Miracle-dz/UniFAR-FTUs huggingface dataset:
Self-Recovering Parallel Applications in Multi-core Systems

In this paper, a Self-Recovering strategy, which is able to "re-map" dynamically application tasks on a multi-core system, is presented. Based on run-time failure aware techniques, this Self-Recovering strategy guarantees seamlessly termination and delivering the expected results despite multiple node and link failures in a 2D mesh topology. It has been demonstrated, based on a statistical analysis, that the proposed technique is able to re-map the tasks of faulty nodes in a bounded number of steps. The theoretical results have been validated by simulations. The proposed technique is allowing to bypass multiple nodes, routers and links failures with a predictable number of hops. It has been demonstrated that the Motion JPEG-2000 application can be parallelized and formally represented as a Directed Acyclic Graph (DAG). It is worth noting that the proposed technique has been validated by the simulation of a 1000 cores system, in the presence of nodes and links failures up to 10%. Therefore, the proposed technique has been shown to be efficient for seamless execution of parallel streaming applications and to provide the Execution Time Reduction Ratio close to ideal.
CZT in space-based hard x-ray astronomy: background predictions for EXIST

One of the key aspects of a detector material for space-borne hard X-ray and gamma-ray telescopes is the rate of prompt and delayed background events generated inside the material by charged and neutral particles striking the detector. These particles are Cosmic Rays, particles trapped in Earth's magnetic field, and secondaries from Cosmic Ray interacting with the atmosphere and the spacecraft. Here, we present a preliminary study of Cadmium Zinc Telluride (CZT) and its behaviour in space environments. We have used the simulation package MGGPOD to estimate the background of the CZT detectors in the proposed Energetic X-ray Imaging Survey Telescope (EXIST) for possible orbital parameters. The EXIST mission will make use of ~6 m2 of >0.5 cm thick CZT detectors to record cosmic X-rays in the energy range from 10 keV to 600 keV. The detectors will be shielded by a fully or partly active shield. For the specific detector and shielding geometry considered here and an orbit with a low (7°) inclination, the background rate is dominated by diffuse extragalactic photons below ~200 keV. Prompt and delayed hadronic backgrounds grow increasingly important above this energy, becoming the main contributors to the total background above ~1 MeV. A fully active shield performs slightly better than a half active/half passive shield.
The Research for Soft Measuring Technique of Sintering Burning Through Point

Accurate control for burning through point (BTP) can not only make the sintering process stable but also use the sintering area effectively. The condition of BTP affects the sintering output and quality. Currently there are no instruments that can be used to measure BTP online. In this paper, the online judgment of BTP is researched. The math model will be built based on the relation of measurable variables with BTP to judge the BTP online. Quadratic curve is fitted according to three measured points including the highest waste gas in five windboxes at discharge end. Leading correction for inertia measuring elements is also taken. Based on the math model derived, a feedback correction of BTP by bringing in the temperature of waste gas in flue is needed duo to air leakage at discharge end to ensure the accurate of BTP judgment. In the paper an application of soft measuring technique of BTP is introduced. Digital filter algorithm suitable to inertia and slow time-various characteristics of temperature is also introduced
CEP Discussion Paper No 655 October 2004 The Self Selection of Migrant Workers Revisited

Work of low-skilled migrant workers from developing countries in developed economies is a growing phenomenon and a key political and economic issue. An extensive literature has found (for the most part) that these workers come from the lower part of the skill distribution. This paper revisits the issue, using a self-selection model, a unique data-set on migrant workers as well as on workers that chose not to migrate (‘stayers’), and direct estimation of the moments of the latent unobserved skill distributions. The main findings are that there are two dimensions to self-selection: in terms of observed skills, a substantial migration premium lures migrant workers, while very low returns to skills in the foreign economy deter skilled workers, leading to negative self-selection. In terms of unobservable skills, self-selection is found to be positive rather than negative. The latter finding entails substantial increases in mean wages and reduction in wage inequality, relative to random assignment and to the alternative of not migrating. The analysis also demonstrates that estimates of skill premia for migrants — an important issue in the immigration literature — are upward biased if selection is not accounted for. Relevant skills are multi-dimensional, hence assignments in this context are non-hierarchical.
Proliferation of A 375 Melanoma Cells via Nitric Oxide Release in Vitro Nitric Oxide / Nucleophile Complexes Inhibit the Updated

Cell-mediated antitumor effects have, in part, been attributed to the production of NO. Compounds which generate NO might, therefore, be useful in attenuating the growth of tumor cells. Six nitric oxide/nucleophile adducts that release NO spontaneously in solution were tested for their effectiveness in inhibiting DNA synthesis in A375 human melanoma cells. The complexes of NO with spermine, 3-(n-propylamino)propylamine (PAPA/NO), and diethylamine reduced thymidine incorporation by 50% at concentrations of 24, 44, and 128 MM,respectively. The degree of inhi bition was, in general, related to the rate and extent of NO release in solution. A melanoma cell clone sensitive to interleukin 1-mediated cytostasis (A375-C6) was no more sensitive to PAPA/NO than a clone resistant to interleukin l (A375-C5), suggesting that the differing inhibitory effects of interleukin 1 in the two A375 cell clones are not due to a differential sensitivity to nitric oxide. Oxymyoglobin (125 UM),a known scavenger of NO, restored the ability of A375-C6 cells to incorporate thymidine in the presence of up to 200 UM PAPA/NO. When PAPA/NO was added to a solution of oxymyoglobin, nitrosylmyoglobin was formed, indicating that the protective effect of myoglobin was due to scavenging of NO. The results are consistent with a nitric oxide-mediated mechanism for NO/ nucleophile cytostasis and suggest that such compounds may be useful as tools for investigating the role of reactive nitrogen intermediates in cyto stasis and cytotoxicity.
Secrecy Capacity of Space Keying with Two Antennas

Spatial modulation (SM) and space shift keying (SSK) use only one out of several transmit antennas at a time to transmit data via an antenna index. In such a system, the information is encoded by exploiting channel randomness i.e. the fact that channels between different transmit and receive antennas are random. This difference is used to distinguish among the transmit antennas. While SSK uses only antenna index to transmit data, SM also uses ordinary signal modulation. In wireless secrecy systems, one of the key performance measures is secrecy capacity. It specifies the rate at which the transmitter can communicates on the main link to the desired receiver while this information cannot be decoded by the eavesdropper. We investigate SM and SSK in the context of wireless secrecy capacity when the underlying modulation and the difference between the legitimate and eavesdropper signal to noise ratios (SNRs) are varied.
The Price equation framework to study disease within‐host evolution

The evolution of infectious diseases is known to affect epidemiological dynamics, but, for some viruses and bacteria, this evolution also takes place inside a host during the course of an infection. I develop an original approach to study intrahost evolutionary dynamics of quantitative disease traits. This approach can be expressed mathematically using the ‘Price equation’ framework recently developed in evolutionary epidemiology. This framework combines population genetics and within‐host population dynamics models to identify trade‐offs that affect disease intrahost evolution and to predict short‐term evolutionary dynamics of life‐history traits. I show that this can be applied to study the evolution of viruses competing for host cells or to study the coevolution between parasites and the immune system of the host. This framework can also easily incorporate experimental data. Studying intrahost evolutionary dynamics provides insight at the within‐host level, because it allows us to better understand the course of chronic infections, and at the epidemiological level, because it helps to study multi‐scale evolutionary processes. This framework can be used to address important biological issues, from immune escape to disease evolutionary response to treatments.
Auditory recognition of familiar and unfamiliar subjects with wind turbine noise

Considering the wide growth of the wind turbine market over the last decade as well as their increasing power size, more and more potential conflicts have arisen in society due to the noise radiated by these plants. Our goal was to determine whether the annoyance caused by wind farms is related to aspects other than noise. To accomplish this, an auditory experiment on the recognition of wind turbine noise was conducted to people with long experience of wind turbine noise exposure and to people with no previous experience to this type of noise source. Our findings demonstrated that the trend of the auditory recognition is the same for the two examined groups, as far as the increase of the distance and the decrease of the values of sound equivalent levels and loudness are concerned. Significant differences between the two groups were observed as the distance increases. People with wind turbine noise experience showed a higher tendency to report false alarms than people without experience.
Fusion of Manifold Learning and Spectral Clustering Algorithmwith Applications to Fault Diagnosis

Large amount of multivariate data in many areas of science raises the problem of data analysis and visualization. Focusing on high dimensional and nonlinear data analysis, an improved manifold learning algorithm is introduced, then a new approach is proposed by combining adaptive local linear embedding (ALLE) and recursively applying normalized cut algorithm (RANCA). A novel adaptive local linear embedding algorithm is employed for nonlinear dimension reduction of original dataset. The recursively applying normalized cut algorithm is used for clustering of low dimensional data. The simulation results on three UCI standard datasets show that the new algorithm maps high-dimensional data into low-dimensional intrinsic space, and perfectly solves the problem of higher dependence on the structure of datasets in the traditional methods. Thus classification accuracy and robustness of spectral clustering algorithm are remarkably improved. The experiment results on Tennessee-Eastman process (TEP) also demonstrate the feasibility and effectiveness in fault pattern recognition.
The prognostic and predictive value of serum CA19.9 in pancreatic cancer

Background Current staging methods for pancreatic cancer (PC) are inadequate, and biomarkers to aid clinical decision making are lacking. Despite the availability of the serum marker carbohydrate antigen 19.9 (CA19.9) for over two decades, its precise role in the management of PC is yet to be defined, and as a consequence, it is not widely used. Methods We assessed the relationship between perioperative serum CA19.9 levels, survival and adjuvant chemotherapeutic responsiveness in a cohort of 260 patients who underwent operative resection for PC. Results By specifically assessing the subgroup of patients with detectable CA19.9, we identified potential utility at key clinical decision points. Low postoperative CA19.9 at 3 months (median survival 25.6 vs 14.8 months, P = 0.0052) and before adjuvant chemotherapy were independent prognostic factors. Patients with postoperative CA 19.9 levels >90 U/ml did not benefit from adjuvant chemotherapy (P = 0.7194) compared with those with a CA19.9 of ≤90 U/ml (median 26.0 vs 16.7 months, P = 0.0108). Normalization of CA19.9 within 6 months of resection was also an independent favorable prognostic factor (median 29.9 vs 14.8 months, P = 0.0004) and normal perioperative CA19.9 levels identified a good prognostic group, which was associated with a 5-year survival of 42%. Conclusions Perioperative serum CA19.9 measurements are informative in patients with detectable CA19.9 (defined by serum levels of >5 U/ml) and have potential clinical utility in predicting outcome and response to adjuvant chemotherapy. Future clinical trials should prioritize incorporation of CA19.9 measurement at key decision points to prospectively validate these findings and facilitate implementation.
Directional enhancements for emergency navigation

We present a novel direction based shortest path search algorithm to guide evacuees during an emergency. It uses opportunistic communications (oppcomms) with low-cost wearable mobile nodes that can exchange packets at close range of a few to some tens of meters without help of an infrastructure. The algorithm seeks the shortest path to exits which are safest with regard to a hazard, and is integrated into an autonomous Emergency Support System (ESS) to guide evacuees in a built environment. The ESS that we propose, that includes the directional algorithm and the Oppcomms, are evaluated using simulation experiments with the DBES (Distributed Building Evacuation Simulator) tool by simulating a shopping centre where fire is spreading. The results show that the directional path finding algorithm can offer significant improvements for the evacuees. In particular, we see that the improved and more reliable communications offered by Oppcomms, especially when the number of evacuees is larger, can help to compensate for the effects of congestion and improve the overall success of the evacuation scheme. Throughout the simulations we observe improvements of a few percent, which can translate into a valuable number of more people that are safely evacuated when human lives and safety are at risk.
Using Continuous-Planning Techniques to Achieve Autonomy and Coordination Among Multiple Unmanned Aerial Vehicles

Abstract : Existing Unmanned Aerial Vehicle (UAV) systems exhibit shortcomings in providing continuous, responsive, timely, and detailed information and targeting support to Army tactical commander's combat operations in an Army XXI battlespace. To synchronize Tactical UAV (TUAV) missions with supported operations, time is the critical element. Anything that can reduce TUAV planning time, while maintaining plan effectiveness, will expedite execution of a TUAV1s mission. Autonomous flight with some ability to avoid and evade certain threats would increase survivability further. This paper begins by presenting some of the recent successes achieved by artificial intelligence (Al) planners and schedulers on complex real-world problems. It then attempts to show how NASA's demonstrated utility of a dynamic Al planning system prototype for conducting autonomous distributed planning and execution for a team of rovers engaged in missions to achieve science goals during planetary operations can be generalized and applied to a team of TUAVs. Last, it discusses some data collection opportunities that should appear due to the ability to place increasingly more processing and data storage capabilities onboard TUAVs and some of the key challenges to use those capabilities to produce more timely and immediately usable interpretations.
Tracing the Evolution of Pluralism in Community-Based Coalitions

Abstract: In this study, a crisis of leadership succession led to greater subsequent pluralism by the previously less inclusive coalition. Substantial tension existed between both coalitions and the federally funded Appalachia Cancer Network, especially around its evidence-based mission. The fact that this tension occurred even at the more locally inclusive site indicates that pluralism may vary across levels within the same coalition. This article contributes to theory by exploring how coalitions evolve over time across community boundaries, as well as to management practice by yielding guidance about how to build inclusive organizations.
Cosmological Parameter Determination from Counts of Galaxies

We study constraints that anticipated DEEP2 survey galaxy counts versus redshift data will place on cosmological model parameters in a model with space curvature and a constant cosmological constant Λ and in a spatially flat quintessence model with a time-variable Λ. These data will result in fairly tight constraints on these parameters. For example, if all other parameters of a spatially flat model with a constant Λ are known, the galaxy counts data should constrain the nonrelativistic matter density parameter Ω0 to about 5% (10%, 1.5%) at 1 σ with neutral (worst case, best case) assumptions about data quality.
Design and implementation of a flexible DMA controller in video codec system

To meet rigorous high sustained bandwidth demand and exploit the data level access parallelism, a new architecture of DMA controller aiming at multimedia applications is proposed in this paper. Through analyzing the characteristics of video data transfer, we customize four shared channels with block address-conversion algorithm to adapt to many regular memory-access patterns. Furthermore, in order to transfer plenty of macro blocks whose addresses are not consecutive, channel descriptor model is applied into the design, which provides the most flexibility in managing the system's transfers. Besides, the design can also perform boundary extension, priority arbitrage and parameter prefetching as well as data rearrangement process. The proposed design is implemented in H.264/RVC encoder chip by SMIC 65nm technology with a clock frequency of 250MHz and 23.6K equivalent logic gates. Experimental results show that the customized design performs around 2~4 times faster than traditional DMA controller, and the lower ratio of setting time to transfer time proves that the burden of the processor is reduced significantly.
Predicting Nucleic Acid Hybridization and Melting Profiles

Many applications in modern biotechnology require a rapid and sensitive prediction of hybridization or partial hybridization between an oligonucleotide and potential targets in a genomic DNA or mRNA database. In addition, the accurate prediction of melting profiles between an oligonucleotide and a target nucleic acid is also of great value. DNA and RNA chip technologies [16, 17], PCR primer design, sequencing by hybridization and gene diagnostic methods, including SNP detection, are all technologies for which these predictions are very important. DNA chips alone have numerous applications. They are useful to monitor whole genome gene expression [15]. They are well adapted to the detection of single nucleotide polymorphisms (SNPs) [8], to identifying organisms from their sequences [2] or the characterization of splicing variants [5]. They can be used for DNA sequencing [3] or to search for protein target sites on DNA [7]. Computational methods for hybridization and melting prediction tend to make use of existing tools. Thus the very well-known BLAST [1] program is used for database searching to determine oligonu-cleotide specificity. BLAST or MegaBLAST are inappropriate methods since they were designed to search for similarity based on an evolutionary model rather than hybridization based on equilibrium thermodynamics. Similarly, melting temperatures for folded, single stranded oligonucleotides, or hy-bridized pairs of single stranded nucleic acids are usually determined using simple two state models that assume a single, presumably minimum energy folding, or hybridization versus a totally unfolded or non-hybridized state. In the case of hybridization, the target is assumed to be the reverse complement , with possibly a few mismatches allowed, so that no computation is needed to determine the hybridized state. In some cases, melting temperatures are estimated by using ad hoc methods based on GC content. We have undertaken a research program to provide more sophisticated and therfore, we hope, more accurate algorithms and software to address the above issues. In the case of DNA or RNA melting, the work is also of theoretical interest, since we are attempting to determine entire melting profiles, and not just melting temperatures. In addition, we are attempting to determine thermodynamic values, such as the free energy, enthalpy and entropy changes during melting. These can be measured using calorimetric methods. We have already created a prototype version of a program that we have named " FASTH " (FAST Hybridization). The name was deliberately chosen because of similarities to the existing FASTA software [9, 11, …
Computer Modeling Strategies for Meta-analysis

Over the past decade, meta-analyses have played an increasingly important role in summarizing clinical information and informing policy. Consequently, a new generation of meta-analysts have come forth and the demand for a streamlined modeling approach has emerged. In particular, compared to linear model estimation, many aspects of selecting and tting models for meta-analysis involve nonstandard data structures and statistical assumptions. For example, each data point in the analysis is associated with its own measure of precision that must be accounted for in the estimation process. Other study variables such as study design covariates, within-study predictors, and other aspects of the studies also play an important role when making inferences. Model-selection therefore can be considerably facilitated by exploratory graphical analyses. In this Chapter, we discuss exploratory methods and a uniied modeling approach to meta-analysis which integrates xed, random and mixed eeects models, as well as Bayesian hierarchical models into one framework. The authors gratefully acknowledge their colleagues with whom they have collaborated in the development of MetaGraphs, c a software package designed to perform meta-analysis using Hierarchical Bayes Linear Models: Richard
A Study on Voice Sobriety Test Algorithm in a Time-Frequency Domain

Voice is an important tool to identify individuals. In recent years, the voice can determine personality, age, and health status as well as physical conditions such as height and stature. The purpose of this paper is to develop an algorithm to determine whether when one is intoxicated by using the voice; characteristic parameters of the intoxicated voice signal were extracted by comparing the voices before and after drinking using several speech analysis methods. First, the change was observed in the body, glottis and vocal tract after drinking in order to examine the influence of drinking on phonation. In addition, differences of voice signals of a variety of the speakers were examined before and after drinking in order to find characteristic parameters for intoxicated voice signal that enable a judgment about whether or not one is drunk. The result of this study is expected to prevent drinking and driving, if applied to the development of the intoxication judgment system.