for multimedia content description and is therefore publicly available in the form of a set of standardised interfaces and software reference tools for developers and researchers.
Application of compression after the detection of endometrial carcinoma imaging: Future scopes

Medical Imaging is an important keystone of modem healthcare and will continue to play a role of ever increasing importance at all levels of the healthcare system due to advances in imaging technology (US, CT, MR and Molecular Imaging). Due to this big data of medical images, compression is required to achieve efficient transmission and storage. The proposed procedure is applied to diverse ultrasound cancerous images (endometrial cancer). Hence diagnosis of this type of uterus cancer in the premier stage is crucial, certain segmentation algorithms are applied and these will separate the infected region from the background which will be easy for the medical practitioners to decide the cancer and steer medication. The ultrasound image which is developed from an organ is preprocessed and the filtered image is given to level set segmentation and finally the contextual part of the image is encoded using wavelet decomposition.
Study of ultra-precision polishing of electroless nickel molding dies

Electroless nickel is an excellent material for making optical molding dies, because of its machinability with both single-point diamond turning and polishing, as well as its suitable hardness and durability. This paper deals with the ultra-precision polishing of molding dies for telescope mirrors with a super smooth surface with a roughness below 1 nm root-mean- square (rms). According to the probability density distribution function of different sizes of abrasive grains cut into the workpiece, a surface roughness model combining the micro contact model and the force balance principle was established. A surface roughness of 0.316 nm Ra was obtained on slab molding dies of 30 mm in diameter.
Financial Markets Analysis by Probabilistic Fuzzy Modelling

For successful trading in financial markets, it is important to develop financial models where one can identify different states of the market for modifying one? s actions. In this paper, we propose to use probabilistic fuzzy systems for this purpose. We concentrate on Takagi? Sugeno (TS) probabilistic fuzzy systems that combine interpretability of fuzzy systems with the statistical properties of probabilistic systems. We start by recapitulating the general architecture of TS probabilistic fuzzy rule-based systems and summarize the corresponding reasoning schemes. We mention how probabilities can be estimated from a given data set and how a probability distribution can be approximated by a fuzzy histogram. We apply our methodology for financial time series analysis and demonstrate how a probabilistic TS fuzzy system can be identified, assuming that a linguistic term set is given. We illustrate the interpretability of such a system by inspecting the rule bases of our models.
Dealing with Emphatic Consonants to Improve the Performance of Arabic Speech Recognition

The Arabic language presents a number of challenges for speech recognition, due in part to the presence of some unique phonemes in its phonetic system. In this paper, we are concerned with developing a speaker-independent isolated word Automatic Speech Recognition (ASR) system that can deal with the unique emphatic consonants of the Arabic language. This system is based on the Hidden Markov Models (HMMs) and is designed using the Hidden Markov Model Toolkit (HTK). The database used for both training and testing consists of 3200 tokens in total, created with the help of 20 Arabic native speakers. For the best use of data, the research uses 5 fold cross-validation in order to improve the robustness of the testing. The experimental results shows that the overall system performance was 22.6% when using the word as an acoustic unit in modelling the speech, which confirms that these Arabic unique consonants are a major source of difficulty in developing Arabic ASR systems. Furthermore, the research finds that by using the phonemes as the acoustic model the accuracy rate can be improved to 61.4%. The research presents a novel approach for confusability reduction which uses underspecified phonetic transcription for the input speech. The presented technique reported overall system error reduction rates by 23% compared to the baseline system. The research suggests that using this system in language learning is particularly helpful to non-native speakers for correctly producing the required sounds of the language.
Chemical vapour deposition synthetic diamond: materials, technology and applications

Substantial developments have been achieved in the synthesis of chemical vapour deposition (CVD) diamond in recent years, providing engineers and designers with access to a large range of new diamond materials. CVD diamond has a number of outstanding material properties that can enable exceptional performance in applications as diverse as medical diagnostics, water treatment, radiation detection, high power electronics, consumer audio, magnetometry and novel lasers. Often the material is synthesized in planar form; however, non-planar geometries are also possible and enable a number of key applications. This paper reviews the material properties and characteristics of single crystal and polycrystalline CVD diamond, and how these can be utilized, focusing particularly on optics, electronics and electrochemistry. It also summarizes how CVD diamond can be tailored for specific applications, on the basis of the ability to synthesize a consistent and engineered high performance product.
Plasma-treated Ce/TiO2–SiO2 catalyst for the NH3-SCR of NOx

ABSTRACT Ce/TiO2–SiO2 catalysts with different Ti/Si molar ratios are prepared by the incipient impregnation method and their NH3-SCR activities are evaluated at 100–500°C on a fixed reactor. The Ce/TiO2–SiO2 (3/1) catalyst, modified by non-thermal plasma (NTP) treatment and then activated by thermal treatment at 500°C for 4 h, exhibits best performance. Comprehensive deNOx performance of the catalyst is evidently improved and its efficiency reaches up to 99.21% at 350°C. NO conversion efficiency of the treated catalyst doped with K remains about 90.23% at 300°C and the catalyst also shows improved activity at lower temperatures. Various characterization methods show that the activity enhancement is correlated only with NTP treatment, as it increases the number of Ce3+ species, which generates more chemisorbed oxygen, leads to improved dispersion of Brønsted and Lewis acidic sites and finally has an inherent etching effect.
Characterizing the evolution of genetic variance using genetic covariance tensors

Determining how genetic variance changes under selection in natural populations has proved to be a very resilient problem in evolutionary genetics. In the same way that understanding the availability of genetic variance within populations requires the simultaneous consideration of genetic variance in sets of functionally related traits, determining how genetic variance changes under selection in natural populations will require ascertaining how genetic variance–covariance (G) matrices evolve. Here, we develop a geometric framework using higher-order tensors, which enables the empirical characterization of how G matrices have diverged among populations. We then show how divergence among populations in genetic covariance structure can then be associated with divergence in selection acting on those traits using key equations from evolutionary theory. Using estimates of G matrices of eight male sexually selected traits from nine geographical populations of Drosophila serrata, we show that much of the divergence in genetic variance occurred in a single trait combination, a conclusion that could not have been reached by examining variation among the individual elements of the nine G matrices. Divergence in G was primarily in the direction of the major axes of genetic variance within populations, suggesting that genetic drift may be a major cause of divergence in genetic variance among these populations.
Quantifying antiepileptic drug effects using intrinsic excitability measures

Pathologic increases in excitability levels of cortical tissue commonly underlie the initiation and spread of seizure activity in patients with epilepsy. By reducing the excitability levels in neural tissue, antiepileptic drug (AED) pharmacotherapy aims to reduce seizure severity and frequency. However, AEDs may also bring about adverse effects, which have been reported to increase with higher AED load. Measures that monitor the dose‐dependent effects of AEDs on cortical tissue and quantify its excitability level are therefore of prime importance for efficient clinical care and treatment but have been difficult to identify. Here, we systematically analyze continuous multiday electrocorticography (ECoG) data from 10 patients under different levels of AED load and derive the recently proposed intrinsic excitability measures (IEMs) from different brain regions and across different frequency bands. We find that IEMs are significantly negatively correlated with AED load (prescribed daily dose/defined daily dose). Furthermore, we demonstrate that IEMs derived from different brain regions can robustly capture global changes in the degree of excitability. These results provide a step toward the ultimate goal of developing a reliable quantitative measure of central physiologic effects of AEDs in patients with epilepsy.
Long-term effects of ranirestat (AS-3201) on peripheral nerve function in patients with diabetic sensorimotor polyneuropathy.

OBJECTIVES We aimed to determine whether ranirestat, an aldose reductase inhibitor, maintains the improved nerve function observed in patients with diabetic sensorimotor polyneuropathy (DSP) after completing a 12-week nerve biopsy study. RESEARCH DESIGN AND METHODS Patients with mild to moderate DSP, as determined by the presence of sural nerve responses, were enrolled in a double-blind, placebo-controlled biopsy trial and randomized to placebo or 5 or 20 mg/day ranirestat for 12 weeks. Patients completing this biopsy study were offered a 48-week extension at the same ranirestat dose or at 5 mg/day ranirestat if they were originally treated with placebo. Electrophysiological tests, the Toronto Clinical Neuropathy Score, and vibration perception thresholds (VPTs) were performed at entry and at 12 (end of the biopsy study) and 60 (end of the 48-week extension) weeks. RESULTS Peroneal motor nerve conduction velocity (NCV) improved in the 20-mg/day group following 60 weeks of treatment. Sural and median sensory NCV improved after both 12 and 60 weeks of treatment with 20 mg/day. VPT improved after 60 weeks of treatment with 20 mg/day. Ranirestat was well tolerated with no difference in adverse events between the 5- and 20-mg/day groups. CONCLUSIONS Twenty milligrams ranirestat per day improves NCV and VPT following 60 weeks of administration. The improved sensory nerve function observed after 12 weeks of therapy was maintained at 60 weeks, and improved motor nerve function was observed at 60 weeks.
The use of Doppler tissue imaging to predict cellular and antibody‐mediated rejection in pediatric heart transplant recipients

Abstract: DTI indices have been associated with cellular rejection in adult heart transplant recipients, but their predictive value in pediatric recipients is unknown. The purpose of this study was to evaluate DTI measures in the detection of cellular and AMR in pediatric heart transplant recipients. One hundred and forty‐eight pediatric heart transplant recipients who had 267 cardiac catheterization procedures with EMB, echocardiogram with DTI, and BNP level performed on the same day were included in the study. For the mitral and tricuspid valves, the ratios (E/E’) between the early diastolic inflow velocity by pulsed Doppler (E, m/s) and the early diastolic annular velocity by DTI (E’, m/s) were obtained and compared between subjects with and without rejection. Of the 148 recipients, 30 subjects had a total of 37 episodes of rejection: 10 cellular (≥1B), 17 AMR, and 10 biopsy‐negative clinical rejection. Mitral and tricuspid valve E/E’ ratios were significantly higher in rejectors than in non‐rejectors (5.5 ± 1.3 vs. 4.4 ± 1.4, p < 0.001 and 4.9 ± 2.1 vs. 4.1 ± 1.5, p < 0.01, respectively). By multivariate linear regression, mitral valve E/E’ was an independent predictor of rejection. Mitral and tricuspid valve E/E’ <5.0 had 93% and 89% NPV, respectively, for rejection. Mitral and tricuspid valve E/E’ ratios <5.0 may be useful non‐invasive screening measures to exclude rejection in pediatric heart transplant recipients.
Efficient Low-Cost Materials for Solar Energy Applications: Roles of Nanotechnology

The generation of energy to meet the increasing global demand should not compro- mise the environment and the future. Therefore, renewable energies have been identified as potential alternatives to fossil fuels that are associated with CO 2 emissions. Subsequently, photovoltaic (PV) solar system is seen as the most versatile and the larg-est source of electricity for the future globally. Nanotechnology is a facilitating tool that offers a wide range of resources to resolve material challenges in different application areas. This studies X-rays, energy trilemma, potential nanotechnology-based materials for low-cost PV solar cell fabrication, and atomic layer deposition (ALD). In pursu-ance of improved performance, PV solar-cell technologies have revolutionized from first-generation PV solar cells to third-generation PV solar cells. The efficiency (19%) of second-generation PV cells is higher than the efficiency (15%) of first-generation cells. The second-generation PV cell technologies include a-Si, CdTe and Cu(In,Ga)Se 2 ), Cu(In,Ga)Se 2 (CIGS) cells. The third-generation PV cells are organic-inorganic hybrid assemblies, nanostructured semiconductors, and molecular assemblies. This nanocom-posite-based technology aims at developing low-cost high efficiency PV solar cells. The nanotechnology manufacturing technique, ALD, is seen as the future technology of PV solar cell production.
Once-daily NVA237 improves exercise tolerance from the first dose in patients with COPD: the GLOW3 trial

Introduction Exercise limitation, dynamic hyperinflation, and exertional dyspnea are key features of symptomatic chronic obstructive pulmonary disease (COPD). We assessed the effects of glycopyrronium bromide (NVA237), a once-daily, long-acting muscarinic antagonist, on exercise tolerance in patients with moderate to severe COPD. Methods Patients were randomized to a cross-over design of once-daily NVA237 50 μg or placebo for 3 weeks, with a 14-day washout. Exercise endurance, inspiratory capacity (IC) during exercise, IC and expiratory volumes from spirometry, plethysmographic lung volumes, leg discomfort and dyspnea under exercise (Borg scales), and transition dyspnea index were measured on Days 1 and 21 of treatment. The primary endpoint was endurance time during a submaximal constant-load cycle ergometry test on Day 21. Results A total of 108 patients were randomized to different treatment groups (mean age, 60.5 years; mean post-bronchodilator, forced expiratory volume in 1 second [FEV1] 57.1% predicted). Ninety-five patients completed the study. On Day 21, a 21% difference in endurance time was observed between patients treated with NVA237 and those treated with placebo (P < 0.001); the effect was also significant from Day 1, with an increase of 10%. Dynamic IC at exercise isotime and trough FEV1 showed significant and clinically relevant improvements from Day 1 of treatment that were maintained throughout the study. This was accompanied by inverse decreases in residual volume and functional residual capacity. NVA237 was superior to placebo (P < 0.05) in decreasing leg discomfort (Borg CR10 scale) on Day 21 and exertional dyspnea on Days 1 and 21 (transition dyspnea index and Borg CR10 scale at isotime). The safety profile of NVA237 was similar to that of the placebo. Conclusion NVA237 50 μg once daily produced immediate and significant improvement in exercise tolerance from Day 1. This was accompanied by sustained reductions in lung hyperinflation (indicated by sustained and significant improvements in IC at isotime), and meaningful improvements in trough FEV1 and dyspnea. Improvements in exercise endurance increased over time, suggesting that mechanisms beyond improved lung function may be involved in enhanced exercise tolerance. (ClinicalTrials.gov Identifier: NCT01154127).
Design, Fabrication, and Characterization of Novel Optoelectronic Devices for Near-infrared Detection

Investigating semiconductor materials and devices at the nanoscale has become crucial in order to maintain the exponential development in today’s technology. There is a critical need for making devices lower in power consumption and smaller in size. Nanoscale semiconductor materials provide a powerful platform for optoelectronic device engineers. They own interesting properties which include enhanced photoconductivity and size-tunable interband transitions. In this research, different types of nanostructures were investigated for optoelectronic devices: nanocrystals, nanowires, and thin-films. First, lead selenide nanocrystals with narrow bandgap were synthesized, size-tailored, and functionalized with molecular ligands for the application of uncooled near-infrared photodetectors. The devices showed strong roomtemperature responsivity that is covering the entire near-infrared spectral region. In the second investigation self-powered devices based on asymmetric Schottky contacts were designed and fabricated to efficiently detect near-infrared radiations without external biasing. The dimensions and the type of the metal contacts were optimized in order to improve on the device performance. Then silicon nanowires were integrated with the asymmetric contacts to further enhance the performance of the self-powered detectors by increasing the light absorption. Third, an array of gold thin-films was designed to enhance the photocurrent in the near-infrared through the internal photoemission of hot electrons. The photocurrent enhancement was studied as function of thickness and type of the metal thin-film. Overall, those investigations provided important design considerations for future optoelectronic devices based on nanostructures. Moreover, the implementation of nanostructures with the devices showed superior performance as compared to the bulk. © 2018 by Ahmad Nusir All Rights Reserved