Miracle-dz/UniFAR-FTUs huggingface dataset:
Noninvasive Strategies to Promote Functional Recovery after Stroke

Stroke is a common and disabling global health-care problem, which is the third most common cause of death and one of the main causes of acquired adult disability in many countries. Rehabilitation interventions are a major component of patient care. In the last few years, brain stimulation, mirror therapy, action observation, or mental practice with motor imagery has emerged as interesting options as add-on interventions to standard physical therapies. The neural bases for poststroke recovery rely on the concept of plasticity, namely, the ability of central nervous system cells to modify their structure and function in response to external stimuli. In this review, we will discuss recent noninvasive strategies employed to enhance functional recovery in stroke patients and we will provide an overview of neural plastic events associated with rehabilitation in preclinical models of stroke.
Involvement of Per-Arnt-Sim Kinase and Extracellular-Regulated Kinases-1/2 in Palmitate Inhibition of Insulin Gene Expression in Pancreatic β-Cells

OBJECTIVE Prolonged exposure of pancreatic β-cells to simultaneously elevated levels of fatty acids and glucose (glucolipotoxicity) impairs insulin gene transcription. However, the intracellular signaling pathways mediating these effects are mostly unknown. This study aimed to ascertain the role of extracellular-regulated kinases (ERKs)1/2, protein kinase B (PKB), and Per-Arnt-Sim kinase (PASK) in palmitate inhibition of insulin gene expression in pancreatic β-cells. RESEARCH DESIGN AND METHODS MIN6 cells and isolated rat islets were cultured in the presence of elevated glucose, with or without palmitate or ceramide. ERK1/2 phosphorylation, PKB phosphorylation, and PASK expression were examined by immunoblotting and real-time PCR. The role of these kinases in insulin gene expression was assessed using pharmacological and molecular approaches. RESULTS Exposure of MIN6 cells and islets to elevated glucose induced ERK1/2 and PKB phosphorylation, which was further enhanced by palmitate. Inhibition of ERK1/2, but not of PKB, partially prevented the inhibition of insulin gene expression in the presence of palmitate or ceramide. Glucose-induced expression of PASK mRNA and protein levels was reduced in the presence of palmitate. Overexpression of wild-type PASK increased insulin and pancreatic duodenal homeobox-1 gene expression in MIN6 cells and rat islets incubated with glucose and palmitate, whereas overexpression of a kinase-dead PASK mutant in rat islets decreased expression of insulin and pancreatic duodenal homeobox-1 and increased C/EBPβ expression. CONCLUSIONS Both the PASK and ERK1/2 signaling pathways mediate palmitate inhibition of insulin gene expression. These findings identify PASK as a novel mediator of glucolipotoxicity on the insulin gene in pancreatic β-cells.
A Neural Network Based Tool for Aircraft SFDIA Modeling and Simulation

This paper presents a Neural Network (NN) based tool for the modeling, simulation and analysis of aircraft Sensor Failure, Detection, Identification and Accommodation (SFDIA) problems. The SFDIA scheme exploits the analytical redundancy of the system to provide validation capability to measurement devices by employing Neural Networks as on-line non-linear approximators. The tool allows evaluating either the open loop or the closed loop performance of the SFDIA scheme. Several kinds of NN approximators and learning algorithms are employed, and a library comprising all these different adaptive neural networks is presented. In particular, Resource Allocating Networks featuring fully tuned Radial Basis Activation Functions are proposed as one of the most effective architectures. Finally, the results of a comparative study of different NN approximators applied to the SFDIA problem on a detailed nonlinear model of a De Havilland DHC-2 “Beaver” aircraft are reported.
Waffle Mixer : A Library for Distributing Genetic Algorithms

We describe a toolkit that enables simple parallelization of genetic algorithms. Genetic algorithms are favored for optimization problems because they lend themselves to both continuous and discrete combinatorial problems and are less susceptible to becoming trapped at local optima in comparison to gradient search methods. Unfortunately, GAs are typically computationally expensive. The toolkit enables writers of genetic algorithm applications to choose between local (one machine) operation or distributed computation at runtime. The distributed approach achieves the same result or better than a local computation, but significantly diminishes the required computation time. An analysis of the system’s performance is described.
Liquid Drop Analysis Technology Based on Computer Vision

In consideration of the limitations of fiber and capacitor drop analysis, the image drop analysis based on computer vision is put forward in this paper. With this method the limitations of fiber and capacitor analysis methods can be avoided, and the more significant is that the variation information of the liquid drop’s shape during its forming process is acquirable, thus we can research the liquid’s property through the contour feature of its drop. The image drop analysis method realizes the analysis to liquid drop images through the real time record of drop growth process with CCD camera. And after further processing the region area, boundary perimeter, drop length, satiety, circularity, and the profile edge of the liquid drop image will be extracted and analyzed. These information can be as the basis in liquid analysis and discrimination. The feasibility of this method is illustrated with experiments in this paper.
Maximum Entropy Modeling of Acoustic and Linguistic Features

Traditionally, speech recognition system is established assuming that acoustic and linguistic information sources are independent. Parameters of hidden Markov model and n-gram are estimated individually and then plugged in a maximum a posteriori classification rule. However, acoustic and linguistic features are correlated in essence. Modeling performance is limited accordingly. This study aims to relax the independence assumption and achieve sophisticated acoustic and linguistic modeling for speech recognition. We propose an integrated approach based on maximum entropy (ME) principle where acoustic and linguistic features are optimally merged in a unified framework. The correlations between acoustic and linguistic features are explored and properly represented in the integrated models. Due to the flexibility of ME model, we can further combine other high-level linguistic features. In the experiments, we carry out the proposed methods for broadcast news transcription using MATBN database. We obtain significant improvement compared to conventional speech recognition system using individual maximum likelihood training
India's Macroeconomic Performance Since 1970: Is There Any Change Under the Regime of 'Liberalisation'?

This paper examines trends in Indian macroeconomic series since 1970 and during the regime of 'liberalisation' since 1991. It finds no significant change in India's macroeconomic performance under liberalisation. Growth in export earnings did not pick up. Real sectors (industry and agriculture) did not experience any accelerated growth. In view of increasing foreign debt, the possibility of debt crisis cannot be ruled out.
Pattern trees for regression and fuzzy systems modeling

Fuzzy pattern tree induction has recently been introduced as a novel classification method in the context of machine learning. Roughly speaking, a pattern tree is a hierarchical, tree-like structure, whose inner nodes are marked with generalized (fuzzy) logical operators and whose leaf nodes are associated with fuzzy predicates on input attributes. In this paper, we adapt the method of pattern tree induction so as to make it applicable to another learning task, namely regression. Thus, instead of predicting one among a finite number of discrete class labels, we address the problem of predicting a real-valued target output. Apart from showing that fuzzy pattern trees are able to approximate real-valued functions in an accurate manner, we argue that such trees are also interesting from a modeling point of view. In fact, by describing a functional relationship between several input attributes and an output variable in an interpretable way, pattern trees constitute a viable alternative to classical fuzzy rule models. Compared to flat rule models, the hierarchical structure of patterns trees further allows for a more compact representation and for trading off accuracy against model simplicity in a seamless manner.
Optimal monetary policy under labor market frictions: the role of wage rigidity and demand shocks

In this paper, I investigate optimal monetary policy in an environment with labor market frictions, heterogeneous wage setting, and demand shocks. When employing a form of wage rigidity which corresponds to empirical evidence, the short-run inflation unemployment trade-off obtained by Blanchard and Gaĺi (2006) in their model with a uniformly rigid wage usually motivated as a solution to the unemployment volatility puzzle disappears. Furthermore, after incorporating demand shocks as an alternative mechanism to address this puzzle, I investigate the consequences for the dynamic responses of inflation and unemployment to those shocks under different monetary policy regimes and, in particular, optimal monetary policy. The results of this exercise support the typical finding of the literature concerning the importance of price stability. In addition, demand shocks of the kind employed in this paper do not generate a significant amount of volatility in unemployment.
On the Weak Computability of Continuous Real Functions

In computable analysis, sequences of rational numbers which effectively converge to a real number x are used as the (rho-) names of x. A real number x is computable if it has a computable name, and a real function f is computable if there is a Turing machine M which computes f in the sense that, M accepts any rho-name of x as input and outputs a rho-name of f(x) for any x in the domain of f. By weakening the effectiveness requirement of the convergence and classifying the converging speeds of rational sequences, several interesting classes of real numbers of weak computability have been introduced in literature, e.g., in addition to the class of computable real numbers (EC), we have the classes of semi-computable (SC), weakly computable (WC), divergence bounded computable (DBC) and computably approximable real numbers (CA). In this paper, we are interested in the weak computability of continuous real functions and try to introduce an analogous classification of weakly computable real functions. We present definitions of these functions by Turing machines as well as by sequences of rational polygons and prove these two definitions are not equivalent. Furthermore, we explore the properties of these functions, and among others, show their closure properties under arithmetic operations and composition.
Transfer of Ho Endonuclease and Ufo1 to the Proteasome by the UbL-UbA Shuttle Protein, Ddi1, Analysed by Complex Formation In Vitro

The F-box protein, Ufo1, recruits Ho endonuclease to the SCFUfo1 complex for ubiquitylation. Both ubiquitylated Ho and Ufo1 are transferred by the UbL-UbA protein, Ddi1, to the 19S Regulatory Particle (RP) of the proteasome for degradation. The Ddi1-UbL domain binds Rpn1 of the 19S RP, the Ddi1-UbA domain binds ubiquitin chains on the degradation substrate. Here we used complex reconstitution in vitro to identify stages in the transfer of Ho and Ufo1 from the SCFUfo1 complex to the proteasome. We report SCFUfo1 complex at the proteasome formed in the presence of Ho. Subsequently Ddi1 is recruited to this complex by interaction between the Ddi1-UbL domain and Ufo1. The core of Ddi1 binds both Ufo1 and Rpn1; this interaction confers specificity of SCFUfo1 for Ddi1. The substrate-shield model predicts that Ho would protect Ufo1 from degradation and we find that Ddi1 binds Ho, Ufo1, and Rpn1 simultaneously forming a complex for transfer of Ho to the 19S RP. In contrast, in the absence of Ho, Rpn1 displaces Ufo1 from Ddi1 indicating a higher affinity of the Ddi1-UbL for the 19S RP. However, at high Rpn1 levels there is synergistic binding of Ufo1 to Ddi1 that is dependent on the Ddi1-UbA domain. Our interpretation is that in the absence of substrate, the Ddi1-UbL binds Rpn1 while the Ddi1-UbA binds ubiquitin chains on Ufo1. This would promote degradation of Ufo1 and disassembly of SCFUfo1 complexes.
Gender differences in head impacts sustained by collegiate ice hockey players.

PURPOSE This study aimed to quantify the frequency, magnitude, and location of head impacts sustained by male and female collegiate ice hockey players during two seasons of play. METHODS During two seasons, 88 collegiate athletes (51 females, 37 males) on two female and male National Collegiate Athletic Association varsity ice hockey teams wore instrumented helmets. Each helmet was equipped with six single-axis accelerometers and a miniature data acquisition system to capture and record head impacts sustained during play. Data collected from the helmets were postprocessed to compute linear and rotational accelerations of the head as well as impact location. The head impact exposure data (frequency, location, and magnitude) were then compared between genders. RESULTS Female hockey players experienced a significantly lower (P < 0.001) number of impacts per athlete exposure than males (females = 1.7 ± 0.7, males = 2.9 ± 1.2). The frequency of impacts by location was the same between genders (P > 0.278) for all locations except the right side of the head, where males received fewer impacts than females (P = 0.031). Female hockey players were 1.1 times more likely than males to sustain an impact less than 50 g, whereas males were 1.3 times more likely to sustain an impact greater than 100 g. Similarly, males were 1.9 times more likely to sustain an impact with peak rotational acceleration greater than 5000 rad·s(-2) and 3.5 times more likely to sustain an impact greater than 10,000 rad·s(-2). CONCLUSIONS Although the incidence of concussion has typically been higher for female hockey players than male hockey players, female players sustain fewer impacts and impacts resulting in lower head acceleration than males. Further study is required to better understand the intrinsic and extrinsic risk factors that lead to higher rates of concussion for females that have been previously reported.
Low-dose isoproterenol for repetitive ventricular arrhythmia in patients with Brugada syndrome.

AIMS Arrhythmic storm or repetitive ventricular arrhythmia (VA) has been occasionally observed in Brugada syndrome (BS). A beta-adrenergic stimulator [isoproterenol (ISP)] has been reported to suppress this arrhythmic storm in sporadic cases. Accordingly, we investigated the antiarrhythmic effects of ISP infusion in consecutive BS patients with arrhythmic storm or repetitive VA. METHODS AND RESULTS Seven BS patients with arrhythmic storm were studied. Intravenous ISP was administered as a bolus injection (1-2 microg), followed by continuous infusion (0.15 microg/min). Arrhythmic storm or repetitive VA was suppressed immediately after the bolus administration of ISP, which was followed by continuous infusion of low-dose ISP for 1-3 days. In all patients, ST-elevation decreased in right precordial leads. In six of the seven patients, VA subsided after the discontinuance of ISP. RR interval was shortened and ST-elevation in right precordial leads was decreased after ISP bolus injection. ST-elevation in right precordial leads remained decreased during continuous ISP infusion, whereas the RR interval returned to the control level. CONCLUSION Continuous administration of low-dose ISP may be effective for the suppression of repetitive VA occurrence in patients with BS.
Does comparative-effectiveness research threaten personalized medicine?

Concerns have been raised that comparative-effectiveness research (CER) will not take adequate account of individual patient differences and may impede the development and adoption of improvements in medical care. Drs. Alan Garber and Sean Tunis argue that CER offers a way to hasten the discovery of the best approaches to personalization.
Wavelet BEM based channel estimation over rapidly time-varying channels

This paper proposes a novel basis expansion model (BEM) to conduct channel estimation for single carrier single input single output (SC-SISO) systems over rapidly time-varying channels. Compared to complex exponential (CE) and polynomial BEM, wavelet BEM is less vulnerable to Doppler shift. Simulations show that the proposed wavelet BEM outperforms CE and polynomial BEM with about 2.5dB and 5.0dB respectively in terms of the mean square error-signal noise ratio (MSE-SNR) performance.
Advancing High-Quality Professional Learning through Collective Bargaining and State Policy: An Initial Review and Recommendations to Support Student Learning.

the American federation of teachers, council of chief state school officers, national education Association, and national staff development council deeply appreciate the contribution of the task force members who committed their expertise, perspective, and time to this initiative. A joint initiative among American federation of teachers council of chief state school officers national education Association national staff development council And state teams from Minnesota new Jersey new york north carolina ohio texas A report of the American federation of teachers, national education Association, national staff development council, and council of chief state school officers. reproduction in whole or part without written permission is prohibited beyond 30 copies if they are to be used for instructional purposes and the report and authoring organizations are properly credited. to obtain permission to copy or reprint these materials, request permission using the procedure outlined the American federation of teachers, the council of chief state school officers, the national education Association, and the national staff development council are committed to student success. our four organizations have joined together because we know that teacher quality and student learning are directly linked. this initial report is just the beginning of our commitment to strengthen professional learning in our nation's schools. We recognize that not all teachers have access to effective professional learning that respects teachers' professionalism and their commitment to student success. further, we recognize and acknowledge the essential role that collective bargaining and state and local policies play in ensuring that effective professional development — focused on improving student learning — is a routine part of every teacher's workday. this publication is the result of an 18-month project that brought together teams from six states — Minnesota, new Jersey, new york, north carolina, ohio, and texas — along with their national organizations in a groundbreaking partnership to identify collective bargaining language and policies that support high-quality professional development. independently, each of us has tackled the important issue of ensuring that teachers engage in effective professional development to improve teaching and learning. together, however, our collective voice speaks more loudly than any of us can individually. 6 We strongly recommend that the education and policy-making communities use this report as a guide to developing collective bargaining agreements or memoranda of understanding with their school staff, as well as pursuing state and local level policies that assure the highest-caliber professional learning for all teachers. We thank our affiliates …
Conquest, Domination and Control: Europe's Mastery of Nature in Historic Perspective

This article contributes to the broadening agenda of critical globalisation(s) research by analysing one of the most fundamental ideological foundations of the current global transformation in a historical perspective: the ideology of "domination over nature" that was implemented in Europe from 1500 onwards. Humans have always shaped and altered their environment according to their needs and aspirations. However, it is the distinct ideology of mastery and domination over nature that underlines this unprecedented enterprise. An ideology in this context is understood as a codified justification for social practices, codified in concrete as well as highly abstract systems of rule. The question I seek to answer in this contribution is why Europe – a backward civilisation up to the late Middle Ages and the Renaissance – was the birthplace of the distinct ideology of mastery over nature, globalising itself through exploration, discovery, and trade to nearly every corner of the planet. Key words: ideology of mastery, human-nature relations, ecological imperialism, historical political ecology
Spin of Stellar-Mass Black Holes Estimated by a Model of Quasi-Periodic Oscillations

We have proposed in previous papers that the high-frequency pair of quasi-periodic oscillations observed in black-hole binaries with a frequency ratio of 3 : 2 are inertial-acoustic oscillations (nearly horizontal oscillations with no node in the vertical direction) or g-mode oscillations, which are resonantly excited on warped relativistic disks. The resonance occurs through horizontal motions. In this model, the dimensionless spin parameter, a∗ ,o f the central sources can be estimated when their masses are known from other observations. This estimate is done for
Taurine chloramine, a product of activated neutrophils, inhibits in vitro the generation of nitric oxide and other macrophage inflammatory mediators

Taurine (Tau) is an exceptionally abundant free amino acid in the cytosol of inflammatory cells and especially in neutrophils. Taurine protects cells from self‐destruction during processes that generate oxidants. The major function of Tau in leukocytes is to trap chlorinated oxidants (HOCl). Taurine reacts with HOCl to produce the long‐lived compound taurine chloramine (TauCl). Previously, we have shown that other products of the neutrophil chlorinating system are able to modify functions of macrophages. In this study, we investigated in vitro the influence of TauCl on the generation of inflammatory mediators by activated macrophages. We have found that TauCl inhibited the generation of nitric oxide, prostaglandin E2, tumor necrosis factor α, and interleukin‐6, but TauCl slightly enhanced the release of IL‐1α. The formation of nitrites by interferon‐γ‐activated macrophages was inhibited by TauCl in a dose‐dependent manner. Taurine chloramine also reduced the level of inducible nitric oxide synthase (iNOS) mRNA in macrophages, in a similar concentration‐dependent manner. Although our experiments do not exclude a direct effect of TauCl on enzymatic activity of iNOS, the inhibition of iNOS expression seems to be the major mechanism responsible for suppression of NO formation. Finally, we discuss the biological role of TauCl in vivo. We suggest that at the site of inflammation TauCl works as a specific signaling molecule of activated neutrophils that coordinates the generation of inflammatory mediators in macrophages.
LTV Model Reduction With Upper Error Bounds

A new approach for computing upper error bounds for reduced-order models of linear time-varying systems is presented. It is based on a transformation technique of the Hankel singular values using positive-real, odd incremented functions. By applying such time-varying functions, the singular values to be removed can be forced to become equal and constant, so that they can be reduced. Two variations of this method are proposed: one for finite-time horizons and the other for infinite-time problems including periodic systems.