Miracle-dz/UniFAR-FTUs huggingface dataset:
LTE/LTE-A signal compression on the CPRI interface

The Centralized, Cooperative, Cloud Radio Access Network (C-RAN) is a next-generation wireless access network architecture based on centralized processing, collaborative radio, and real time cloud infrastructure. In this architecture, different access technologies (Global System for Mobile Communications (GSM)/Time Division Synchronous Code Division Multiple Access (TD-SCDMA)/Wideband Code Division Multiple Access (WCDMA)/Long Term Evolution (LTE)) can be supported on the same hardware platform in a baseband pool system, which can largely reduce system costs. Long Term Evolution (LTE) and Long Term Evolution-Advanced (LTE-A), which are based on Orthogonal Frequency Division Multiplexing (OFDM) and multiple input multiple output (MIMO) technologies, are regarded as the main wireless access technologies in the evolution from 3G to 4G. A variety of novel technologies such as multi-antenna MIMO, carrier aggregation (CA), and coordinated multipoint have been introduced in LTE/LTE-A to improve system performance, especially in the C-RAN architecture. However, one of the technical challenges for the C-RAN architecture is the fiber bandwidth required for data transmission between the remote radio unit (RRU) and the baseband unit (BBU). We propose using a low-latency baseband signal compression algorithm to solve this problem by reducing the fiber data rate. Using the characteristics of the LTE signal data, we remove the redundancy in the spectral domain. We also leverage block scaling in conjunction with using a linear or nonlinear (non-uniform) quantizer to minimize quantization error. This algorithm effectively reduces the amount of data transmitted between the BBU and RRU, and facilitates the deployment of LTE in the C-RAN architecture. We verified the robustness of the algorithm via simulations and lab tests. The proposed algorithm yields good system performance at a 1/2 compression rate and at a 1/3 compression rate in a practical propagation environment.
Taking the other out of mother: the transition to secondtime motherhood

Aim: Research into maternal identity often focuses on the transition to motherhood (Smith, 1999; Miller, 2004) and the mother-child bond (e.g. Winnicott, 1956). The literature around mothers is frequently infantocentric and the emphasis on the initial transition brings an inherent assumption of just one child. When the newborn is the second child different understandings are required. By examining accounts of expectation and reality this paper seeks to explore the transition to second time motherhood. Method: Semi-structured interviews with women were carried out from six months into pregnancy. The data was interrogated using narrative analysis. Feminist, psychoanalytic understanding was applied to interpret the narratives and gain insight to the psychological processes and experiences described by these women through their storytelling. Findings: The reawakening of psychic conflicts and fantasies were identified in stories of the birth. Expectations were constructed using previous experience, social discourses and individual psychological processes. Realities often differed to the fantasies constructed in pregnancy. Stories of immobility during pregnancy and when encumbered with the extra equipment needed for life with two young children gave an understanding of the sense of availability and use of the womens’ space – taking it up physically and losing it psychologically. Implications: The study has shown that having a second child enables experience to contribute to a second awakening of inner conflict, fears and fantasies. Whilst this may mediate expectations it does not preclude an uninvited recurrence of psychic processes already experienced first time around or unexpected realities of having a second child.
EEG-fMRI signatures of spontaneous brain activity in healthy volunteers and epilepsy patients

Background: Functional magnetic resonance imaging (fMRI) provides maps of haemodynamic activity with uniform resolution across the brain. Simultaneous recording of electroencephalography (EEG) during fMRI (EEG-fMRI) was developed to localize spontaneously occurring epileptiform discharges. In focal epilepsy, it can identify candidate brain regions for surgical removal as a treatment option in medically refractory epilepsy; and in generalized epilepsy syndromes reveals those involved during the EEG changes. In healthy subjects, EEG-fMRI has linked spontaneous ongoing EEG activity with fMRI resting state networks. Methods: After method refinements, patients with medically refractory focal epilepsy and those with generalized epilepsy were studied with EEG-fMRI and group analyses performed to identify typical sets of brain regions involved in the epileptic process. Findings: In individual patients with refractory focal epilepsy, EEG-fMRI can produce activity maps including the seizure onset zone and propagated epileptic activity. Clinically, these can be confirmatory of results from alternative diagnostic techniques, or alternatively serve to generate a hypothesis on the potential epileptic focus, but under certain conditions may also be of negative predictive value with respect to surgical treatment success. At the group level in patients with temporal lobe epilepsy and complex partial seizures as well as in patients with generalized epilepsy and absence seizures, altered resting state network activity during EEG changes were found in default mode brain regions fitting well the ictal semiology, because these are known to reduce their activity during states of reduced consciousness. In (1) lateralized temporal lobe epilepsies, (2) an unselected mix of focal epilepsies, and (3) generalized epilepsies, activity increases occurred in typical brain regions suggesting an associated “hub function”, namely ipsilateral to the presumed cortical focus in the hippocampus; in an area near the frontal piriform cortex; and bilaterally in the thalamus, respectively. These findings argue for a network rather than a zone concept of epilepsy.
Alterations in cardiac SR Ca 2 1-release channels during development of heart failure in cardiomyopathic hamsters

Ueyama, Takeshi, Tomoko Ohkusa, Yuji Hisamatsu, Yasuma Nakamura, Takeshi Yamamoto, Masafumi Yano, and Masunori Matsuzaki. Alterations in cardiac SR Ca21release channels during development of heart failure in cardiomyopathic hamsters. Am. J. Physiol. 274 (Heart Circ. Physiol. 43): H1–H7, 1998. —The cardiomyopathic Syrian hamster develops a progressive cardiomyopathy characterized by cellular necrosis, hypertrophy, cardiac dilatation, and congestive heart failure. This study aimed to identify alterations in cardiac mechanical function and in the cellular content of sarcoplasmic reticulum (SR) Ca21-release channels (ryanodine receptors, RyR) in the heart of the UM-X7.1 cardiomyopathic hamster during the development of heart failure. Experimental and healthy control hamsters were examined at 8, 18, and 28 wk of age. The UM-X7.1 hamsters had developed left ventricular (LV) hypertrophy at 8 wk and a marked LV dilatation at 18–28 wk. During the latter stage, the UM-X7.1 hamster hearts showed global hypokinesis. Equilibrium binding assays of high-affinity sites for [3H]ryanodine were performed in ventricular homogenate preparations. There was no significant difference between the two groups in the maximum number of [3H]ryanodine binding sites (Bmax) at either 8 or 18 wk of age, although the cardiac pump function was impaired in UM-X7.1 hamsters at 18 wk of age. By 28 wk, Bmax was significantly lower in the UM-X7.1 hamsters. Quantitative immunoblot assay revealed that the content of RyR protein in cardiomyopathic hearts, which was increased at the early stage, declined to below normal as heart failure advanced. These results suggest that the number of RyR in the UM-X7.1 cardiomyopathic hamsters was preserved at both the hypertrophic and early stages of heart failure with a possibly compensatory increase in the level of protein expression, although the cardiac function already showed a tendency to be impaired.
Schizophrenia and 22q11.2 Deletion Syndrome

22q11.2 deletion syndrome (22q11.2DS), also known as velocardiofacial syndrome, is the most frequent known interstitial deletion found in humans. It is associated with high rates of psychiatric disorder and, in particular, schizophrenia (approximately 30%) and schizophrenia-spectrum disorders. The 22q11.2 region is rich in genes coding for brain development, and consequently, deletion of 22q11.2 provides a useful neurodevelopmental model for understanding the evolution of psychotic disorders in both 22q11.2DS and the nondeleted general population. 22q11.2DS is also associated with significant structural and functional neuroanatomical abnormalities, which underlie the high rates of psychosis seen in affected individuals. Further research is currently underway to determine the cognitive, genetic and neuroanatomical correlates of psychosis seen in the disorder. Key Concepts: 22q11.2DS provides for a genetic and neurodevelopmental model for understanding psychotic disorder seen not only with the syndrome but can also be extrapolated to the general nondeleted population. Although 22q11.2DS is associated with marked phenotypic variability, psychiatric disorder and, in particular, schizophrenia-spectrum disorders occur in approximately 30% of deleted individuals. Schizophrenia-spectrum disorders arise as prodromal or subthreshold psychotic symptoms during childhood and adolescence followed by subsequent expression during adulthood where it is largely indistinguishable from the psychosis seen in the nondeleted population. Apart from being the monozygotic co-twin of a proband with psychosis or being the offspring of parents with schizophrenia, 22q11.2 deletion is the highest known risk factor for the development of schizophrenia. Keywords: VCFS; velocardiofacial syndrome; schizophrenia; chromosome 22q11; psychosis; 22q11DS
Generalized dynamic inversion for multiaxial nonlinear flight control

The nonlinear problem of aircraft trajectory track ing is tackled in the framework of multiple linear time-varying constrained control using the newly developed paradigm of generalized dynamic inversion. The time differential forms of the multiple constraints encapsulate the control objectives, and are inverted to obtain the reference trajectory-realizing control law. The inversion process utilizes the Moore-Penrose generalized inverse, and it predictably involves the problematic generalized inversion singularity. Thus, a singularity avoidance scheme based on a new type of dynamic scaling factors is introduced that guarantees asymptotically stable tracking and singularity avoidance. The steady state closed loop system allows for two inherently noninterfering control actions working towards a unified goal to exploit the aircraft's control authority over the entire state space. One control action is performed on the range space of the constraint generalized inverse matrix, and it works to impose the prescribed aircraft constrained dynamics. The other control action is performed on the complementary orthogonal nullspace of the constraint matrix, and it provides aircraft's global inner stability using a novel type of dynamically scaled nullprojection control Lyapunov functions. Numerical simulations of a multiaxial aircraft coordinated maneuver verify the efficacy of designing nonlinear flight control systems via this technique.
A methodology for parameter estimation of equivalent wind power plant

A methodology for parameter estimation of equivalent wind power plant is proposed in this paper. The parameter algorithm is formulated as an optimization problem which miminize the output between the real system and the mathematical model. The parameters are updated using Newton-Raphson method which depends on the information of trajectory sensitivity functions. A generic equivalent of wind power plant was used as a structure of the model, which is valid for Double-Fed Induction Generator (DFIG) and full Converter Based Wind Turbine. In addition, the procedure to obtain of the trajectory sensitivity functions of the model is presented in this paper. A discussion of the estimated results is also analysed. In general, the convergence happened in a few seconds for most of the cases studied.
Index wiki database: design and experiments

With the fantastic growth of Internet usage, information search in documents of a special type called a "wiki page" that is written using a simple markup language, has become an important problem. This paper describes the software architectural model for indexing wiki texts in three languages (Russian, English, and German) and the interaction between the software components (GATE, Lemmatizer, and Synarcher). The inverted file index database was designed using visual tool DBDesigner. The rules for parsing Wikipedia texts are illustrated by examples. Two index databases of Russian Wikipedia (RW) and Simple English Wikipedia (SEW) are built and compared. The size of RW is by order of magnitude higher than SEW (number of words, lexemes), though the growth rate of number of pages in SEW was found to be 14% higher than in Russian, and the rate of acquisition of new words in SEW lexicon was 7% higher during a period of five months (from September 2007 to February 2008). The Zipf's law was tested with both Russian and Simple Wikipedias. The entire source code of the indexing software and the generated index databases are freely available under GPL (GNU General Public License).
Verbal encouragement: effects on maximum effort voluntary muscle: action

Objective To examine the effects of verbal encouragement on the peak force of the elbow flexors during an isometric muscle action. Methods A crossover design whereby 20 subjects were divided into 10 2×2 Latin squares was undertaken. Peak forces were measured on a Kin-Com dynamometer, and electromyographic (EMG) activity was also recorded from the biceps brachii. All subjects completed trials with and without verbal encouragement. Results Mean peak force increased (P<0.05) from 296 to 311 N (5%) when verbal encouragement was presented. A spectral analysis of the EMG activity showed no changes (P>0.05) to the median frequency in the condition where verbal encouragement was present. Conclusions These findings have ramifications for training and exercise therapy. An awareness of the effects of verbal encouragement is important when motivating athletes and patients to attain maximum performance during exercise.
Recovery of People with Mental Illness: Philosophical and Related Perspectives

Preface: background and overview About the authors Overview of Chapter 1 1. Introduction SECTION 1: FIRST PERSON ACCOUNTS IN RELATION TO RECOVERY 2. Life beyond psychiatry 3. A wellness approach to mental health recovery 4. Families and patients with mental illness - on the recovery road SECTION 2: HISTORICAL, EPISTEMOLOGICAL AND METAPHYSICAL ASPECTS OF RECOVERY OF PEOPLE WITH MENTAL ILLNESS 5. Benevolence and discipline: the concept of recovery in early 19th century moral treatment 6. The epistemological basis of personal recovery 7. Contrasting conceptualizations of recovery imply distinct research methodology 8. Cultural contexts and constructions of recovery 9. Recovery and hope in relation to schizophrenia 10. Recovery, narrative theory and generative madness 11. From being subjected to being a subject: recovery in relation to schizophrenia SECTION 3: JUSTICE AND OTHER ETHICAL ASPECTS OF RECOVERY OF PEOPLE WITH MENTAL ILLNESS 12. Some social science antinomies and their implications for the recovery-oriented approach to mental illness and psychiatric rehabilitation 13. Recovery and the partitioning of scientific authority in psychiatry 14. Being ill and getting better: recovery and accounts of disorder 15. Is recovery a model? 16. Considering recovery as a process: or, life is not an outcome 17. Recovery and stigma: issues of social justice 18. Recovery and advocacy: contextualising justice in relation to recovery from mental illness in East Asia 19. Ethical and related practical issues faced by recovery-oriented mental health care providers: a risk-benefit analysis
Code Acquisition at Low SINR in Spread Spectrum Communications

We consider the problem of code acquisition at low signal to interference and noise ratio (SINR) in packet-based spread spectrum communications, where a centralized "pilot" synchronization signal and high-precision oscillators are not available. Such problems arise in the context of ad-hoc networks, for example, which require fast code acquisition times and gradual degradation of the network with decreasing SINR. We motivate the use of the "postdetection integration" approach, which utilizes the energy of multiple bits in a packet, for code acquisition at low SINR. We present the implementation of a fully parallel architecture which simultaneously looks at all possible code alignments over multiple bits. This leads to a drastic reduction in acquisition time compared to serial search based methods. We report some preliminary simulation and experimental results from a hardware prototype of a transceiver on which the code acquisition algorithm was implemented
Reducing the number of features for seizure prediction of spectral power in intracranial EEG

A low-powered implantable device that could detect a pre-seizure state using intracranial EEG (iEEG) could provide significant improvement in quality of life for people with epilepsy. In our previous work, we proposed a prediction algorithm using 27-54 linear features of spectral power and nonlinear support vector machine (SVM) classification. Though the algorithm can produce high prediction rate, it may suffer from its high complexity and may not be feasible for an implantable device. In this study, we have lowered the complexity of the algorithm by examining small numbers of key features and replacing the nonlinear SVM with linear one. The key features for seizure prediction have been determined using a method of two-step recursive feature elimination using SVMs (RFE SVM). The proposed reduced-complexity algorithm uses 6 or 9 key features of spectral power, the linear SVM, and a 20-point moving-average postprocessing filter. It has been out-of-sample tested on 9 subjects on the Freiburg database that we demonstrated high prediction rate with the full 27-54 features in our previous work. The reduced-complexity algorithm with 6 time-differential features has demonstrated high sensitivity of 100.0% (38 of total 38 preictal events), low false positive (FP) rate of 0.15 per hour (total 32 FPs), and FP time of 9.65% (21.0-hour) in the 217.5-hour interictal recordings. With 9 time-differential key features, it has achieved sensitivity of 97.4% (37/38), FP rate of 0.11/hour (25 FPs), and FP portion of 6.95% (15.1-hour). The proposed algorithm demonstrates that high prediction rate can be maintained while significantly lowering complexity. Our proposed methods for reducing complexity can be expanded to other biomedical engineering applications, especially where key feature determination with respect to accuracy and complexity is necessary.
VESICLE: Volumetric Evaluation of Synaptic Inferfaces using Computer Vision at Large Scale

An open challenge problem at the forefront of modern neuroscience is to obtain a comprehensive mapping of the neural pathways that underlie human brain function; an enhanced understanding of the wiring diagram of the brain promises to lead to new breakthroughs in diagnosing and treating neurological disorders. Inferring brain structure from image data, such as that obtained via electron microscopy (EM), entails solving the problem of identifying biological structures in large data volumes. Synapses, which are a key communication structure in the brain, are particularly difficult to detect due to their small size and limited contrast. Prior work in automated synapse detection has relied upon time-intensive biological preparations (post-staining, isotropic slice thicknesses) in order to simplify the problem. This paper presents VESICLE, the first known approach designed for mammalian synapse detection in anisotropic, non-post-stained data. Our methods explicitly leverage biological context, and the results exceed existing synapse detection methods in terms of accuracy and scalability. We provide two different approaches - one a deep learning classifier (VESICLE-CNN) and one a lightweight Random Forest approach (VESICLE-RF) to offer alternatives in the performance-scalability space. Addressing this synapse detection challenge enables the analysis of high-throughput imaging data soon expected to reach petabytes of data, and provide tools for more rapid estimation of brain-graphs. Finally, to facilitate community efforts, we developed tools for large-scale object detection, and demonstrated this framework to find $\approx$ 50,000 synapses in 60,000 $\mu m ^3$ (220 GB on disk) of electron microscopy data.
Integrating vision and speech for conversations with multiple persons

An essential capability for a robot designed to interact with humans is to show attention to the people in its surroundings. To enable a robot to involve multiple persons into interaction requires the maintenance of an accurate belief about the people in the environment. In this paper, we use a probabilistic technique to update the knowledge of the robot based on sensory input. In this way, the robot is able to reason about the uncertainty in its belief about people in the vicinity and is able to shift its attention between different persons. Even people who are not the primary conversational partners are included into the interaction. In practical experiments with a humanoid robot, we demonstrate the effectiveness of our approach.
An effective design technique to reduce leakage power

Now a day's low power Design is a essential requirement for This electronic document is a “live” template. The various components of your paper [title, text, heads, etc.] are already defined on the style hardware implementation. Technology moving into deep submicron region causes increase in leakage power. MTCMOS is promising technique for reducing leakage power but use of this technique results in delay overhead in active mode and data retention problem for sequential circuit. This paper propose a design technique for reducing the leakage power and data loss problem during sleep mode. Simulation results show that reduction in leakage power while preserving the state of the circuit.
Emulating TCP (A Reliable Internet Protocol) Using a Fixed Point Algorithm

The feedback nature of reliable Internet protocols can be represented by a fixed point algorithm (FPA). The network signals congestion based on the aggregate traffic offered to it and each source adjusts its sending rate based on the feedback from the network to reach the network operating regime. The algorithms of reliable (transport) protocols are based on this fact. The FPA has been one of the most useful ways of solving analytical models of Internet performance. Apart from implementing the FPA for simple networks with few bottleneck links, no implementation algorithm of this complex procedure is given to the best of our knowledge. In this paper the author develops an implementation algorithm of the FPA for analytical models of the transmission control protocol (TCP) which is the most widely used transport protocol on the Internet and show how the FPA emulates TCP. Even though the algorithm considers TCP it can be easily generalized to any reliable Internet protocol. The implementation algorithm can be used to develop efficient and comprehensive analytical tools for the performance investigation of networks (the Internet) with an arbitrary number of bottleneck links and sources. Such tools help to analyze existing protocols and propose more efficient ones. In this paper the author also briefly discuss important ideas which can be used to prove the convergence of the FPA (and hence TCP) and the uniqueness of the fixed points. These ideas can be used to easily study the stability of the TCP protocol. Unlike previous proofs of convergence which apply to only specific network scenarios, our approach applies to different network scenarios