Miracle-dz/UniFAR-FTUs huggingface dataset:
Adaptive learning algorithm for pattern classification

In this paper, a pattern classification task was regarded as a sample selection problem where a sparse subset of sample from the labeled training set was chosen. We proposed an adaptive learning algorithm utilizing the least square function to address this problem. Using these selected samples, which we call informative vectors, a classifier capable of recognizing the test samples was established. This novel algorithm is a combination of searching strategies that, not only based on forward searching steps, but adaptively takes backward steps to correct the errors introduced by earlier forward steps. We experimentally demonstrated on face image and text dataset that classifier using such informative vectors outperformed other methods.
Embedded multiple object detection based on deep learning technique for advanced driver assistance system

This paper proposes an optimized pedestrian and vehicle detection method based on deep learning technique. We optimize the convolutional neural network architecture by three mainly methods. The first one is the choice of the learning policy. The second one is to simplify the convolutional neural network architecture. The last one is careful choice of training samples. With limited loss of accuracy, we can greatly speed up the original deep learning method coming from CAFFE. The proposed system is developed on PCs and implemented on the platforms of both the PC and embedded systems. We can achieve around 90% accuracy when it is tested on an open-source dataset. On PCs with Intel i7@3.5GHz CPU, the proposed design can reach the performance about 720×480 video at 25 frames per second. On the NVIDIA JETSON TX1 embedded system, the proposed design can reach the performance about 720×480 video at 5 frames per second.
Diagnostic Efficiency of Troponin T Measurements in Acute Myocardial Infarction

BackgroundThe present study was designed to evaluate the effliciency of a newly developed troponin T enzyme immunoassay for the detection of acute myocardial infarction. Methods and ResultsThe study comprised 388 patients admitted with chest pain and suspected myocardial infarction and 101 patients with skeletal muscle damage and additional suspected myocardial cell damage. Troponin T was elevated to more than twice the analytical sensitivity of the assay (0.5 μg/l) in all patients with non-Q wave (range, 1.2-5 μg/l) and Q wave infarction (range, 3-220 μg/l). Troponin T appeared in serum as early as 3 hours after onset of pain in 50% of the patients and remained elevated in all patients for more than 130 hours, revealing release kinetics of both free cytosolic and structurally bound molecules. The diagnostic efficiency of troponin T was superior to that of creatine kinase-MB (98% versus 97%) and remained at 98% until 5.5 days after admission, if patients with unstable angina were excluded from analysis. In the 79 patients with unstable angina, troponin T was elevated (range, 0.55-3.1 μg/l) in at least one blood sample from each of 37 patients (56%). Circulating troponin T was correlated to the presence of reversible ST segment or T wave changes on the electrocardiogram (p<0.005) and to the frequency of in-hospital complications. In the 101 patients with skeletal muscle damage and suspected additional cardiac muscle damage, troponin T was the most useful test; its efficiency was 89% or 94% (depending on the discriminator value used) as compared with 63% for creatine kinase-MB. ConclusionsThus, the data of the study indicate that the newly developed troponin T test improves the efficiency of serodiagnostic tools for the detection of myocardial cell necrosis as compared with conventionally used cardiac enzymes. (Circulation 1991;83:902–912)
Software abstractions for trusted sensors

With the proliferation of e-commerce, e-wallet, and e-health smartphone applications, the need for trusted mobile applications is greater than ever. Unlike their desktop counterparts, many mobile applications rely heavily on sensor inputs. As a result, trust often requires authenticity and integrity of sensor readings. For example, applications may need trusted readings from sensors such as a GPS, camera, or microphone. Recent research has started to recognize the need for "trusted sensors", yet providing the right programming abstractions and system support for building mobile trusted applications is an open problem. This paper proposes two software abstractions for offering trusted sensors to mobile applications. We present the design and implementation of these abstractions on both x86 and ARM platforms. We implement a trusted GPS sensor on both platforms, and we provide a privacy control for trusted location using differential privacy. Our evaluation shows that implementing these abstractions comes with moderate overhead on both x86 and ARM platforms. We find these software abstractions to be versatile and practical - using them we implement one novel enterprise mobile application.
Alchemical free energy simulations for biological complexes: powerful but temperamental …

Free energy simulations compare multiple ligand:receptor complexes by “alchemically” transforming one into another, yielding binding free energy differences. Since their introduction in the 1980s, many technical and theoretical obstacles were surmounted, and the method (“MDFE,” since molecular dynamics are often used) has matured into a powerful tool. We describe its current status, its effectiveness, and the challenges it faces. MDFE has provided chemical accuracy for many systems but remains expensive, with significant human overhead costs. The bottlenecks have shifted, partly due to increased computer power. To study diverse sets of ligands, force field availability and accuracy can be a major difficulty. Another difficulty is the frequent need to consider multiple states, related to sidechain protonation or buried waters, for example. Sophisticated, automated methods to sample these states are maturing, such as constant pH simulations. Meanwhile, combinations of MDFE and simpler approaches, like continuum dielectric models, can be very effective. As illustrations, we show how, with careful force field parameterization, MDFE accurately predicts binding specificities between complex tetracycline ligands and their targets. We describe substrate binding to the aspartyl‐tRNA synthetase enzyme, where many distinct electrostatic states play a role, and a histidine and a Mg2+ ion act as coupled switches that help enforce a strict preference for the aspartate substrate, relative to several analogs. Overall, MDFE has achieved a predictive status, where novel ligands can be studied and molecular recognition elucidated in depth. It should play an increasing role in the analysis of complex cellular processes and biomolecular engineering. Copyright © 2009 John Wiley & Sons, Ltd.
Cooperative simultaneous localization and tracking for mobile AD-HOC sensor networks

Over the past decade, there has been much focus on mobile ad-hoc sensor networks. The mobility alleviates several issues relating to sensor network coverage and connectivity, whereas aggravates the difficulties of applications such as target tracking. Traditional solutions always localize the sensors first, and then track the target. In contrast, cooperative simultaneous localization and tracking (CoSLAT) adopts both the sensor-target and the inter-sensor observations to simultaneously refine the target and the sensor estimates. We propose a distributed variational filtering (VF) algorithm for CoSLAT, which greatly cuts down the estimate errors, while having nearly the same complexity as the traditional particle filtering (PF) algorithm. In addition, the update and the approximation of the a posteriori distribution are jointly performed by the VF, yielding a natural and adaptive compression. Since the temporal dependence is reduced from a great number of particles to one Gaussian component, the communication cost is significantly diminished.
Importance of Hydrothermal Vents in Scavenging Removal of 230Th in the Nansen Basin

In this study we present dissolved and particulate 230Th and 232Th results, as well as particulate 234Th data, obtained as part of the GEOTRACES central Arctic Ocean sections GN04 (2015) and IPY11 (2007). Samples were analyzed following GEOTRACES methods and compared to previous results from 1991. We observe significant decreases in 230Th concentrations in the deep waters of the Nansen Basin. We ascribe this nonsteady state removal process to a variable release and scavenging of trace metals near an ultraslow spreading ridge. This finding demonstrates that hydrothermal scavenging in the deep‐sea may vary on annual time scales and highlights the importance of repeated GEOTRACES sections.
A viral kinase mimics S6 kinase to enhance cell proliferation

Significance Viruses usurp the host cell machinery to replicate, disseminate, and propagate themselves. Kaposi’s sarcoma-associated herpesvirus (KSHV) encodes a viral protein kinase (vPK) also known as ORF36. Using in silico modeling and biochemistry, we report that vPK/ORF36 displays limited homology to cellular S6 kinase B1 (S6KB1). Both kinases share overlapping substrates and can phosphorylate S6. However, unlike S6KB1, vPK augments S6 phosphorylation under conditions where mammalian target of rapamycin (mTOR) is inhibited. vPK modulates cellular proliferation and protein synthesis, augments anchorage independence, and enhances angiogenesis. Depletion of vPK/ORF36 during lytic replication inhibits the production of infectious virions, thereby underscoring the importance of this kinase during the KSHV life cycle. Our collective observations suggest that vPK may function as a constitutively active mimic of S6KB1. Viruses depend upon the host cell for manufacturing components of progeny virions. To mitigate the inextricable dependence on host cell protein synthesis, viruses can modulate protein synthesis through a variety of mechanisms. We report that the viral protein kinase (vPK) encoded by open reading frame 36 (ORF36) of Kaposi’s sarcoma-associated herpesvirus (KSHV) enhances protein synthesis by mimicking the function of the cellular protein S6 kinase (S6KB1). Similar to S6KB1, vPK phosphorylates the ribosomal S6 protein and up-regulates global protein synthesis. vPK also augments cellular proliferation and anchorage-independent growth. Furthermore, we report that both vPK and S6KB1 phosphorylate the enzyme 6-phosphofructo-2-kinase/fructose-2, 6-bisphosphatase 2 (PFKFB2) and that both kinases promote endothelial capillary tubule formation.
An Improved Method for Soil DNA Extraction to Study the Microbial Assortment within Rhizospheric Region

The need for identification of soil microbial community mainly depends on direct extraction of DNA from soil, a multifaceted environment that is a major pool for microbial genetic diversity. The soil DNA extraction procedures usually suffer from two major problems, namely, inappropriate rupturing of cells and contamination with humic substances. In the present study, five protocols for single type of rhizospheric soil were investigated and their comparison indicated that the inclusion of 120 mM phosphate buffered saline (PBS) for washing and mannitol in the lysis buffer allowed the processing of soil sample in minimal time with no specific equipment requirement. Furthermore, DNA purity and yield were also improved, which allowed the exploitation of genetic potential of soil microbes within soil sample thereby facilitating the amplification of metagenomic DNA. The effectiveness of methods was analyzed using random amplification of polymorphic DNA. The banding patterns revealed that both the abundance and the composition of indigenous microbial community depend on the DNA recovery method.
Semantics-driven interoperability between Scala.js and JavaScript

Hundreds of programming languages compile to JavaScript. Yet, most of them fail, at one level or another, to provide satisfactory interoperability with JavaScript APIs. This is limiting, as interoperability is at least required to manipulate web pages through the DOM API, but also to use the eco-system of existing JavaScript libraries. This paper presents the interoperability features of Scala.js, which solves the shortcomings of previous approaches. Scala.js offers a separate hierarchy of JavaScript types, whose operations have semantics borrowed from ECMAScript 2015. The interoperability features are complete with respect to ECMAScript 2015, save for two exceptions which are still being worked on. This allows Scala.js programs to perform any operation that an ECMAScript program could do, thereby guaranteeing that they can talk to any JavaScript library.
A high performance hardware based RNS-to-binary converter

Due to its small size and parallel arithmetic operations, Residue Number System (RNS) based data is well suitable for implementing various digital signal processing functions that are commonly used in many consumer electronic devices nowadays. This paper presents the design of the RNS to Binary reverse converter which is typically the bottleneck in an RNS based signal processing system. Specifically, it describes a pipelined parallel prefix based modular adders which is used to implement the reverse converter for the {2k-1, 2k, 2k+1} moduli set based RNS system.
Eicosapentaenoic acid (20:5 n-3) increases fatty acid and glucose uptake in cultured human skeletal muscle cells Published, JLR Papers in Press, November 21, 2005.

This study was conducted to evaluate the chronic effects of eicosapentaenoic acid (EPA) on fatty acid and glucose metabolism in human skeletal muscle cells. Uptake of [14C]oleate was increased >2-fold after preincubation of myotubes with 0.6 mM EPA for 24 h, and incorporation into various lipid classes showed that cellular triacylgycerol (TAG) and phospholipids were increased 2- to 3-fold compared with control cells. After exposure to oleic acid (OA), TAG was increased 2-fold. Insulin (100 nM) further increased the incorporation of [14C]oleate into all lipid classes for EPA-treated myotubes. Fatty acid β-oxidation was unchanged, and complete oxidation (CO2) decreased in EPA-treated cells. Basal glucose transport and oxidation (CO2) were increased 2-fold after EPA, and insulin (100 nM) stimulated glucose transport and oxidation similarly in control and EPA-treated myotubes, whereas these responses to insulin were abolished after OA treatment. Lower concentrations of EPA (0.1 mM) also increased fatty acid and glucose uptake. CD36/FAT (fatty acid transporter) mRNA expression was increased after EPA and OA treatment compared with control cells. Moreover, GLUT1 expression was increased 2.5-fold by EPA, whereas GLUT4 expression was unchanged, and activities of the mitogen-activated protein kinase p38 and extracellular signal-regulated kinase were decreased after treatment with OA compared with EPA. Together, our data show that chronic exposure of myotubes to EPA promotes increased uptake and oxidation of glucose despite a markedly increased fatty acid uptake and synthesis of complex lipids.
How is Health Economics Relevant to Transplant Clinicians?

Decision making is complex and difficult in clinical practice. Clinicians are often faced with a large range of possible alternative decision options, each with their own consequences and trade-offs. Health economics methods enable informed decision making on how best to allocate limited resources that could lead to most health gains. Economic evaluation in particular is highly relevant in transplantation medicine. Transplantation is an expensive intervention, but it improves the quality of life and survival of people with chronic diseases. The balance between health care resource use and the optimal health gains is useful not only to decision-makers, but also to consumers, clinicians, and researchers. This article is an overview of the concepts of economic evaluation in the setting of transplantation and highlights the applicability of these concepts in clinical transplantation.
Reared Microgastrine Wasps (Hymenoptera: Braconidae) from Yanayacu Biological Station and Environs (Napo Province, Ecuador): Diversity and Host Specialization

Abstract The microgastrine braconid wasps recovered up through 2007 by the NSF-sponsored rearing project “Caterpillars and Parasitoids of the Eastern Andes in Ecuador” are summarized in terms of their host specialization and faunistic uniqueness. Two hundred fifty eight rearings of caterpillars resulted in records of Microgastrinae, distributed among 14 genera (Apanteles Förster, Choeras Mason, Cotesia Cameron, Diolcogaster Ashmead, Distatrix Mason, Dolichogenidea Viereck, Exix Mason, Glyptapanteles Ashmead, Hypomicrogaster Ashmead, Papanteles Mason, Parapanteles Ashmead, Protapanteles Ashmead, Sathon Mason and Venanus Mason). Eleven records of hyperparasitoids of Microgastrinae are also summarized; Mesochorus Gravenhorst (Ichneumonidae) and Perilampidae are both recorded. The results are compared to those recovered by surveys in other parts of the world, especially by the Janzen-Hallwachs survey of the Area de Conservación Guanacaste (ACG) in Costa Rica. An annotated list of microgastrine genera not yet recorded at Yanayacu, but which we expect to eventually find there based on extrapolation from their known geographic distributions, is provided.
Data Cleaning for Classification Using Misclassification Analysis

In most classification problems, sometimes in order to achieve better results, data cleaning is used as a preprocessing technique. The purpose of data cleaning is to remove noise, inconsistent data and errors in the training data. This should enable the use of a better and representative data set to develop a reliable classification model. In most classification models, unclean data could sometime affect the classification accuracies of a model. In this paper, we investigate the use of misclassification analysis for data cleaning. In order to demonstrate our concept, we have used Artificial Neural Network (ANN) as the core computational intelligence technique. We use four benchmark data sets obtained from the University of California Irvine (UCI) machine learning repository to investigate the results from our proposed data cleaning technique. The experimental data sets used in our experiment are binary classification problems, which are German credit data, BUPA liver disorders, Johns Hopkins Ionosphere and Pima Indians Diabetes. The results show that the proposed cleaning technique could be a good alternative to provide some confidence when constructing a classification model.
International Geomagnetic Reference Field: the eleventh generation

The eleventh generation of the International Geomagnetic Reference Field (IGRF) was adopted in December 2009 by the International Association of Geomagnetism and Aeronomy Working Group V-MOD. It updates the previous IGRF generation with a definitive main field model for epoch 2005.0, a main field model for epoch 2010.0, and a linear predictive secular variation model for 2010.0–2015.0. In this note the equations defining the IGRF model are provided along with the spherical harmonic coefficients for the eleventh generation. Maps of the magnetic declination, inclination and total intensity for epoch 2010.0 and their predicted rates of change for 2010.0–2015.0 are presented. The recent evolution of the South Atlantic Anomaly and magnetic pole positions are also examined.
Cognitive Cooperative Control for Autonomous Underwater Vehicles An overview of achievements in the first project year

The aim of the EU-project "Cooperative Cognitive Control for Autonomous Underwater Vehicles (Co3AUVs)" is to develop, implement and test advanced cognitive systems for coordination and cooperative control of multiple AUVs. Several aspects are investigated including 3D perception and mapping, cooperative situation awareness, deliberation and navigation as well as behavioral control strictly linked with the underwater communication challenges. We present in this paper results from the first year of the project. This includes contributions for a simulator, the development of vehicles and components, 2D as well as 3D underwater mapping, cooperative navigation and motion control, and cooperative skills. published in: 9th International Conference on Computer Applications and Information Technology in the Maritime Industries (COMPIT), Gubbio, Italy, 2010
Using Graphics Processing Units to Parallelize the FDK Algorithm for Tomographic Image Reconstruction

The paper presents the implementation of a parallel version of FDK (Felkamp, David e Kress) algorithm using graphics processing units. Discussion was briefly some elements the computed tomographic scan and FDK algorithm; and some ideas about GPUs (Graphics Processing Units) and its use in general purpose computing were presented. The paper shows a computational implementation of FDK algorithm and the process of parallelization of this implementation. Compare the parallel version of the algorithm with the sequential version, used speedup as a performance metric. To evaluate the performance of parallel version, two GPUs, GeForce 9400GT (16 cores) a low capacity GPU and Quadro 2000 (192 cores) a medium capacity GPU was reached speedup of 3.37.
Effects of macroeconomic conditions on health in Brazil.

OBJECTIVE To analyze the relationship between macroeconomic conditions and health in Brazil. METHODS The analysis of the impact of employment and income on mortality in Brazil was based on panel data from Brazilian states between 1981 and 2002. Mortality rates obtained from the national mortality database was used as a proxy for health status, whereas the variables employment, income, and illiteracy rates were used as proxies for macroeconomic and socioeconomic conditions. Static and dynamic models were applied for the analysis of two hypotheses: a) there is a positive relationship between mortality rates and income and employment, as suggested by Ruhm; b) there is a negative relationship between mortality rates and income and employment, as suggested by Brenner. RESULTS There was found a negative relationship between mortality rates (proxy for health) and macroeconomic conditions (measured by employment rate). The estimates indicated that the overall mortality rate was higher during economic recession, suggesting that as macroeconomic conditions improved, increasing employment rates, there was a decrease in the mortality rate. The estimate for the relationship between illiteracy (proxy for education level) and mortality rate showed that higher levels of education can improve health. CONCLUSIONS The results from the static and dynamic models support Brenner's hypothesis that there is a negative relationship between mortality rates and macroeconomic conditions.
Confidence Preserving Machine for Facial Action Unit Detection

Varied sources of error contribute to the challenge of facial action unit detection. Previous approaches address specific and known sources. However, many sources are unknown. To address the ubiquity of error, we propose a Confident Preserving Machine (CPM) that follows an easy-to-hard classification strategy. During training, CPM learns two confident classifiers. A confident positive classifier separates easily identified positive samples from all else, a confident negative classifier does same for negative samples. During testing, CPM then learns a person-specific classifier using "virtual labels" provided by confident classifiers. This step is achieved using a quasi-semi-supervised (QSS) approach. Hard samples are typically close to the decision boundary, and the QSS approach disambiguates them using spatio-temporal constraints. To evaluate CPM, we compared it with a baseline single-margin classifier and state-of-the-art semi-supervised learning, transfer learning, and boosting methods in three datasets of spontaneous facial behavior. With few exceptions, CPM outperformed baseline and state-of-the art methods.