Miracle-dz/UniFAR-FTUs huggingface dataset:
Choice of Routes in Congested Traffic Networks: Experimental Tests of the Braess Paradox

The Braess Paradox consists of showing that, in equilibrium, adding a new link that connects two routes running between a common origin and common destination may raise the travel cost for each network user. We report the results of two experiments designed to study whether the paradox is behaviorally realized in two simulated traffic networks that differ from each other in their topology. Both experiments include relatively large groups of participants who independently and repeatedly choose travel routes in one of two types of traffic networks, one with the added links and the other without them. Our results reject the hypothesis that the paradox is of marginal value and its force diminishes with experience. Rather, they strongly support the alternative hypothesis that with experience in traversing the networks financially motivated players converge to choosing the equilibrium routes in the network with added capacity despite sustaining a sharp decline in earnings.
Linear Pre-Coding Performance in Measured Very-Large MIMO Channels

Wireless communication using very-large multiple-input multiple-output (MIMO) antennas is a new research field, where base stations are equipped with a very large number of antennas as compared to previously considered systems. In theory, as the number of antennas increases, propagation properties that were random before start to become deterministic. Theoretical investigations with independent identically distributed (i.i.d.) complex Gaussian (Rayleigh fading) channels and unlimited number of antennas have been done, but in practice we need to know what benefits we can get from very large, but limited, number of antenna elements in realistic propagation environments. In this study we evaluate properties of measured residential-area channels, where the base station is equipped with 128 antenna ports. An important property to consider is the orthogonality between channels to different users, since this property tells us how advanced multi-user MIMO (MU-MIMO) pre-coding schemes we need in the downlink. We show that orthogonality improves with increasing number of antennas, but for two single-antenna users there is very little improvement beyond 20 antennas. We also evaluate sum-rate performance for two linear pre-coding schemes, zero-forcing (ZF) and minimum mean squared error (MMSE), as a function of the number of base station antennas. Already at 20 base station antennas these linear pre-coding schemes reach 98% of the optimal dirty-paper coding (DPC) capacity for the measured channels.
Clinical and Histopathological Features of Patients with Systemic Sclerosis Undergoing Endomyocardial Biopsy

Background Cardiac involvement in systemic sclerosis (SSc) is associated with a variable phenotype including heart failure, arrhythmias and pulmonary hypertension. The aim of the present study was to evaluate clinical characteristics, histopathological findings and outcome of patients with SSc and a clinical phenotype suggesting cardiac involvement. Methods and Results 25 patients with SSc and clinical signs of cardiac involvement were included between June 2007 and December 2010. They underwent routine clinical work-up including laboratory testing, echocardiography, left and right heart catheterization, holter recordings and endomyocardial biopsy. Primary endpoint (EP) was defined as the combination of cardiovascular death, arrhythmic endpoints (defined as appropriate discharge of implantable cardioverter defibrillator (ICD)) or rehospitalization due to heart failure. The majority of patients presented with slightly impaired left ventricular function (mean LVEF 54.1±9.0%, determined by echocardiography). Endomyocardial biopsies detected cardiac fibrosis in all patients with a variable area percentage of 8% to 32%. Cardiac inflammation was diagnosed as follows: No inflammation in 3.8%, isolated inflammatory cells in 38.5%, a few foci of inflammation in 30.8%, several foci of inflammation in 15.4%, and pronounced inflammation in 7.7% of patients. During follow up (FU) (22.5 months), seven (28%) patients reached the primary EP. Patients with subsequent events showed a higher degree of fibrosis and inflammation in the myocardium by trend. While patients with an inflammation grade 0 or 1 showed an event rate of 18.2%, the subgroup of patients with an inflammation grade 2 presented with an event rate of 25% versus an event rate of 50% in the subgroup of patients with an inflammation grade 3 and 4, respectively (p=0.193). Furthermore, the subgroup of patients with fibrosis grade 1 showed an event rate of 11%, patients with fibrosis grade 2 and 3 presented with an event rate of 33% and 42% respectively (p = 0.160). Conclusions Patients with SSc and clinical signs of cardiac involvement presented with mildly impaired LVEF. Prognosis was poor with an event rate of 28% within 22.5 months FU and was associated with the degree of cardiac inflammation and fibrosis.
LQG control of large networks: A clustering-based approach

In this paper we present a Linear Quadratic Gaussian (LQG) control design for large-dimensional network dynamic systems using the idea of network clustering. When networks have tens of thousands of nodes spread over a wide geographical span, the design of conventional output feedback controllers becomes numerically challenging, and their implementation requires a large number of communication links. Our proposed algorithm bypasses these difficulties by clustering the network nodes using structural properties of its closed-loop transfer matrix. The cluster assignment is applied for constructing a structured projection matrix P, which is used to pose a significantly lower-dimensional controller design. The problem is, therefore, posed in terms of finding the optimal set of clusters or P that minimizes the ℋ2-norm of the error between the transfer matrices of the full-order network with a conventional LQG controller and that with the projected LQG controller. We derive an upper bound on this error as a function of P, and design a P that minimizes this bound.
Improving the Accuracy of Document Similarity Approach using Word Sense Disambiguation

The aspects of Artificial Intelligence and statistics such as Text mining, Data Mining can provide solutions to the area of concept mining. It provides powerful insights into the meaning and documents similarity without exploiting the semantics of the terms or phrases in the document. Our work determines the similarity of documents using semantic processing namely Word Sense Disambiguation by annotating the senses of the words in the documents and then performs traditional PageRank algorithm over it. The Algorithm ranks the possible senses and finds the correct sense according to the context. Our paper proposes the method of disambiguating the ambiguous words in order to find the document similarity. Moreover it is compared with the cosine similarity approach, which is frequently used to determine similarity between two documents to prove the accuracy of our work.
Identification of key genes and pathways associated with spinal cord injury

The present study was designed to identify key genes or significant signaling pathways associated with spinal cord injury (SCI), and to clarify the underlying molecular mechanisms of SCI. Data from the GSE45550 array were downloaded from the Gene Expression Omnibus database. A total of 6 control samples, 6 samples at 3 days post-SCI (SCI3d), 6 samples at 8 days post-SCI (SCI8d) and 6 samples at 14 days post-SCI (SCI14d) were included. The microarray data was preprocessed by the robust multi-array average algorithm. The differentially expressed genes (DEGs) were identified using the limma package. The overlapping DEGs among groups were analyzed using the Venny 2.0 online tool. Modules enriched by DEGs were selected by weighted gene co-expression network analysis. Gene Ontology annotation and the Kyoto Encyclopedia of Genes and Genomes pathways were identified for DEGs using the Database for Annotation, Visualization and Integrated Discovery. A total of 693 genes were obtained by combining the DEGs of the SCI3d, SCI8d and SCI14d groups. The pink module and green module with smaller P-values obtained from weighted gene co-expression network analysis module analyses of DEGs demonstrated a higher correlation with SCI. In addition, the peroxisome proliferator-activated receptor (PPAR) signaling pathway that the cluster of differentiation 36 (CD36) was significantly enriched in, was one of the significant pathways in the pink module. The p53 signaling pathway that Caspase-3 (Casp3) was significantly enriched in was one of the significant pathways in the green module. In conclusion, the results of the present study demonstrated that the PPAR and p53 signaling pathway may serve important roles in the progression of SCI. In addition, CD36 and Casp3 may be involved in the progression of SCI via the PPAR and p53 signaling pathways, respectively.
Predicting current and future biological invasions: both native and invaded ranges matter

The classical approach to predicting the geographical extent of species invasions consists of training models in the native range and projecting them in distinct, potentially invasible areas. However, recent studies have demonstrated that this approach could be hampered by a change of the realized climatic niche, allowing invasive species to spread into habitats in the invaded ranges that are climatically distinct from those occupied in the native range. We propose an alternative approach that involves fitting models with pooled data from all ranges. We show that this pooled approach improves prediction of the extent of invasion of spotted knapweed (Centaurea maculosa) in North America on models based solely on the European native range. Furthermore, it performs equally well on models based on the invaded range, while ensuring the inclusion of areas with similar climate to the European niche, where the species is likely to spread further. We then compare projections from these models for 2080 under a severe climate warming scenario. Projections from the pooled models show fewer areas of intermediate climatic suitability than projections from the native or invaded range models, suggesting a better consensus among modelling techniques and reduced uncertainty.
Pulse contour cardiac output derived from non‐invasive arterial pressure in cardiovascular disease

Pulse contour methods determine cardiac output semi‐invasively using standard arterial access. This study assessed whether cardiac output can be determined non‐invasively by replacing the intra‐arterial pressure input with a non‐invasive finger arterial pressure input in two methods, Nexfin CO‐trek® and Modelflow®, in 25 awake patients after coronary artery bypass surgery. Pulmonary artery thermodilution cardiac output served as a reference. In the supine position, the mean (SD) differences between thermodilution cardiac output and Nexfin CO‐trek were 0.22 (0.77) and 0.44 (0.81) l.min−1, for intra‐arterial and non‐invasive pressures, respectively. For Modelflow, these differences were 0.70 (1.08) and 1.80 (1.59) l.min−1, respectively. Similarly, in the sitting position, differences between thermodilution cardiac output and Nexfin CO‐trek were 0.16 (0.78) and 0.34 (0.83), for intra‐arterial and non‐invasive arterial pressure, respectively. For Modelflow, these differences were 0.58 (1.11) and 1.52 (1.54) l.min−1, respectively. Thus, Nexfin CO‐trek readings were not different from thermodilution cardiac output, for both invasive and non‐invasive inputs. However, Modelflow readings differed greatly from thermodilution when using non‐invasive arterial pressure input.
Individual Mining and Prediction of Patterns for Improving Mobile Commerce

commerce is a new frontier.It involves the purchase transactions based on a mobile device.The mining and prediction of patterns can suggest stores that are more similar to his/her previous patterns mined and unknown to a customer.In this paper we propose a framework for pattern mining and prediction which is different from all previous perspectives.The difference is advantageous to the user mainly, when a user has no patterns to mine, that is a new customer. To improve mobile commerce, we propose a credit point system. This work enables the user to motivate the purchasing skills, thereby improving mobile commerce. We perform experiments based on various performance metrics and show that it can achieve good results.
Noise Robust Formant Frequency Estimation Method Based on Spectral Model of Repeated Autocorrelation of Speech

In this paper, a noise robust formant frequency estimation scheme is developed based on a spectral model matching algorithm. Considering the vocal tract as an autoregressive system, a spectral model of repeated autocorrelation function (RACF) of band-limited speech signal is proposed. It is shown that because of the repeated autocorrelation operation on band-limited signal, the proposed model can exhibit prominent formant characteristics. First from given noisy speech observations, an adaptive band selection criterion is developed. Next, on each resulting band-limited noisy speech signal, a repeated autocorrelation operation is carried out, which not only reduces the effect of noise but also strengthens the dominant poles corresponding to the formant frequencies. Finally, spectrum of the RACF is computed and instead of direct spectral peak picking, a model fitting scheme is introduced to find out model parameters which lead to formant estimation. The proposed algorithm has been tested on natural vowels as well as some naturally spoken sentences in the presence of different environmental noises. It is found that the proposed scheme provides better formant estimation accuracy in comparison to some of the existing methods at low levels of signal-to-noise ratio.
A Characteristic Velocity for Gas-Fed PPT Performance Scaling

The performance scaling of gas-fed pulsed plasma thrusters (GFPPTs) is investigated theoretically and experimentally. A characteristic velocity for GFPPTs that depends on the inductance-per-unit-length and the square root of the capacitance to initial inductance ratio has been identifled. An analytical model of the discharge current predicts the e‐ciency to be proportional to the GFPPT performance scaling number, deflned here as the ratio of the exhaust velocity to the GFPPT characteristic velocity. To test the validity of the predicted scaling relations, the performance of two rapid-pulse-rate GFPPT designs, PT5 (coaxial electrodes) and PT9 (parallel-plate electrodes), has been measured over 70 difierent operating conditions with argon propellant. The measurements demonstrate that the impulse bit scales linearly with the integral of the discharge current squared as expected for an electromagnetic accelerator. The measured performance scaling in both electrode geometries is shown to be in good agreement with theoretical predictions using the performance scaling number. Normalizing the exhaust velocity and the impulse-to-energy ratio by the GFPPT characteristic velocity collapses almost all the measured data onto single curves that represent the scaling relations for these GFPPTs.
Design and Modeling of a High-Speed AFM-Scanner

A new mechanical scanner design for a high-speed atomic force microscope (AFM) is presented and discussed in terms of modeling and control. The positioning range of this scanner is 13 mum in the X- and Y-directions and 4.3 mum in the vertical direction. The lowest resonance frequency of this scanner is above 22 kHz. This paper is focused on the vertical direction of the scanner, being the crucial axis of motion with the highest precision and bandwidth requirements for gentle imaging with the AFM. A second- and a fourth-order mathematical model of the scanner are derived that allow new insights into important design parameters. Proportional-integral (Pl)-feedback control of the high-speed scanner is discussed and the performance of the new AFM is demonstrated by imaging a calibration grating and a biological sample at 8 frames/s.
Alpha-actinin: a direct link between actin and integrins.

Introduction Cells use a variety of surface adhesion molecules to interact with other cells and with the extracellular matrix. When many types of adhesion molecules encounter a specific ligand they are capable of communicating signals across the membrane to the interior of the cell. Signalling via cell surface receptors leads to an assortment of events inside the cell which can ultimately regulate cell function. This review discusses our recent efforts to understand the process of transmembrane communication by studying how one class of adhesion molecules, the integrins, physically associate with components of the actin cytoskeleton. We will focus on our recent work which has identified a novel role for the actinbinding protein a-actinin as a direct link between actin and integrins.
Sequential Action of MalE and Maltose Allows Coupling ATP Hydrolysis to Translocation in the MalFGK2 Transporter*

Background: MalE and maltose together stimulate the ATPase activity of MalFGK2. Results: Binding of open-state MalE triggers the cleavage of ATP; maltose triggers the release of Pi. Conclusion: Open-state MalE stabilizes the transporter in the outward-facing conformation; maltose triggers return to the inward-facing state. Significance: The complementary action of MalE and maltose allows coupling ATP consumption to transport. ATP-binding cassette (ABC) transporters have evolved an ATP-dependent alternating-access mechanism to transport substrates across membranes. Despite important progress, especially in their structural analysis, it is still unknown how the substrate stimulates ATP hydrolysis, the hallmark of ABC transporters. In this study, we measure the ATP turnover cycle of MalFGK2 in steady and pre-steady state conditions. We show that (i) the basal ATPase activity of MalFGK2 is very low because the cleavage of ATP is rate-limiting, (ii) the binding of open-state MalE to the transporter induces ATP cleavage but leaves release of Pi limiting, and (iii) the additional presence of maltose stimulates release of Pi, and therefore increases the overall ATP turnover cycle. We conclude that open-state MalE stabilizes MalFGK2 in the outward-facing conformation until maltose triggers return to the inward-facing state for substrate and Pi release. This concerted action explains why ATPase activity of MalFGK2 depends on maltose, and why MalE is essential for transport.
Machine prediction of personality from Facebook profiles

An increasing number of Americans use social networking sites such as Facebook, but few fully appreciate the amount of information they share with the world as a result. Although studies exist on the sharing of specific types of information (photos, posts, etc.), one area that has been less explored is how Facebook profiles can share personality information in a broad, machine-readable fashion. In this study, we apply data-mining and machine learning techniques to predict users' personality traits (specifically, the traits of the Big Five personality model) using only demographic and text-based attributes extracted from their profiles. We then use these predictions to rank individuals in terms of the five traits, predicting which users will appear in the top or bottom 5% or 10% of these traits. Our results show that when using certain models, we can find the top 10% most Open individuals with nearly 75% accuracy, and across all traits and directions, we can predict the top 10% with at least 34.5% accuracy (exceeding 21.8%, which is the best accuracy when using just the best-performing profile attribute). These results have privacy implications in terms of allowing advertisers and other groups to focus on a specific subset of individuals based on their personality traits.
Do we need the h index and its variants in addition to standard bibliometric measures?

In this study, we investigate whether there is a need for the h index and its variants in addition to standard biblio-metric measures (SBMs). Results from our recent study 2008) have indicated that there are two types of indices: One type of indices (e.g., h index) describes the most productive core of a scientist's output and informs about the number of papers in the core.The other type of indices (e.g., a index) depicts the impact of the papers in the core. In evaluative bibliometric studies, the two dimensions quantity and quality of output are usually assessed using the SBMs " number of publications " (for the quantity dimension) and " total citation counts " (for the impact dimension). We additionally included the SBMs into the factor analysis. The results of the newly calculated analysis indicate that there is a high intercorrelation between " number of publications " and the indices that load substantially on the factor Quantity of the Productive Core as well as between " total citation counts " and the indices that load substantially on the factor Impact of the Productive Core. The high-loading indices and SBMs within one performance dimension could be called redundant in empirical application, as high intercorrelations between different indicators are a sign for measuring something similar (or the same). Based on our findings, we propose the use of any pair of indicators (one relating to the number of papers in a researcher's productive core and one relating to the impact of these core papers) as a meaningful approach for comparing scientists.
Performance analysis of synchronization algorithm based on the improved S-V channel model for UWB systems

Timing synchronization has been one of the largest challenges for Ultra-wideband (UWB) systems. To achieve the excellent performance, synchronization systems must have the characteristics of high speed, high accuracy and low complexity. In another literature, we have proposed a novel synchronization method, Multi-hypothesis Maximum Energy Path Acquisition (MH-MEPA) algorithm, based on the improved S-V channel model proposed by IEEE 802.15. 3a group to rapidly realize timing synchronization with high accuracy. To improve the MH-MEPA algorithm, the paper deduces the expressions of the probability of acquisition, mean acquisition time and the error probability and analyzes the effects of the time delay jitter on the detection probability, mean acquisition time and error probability. Simulation results show that the MH-MEPA algorithm outperforms the existing ones, i.e., achieving the smaller mean acquisition time, higher accuracy and lower error probability than others.
Incorporating shape into spatially-aware adaptive object segmentation algorithm

Semantically accurate segmentation of a particular Object Of Interest (OOI) in an image is an important but challenging step in computer vision tasks. Our recently proposed object-specific segmentation algorithm learns a model of the OOI which includes information on both the visual appearance of and the spatial relationships among the OOI components. However, its performance heavily depends on the assumption that the visual appearance variability among OOI instances is low. We present an extension to our algorithm that relaxes this assumption by incorporating shape information into the OOI model. Experimental results and an ANOVA-based statistical test confirm that the incorporation of shape has a highly significant positive effect on segmentation performance.