Miracle-dz/UniFAR-FTUs huggingface dataset:
A randomized controlled trial of the effectiveness of a modified recovery workbook program: preliminary findings.

OBJECTIVE The study examined the effectiveness of the Recovery Workbook as a group intervention for facilitating recovery of persons with serious mental illness. METHODS The multicenter, prospective, single-blind, randomized controlled trial included 33 persons who were receiving assertive community treatment services. For 12 weeks, a control group (N=17) received treatment as usual and an intervention group (N=16) received Recovery Workbook training in addition to usual treatment. At study entry and within three days of completion of the intervention, participants' perceived level of hope, empowerment, recovery, and quality of life were measured with the Herth Hope Index, the Empowerment Scale, the Recovery Assessment Scale, and the Quality of Life Index, respectively. Repeated-measures analysis of variance was used to examine between-group differences. RESULTS Participation in the intervention group was associated with positive change in perceived level of hope, empowerment, and recovery but not in quality of life. The associations remained after analyses controlled for demographic variables. CONCLUSIONS The study, which is one of the first randomized controlled trials of a recovery-based group intervention for persons with serious mental illness, showed that the Recovery Workbook group program was effective in increasing individuals' perceived sense of hope, empowerment, and recovery. In an era when recovery is the primary goal around which reformed mental health service delivery is organized, researchers should continue to study recovery-based interventions such as the Recovery Workbook to determine their potential as evidence-based treatment options.
Global nature of dilute-to-dense transition of granular flows in a 2D channel.

The dilute-to-dense transition of granular flow of particle size d(0) is studied experimentally in a two-dimensional channel (width D) with confined exit (width d). Our results show that with fixed d and D there is a maximum inflow rate Q(c) above which the flow changes from dilute to dense and the outflow rate drops abruptly from Q(c) to a dense rate Q(d). A rescaled critical rate q(c) is found to be a function of a scaling variable lambda only: q(c) approximately F(lambda), where lambda identical with d/d(0) d/D-d. This form of lambda suggests that the dilute-to-dense transition is a global property of the flow, unlike the jamming transition which depends only on d/d(0). Furthermore, the transition is found to occur when the area fraction of particles near the exit exceeds a critical value which is close to 0.65+/-0.03.
Using initiative to provide clinical intervention groups in prison: a process evaluation

We present a process evaluation of a new anger control intervention within an urban remand prison in London, UK. An anger control group was created and run as an extension of the prison in-reach healthcare team, in order to meet the needs of prisoners. We evaluate the aims of the intervention, therapeutic methodology, administrative process, and post-intervention outcomes. We report change in anger scores (State Trait Anger Expression Inventory; STAXI-II), showing how a service of this type might deliver important benefits. Through the use of a focus group with the clinicians who ran the service, we have reflected on this process to inform the evaluation. We conclude that anger management may have a useful role in remand prisons, not just for violent offenders, but as part of a wider public health agenda. Resources for new prison healthcare groups are scarce, particularly in urban remand prisons, and clinicians may have to collaborate with other teams to provide a range of interventions. Following the expressed needs of the prisoner population promotes a strong uptake of clients. Prison health services operate within a complex and environment which restricts healthcare teams’ ability to run groups. We provide recommendations on overcoming potential barriers to care.
Photosensitivity Characterization of Nanostructured Tin Oxide Films and Alternative Photodetector Application

In this paper, we present an analysis of the photosensitivity property of electrical resistance of nanostructured porous tin oxide films (SnO2) deposited on Si substrates using a spray method. Based on this property, we propose a new application for this material as an element in a photodetector device. As we verified that the film photosensitivity is influenced by room temperature, to develop a photodetector device, we propose a microcontroller-based algorithm for compensating temperature changes in a certain range. The morphological and chemical structure of the sample films revealed by atomic force microscopy (AFM) and Raman spectroscopy are also discussed. The dynamics of the photodetector have been tested by varying the frequency of light excitation and the temperature of the film. The results show that the device works properly for intermediate ranges of frequency and temperature, but its response degrades as the frequency or temperature rises.
2 Mb SPRAM (SPin-Transfer Torque RAM) With Bit-by-Bit Bi-Directional Current Write and Parallelizing-Direction Current Read

A 1.8 V 2 Mb SPin-transfer torque RAM (SPRAM) chip using a 0.2 mum logic process with an MgO tunneling barrier cell demonstrates the circuit technologies for potential low-power nonvolatile RAM, or universal memory. This chip features an array scheme with bit-by-bit bi-directional current writing to achieve proper spin-transfer torque writing of 100 ns, and parallelizing-direction current reading with a low-voltage bit-line for preventing read disturbances that lead to 40 ns access time.
Antigenic and Genetic Characterization of Influenza C Viruses Which Caused Two Outbreaks in Yamagata City, Japan, in 1996 and 1998

ABSTRACT During the 3 years from January 1996 to December 1998, a total of 33 strains of influenza C virus were isolated from 10,726 throat swab specimens collected from children with acute respiratory illness who visited two pediatric clinics in Yamagata City, Japan. These 33 strains were isolated in clusters during two different periods, 20 strains in May to August 1996 and the remaining 13 in March to June 1998. Antigenic analysis with monoclonal antibodies to the hemagglutinin-esterase (HE) glycoprotein and phylogenetic analysis of seven RNA segments showed that the 33 influenza C viruses isolated were antigenically and genetically similar and that they were reassortant viruses which had obtained PB2, PB1, HE, M, and NS genes from a C/pig/Beijing/115/81-like virus and P3 and NP genes from a C/Mississippi/80-like virus. These observations suggest strongly that during the survey period of 3 years, two outbreaks of influenza C occurred in Yamagata City, both of which were caused by a reassortant virus having the genome composition described above.
A novel approach of mining strong jumping emerging patterns based on BSC-tree

It is a great challenge to discover strong jumping emerging patterns (SJEPs) from a high-dimensional dataset because of the huge pattern space. In this article, we propose a dynamically growing contrast pattern tree (DGCP-tree) structure to store grown patterns and their path codes arrays with 1-bit counts, which are from the constructed bit string compression tree. A method of mining SJEPs based on DGCP-tree is developed. In order to reduce the pattern search space, we introduce a novel pattern pruning method, which dramatically reduces non-minimal jumping emerging patterns (JEPs) during the mining process. Experiments are performed on three real cancer datasets and three datasets from the University of California, Irvine machine-learning repository. Compared with the well-known CP-tree method, the results show that the proposed method is substantially faster, able to handle higher-dimensional datasets and to prune more non-minimal JEPs.
Troponin Elevation After Percutaneous Coronary Intervention Directly Represents the Extent of Irreversible Myocardial Injury: Insights From Cardiovascular Magnetic Resonance Imaging

Background—Although troponin elevation after percutaneous coronary intervention (PCI) is common, uncertainties remain about the mechanisms of its release and its relationship to the volume of myocardial tissue loss. Delayed-enhancement MRI of the heart has been shown to reliably quantify areas of irreversible myocardial injury. To investigate the quantitative relationship between irreversible injury and cardiac troponin release, we studied the incidence and extent of new irreversible injury in patients undergoing PCI and correlated it to postprocedural changes in cardiac troponin I. Methods and Results—Fifty patients undergoing PCI were studied with preprocedural and postprocedural (24 hours) delayed-enhancement MRI for assessment of new irreversible myocardial injury. Cardiac troponin I measurements were obtained before PCI and 24 hours after PCI. Of these 50 patients, 24 underwent a further third MRI scan at a median of 8 months after the procedure. Mean patient age was 64±12 years. After the procedure, 14 patients (28%) had evidence of new myocardial hyperenhancement, with a mean mass of 6.0±5.8 g, or 5.0±4.8% of total left ventricular mass. All of these patients had raised troponin I levels (range 1.0 to 9.4 &mgr;g/L). Thirty-four patients (68%) had no elevated troponin I and no evidence of new myocardial necrosis on MRI. There was a strong correlation between the rise in troponin I measurements at 24 hours and mean mass of new myocardial hyperenhancement, both early (r=0.84; P<0.001) and late (r=0.71; P<0.001) after PCI, although there was a trend for a reduction in the size of PCI-induced myocardial injury in the late follow-up scan (P=0.07). Conclusions—In the setting of PCI, patients demonstrating postprocedural elevation in troponin I have evidence of new irreversible myocardial injury on delayed-enhancement MRI. The magnitude of this injury correlates directly with the extent of troponin elevation.
Fuzzy reasoning model of facial selection and its applications

We have been spending more time on interaction with computer systems in the information-oriented society. Human face-to-face interaction consists of both verbal communication and nonverbal communication such as facial expressions and gestures. Therefore we have adopted facial expressions for human computer interaction. We propose a fuzzy reasoning model for selecting faces expressing emotions caused by several situations. Nine faces with three levels of brow and eye deflection and three levels of mouth deflection were used to construct the fuzzy reasoning model. The fuzzy reasoning model was applied to selecting faces expressing emotions caused by sentences on the computer display. A questionnaire survey reveals the usefulness of our method as a human-computer interface.
NUMERICAL IMPLEMENTATION OF FRETTING WEAR IN THE FRAMEWORK OF THE MDR

Two numerical methods are proposed to improve accuracy of the numerical calculation of fretting wear in the framework of the Method of Dimensionality Reduction (MDR). Due to the singularity of the transformation equations, instabilities appear at the border between the stick and slip regions after many transformations from the one-dimensional to the three-dimensional contact and back. In these two methods, the transformation equations are reformulated to weaken the singularity of the integrals and a stable simulation of fretting wear is realized even with the wear models which go beyond the classical Archard law. With an example of dual-oscillation, we show the change in the worn profile of a parabolic indenter as well as the stress distribution on the contacting surface during the oscillating cycles under the Archard’s law of wear and Coulomb’s law of friction.
Extending the Concept and Assessment of Teacher Efficacy

This report describes an effort to develop an instrument to assess teacher efficacy for enhancing student social relations (TES). In addition, the psychometric properties of the teacher efficacy scale produced by Gibson and Dembo were examined after translation to Hebrew and administration to 218 Israeli teachers. Results indicated that the TES subscale is independent of the two original subscales and demonstrates good internal and test-retest reliability. Also, the factorial structure of the original teacher efficacy scale was replicated with the Israeli sample, and reliability levels were generally adequate. Some problems with one of the original subscales are noted.
Flexible liver-needle navigation using fish-like robotic elements

This paper proposes a new method for steering a flexible needle in soft tissue according to an analogy of the swimming wave motion of fish locomotion. Assuming small deflection, the flexible needle is modeled as a linear beam. The governing equation for cantilever deflection is used to minimize the strain energy of the needle. Our simulation demonstrated that the repetitive motion has presented a more flexible agility to avoid obstacles, and possess better ability to find the appropriate path according to the external forces applied on the tissue during navigation. The motion of the needle can be tracked by comparing the desired deflection with needle position from x-ray images. Point-to-point algorithm is used to achieve real time control of the flexible needle.
MOTHER: System for continuous capturing of display stream

This paper describes an efficient technique to record display output stream with memory resident software. This kind of recording can be made useful for studying text writing processes experimentally, for example programmers behaviour during coding. The system is inconspicuous in test situation and does not seem to affect the testees working. Separate software has been developed for reviewing captured sessions.
Stealth breakpoints

Microscopic analysis of malicious code (malware) requires the aid of a variety of powerful tools. Chief among them is a debugger that enables runtime binary analysis at an instruction level. One of the important services provided by a debugger is the ability to stop execution of code at an arbitrary point during runtime, using breakpoints. Software breakpoints support an unlimited number of breakpoint locations by changing the code being debugged so that it can be interrupted during runtime. Most, if not all, malware are very sensitive to code modification with self-modifying and/or self-checking (SM-SC) capabilities, rendering the use of software breakpoints limited in their scope. Hardware breakpoints supported by the underlying processor, on the other hand, use a subset of the processor register set and exception mechanisms to provide breakpoints that do not entail code modification. This makes hardware breakpoints the most powerful breakpoint mechanism for malware analysis. However, current processors provide a very limited number of hardware breakpoints (typically 2-4 locations). Thus, a serious restriction is imposed on the debugger to set a desired number of breakpoints without resorting to the limited alternative of software breakpoints. Also, with the ever evolving nature of malware, there are techniques being employed that prevent the use of hardware breakpoints. This calls for a new breakpoint mechanism that retains the features of hardware breakpoints while providing an unlimited number of breakpoints, which cannot be detected or countered. In this paper, we present the concept of stealth breakpoints and discuss the design and implementation of VAMPiRE, a realization of this concept. VAMPiRE cannot be detected or countered and provides unlimited number of breakpoints to be set on code, data, and I/O with the same precision as that of hardware breakpoints. It does so by employing a subtle combination of simple stealth techniques using virtual memory and hardware single-stepping mechanisms that are available on all processors, old and new. This technique makes VAMPiRE portable to any architecture, providing powerful breakpoint ability similar to hardware breakpoints for microscopic malware analysis
Kinetics and mechanism of a reaction catalyzed by PST‐01 protease from Pseudomonas aeruginosa PST‐01

The initial rates of carboxybenzoyl‐alanyl‐l‐leucyl‐amide (Z‐l‐Ala‐l‐Leu‐NH2) synthesis from carboxybenzoyl‐l‐alanine (Z‐l‐Ala) and l‐leucineamide (l‐Leu‐NH2) and Z‐l‐Ala‐l‐Leu‐NH2 hydrolysis in a homogeneous dimethyl sulfoxide‐aqueous buffer solution [1:1 (v/v)] system catalyzed by PST‐01 protease from Pseudomonas aeruginosa were measured under a wide range of Z‐l‐Ala, l‐Leu‐NH2 and Z‐l‐Ala‐l‐Leu‐NH2 concentrations. The initial rates of the synthetic reaction, in which Z‐l‐Ala‐l‐Leu‐NH2 was produced from Z‐l‐Ala and l‐Leu‐NH2, were inhibited by the substrates. Furthermore, the initial rates of the synthetic reaction were not inhibited by the product Z‐l‐Ala‐l‐Leu‐NH2, and those of the hydrolytic reaction were inhibited by Z‐l‐Ala and l‐Leu‐NH2. All the initial rate data of the synthetic and hydrolytic reactions were well correlated with the rate equation derived based on the proposed reaction scheme. © 2004 Wiley Periodicals, Inc.
Downscaling Land Surface Temperature in Complex Regions by Using Multiple Scale Factors with Adaptive Thresholds

Many downscaling algorithms have been proposed to address the issue of coarse-resolution land surface temperature (LST) derived from available satellite-borne sensors. However, few studies have focused on improving LST downscaling in urban areas with several mixed surface types. In this study, LST was downscaled by a multiple linear regression model between LST and multiple scale factors in mixed areas with three or four surface types. The correlation coefficients (CCs) between LST and the scale factors were used to assess the importance of the scale factors within a moving window. CC thresholds determined which factors participated in the fitting of the regression equation. The proposed downscaling approach, which involves an adaptive selection of the scale factors, was evaluated using the LST derived from four Landsat 8 thermal imageries of Nanjing City in different seasons. Results of the visual and quantitative analyses show that the proposed approach achieves relatively satisfactory downscaling results on 11 August, with coefficient of determination and root-mean-square error of 0.87 and 1.13 °C, respectively. Relative to other approaches, our approach shows the similar accuracy and the availability in all seasons. The best (worst) availability occurred in the region of vegetation (water). Thus, the approach is an efficient and reliable LST downscaling method. Future tasks include reliable LST downscaling in challenging regions and the application of our model in middle and low spatial resolutions.
A Statistical Machine Translation Model with Forest-to-Tree Algorithm for Semantic Parsing

In this paper, we propose a novel supervised model for parsing natural language sentences into their formal semantic representations. This model treats sentence-to-lambda-logical expression conversion within the framework of the statistical machine translation with forest-to-tree algorithm. To make this work, we transform the lambda-logical expression structure into a form suitable for the mechanics of statistical machine translation and useful for modeling. We show that our model is able to yield new state-of-the-art results on both standard datasets with simple features.
MEG Connectivity and Power Detections with Minimum Norm Estimates Require Different Regularization Parameters

Minimum Norm Estimation (MNE) is an inverse solution method widely used to reconstruct the source time series that underlie magnetoencephalography (MEG) data. MNE addresses the ill-posed nature of MEG source estimation through regularization (e.g., Tikhonov regularization). Selecting the best regularization parameter is a critical step. Generally, once set, it is common practice to keep the same coefficient throughout a study. However, it is yet to be known whether the optimal lambda for spectral power analysis of MEG source data coincides with the optimal regularization for source-level oscillatory coupling analysis. We addressed this question via extensive Monte-Carlo simulations of MEG data, where we generated 21,600 configurations of pairs of coupled sources with varying sizes, signal-to-noise ratio (SNR), and coupling strengths. Then, we searched for the Tikhonov regularization coefficients (lambda) that maximize detection performance for (a) power and (b) coherence. For coherence, the optimal lambda was two orders of magnitude smaller than the best lambda for power. Moreover, we found that the spatial extent of the interacting sources and SNR, but not the extent of coupling, were the main parameters affecting the best choice for lambda. Our findings suggest using less regularization when measuring oscillatory coupling compared to power estimation.
Ricci curvature and conformality of Riemannian manifolds to spheres

Abstract In this paper we give bounds on the least eigenvalue of the conformal Laplacian and the Yamabe invariant of a compact Riemannian manifold in terms of the Ricci curvature and the diameter and deduce a sufficient condition for the manifold to be conformally equivalent to a sphere. Résumé Soit (M, g) une variété riemannienne compacte sans bord de dimension n. En utilisant des bornes inférieures sur la courbure de Ricci et le diamètre de (M, g) on minore la plus petite valeur propre du laplacien conforme ainsi que l'invariant de Yamabe de cette variété. On en déduit certaines conditions pour que (M, g) soit conformément difféomorphe à la sphère unité de même dimension.
Service level management convergence for future network enterprise platforms

This paper introduces a convergence capability maturity model of network, compute and storage management for virtual infrastructures across distributed locations. It additionally presents a service middleware layer that enhances convergence maturity, while enabling business objectives to be translated into technical resource demands. Architectural and application studies show the value of the model and application of the service middleware layer.
Genetic selection of sox1GFP‐expressing neural precursors removes residual tumorigenic pluripotent stem cells and attenuates tumor formation after transplantation

Because of their ability to proliferate and to differentiate into diverse cell types, embryonic stem (ES) cells are a potential source of cells for transplantation therapy of various diseases, including Parkinson's disease. A critical issue for this potential therapy is the elimination of undifferentiated cells that, even in low numbers, could result in teratoma formation in the host brain. We hypothesize that an efficient solution would consist of purifying the desired cell types, such as neural precursors, prior to transplantation. To test this hypothesis, we differentiated sox1‐green fluorescent protein (GFP) knock‐in ES cells in vitro, purified neural precursor cells by fluorescence‐activated cell sorting (FACS), and characterized the purified cells in vitro as well as in vivo. Immunocytofluorescence and RT‐PCR analyses showed that this genetic purification procedure efficiently removed undifferentiated pluripotent stem cells. Furthermore, when differentiated into mature neurons in vitro, the purified GFP+ cell population generated enriched neuronal populations, whereas the GFP– population generated much fewer neurons. When treated with dopaminergic inducing signals such as sonic hedgehog (SHH) and fibroblast growth factor‐8 (FGF8), FACS‐purified neural precursor cells responded to these molecules and generated dopaminergic neurons as well as other neural subtypes. When transplanted, the GFP+ cell population generated well contained grafts containing dopaminergic neurons, whereas the GFP– population generated significantly larger grafts (about 20‐fold) and frequent tumor‐related deaths in the transplanted animals. Taken together, our results demonstrate that genetic purification of neural precursor cells using FACS isolation can effectively remove unwanted proliferating cell types and avoid tumor formation after transplantation.