Miracle-dz/UniFAR-FTUs huggingface dataset:
Design space exploration of the turbo decoding algorithm on GPUs

In this paper, we explore the design space of the Turbo decoding algorithm on GPUs and find a performance bottleneck. We consider three axes for the design space exploration: a radix degree, a parallelization method, and the number of sub-frames per thread block. In Turbo decoding, a degree of radix affects computational complexity and memory access patterns in both algorithmic and implementation viewpoints. Second, computations of branch metrics (BMs) and state metrics (SMs) have a different degree of parallelism, which affects the mapping method of computational tasks to GPU threads. Finally, we can easily adjust the number of sub-frames per thread block to balance the occupancy and memory access traffic. Experimental results show that the radix-4 algorithm with the SM-centric mapping method shows the best performance at four sub-frames per thread block. According to our analysis, two factors -- the occupancy and shared memory bank conflicts -- differentiate the performance of different cases in the design space. We show further performance improvements by optimizing a kernel operation (max*) and applying the MAX-Log-Maximum A Posteriori (MAP) algorithm. A performance bottleneck at the finally optimized case is global memory access latency. Since the most optimized performance is comparable to that of the other programmable platforms, the GPU can be considered as another type of coprocessor for Turbo decoding implementations in mobile devices.
Accurate Respiration Measurement Using DC-Coupled Continuous-Wave Radar Sensor for Motion-Adaptive Cancer Radiotherapy

Accurate respiration measurement is crucial in motion-adaptive cancer radiotherapy. Conventional methods for respiration measurement are undesirable because they are either invasive to the patient or do not have sufficient accuracy. In addition, measurement of external respiration signal based on conventional approaches requires close patient contact to the physical device which often causes patient discomfort and undesirable motion during radiation dose delivery. In this paper, a dc-coupled continuous-wave radar sensor was presented to provide a noncontact and noninvasive approach for respiration measurement. The radar sensor was designed with dc-coupled adaptive tuning architectures that include RF coarse-tuning and baseband fine-tuning, which allows the radar sensor to precisely measure movement with stationary moment and always work with the maximum dynamic range. The accuracy of respiration measurement with the proposed radar sensor was experimentally evaluated using a physical phantom, human subject, and moving plate in a radiotherapy environment. It was shown that respiration measurement with radar sensor while the radiation beam is on is feasible and the measurement has a submillimeter accuracy when compared with a commercial respiration monitoring system which requires patient contact. The proposed radar sensor provides accurate, noninvasive, and noncontact respiration measurement and therefore has a great potential in motion-adaptive radiotherapy.
Optimised scheduling for Wireless Mesh Networks using fixed cycle times

In this paper, we consider the optimisation of transmission schedules for infrastructure Wireless Mesh Networks in which data is forwarded through mesh routers from a single Internet Gateway node. The mesh routers receive and aggregate data from local mobile devices and each mesh router has an assigned data allowance to ensure fairness, set depending on its geographical position or the predicted usage patterns. We examine the use of fair and efficient link scheduling for Wireless Mesh Networks and provide an integer program for maximising the throughput allowance for each mesh router in a network given the topology. The program uses a slotted time approach to maximise the throughput within a given number of slots N, thus allowing a network to be split into sub networks for local access to the mesh routers, and back-haul transmissions to the gateway. Results are presented showing the optimised throughput for a selection of networks and a range of values for N.
Introduction to the Shallow Parsing Contest for South Asian Languages

As part of the IJCAI workshop on ”Shallow Parsing for South Asian Languages”, a contest was held in which the participants trained and tested their shallow parsing systems for Hindi, Bengali and Telugu. This paper gives the complete account of the contest in terms of how the data for the three languages was released, the performances of the participating systems and an overview of the approaches followed for POS tagging and chunking. We finally give an analysis of the systems which gives insights to directions for future research on shallow parsing for South Asian languages.
Design and experiments of a novel axial flux circumferential current permanent magnet (AFCC) machine with radial airgap

In this paper, an improvement to the axial flux, circumferential current (AFCC) machine is presented by introducing a radial airgap instead of an axial airgap. Sizing equations and three-dimensional finite element analyses are presented to predict the flux distribution, inductance, torque capability and other performances of this novel machine. Time-domain simulations are also performed to confirm the analysis and operation with a power converter. Design guidelines have been summarized for the quest for machine topologies with high power density or high torque capability. A prototype of the machine had been designed, built and tested with a closed-loop drive system based on DSP technology. The test results of the system are compared with the estimations. It is found that the machine offers larger torque capability in comparison with traditional commercial induction machines and brushless permanent magnet machines.
Geometric Unique Set Cover on Unit Disks and Unit Squares

We study the Unique Set Cover problem on unit disks and unit squares. For a given set $P$ of $n$ points and a set $D$ of $m$ geometric objects both in the plane, the objective of the Unique Set Cover problem is to select a subset $D'\subseteq D$ of objects such that every point in $P$ is covered by at least one object in $D'$ and the number of points covered uniquely is maximized, where a point is covered uniquely if the point is covered by exactly one object in $D'$. In this paper, (i) we show that the Unique Set Cover is NP-hard on both unit disks and unit squares, and (ii) we give a PTAS for this problem on unit squares by applying the mod-one approach of Chan and Hu (Comput. Geom. 48(5), 2015).
Chromatin Landscape Dictates HSF Binding to Target DNA Elements

Sequence-specific transcription factors (TFs) are critical for specifying patterns and levels of gene expression, but target DNA elements are not sufficient to specify TF binding in vivo. In eukaryotes, the binding of a TF is in competition with a constellation of other proteins, including histones, which package DNA into nucleosomes. We used the ChIP-seq assay to examine the genome-wide distribution of Drosophila Heat Shock Factor (HSF), a TF whose binding activity is mediated by heat shock-induced trimerization. HSF binds to 464 sites after heat shock, the vast majority of which contain HSF Sequence-binding Elements (HSEs). HSF-bound sequence motifs represent only a small fraction of the total HSEs present in the genome. ModENCODE ChIP-chip datasets, generated during non-heat shock conditions, were used to show that inducibly bound HSE motifs are associated with histone acetylation, H3K4 trimethylation, RNA Polymerase II, and coactivators, compared to HSE motifs that remain HSF-free. Furthermore, directly changing the chromatin landscape, from an inactive to an active state, permits inducible HSF binding. There is a strong correlation of bound HSEs to active chromatin marks present prior to induced HSF binding, indicating that an HSE's residence in “active” chromatin is a primary determinant of whether HSF can bind following heat shock.
Specific DNA structural attributes modulate platinum anticancer drug site selection and cross-link generation

Heavy metal compounds have toxic and medicinal potential through capacity to form strong specific bonds with macromolecules, and the interaction of platinum drugs at the major groove nitrogen atom of guanine bases primarily underlies their therapeutic activity. By crystallographic analysis of transition metal–and in particular platinum compound–DNA site selectivity in the nucleosome core, we establish that steric accessibility, which is controlled by specific structural parameters of the double helix, modulates initial guanine–metal bond formation. Moreover, DNA conformational features can be linked to both similarities and distinctions in platinum drug adduct formation between the naked and nucleosomal DNA states. Notably, structures that facilitate initial platinum–guanine bond formation can oppose cross-link generation, rationalizing the occurrence of long-lived therapeutically ineffective monofunctional adducts. These findings illuminate DNA structure-dependent reactivity and provide a novel framework for understanding metal–double helix interactions, which should facilitate the development of improved chromatin-targeting medicinal agents.
DriverDB: an exome sequencing database for cancer driver gene identification

Exome sequencing (exome-seq) has aided in the discovery of a huge amount of mutations in cancers, yet challenges remain in converting oncogenomics data into information that is interpretable and accessible for clinical care. We constructed DriverDB (http://ngs.ym.edu.tw/driverdb/), a database which incorporates 6079 cases of exome-seq data, annotation databases (such as dbSNP, 1000 Genome and Cosmic) and published bioinformatics algorithms dedicated to driver gene/mutation identification. We provide two points of view, ‘Cancer’ and ‘Gene’, to help researchers to visualize the relationships between cancers and driver genes/mutations. The ‘Cancer’ section summarizes the calculated results of driver genes by eight computational methods for a specific cancer type/dataset and provides three levels of biological interpretation for realization of the relationships between driver genes. The ‘Gene’ section is designed to visualize the mutation information of a driver gene in five different aspects. Moreover, a ‘Meta-Analysis’ function is provided so researchers may identify driver genes in customer-defined samples. The novel driver genes/mutations identified hold potential for both basic research and biotech applications.
Patterns for Parallel Processing of Non-Linear Hierarchical Structures

Processing of large non-linear hierarchical structures could achieve better performance whether implemented over parallel environments. Although there are a wide range of applications for such parallelized structures, it lacks well-defined design patterns to model them, even though some parallel programming patterns had already been proposed. This paper proposes a set of design patterns that address these issues as well as it suggests some applications of them.
Trajectory training considering global variance for speech synthesis based on neural networks

This paper proposes a new training method of deep neural networks (DNNs) for statistical parametric speech synthesis. DNNs are recently used as acoustic models that represent mapping functions from linguistic features to acoustic features in statistical parametric speech synthesis. There are problems to be solved in conventional DNN-based speech synthesis: 1) the inconsistency between the training and synthesis criteria; and 2) the over-smoothing of the generated parameter trajectories. In this paper, we introduce the parameter trajectory generation process considering the global variance (GV) into the training of DNNs. A unified framework which consistently uses the same criterion in both training and synthesis can be obtained and the model parameters are optimized for parameter generation considering the GV in the proposed method. Experimental results show that the proposed method outperforms the conventional method in the naturalness of synthesized speech.
Effect on Renal Function of Restoration of Euthyroidism in Hyperthyroid Cats with Iatrogenic Hypothyroidism

Background Iatrogenic hypothyroidism is associated with an increased incidence of azotemia after treatment of hyperthyroidism, and decreased survival time in azotemic hyperthyroid cats. Hypothesis Restoration of euthyroidism will decrease plasma creatinine concentrations. Animals Nineteen client‐owned, methimazole‐ or carbimazole‐treated, hyperthyroid cats with documented iatrogenic hypothyroidism (based on subnormal plasma total thyroxine concentrations [TT4] and increased plasma thyroid‐stimulating hormone concentrations). Methods Prospective interventional study. Doses of antithyroid medication were reduced until euthyroidism was restored (TT4 10–40 nmol/L). Plasma creatinine concentration and selected other clinicopathologic variables were evaluated before and after restoration of euthyroidism and compared by nonparametric statistics. Data are presented as median [25th, 75th percentile]. Results Restoration of euthyroidism was associated with a significant decrease in plasma creatinine concentrations (2.61 [1.90, 3.26] mg/dL versus 2.07 [1.42, 2.82] mg/dL; P < .001) and body weight (4.03 [3.59, 4.53] kg versus 3.89 [3.34, 4.18] kg; P = .019), and a significant increase in packed cell volume (30 [28, 39]% versus 34 [29, 39]%; P = .038), heart rate (174 [163, 201] bpm versus 190 [164, 202] bpm; P = .009), and plasma alkaline phosphatase activity (26.6 [17.0, 33.0] IU/L versus 38.0 [23.5, 46.5] IU/L; P < .001). Conclusions and Clinical Importance Restoration of euthyroidism in medically treated hyperthyroid cats with iatrogenic hypothyroidism causes a reduction in plasma creatinine concentrations, and thus might improve renal function; however, this could be influenced by concurrent changes in body weight.
Conflicts as aversive signals : Investigations on the affective valence of conflict stimuli

According to a recent theory by Matthew Botvinick (2007), conflicts in information processing are aversive. This assumption, its boundaries and its functionality, have been examined in three studies. STUDY 1 tested if the conflict priming effect as found by Dreisbach and Fischer (2012a) can be reproduced with a different dependent variable, offering more clear-cut evidence for conflict aversiveness. Participants had to judge the valence of neutral German words or Chinese pictographs after being primed by conflict or non-conflict Stroop primes in two experiments. Results show that priming with conflict stimuli increases the frequency of negative judgments, thus giving unequivocal evidence for the aversiveness of conflicts. STUDY 2 was designed to test the time characteristics of the conflict priming effect. In three experiments, the results show that conflict priming is present already with a SOA of 200 ms, highlighting the similarity between conflicts and other aversive stimuli. Furthermore, Study 2 showed a reverse priming effect for a SOA of 800 ms with continued prime presentation, maybe due to processes of affective counter-regulation. STUDY 3 investigated whether it is the aversiveness of conflict stimuli that motivates conflict adaptation. In two separate experiments, subjects participated in two response conflict tasks, a color version of the Eriksen Flanker task and a manual version of the Stroop task. Here, the stimuli’s perceptual fluency (i.e., the ease of processing) was manipulated in short blocks of ten trials length. Disfluency (reduced figure-ground contrast) is associated with the experience of negative affect. Results showed that increasing the general stimulus aversiveness by adding disfluency eliminated conflict adaptation instead of increasing it. The results of the three studies are discussed in the light of current emotion and cognitive control research.
Livelihood Strategies and Development Interventions in the Southern Andes of Bolivia: Contrasting Views on Development

Based on the characteristics of the livelihood strategies of farmers in the northern part of Chuquisaca and Potosí (Bolivia) on the one hand, and the features of development interventions realized in this region on the other, this paper analyzes the point of contact; in other words the coincidence between farmers' strategies and development interventions from the drought (1983) until the present. The conclusion is that in many respects there are considerable contrasts in trends and priorities.
An investigation of inter-cell subcarrier collisions in OFDM-based cognitive radio networks

An OFDM-based cognitive radio (CR) system that assumes a random carrier access method is studied herein paper, where secondary users (SUs) randomly access the subcarriers belonging to the primary network. The SUs do not have access to any information concerning the availability of primary users (PUs) subcarriers because no spectrum sensing mechanism is employed. Therefore, subcarrier collisions may occur between the subcarriers of SUs and PUs. In addition, inter-cell collisions among the subcarriers of SUs belonging to different cells can occur due to the inherent nature of random access scheme. This paper conducts a stochastic analysis of the number of subcarrier collisions between the SUs' and PU's subcarriers assuming fixed and random number of subcarriers for each user, respectively. As a performance benchmark, the expression of the average capacity of a SU is derived and simulated under the Rayleigh channel fading model.
An improved measure for data clustering in high dimensional space

The k-means clustering fails to correctly cluster the data points in high dimensional space, primarily for employing Euclidean norm as the distance metric. The Euclidean metric increases with the increase in data dimension, thus posing difficulty to segregate intra-cluster and inter-cluster data points. Adoption of k-means clustering, realized with Euclidean distance norm, often misguides the selection of cluster centres in a given iteration. This paper proposes a novel approach to k-means clustering algorithm by replacing the Euclidean distance metric by a new one. The merit of the proposed metric lies in keeping the distance low, even for large dimensional data points. The new metric enables the algorithm to correctly select the cluster centres over the iterations. Experiments undertaken revealed that the said distance metric based k-means clustering outperforms the traditional one by a large margin.
Faces in the Distorting Mirror: Revisiting Photo-based Social Authentication

In an effort to hinder attackers from compromising user accounts, Facebook launched a form of two-factor authentication called social authentication (SA), where users are required to identify photos of their friends to complete a log-in attempt. Recent research, however, demonstrated that attackers can bypass the mechanism by employing face recognition software. Here we demonstrate an alternative attack. that employs image comparison techniques to identify the SA photos within an offline collection of the users' photos. In this paper, we revisit the concept of SA and design a system with a novel photo selection and transformation process, which generates challenges that are robust against these attacks. The intuition behind our photo selection is to use photos. that fail software-based face recognition, while remaining recognizable to humans who are familiar with the depicted people. The photo transformation process. creates challenges in the form of photo collages, where faces are transformed so as to render image matching techniques ineffective. We experimentally confirm the robustness of our approach against three template. matching algorithms that solve 0.4% of the challenges, while requiring four orders of magnitude more processing effort. Furthermore, when the transformations are applied, face detection software fails to detect even a single face. Our user studies confirm that users are able to identify their friends in over 99% of the photos with faces unrecognizable by software, and can solve over 94\% of the challenges with transformed photos.
Movie Recommender system using the user's psychological profile

In this paper we present Movie Recommender, a system which provides movie recommendations based on the information known about the users. These recommendations are done using the analysis of the users' psychological profile, their watching history and the movies scores from other websites. They are based on aggregate similarity calculation. The system uses both collaborative filtering and content filtering (using an approach based on different features of the movies from the database). Although there are similar applications available, they tend to ignore the data specific to the user, which in our opinion is essential for his/her behavior.
Beneficial therapeutic effects of Nigella sativa and/or Zingiber officinale in HCV patients in Egypt

Hepatitis C is a major global health burden and Egypt has the highest prevalence of hepatitis C virus (HCV) worldwide. The current study was designed to evaluate the beneficial therapeutic effects of ethanolic extracts of Nigella sativa, Zingiber officinale and their mixture in Egyptian HCV patients. Sixty volunteer patients with proven HCV and fifteen age matched healthy subjects were included in this study. Exclusion criteria included patients on interferon alpha (IFN-α) therapy, infection with hepatitis B virus, drug-induced liver diseases, advanced cirrhosis, hepatocellular carcinoma (HCC) or other malignancies, blood picture abnormalities and major severe illness. Liver function enzymes, albumin, total bilirubin, prothrombin time and concentration, international normalized ratio, alpha fetoprotein and viral load were all assessed at baseline and at the end of the study. Ethanolic extracts of Nigella sativa and Zingiber officinale were prepared and formulated into gelatinous capsules, each containing 500 mg of Nigella sativa and/or Zingiber officinale. Clinical response and incidence of adverse drug reactions were assessed initially, periodically, and at the end of the study. Both extracts as well as their mixture significantly ameliorated the altered viral load, alpha fetoprotein, liver function parameters; with more potent effect for the combined therapy. In conclusion, administration of Nigella sativa and/or Zingiber officinale ethanolic extracts to HCV patients exhibited potential therapeutic benefits via decreasing viral load and alleviating the altered liver function, with more potent effect offered by the mixture.
Virtual Worlds for Testing Robot Navigation: A Study on the Difficulty Level

The ability to navigate in diverse and previously unknown environments is a critical service of autonomous robots. We propose a test framework based on MORSE (Modular Open Robots Simulation Engine), and using the generation of virtual 3D worlds to challenge the navigation service. We elaborate on the notion of the difficulty of the generated worlds, which we characterize in terms of mission achievement, mission duration and trajectory curves. We experimentally study our ability to control the difficulty level by means of the generation parameters. We also assess the indeterminism of the navigation and how it evolves depending on the difficulty level. The experimental outcomes provide insights toward the definition of test strategies to further stress the navigation service.