Miracle-dz/UniFAR-FTUs huggingface dataset:
Active Guardband Management in Power7+ to Save Energy and Maintain Reliability

Microprocessor voltage levels traditionally include substantial margin to ensure reliable operation despite variations in manufacturing, workload, and environmental parameters. This margin allows the microprocessor to function correctly during worst-case conditions, but during typical operation it is larger than necessary and wastes energy. The authors present a mechanism that reduces excess voltage margin by introducing a critical-path monitor (CPM) circuit that measures available timing margin in real time; coupling the CPM output to the clock generation circuit to rapidly adjust clock frequency in response to excess or inadequate timing margin; and adjusting the processor voltage level periodically in firmware to achieve a specified average clock frequency target. They first demonstrated this mechanism in an IBM Power7 server and proved its effectiveness in the Power7+ product. Power consumption on the VDD rail was reduced by 11 percent for SPEC CPU2006 workloads with negligible performance loss yet increased protection against noise events.
Gait Phase Recognition for Lower-Limb Exoskeleton with Only Joint Angular Sensors

Gait phase is widely used for gait trajectory generation, gait control and gait evaluation on lower-limb exoskeletons. So far, a variety of methods have been developed to identify the gait phase for lower-limb exoskeletons. Angular sensors on lower-limb exoskeletons are essential for joint closed-loop controlling; however, other types of sensors, such as plantar pressure, attitude or inertial measurement unit, are not indispensable.Therefore, to make full use of existing sensors, we propose a novel gait phase recognition method for lower-limb exoskeletons using only joint angular sensors. The method consists of two procedures. Firstly, the gait deviation distances during walking are calculated and classified by Fisher’s linear discriminant method, and one gait cycle is divided into eight gait phases. The validity of the classification results is also verified based on large gait samples. Secondly, we build a gait phase recognition model based on multilayer perceptron and train it with the phase-labeled gait data. The experimental result of cross-validation shows that the model has a 94.45% average correct rate of set (CRS) and an 87.22% average correct rate of phase (CRP) on the testing set, and it can predict the gait phase accurately. The novel method avoids installing additional sensors on the exoskeleton or human body and simplifies the sensory system of the lower-limb exoskeleton.
Maximum likelihood PSD estimation for speech enhancement in reverberant and noisy conditions

We propose a novel Power Spectral Density (PSD) estimator for multi-microphone systems operating in reverberant and noisy conditions. The estimator is derived using the maximum likelihood approach and is based on a blocked and pre-whitened additive signal model. The intended application of the estimator is in speech enhancement algorithms, such as the Multi-channel Wiener Filter (MWF) and the Minimum Variance Distortionless Response (MVDR) beamformer. We evaluate these two algorithms in a speech dereverberation task and compare the performance obtained using the proposed and a competing PSD estimator. Instrumental performance measures indicate an advantage of the proposed estimator over the competing one. In a speech intelligibility test all algorithms significantly improved the word intelligibility score. While the results suggest a minor advantage of using the proposed PSD estimator, the difference between algorithms was found to be statistically significant only in some of the experimental conditions.
Micromachined thermal shear-stress sensor for underwater applications

This paper reports the development of micromachined thermal shear-stress sensors for underwater applications. The thermal shear-stress sensor is a polysilicon resistor sitting atop a vacuum-insulated nitride diaphragm. Special challenges for underwater measurements, such as the waterproof coating and minimization of pressure crosstalk, have been addressed. More rigid diaphragms than the aerial sensors are implemented to increase the operating range and reduce pressure crosstalk, with the cost of larger power consumption and lower sensitivity. Sensors with different diaphragm dimensions and resistor lengths have been fabricated and tested. Nearly zero pressure sensitivity has been achieved by either reducing the diaphragm width or adjusting the sensing element length. The effects of overheat ratio and operating mode on the sensor's pressure crosstalk have been discussed. Parylene C is chosen as the waterproof material for the underwater shear-stress sensors. The primary failure mode is identified as the corrosion of the soldering pads.
Control of Active Suspension System by Using H ∞ Theory

Automotive suspension systems have considerable importance in vehicle design. The designed suspension must provides for a trade-off between several competing objectives: passenger comfort, small suspension stroke for packing, and small tire deflection for vehicle handling. The passenger comfort index is judged by the acceleration of the car body. The next ones are suspension and tire deflection indices. They usually consist of a spring and a damper. With only mechanical construction, the passive suspension systems have their limit properties. In the interest of H controller, three interest transfer functions from road disturbance to car body acceleration, suspension deflection, and tire deflection are plotted: the plotted results are compared to the passive case to show the effectiveness of H controller. In the experimental apparatus, the road disturbance is generated by a cam shaft. By changing the revolution of cam shaft, the road disturbances are given with different frequencies. Measuring the suspension deflection, tire deflection and calculating the car body acceleration from measured car body displacement, then we can derive the gains of three interest transfer functions. These transfer functions are plotted to verify the simulation results. The results showed us that H controller reduces considerably the gains of three interest transfer functions at frequency region around 1 Hz. Abstract : This paper presents a control of active suspension for quarter car model with two degree of freedom by using H∞ method. Absolute velocity of car body is measured for feedback. The system parameter variations are treated with multiplicative uncertainty model. Simulation results show that the H∞controller provides good trade-off between ride quality, suspension packaging and road holding constraints. The experiment with a front wheel suspension system was done to verify the simulation results.
Exploring the effects of communication intervention for developmental pragmatic language impairments: a signal-generation study.

BACKGROUND The remediation of pragmatic problems forms a significant part of the caseload for professionals working with children with communication problems. There is little systematic evidence that demonstrates the benefits of speech and language therapy for children whose difficulties lie primarily within the pragmatic domain or which indicates whether changes in pragmatic behaviours, which are a result of a specific intervention, can be measured over time. AIMS To generate a signal of change in pragmatic and other language behaviours for children with pragmatic language impairments; to gauge the magnitude and nature of the signal and to make recommendations for future studies. METHODS AND PROCEDURES A case series of six children with pragmatic language impairments without diagnosis of autism received 8 weeks of individual intensive speech and language therapy supported in a mainstream educational setting in the UK. Measures of pragmatic behaviours in conversation were made at seven data points before and after therapy using Bishop's ALICC procedure. Conversation coders were blind to the point of assessment. Inferential comprehension, narrative, sentence formulation and sentence recall skills were also tested before and after therapy. The opinions of teachers and parents were sought regarding any change in communication and social abilities of the children over time. OUTCOMES AND RESULTS All children showed change in communication behaviour on some conversational measures, even if the child functioned at the ceiling on standardized language testing. Some conversation measures had more utility as outcome measures than others. Most children showed substantial change on standardized language measures, but there are limitations on the use of these due to heterogeneity within the group. Overall, the intervention produced a signal for change in pragmatics and/or language behaviour in all children. Parent/teacher opinion reported demonstrable change in communication behaviour and engagement in the curriculum. CONCLUSIONS There is a strong signal that change in pragmatic language behaviour can be measured in well-controlled intervention studies but this signal is complex. Outcome measures should take into account changes in language processing skills that are significantly impaired in many children with PLI. For those children within the PLI group who function at ceiling on language tests, conversational measures may have the potential to signal change, but this finding has not been subjected to group study or to testing in generalized settings. Qualitative data regarding behaviour, classroom engagement and generalization of language gains will be an essential supplement to measuring progress in a diverse population.
The social cost of acting "extra": Dilemmas of student identity and academic success in postcolonial Papua New Guinea

THE SOCIAL COST OF ACTING ’’EXTRA:” DILEMMAS OF STUDENT IDENTITY AND ACADEMIC SUCCESS IN POST-COLONIAL PAPUA NEW GUINEA MAY 1997 PETER W. DEMERATH, B.A., HAVERFORD COLLEGE M.A., UNIVERSITY OF PENNSYLVANIA Ed.D. , UNIVERSITY OF MASSACHUSETTS AMHERST Directed by: Professor Gretchen B. Rossman This dissertation describes how and why high school students in a developing country may resist educational processes intended to make them into modem citizens. The research set out to illuminate in-school processes which affected students' academic engagement and to help explicate an eight-year decline on the Grade 10 School Certificate Examination in Manus Province, Papua New Guinea. The report is based on one year of ethnographic research conducted in Pere village on the southeast coast and two high schools in Lorengau, the provincial capital, in 1994-95. I claim that at the time of study a shift away from the village in critical economic resources, rising unemployment, the ongoing viability of the subsistence base, and a need to maintain a degree of control over those living in towns led many Pere Villagers to be discouraged about the value of educational investment and to make claims to a somewhat invented "traditionality. "
Behavioural Finance, entrepreneurial cognition and SME financial management

The principal purpose of this review article is to discover what insights on the financial management of small and medium-sized enterprises the rapidly emerging field of Behavioural Finance can provide. The evolution of Behavioural Finance as a scholarly field is first reviewed. Thereafter, the growing literature in the relatively new field of Entrepreneurial Cognition is also reviewed. The paper culminates in examining the financial management of small and medium-sized enterprises through the combined lenses of Behavioural Finance and Entrepreneurial Cognition. The paper closes with recommendations for further scholarly inquiry into the financial management of small and medium-sized enterprises. Looking out at the world through completely rational eyes, entrepreneurs might well never get started – the odds would appear, realistically, far too daunting. Baron (1998, p. 290) Introduction The principal purpose of this review article is to discover what insights on the financial management of small and medium-sized enterprises (SMEs) the rapidly emerging field of Behavioural Finance can provide. A central concern of Behavioural Finance is the degree of rationality of realistic, as opposed to idealised, financial agents, and how this impacts upon their decision-making practices and behaviours. Behavioural Finance introduces the possibility that, in their real world decision-making, financial agents are less than fully rational and they employ heuristics and exhibit certain systematic cognitive biases that together lead to significant departures from the tenets of Modern Finance Theory. If SME financial management is to be considered from a Behavioural Finance perspective, it is necessary to establish that decision-making heuristics and cognitive biases are typically employed or exhibited by SME owner-managers. For such evidence, the paper draws on a growing literature in the relatively new field of Entrepreneurial Cognition which is at the scholarly intersection of entrepreneurship and cognitive psychology. The structure of the paper is as follows. In the following section, a background review of the evolution of Behavioural Finance is presented. The literature on Entrepreneurial Cognition is then reviewed to the point of
Pro12Ala variant of the PPARG2 gene increases body mass index: An updated meta‐analysis encompassing 49,092 subjects

The peroxisome proliferator‐activated receptor gamma 2 (PPARG2) gene has been intensively studied with relation to obesity and metabolic disorders. Indeed, a large number of studies assessing the association between the PPARG2 polymorphism Pro12Ala (rs1801282) and body mass index (BMI) have been published with some controversial results. In this meta‐analysis, the effects of Pro12Ala polymorphism of the PPARG2 gene on BMI were investigated.
Reliable hopping sequence design for highly interfered wireless sensor networks

Guaranteeing reliability in highly interfered environments is a challenging requirement of current and future wireless applications. A promising state-of-the-art solution for low-power wireless technologies, e.g., wireless sensor networks (WSNs), is frequency hopping aided with black- and white-listing of channels. Both methods, although increase reliability, sacrifice frequency resources. Extensive measurements of channels' packet drop probabilities show that interfered channels are not fully blocked. Motivated by this discovery, we propose the whitening - a methodology for reliable hopping sequence design without resource sacrifice. We model the efficiency of interfered ISM band channels, and study the gains and trade-offs of applying whitening in different scenarios. Application reliability is achieved by granting re-transmissions within a time deadline. Simulations and measurements, performed on the exemplary use case of Time Slotted Channel Hopping WSNs, show that the proposed methods outperform state-of-the-art solutions in the presence of interference in terms of reliability.
Identification of Francisella tularensis using real-time fluorescence polymerase chain reaction.

A Francisella tularensis-specific, TaqMan probe-based, real-time fluorescence polymerase chain reaction (PCR) assay required approximately 60 minutes and consistently achieved a sensitivity of < or = 10 fg of F. tularensis genomic DNA (five genome equivalents). Specificity testing against a genomic DNA cross-reaction panel comprised of 22 bacterial organisms representing closely related species, diverse genera, and human genomic DNA resulted in no false positives of significance. The assay was conducted on a field-deployable thermocycler, the R.A. P.I. D. ("Ruggedized" Advanced Pathogen Identification Device), a microbial identification system that can provide rapid and accurate identification F. tularensis.
Improving tracking by integrating reliability of multiple sources

Tracking algorithms are often designed around optimistic assumptions on uncertainty model. Handling with conflicting data, however, requires specific strategies, that consider quality of information sources. To improve performance of tracking systems, the use of reliability, as evaluation of quality of data sources, has been proved to be a promising technique. In this paper we show how to use reliability of information sources to increase performance of tracking methods, using two different strategies: discount and pruning. We apply those two strategies in two different scenarios: landmark based mobile robot localization using extended Kalman filter and multi-agent object-tracking using particle filter. Experimental results show effectiveness of proposed methodology.
Robustness analysis of a Moving Horizon Estimator for space debris tracking during atmospheric reentry

Trajectory estimation during atmospheric reentry of ballistic objects such as space debris is a very complex problem due to high variations of their ballistic coefficients. In general, the characteristics of the tracked object are not accurately known and an assumption on the dynamics of the ballistic coefficient has to be made in the estimation model. The designed estimator must hence prove to be robust enough to such model uncertainties, and to bad initialization if no good prior information on the initial position, velocity, and the characteristics of the object is available. Robustness of a Moving Horizon Estimator (MHE) is studied in this paper and compared to several other filters: Extended Kalman Filter (EKF), Unscented Kalman Filter (UKF) and Regularized Particle Filter (RPF). The performances of the filters are analysed in terms of convergence percentage, accuracy, robustness to bad initialization, and computation time, via Monte Carlo simulations of trajectories of several space debris. Contrary to the classical tracking problem of supersonic ballistic objects for which RPF has been proven to be efficient in the literature, it is shown that its performance are overcome by MHE for the space debris tracking problem considered in this paper.
Predicting Hospital safety: A Comparison of Four Models

Choosing the best hospitals or avoiding the worst hospitals is important to patients, physicians, and insurers. There is a wealth of publicly reported quality data to use in making those choices, but that data is presented in ways that may conceal important information. We develop three models of how individuals might use the available data in choosing a hospital and present a model that relies on a group-based alternative to the current reporting methods. We compare these four models on their ability to both predict hospital performance on quality and to identify the best and worst hospitals using three measures of patient safety calculated for California hospitals 1997-2006. We find that there are no clear winners in predicting the levels of quality, but we do find evidence that groupbased models may be better at identifying the worst hospitals.
Decentralized power system state estimation with reduced inter-area communication

In this paper, we present a new algorithm for decentralized state estimation in multi-area power systems. The proposed method features significantly reduced communication between areas when compared to the existing gossip-based Gauss-Newton approach. We achieve this by confining gossip iterations associated with a specific state variable to only those areas which actually observe that state variable. This increases the speed of convergence of the gossip iterations, while reducing the amount of communication required for the gossip iterations to converge. We demonstrate the efficacy of our solution with simulations on the IEEE 118-bus system with different communication models.
Multiscale Binarization of Gene Expression Data for Reconstructing Boolean Networks

Network inference algorithms can assist life scientists in unraveling gene-regulatory systems on a molecular level. In recent years, great attention has been drawn to the reconstruction of Boolean networks from time series. These need to be binarized, as such networks model genes as binary variables (either "expressed” or "not expressed”). Common binarization methods often cluster measurements or separate them according to statistical or information theoretic characteristics and may require many data points to determine a robust threshold. Yet, time series measurements frequently comprise only a small number of samples. To overcome this limitation, we propose a binarization that incorporates measurements at multiple resolutions. We introduce two such binarization approaches which determine thresholds based on limited numbers of samples and additionally provide a measure of threshold validity. Thus, network reconstruction and further analysis can be restricted to genes with meaningful thresholds. This reduces the complexity of network inference. The performance of our binarization algorithms was evaluated in network reconstruction experiments using artificial data as well as real-world yeast expression time series. The new approaches yield considerably improved correct network identification rates compared to other binarization techniques by effectively reducing the amount of candidate networks.
Regional forest and non-forest mapping using Envisat ASAR data

Envisat Advanced Synthetic Aperture Radar (ASAR) dual-polarization data are shown to be effective for regional forest monitoring. To this scope, an automatic SAR image preprocessing procedure was developed using SRTM DEM and Landsat TM image for geocoding in rugged terrain and smooth terrain areas, respectively. An object-oriented forest and non-forest classif ication method was then proposed based on the HH (horizontal transmit and horizontal receive) to HV (horizontal transmit and vertical receive) polarization intensity ratio and HV images of ASAR data at single acquisition time in winter. The developed method was applied to forest and non-forest mapping in Northeast China. The overall accuracy, the user’s accuracy and the producer’s accuracy of forest were 83.7%, 85.6% and 75.7%, respectively. These results indicate that the proposed method is promising for operational forest mapping at regional scale.
Complex Formation of Adenomatous Polyposis Coli Gene Product and Axin Facilitates Glycogen Synthase Kinase-3β-dependent Phosphorylation of β-Catenin and Down-regulates β-Catenin*

Adenomatous polyposis coli gene product (APC) functions as a tumor suppressor and its mutations in familial adenomatous polyposis and colorectal cancers lead to the accumulation of cytoplasmic β-catenin. The molecular mechanism by which APC regulates the stability of β-catenin was investigated. The central region of APC, APC-(1211–2075), has the β-catenin- and Axin-binding sites and down-regulates β-catenin. Glycogen synthase kinase-3β (GSK-3β) phosphorylated β-catenin slightly in the presence of either APC-(1211–2075) or AxinΔ β -catenin, in which the β-catenin-binding site is deleted, and greatly in the presence of both proteins. The enhancement of the GSK-3β-dependent phosphorylation of β-catenin was eliminated by the APC-binding site of Axin. Axin down-regulated β-catenin in SW480 cells, but not AxinΔ β -catenin. In L cells where APC is intact, AxinΔ β -catenin inhibited Wnt-dependent accumulation of β-catenin but not Axin-(298–832)Δ β -catenin in which the APC- and β-catenin-binding sites are deleted. These results indicate that the complex formation of APC and Axin enhances the phosphorylation of β-catenin by GSK-3β, leading to the down-regulation of β-catenin.