Miracle-dz/UniFAR-FTUs huggingface dataset:
Change in science teacher practice towards IBSE

This study reports on the introduction of inquiry-based science education (IBSE) to the classroom through teacher professional development. The study occurs in three phases. Teachers initially participated in a professional learning community (PLC) in Phase 1 of the study. They then participated in a community of practice (CoP) in Phase 2. In Phase 1 teachers (as a PLC) were introduced to the concept of teaching by inquiry and delivered Topic 1 to students in the junior cycle of secondary school. Teachers and students encountered challenges. This did not deter most of the teachers who continued to the next phase. The teachers in Phase 2 became part of a CoP that developed resources for two more inquiry based topics to be taught by them in the classroom. Professional development of science teachers using CoP appeared to be effective as a vehicle for teachers to grow in understanding of IBSE in this study. Teachers continued to implement inquiry learning in other classes outside of the study with different resources and so introduced inquiry at a school department level. CoP may be used as a model for teacher professional development to introduce IBL into the classroom.
Peritoneal dialysis in polycystic kidney disease patients. Report from the French peritoneal dialysis registry (RDPLF).

BACKGROUND It is commonly believed that polycystic kidney disease (PKD) patients on peritoneal dialysis (PD) are over-exposed to technique failure and peritonitis compared with other patients. This study was carried out to assess whether PKD is associated with technique failure and to evaluate the outcome of PKD patients on PD. METHODS This was a retrospective cohort study based on the data of the French Language Peritoneal Dialysis Registry. We analysed 4162 incident non-diabetic patients who started PD between January 2002 and December 2007. The end of the observation period was 31 December 2008. RESULTS Among 4162 patients, there were 344 PKD patients and 3818 patients who had another underlying nephropathy. PKD patients were younger, had a lower Charlson comorbidity index, were more frequently treated by automated PD and were less frequently assisted than other patients. For the PKD patients, the main reason for PD cessation was renal transplantation. In the multivariate analysis, comorbidities and centre size were associated with technique survival, and no association between PKD and technique failure was observed. There was no statistically significant association between PKD and peritonitis or between PKD and enteric peritonitis. On multivariate analysis, patient survival was associated with PKD and with patient age, comorbidities and the modality of assistance. Centre size was not associated with patient survival. CONCLUSION PD is a suitable method for at least a subgroup of PKD patients reaching end-stage renal disease in a country where renal transplantation is available.
Fault Detection and Isolation for an Uncertain Takagi-Sugeno Fuzzy System using the Interval Approach

This work deals with the fault detection and localization in the case of uncertain nonlinear systems. The presented method uses the diagnosis based on mathematical models. To model nonlinear systems, the multiple model approach is used. This method uses the Takagi-Sugeno fuzzy systems principle to obtain a nonlinear system named multiple models. This modeling principle has the advantage of obtaining a general model that can describe any class of nonlinear systems. This modeling principle also allows one to obtain the generalization of many results that are already obtained for linear systems to the nonlinear systems. To model the system uncertainties, the interval approach is used because the faults or disturbances are generally unknown, but it is possible to know their upper and lower bounds. The proposed technique is insensitive to measurement uncertainties and highly reliable in case of a fault affecting the outputs system.
A study of the identification of authorship for Chinese texts

II. FEATURE SELECTION Every language has its own characteristics. Different from English in which there is natural space between words, Chinese words are linked together without any space. Thus we have to get the words separately through segmentation. At the same time, as the minimum unit of English, characters are meaningless while most of its counterparts in Chinese have definite meaning. Furthermore, in old Chinese single-character words are much more frequently used than multi-character words. In the GB-2312, a standard internal code for Chinese characters, there are total 6763 characters in this code set. This amount allows us to abstract characters from texts as features. According to the characteristics of modern Chinese, we intend to conduct experiments to verify the effectiveness of the features which are extracted from the character and word levels, and we also undergo tests using feature combination from these two levels. At the character level, we transform every text into a 272-dimension vector of which every dimension represents the relative frequency of a certain character in this text. The characters we choose are the most frequently used ones based on the most frequently used characters table which was released by the National Language Committee in 1989. At the same time, we also use the eight most frequently used punctuations as features. At the word level, we use Hai Liang tool to do word segmentation and POS tagging and we extract the 31 tagging types’ distribution as features. In addition to that, we also do experiments for extracting word polarity distribution and average sentence length as features separately.
Stably stratified canopy flow in complex terrain

Abstract. Stably stratified canopy flow in complex terrain has been considered a difficult condition for measuring net ecosystem–atmosphere exchanges of carbon, water vapor, and energy. A long-standing advection error in eddy-flux measurements is caused by stably stratified canopy flow. Such a condition with strong thermal gradient and less turbulent air is also difficult for modeling. To understand the challenging atmospheric condition for eddy-flux measurements, we use the renormalized group (RNG) k–v turbulence model to investigate the main characteristics of stably stratified canopy flows in complex terrain. In this two-dimensional simulation, we imposed persistent constant heat flux at ground surface and linearly increasing cooling rate in the upper-canopy layer, vertically varying dissipative force from canopy drag elements, buoyancy forcing induced from thermal stratification and the hill terrain. These strong boundary effects keep nonlinearity in the two-dimensional Navier–Stokes equations high enough to generate turbulent behavior. The fundamental characteristics of nighttime canopy flow over complex terrain measured by the small number of available multi-tower advection experiments can be reproduced by this numerical simulation, such as (1) unstable layer in the canopy and super-stable layers associated with flow decoupling in deep canopy and near the top of canopy; (2) sub-canopy drainage flow and drainage flow near the top of canopy in calm night; (3) upward momentum transfer in canopy, downward heat transfer in upper canopy and upward heat transfer in deep canopy; and (4) large buoyancy suppression and weak shear production in strong stability.
Comparison of Two Speaker Recognition Systems

– This paper presents a comparison between two speaker recognition systems. One system uses 30 Shannon entropy values extracted from a four level wavelet packet decomposition method in addition to the first three formant frequencies as features and a cascaded feed forward back propagation neural network is used as classifier. The second system uses Mel frequency cepstral coefficients (MFCC) as features and a support vector machine (SVM) as classifier. Results suggest that wavelet based system has better performance than the classic MFCCs with an efficiency of 89.56%.
A pharmacokinetic evaluation and metabolite identification of the GHB receptor antagonist NCS‐382 in mouse informs novel therapeutic strategies for the treatment of GHB intoxication

Gamma‐aminobutyric acid (GABA) is an endogenous inhibitory neurotransmitter and precursor of gamma‐hydroxybutyric acid (GHB). NCS‐382 (6,7,8,9‐tetrahydro‐5‐hydroxy‐5H‐benzo‐cyclohept‐6‐ylideneacetic acid), a known GHB receptor antagonist, has shown significant efficacy in a murine model of succinic semialdehyde dehydrogenase deficiency (SSADHD), a heritable neurological disorder featuring chronic elevation of GHB that blocks the final step of GABA degradation. NCS‐382 exposures and elimination pathways remain unknown; therefore, the goal of the present work was to obtain in vivo pharmacokinetic data in a murine model and to identify the NCS‐382 metabolites formed by mouse and human. NCS‐382 single‐dose mouse pharmacokinetics were established following an intraperitoneal injection (100, 300, and 500 mg/kg body weight) and metabolite identification was conducted using HPLC‐MS/MS. Kinetic enzyme assays employed mouse and human liver microsomes. Upon gaining an understanding of the NCS‐382 clearance mechanisms, a chemical inhibitor was used to increase NCS‐382 brain exposure in a pharmacokinetic/pharmacodynamic study. Two major metabolic pathways of NCS‐382 were identified as dehydrogenation and glucuronidation. The Km for the dehydrogenation pathway was determined in mouse (Km = 29.5 ± 10.0 μmol/L) and human (Km = 12.7 ± 4.8 μmol/L) liver microsomes. Comparable parameters for glucuronidation were >100 μmol/L in both species. Inhibition of NCS‐382 glucuronidation, in vivo, by diclofenac resulted in increased NCS‐382 brain concentrations and protective effects in gamma‐butyrolactone‐treated mice. These initial evaluations of NCS‐382 pharmacokinetics and metabolism inform the development of NCS‐382 as a potential therapy for conditions of GHB elevation (including acute intoxication & SSADHD).
Amiodarone versus lidocaine for the prevention of reperfusion ventricular fibrillation: A randomized clinical trial

BACKGROUND Reperfusion ventricular fibrillation after aortic cross clamp is one of the important complications of open cardiac surgery and its prevention could reduce myocardial injuries. This study aimed to evaluate the efficacy of single dose of amiodarone or lidocaine by the way of pump circuit three minutes before aortic cross clamp release and compare the results with normal saline as placebo in a randomized double blinded controlled trial. METHODS One hundred fifty patients scheduled for first time elective coronary artery bypass graft surgery were randomly assigned to receive either single dose of amiodarone (150 mg), lidocaine (100 mg), or normal saline (5 ml) three minutes before aortic cross clamp release. The incidence of ventricular fibrillation and the need for reuse of drug were compared between these groups by chi-square, Student’s t-test, Mann-Whitney test, and One-way ANOVA. SPSS software was used for statistical analysis. RESULTS The incidence of ventricular fibrillation is higher in the placebo group (15.9%) compare to lidocaine (11.8%) and amiodarone (8.9%) groups; however, there was no statistical difference among the three groups (P = 0.41). Moreover, the reuse of amiodarone (22.7%) was statistically higher (P < 0.05) than lidocaine (5.9%). CONCLUSION This study showed no difference among lidocaine, amiodarone, and placebo in preventing ventricular fibrillation after aortic cross clamp release.
Auto-Tuning Dedispersion for Many-Core Accelerators

Dedispersion is a basic algorithm to reconstruct impulsive astrophysical signals. It is used in high sampling-rate radio astronomy to counteract temporal smearing by intervening interstellar medium. To counteract this smearing, the received signal train must be dedispersed for thousands of trial distances, after which the transformed signals are further analyzed. This process is expensive on both computing and data handling. This challenge is exacerbated in future, and even some current, radio telescopes which routinely produce hundreds of such data streams in parallel. There, the compute requirements for dedispersion are high (petascale), while the data intensity is extreme. Yet, the dedispersion algorithm remains a basic component of every radio telescope, and a fundamental step in searching the sky for radio pulsars and other transient astrophysical objects. In this paper, we study the parallelization of the dedispersion algorithm on many-core accelerators, including GPUs from AMD and NVIDIA, and the Intel Xeon Phi. An important contribution is the computational analysis of the algorithm, from which we conclude that dedispersion is inherently memory-bound in any realistic scenario, in contrast to earlier reports. We also provide empirical proof that, even in unrealistic scenarios, hardware limitations keep the arithmetic intensity low, thus limiting performance. We exploit auto-tuning to adapt the algorithm, not only to different accelerators, but also to different observations, and even telescopes. Our experiments show how the algorithm is tuned automatically for different scenarios and how it exploits and highlights the underlying specificities of the hardware: in some observations, the tuner automatically optimizes device occupancy, while in others it optimizes memory bandwidth. We quantitatively analyze the problem space, and by comparing the results of optimal auto-tuned versions against the best performing fixed codes, we show the impact that auto-tuning has on performance, and conclude that it is statistically relevant.
Artificial neural networks as rainfall-runoff models

Abstract A series of numerical experiments, in which flow data were generated from synthetic storm sequences routed through a conceptual hydrological model consisting of a single nonlinear reservoir, has demonstrated the closeness of fit that can be achieved to such data sets using Artificial Neural Networks (ANNs). The application of different standardization factors to both training and verification sequences has underlined the importance of such factors to network performance. Trials with both one and two hidden layers in the ANN have shown that, although improved performances are achieved with the extra hidden layer, the additional computational effort does not appear justified for data sets exhibiting the degree of nonlinear behaviour typical of rainfall and flow sequences from many catchment areas.
Constraint solving on modular integers

Constraint solving over nite-sized integers involves the def- inition of propagators able to capture modular (a.k.a. wrap-around) in- teger computations. In this paper, we propose e cient propagators for a fragment of modular integer constraints including adders, multipliers and comparators. Our approach is based on the original notion of Clock- wise Interval for which we de ne a complete arithmetic. We also present three distinct implementations of modular integer constraint solving in the context of software verification.
Acoustic voxels

Acoustic filters have a wide range of applications, yet customizing them with desired properties is difficult. Motivated by recent progress in additive manufacturing that allows for fast prototyping of complex shapes, we present a computational approach that automates the design of acoustic filters with complex geometries. In our approach, we construct an acoustic filter comprised of a set of parameterized shape primitives, whose transmission matrices can be precomputed. Using an efficient method of simulating the transmission matrix of an assembly built from these underlying primitives, our method is able to optimize both the arrangement and the parameters of the acoustic shape primitives in order to satisfy target acoustic properties of the filter. We validate our results against industrial laboratory measurements and high-quality off-line simulations. We demonstrate that our method enables a wide range of applications including muffler design, musical wind instrument prototyping, and encoding imperceptible acoustic information into everyday objects.
Solving Nonlinear Complementarity Problems with Linear Threshold Neural Networks

In this paper, we present a recurrent neural network for solving the nonlinear complementarity problems. The neural network model is derived from an unconstrained reformulation of the nonlinear complementarity problems. It is proved that the trajectories are still in R+ with the initial state in R+. The existence of the equilibrium points of the linear threshold neural networks is addressed in this paper. In addition, the convergence of the trajectory of the LT neural network is studied in this paper. Simulation shows that the proposed network is effective in solving these nonlinear complementarity problems.
Application of Fuzzy Edge Detection for Fast Object-based Image Retrieval

This paper describes our use of fuzzy logic techniques for fast object-based retrieval of images. To start with, the user specifies a region containing the object of interest. The image processing methods that are employed work with gray level versions of the region image and of the images in the database. In the retrieval process, we use edge based representations. Fuzzy edge detection coupled with edge thinning forms the primary process of creating edge-maps. Images containing the object are retrieved by similarity matching using a multi-resolution feature list consisting of edge crossings with grid lines. For speed, edge detected multi-resolution representations are computed in a preprocessing operation for all images in the database. Experiments on a database of images obtained using a simple camera yielded good retrieval performance
Surv ey of T echniques for F ormal Veri cation of Combinational Circuits

With the increase in the complexity of present day systems, proving the correctness of a design has become a major concern. Simulation based methodologies are generally inadequate to validate the correctness of a design with a reasonable con dence. More and more designers are moving towards formal methods to guarantee the correctness of their designs. In this paper we survey some state-of-the-art techniques used to perform automatic veri cation of combinational circuits. We classify the current approaches for combinational veri cation into two categories: functional and structural. The functional methods consist of representing a circuit as a canonical decision diagram. Two circuits are equivalent if and only if their decision diagrams are equal. The structural methods consist of identifying related nodes in the circuit and using them to simplify the problem of veri cation. We brie y describe some of the methods in both the categories and discuss their merits and drawbacks.
The effect of screening on the prevalence of diagnosed type 2 diabetes in primary care

Abstract Objective. To investigate to what extent differences in diagnosed diabetes prevalence can be attributed to differences in the general practitioner's (GP) screening activity. Design. An analysis of electronic patient files in combination with a survey among GPs. Setting. Ten primary healthcare centres with 44 GPs in the Netherlands. Patients. General population (n = 58,919) and type 2 diabetic patients (n = 2582). Main outcome measures. Each GP filled in a questionnaire with questions concerning screening methods for diabetes. The presence of diabetes and date of diagnosis were determined. The potential confounding variables age, sex, and postal code (which we used to determine socioeconomic status) were retrieved from patient records. Results. The yearly point prevalence of diabetes increased significantly from 2.92% in 2000–2001 to 4.25% in 2005–2006 (p = 0.002). The incidence increased from 3.29/1000 person-years to 5.13/1000 person-years (p = 0.019). High screening activity of the general practitioner resulted in statistically significantly higher odds (1.35; p = 0.015) of being diagnosed as a patient with diabetes. The effect was independent of the influence of age, gender, and socioeconomic status. Conclusion. Screening activity of the GP has a statistically significant and relevant influence on the prevalence of diagnosed diabetes. General practitioners should evaluate their screening activity to optimize the identification of diabetic patients.
A visual tool for trellis construction and Viterbi decoder of augmented RAC array codes

A software tool for constructing trellis diagram and tracing visually the Viterbi decoder of augmented twodimensional (2D) row and column (RAC) array codes has been designed and implemented. Augmentation technique of 2D RAC codes given here has been performed by utilizing parity-check positions. The augmentation process can be conducted on only row-parity check positions, or on both row and column positions. The tool provides an interface for introducing errors at specific array positions and their effect can be easily determined. The visual tool has been implemented in an adaptive manner, so be able to change different parameters of these codes and see their effects immediately.
The Influence of Video Sampling Rate on Lipreading Performance

That adding visual information improves the recognition of speech is an established fact. However, since the video sampling is done at a much lower rate than speech sampling and the increase in performance, while promising, is still not at the expected level, the question of whether or not is it useful to use high speed recordings makes its appearance. We propose in this paper an analysis of the gain in information from the point of view of lipreading accuracy, based on Root Mean Square Deviation (RMSD) measure. We analyze both real data, recorded using high speed technology, and synthetic data obtained using the well known software tools CUAnimate and CSLU Toolkit. The analysis is performed on two different and highly used types of features the mouth width and height and optical flow. Taking into account the rate of speech our preliminary findings show two different situations. In the case of low speech rate, usually used during spellings or when uttering connected digits (e.g. telephone numbers, account numbers) or uttering separate words, the information gained by using high speed recordings is not significant enough to justify the tremendous amount of resources needed when working with high speed recordings. However, in the case of continuous speech, when the speech rate tends to increase, a recording rate in the range of 24 to 30 frames per second is definitely insufficient. Then interpolation is needed which decreases the recognition performance.