Miracle-dz/UniFAR-FTUs huggingface dataset:
Relaxation training after stroke: potential to reduce anxiety

Abstract Objective: To consider the feasibility of setting up a relaxation group to treat symptoms of post stroke anxiety in an in-patient post-acute setting; and to explore the effectiveness of relaxation training in reducing self-reported tension. Method: A relaxation group protocol was developed in consultation with a multidisciplinary team and a user group. Over a period of 24 months, 55 stroke patients attended group autogenic relaxation training on a rehabilitation ward. Attendance ranged between one and eleven sessions. Self-reported tension was assessed pre and post relaxation training using the Tension Rating Circles (TRCs). Results: The TRCs identified a significant reduction in self-reported tension from pre to post training, irrespective of the number of sessions attended; z = −3.656, p < 0.001, r = −0.67, for those who attended multiple sessions, z = −2.758, p < 0.01, r = −0.6 for those who attended a single session. Discussion: The routine use of relaxation techniques in treating anxiety in patients undergoing post-stroke rehabilitation shows potential. Self-reported tension decreased after attendance at relaxation training. The TRCs proved acceptable to group members, but should be validated against standard anxiety measures. Further exploration of the application of relaxation techniques in clinical practice is desirable. Implications for Rehabilitation Anxiety is prevalent after stroke and likely affects rehabilitation outcomes. Relaxation training is a well proven treatment for anxiety in the non-stroke population. A significant within session reduction in tension, a hallmark symptom of anxiety, was evidenced via group relaxation training delivered in a post-acute, in-patient stroke unit setting. Relaxation training a shows promise as a treatment for anxiety after stroke.
Fabrication and characterization of reactive nanoscale multilayer systems for low-temperature bonding in microsystem technology

Reactive bonding is a still new low-temperature joining process that is based on reactive nanoscale multilayer systems. The heat required for the bonding process is generated by a self-propagating exothermic reaction within the multilayer system while the adhesive interconnect is supported by solder films. For microsystem applications, the approach is particularly useful if temperature-sensitive components and materials with high differences in coefficient of thermal expansion have to be joined. In this paper, this is successfully demonstrated for bonding a quartz strain gauge onto a stainless steel membrane and an IR-emitter onto a covar socket by using commercially available nickel/aluminum NanoFoils©. The quality of the bond interface of both demonstrators was investigated by scanning electron microscopy and the strength was determined by a tensile test. On the other hand, integrated microsystem applications beyond die attachment require patterned bond structures, e.g. to form bond frames. Thus, alternative materials were additionally considered that can be directly deposited on silicon substrates by magnetron sputtering, such as aluminum/titanium as well as titanium/amorphous silicon (Ti/a-Si) bilayer systems. The properties of these basic multilayer systems and their reaction products were characterized by differential scanning calorimetry and high-resolution electron microscopy. It is shown that specifically the Ti/a-Si system has substantial potential for direct microsystem technology integration provided the remaining open technological issues can be addressed during future research. In general, the results obtained in this study demonstrate the high potential of the reactive bonding process as a new advantageous assembly technology for the fabrication of future microsystems.
Research on Scenic Spot’s Sustainable Development Based on a SD Model: A Case Study of the Jiuzhai Valley

In the field of tourism, the development of tourist attractions is playing an increasingly crucial role in tourism economy, regional economy and national economy. However, the eco-environment has been damaged while tourism industry develops rapidly. Thus, to solve the contradiction between tourism development and eco-environment protection is the key to achieving sustainable development of tourism. This paper builds a SD model, which is based on the analysis of the economic subsystem and environment subsystem, to promote sustainable development. In order to show the effectiveness of the model, Jiuzhai Valley is taken as the research object and a decisive basis is provided for the path adjustment of sustainable development in tourist scenic.
An approach to dealing with missing values in heterogeneous data using k-nearest neighbors

Techniques such as clusterization, neural networks and decision making usually rely on algorithms that are not well suited to deal with missing values. However, real world data frequently contains such cases. The simplest solution is to either substitute them by a best guess value or completely disregard the missing values. Unfortunately, both approaches can lead to biased results. In this paper, we propose a technique for dealing with missing values in heterogeneous data using imputation based on the k-nearest neighbors algorithm. It can handle real (which we refer to as crisp henceforward), interval and fuzzy data. The effectiveness of the algorithm is tested on several datasets and the numerical results are promising.
Intracellular Forms of Adenovirus DNA III. Integration of the DNA of Adenovirus Type 2 into Host DNA in Productively Infected Cells

KB cells productively infected with human adenovirus type 2 contain an alkalistable class of viral DNA sedimenting in a broad zone between 50 and 90S as compared to 34S for virion DNA. This type of DNA is characterized as viral by DNA-DNA hybridization. It is extremely sensitive to shear fragmentation. Extensive control experiments demonstrate that the fast-sedimenting viral DNA is not due to artifactual drag of viral DNA mechanically trapped in cellular DNA or to association of viral DNA with protein or RNA. Furthermore, the fast-sedimenting DNA is found after infection with multiplicities between 1 and 1,000 PFU/cell and from 6 to 8 h postinfection until very late in infection (24 h). Analysis in dye-buoyant density gradients eliminates the possibility that the fast-sedimenting viral DNA represents supercoiled circular molecules. Upon equilibrium centrifugation in alkaline CsCl density gradients, the fast-sedimenting viral DNA bands in a density stratum intermediate between that of cellular and viral DNA. In contrast, the 34S virion DNA isolated and treated in the same manner as the fast-sedimenting DNA cobands with viral marker DNA. After ultrasonic treatment of the fast-sedimenting viral DNA, it shifts to the density positions of viral DNA and to a lesser extent to that of cellular DNA. The evidence presented here demonstrates that the 50 to 90S viral DNA represents adenovirus DNA covalently integrated into cell DNA.
Centralized Multiple Random Access Protocol with Contention Window Adjustment

In this paper, we propose a new multiple access protocol for the ubiquitous network and analyze its performance in the nonsaturated condition. Based on the concept of equilibrium analysis, we analyze its throughput and the contention window size that maximizes its throughput by constructing a Markov model of terminal state. From this work we introduce an index that uniquely decides throughput regardless of the number of terminals or the offered traffic and propose a contention window adjustment algorithm based on the index. Computer simulations that compare the proposed protocol to conventional protocols clarify that the former has superior throughput.
Using an external electric field to reduce laser damage of DLC films

Unbalanced magnetron sputtering (UBMS) was used to deposit a diamond-like carbon (DLC) film on Si substrates. The film was subjected to a laser to result damages both before and after an external electric field was applied. A contrast of the damages shows that the external electric field improves the film’s laser induced damage threshold (LIDT) from 0.70 J/cm2 up to 0.82 J/cm2; when the optical energy is maintained at 1.88 J/cm2, the damaged area of the film decreases with increasing external electric field. The results show that the external electric field influences the anti-laser-damage ability of a DLC film because both the photoelectrons produced by the excitation from the laser and the free electrons in the DLC film can move quickly within the film. This movement indirectly decreases the energy density in the laser-irradiated area and slows down the DLC film’s graphitisation process, consequently improving the film’s ability to withstand laser damage.
Distributed Parallel Computing with Low Cost Microcontrollers for High Performance Electric Vehicles

In this paper, we implement a distributed parallel system, to control, with high performance, a power DC-DC buck converter in electric vehicles. A Permanent Magnet Direct Current (PMDC) motor is used, capable of running at 14,4 kW in a continuous mode. Low cost microcontroller (MCU) is used to monitor and control in real time proporcional-integrative-derivative (PID) controller. The Serial Peripheral Interface (SPI) protocol is used for communication between MCUs. The distributed parallel computing allows that the controller becomes cost effective and scalable. Implementing distributed parallel computing increased performance in 5 times with two microcontrollers and 10 times with three when compared to 1 microcontroller.
Automatic Best Reference Slice Selection for Smooth Volume Reconstruction of a Mouse Brain From Histological Images

In this paper, we present a novel and effective method for registering histological slices of a mouse brain to reconstruct a 3-D volume. First, intensity variations in images are corrected through an intensity standardization process so that intensity values remain constant across slices. Second, the image space is transformed to a feature space where continuous variables are taken as high fidelity image features for accurate registration. Third, in order to improve the quality of the reconstructed volume, an automatic best reference slice selection algorithm is developed based on iterative assessment of image entropy and mean square error of the registration process. Fourth, a novel metric for evaluating the quality of the reconstructed volume is developed. Finally, the effect of optimal reference slice selection on the quality of registration and subsequent reconstruction is demonstrated.
Resting state fMRI connectivity analysis as a tool for detection of abnormalities in five different cognitive networks of the brain in Multiple Sclerosis patients

Objectives Cognitive dysfunction is present in at least half of patients with Multiple Sclerosis. The purpose of this study was to examine functional connectivity abnormalities in patients with multiple sclerosis (MS) using resting state fMRI (rsfMRI). Methods Conventional MRI, rsfMRI and diffusion tensor imaging (DTI) data was acquired from 10 patients with relapsing-remitting multiple sclerosis (RRMS) and 20 healthy controls. Cross-correlation of the resting state average signal among the voxels in each brain region of the five cognitive networks: default mode network (DMN), attention, verbal memory, memory, and visuospatial working memory network, was calculated. Voxelwise analyses were used to investigate fractional anisotropy (FA) of white matter tracts. The normalized gray matter (GM), white matter and thalamus volumes were calculated. Results Compared to controls, significant deficit in MS patients at each of five networks, attention (p=0.026), DMN (p=0.004), verbal memory (p<0.001), memory (p=0.001), visuospatial working memory (p=0.003) was found. Significant reduction (p=0.034) in the normalized GM volume and asymmetry in thalamus volume (p=0.041) was detected in MS patients compared to controls. Conclusion Wide spread of functional abnormalities are present within different cognitive networks in patients with RRMS, suggesting that DMN may not be sufficient for measurement of MS cognitive impairment. Larger and longitudinal studies should ascertain whether rsfMRI of cognitive networks and changes in GM and thalamus volume can be used as tools for assessment of cognition in clinical trials in MS.
TEXTURAL CHARACTERISTICS OF PASTA MADE FROM RICE FLOUR SUPPLEMENTED WITH PROTEINS AND HYDROCOLLOIDS

Broken pieces of three indigenous rice cultivars were utilized for the formulation of tube type pasta (Ziti-cut) using four levels each of vital gluten and guar gum. The rice flours were modified by pregelatinization and the pregelatinized flour was found suitable for pasta preparation based on instrumental and sensory texture analysis. The cooking time for pasta was reduced from 10 to 6 min by using pregelatinized rice flour. The textural quality of pasta was analyzed using texture analyzer (TAXT-2i) and descriptive sensory analysis techniques. A protein level of 16% was found suitable for production of rice pasta, which was comparable to commercial semolina sample whereas a gum level of 1.5% supplemented to pregelatinized rice flour containing 14% protein was judged the best on the basis of instrumental as well as sensory textural characteristics.
A terahertz band-pass resonator based on enhanced reflectivity using spoof surface plasmons

We demonstrate a band-pass resonator in the terahertz (THz) range, based on a frequency-selective designer reflector. The resonator consists of a parallel-plate waveguide, a designed groove pattern cut into the output facet of each plate, and a reflecting mirror. The patterned facet supports a spoof surface plasmon mode, which modifies the reflectivity at the waveguide output facet by interacting with the waveguide mode. By tuning the geometrical parameters of the groove pattern, the reflectivity at the patterned output facet can be increased up to ∼100% for a selected frequency. Broadband THz waves are quasi-optically coupled into this resonator and reflected multiple times from the patterned facet. This leads to a narrowing of the spectrum at the selected frequency. The Q value of the resonator increases as the number of reflections on the patterned facet increases, reaching ∼25 when the THz wave has experienced 12 reflections. 1 Author to whom any correspondence should be addressed. Content from this work may be used under the terms of the Creative Commons Attribution 3.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI. New Journal of Physics 15 (2013) 055002 1367-2630/13/055002+16$33.00 © IOP Publishing Ltd and Deutsche Physikalische Gesellschaft
Augmenting words with linguistic information for n-gram language models

The main goal of the present work is to explore the use of rich lexical information in language modelling. We reformulated the task of a language model from predicting the next word given its history to predicting simultaneously both the word and a tag encoding various types of lexical information. Using part-of-speech tags and syntactic/semantic feature tags obtained with a set of NLP tools developed at Microsoft Research, we obtained a reduction in perplexity compared to the baseline phrase trigram model in a set of preliminary tests performed on part of the WSJ corpus.
Efficient and Highly Scalable Route Discovey for On-demand Routing Protocols in Ad hoc Networks

This paper presents a number of different route discovery strategies for on-demand routing protocols, which provide more control to each intermediate node make during the route discovery phase to make intelligent forwarding decisions. This is achieved through the idea of self-selection. In self-selecting route discovery each node independently makes route request (RREQ) forwarding decisions based upon a selection criterion or by satisfying certain conditions. The nodes which do not satisfy the selection criterion do not rebroadcast the routing packets. We implemented our self-selecting route discovery strategies over AODV using the GloMoSim network simulation package, and compared the performance with existing route discovery strategies used in AODV. Our simulation results show that a significant drop in the number of control packets can be achieved by giving each intermediate node more authority for self-selection during route discovery. Furthermore, a significant increase in throughput is achieved as the number nodes in the network is increased
Modeling and Numerical Solution for Dam Breach of Tangjiashan Quake Lake

This paper proposes a modeling scheme for dam- breach of Tangjiashan Quake Lake. Firstly, a water level forecasting model based on weather forecast and delayed effect of rainwater is built. Secondly, a dam-breach model based on OE2ED methodology is developed including several factors such as hydraulic, sediment transport, geometry characteristic and reservoir capacity as well as flow. Finally, a simplified dam-break wave model was developed to simulate the flood evolution and evaluate the risk of downstream countries. Simulation results show that the suggested scheme provides better performance for making emergency decision and evaluating the risk.
Software Outsourcing Subcontracting and Its Impacts: An Exploratory Investigation

China now is one of the most important places where software outsourcing businesses are flourishing. However, the subcontracting in the current software outsourcing practices has not received enough attentions. This research attempts to further the understanding on this issue. Mixed empirical research approaches were used to explore the extent and the impacts of the outsourcing subcontracting. The findings suggest the subcontracting widely exists in current China outsourcing industry. Its major enabling factors were also identified. While subcontracting provides the industry with specialized services as well as organizational and managerial flexibility in a low cost way, it also introduces some negative influences. Four future trends are also addressed in this paper.
Journal of Insect Science: Vol. 6 | Article 6

Aedes (Stegomyia) aegypti is an important dengue vector in tropical and subtropical zones throughout the world. A transcriptome of Ae. aegypti vitellogenic fat bodies is described here. The fat body is a dynamic tissue that participates in multiple biochemical functions of intermediate metabolism. A total of 589 randomly selected cDNAs were assembled into 262 clusters based on their primary sequence similarities. The putative translated proteins were classified into categories based on their function in accordance with significant similarity using the BlastX at NCBI FTP site and Pfam (Bateman et al. 2000) and SMART (Schultz et al. 2000) databases. The characterization of transcripts expressed in the fat body of Ae. aegypti at 24 hours post blood meal provides a basic tool for understanding the processes occurring in this organ and could identify putative new genes whose promoters can be used to specifically express transgenes in the fat bodies of Ae. aegypti. Correspondence: mcapurro@icb.usp. br Received: 4.5. 2005 | Accepted: 8.11. 2005 | Published: 6.8. 2006 Copyright: Creative Commons Attribution 2.5 (http://creativecommons.org/licenses/by/2.5) ISSN: 1536-2442 | Volume 6, Number 6
Turbo equalization and demodulation of multicode space time codes

This work considers a high rate, multiple input multiple output (MIMO) systems using multiple codes, as well as channel coding and space time (ST) coding. The transmitter consists of a channel encoder followed by parallel linear dispersion codes (LDC) ST encoders using different spreading codes. The iterative receiver consists of a soft input and soft output (SISO) demodulator, followed by a SISO detector. Simulation results in realistic frequency selective third generation partnership project test cases reveal good performance even for high rate HSDPA services.
The Multilayer In-Place Learning Network for the Development of General Invariances and Multi-Task Learning

Currently, there is a lack of general-purpose in-place learning engines that incrementally learn multiple tasks, to develop "soft" multi-task-shared invariances in the intermediate internal representation while a developmental robot interacts with its environment. Computationally, biologically inspired in-place learning provides unusually efficient learning algorithms whose simplicity, low computational complexity, and generality are set apart from typical conventional learning algorithms. We present in this paper the multiple-layer in-place learning network (MILN) for this ambitious goal. As a key requirement for autonomous mental development, the network enables both unsupervised and supervised learning to occur concurrently, depending on whether motor supervision signals are available or not at the motor end (the last layer) during the agent's interactions with the environment. We present principles based on which MILN automatically develops invariant neurons in different layers and why such invariant neuronal clusters are important for learning later tasks in open-ended development.
Critical Analysis of the Signal‐Averaged Electrocardiogram Improved Identification of Late Potentials

BackgroundThis study performed a critical analysis of signal-averaging methods. The objective was to optimize detection of late potentials. Methods and ResultsWe studied two patient populations: a low-arrhythmia-risk group with no evidence of heart disease and a group with clinically documented ventricular tachycardia (VT). Filtered QRS duration (QRSD) and terminal QRS amplitude (RMS40) were measured from the vector magnitude. A QRS duration based on the latest detectable ventricular activity in any of the three individual XYZ leads was also measured. Because of improved signal-to-noise ratio, both individual lead analysis and extended (600- versus 200-beat) averaging yielded significant changes in signal-averaged ECG parameters. Both approaches gave an increased sensitivity for VT identification. Sensitivity, specificity, and accuracy were evaluated as functions of critical values of QRSD and RMS40. RMS measurements in the terminal QRS, ranging from 20 to 100 msec and including RMS40, did not contribute to maximizing sensitivity and were highly correlated with QRSD. Our results from the low-arrhythmia-risk group suggest that age and sex should be considered in the definition of late potentials. ConclusionsWe propose a VT risk stratification scheme using signal-averaged ECG parameters obtained from both individual lead and vector magnitude analysis. This allows definition of four categories of VT risk derived statistically from the study data. This definition is based on combined measures of sensitivity, specificity, and negative and positive predictive value.
Coupled fluid-thermal network modeling approach for electrical machines

This paper presents a coupled fluid-thermal network modeling approach. Thermal conduction and convection and interaction with the air flow are modeled. Special emphasis is put on a modular model so that geometry and cooling methods can be simply modified. The structure of all necessary modules is introduced. To demonstrate the abilities of this modeling approach, a network involving a 6 MW synchronous machine with cylindrical rotor with directly cooled conductors and a rotor with indirectly cooled conductors is generated and the results are investigated.