Miracle-dz/UniFAR-FTUs huggingface dataset:
Fe b 20 06 X-Ray Emission by A Shocked Fast Wind from the Central Stars of Planetary Nebulae

We calculate the X-ray emission from the shocked fast wind blown by the central stars of planetary nebulae (PNs) and compare with observations. Using spherically symmetric self similar solutions, we calculate the flow structure and X-ray temperature for a fast wind slamming into a previously ejected slow wind. We find that the observed X-ray emission of six PNs can be accounted for by shocked wind segments that were expelled during the early PN phase, if the fast wind speed is moderate, v2 ∼ 400-600 km s, and the mass loss rate is a few times 10−7M⊙ yr . We find, as proposed previously, that the morphology of the X-ray emission is in the form of a narrow ring inner to the optical bright part of the nebula. The bipolar X-ray morphology of several observed PNs, which indicates an important role of jets rather than a spherical fast wind, cannot be explained by the flow studied here. Subject headings: Subject headings: stars: mass loss stars: winds, outflows planetary nebulae: X-ray X-rays: ISM
Effects of acupuncture stimulation on blood glucose concentration in the Otsuka Long-Evans Tokushima Fatty (OLETF) rat, an animal model for type-2 diabetes mellitus

Background Effects of acupuncture stimulation on blood glucose concentration and body weight were investigated in the Otsuka Long-Evans Tokushima Fatty (OLETF) rat, a model for type-2 diabetes. Material/Methods Three groups of rats were used: OLETF, acupuncture-treated OLETF (AcOLETF), and Long-Evans Tokushima Otsuka (LETO) rats (as control for the OLETF rats). In AcOLETF rats, acupuncture stimulation was applied twice a week to 6 points (zhongwan, tianshu, qihai, ganshu, pishu, shenshu) and changes in blood glucose concentration and body weight were measured. Results Initially, at 6 weeks old, there was no significant difference in blood glucose levels between groups. Blood glucose levels increased with age in each group, reaching a maximum of about 430 mg/dl at 37 weeks in OLETF rats. In AcOLETF rats, blood glucose levels increased at a slower rate than in OLETF rats, reaching a maximum concentration of about 280 mg/dl at 37 weeks of age, significantly lower than that in OLETF rats. The concentration of blood glucose in LETO rats had stabilized at a maximum value of 120~140 mg/dl by 16 weeks, remaining at this level for up to 39 weeks. In each group, body weight increased with age and was not affected by acupuncture treatment. Conclusions In OLETF rats, acupuncture treatment significantly reduced blood glucose levels, but not their body weight, suggesting that acupuncture therapy was effective in preventing the development of type-2 diabetes mellitus.
Transmission characteristics of the human body

Intra-body communication is a relatively novel data transmission method that eliminates the need for linking communication devices via cables. In contrast to wireless communication technologies, there is no electric field emission into the environment. In this study, transmission characteristics of the human body were examined using the capacitive coupling method in the frequency range 10 kHz - 5 MHz. In addition, noise signal and other potential measurement-interfering agents were analysed. The frequency range suitable for intra-body communication, the settings required for the input circuit of the receiver, and the human body voltage amplitude were determined.
Procams-Based Cybernetics

Procams-based cybernetics is a unique, emerging research field, which aims at enhancing and supporting our activities by naturally connecting human and computers/machines as a cooperative integrated system via projector-camera systems (procams). It rests on various research domains such as virtual/augmented reality, computer vision, computer graphics, projection display, human computer interface, human robot interaction and so on. This laboratory presentation provides a brief history including recent achievements of our procams-based cybernetics project.
Emergence of NMDAR‐independent long‐term potentiation at hippocampal CA1 synapses following early adolescent exposure to chronic intermittent ethanol: Role for sigma‐receptors

Adolescent humans who abuse alcohol are more vulnerable than adults to the development of memory impairments. Memory impairments often involve modifications in the ability of hippocampal neurons to establish long‐term potentiation (LTP) of excitatory neurotransmission; however, few studies have examined how chronic ethanol exposure during adolescence affects LTP mechanisms in hippocampus. We investigated changes in LTP mechanisms in hippocamal slices from rats exposed to intoxicating concentrations of chronic intermittent ethanol (CIE) vapors in their period of early‐adolescent (i.e., prepubescent) or late‐adolescent (i.e., postpubescent) development. LTP was evaluated at excitatory CA1 synapses in hippocampal slices at 24 h after the cessation of air (control) or CIE vapor treatments. CA1 synapses in control slices showed steady LTP following induction by high‐frequency stimulation, which was fully dependent on NMDAR function. By contrast, slices from early‐adolescent CIE exposed animals showed a compound form of LTP consisting of an NMDAR‐dependent component and a slow‐developing component independent of NMDARs. These components summated to yield LTP of robust magnitude above LTP levels in age‐matched control slices. Bath‐application of the σ‐receptor antagonist BD1047 and the neuroactive steroid pregnenolone sulfate, but not acute ethanol application, blocked NMDAR‐independent LTP, while leaving NMDAR‐dependent LTP intact. Analysis of presynaptic function during NMDAR‐independent LTP induction demonstrated increased presynaptic function via a σ‐receptor‐dependent mechanism in slices from early‐adolescent CIE‐exposed animals. By contrast, CIE exposure after puberty onset in late‐adolescent animals produced decrements in LTP levels. The identification of a role for σ‐receptors and neuroactive steroids in the development of NMDAR‐independent LTP suggests an important pathway by which hippocampal synaptic plasticity, and perhaps memory, may be uniquely altered by chronic ethanol exposure during the prepubescent phase of adolescent development. © 2007 Wiley‐Liss, Inc.
Large scale field trial results on frequency domain compression for uplink joint detection

The spectral efficiency of cellular communication systems is limited by inter-cell interference. Especially cell edge users will experience bad performance. A potential remedy to inter-cell interference is joint signal processing on the base station (BS) side. In the cellular uplink the received signals of multiple BSs can be processed at a central node, referred to as joint detection (JD). Field trials of this technique verify large improvements in spectral efficiency and fairness which were initially proven in theoretical and simulation studies. Recent studies encourage that JD is even beneficial under stringent backhaul constraints which are likely to occur in real deployments. The general solution in case of limited backhaul capacity is based on the compression of exchanged signals. This paper presents the most significant design criteria of such compression algorithms for an LTE-Advanced system. We focus on the exchange of frequency domain IQ-symbols. The limits and potentials of a comprehensive system solution are evaluated using data from large scale field trials.
Continuous-Discrete Path Integral Filtering

A summary of the relationship between the Langevin equation, Fokker-Planck-Kolmogorov forward equation (FPKfe) and the Feynman path integral descriptions of stochastic processes relevant for the solution of the continuous-discrete filtering problem is provided in this paper. The practical utility of the path integral formula is demonstrated via some nontrivial examples. Specifically, it is shown that the simplest approximation of the path integral formula for the fundamental solution of the FPKfe can be applied to solve nonlinear continuous-discrete filtering problems quite accurately. The Dirac-Feynman path integral filtering algorithm is quite simple, and is suitable for real-time implementation.
The impact of interface affordances on human ideation, problem solving, and inferential reasoning

This article presents two studies investigating how computer interface affordances influence basic cognition, including ideational fluency, problem solving, and inferential reasoning. In one study comparing interfaces with different input capabilities, students expressed 56% more nonlinguistic representations (diagrams, symbols, numbers) when using pen interfaces. A linear regression confirmed that nonlinguistic communication directly mediated a substantial increase (38.5%) in students' ability to produce appropriate science ideas. In contrast, students expressed 41% more linguistic content when using a keyboard-based interface, which mediated a drop in science ideation. A follow-up study pursued the question of how interfaces that prime nonlinguistic communication so effectively facilitate cognition. This study examined the relation between students' expression of nonlinguistic representations and their inference accuracy when using analogous digital and non-digital pen tools. Perhaps surprisingly, the digital pen interface stimulated construction of more diagrams, more correct Venn diagrams, and more accurate domain inferences. Students' construction of multiple diagrams to represent a problem also directly suppressed overgeneralization errors, which were the most common inference failure. These research results reveal that computer interfaces have communications affordances which elicit communication patterns that can substantially stimulate or impede basic cognition. Implications are discussed for designing new digital tools for thinking, with an emphasis on nonlinguistic and especially spatial representations that are most poorly supported by current keyboard-based interfaces.
Speed and rotor flux observer for sensorless induction motor drives

This paper presents a new rotor flux and rotor speed observer of induction motor. The new observer is based on an adaptive mechanism. The design of the new observer is done using the notion of Lyapunov stability. The observer is designed to be used within a speed sensorless direct rotor field oriented control of induction motors.
Mobile Botnet Classification by using Hybrid Analysis

The popularity and adoption of Android smartphones has attracted malware authors to spread the malware to smartphone users. The malware on smartphone comes in various forms such as Trojans, viruses, worms and mobile botnet. However, mobile botnet or Android botnet are more dangerous since they pose serious threats by stealing user credential information, distributing spam and sending distributed denial of service (DDoS) attacks. Mobile botnet is defined as a collection of compromised mobile smartphones and controlled by a botmaster through a command and control (C&C) channel to serve a malicious purpose. Current research is still lacking in terms of their low detection rate due to their selected features. It is expected that a hybrid analysis could improve the detection rate. Therefore, machine learning methods and hybrid analysis which combines static and dynamic analyses were used to analyse and classify system calls, permission and API calls. The objective of this paper is to leverage machine learning techniques to classify the Android applications (apps) as botnet or benign. The experiment used malware dataset from the Drebin for the training and mobile applications from Google Play Store for testing. The results showed that Random Forest Algorithm achieved the highest accuracy rate of 97.9%. In future, more significant approach by using different feature selection such as intent, string and system component will be further explored for a better detection and accuracy rate.
A Robust Method for Hand Tracking Using Mean-shift Algorithm and Kalman Filter in Stereo Color Image Sequences

Real-time hand tracking is a challenging task in many computer vision applications such as gesture recognition. This paper proposes a robust method for hand tracking in a complex environment using Mean-shift analysis and Kalman filter in conjunction with 3D depth map. The depth information solve the overlapping problem between hands and face, which is obtained by passive stereo mea- suring based on cross correlation and the known calibration data of the cameras. Mean-shift analysis uses the gradient of Bhattacharyya coefficient as a similarity function to derive the candidate of the hand that is most similar to a given hand target model. And then, Kalman filter is used to estimate the position of the hand target. The results of hand tracking, tested on various video sequences, are robust to changes in shape as well as partial occlusion. Keywords—Computer Vision and Image Analysis, Object Track- ing, Gesture Recognition.
D ec 2 00 2 UUITP-18 / 02 hep-th / 0212042 D-branes in N = 2 WZW models

We briefly review the construction of N=2 WZW models in terms of Manin triples. We analyse the restrictions which should be imposed on the gluing conditions of the affine currents in order to preserve half of the bulk supersymmetry. In analogy with the Kähler case there are two types of D-branes, A-and B-types which have a nice algebraic interpretation in terms of the Manin triple.
Characteristics of Turbulent Round Jets in its Potential-Core Region

— In this work, stationary hot-wire measurements are carried out to investigate the characteristics of a round free jet in its potential core region (0 ≤ x/d ≤ 10). Measurements are carried out on an incompressible round jet for a range of Reynolds numbers from 4000 to 8000, calculated based on the jet exit mean velocity and the nozzle diameter. The effect of flow velocity on the development characteristics of the jet in the core region is analyzed. Time-averaged statistics, spectra of velocity and its higher order moments are presented and explained .
Noninvasive estimation of raised intracranial pressure using ocular ultrasonography in liver transplant recipients with acute liver failure -A report of two cases-

Intracranial pressure (ICP) monitoring is an important issue for liver transplant recipients, since increased ICP is associated with advanced hepatic encephalopathy or graft reperfusion during liver transplantation. Invasive monitoring of ICP is known as a gold standard method, but it can provoke bleeding and infection; thus, its use is a controversial issue. Studies have shown that optic nerve sheath diameter > 5 mm by ocular ultrasonography is useful for evaluating ICP > 20 mmHg noninvasively in many clinical settings. In this case report, we present experiences of using ocular ultrasound as a diagnostic tool that could detect changes in ICP noninvasively during liver transplantation.
A critical review of Artificial Bee Colony optimizing technique in software testing

Any software development is governed by implementation of all steps in a Software Development Life Cycle in an effective manner. Out of all the steps in SDLC, the testing phase plays an important role in determining whether the software is developed in the most efficient and correct manner, since it states the measure of correctness of the product and also verifies whether the software is completely acceptable to the user or not. Testing phase can be achieved successfully either through manual means or can be automated by various testing tools. Manual testing will obviously take more time and may also lead to many errors that can remain unidentified. However, automatic testing ensures that all bugs are identified and all errors are removed with the help of various meta-heuristic techniques such as Genetic Algorithms with Mutation Testing, Artificial Bee Colony Algorithm and Ant Colony Optimization. The Artificial Bee Colony works on the intelligent synchronization of bees where they help each other to find nodes in the software code with promising results. This approach has been discussed in detail. The proposed approach is more scalable, requires less computation time and is easy to understand and implement.
A Method for Improving Data Delivery Efficiency in Delay Tolerant VANET with Scheduled Routes of Cars

In Vehicular Ad Hoc Networks (VANETs), delivering messages to a specific location is difficult due to the high mobility of vehicles. In this paper, we propose a method for efficient message delivery in VANETs utilizing the route information in car navigation systems. In the proposed method, each car periodically exchanges the information on its current position and scheduled route in the car navigation system with neighboring cars within radio range. By referring to the exchanged information, each car forwards messages to the neighboring car that will most closely approach the destination. Through simulations, we confirm that the proposed method achieves a better delivery rate with low bandwidth usage than a Geocast-based method and Epidemic routing.
Angle localization and orientation system with 4 receivers and based on audible sound signals

This paper presents a 2D indoor localization and orientation system based on a TDOA (Time Difference of Arrival) technique. It uses an array of receivers to implement low computational effort DOA (Direction of Arrival) algorithms. The system is implemented in the audible bandwidth (reference signal frequency is 11 kHz) with low cost microphones and speakers and its performance is compared to the same system but implemented with ultrasonic devices.
A Novel Method of Early Diagnosis of Alzheimer's Disease Based on EEG Signals

Studies have reported that electroencephalogram signals in Alzheimer's disease patients usually have less synchronization than those of healthy subjects. Changes in electroencephalogram signals start at early stage but, clinically, these changes are not easily detected. To detect this perturbation, three neural synchrony measurement techniques: phase synchrony, magnitude squared coherence, and cross correlation are applied to three different databases of mild Alzheimer's disease patients and healthy subjects. We have compared the right and left temporal lobes of the brain with the rest of the brain areas (frontal, central, and occipital) as temporal regions are relatively the first ones to be affected by Alzheimer's disease. Moreover, electroencephalogram signals are further classified into five different frequency bands (delta, theta, alpha beta, and gamma) because each frequency band has its own physiological significance in terms of signal evaluation. A new approach using principal component analysis before applying neural synchrony measurement techniques has been presented and compared with Average technique. The simulation results indicated that applying principal component analysis before synchrony measurement techniques shows significantly better results as compared to the lateral one. At the end, all the aforementioned techniques are assessed by a statistical test (Mann-Whitney U test) to compare the results.
The checkpoint-dependent nuclear accumulation of Rho1p exchange factor Rgf1p is important for tolerance to chronic replication stress

Fission yeast Rho1p exchange factor Rgf1p is relocalized to the cell nucleus during the stalled replication caused by hydroxyurea. The Cds1p checkpoint kinase, helped by the chaperone Rad24p, controls the nuclear accumulation of Rgf1p by inhibiting its nuclear export. Failure to do so produces inefficient recovery from replication arrest.
A Two Stage Language Independent Named Entity Recognition for Indian Languages

This paper describes about the development of a two stage hybrid Named Entity Recognition (NER) system for Indian Languages particularly for Hindi, Oriya, Bengali and Telugu. We have used both statistical Maximum Entropy Model (MaxEnt) and Hidden Markov Model (HMM) in this system. We have used variety of features and contextual information for predicting the various Named Entity (NE) classes. The system uses both language dependent and language independent rules. We have also tried to identify the nested named Entities (NES) by giving some linguistic rules and the rules are purely language independent. We have also used gazetteer list in addition to the rules for Oriya, Bengali and Hindi for better accuracy. The system has been trained with Hindi (450, 150 tokens), Oriya (150, 100 tokens), Bengali (93, 023 tokens), and Telugu (50, 250 tokens). The system has been tested with 35,018 tokens of Hindi 45,100 tokens of Oriya, 28,123 tokens of Bengali and 4,320 tokens of Telugu.
Growing 1D and Quasi-2D Unstable Manifolds of Maps

We present a new 1D algorithm for computing the global one-dimensional unstable manifold of a saddle point of a map. Our method can be generalized to compute two-dimensional unstable manifolds of maps with three-dimensional state spaces. This is shown here with a quasi-2D (Q2D) algorithm for the special case of a quasiperiodically forced map, which allows for a substantial simplification of the general case described in Krauskopf and Osinga (1998). The key idea is to “grow” the manifold in steps, which consist of finding a new point on the manifold at a prescribed distance from the last point. The speed of growth is determined only by the curvature of the manifold, and not by the dynamics.The performance of the 1D algorithm is demonstrated with a constructed test example, and it is then used to compute one-dimensional manifolds of a map modeling mixing in a stirring tank. With the Q2D algorithm we compute two-dimensional unstable manifolds in the quasiperiodically forced Henon map.
Performance Analysis of Relay-Based Cooperative Spectrum Sensing in Cognitive Radio Networks Over Non-Identical Nakagami-  $m$ Channels

This paper provides performance analysis of relay-based cognitive radio (CR) networks and presents a detect-amplify-and-forward (DAF) relaying strategy for cooperative spectrum sensing over non-identical Nakagami-m fading channels. An advanced statistical approach is introduced to derive new exact closed-form expressions for average false alarm probability and average detection probability. We also introduce a novel approximation to alleviate the computational complexity of the proposed models. This paper points out the inconsistency of several assumptions that are typically used for performance analysis of CR networks and reveals that channel fading on the relaying links yields similar performance degradations as on the sensing channel. The study also shows that it is not necessary to incorporate all CRs in the cooperative process and that a small number of reliable radios are enough to achieve practical detection level. Compared with the amplify-and-forward strategy, refraining the heavily faded relays in the DAF strategy improves the detection accuracy and reduces the bandwidth requirement of the relaying links. The presented analysis could lead to intuitive system design guidelines for CR networks impaired with non-identical faded channels.