Miracle-dz/UniFAR-FTUs huggingface dataset:
Broadband Wireless Access From the Single Carrier MIMO Signal Processing Perspective

Iterative multiuser detection in single-carrier broadband multiple-input multiple-output (MIMO) system is studied in this paper. A minimum-mean-squared-error (MMSE) low complexity multiuser receiver is derived for space-division-multipleaccess (SDMA) space-time trellis coded (STTrC) systems in frequency selective fading channels. The receiver uses MMSE filtering to jointly detect several transmit antennas of the user of interest, while the interference from the undetected transmit antennas, co-channel interference (CCI) and inter-symbolinterference (ISI) are all cancelled by the soft cancellation. The performances of two extreme receiver cases are evaluated. In the first case only one transmit antenna of the user of interest is detected at a time and the remaining ones are cancelled by soft cancellation. In the second case all the transmit antennas are detected jointly. The comparison of the two cases shows the improvement with the latter one both in single user and multiuser communications and in the presence of unknown cochannel interference (UCCI). It is further shown that in the multiuser case the proposed receivers approach the corresponding singleuser bounds. The number of receive antenna elements required to achieve single-user bound is thereby equal to the number of users and not to the total number of transmit antennas. The receiver with joint antenna detection shows more robust performance to the spatial correlation than the antenna by antenna detection. BROADBAND WIRELESS ACCESS FROM THE SINGLE CARRIER MIMO SIGNAL PROCESSING PERSPECTIVE, Veselinovic N. , Matsumoto T. , Juntti M.
Neural Networks for Atmospheric Temperature Retrieval from AQUA AIRS / AMSU / HSB Measurements

The high spectral resolution sounding suite instruments on EOS Aqua are expected to provide estimated atmospheric profiles with higher accuracy and better vertical resolution. To validate and test it’s performance with it’s orbital measurements, temperature profiles at 101 pressure levels, up to 0.005 hPa, with 1km vertical resolution at troposphere, were retrieved on different types of terrain with different spectral bands in the middle latitude area by using a three-layered feed-forward neural networks with back-propagation algorithm. Results show that the Qinghai-Tibet Plateau has a measurable impact on the retrieval accuracy which is corresponding to the spectral bands used in performing retrievals. A promising approach to the elimination of this effect is to apply additional predictors which are non-satellite observed (e.g. surface altitude).
Oxidized Calmodulin Kinase II Regulates Conduction Following Myocardial Infarction: A Computational Analysis

Calmodulin kinase II (CaMKII) mediates critical signaling pathways responsible for divergent functions in the heart including calcium cycling, hypertrophy and apoptosis. Dysfunction in the CaMKII signaling pathway occurs in heart disease and is associated with increased susceptibility to life-threatening arrhythmia. Furthermore, CaMKII inhibition prevents cardiac arrhythmia and improves heart function following myocardial infarction. Recently, a novel mechanism for oxidative CaMKII activation was discovered in the heart. Here, we provide the first report of CaMKII oxidation state in a well-validated, large-animal model of heart disease. Specifically, we observe increased levels of oxidized CaMKII in the infarct border zone (BZ). These unexpected new data identify an alternative activation pathway for CaMKII in common cardiovascular disease. To study the role of oxidation-dependent CaMKII activation in creating a pro-arrhythmia substrate following myocardial infarction, we developed a new mathematical model of CaMKII activity including both oxidative and autophosphorylation activation pathways. Computer simulations using a multicellular mathematical model of the cardiac fiber demonstrate that enhanced CaMKII activity in the infarct BZ, due primarily to increased oxidation, is associated with reduced conduction velocity, increased effective refractory period, and increased susceptibility to formation of conduction block at the BZ margin, a prerequisite for reentry. Furthermore, our model predicts that CaMKII inhibition improves conduction and reduces refractoriness in the BZ, thereby reducing vulnerability to conduction block and reentry. These results identify a novel oxidation-dependent pathway for CaMKII activation in the infarct BZ that may be an effective therapeutic target for improving conduction and reducing heterogeneity in the infarcted heart.
Induced-strain multimorphs for microscale sensory actuation design

The paper proposes an analytic model that evaluates the levels of actuation and sensing by microbenders formed of several sandwiched layers (multimorphs) of active/sensitive materials such as piezoelectric (PZT) and shape memory alloys (SMA) interspersed with structural materials which only react to thermal variations. The model is generic, such that any type of induced strain can be incorporated into it, and its prediction gives the deformed (bent) shape, the corresponding tip bending moment, as well as the position of the neutral axis (NA) and the composite bending rigidity. The generic model reduces to the well-known Timoshenko ‘bi-metal thermostat’ model in the case of two layers of which one is thermally heated. Finite element simulation produces results that are very close to the analytic model predictions for a three-layer (trimorph) bender when all layers are heated. Concrete examples are further studied that can be encountered in small-scale (MEMS) applications, such as an antisymmetric PZT trimorph with either unilateral actuation and sensing or just antisymmetric actuation, a SMA-actuated bimorph and a hybrid PZT–SMA trimorph that can act as a simultaneous sensory actuator microdevice. Numerical simulations are performed for all examples in order to highlight trends in performance as a function of the microcantilever geometry.
Fusion of qualitative beliefs using DSmT

Florentin Smarandache Department of Mathematics University of New Mexico Gallup, NM 87301, U.S.A. smarand@unm.edu Jean Dezert ONERA 29 Av. de la Division Leclerc 92320 Châtillon, France. Jean.Dezert@onera.fr Abstract – This paper introduces the notion of qualitative belief assignment to model beliefs of human experts expressed in natural language (with linguistic labels). We show how qualitative beliefs can be efficiently combined using an extension of Dezert-Smarandache Theory (DSmT) of plausible and paradoxical quantitative reasoning to qualitative reasoning. We propose a new arithmetic on linguistic labels which allows a direct extension of classical DSm fusion rule or DSm Hybrid rules. An approximate qualitative PCR5 rule is also proposed jointly with a Qualitative Average Operator. We also show how crisp or interval mappings can be used to deal indirectly with linguistic labels. A very simple example is provided to illustrate our qualitative fusion rules.
Recent progress in GaInAsSb and InAsSbP photodetectors for mid-infrared wavelengths

Progress on mid-IR photodetectors fabricated by the liquid phase epitaxial growth of GaInAsSb and InAsSbP on GaSb and InAs substrates is reported. GaInAsSb p/n and p-i-n detectors and InAsSbP p/n detector structures were fabricated. Preliminary results indicate that these devices can have higher detectivity with lower cooling requirements than commercially available detectors in the same wavelength range. IR p/n junction detectors made from GaInAsSb and InAsSbP showed cut-off wavelengths of 2.3 micrometers and 2.9 micrometers respectively. Room temperature background noise- limited detectivity of 4 X 1010 cmHz1/2/W GaInAsSb detectors and 4 X 108 cmHz1/2/W for InAsSbP was measured.
Understanding physicians' intentions to withdraw from practice: The role of job satisfaction, job stress, mental and physical health

Health care organizations may incur high costs due to a stressed, dissatisfied physician workforce. This study proposes and tests a model relating job stress to four intentions to withdraw from practice mediated by job satisfaction and perceptions of physical and mental health. The test used a sample of 1735 physicians and generally supported the model. Given the movement of physicians into increasingly bureaucratic structures, the clinical work environment must be effectively managed.
Data stream mining based real-time highspeed traffic classification

In current high-speed network, Peer-to-Peer(P2P) applications have overtaken Web applications as the major contribution on the Internet. Thereby, how to identify P2P traffic in real-time accurately and efficiently is a key step for network management. In this paper, we highlight the importance of applying data stream method in traffic classification to achieve real-time P2P traffic identification. We not only introduce a VFDT-based real-time highspeed traffic classification method, but also take thoroughly analysis on how to select a reasonable tie confidence (TieC), minimum gathering flow (MinGF) and category number (CaNum). Meanwhile, analysis has been done to ascertain the packet's interval which is used to calculate flow's real-time attribute. Experiment results have shown that when TieC is less than threshold, the larger TieC is, the better accuracy of identification is; when TieC exceeds threshold, decision trees are the same. Concerning MinGF and CaNum, although the smaller both of them are, the better performance of decision tree is, the value of them must be properly set according to requirements of classification system.
Simple vector microprocessors for multimedia applications

In anticipation of the emergence of multimedia applications as an important workload, microprocessor companies have augmented their instruction-set architectures with short vector extensions, thus adding basic vector hardware to state-of-the-art superscalar processors. Although a vector architecture may be a good match for multimedia applications, there is growing evidence that the control logic for increasingly complex superscalar processors is difficult to implement, Rather than combining a complex superscalar core with short wide vector hardware, we propose using a much simpler processor design that is similar to traditional vector computers with long vectors and simple control logic for instruction issue. Such a design would use the bulk of its transistors and die area for datapath and registers, and thus lessen the time required to design, implement, and verify control. In this paper we present data that quantifies this trading of control transistors for datapath and register transistors. We demonstrate that a 2-way, in-order vector processor with a vector length of 64 and a vector width of 8 requires no more die area, and possibly significantly less area, than a 4-way, out-of-order superscalar processor with short vector extensions. Furthermore, we show that the simple long vector processor is, on average, 2.7 times faster executing multimedia applications than the superscalar processor; and 1.6 times faster than one with short vector extensions. To explain the reasons for the higher performance, we analyze execution time in terms of dynamic operation count and cycles per operation (CPO). A vector processor executes fewer operations by using vector instructions to stripmine a loop. Moreover, a long vector processor achieves a lower CPO by effectively using parallelism at both the operation and the instruction levels. Thus by reducing both terms of the CPO equation, the simple long vector processor achieves greater performance.
A cortical potential reflecting cardiac function

Emotional trauma and psychological stress can precipitate cardiac arrhythmia and sudden death through arrhythmogenic effects of efferent sympathetic drive. Patients with preexisting heart disease are particularly at risk. Moreover, generation of proarrhythmic activity patterns within cerebral autonomic centers may be amplified by afferent feedback from a dysfunctional myocardium. An electrocortical potential reflecting afferent cardiac information has been described, reflecting individual differences in interoceptive sensitivity (awareness of one's own heartbeats). To inform our understanding of mechanisms underlying arrhythmogenesis, we extended this approach, identifying electrocortical potentials corresponding to the cortical expression of afferent information about the integrity of myocardial function during stress. We measured changes in cardiac response simultaneously with electroencephalography in patients with established ventricular dysfunction. Experimentally induced mental stress enhanced cardiovascular indices of sympathetic activity (systolic blood pressure, heart rate, ventricular ejection fraction, and skin conductance) across all patients. However, the functional response of the myocardium varied; some patients increased, whereas others decreased, cardiac output during stress. Across patients, heartbeat-evoked potential amplitude at left temporal and lateral frontal electrode locations correlated with stress-induced changes in cardiac output, consistent with an afferent cortical representation of myocardial function during stress. Moreover, the amplitude of the heartbeat-evoked potential in the left temporal region reflected the proarrhythmic status of the heart (inhomogeneity of left ventricular repolarization). These observations delineate a cortical representation of cardiac function predictive of proarrhythmic abnormalities in cardiac repolarization. Our findings highlight the dynamic interaction of heart and brain in stress-induced cardiovascular morbidity.
Low-angle X-ray diffraction patterns of collagen

Measurements have been made of the intensities of up to 25 orders of the low-angle X-ray diffraction patterns of wet and dry collagen fibres from three different sources. From these data Patterson functions have been plotted, and using these curves, and the known results of electron microscopy as guides in making initial assumptions about the electron density distribution in collagen fibres, satisfactory interpretations of the diffraction patterns of wet and dry fibres have been reached. These results show that the conspicuous periodic raised bands seen in electron micrographs of metal-shadowed fibres change in length on wetting the fibres, while the regions between them are but little affected, and it is concluded that these bands are highly disordered regions in dry fibres, becoming more orderly on hydration, while the interbands are always well ordered. Some evidence has also been obtained for the existence of an axial periodicity of about 32·8 Å.
Characterization of Three L-Asparaginases from Maritime Pine (Pinus pinaster Ait.)

Asparaginases (ASPG, EC 3.5.1.1) catalyze the hydrolysis of the amide group of L-asparagine producing L-aspartate and ammonium. Three ASPG, PpASPG1, PpASPG2, and PpASPG3, have been identified in the transcriptome of maritime pine (Pinus pinaster Ait.) that were transiently expressed in Nicotiana benthamiana by agroinfection. The three recombinant proteins were processed in planta to active enzymes and it was found that all mature forms exhibited double activity asparaginase/isoaspartyl dipeptidase but only PpASPG1 was able to catalyze efficiently L-asparagine hydrolysis. PpASPG1 contains a variable region of 77 amino acids that is critical for proteolytic processing of the precursor and is retained in the mature enzyme. Furthermore, the functional analysis of deletion mutants demonstrated that this protein fragment is required for specific recognition of the substrate and favors enzyme stability. Potassium has a limited effect on the activation of maritime pine ASPG what is consistent with the lack of a critical residue essential for interaction of cation. Taken together, the results presented here highlight the specific features of ASPG from conifers when compared to the enzymes from angiosperms.
A Kalman filter approach to track fast impedance changes in electrical impedance tomography

In electrical impedance tomography (EIT), an estimate for the cross-sectional impedance distribution is obtained from the body by using current and voltage measurements made from the boundary. All well-known reconstruction algorithms use a full set of independent current patterns for each reconstruction. In some applications, the impedance changes may be so fast that information on the time evolution of the impedance distribution is either lost or severely blurred. Here, the authors propose an algorithm for EIT reconstruction that is able to track fast changes in the impedance distribution. The method is based on the formulation of EIT as a state-estimation problem and the recursive estimation of the state with the aid of the Kalman filter. The performance of the proposed method is evaluated with a simulation of human thorax in a situation in which the impedances of the ventricles change rapidly. The authors show that with optimal current patterns and proper parameterization, the proposed approach yields significant enhancement of the temporal resolution over the conventional reconstruction strategy.
Impaired generation of mature neurons by neural stem cells from hypomorphic Sox2 mutants

The transcription factor Sox2 is active in neural stem cells, and Sox2 `knockdown' mice show defects in neural stem/progenitor cells in the hippocampus and eye, and possibly some neurons. In humans, heterozygous Sox2 deficiency is associated with eye abnormalities, hippocampal malformation and epilepsy. To better understand the role of Sox2, we performed in vitro differentiation studies on neural stem cells cultured from embryonic and adult brains of `knockdown' mutants. Sox2 expression is high in undifferentiated cells, and declines with differentiation, but remains visible in at least some of the mature neurons. In mutant cells, neuronal, but not astroglial, differentiation was profoundly affected. β-Tubulin-positive cells were abundant, but most failed to progress to more mature neurons, and showed morphological abnormalities. Overexpression of Sox2 in neural cells at early, but not late, stages of differentiation, rescued the neuronal maturation defect. In addition, it suppressed GFAP expression in glial cells. Our results show an in vitro requirement for Sox2 in early differentiating neuronal lineage cells, for maturation and for suppression of alternative lineage markers. Finally, we examined newly generated neurons from Sox2 `knockdown' newborn and adult mice. GABAergic neurons were greatly diminished in number in newborn mouse cortex and in the adult olfactory bulb, and some showed abnormal morphology and migration properties. GABA deficiency represents a plausible explanation for the epilepsy observed in some of the knockdown mice, as well as in SOX2-deficient individuals.
Cost-Aware Cooperative Resource Provisioning for Heterogeneous Workloads in Data Centers

Recent cost analysis shows that the server cost still dominates the total cost of high-scale data centers or cloud systems. In this paper, we argue for a new twist on the classical resource provisioning problem: heterogeneous workloads are a fact of life in large-scale data centers, and current resource provisioning solutions do not act upon this heterogeneity. Our contributions are threefold: first, we propose a cooperative resource provisioning solution, and take advantage of differences of heterogeneous workloads so as to decrease their peak resources consumption under competitive conditions; second, for four typical heterogeneous workloads: parallel batch jobs, web servers, search engines, and MapReduce jobs, we build an agile system PhoenixCloud that enables cooperative resource provisioning; and third, we perform a comprehensive evaluation for both real and synthetic workload traces. Our experiments show that our solution could save the server cost aggressively with respect to the noncooperative solutions that are widely used in state-of-the-practice hosting data centers or cloud systems: for example, EC2, which leverages the statistical multiplexing technique, or RightScale, which roughly implements the elastic resource provisioning technique proposed in related state-of-the-art work.
A Framework to Balance Privacy and Data Usability Using Data Degradation

Personal data is a valuable asset for service providers. To collect such data, free services are offered to users, for whom the risk of loosing privacy by subscribing to a service is often not clear. Although the services are free in terms of money, the user does not know how much he or she actually pays for a given service when allowing his or her data to be collected, unaware of taking a significant privacy risk by doing so. In practice, this risk is even not taken into account when deciding how long the data will be retained; the service provider simply wants to optimize the total worth of the stored data by retaining the data as long as possible. In this paper, we express the privacy risk for the user in terms of such a retention period; the user wants to optimize its privacy by allowing the data to be retained as short as possible. Now, in stead of only considering the interests of the service provider, we argue that we should optimize the common interest of both parties, and present a framework to reason about worth and privacy to find such optimum. Going one step further, we refine and generalize limited retention to data degradation, which prescribes to store data in progressively less accurate forms. Data degradation gives users and service providers a fine grained control over the price to be paid, in terms of privacy risks, and to optimize their common interest: balancing privacy and data usability.
Scene emotion detection using closed caption based on hierarchical attention network

This paper proposes a method of emotion detection using closed caption. Closed caption is a one of the texts related with video contents, which can be obtained actual dialogue information. Emotion information in video contents has been used in various service such as video recommendation, video retrieval. To detect scene emotion, we apply hierarchical learning structure of closed caption, such as word-sentence-document. In this paper, we introduce scene emotion detection method based on bidirectional LSTM and hierarchical attention network model. In experiments, we show the results of emotion detection using closed caption which from Korean movie.
Parallel training of convolutional neural networks for small sample learning

We propose a parallel training framework of convolutional neural networks (CNNs) for small sample learning. In the framework we model the feature filter process and show Sadowsky energy distribution exists in the model. Using Sadowsky energy distribution, the weights in convolutional kernels can be rearranged after each update according to special cases. With this rearrangement, each CNNs in the framework has different predicted probability especially for easily misclassified samples, which avoids the situation of a low predicted probability traditional CNNs may have. The class that gets the maximum predicted probability among the CNNs would be chosen as the result of prediction. Our CNNs framework gives better hand-written digit classification for small samples than one-stage CNNs, and has a faster convergence rate than multiplestages CNNs.
Frequency doubling with KNbO(3) in an external cavity.

Potassium niobate is employed in an external resonator to generate single-frequency tunable radiation near 430 nm. For excitation with 1.35 W of power from a cw titanium-sapphire laser, 0.65 W of blue light is produced. A simple model has been developed to account for thermal lensing in the nonlinear crystal.