Miracle-dz/UniFAR-FTUs huggingface dataset:
Implementation Trade-Offs of Soft-Input Soft-Output MAP Decoders for Convolutional Codes

Soft-input soft-output (SISO) maximum a-posteriori (MAP) decoders for convolutional codes (CCs) are an integral part of many modern wireless communication systems. Specifically, SISO-MAP decoding forms the basis for turbo decoders, as, e.g., specified for HSDPA or 3GPP-LTE, or for iterative detection and decoding in multiple-input multiple-output wireless systems, such as IEEE 802.11n. In this paper, we investigate the silicon-area, throughput, and energy-efficiency trade-offs associated with SISO-MAP decoders based on the algorithm developed by Bahl, Cocke, Jelinek, and Raviv (BCJR). To this end, we develop radix-2 and radix-4 architectures for high-throughput SISO-MAP decoding of CCs having 4, 8, 16, 32, and 64 states and present corresponding implementation results in 180 nm, 130 nm, and 90 nm CMOS technology. We validate technology-scaling rules and finally demonstrate the use of the presented trade-off analysis by identifying the key design parameters for parallel turbo-decoder implementations.
Design and control of a low power DC-AC converter fed by a photovoltaic array

In this paper, we present a DC-AC converter fed by a PV array for stand alone applications up to 50 W. It is dedicated to rural areas in countries having abundant sunshine and where there is no grid connection to the utility network or the power supply is weak as in many underdeveloped countries. Using a single PV array of 50 W as typical power, the aim is to have a simple system, robust, free-maintenance and highly efficient for cellar phone adapter e.g. The design of the structure has led to a double boost for the DC-DC module (400 V as output voltage) where a high gain is needed. The DC-AC converter is made of a half-bridge inverter and an (LC) filter tuned for 50 Hz. Using simulation packages, we have obtained the power components parameters (inductances, switches and diodes) and set the switching frequency. For control purposes, a linear controller (PID type) is used and a non-linear approach using sliding mode is evaluated. Simulation results in terms of robustness and efficiency are promising.
Loss to Follow-Up as a Competing Risk in an Observational Study of HIV-1 Incidence

Objective Conventional survival estimates may be biased if loss to follow-up (LTF) is associated with the outcome of interest. Our goal was to assess whether the association between sexual risk behavior and HIV-1 acquisition changed after accounting for LTF with competing risks regression. Methods HIV-1-seronegative women who enrolled in a Kenyan sex worker cohort from 1993–2007 were followed prospectively and tested for HIV at monthly clinic visits. Our primary predictor was self-reported sexual risk behavior in the past week, analyzed as a time-dependent covariate. Outcomes included HIV-1 acquisition and LTF. We analyzed the data using Cox proportional hazards regression and competing risks regression, in which LTF was treated as a competing event. Results A total of 1,513 women contributed 4,150 person-years (py), during which 198 (13.1%) acquired HIV-1 infection (incidence, 4.5 per 100 py) and 969 (64.0%) were LTF (incidence, 23.4 per 100 py). After adjusting for potential confounders, women reporting unprotected sex with multiple partners were less likely to be lost to follow-up (adjusted sub-hazard ratio (aSHR) 0.50, 95% confidence interval (CI) 0.32–0.76, relative to no sexual activity). The risk of HIV-1 acquisition after reporting unprotected sex with multiple partners was similar with Cox regression (adjusted hazard ratio (aHR) 2.41, 95% CI 1.36–4.27) and competing risks regression (aSHR 2.47, 95% CI 1.33–4.58). Conclusions Unprotected sex with multiple partners was associated with higher HIV-1 acquisition risk, but lower attrition. This differential attrition did not substantially bias Cox regression estimates when compared to competing risks regression results.
Optimal Bidding Strategies for Wind Power Producers in the Day-ahead Electricity Market

Wind Power Producers (WPPs) seek to maximize profit and minimize the imbalance costs when bidding into the day-ahead market, but uncertainties in the hourly available wind and forecasting errors make the bidding risky. This paper assumes that hourly wind power output given by the forecast follows a normal distribution, and proposes three different bidding strategies, i.e. , the expected profit-maximization strategy (EPS), the chance-constrained programming-based strategy (CPS) and the multi-objective bidding strategy (ECPS). Analytical solutions under the three strategies are obtained. Comparisons among the three strategies are conducted on a hypothetical wind farm which follows the Spanish market rules. Results show that bid under the EPS is highly dependent on market clearing price, imbalance prices, and also the mean value and standard deviation of wind forecast, and that bid under the CPS is largely driven by risk parameters and the mean value and standard deviation of the wind forecast. The ECPS combining both EPS and CPS tends to choose a compromise bid. Furthermore, the ECPS can effectively control the tradeoff between expected profit and target profit for WPPs operating in volatile electricity markets.
Digital sketch maps and eye tracking statistics as instruments to obtain insights into spatial cognition

This paper explores map users' cognitive processes in learning, acquiring and remembering information presented via screen maps. In this context, we conducted a mixed-methods user experiment employing digital sketch maps and eye tracking. On the one hand, the performance of the participants was assessed based on the order with which the objects were drawn and the influence of visual variables (e.g. presence & location, size, shape, color). On the other hand, trial durations and eye tracking statistics such as average duration of fixations, and number of fixations per seconds were compared. Moreover, selected AoIs (Area of Interests) were explored to gain a deeper insight on visual behavior of map users. Depending on the normality of the data, we used either two-way ANOVA or Mann-Whitney U test to inspect the significance of the results. Based on the evaluation of the drawing order, we observed that experts and males drew roads first whereas; novices and females focused more on hydrographic object. According to the assessment of drawn elements, no significant differences emerged between neither experts and novices, nor females and males for the retrieval of spatial information presented on 2D maps with a simple design and content. The differences in trial durations between novices and experts were not statistically significant while both studying and drawing. Similarly, no significant difference occurred between female and male participants for either studying or drawing. Eye tracking metrics also supported these findings. For average duration of fixation, there was found no significant difference between experts and novices, as well as between females and males. Similarly, no significant differences were found for the mean number of fixation.
Paraphrase Recognition Using Machine Learning to Combine Similarity Measures

This paper presents three methods that can be used to recognize paraphrases. They all employ string similarity measures applied to shallow abstractions of the input sentences, and a Maximum Entropy classifier to learn how to combine the resulting features. Two of the methods also exploit WordNet to detect synonyms and one of them also exploits a dependency parser. We experiment on two datasets, the MSR paraphrasing corpus and a dataset that we automatically created from the MTC corpus. Our system achieves state of the art or better results.
Neuroimaging studies of cognitive remediation in schizophrenia: A systematic and critical review

AIM To examine the effects of cognitive remediation therapies on brain functioning through neuroimaging procedures in patients with schizophrenia. METHODS A systematic, computerised literature search was conducted in the PubMed/Medline and PsychInfo databases. The search was performed through February 2016 without any restrictions on language or publication date. The search was performed using the following search terms: [(“cogniti*” and “remediation” or “training” or “enhancement”) and (“fMRI” or “MRI” or “PET” or “SPECT”) and (schizophrenia or schiz*)]. The search was accompanied by a manual online search and a review of the references from each of the papers selected, and those papers fulfilling our inclusion criteria were also included. RESULTS A total of 101 studies were found, but only 18 of them fulfilled the inclusion criteria. These studies indicated that cognitive remediation improves brain activation in neuroimaging studies. The most commonly reported changes were those that involved the prefrontal and thalamic regions. Those findings are in agreement with the hypofrontality hypothesis, which proposes that frontal hypoactivation is the underlying mechanism of cognitive impairments in schizophrenia. Nonetheless, great heterogeneity among the studies was found. They presented different hypotheses, different results and different findings. The results of more recent studies interpreted cognitive recovery within broader frameworks, namely, as amelioration of the efficiency of different networks. Furthermore, advances in neuroimaging methodologies, such as the use of whole-brain analysis, tractography, graph analysis, and other sophisticated methodologies of data processing, might be conditioning the interpretation of results and generating new theoretical frameworks. Additionally, structural changes were described in both the grey and white matter, suggesting a neuroprotective effect of cognitive remediation. Cognitive, functional and structural improvements tended to be positively correlated. CONCLUSION Neuroimaging studies of cognitive remediation in patients with schizophrenia suggest a positive effect on brain functioning in terms of the functional reorganisation of neural networks.
Integrated Information and Prospects for Gliding Mechanism of the Pathogenic Bacterium Mycoplasma pneumoniae

Mycoplasma pneumoniae forms a membrane protrusion at a cell pole and is known to adhere to solid surfaces, including animal cells, and can glide on these surfaces with a speed up to 1 μm per second. Notably, gliding appears to be involved in the infectious process in addition to providing the bacteria with a means of escaping the host's immune systems. However, the genome of M. pneumoniae does not encode any of the known genes found in other bacterial motility systems or any conventional motor proteins that are responsible for eukaryotic motility. Thus, further analysis of the mechanism underlying M. pneumoniae gliding is warranted. The gliding machinery formed as the membrane protrusion can be divided into the surface and internal structures. On the surface, P1 adhesin, a 170 kDa transmembrane protein forms an adhesin complex with other two proteins. The internal structure features a terminal button, paired plates, and a bowl (wheel) complex. In total, the organelle is composed of more than 15 proteins. By integrating the currently available information by genetics, microscopy, and structural analyses, we have suggested a working model for the architecture of the organelle. Furthermore, in this article, we suggest and discuss a possible mechanism of gliding based on the structural model, in which the force generated around the bowl complex transmits through the paired plates, reaching the adhesin complex, resulting in the repeated catch of sialylated oligosaccharides on the host surface by the adhesin complex.
ZBD: Using Transparent Compression at the Block Level to Increase Storage Space Efficiency

In this work we examine how transparent compression in the I/O path can improve space efficiency for online storage. We extend the block layer with the ability to compress and decompress data as they flow between the file-system and the disk. Achieving transparent compression requires extensive metadata management for dealing with variable block sizes, dynamic block mapping, block allocation, explicit work scheduling and I/O optimizations to mitigate the impact of additional I/O sand compression overheads. Preliminary results show that online transparent compression is a viable option for improving effective storage capacity, it can improve I/O performance by reducing I/O traffic and seek distance, and has a negative impact on performance only when single-thread I/O latency is critical.
Robots guiding small groups: the effect of appearance change on the user experience

In this paper we present an exploratory user study in which a robot guided small groups of two to three people. We manipulated the appearance of the robot in terms of the position of a tablet providing information (facing the group that was guided or the walking direction) and the type of information displayed (eyes or route information). Our results indicate that users preferred eyes on a display that faced the walking direction and route information on a display that faced them. The study gave us strong indication to believe that people are not in favor of eyes looking at them during the guiding.
Extraction of relative proximity from electrostatic images using Wide-Field Integration methods

Weakly electric fish use a self-generated electric field to interrogate the environment around them for obstacles, predators, and prey. These objects appear as spatial perturbations to an electric image formed by electro-receptors which are distributed over their bodies. The influence on an electric image, formed on a simulation model, due to the proximity of wide-field obstacles is derived here from standard principles of electrostatics. Wide-Field Integration (WFI) methods are then applied to perturbed electric images to extract relative position and orientation information, and a static output feedback methodology is presented to achieve local unmapped reflexive obstacle avoidance.
A low dimensional intensity-based feature descriptor for fast image matching

In this paper, we propose a novel image feature descriptor based on intensity information. In comparison with the widely-used SIFT algorithm, it can be implemented easily, computed efficiently, while at the same time demonstrating high performance under various conditions including the transformation of rotation, scale, viewpoint, illumination and JPEG compression. Additionally, this descriptor's low dimensionality leads to lower memory usage.
Between Scylla and Charybdis: Reflections on and problems associated with the evaluation of teachers in an era of metrification

The Scylla and Charybdis in this discussion of teacher evaluation are standardized achievement test data on the one hand, and classroom observational systems on the other. These are the two most common methods used to judge teachers’ competency. Both have serious flaws: the former primarily with validity, the latter primarily with reliability. At most these evaluation strategies provide teachers’ and their supervisors information about which to converse. But these two methods have such serious flaws that they should never be used as the primary grounds for rewarding, punishing, or firing teachers. When both methods of evaluation are used to judge teacher competency, the correlation between achievement tests and observational data is quite low. When two methods claiming to assess the same construct do not correlate well, either one or both methods are failing to assess the intended construct. There are two alternatives for navigating between Scylla and Charybdis: “Duties Based Teacher Evaluation” and “Performance Measures. ” These methods have much to recommend them, though like all methods of personnel evaluation, reliability and validity issues remain problematic.
Tackling Polytype Queries in Inconsistent Databases: Theory and Algorithm

To expand query types under a set of integrity constraints for obtaining consistent answers over inconsistent databases, a computational theory is proposed based on first-order logic. According to directed join graphs of queries and their join completeness, computational complexities of CQA are PTIME if query types are key-key, nonkey-key, incomplete key-key with acyclic join. This paper presents several algorithms to tackle a large and practical class of queries, which can obtain the rewritten queries for computing consistent answers. For a rewritable initial query, a consistent identification statement is constructed based on the join graph by recursive computation; and the statement combines with the initial query to construct a new first-order rewritten query for computing consistent answers. To acyclic self-join queries, the recursive rewriting algorithm cannot eliminate inconsistent tuples, so the initial query combines with the statement that eliminates them.
Predictive evidence of phosphorylation sites using in silico resources and 2-D-gel of gastrocnemic muscle proteins as analytical model

The identification of proteins separated by twodimensional (2D) gel electrophoresis is crucial to proteome projects aiming at characterization of all proteins expressed by a given organism or tissue in a given circumstance. The use of 2D gel electrophoresis in functional genomic research has proved to be an essential tool to understand the differential expression of protein isoforms. Structural alterations of proteins can reflect their conformational and functional changes and, consequently, their role in tissue physiology. Therefore, there is a massive accumulation of bioinformatics resources that could be used to obtain presumptive information about posttranslational modifications (PTM), including the reversible phosphorylation of proteins. Manual characterization of phosphorylation sites in experimental data is a long, difficult and laborious work to proteomics researchers. However, new and numerous bioinformatics tools for phosphorylation prediction are now located in the web. Using 2D electrophoresis experimental and analytical data (isoelectric point and molecular weight, as well as information retrieved after proteomic databases searches), we have performed in silico identification of phosphorylated sites that can be useful for PTM study. Comparing the profile of the “train of phosphorylated proteins”, comprised by twelve isoforms of the gastrocnemic muscle protein model, we have found a qualitative correlation between the in silico prediction and the experimental data. Comparison of putative phosphorylation sites of proteins from three species (rat, mouse and human) and our protein model, revealed the high conservation of motifs responsible for phosphate ligation. The phosphoserine site was found to be the most abundant in gastrocnemic muscle proteins. Particularly, the differential expression of a specific isoform is discussed. Proteins from the gastrocnemic muscle have presented a relative molecular weight (rMW) compatible with the proteins used as comparative model. Thus, the current comparison is useful to predict probable PTMs and to give support to more detailed studies about protein modification
Radio continuum and near-infrared study of the MGRO J2019+37 region

Context. MGRO J2019+37 is an unidentified extended source of very high energy gamm a-rays originally reported by the Milagro Collaboration as the brightest TeV source in the Cygnus region. Its extended emission could be powered by either a single or several sources. The GeV pulsar AGL J2020.5+3653, discovered by AGILE and associated with PSR J2021+3651, could contribute to the emission from MGRO J2019+37. Aims. Our aim is to identify radio and near-infrared sources in the field of the extended TeV source MGRO J2019+37, and study potential counterparts to explain its emission. Methods. We surveyed a region of about 6 square degrees with the Giant Metrewave Radio Telescope (GMRT) at the frequency 610 MHz. We also observed the central square degree of this survey in the near-infrared Ks-band using the 3.5 m telescope in Calar Alto. Archival X-ray observations of some specific fiel ds are included. VLBI observations of an interesting radio source were performed. We explored possible scenarios to produce the multi-TeV emission from MGRO J2019+37 and studied which of the sources could be the main particle accelerator. Results. We present a catalogue of 362 radio sources detected with the GMRT in the field of MGRO J2019+37, and the results of a cross-correlation of this catalog with one obtained at n ear-infrared wavelengths, which contains∼ 3× 10 5 sources, as well as with available X-ray observations of the region. Some peculiar sources inside the∼1 ◦ uncertainty region of the TeV emission from MGRO J2019+37 are discussed in detail, including the pulsar PSR J2021+3651 and its pulsar wind nebula PWN G75.2+0.1, two new radio-jet sources, the Hii region Sh 2-104 containing two star clusters, and the radio source NVSS J202032+363158. We also find that the hadronic scenario is the most likely in case of a s ingle accelerator, and discuss the possible contribution f rom the sources mentioned above. Conclusions. Although the radio and GeV pulsar PSR J2021+3651 / AGL J2020.5+3653 and its associated pulsar wind nebula PWN G75.2+0.1 can contribute to the emission from MGRO J2019+37, extrapolation of the GeV spectrum does not explain the detected multi-TeV flux. Other sources discussed here could contribute to the emission of the Milagro source.
Facing more than moore, is magnetic microscopy the new Swiss knife for 3D defect localization in SiP?

So far, most of the defects at system level are assembly related. This trend obviously concerns Systems in Package, Stacked dies, Packages on Package devices, passive integration, integration of logic, power, wireless, analog, sensor and actuator in the same packaged device… All these Systems in Package defy our failure localization tools. For the first time, we have to face non transparent material, massive 3D structure with mandatory long working distance and need of relatively high spatial resolution. Magnetic microscopy has the ability do this as long as we are able to adapt its principle to the mandatory 3D sensitivity and resolution. We have developed a global 3D approach based on simulation in order to target μm resolution at long working distance.
Cross-task code reuse in genetic programming applied to visual learning

Abstract We propose a method that enables effective code reuse between evolutionary runs that solve a set of related visual learning tasks. We start with introducing a visual learning approach that uses genetic programming individuals to recognize objects. The process of recognition is generative, i.e., requires the learner to restore the shape of the processed object. This method is extended with a code reuse mechanism by introducing a crossbreeding operator that allows importing the genetic material from other evolutionary runs. In the experimental part, we compare the performance of the extended approach to the basic method on a real-world task of handwritten character recognition, and conclude that code reuse leads to better results in terms of fitness and recognition accuracy. Detailed analysis of the crossbred genetic material shows also that code reuse is most profitable when the recognized objects exhibit visual similarity.