Miracle-dz/UniFAR-FTUs huggingface dataset:
TWO DIFFERENT ARCHITECTURES FOR THE HARDWARE IMPLEMENTATION OF THE RIJNDAEL ALGORITHM

Two architectures and VLSI implementations of the AES Proposal Rijndael, are presented in this paper. These alternative architectures are operated both for encryption and decryption process. They reduce the required hardware resources and achieve high-speed performance. Their design philosophy is completely different. The first uses feedback logic and reaches a throughput value equal to 259 Mbit/sec. It performs efficiently in applications with low covered area resources. The second architectures is optimized for high-speed performance using pipelined technique. Its throughput can reach 3.65 Gbit/sec.
Encrypted Association Rule Mining for Outsourced Data Mining

Rule mining, for discovering valuable relations between items in large databases, has been a popular and well researched method for years. However, such old but important technique faces huge challenges and difficulties in the era of cloud computing although which affords both storage and computing scalability: 1) data are outsourced to a cloud due to data explosion and high storage and management cost, 2) moreover, data are usually encrypted first before being outsourced for privacy's sake. Existing privacy-preserving rule mining methods only assume a distributed model where every data owner holds the self data without encryption and together follow a secure protocol to perform rule mining. To address this limitation, we propose a novel Protocol for Outsourced Rule Mining (PORM) in this paper. PORM performs rule mining in a cloud environment where data are both encrypted and outsourced. We formally proved that PORM is both correct and secure, and we also extended PORM to the multiple-user scenario.
Distinct microRNA Expression Profile in Prostate Cancer Patients with Early Clinical Failure and the Impact of let-7 as Prognostic Marker in High-Risk Prostate Cancer

Background The identification of additional prognostic markers to improve risk stratification and to avoid overtreatment is one of the most urgent clinical needs in prostate cancer (PCa). MicroRNAs, being important regulators of gene expression, are promising biomarkers in various cancer entities, though the impact as prognostic predictors in PCa is poorly understood. The aim of this study was to identify specific miRNAs as potential prognostic markers in high-risk PCa and to validate their clinical impact. Methodology and Principal Findings We performed miRNA-microarray analysis in a high-risk PCa study group selected by their clinical outcome (clinical progression free survival (CPFS) vs. clinical failure (CF)). We identified seven candidate miRNAs (let-7a/b/c, miR-515-3p/5p, -181b, -146b, and -361) that showed differential expression between both groups. Further qRT-PCR analysis revealed down-regulation of members of the let-7 family in the majority of a large, well-characterized high-risk PCa cohort (n = 98). Expression of let-7a/b/and -c was correlated to clinical outcome parameters of this group. While let-7a showed no association or correlation with clinical relevant data, let-7b and let-7c were associated with CF in PCa patients and functioned partially as independent prognostic marker. Validation of the data using an independent high-risk study cohort revealed that let-7b, but not let-7c, has impact as an independent prognostic marker for BCR and CF. Furthermore, we identified HMGA1, a non-histone protein, as a new target of let-7b and found correlation of let-7b down-regulation with HMGA1 over-expression in primary PCa samples. Conclusion Our findings define a distinct miRNA expression profile in PCa cases with early CF and identified let-7b as prognostic biomarker in high-risk PCa. This study highlights the importance of let-7b as tumor suppressor miRNA in high-risk PCa and presents a basis to improve individual therapy for high-risk PCa patients.
Can programming be liberated from the von Neumann style?: a functional style and its algebra of programs

Conventional programming languages are growing ever more enormous, but not stronger. Inherent defects at the most basic level cause them to be both fat and weak: their primitive word-at-a-time style of programming inherited from their common ancestor—the von Neumann computer, their close coupling of semantics to state transitions, their division of programming into a world of expressions and a world of statements, their inability to effectively use powerful combining forms for building new programs from existing ones, and their lack of useful mathematical properties for reasoning about programs. An alternative functional style of programming is founded on the use of combining forms for creating programs. Functional programs deal with structured data, are often nonrepetitive and nonrecursive, are hierarchically constructed, do not name their arguments, and do not require the complex machinery of procedure declarations to become generally applicable. Combining forms can use high level programs to build still higher level ones in a style not possible in conventional languages. Associated with the functional style of programming is an algebra of programs whose variables range over programs and whose operations are combining forms. This algebra can be used to transform programs and to solve equations whose “unknowns” are programs in much the same way one transforms equations in high school algebra. These transformations are given by algebraic laws and are carried out in the same language in which programs are written. Combining forms are chosen not only for their programming power but also for the power of their associated algebraic laws. General theorems of the algebra give the detailed behavior and termination conditions for large classes of programs. A new class of computing systems uses the functional programming style both in its programming language and in its state transition rules. Unlike von Neumann languages, these systems have semantics loosely coupled to states—only one state transition occurs per major computation.
An Analysis of Stream processing Languages

Stream processing languages and stream processing engines have become more popular as they emerged from several modern data stream intensive applications such as sensor monitoring, stock markets and network monitoring. This study discusses the characteristics and features of the stream processing technology to provide an in-depth high-level guidance and comparison for stream processing systems and its underlying languages and technology with respect to the characteristics and features used by certain applications. The overall aim of this paper is to analyze and to identify the desired features of stream processing languages and to evaluate a few representative stream processing systems and languages on the basis of those desired features. The analysis could help in the identification of a suitable stream processing technology for particular applications as well as aiding the design and development of such languages for new, emerging applications.
HCRS: A Routing Scheme for Ad Hoc Networks as a QoS Guarantee Primitive

With the support of multimedia and real-time services in ad hoc networks, the design of a routing scheme supporting quality of service (QoS) is extremely challenging because of mobility, limited power, unpredictable radio channel behavior and constrained bandwidth, which is still an open issue for ad hoc networks at present. It was found that most present schemes do not consider network parameters other than the shortest path and bandwidth for routing decisions. This paper provides a routing scheme guaranteed QoS with multiple constraints for ad hoc networks: Hierarchical Cluster-Based Routing Scheme (HCRS). HCRS consists of two algorithms for intra- and inter-clusters aimed at different targets respectively. For inter-clusters routing, HCRS takes high-efficient and simple algorithm to guarantee stable route, while for intra-clusters routing, ant colony algorithm is very suitable to do this due to its flexibility and low computation complexity. Nevertheless, because of the defects of slow-convergence and stagnation phenomenon, we improve the ant colony algorithm to calculate different required QoS routes with multiple constraints. Here we take time delay, delay jitter, bandwidth, packet loss rate and cost into consideration. At last, the simulation results prove that HCRS is more effective.
TROPOSPHERIC OH PRIMARY PRODUCTION FROM ERS-2 DATA

In order to calculate the OH primary production rate from satellite measurements, one has to estimate the following quantities: profile of the photodissociation rate of ozone to O(D), tropospheric ozone profile and tropospheric water vapour profile. The estimation of tropospheric OH primary production rate from ERS-2 data is demonstrated. The tropospheric ozone profiles retrieved at the Rutherford Appleton Laboratory (RAL) from GOME narrow-swath mode (40 km by 80 km) available via the British Atmospheric Data Centre (BADC) are used. Tropospheric actinic flux profiles and photodissociation rates of ozone are calculated from GOME and ATSR-2 measurements using the TUV radiation model with the DISORT radiative transfer code. For partially cloudy GOME ground pixels the photodissociation rates are approximated as a linear combination from the clear-sky and the fully cloudy cases according to an independent pixel approximation. Total ozone, ozone profile, NO2 column, spectral albedo, solar spectrum, UTC date and time of pixel at the end of integration time, and ground pixel location co-ordinates are used in the TUV model from the GOME measurements. Thick and thin cloud fraction and cloud top height for GOME field of view (FOV) are used from the ATSR-2 measurements processed by RAL and available via BADC. The cloud optical thickness is determined from GOME albedo at 350 nm using the radiative transfer model. The simulated GOME albedo spectra are validated with the measured ones. Specific humidity profiles from ECMWF data are used to estimate the tropospheric OH primary production rates.
Prioritizing verification via value-based correctness criticality

Microprocessors are becoming increasingly susceptible to soft errors due to the current trends of semiconductor technology scaling. Traditional redundant multi-threading architectures provide good fault tolerance by re-executing all the computations. However, such a full re-execution significantly increases the demand on the processor resources, resulting in severe performance degradation. To address this problem, this paper introduces a correctness criticality based filter checker, which prioritizes the verification candidates so as to selectively do verification. Binary Correctness Criticality (BCC) and Likelihood of Correctness Criticality (LoCC) are metrics that quantify whether an instruction is important for reliability or how likely an instruction is correctness-critical, respectively. A likelihood of correctness criticality is computed by a value vulnerability factor, which is defined by the numerically significant bit-width used to compute a result. The proposed technique is accomplished by exploiting information redundancy of compressing computationally useful data bits. Based on the likelihood of correctness criticality test, the filter checker mitigates the verification workload by bypassing instructions that are unimportant for correct execution. Extensive measurements prove that the LoCC metric yields quite a wide distribution of values, indicating that it has the potential to differentiate diverse degrees of correctness criticality. Experimental results show that the proposed scheme accelerates a traditional fully-fault-tolerant processor by 1.7 times, while it reduces the soft error rate to 18% of that of a non-fault-tolerant processor.
Astrocytes Survive Chronic Infection and Cytopathic Effects of the ts1 Mutant of the Retrovirus Moloney Murine Leukemia Virus by Upregulation of Antioxidant Defenses

ABSTRACT The ts1 mutant of Moloney murine leukemia virus (MoMuLV) induces a neurodegenerative disease in mice, in which glial cells are infected by the retrovirus but neurons are not. ts1 infection of primary astrocytes, or of the immortalized astrocytic cell line C1, results in accumulation of the ts1 gPr80env envelope protein in the endoplasmic reticulum (ER), with ER and oxidative stress. Notably, only about half of the infected astrocytes die in these cultures, while the other half survive, continue to proliferate, and continue to produce virus. To determine how these astrocytes survive ts1 infection in culture, we established a chronically infected subline of the living cells remaining after the death of all acutely infected cells in an infected C1 cell culture (C1-ts1-S). We report here that C1-ts1-S cells proliferate more slowly, produce less virus, show reduced H2O2 levels, increase their uptake of cystine, and maintain higher levels of intracellular GSH and cysteine compared to acutely infected or uninfected C1 cells. C1-ts1-S cells also upregulate their thiol antioxidant defenses by activation of the transcription factor NF-E2-related factor 2 (Nrf2) and its target genes. Interestingly, despite maintenance of higher levels of intracellular reduced thiols, C1-ts1-S cells are more sensitive to cystine deprivation than uninfected C1 cells. We conclude that some ts1-infected astrocytes survive and adapt to virus-induced oxidative stress by successfully mobilizing their thiol redox defenses.
Detection of Attacks and QoS Improvement using Heterogeneous Green Framework in Cognitive Radio Network

— Energy-efficient communication has sparked tremendous interest in recent years as one of the main design goals of future wireless Heterogeneous Networks (HetNets). This has resulted in paradigm shift of current operation from data oriented to energy-efficient oriented networks. This framework is cognitive in holistic sense and aims at improving energy efficiency of the entire network, not presently one remote part of the association. In particular, a repeated approach, name as energy-cognitive sequence, which extend the standard cognitive phase and enables dynamic selection of different available strategies for reducing the energy consumption in the network while satisfying the quality of service constraints.
Using merged kinematic and anatomical data to evaluate humeral motion estimation: a pilot study

Optoelectronic systems are widely used in 3D motion capture. However, the reliability of the motion estimation depends on soft tissue artefacts and should therefore be validated. Two different sets of humeral markers were studied on four subjects. Anatomical and kinematic measurements were combined and the plausibility of the relative position of the bones in the glenohumeral joint during motion was evaluated using a new coherence index. Our findings show that an identical protocol leads to a large variability of the articular coherence for the subjects. However, the use of an extra marker on the distal part of the humerus improves the humeral kinematics for three of the four subjects. Scientists and clinicians using 3D systems should remain aware of the influence of subject-specific morphology on the accuracy of the measure. Differences with a reference group may come from clinical reasons but also from measurement errors due to the inter-individual morphological differences.
Optimal field measurement design for radio environment mapping

White spaces are locally or temporally available frequencies that are principally reserved for primary use such as TV broadcasting. The currently prevalent view to the utilization of such spectrum resources is that white space devices must query a geolocation database to obtain information about available frequencies and related maximum transmission powers. A geolocation database is fundamentally based on field strength estimates of the primary service obtained using radio propagation models. However, field strength estimates for geographically extensive broadcast networks are typically computed for spatial resolutions of hundreds of square meters. Therefore, even with the most sophisticated propagation models currently available, the predicted values always contain errors due to the limited geographical information. To overcome such deficiency, we propose a geostatistical approach for estimating the radio environment based on universal kriging interpolation. In addition, we optimize the locations of field measurements using spatial simulated annealing, and show that it improves significantly local field strength estimates. Index Terms-radio
Abdominal obesity is the most significant metabolic syndrome component predictive of cardiovascular events in chronic hemodialysis patients.

BACKGROUND Five components of metabolic syndrome (MetS) have been identified as predictive of cardiovascular events (CVEs) in the general population: impaired fasting glucose, abdominal obesity, hypertriglyceridemia, hypertension and low high-density lipoprotein cholesterol. Whether MetS and its components are also predictive of CVEs in chronic hemodialysis (HD) patients remains unclear. We therefore investigated the role of MetS and its components in patients on chronic HD. METHODS MetS at baseline was diagnosed in 91 HD patients based on the American Heart Association/National Heart, Lung and Blood Institute (AHA/NHLBI) and the International Diabetes Federation (IDF) definitions. During a 3-year period, all hospitalizations, CVEs and deaths were recorded and analyzed using Kaplan-Meier survival analysis and Cox regression. RESULTS There were no differences in the number of CVEs, hospitalizations or deaths between patients with and without AHA/NHLBI-defined MetS; however, patients with IDF-defined MetS were found to be at a higher risk for CVEs (P = 0.006). Cox regression analysis showed that, of the MetS components, abdominal obesity was the single most significant predictor of CVEs (hazard ratio 6.25; 95% confidence interval: 1.65-23.6; P = 0.007). CONCLUSIONS IDF-defined MetS was more predictive of CVEs than AHA/NHLBI-defined MetS. Of the MetS components, abdominal obesity was the single most significant predictor of CVEs in chronic HD patients.
The comparison and improvement of data processing methods in video quality subjective assessment

Data screening applied in video quality subjective assessment is helpful to remove abnormal observers and ensure the precision and effectiveness of the results. This paper firstly introduces two main data-processing methods, which are recommended in ITU-R BT.500 and ITU-R BT.1788 respectively, and then proposes an improved data-processing method, which is used to eliminate observers whose score trends are inconsistent with the overall trend in the first stage and then eliminate observers with too many outliers. Finally we analyze the applicability of those data-processing methods and verify the effectiveness of the improved method.
Main title Subtitle Sou dRecover and its benefit for Hearing Instrument wearers with a moderately-severe to severe hearing loss

Frequency compression is a proven new technique for improving the ability of people with hearing impairment to detect and recognise high-frequency sounds. As difficulty perceiving such sounds is one of the most common characteristics of hearing loss, the practical success of frequency compression is a significant advance in the field of hearing instruments. SoundRecover, a Phonak proprietary algorithm implementing frequency compression, was introduced recently in Naída UltraPower hearing instruments. Extensive trials have demonstrated the benefits of SoundRecover for many adults and children with severe to profound hearing impairment. Similar benefits may also be obtained by users of SoundRecover who have less-severe losses. Results from preliminary studies with Naída users having moderate or worse bilateral hearing loss show, that SoundRecover is generally both readily accepted and reported to assist with sound perception. This article explains the importance of SoundRecover even to hearing-instrument users with a moderately severe to severe hearing loss.
Robust adaptive detection in linearly precoded MIMO-OFDM systems with hard/soft decoding

Maximum likelihood detection (MLD) has been shown to offer large performance gains within the context of linearly precoded MIMO-OFDM systems with multiple-stream transmission when compared to an all-linear setup (i.e., linear transmitter/receiver), although at the cost of a higher computational complexity. To overcome this handicap, this paper proposes a method to selectively choose the detection strategy (ML or linear) as a function of the instantaneous channel conditions and the accuracy of the channel state information at the transmitter (CSIT). The proposed technique is suitable for both hard- and soft-decoded setups. Numerical results show that a cautious and selective use of ML detection substantially reduces complexity while still reaping most of the performance advantage.
A NONLINEAR HARMONIC BALANCE METHOD FOR THE CFD CODE OVERFLOW 2

Abstract. A National Aeronautics and Space Administration computational fluid dynamics code, OVERFLOW 2, was modified to utilize a harmonic balance solution method. This modification allows for the direct calculation of the nonlinear frequency-domain solution of a periodic unsteady flow while avoiding the time consuming calculation of long physical transients that arise in aeroelastic applications. With the usual implementation of this harmonic balance method, converting an implicit flow solver from a time marching solution method to a harmonic balance solution method results in an unstable numerical scheme. However, a relatively simple and computationally inexpensive stabilization technique has been developed and is utilized in this paper. With this stabilization technique, it is possible to convert an existing implicit time-domain solver to a nonlinear frequencydomain method with minimal modifications to the existing code. This new frequencydomain version of OVERFLOW 2 utilizes the many features of the original code, such as various discretization methods and several turbulence models. The use of Chimera overset grids in OVERFLOW 2 requires care when implemented in the frequency-domain. This paper presents a harmonic balance version of OVERFLOW 2 capable of solving on overset grids for sufficiently small unsteady amplitudes.
Rapid Fishery Assessment by Market Survey (RFAMS) – An Improved Rapid-Assessment Approach to Characterising Fish Landings in Developing Countries

The complex multi-gear, multi-species tropical fisheries in developing countries are poorly understood and characterising the landings from these fisheries is often impossible using conventional approaches. A rapid assessment method for characterising landings at fish markets, using an index of abundance and estimated weight within taxonomic groups, is described. This approach was developed for contexts where there are no detailed data collection protocols, and where consistent data collection across a wide range of fisheries types and geographic areas is required, regardless of the size of the site and scale of the landings. This methodology, which was demonstrated at seven fish landing sites/fish markets in southern Indonesia between July 2008 and January 2011, provides a rapid assessment of the abundance and diversity in the wild catch over a wide variety of taxonomic groups. The approach has wider application for species-rich fisheries in developing countries where there is an urgent need for better data collection protocols, monitoring future changes in market demographics, and evaluating health of fisheries.