Miracle-dz/UniFAR-FTUs huggingface dataset:
Efficient Sequential Consistency in GPUs via Relativistic Cache Coherence

Recent work has argued that sequential consistency (SC) in GPUs can perform on par with weak memory models, provided ordering stalls are made less frequent by relaxing ordering for private and read-only data. In this paper, we address the complementary problem of reducing stall latencies for both read-only and read-write data. We find that SC stalls are particularly problematic for workloads with inter-workgroup sharing, and occur primarily due to earlier stores in the same thread, a substantial part of the overhead comes from the need to stall until write permissions are obtained (to ensure write atomicity). To address this, we propose RCC, a GPU coherence protocol which grants write permissions without stalling but can still be used to implement SC. RCC uses logical timestamps to determine a global memory order and L1 read permissions, even though each core may see a different logical "time," SC ordering can still be maintained. Unlike previous GPU SC proposals, our design does not require invasive core changes and additional per-core storage to classify read-only/private data. For workloads with inter-workgroup sharing overall performance is 29% better and energy is 25% less than in best previous GPU SC proposals, and within 7% of the best non-SC design.
Improving Node Security in MANET Clusters: A Comparison Study of Two Fuzzy-Based Systems

A Mobile Ad hoc Network (MANET) is a multi-hop wireless network in which the mobile nodes are dynamic in nature and has a limited bandwidth and minimum battery power. Due to this challenging environment the mobile nodes can be grouped into clusters to achieve better stability and scalability. Grouping the mobile nodes is called clustering, in which a leader node is elected to manage the entire network. In this paper, first we introduce various approaches for clustering focus on different performance metrics. Then, we show some clustering schemes such as Mobility-based clustering, Energy-efficient clustering, Connectivity-based clustering, Weighted-based clustering. Finally, we present and compare two Fuzzy based systems (called F2SMC1 and F2SMC2) for improving the security of cluster nodes in MANETs. We compare the performance of F2SMC1 and F2SMC2 and show that the F2SMC2 is more complex than F2SMC1, but is more reliable and secure.
Explicit substitutions and higher-order syntax

Recently there has been a great deal of interest in higher-order syntax which seeks to extend standard initial algebra semantics to cover languages with variable binding by using functor categories. The canonical example studied in the literature is that of the untyped λ-calculus which is handled as an instance of the general theory of binding algebras, cf. Fiore, Plotkin, Turi [8]. Another important syntactic construction is that of explicit substitutions. The syntax of a language with explicit substitutions does not form a binding algebra as an explicit substitution may bind an arbitrary number of variables. Nevertheless we show that the language given by a standard signature Σ and explicit substitutions is naturally modelled as the initial algebra of the endofunctor Id + FΣ o - + - o - on a functor category. We also comment on the apparent lack of modularity in syntax with variable binding as compared to first-order languages.
Testability of Dynamic Real-Time Systems: An Empirical Study of Constrained Execution Environment Implications

Real-time systems must respond to events in a timely fashion; in hard real-time systems the penalty for a missed deadline is high. It is therefore necessary to design hard real-time systems so that the timing behavior of the tasks can be predicted. Static real-time systems have prior knowledge of the worst-case arrival patterns and resource usage. Therefore, a schedule can be calculated off-line and tasks can be guaranteed to have sufficient resources to complete (resource adequacy). Dynamic real-time systems, on the other hand, do not have such prior knowledge, and therefore must react to events when they occur. They also must adapt to changes in the urgencies of various tasks, and fairly allocate resources among the tasks. A disadvantage of static real-time systems is that a requirement on resource adequacy makes them expensive and often impractical. Dynamic realtime systems, on the other hand, have the disadvantage of being less predictable and therefore difficult to test. Hence, in dynamic systems, timeliness is hard to guarantee and reliability is often low. Using a constrained execution environment, we attempt to increase the testability of such systems. An initial step is to identify factors that affect testability. We present empirical results on how various factors in the execution environment impacts testability of real-time systems. The results show that some of the factors, previously identified as possibly impacting testability, do not have an impact, while others do.
Indicator-based Policy Compliance of Business Processes

Business process compliance management has recently grabbed a lot of attention in both business and academia as it helps organizations not only to control and monitor their business processes from a legal point of view but also to avoid financial penalties and undesirable consequences to their reputation. Balancing compliance obligations with business objectives remains however a difficult challenge. We believe goal-oriented compliance management using Key Performance Indicators (KPIs) to measure the compliance level of organizations is an area that can be further developed to tackle this challenge. Goaloriented compliance management concepts have been explored before. However, there is little research on how to measure and improve the compliance level of organizations using KPIs while considering the impact of candidate adjustments on business goals. We discuss a proposal toward a framework to address the aforementioned problems.
Hedging one's bets too much? A reply to Levelt (2002)

Levelt (2002) challenges the theoretical motivation and the interpretation of the data reported in Alario, Costa, and Caramazza's (2002) study on utterance planning during speech production. In this response we argue against these criticisms. First, we show that the hypotheses entertained in our research about the scope of phonological encoding are well motivated in the context of current theories of speech production. Second, we argue that although alternative interpretations of the frequency effect we report are logically possible, the available empirical evidence makes them very unlikely.
Deep multi-view representation learning for multi-modal features of the schizophrenia and schizo-affective disorder

This work is originated from the MLSP 2014 Classification Challenge which tries to automatically detect subjects with schizophrenia and schizo-affective disorder by analyzing multi-modal features derived from magnetic resonance imaging (MRI) data. We employ Deep Neural Network (DNN)-based multi-view representation learning for combining multimodal features. The DNN-based multi-view models include deep canonical correlation analysis (DCCA) and deep canonically correlated auto-encoders (DCCAE). In addition, support vector machine with Gaussian kernel is used to conduct classification with the compact bottleneck features learned by the deep multi-view models. Our experiments on the dataset provided by the MLSP Classification Challenge show that bottleneck features learned via deep multi-view models obtain better results than the trimming features used in the baseline system in terms of the receiver operating characteristic (ROC) area under the curve (AUC).
Audio-visual speech perception in mild cognitive impairment and healthy elderly controls

An audio-visual (AV) speech presentation mode can significantly improve spoken word identification. Language comprehension and communication in patients with Alzheimer disease (AD) can be compromised; however, little is known about the extent to which patients might benefit from an AV mode. Patients with mild cognitive impairment (MCI) are at risk for developing AD and can demonstrate parallel but milder difficulties in aspects of language function. Here we report on preliminary findings of a study that investigates the impact of AV speech and sentence context on word identification in patients with MCI and healthy elderly controls. Although both groups performed better in the AV condition compared to an auditory-alone condition and when a constraining sentence context was present, the patients performed worse than controls overall and in the condition that should afford the greatest benefit. This suggests that the cognitive deficits present in MCI may limit their ability to benefit fully from supportive perceptual and linguistic cues.
ANALISIS OVERREACTION HYPHOTHESIS, DANPENGARUH FIRM SIZE, LIKUIDITAS & BID-ASKSPREAD TERHADAP FENOMENA PRICEREVERSALDI BURSA EFEK JAKARTA

Dalam melakukan investasi, khususnya investasi dalam bentuk saham ketersediaan informasi merupakan hal yang penting. Para investor memerlukan informasi yang dipublikasikan maupun yang tidak dipublikasikan untuk menganalisis suatu saham sebelum akhirnya memutuskan untuk membeli atau menjual saham. Secara informasional, pasar modal dikatakan efisien bila harga sekuritas-sekuritasnya telah mencerminkan semua informasi yang tersedia dan relevan. Namun demikian banyak penelitian yang menyebutkan adanya beberapa fenomena yang tidak sesuai dengan hipotesis pasar efisien, salah satunya adalah fenomena pembalikan harga (price reversal). Fenomena ini berhubungan dengan anomali winner-loser yang menciptakan strategi investasi kontrarian. Penelitian ini bertujuan menganalisis keberadaan reaksi berlebihan dari investor dalam fenomena pembalikan harga, menganalisis apakah terdapat pengaruh dari ukuran perusahaan, likuiditas dan bid-ask spread terhadap pembalikan harga. Penelitian ini menguji return saham yang mengikuti satu hari perubahan besar harga saham di Bursa Efek Jakarta (BEJ) periode 2005 - 2006. Sampel dari penelitian ini menggunakan 171 perusahaan yang terdaftar di BEJ. Sampel ini kemudian diklasifikasikan lagi menjadi 48 perusahaan yang menjadi sampel winner dan 33 perusahaan yang menjadi sampel loser. Penelitian ini menggunakan data harian, sedangkan perhitungan abnormal return menggunakan Market Adjusted Model. Periode pengamatan dalam penelitian ini adalah 5 hari sebelum t=0 dan 20 hari setelah t=0. Analisis yang digunakan adalah uji t, korelasi, dan regresi berganda. Data yang digunakan dalam penelitian ini adalah closing price, IHSG, kapitalisasi pasar,volume perdagangan saham, serta bid dan ask price. Hasil penelitian melalui uji t mengidentifikasikan bahwa pada saham winner maupun loser terjadi pembalikan harga. Dari analisis korelasi, didapatkan hasil korelasi yang bernilai negatif dan signifikan berbeda dengan nol. Hal ini menunjukkan terdapat reaksi berlebihan dari investor. Reaksi berlebihan ini kemudian disadari investor sehingga melakukan koreksi terhadap tindakan tersebut. Pada saham winner, periode koreksi yang dibutuhkan adalah selama 13 hari setelah hari peristiwa, sedangkan saham loser hanya memerlukan waktu selama 5 hari setelah hari perubahan besar harga saham. Terdapatnya reaksi berlebihan dari investor dalam pembalikan harga mengimplikasikan bahwa pasar belum efisien, karena harga saham dapat diprediksikan berdasarkan harga saham masa lalu. Persamaan regresi untuk saham winner dan loser menunjukkan bahwa ukuran perusahaan, likuiditas dan bidask spread berpengaruh secara signifikan terhadap pembalikan harga. Hal ini berarti investor dapat mempertimbangkan faktor ukuran perusahaan, likuiditas dan bid-ask spread dalam memprediksi harga saham yang akan datang sehingga dapat melakukan contrarian strategy (strategi berkebalikan) dengan tepat.
CQRD: A switch-based approach to flow interference in Data Center Networks

Modern data centers need to satisfy stringent low-latency for real-time interactive applications (e.g. search, web retail). However, short delay-sensitive flows often have to wait a long time for memory and link resource occupied by a few of long bandwidth-greedy flows because they share the same switch output queue (OQ). To address the above flow interference problem, this paper advocates more fine-grained flow separation in the switches than traditional OQ. We propose CQRD, a simple and cost-effective queue management scheme for data center switches, through only minor changes to the buffering and scheduling scheme. No change to the transport layer or coordination among switches is required. Simulation results show that CQRD can reduce the FCT of short flows by 20-44% in a single switch and 8-30% in a multi-stage data center switch network, only at the cost of a minor goodput decrease of large of flows.
The Emerging Role of Emotional Intelligence in Business Communication Classes

The present invention provides for the use of Tripterygium wilfordii Hook F extracts and purified components thereof in the treatment of inflammation or an immune disorder with concomitant lack of steroidal effect. Extracts of this plant (T2) bound to the glucocorticoid receptor and competitively inhibited glucocorticoid mediated cellular processes, such as dexamethasone binding to the glucocorticoid receptor, glucocorticoid mediated activation of target genes, dexamethasone dependent cellular growth, with concomitant inhibition of cyclooxygenase-2 induction and inflammatory processes such as the production of prostaglandin E2. The T2 extract components triptolide and tripdiolide were effective inhibitors. The particular advantage provided by the methods herein is the treatment or prevention of inflammation and the concomitant lack of steroidal agonist effects and NSAID side effects. Conditions treatable by the present methods include inflammation and immune disorders including autoimmune disease.
Biological Crystallography Structural and Biochemical Analyses of Alanine Racemase from the Multidrug-resistant Clostridium Difficile Strain 630

Clostridium difficile, a Gram-positive, spore-forming anae-robic bacterium, is the leading cause of infectious diarrhea among hospitalized patients. C. difficile is frequently associated with antibiotic treatment, and causes diseases ranging from antibiotic-associated diarrhea to life-threatening pseudo-membranous colitis. The severity of C. difficile infections is exacerbated by the emergence of hypervirulent and multi-drug-resistant strains, which are difficult to treat and are often associated with increased mortality rates. Alanine racemase (Alr) is a pyridoxal-5 0-phosphate (PLP)-dependent enzyme that catalyzes the reversible racemization of land d-alanine. Since d-alanine is an essential component of the bacterial cell-wall peptidoglycan, and there are no known Alr homologs in humans, this enzyme is being tested as an antibiotic target. Cycloserine is an antibiotic that inhibits Alr. In this study, the catalytic properties and crystal structures of recombinant Alr from the virulent and multidrug-resistant C. difficile strain 630 are presented. Three crystal structures of C. difficile Alr (CdAlr), corresponding to the complex with PLP, the complex with cycloserine and a K271T mutant form of the enzyme with bound PLP, are presented. The structures are prototypical Alr homodimers with two active sites in which the cofactor PLP and cycloserine are localized. Kinetic analyses reveal that the K271T mutant CdAlr has the highest catalytic constants reported to date for any Alr. Additional studies are needed to identify the basis for the high catalytic activity. The structural and activity data presented are first steps towards using CdAlr for the development of structure-based therapeutics for C. difficile infections.
Concept-based Summarization using Integer Linear Programming: From Concept Pruning to Multiple Optimal Solutions

In concept-based summarization, sentence selection is modelled as a budgeted maximum coverage problem. As this problem is NP-hard, pruning low-weight concepts is required for the solver to find optimal solutions efficiently. This work shows that reducing the number of concepts in the model leads to lower Rouge scores, and more importantly to the presence of multiple optimal solutions. We address these issues by extending the model to provide a single optimal solution, and eliminate the need for concept pruning using an approximation algorithm that achieves comparable performance to exact inference.
Doxorubicin blocks proliferation of cancer cells through proteolytic activation of CREB3L1

Doxorubicin is used extensively for chemotherapy of diverse types of cancer, yet the mechanism through which it inhibits proliferation of cancer cells remains unclear. Here we report that doxorubicin stimulates de novo synthesis of ceramide, which in turn activates CREB3L1, a transcription factor synthesized as a membrane-bound precursor. Doxorubicin stimulates proteolytic cleavage of CREB3L1 by Site-1 Protease and Site-2 Protease, allowing the NH2-terminal domain of CREB3L1 to enter the nucleus where it activates transcription of genes encoding inhibitors of the cell cycle, including p21. Knockdown of CREB3L1 mRNA in human hepatoma Huh7 cells and immortalized human fibroblast SV589 cells conferred increased resistance to doxorubicin, whereas overexpression of CREB3L1 in human breast cancer MCF-7 cells markedly enhanced the sensitivity of these cells to doxorubicin. These results suggest that measurement of CREB3L1 expression may be a useful biomarker in identifying cancer cells sensitive to doxorubicin. DOI: http://dx.doi. org/10.7554/eLife.00090. 001
Transcriptomic Profile Reveals Gender-Specific Molecular Mechanisms Driving Multiple Sclerosis Progression

Background Although the most common clinical presentation of multiple sclerosis (MS) is the so called Relapsing-Remitting MS (RRMS), the molecular mechanisms responsible for its progression are currently unknown. To tackle this problem, a whole-genome gene expression analysis has been performed on RRMS patients. Results The comparative analysis of the Affymetrix Human Gene 1.0 ST microarray data from peripheral blood leucocytes obtained from 25 patients in remission and relapse and 25 healthy subjects has revealed 174 genes altered in both remission and relapse, a high proportion of them showing what we have called “mirror pattern”: they are upregulated in remission and downregulated in relapse or vice versa. The coexpression analysis of these genes has shown that they are organized in three female-specific and one male-specific modules. Conclusions The interpretation of the modules of the coexpression network suggests that Epstein-Barr virus (EBV) reactivation of B cells happens in MS relapses; however, qPCR expression data of the viral genes supports that hypothesis only in female patients, reinforcing the notion that different molecular processes drive disease progression in females and males. Besides, we propose that the “primed” state showed by neutrophils in women is an endogenous control mechanism triggered to keep EBV reactivation under control through vitamin B12 physiology. Finally, our results also point towards an important sex-specific role of non-coding RNA in MS.
Control of a biped robot driven by elastomer-based series elastic actuator

This paper proposes the novel force control method based on higher-order derivative for high-backdrivable actuation of the robot employing elastomer-based series elastic actuators (SEAs). Control of SEAs is generally difficult because they consist of an underactuated 2-inertia system. Previously, we control it with a position control method. Lately, we employ a torque control method to overcome several problems. The new one enable robot to be controlled more easily, safely and efficiently. To evaluate this method, the experiments of previous position control method, conventional force control method, and proposed force control method are performed.
Taxonomy development in information systems: Developing a taxonomy of mobile applications

The complexity of the information systems field often lends itself to classification schemes, or taxonomies, which provide ways to understand the similarities and differences among objects under study. Developing a taxonomy, however, is a complex process that is often done in an ad hoc way. This research-in-progress paper uses the design science paradigm to develop a systematic method for taxonomy development in information systems. The method we propose uses an indicator or operational level model that combines both empirical to deductive and deductive to empirical approaches. We evaluate this method by using it to develop a taxonomy of mobile applications, which we have chosen because of their ever-increasing number and variety. The resulting taxonomy contains seven dimensions with fifteen characteristics. We demonstrate the usefulness of this taxonomy by analyzing a range of current and proposed mobile applications. From the results of this analysis we identify combinations of characteristics where applications are missing and thus are candidates for new and potentially useful applications.
CG-3 — Beyond Classical Constraint Grammar

This paper discusses methodological strengths and shortcomings of the Constraint Grammar paradigm (CG), showing how the classical CG formalism can be extended to achieve greater expressive power and how it can be enhanced and hybridized with techniques from other parsing paradigms. We present a new, largely theory­independent CG framework and rule compiler (CG­3), that allows the linguist to write CG rules incorporating different types of linguistic information and methodology from a wide range of parsing approaches, covering not only CG's native topological technique, but also dependency grammar, phrase structure grammar and unification grammar. In addition, we allow the integration of statistical­numerical constraints and non­discrete tag and string sets.
Involvement of Glyceraldehyde-3-phosphate Dehydrogenase in the X-Ray Resistance of HeLa Cells

We investigated changes in the sub-cellular distribution of glycelaldehyde-3-phosphate dehydrogenase (GAPDH) after X-ray irradiation in HeLa cells. Twenty-four h after irradiation at 5 Gy, nuclear GAPDH levels increased 2.6-fold, whereas total GAPDH levels increased only 1.2-fold. Knockdown of GAPDH using specific small interfering RNA (siRNA) led to sensitization to X-ray-induced cell death. These results suggest that GAPDH plays a role in the radioresponse.