Miracle-dz/UniFAR-FTUs huggingface dataset:
A novel modeling of nonlinear plants with hysteresis described by non-symmetric play operator

A novel modeling of nonlinear plants with hysteresis is proposed. The hysteresis nonlinearity is described by a modified Prandtl-Ishlinskii hysteresis model which is the weighted superposition of non-symmetric play operator. The proposed hysteresis model also facilitates the utilization of robust right coprime factorization. Simulation result is presented to show the feasibility of the proposed hysteresis model.
An On-Chip Trainable and the Clock-Less Spiking Neural Network With 1R Memristive Synapses

Spiking neural networks (SNNs) are being explored in an attempt to mimic brain's capability to learn and recognize at low power. Crossbar architecture with highly scalable resistive RAM or RRAM array serving as synaptic weights and neuronal drivers in the periphery is an attractive option for the SNN. Recognition (akin to “reading” the synaptic weight) requires small amplitude bias applied across the RRAM to minimize conductance change. Learning (akin to “writing” or updating the synaptic weight) requires large amplitude bias pulses to produce a conductance change. The contradictory bias amplitude requirement to perform reading and writing simultaneously and asynchronously, akin to biology, is a major challenge. Solutions suggested in the literature rely on time-division-multiplexing of read and write operations based on clocks, or approximations ignoring the reading when coincidental with writing. In this paper, we overcome this challenge and present a clock-less approach wherein reading and writing are performed in different frequency domains. This enables learning and recognition simultaneously on an SNN. We validate our scheme in SPICE circuit simulator by translating a two-layered feed-forward Iris classifying SNN to demonstrate software-equivalent performance. The system performance is not adversely affected by a voltage dependence of conductance in realistic RRAMs, despite departing from linearity. Overall, our approach enables direct implementation of biological SNN algorithms in hardware.
Allgemeine Intelligenz und beruflicher Erfolg in Deutschland

Zusammenfassung. Die Zusammenhange von Intelligenz (general mental ability, GMA) mit den Karriereerfolgsindikatoren Einkommen und berufliche Entwicklung werden erstmals anhand von Studien aus Deutschland spezifiziert. Daruber hinaus stellen die vorliegenden Metaanalysen Updates fruherer Analysen dar, die die Validitat von GMA in Bezug auf subjektiv bewertete Arbeitsleistung und berufsbezogene Lernleistung in Deutschland untersucht haben. Die Anzahl der inkludierten Studien zu beiden Leistungsbereichen konnte mehr als verdoppelt werden. Die vorliegenden Analysen werden nach der Methode von Hunter und Schmidt (2004) vorgenommen. Methodische Neuerungen sind die Berucksichtigung insignifikanter nicht berichteter Korrelationen mit Hilfe eines Substitutionsverfahrens und die indirekte Korrektur der Varianzeinschrankung im Pradiktor. Dadurch werden akkuratere Schatzungen der Validitat von GMA im Hinblick auf die zwei Leistungsbereiche ermoglicht. Die Ergebnisse zur operationalen Validitat von GMA in Bezug auf su.
Comprehension difficulties after year 4: Actioning appropriately

Abstract Many children identified with average intelligence exhibit ongoing reading comprehension difficulties after Year 4. They typically have language delays that are possibly due to their disengagement with reading and they do not process information efficiently in working memory. As a consequence they do not adequately learn from their encounters with print and they develop a reluctance to use appropriate self‐monitoring strategies. Many intervention programs have a limited focus by concentrating on word level processes but these may be largely inappropriate for older children with reading comprehension difficulties. What may be more suitable is the use of scaffolding techniques that promote cognitive and motivational engagement in a rich personalised language environment. The article investigates the problems experienced by such children and suggests some appropriate text processing and reorganisation strategies that can be applied to teaching practice.
Rank-One and Transformed Sparse Decomposition for Dynamic Cardiac MRI

It is challenging and inspiring for us to achieve high spatiotemporal resolutions in dynamic cardiac magnetic resonance imaging (MRI). In this paper, we introduce two novel models and algorithms to reconstruct dynamic cardiac MRI data from under-sampled k − t space data. In contrast to classical low-rank and sparse model, we use rank-one and transformed sparse model to exploit the correlations in the dataset. In addition, we propose projected alternative direction method (PADM) and alternative hard thresholding method (AHTM) to solve our proposed models. Numerical experiments of cardiac perfusion and cardiac cine MRI data demonstrate improvement in performance.
Cardiac Pathology and Molecular Epidemiology by Avian Leukosis Viruses in Japan

Epidemiological studies suggest that retroviruses, including human immunodeficiency virus type 1, are associated with cardiomyopathy and myocarditis, but a causal relationship remains to be established. We encountered unusual cardiomyocyte hypertrophy and mitosis in Japanese native fowls infected with subgroup A of the avian leukosis viruses (ALVs-A), which belong to the genus Alpharetrovirus of the family Retroviridae and mainly induce lymphoid neoplasm in chickens. The affected hearts were evaluated by histopathology and immunohistochemistry, viral isolation, viral genome sequencing and experimental infection. There was non-suppurative myocarditis in eighteen fowls and seven of them had abnormal cardiomyocytes, which were distributed predominantly in the left ventricular wall and showed hypertrophic cytoplasm and atypical large nuclei. Nuclear chains and mitosis were frequently noted in these cardiomyocytes and immunohistochemistry for proliferating cell nuclear antigen supported the enhancement of mitotic activity. ALVs were isolated from all affected cases and phylogenic analysis of envSU genes showed that the isolates were mainly classified into two different clusters, suggesting viral genome diversity. In ovo experimental infection with two of the isolates was demonstrated to cause myocarditis and cardiomyocyte hypertrophy similar to those in the naturally occurring lesions and cardiac hamartoma (rhabdomyoma) in a shorter period of time (at 70 days of age) than expected. These results indicate that ALVs cause myocarditis as well as cardiomyocyte abnormality in chickens, implying a pathogenetic mechanism different from insertional mutagenesis and the existence of retrovirus-induced heart disorder.
Lipoic acid in secondary progressive MS

Objective: To determine whether lipoic acid (LA), an endogenously produced antioxidant, slowed the whole-brain atrophy rate and was safe in secondary progressive MS (SPMS). Methods: Patients with SPMS aged 40–70 years enrolled in a single center, 2-year, double-blind, randomized trial of daily oral 1,200 mg LA vs placebo. Primary outcome was change in annualized percent change brain volume (PCBV). Secondary outcomes were changes in rates of atrophy of segmented brain, spinal cord, and retinal substructures, disability, quality of life, and safety. Intention-to-treat analysis used linear mixed models. Results: Participation occurred between May 2, 2011, and August 14, 2015. Study arms of LA (n = 27) and placebo (n = 24) were matched with mean age of 58.5 (SD 5.9) years, 61% women, mean disease duration of 29.6 (SD 9.5) years, and median Expanded Disability Status Score of 6.0 (interquartile range 1.75). After 2 years, the annualized PCBV was significantly less in the LA arm compared with placebo (−0.21 [standard error of the coefficient estimate (SEE) 0.14] vs −0.65 [SEE 0.10], 95% confidence interval [CI] 0.157–0.727, p = 0.002). Improved Timed 25-Foot Walk was almost but not significantly better in the LA than in the control group (−0.535 [SEE 0.358] vs 0.137 [SEE 0.247], 95% CI −1.37 to 0.03, p = 0.06). Significantly more gastrointestinal upset and fewer falls occurred in LA patients. Unexpected renal failure (n = 1) and glomerulonephritis (n = 1) occurred in the LA cohort. Compliance, measured by pill counts, was 87%. Conclusions: LA demonstrated a 68% reduction in annualized PCBV and suggested a clinical benefit in SPMS while maintaining favorable safety, tolerability, and compliance over 2 years. ClinicalTrials.gov identifier: NCT01188811. Classification of evidence: This study provides Class I evidence that for patients with SPMS, LA reduces the rate of brain atrophy.
Fetal Alcohol Spectrum Disorder: An Overview

There has been an increase in awareness of fetal alcohol spectrum disorders in both the lay and academic press of late. However, evidence from national, regional and local conferences as well as a pilot survey of awareness (unpublished data) suggests they remain a set of conditions that are poorly understood in the UK both by the general public and health practitioners. This is despite the conditions being relevant to specialties as diverse as obstetrics, paediatrics, general practice, neurology, public health and psychiatry. This article provides an overview to inform medical practitioners of important aspects related to their practice.
Demonstration of a B-lymphocyte mitogen produced by the Lyme disease pathogen, Borrelia burgdorferi

Lyme disease refers to the multisymptomatic illness in humans which results from infection with the tick-borne spirochete Borrelia burgdorferi. The white-footed mouse is the major reservoir for B. burgdorferi and, upon infection, certain inbred mice develop symptoms similar to those reported in human disease. Sonicated preparations of washed spirochetes were found to have potent mitogenic activity when cultured with lymphocytes from naive C57BL/6, C3H/HeJ, or BALB/c mice. The activity of the B. burgdorferi sonicate was approximately fourfold greater than that of a similarly prepared Escherichia coli sonicate. Polymyxin B efficiently inhibited the mitogenic activity of the E. coli sonicate but only slightly inhibited that of the B. burgdorferi sonicate, suggesting that a lipid A-containing lipopolysaccharide was not responsible for the B. burgdorferi activity. Kinetic analysis indicated peak proliferation at 2 to 3 days of culturing, suggesting polyclonal activation. B- and T-lymphocyte depletion experiments indicated that the major cell type responding to the B. burgdorferi mitogen was the B lymphocyte. This mitogen stimulated murine B cells not only to proliferate but also to differentiate into antibody-secreting cells, as demonstrated by the production of immunoglobulin by stimulated splenocytes. Furthermore, the sonicated preparation stimulated the B-cell tumor line CH12.LX to secrete immunoglobulin in the absence of accessory cells. B. burgdorferi also stimulated interleukin-6 production in splenocyte cultures. The observation that B. burgdorferi can stimulate activation of and immunoglobulin production by normal B lymphocytes may directly reflect on the development of arthritis associated with persistent infection by this organism.
A Novel Cluster Head Selection Method for Energy Efficient Wireless Sensor Network

In the development of wireless sensor networks (WSNs) applications, organizing sensor nodes into a communication network and route the sensed data from sensor nodes to a remote sink is a challenging task. Energy efficient and reliable routing of data from the source to destination with minimal power consumption remains as a core research problem. So, in WSN we need an efficient protocol to route any transmitted data with extended lifetime of network. In this paper, we propose a novel clustering algorithm, Front-Leading Energy Efficient Cluster Heads (FLEECH), in which the whole network is partitioned into regions with diminishing sizes. In each region, we form multiple clusters. The selection of the Cluster Head (CH) is based on residual energy and distance of each node to the sink as its parameter. Simulation results show that our proposed model FLEECH outperforms Low Energy Adaptive Clustering Hierarchy (LEACH) with respect to energy consumption and extension of network life time.
The uncharged surface features surrounding the active site of Escherichia coli DsbA are conserved and are implicated in peptide binding

DsbA is a protein‐folding catalyst from the periplasm of Escherichia coli that interacts with newly translocated polypeptide substrate and catalyzes the formation of disulfide bonds in these secreted proteins. The precise nature of the interaction between DsbA and unfolded substrate is not known. Here, we give a detailed analysis of the DsbA crystal structure, now refined to 1.7 Å, and present a proposal for its interaction with peptide.
A New Transducer for Magnetic Induction Tomography

In this paper we compare results of calculations and measurements made for different objects being tested with magnetic induction tomography system developed and constructed at the West Pomeranian University of Technology, Szczecin, Poland. The forward problem, i.e., determining induced currents in the object and their magnetic fields, is formulated. The finite element method (FEM) is employed to find the scalar potential distribution inside the object under test. An analytical solution is derived for homogeneous conductive cylindrical objects in order to test FEM solutions.
A High-Order Projection Method for Tracking Fluid Interfaces in Variable Density Incompressible Flows

We present a numerical method for computing solutions of the incompressible Euler or Navier? Stokes equations when a principal feature of the flow is the presence of an interface between two fluids with different fluid properties. The method is based on a second-order projection method for variable density flows using an “approximate projection” formulation. The boundary between the fluids is tracked with a second-order, volume-of-fluid interface tracking algorithm. We present results for viscious Rayleigh? Taylor problems at early time with equal and unequal viscosities to demonstrate the convergence of the algorithm. We also present computational results for the Rayleigh? Taylor instability in air-helium and for bubbles and drops in an air? water system without surface tension to demonstrate the behavior of the algorithm on problems with large density and viscosity contrasts.
The mastery of movement

By searching the title, publisher, or authors of guide you essentially want, you can discover them rapidly. In the house, workplace, or perhaps in your method can be every best area within net connections. If you ambition to download and install the the mastery of movement, it is no question easy then, back currently we extend the associate to purchase and create bargains to download and install the mastery of movement hence simple!
User Simulation for Spoken Dialogue

We propose the “advanced” n-grams as a new technique for simulating user behaviour in spoken dialogue systems, and we compare it with two methods used in our prior work, i.e. linear feature combination and “normal” n-grams. All methods operate on the intention level and can incorporate speech recognition and understanding errors. In the linear feature combination model user actions (lists of 〈 speech act, task 〉 pairs) are selected, based on features of the current dialogue state which encodes the whole history of the dialogue. The user simulation based on “normal” n-grams treats a dialogue as a sequence of lists of 〈 speech act, task 〉 pairs. Here the length of the history considered is restricted by the order of the n-gram. The “advanced” n-grams are a variation of the normal ngrams, where user actions are conditioned not only on speech acts and tasks but also on the current status of the tasks, i.e. whether the information needed by the application (in our case flight booking) has been provided and confirmed by the user. This captures elements of goal-directed user behaviour. All models were trained and evaluated on the COMMUNICATOR corpus, to which we added annotations for user actions and dialogue context. We then evaluate how closely the synthetic responses resemble the real user responses by comparing the user response generated by each user simulation model in a given dialogue context (taken from the annotated corpus) with the actual user response. We propose the expected accuracy, expected precision, and expected recall evaluation metrics as opposed to standard precision and recall used in prior work. We also discuss why they are more appropriate metrics for evaluating user simulation models compared to their standard counterparts. The advanced n-grams produce higher scores than the normal n-grams for small values of n, which proves their strength when little amount of data is available to train larger ngrams. The linear model produces the best expected accuracy but with respect to expected precision and expected recall it is outperformed by the large n-grams even though it is trained using more information. As a task-based evaluation, we also run each of the user simulation models against a system policy trained on the same corpus. Here the linear feature combination model outperforms the other methods and the advanced n-grams outperform the normal ngrams for all values of n, which again shows their potential. We also calculate the perplexity of the different user models.
A Model to Explain the Emergence of Imitation Development Based on Predictability Preference

Imitation is a very complicated function which requires a body mapping (a mapping from observed body motions to motor commands) that can discriminate between self motions and those of others. The developmental mechanism of this sophisticated capability, and the order in which the required abilities arise, is poorly understood. In this paper, we present a mechanism for the development of imitation through a simulation of infant-caregiver interaction. A model was created to acquire a body mapping, which is necessary for successful mutual imitation in infant-caregiver interaction, while discriminating self-motion from the motion of the other. The ability to predict motions and the time delay between performing a motion and observing any correlated motion provides clues to assist the development of the body mapping. The simulation results show that the development of imitation capabilities depends on a predictability preference (a function of how an agent feels regarding its options of “what to imitate,” given its ability to predict motions). In addition, the simulated infants in our system are able to develop the components of a healthy body mapping in order, that is, relating self motion first, followed by an understanding of others' motions. This order of development emerges spontaneously without the need for any explicit mechanism or any partitioning of the interaction. These results suggest that this predictability preference is an important factor in infant development.
Oblivious Secure Deletion with Bounded History Independence

We present a new secure cloud storage mechanism that combines three previously disjoint security properties: obliviousness, secure deletion, and history independence. The system maintains strong privacy guarantees against a cloudobservation attack, wherein an attacker learns all previous states of, and accesses to, the persistent cloud storage, as well as a catastrophic attack, where the decryption keys from erasable memory are also leaked. In the first scenario, the access pattern reveals nothing about the contents (obliviousness), and in both scenarios, no previously deleted data is recoverable (secure deletion), and the structure of the data leaks a bounded amount of information about previous states (history independence). To achieve these goals we developed a new oblivious-RAM with variable-size storage blocks (vORAM) and a new history independent, randomized data structure based on B-trees (HIRB tree) stored within the vORAM. We prove that the vORAM+HIRB achieves obliviousness and secure deletion. We also show that any such system must inevitably leak a bounded amount of history information, and prove that our vORAM+HIRB construction matches this lower bound, up to logarithmic factors. Our system also provides better utilization of the ORAM buckets and reduces the amount of local storage requirements by O(logn) as compared to prior work for storing map data structures. Finally, we have implemented and measured the performance of our system using Amazon Web Services for a sample password-management application that maintains the privacy of login records, addition and removal of accounts, and password changes. The empirical performance is comparable to current state of the art in ORAM technologies and greatly outperforms naive approaches that provide the same security properties.
Effectiveness of a Metacognitive Reading Strategies Program for Improving Low Achieving EFL Readers.

As the training of language learners was a main concern of EFL teachers, this study aimed to assess the effectiveness of metacognitive reading strategies instruction (MRSI) on Taif University EFL students who achieved low results in reading. The final sample of this study was (21) female university students. The sample was divided into two groups; the experimental group, which consisted of (10) girls, and the control group, which consisted of (11) girls. By using the quasi experimental-research methodology, three research objectives were addressed in this study: (a) to examine whether there were significant differences between the experimental group and the control group on the employment of metacognitive reading strategies and reading comprehension post-tests): (b) to explore whether there were significant differences between the mean scores of pre- and post-tests on the English Language reading test: (c) to find out whether there were any significant differences between the mean scores of the post-test and the follow up of the use of metacognitive reading strategies and the English Language reading comprehension test given to the experimental group. Data from pre- and post-test measurements were used to investigate the impact the intervention had on EFL low achievers in reading. Statistical analyses of the data showed that there were statistically significant differences between the experimental group and the control group on the post-test reading comprehension test as well as the reading strategies questionnaire. These showed a significant improvement in the reading skill in the experimental group. They also revealed that there were statistically significant differences between the pre-test and post-test results for the experimental group on the reading comprehension test and the reading strategies. This showed that the experimental group improved in reading skills after the students participated in the program, as seen on the post-test. In the light of these results, the study provided a number of procedural recommendations that may contribute to raising the importance of metacognitive reading strategies training for the students with low achievement in reading.