Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimizing quantize-map-and-forward in slow fading relay networks

Quantize-Map-and-Forward (QMF) relaying has been shown to achieve the optimal diversity-multiplexing tradeoff (DMT) for the slow fading single-antenna relay channel, regardless of whether the relay is full-duplex or half-duplex. A key reason for the DMT optimality is that quantizing at the noise level suffices to achieve the cut-set bound approximately and hence the relay does not need any instantaneous channel state information (CSI). However, DMT only captures the high SNR performance and potentially, limited CSI at the relay can help improve the performance in moderate SNR regimes. In this work we propose an optimization framework for QMF relaying in slow fading relay channels. Focusing on vector Gaussian quantizers, for the full-duplex relay we optimize the outage probability by finding the best quantization level according to the available CSI at the relay and the channel statistics. For the half-duplex relay we find good relay schedules using the same framework. Numerical evaluations show the improvement of taking the CSI into account over noise-level quantization and static schedules in moderate SNR regimes.
Extensions to optimistic concurrency control with time intervals

Although an optimistic approach has been shown to be better suited than locking protocols for real time database systems (RTDBS), it has the problems of unnecessary restarts and heavy restart overhead. The article identifies the unnecessary restart problem in OCC-TI (Optimistic Concurrency Control with Time Intervals), proposes a solution to this problem and demonstrates that the solution will produce a correct result. Additionally, two extensions to the basic dynamic adjustment of the serialization order conflict resolution method used in OCC-TI are proposed. Experiments with a prototype implementation of a real time database system show that the proposed method clearly outperforms the original OCC-TI.
PEA-15 Inhibits Tumorigenesis in an MDA-MB-468 Triple-Negative Breast Cancer Xenograft Model through Increased Cytoplasmic Localization of Activated Extracellular Signal-Regulated Kinase

Purpose: To determine the role of PEA-15 in breast cancer. Experimental Design: A reverse-phase protein array was used to measure PEA-15 expression levels in 320 human breast cancers; these levels were correlated with clinical and tumor characteristics. PEA-15 was overexpressed by an adenovirus vector or by stably expressing PEA-15 in different breast cancer cell lines. The effects on breast cancer cell survival and on the downstream apoptotic signaling pathway were measured in terms of cell proliferation (trypan blue for cell viability, bromodeoxyuridine incorporation for DNA synthesis), anchorage-independent growth (soft agar colony formation), and apoptosis (fluorescence-activated cell sorter analysis). The preclinical efficacy of Ad.PEA-15 given intratumorally was evaluated in nude mice bearing tumors from s.c. implanted human MDA-MB-468 triple-negative breast cancer cells. Results: In human breast cancers, low levels of PEA-15 expression correlated with high nuclear grade (P < 0.0001) and with negative hormone receptor status (P = 0.0004). Overexpression of PEA-15 in breast cancer cells resulted in growth inhibition, reduction in DNA synthesis, and onset of caspase-8–dependent apoptosis. In athymic nude mice bearing MDA-MB-468 xenografts, tumor volumes were significantly smaller in mice treated intratumorally with Ad.PEA-15 than in control mice (P < 0.0001). Tumors from mice treated with Ad.PEA-15 had increased levels of activated (phosphorylated) extracellular signal-regulated kinase and reduced levels of Ki-67 compared with tumors from nontreated or control-adenovirus–treated mice. Conclusion: PEA-15 has therapeutic potential in breast cancer. Further preclinical and clinical exploration of PEA-15 as a druggable target is warranted. Clin Cancer Res; 16(6); 1802–11
Mobile Antenna Using Multi-Resonance Feed Structure for Wideband Operation

A multi-resonance feed structure for exciting a mobile handset antenna in order to achieve multiband operation is presented. The feed structure adjusts its impedance and controls the coupling with the antenna structure. Based on the proposed feed structure, the dimensions allowed for the antenna design are only 10 × 55 × 2 mm 3 while the measured impedance bandwidth is from 694 to 1003 MHz in the lower band and from 1656 to 2772 MHz in the higher band under a voltage standing wave ratio of 3:1 with good measured realized efficiency. The proposed antenna is a competitive candidate that fully covers most 4th generation (4G) and existing wireless communication services.
Infectious Hepatitis C Virus Pseudo-particles Containing Functional E1–E2 Envelope Protein Complexes

The study of hepatitis C virus (HCV), a major cause of chronic liver disease, has been hampered by the lack of a cell culture system supporting its replication. Here, we have successfully generated infectious pseudo-particles that were assembled by displaying unmodified and functional HCV glycoproteins onto retroviral and lentiviral core particles. The presence of a green fluorescent protein marker gene packaged within these HCV pseudo-particles allowed reliable and fast determination of infectivity mediated by the HCV glycoproteins. Primary hepatocytes as well as hepato-carcinoma cells were found to be the major targets of infection in vitro. High infectivity of the pseudo-particles required both E1 and E2 HCV glycoproteins, and was neutralized by sera from HCV-infected patients and by some anti-E2 monoclonal antibodies. In addition, these pseudo-particles allowed investigation of the role of putative HCV receptors. Although our results tend to confirm their involvement, they provide evidence that neither LDLr nor CD81 is sufficient to mediate HCV cell entry. Altogether, these studies indicate that these pseudo-particles may mimic the early infection steps of parental HCV and will be suitable for the development of much needed new antiviral therapies.
Iconic and diagrammatic interfaces: an integrated approach

The authors first analyze the motivations for using a visual approach in querying a database. Afterwards they consider the two main visual expressions, i.e. icons and diagrams, used to represent both data and processes, together with their main advantages and limitations. Based on these conditions, they describe a man-machine interface, together with a visual query language, providing an integrated, both iconic and diagrammatic, approach. <<ETX>>
Vehicular Position Tracking Using LTE Signals

This paper proposes and validates, in the field, an approach for position tracking that is based on Long-Term Evolution (LTE) downlink signal measurements. A setup for real data live gathering is used to collect LTE signals while driving a car in the town of Rapperswil, Switzerland. The collected data are then processed to extract the received LTE cell-specific reference signals (CRSs), which are exploited for estimating pseudoranges. More precisely, the pseudoranges are evaluated by using the “ESPRIT and Kalman Filter for Time-of-Arrival Tracking” (EKAT) algorithm and by taking advantage of signal combining in the time, frequency, spatial, and cell ID domains. Finally, the pseudoranges are corrected for base station's clock bias and drift, which are previously estimated, and are used in a positioning filter. The obtained results demonstrate the feasibility of a position tracking system based on the reception of LTE downlink signals.
Effectiveness and Safety Assessment of Citrate Anticoagulation During Albumin Dialysis in Comparison to Other Methods of Anticoagulation

Liver failure is a serious and often deadly disease often requiring MARS (Molecular Adsorbent Recirculating System) therapy. Choosing the safe and effective method of anticoagulation during artificial liver support systems seems to be very difficult and extremely important. The aim of this study was to assess effectiveness and safety of regional anticoagulation with citrate in liver failure patients during MARS. We used a single center observational study. We analyzed 158 MARS sessions performed in 65 patients: 105 (66.5%) sessions in 41 patients with heparin anticoagulation, 40 (25.3%) sessions in 19 patients with citrate, and 13 (8%) sessions in only five patients without anticoagulation, that were excluded from part of the analysis. To determine the effectiveness of regional anticoagulation with citrate, probability of filter survival and changes in laboratory parameters were analyzed according to the applied method of anticoagulation. The safety of citrate was determined by Ca/Ca2+ ratio, acid-base balance, bleeding complications, and the need for blood product transfusions. The probability of filter survival in the citrate group was 94% and in the heparin group 82% (P = 0.204). There was no relationship between the method of anticoagulation and effectiveness of MARS therapy in lowering the levels of the analyzed parameters. Only one patient had a Ca/Ca2+ ratio higher than he safety margin. There were no statistically significant changes in pH and lactate level irrespective of anticoagulation; bicarbonate dropped significantly only in the heparin group (P = 0.03). The frequency of bleeding complications and the need for transfusions did not differ significantly between groups. Regional anticoagulation with citrate can be an effective and safe method of anticoagulation during MARS therapy, but requires attentive monitoring and further studies in liver failure patients.
Knowledge discovery method for deriving conditional probabilities from large datasets

In today's world, enormous amounts of data are being collected everyday. Thus, the problems of storing, handling, and utilizing the data are faced constantly. As the human mind itself can no longer interpret the vast datasets, methods for extracting useful and novel information from the data are needed and developed. These methods are collectively called knowledge discovery methods. In this thesis, a novel combination of feature selection and data modeling methods is presented in order to help with this task. This combination includes the methods of basic statistical analysis, linear correlation, self-organizing map, parallel coordinates, and k-means clustering. The presented method can be used, first, to select the most relevant features from even hundreds of them and, then, to model the complex inter-correlations within the selected ones. The capability to handle hundreds of features opens up the possibility to study more extensive processes instead of just looking at smaller parts of them. The results of k-nearest-neighbors study show that the presented feature selection procedure is valid and appropriate. A second advantage of the presented method is the possibility to use thousands of samples. Whereas the current rules of selecting appropriate limits for utilizing the methods are theoretically proved only for small sample sizes, especially in the case of linear correlation, this thesis gives the guidelines for feature selection with thousands of samples. A third positive aspect is the nature of the results: given that the outcome of the method is a set of conditional probabilities, the derived model is highly unrestrictive and rather easy to interpret. In order to test the presented method in practice, it was applied to study two different cases of steel manufacturing with hot strip rolling. In the first case, the conditional probabilities for different types of retentions were derived and, in the second case, the rolling conditions for the occurrence of wedge were revealed. The results of both of these studies show that steel manufacturing processes are indeed very complex and highly dependent on the various stages of the manufacturing. This was further confirmed by the fact that with studies of k-nearest-neighbors and C4.5, it was impossible to derive useful models concerning the datasets as a whole. It is believed that the reason for this lies in the nature of these two methods, meaning that they are unable to grasp such manifold inter-correlations in the data. On the contrary, the presented method of conditional probabilities allowed new knowledge to be gained of the studied processes, which will help to better understand these processes and to enhance them.
Sensorless position control of permanent magnet synchronous machines without limitation at zero speed

Sensorless position control of surface mounted permanent magnet synchronous machines (SMPMSM) still is a challenge. High performance position control at low and zero speed is only possible using anisotropic effects being considered not in the fundamental-frequency machine models, but in extended high-frequency models. This paper presents a new high-frequency injection method estimating the rotor position, which overcomes the small signal to noise ratio inherent to methods of this type published so far. This enables to track even small saliencies typical for SMPM synchronous machines. A small high-frequency voltage signal is injected into the rotor d-axis with no influence on the torque producing q-current. The demodulation of the responding high-frequency current signal is independent on machine parameters. Therefore the proposed method is independent on machine parameters and simply adaptable to different machines. As only the high frequency current has to be processed for position estimation, there is no additional hardware necessary besides that for standard drives with field oriented control.
Conserved residues in yeast initiator tRNA calibrate initiation accuracy by regulating preinitiation complex stability at the start codon

Eukaryotic initiator tRNA (tRNAi) contains several highly conserved, unique sequence features, yet their importance in accurate start codon selection is unknown. Using genetic and biochemical analyses, Dong et al. show that conserved bases throughout tRNAi, from the anticodon stem to the acceptor stem, play key roles in ensuring the fidelity of start codon recognition. This work delineates specific molecular functions for signature initiator tRNA residues and establishes their importance for initiation accuracy in living eukaryotic cells.
Ambient Air Pollution and Cardiac Arrhythmias in Patients With Implantable Defibrillators

Background: Previous studies of ambient air pollution and ventricular tachyarrhythmias in patients with implantable cardioverter defibrillators have yielded mixed results. Methods: We examined this relationship in a study of 518 patients with 6287 tachyarrhythmic event-days over a 10-year period in Atlanta, Georgia. The air quality data included daily measurements of PM10, ozone, nitrogen dioxide, carbon monoxide, and sulfur dioxide for the entire study period, as well as speciated measurements of PM2.5 mass and oxygenated hydrocarbons for the final 4 years of the study. Our primary analyses utilized generalized estimating equations, controlling for long-term time trends and meteorologic conditions as well as residual correlation within subjects. Results: Our primary modeling approach found no association; additional sensitivity analyses and alternative analytic approaches supported those findings. The most suggestive positive findings were for coarse particles. Conclusions: The present study constitutes the largest study to date of ambient air pollution and tachyarrhythmic events in patients with implantable cardioverter defibrillators. Other than the suggestive findings for coarse particles, the study provides little evidence of an association between ambient air quality levels and tachyarrhythmic events.
Now I see it, now I don’t: researcher’s position and reflexivity in qualitative research

This article addresses potential effects on reflexivity of researcher’s social position (e.g. gender, age, race, immigration status, sexual orientation), personal experiences, and political and professional beliefs. Because reflexivity is a major strategy for quality control in qualitative research, understanding how it may be impacted by the characteristics and experiences of the researcher is of paramount importance. Benefits and challenges to reflexivity under three types of researcher’s position are discussed and illustrated by means of case examples: (1) reflexivity when researcher shares the experience of study participants, (2) reflexivity when researcher moves from the position of an outsider to the position of an insider in the course of the study, and (3) reflexivity when researcher has no personal familiarity or experience with what is being studied. Strategies are offered for harvesting the benefits of researcher’s familiarity with the subject and for curbing its potentially negative effects. Directions for future research are suggested.
IoT Metadata Creation System for Mobile Images and Its Applications

This paper proposes the capturing of IoT data andtheir embedding as metadata in digital snapshots, includingphotos, audios, and videos. Specifically, we focus on IoT devicesbased on Bluetooth Low Energy (BLE) Technology, whichis used for not only data communication but also proximitysensing and is ubiquitous in wearables, smartphones, personaltags, indoor-navigation beacons, and home-automation devices. The IoT metadata can cover different levels, from the radiosignal strength and the media-access controller (MAC) addressto device name, indoor location, temperature, humidity, airquality, and advertising messages. These IoT data can readilyaugment metadata such as timestamp, GPS location, and camerasettings already captured by today's cameras and saved indigital photo files. With such IoT metadata, the user will havemuch richer ways to understand the subject and environmentof the scene being captured by the photo or media, such as thesubject's fitness condition, the advertised events, and the taggedpersonal items at the scene. These metadata will enable newways of searching, querying, and organizing the photos and theassociated objects. Moreover, a novel mechanism we proposeis the ability to pair with a remote device whose identity androuting information is captured as IoT metadata, so that anauthorized user can then pair with it at a later time remotely. We contend that IoT metadata capturing can bring significantbenefits to the users.
Fatigue After Stroke: Relationship to Mobility, Fitness, Ambulatory Activity, Social Support, and Falls Efficacy

&NA; Fatigue is common and persistent in stroke survivors, yet it is not known how mobility deficits, fitness, or other factors, such as social support, relate to fatigue severity, or whether subjective fatigue contributes to reduced ambulatory activity. The severity of fatigue in a sample of 53 community‐dwelling subjects with chronic hemiparetic stroke was examined, and relationships among fatigue and mobility deficit severity, cardiovascular‐metabolic fitness, ambulatory activity, social support, and self‐efficacy for falls were identified. Measures included the Fatigue Severity Scale, timed 10‐meter walks, the Berg Balance Scale, submaximal and peak VO2, total daily step activity derived from microprocessor‐linked Step Activity Monitors, the Medical Outcomes Study Social Support Survey, and the Falls Efficacy Scale. Forty‐six percent of the sample had severe fatigue. Fatigue showed no relationship to ambulatory activity. Fatigue severity was associated with the Berg Balance Scale (p > .01) and falls efficacy (p > .01), but not with cardiovascular fitness variables. Patients with elevated fatigue severity scores had lower social support (p > .05) and poorer falls efficacy scores (p > .05) than patients reporting less fatigue. Only falls efficacy was predictive of fatigue severity (r2 = 0.216, p > .01). Further studies are needed to evaluate whether rehabilitation strategies that include not only fitness and mobility interventions, but also social/behavioral and self‐efficacy components, are associated with reduced fatigue and increased ambulation.
Cascade lemma for set-stable systems

A previous result about uniform global asymptotic stability (UGAS) of the equilibrium of a cascaded time-varying systems, is here also shown to hold for closed (not necessarily compact) sets composed by set-stable subsystems of a cascade. In view of this result an optimal control allocation approach is discussed
Image interpolation using Gaussian Mixture Models with spatially constrained patch clustering

In this paper we address the problem of image interpolation using Gaussian Mixture Models (GMM) as a prior. Previous methods of image restoration with GMM have not considered spatial (geometric) distance between patches in clustering, failing to fully exploit the coherency of nearby patches. The GMM framework in our method for image interpolation is based on the assumption that the accumulation of similar patches in a neighborhood are derived from a multivariate Gaussian probability distribution with a specific covariance and mean. An Expectation Maximization-like (EM-like) algorithm is used in order to determine patches in a cluster and restore them. The results show that our image interpolation method outperforms previous state-of-the-art methods with an acceptable bound.
A model and a pattern for data collection on collaborative actions in CSCL systems

There is an increasing interest in the CSCL field towards the definition of frameworks that support analysis of interactions in order to understand or to regulate collaboration. These analysis processes draw on the automatic collection of data about the collaborative processes for its further analysis by manual or automatic means. Despite this interest, current proposals solve this automatic collection using ad-hoc solutions, and thus they do not consider how this problem can be solved in a modular and reusable manner, so that it could be applied to different collaborative situations and analytical approaches. This paper shows how CSCL can benefit from the field of software engineering by the adaptation of the command design software pattern to the problem of CSCL data collection. In order to perform this adaptation, we draw on a model of interaction that defines the concept of collaborative action as the basis of any interaction, which is also described in this paper. These two aspects: the concept of collaborative action and the adaptation of the command pattern to the problem of CSCL data collection will allow us to address conceptual as well as implementation issues related to the modelling of interactions in CSCL.