Miracle-dz/UniFAR-FTUs huggingface dataset:
Estimation of joint angle based on surface electromyogram signals recorded at different load levels

To control upper-limb exoskeletons and prostheses, surface electromyogram (sEMG) is widely used for estimation of joint angles. However, the variations in the load carried by the user can substantially change the recorded sEMG and consequently degrade the accuracy of joint angle estimation. In this paper, we aim to deal with this problem by training classification models using a pool of sEMG data recorded from all different loads. The classification models are trained as either subject-specific or subject-independent, and their results are compared with the performance of classification models that have information about the carried load. To evaluate the proposed system, the sEMG signals are recorded during elbow flexion and extension from three participants at four different loads (i.e. 1, 2, 4 and 6 Kg) and six different angles (i.e. 0, 30, 60, 90, 120, 150 degrees). The results show while the loads were assumed unknown and the applied training data was relatively small, the proposed joint angle estimation model performed significantly above the chance level in both the subject-specific and subject-independent models. However, transferring from known to unknown load in the subject-specific classifiers leads to 20% to 32% loss in the average accuracy.
Tip-enhanced near-field optical microscopy on the quasi 1D semiconductors carbon nanotubes and CdSe nanowires

Optical microscopy is widely used to visualize small structures that can not be seen by the unaided human eye. On the nanoscale, however, the diffraction limit prevents conventional microscopy from studying materials with the required spatial resolution. This work reports on tip-enhanced near-field optical microscopy (TENOM), a technique that allows for nanoscale optical imaging with high detection sensitivity. It exploits the locally enhanced optical fields at a laser illuminated metal tip that acts as an optical antenna. The main aims of this work are to develop a better understanding of the signal enhancement mechanisms in TENOM and to apply the technique to different 1D semiconducting nanostructures, namely single-walled carbon nanotubes (SWCNTs) and cadmium selenide nanowires (CdSe NWs). In the first part, the angular distribution of photoluminescence (PL) emission from SWCNTs with and without the optical antenna is studied by imaging the back focal plane of the microscope objective. Using model calculations, it is shown that the PL of SWCNTs on a dielectric substrate can be described as emission from a single in-plane point dipole despite the quasi 1D structure of the nanotubes. The signal enhancement due to the antenna is connected to a substantial redistribution of the angular emission. A procedure for the individual quantification of the excitation and radiation rate enhancement factors is developed and applied to the experimental data. In the second part, nanoscale optical imaging of CdSe NWs using TENOM is presented for the first time. Spectrally resolved imaging reveals different band gaps for different NWs and variations of the PL energy and intensity along single NWs with energy gradients up to 1 meV/nm. Even bundled NWs can be spatially resolved by their PL and Raman signals. The third part reports on the angular and spectral emission properties of CdSe NWs and the tip-induced changes in a TENOM measurement. In contrast to SWCNTs, two perpendicularly oriented point dipoles are required to describe the angular intensity distribution of PL emission from CdSe NWs sufficiently. Again, tip-induced signal enhancement is accompanied by a spatial redistribution of the emission. The theoretical description is more complex than in the case of SWCNTs, because different radiating dipole orientations in the NW have to be taken into account that can interact with the tip. Finally, investigations of the tip-sample distance dependence of PL and Raman scattering are presented and discussed.
Secure End-To-End Data Transport in Quantum Networks

A secure end-to-end data transport protocol in quantum network is presented. A quantum network means we transport data by encoding a data into a certain quantum state on a qubit, and transmitting the qubit from sender to receiver. Because of the network scalability and physical technology limit in long distance teleportation, a fully connected quantum network model is impossible. Hence, in our quantum network model, the qubit is transported node by node to the receiver. However, this model arises two new security issues. The first is that intermediate nodes, which forward the qubit in the route, can snoop on information during the data transport. The second is that intermediate nodes can maliciously and illegally modify the transported qubit and forward it to the successor. In this paper, we present a protocol that can (1) prevent from snooping and (2) imperceptibly determine the node that maliciously modifies the transported data. By the presented protocol, we can transport information securely through the entire route in the quantum network.
Optimal Spectral Domain Selection for Maximizing Archaeological Signatures: Italy Case Studies

Different landscape elements, including archaeological remains, can be automatically classified when their spectral characteristics are different, but major difficulties occur when extracting and classifying archaeological spectral features, as archaeological remains do not have unique shape or spectral characteristics. The spectral anomaly characteristics due to buried remains depend strongly on vegetation cover and/or soil types, which can make feature extraction more complicated. For crop areas, such as the test sites selected for this study, soil and moisture changes within near-surface archaeological deposits can influence surface vegetation patterns creating spectral anomalies of various kinds. In this context, this paper analyzes the usefulness of hyperspectral imagery, in the 0.4 to 12.8 μm spectral region, to identify the optimal spectral range for archaeological prospection as a function of the dominant land cover. MIVIS airborne hyperspectral imagery acquired in five different archaeological areas located in Italy has been used. Within these archaeological areas, 97 test sites with homogenous land cover and characterized by a statistically significant number of pixels related to the buried remains have been selected. The archaeological detection potential for all MIVIS bands has been assessed by applying a Separability Index on each spectral anomaly-background system of the test sites. A scatterplot analysis of the SI values vs. the dominant land cover fractional abundances, as retrieved by spectral mixture analysis, was performed to derive the optimal spectral ranges maximizing the archaeological detection. This work demonstrates that whenever we know the dominant land cover fractional abundances in archaeological sites, we can a priori select the optimal spectral range to improve the efficiency of archaeological observations performed by remote sensing data.
Please Scroll down for Article Journal of Organizational Computing and Electronic Commerce Understanding the Determinants of User Acceptance of Enterprise Instant Messaging: an Empirical Study Understanding the Determinants of User Acceptance of Enterprise Instant Messaging: an Empirical Study

This article may be used for research, teaching and private study purposes. Any substantial or systematic reproduction, redistribution , reselling , loan or sub-licensing, systematic supply or distribution in any form to anyone is expressly forbidden. The publisher does not give any warranty express or implied or make any representation that the contents will be complete or accurate or up to date. The accuracy of any instructions, formulae and drug doses should be independently verified with primary sources. The publisher shall not be liable for any loss, actions, claims, proceedings, demand or costs or damages whatsoever or howsoever caused arising directly or indirectly in connection with or arising out of the use of this material. As modern organizations increasingly depend on information systems (IS) to enhance work productivity and seek new business opportunities, communication effectiveness has become one of the key factors that underlie the effective performance of IS implementations and applications. Instant Messaging (IM) presents a revolution in enterprise communication. As more organizations are findings ways to utilize this near-synchronous computing communication technology to enhance communication effectiveness in the workplace, there is a compelling need to understand the factors that are important for the adoption of enterprise IM. We have developed an integrative model based on constructs of the existing IT adoption models as well as theories on motivation, innovation diffusion, and critical mass. Using responses from 140 intended subjects, we have found the results of survey data support the contentions that perceived usefulness, compatibility, enjoyment, and security are significant predictors of intention to use enterprise IM. Although perceived connectivity did not predict the intention directly, it did indirectly through perceived usefulness and perceived ease of use. Implications and future research are discussed.
Minimum hypothesis phone error as a decoding method for speech recognition

In this paper we show how methods for approximating phone error as normally used for Minimum Phone Error (MPE) discriminative training, can be used instead as a decoding criterion for lattice rescoring. This is an alternative to Confusion Networks (CN) which are commonly used in speech recognition. The standard (Maximum A Posteriori) decoding approach is a Minimum Bayes Risk estimate with respect to the Sentence Error Rate (SER); however, we are typically more interested in the Word Error Rate (WER). Methods such as CN and our proposed Minimum Hypothesis Phone Error (MHPE) aim to get closer to minimizing the expected WER. Based on preliminary experiments we find that our approach gives more improvement than CN, and is conceptually simpler. Index Terms: Minimum Bayes Risk (MBR), MPE, Confusion Networks, Speech Recognition, Lattice Rescoring
Analysis of Alternating Overcurrent Response of 2G HTS Tape for SFCL

The scope of this article was to find the transient response of the 2G high-temperature superconducting (HTS) tape under alternating overcurrent. The authors performed a series of measurements for the SF12050 HTS tape produced by SuperPower Inc. The tape was fed by a 50-Hz ac voltage source with adjustable amplitude. The temporal dependences of the tape current and voltage drops in each test segment were recorded simultaneously. The measurements were performed for the current amplitudes exceeding the critical value specified by the manufacturer ( Ic = 270 A @77 K, self-field). The instantaneous values of the tape temperature during overcurrent transient period were also determined. Additionally, the numerical analysis of the SF12050 tape was performed. A numerical model was built using PSPICE environment. The model assumes the nonlinear dependence of tape parameters in the function of temperature, as well as the variable cooling conditions during transient state. The constructed model was verified with measurement results.
CARS: the CFHTLS-Archive-Research Survey - II. Weighing dark matter halos of Lyman-break galaxies at z = 3–5

Aims. We measure the clustering properties for a large samples of u- (z ~ 3), g- (z ~ 4), and r- (z ~ 5) dropouts from the Canada-France-Hawaii Telescope Legacy Survey (CFHTLS) Deep fields. Methods. Photometric redshift distributions along with simulations allow us to de-project the angular correlation measurements and estimate physical quantities such as the correlation length, halo mass, galaxy bias, and halo occupation as a function of UV luminosity. Results. For the first time we detect a significant one-halo term in the correlation function at z ~ 5 . The comoving correlation lengths and halo masses of LBGs are found to decrease with decreasing rest-frame UV-luminosity. No significant redshift evolution is found in either quantity. The typical halo mass hosting an LBG is M ≳ 10^(12)h^(-1) M⊙ and the halos are typically occupied by less than one galaxy. Clustering segregation with UV luminosity is clearly observed in the dropout samples, however redshift evolution cannot clearly be disentangled from systematic uncertainties introduced by the redshift distributions. We study a range of possible redshift distributions to illustrate the effect of this choice. Spectroscopy of representative subsamples is required to make high-accuracy absolute measurements of high-z halo masses.
Developmental Changes in the Metabolic Network of Snapdragon Flowers

Evolutionary and reproductive success of angiosperms, the most diverse group of land plants, relies on visual and olfactory cues for pollinator attraction. Previous work has focused on elucidating the developmental regulation of pathways leading to the formation of pollinator-attracting secondary metabolites such as scent compounds and flower pigments. However, to date little is known about how flowers control their entire metabolic network to achieve the highly regulated production of metabolites attracting pollinators. Integrative analysis of transcripts and metabolites in snapdragon sepals and petals over flower development performed in this study revealed a profound developmental remodeling of gene expression and metabolite profiles in petals, but not in sepals. Genes up-regulated during petal development were enriched in functions related to secondary metabolism, fatty acid catabolism, and amino acid transport, whereas down-regulated genes were enriched in processes involved in cell growth, cell wall formation, and fatty acid biosynthesis. The levels of transcripts and metabolites in pathways leading to scent formation were coordinately up-regulated during petal development, implying transcriptional induction of metabolic pathways preceding scent formation. Developmental gene expression patterns in the pathways involved in scent production were different from those of glycolysis and the pentose phosphate pathway, highlighting distinct developmental regulation of secondary metabolism and primary metabolic pathways feeding into it.
Research on Bearing Capacity of Short Concrete Filled Double Skin Steel Tubes Columns under Axial Compression

The use of steel tube confined concrete columns has been the interests of many structural engineers. For investigation of the axially loading capacity of short concrete filled double skin tubes (CFDST) columns, axial compression loading experiments were carried on 9 short CFDST column samples. According to experimental results and with numerical analysis, an ultimate load estimation equation of CFDST column with one correction parameter is presented, the linear relation between the parameter and the inner-to-outer diameters ratio Di/Do is given out. The ultimate load estimation equation is validated by the test results of short CFDST column samples.
Stokes polarimeter optimization in the presence of shot and Gaussian noise

Abstract: An error minimization method is presented for Stokes polarimeters applicable when the detected signals are affected by a combination of shot and Gaussian noise. The expectation of the Stokes vector variance is used as a performance measure. This measure is compared with the condition number of a polarization state analyzer matrix that is commonly used as a figure of merit. We show that a polarimeter with the minimum condition number is not necessarily optimal. The approach is used to optimize existing prism based polarimeters giving improvements in the performance when shot-noise cannot be neglected.
Toward trusted, social-aware D2D connectivity: bridging across the technology and sociality realms

Driven by the unprecedented increase of mobile data traffic, D2D communications technology is rapidly moving into the mainstream of the 5G networking landscape. While D2D connectivity originally emerged as a technology enabler for public safety services, it is likely to remain at the heart of the 5G ecosystem by spawning a wide diversity of proximate applications and services. In this work, we argue that the widespread adoption of the direct communications paradigm is unlikely without embracing the concepts of trust and social-aware cooperation between end users and network operators. However, such adoption remains conditional on identifying adequate incentives that engage humans and their connected devices in a plethora of collective activities. To this end, the mission of our research is to advance the vision of social-aware and trusted D2D connectivity, as well as to facilitate its further adoption. We begin by reviewing the various types of underlying incentives with the emphasis on sociality and trust, discuss these factors specifically for humans and for networked devices (machines), and also propose a novel framework allowing construction of much needed incentive-aware D2D applications. Our supportive system-level performance evaluations suggest that trusted and social-aware direct connectivity has the potential to decisively augment network performance. We conclude by outlining the future perspectives of its development across the research and standardization sectors.
The nine amino-terminal residues of delta-aminolevulinate synthase direct beta-galactosidase into the mitochondrial matrix

delta-Aminolevulinate synthase, the first enzyme in the heme biosynthetic pathway, is encoded by the nuclear gene HEM1. The enzyme is synthesized as a precursor in the cytoplasm and imported into the matrix of the mitochondria, where it is processed to its mature form. Fusions of beta-galactosidase to various lengths of amino-terminal fragments of delta-aminolevulinate synthase were constructed and transformed into yeast cells. The subcellular location of the fusion proteins was determined by organelle fractionation. Fusion proteins were found to be associated with the mitochondria. Protease protection experiments involving the use of intact mitochondria or mitoplasts localized the fusion proteins to the mitochondrial matrix. This observation was confirmed by fractionation of the mitochondrial compartments and specific activity measurements of beta-galactosidase activity. The shortest fusion protein contains nine amino acid residues of delta-aminolevulinate synthase, indicating that nine amino-terminal residues are sufficient to localize beta-galactosidase to the mitochondrial matrix. The amino acid sequence deduced from the DNA sequence of HEM1 showed that the amino-terminal region of delta-aminolevulinate synthase was largely hydrophobic, with a few basic residues interspersed.
Intuition and Reasoning in Choosing Ambiguous and Risky Lotteries

This paper focuses on information acquisition and individual decision making in ambiguous situations and presents a novel experimental design which may help to tackle open questions from a fresh perspective. Instead of giving subjects the choice between risky and ambiguous Ellsberg urns, we let them choose between a safe option and a risky lottery, whose risk is a priori unknown to subjects. By acquiring information about the probability distribution of the lottery’s payoffs, subjects can reduce or even eliminate the ambiguity and turn the decision situation into one of risk. Under the assumption that an ambiguity averse subject should reduce ambiguity within a decision process we predicted that these subjects would request more information. Moreover, we investigate whether the relation between attitudes towards risk and ambiguity is linked to intuitive and deliberate thinking. Based on a detailed analysis of subjects’ information acquisition and decision processes we do not find that those subjects showing ambiguity aversion in an urn experiment based on Halevy (2007) significantly reduce the ambiguity more than others. More intuitive subjects acquire less information and are more likely to avoid the risky lottery. Intuition seems to be negatively correlated with risk aversion, but not with ambiguity aversion. Moreover, we find a positive correlation between risk and ambiguity aversion.
System for robust 3D speaker tracking using microphone array measurements

A system for three-dimensional passive acoustic speaker localization and tracking using a microphone array is presented and evaluated. Initial speaker position estimates are provided by a time-delay-based localization algorithm. These raw estimates are spatially smoothed by a multiple model adaptive estimator consisting of three extended Kalman filters running in parallel. The performance of the proposed system is evaluated for real data in a common office environment. The reference trajectory of the moving speaker is delivered by visually tracking a color marker on the speaker's forehead by a stereo-camera system. The proposed acoustic source tracker shows robustness and accuracy in a variety of different scenarios.
Efficient pattern mapping for deterministic logic BIST

Deterministic logic BIST (DLBIST) is an attractive test strategy, since it combines advantages of deterministic external testing and pseudo-random LBIST. Unfortunately, previously published DLBIST methods are unsuited for large ICs, since computing time and memory consumption of the DLBIST synthesis algorithms increase exponentially, or at least cubically, with the circuit size. In this paper, we propose a novel DLBIST synthesis procedure that has nearly linear complexity in terms of both computing time and memory consumption. The new algorithms are based on binary decision diagrams (BDDs). We demonstrate the efficiency of the new algorithms for industrial designs up to 2M gates.
The clinical significance of SWI/SNF complex in pancreatic cancer

Chromatin remodeling factors have been the subject of great interest in oncology. However, little is known about their role in pancreatic cancer. The objective of this study was to clarify the clinical significance of the SWItch/sucrose nonfermentable (SWI/SNF) complex in patients with pancreatic cancer. A total of 68 patients with pancreatic cancer who underwent R0, 1 resection were enrolled. Cancer tissues were processed to tissue microarray, then stained immunohistochemically by using antibody of SWI/SNF components; BRM, BRG1, BAF250a, BAF180 and BAF47. The correlation of expression levels and clinicopathological outcomes were analyzed, followed by the multivariate analysis of prognostic factors for overall survival. The expression levels of the SWI/SNF components were categorized as low or high according to the median value of Histoscore. Statistical analysis revealed that BRM expression was related to tumor size, T factor, M factor, lymphatic invasion and stage BRG1 expression to histology and stage BAF180 expression to tumor size and BAF47 expression to lymphatic invasion, respectively. Multivariate Cox proportional hazard analysis showed that high BRM and low BAF180 expression levels were independent predictors of worse survival in patients with pancreatic cancer. High BRM, and low BAF180 were also independent prognostic factors for poor survival in the subgroup with adjuvant gemcitabine. These results suggest that the specific cofactors of SWI/SNF chromatin remodeling complex certainly have roles in pancreatic cancer. High BRM, and low BAF180 are useful biomarkers for poor prognosis in pancreatic cancer.