Miracle-dz/UniFAR-FTUs huggingface dataset:
Terabyte-scale image similarity search: Experience and best practice

While the past decade has witnessed an unprecedented growth of data generated and collected all over the world, existing data management approaches lack the ability to address the challenges of Big Data. One of the most promising tools for Big Data processing is the MapReduce paradigm. Although it has its limitations, the MapReduce programming model has laid the foundations for answering some of the Big Data challenges. In this paper, we focus on Hadoop, the open-source implementation of the MapReduce paradigm. Using as case-study a Hadoop-based application, i.e., image similarity search, we present our experiences with the Hadoop framework when processing terabytes of data. The scale of the data and the application workload allowed us to test the limits of Hadoop and the efficiency of the tools it provides. We present a wide collection of experiments and the practical lessons we have drawn from our experience with the Hadoop environment. Our findings can be shared as best practices and recommendations to the Big Data researchers and practioners.
A spiking Basal Ganglia model of synchrony, exploration and decision making

To make an optimal decision we need to weigh all the available options, compare them with the current goal, and choose the most rewarding one. Depending on the situation an optimal decision could be to either “explore” or “exploit” or “not to take any action” for which the Basal Ganglia (BG) is considered to be a key neural substrate. In an attempt to expand this classical picture of BG function, we had earlier hypothesized that the Indirect Pathway (IP) of the BG could be the subcortical substrate for exploration. In this study we build a spiking network model to relate exploration to synchrony levels in the BG (which are a neural marker for tremor in Parkinson's disease). Key BG nuclei such as the Sub Thalamic Nucleus (STN), Globus Pallidus externus (GPe) and Globus Pallidus internus (GPi) were modeled as Izhikevich spiking neurons whereas the Striatal output was modeled as Poisson spikes. The model is cast in reinforcement learning framework with the dopamine signal representing reward prediction error. We apply the model to two decision making tasks: a binary action selection task (similar to one used by Humphries et al., 2006) and an n-armed bandit task (Bourdaud et al., 2008). The model shows that exploration levels could be controlled by STN's lateral connection strength which also influenced the synchrony levels in the STN-GPe circuit. An increase in STN's lateral strength led to a decrease in exploration which can be thought as the possible explanation for reduced exploratory levels in Parkinson's patients. Our simulations also show that on complete removal of IP, the model exhibits only Go and No-Go behaviors, thereby demonstrating the crucial role of IP in exploration. Our model provides a unified account for synchronization, action section, and explorative behavior.
STAT1‐dependent IgG cell‐surface expression in a human B cell line derived from a STAT1‐deficient patient

STAT1 is a key effector of cytokines involved in the resistance to pathogens; its identified transcriptional targets mediate the innate immune response involved in the defense against viruses and bacteria. Little is known about the role of STAT1 in adaptive immunity, including its impact on BCR or surface Ig expression. Analysis of this point is difficult in humans, as STAT1 deficiency is extremely rare. SD patients die early in childhood from a severe immunodeficiency. Herein, a SD B cell line obtained from a SD patient was compared with a B cell line from a STAT1‐proficient subject in search of differences in surface Ig expression. In this SD B cell line, a complete absence of surface IgG was noted. The mRNA encoding the surface form of IgG was detected only in STAT1‐proficient B cells; the mRNAs encoding the secreted and the surface forms were detected in SD and STAT1‐proficient B cells. Re‐expression of STAT1 in SD B cells restored surface IgG expression and a functional BCR. Conversely, shRNA silencing of STAT1 in B cells reduced considerably the expression of the surface IgG. Although limited to one B cell line, these results suggest that STAT1 may play an essential role in surface IgG expression in human B cells. Possible mechanisms involve regulation of mRNA splicing, transcription, or both. These observations extend the role of STAT1 further in adaptive immunity, including the regulation of BCR expression.
Multimodal Multiplatform Social Media Event Summarization

Social media platforms are turning into important news sources since they provide real-time information from different perspectives. However, high volume, dynamism, noise, and redundancy exhibited by social media data make it difficult to comprehend the entire content. Recent works emphasize on summarizing the content of either a single social media platform or of a single modality (either textual or visual). However, each platform has its own unique characteristics and user base, which brings to light different aspects of real-world events. This makes it critical as well as challenging to combine textual and visual data from different platforms. In this article, we propose summarization of real-world events with data stemming from different platforms and multiple modalities. We present the use of a Markov Random Fields based similarity measure to link content across multiple platforms. This measure also enables the linking of content across time, which is useful for tracking the evolution of long-running events. For the final content selection, summarization is modeled as a subset selection problem. To handle the complexity of the optimal subset selection, we propose the use of submodular objectives. Facets such as coverage, novelty, and significance are modeled as submodular objectives in a multimodal social media setting. We conduct a series of quantitative and qualitative experiments to illustrate the effectiveness of our approach compared to alternative methods.
Hidden Markov Models for Microarray Time Course Data in Multiple Biological Conditions

Among the first microarray experiments were those measuring expression over time, and time course experiments remain common. Most methods to analyze time course data attempt to group genes sharing similar temporal profiles within a single biological condition. However, with time course data in multiple conditions, a main goal is to identify differential expression patterns over time. An intuitive approach to this problem would be to apply at each time point any of the many methods for identifying differentially expressed genes across biological conditions and then somehow combine the results of the repeated marginal analyses. But considering each time point in isolation is inefficient, because it does not use the information contained in the dependence structure of the time course data. This problem is exacerbated in microarray studies, where low sensitivity is a problematic feature of many methods. Furthermore, a gene's expression pattern over time might not be identified by simply combining results from repeated marginal analyses. We propose a hidden Markov modeling approach developed to efficiently identify differentially expressed genes in time course microarray experiments and classify genes based on their temporal expression patterns. Simulation studies demonstrate a substantial increase in sensitivity, with little increase in the false discovery rate, compared with a marginal analysis at each time point. This increase is also observed in data from a case study of the effects of aging on stress response in heart tissue, where a significantly larger number of genes are identified using the proposed approach.
Automated Diagnosis of Alzheimer's Disease with Degenerate SVM-Based Adaboost

Alzheimer disease (AD) is known as the most common form of dementia, which imposes a considerable burden on society. In this paper, we focus on the automated diagnosis of Alzheimer disease. Based on the researches on neuropathology, we adopt the thickness of cortex regions from the magnetic resonance imaging (MRI) to characterize the pathology of AD. 3D reconstruction technique is utilized to extract feature vectors from the structured MRI data. To improve the classification quality of our method, we proposed a new classification method which is Based on the combination of SVM and Adaboost. Experiment results show that our method performs well, and can reaches higher classification accuracy than classical classification methods such as k-Nearest Neighbor (KNN), Linear Discriminant Analysis (LDA), Support Vector Machine (SVM), and Gaussian mixture model (GMM).
Static voltage over-scaling and dynamic voltage variation tolerance with replica circuits and time redundancy in reconfigurable devices

This paper studies performance and timing failure probability of time-shifted redundant circuits and replica circuits. Measurement-based experiments using a fabricated test chip are performed. For an approximately similar false positive error probability for time-shifted redundant circuits and replica circuits, the false negative error probability of time-shifted redundant circuits is approximately two orders of magnitude less than that of the replica circuits. When attaining a false negative error of zero, time-shifted redundant circuits achieves one order of magnitude less in false positive error probability than that of the replica circuits.
Permulin: collaboration on interactive surfaces with personal in- and output

Interactive tables are well suited for co-located collaboration. Most prior research assumed users to share the same overall display output; a key challenge was the appropriate partitioning of screen real estate, assembling the right information 'at the users' finger-tips through simultaneous input. A different approach is followed in recent multi-view display environments: they offer personal output for each team member, yet risk to dissolve the team due to the lack of a common visual focus. Our approach combines both lines of thought, guided by the question: "What if the visible output and simultaneous input was partly shared and partly private? " We present Permulin as a concrete corresponding implementation, based on a set of novel interaction concepts that support fluid transitions between individual and group activities, coordination of group activities, and concurrent, distraction-free in-place manipulation. Study results indicate that users are able to focus on individual work on the whole surface without notable mutual interference, while at the same time establishing a strong sense of collaboration.
Market Condition and Mutual Fund Flow-Performance

In this study we analyze mutual fund flow-performance relation by using a novel sample of Chinese mutual funds and focus on the impact of stock market conditions. we find that the flow-performance relation varies significantly with market conditions and the positive relation is more pronounced during bull markets. The asymmetric flow-performance relation under different market conditions is consistent with Thaler and Johnson's (1990) the house money effect and the overconfidence hypothesis proposed by Gervais and Odean (2001).
Interproximal grinding (disking) of caries in primary molars, attitudes and the extent utilized in a Swedish County

Abstract Objective: To assess the occurrence of interproximal grinding as a caries therapy in primary molars, to what degree grinding replaced conventional restorative caries therapy, to what extent anaesthesia was used while grinding and to assess open comments about attitudes about grinding. Materials and methods: A questionnaire was sent to 108 public dental service clinics with questions concerning the use of grinding as a therapy and alternative to restorative treatment, the use of anaesthesia prior to conventional caries therapy and grinding, respectively. In addition, a content analysis of open comments about grinding was performed. Results: Grinding had been performed in 96% of the clinics. Two-thirds of the dentists used grinding as an alternative to conventional restorative treatment at some point. Most dentists used anaesthesia prior to restorative therapy. Prior to grinding, the frequency of anaesthesia was lower (median 5.0) than for conventional restorative therapy (median 8.7) (p < .001). The open comment analysis revealed complex reasons for the use of grinding. Conclusions: Grinding has been widely practiced in parts of Sweden, is presently a technique employed by a multitude of dentists, and that anaesthesia is used less frequently prior to grinding, in comparison to conventional restorative therapy. Dentist considered grinding as a treatment option in specific situations.
Synthesis of Regular Expressions Revisited: From PSL SEREs to Hardware

We revisit the specification of control circuits and protocols written as regular expressions, and propose a synthesizable subset of the sequences that can be written in the property specification language and system Verilog assertions standards. We give a formal semantics of the sequence operators that can directly be interpreted in terms of circuits, and provide a modular method to achieve the automatic generation of compliant hardware from specifications written as temporal sequences. The method also generates assertions to check the completeness and consistency of the specifications. Results obtained on classical benchmarks show the efficiency of our technique. Finally, we discuss the applications of our prototype tool in an assertion-based verification flow.
A congruence result for process calculi with structural axioms

Bialgebraic models of process calculi enjoy the property that bisimilarity is a congruence. Indeed, the unique morphism to the final bialgebra induces a bisimilarity relation which coincides with observational equivalence and which is a congruence with respect to the operations. However, the application of the bialgebraic approach to process calculi with structural axioms is more problematic, because of the interaction between axioms and inference rules. In this paper, we generalise a previous method proposed by the same authors to lift calculi with structural axioms to bialgebras. In order for the lifting to hold, two conditions are required: the transition rules of the calculus are in tyft format and the axioms bisimulate with respect to the lts. As a simple example of applicability of this general approach we consider CCS with replication, thus providing a compositional bialgebraic model of the calculus.
A Hybrid Genetic Algorithm For The Vehicle Routing Problem With Time Windows

This paper suggests a new hybrid genetic algorithm for the 2D Euclidean vehicle routing problem with time windows. The natural crossover, proposed for the 2D Euclidean traveling salesman problem, was adopted with some modification in the suggested genetic algorithm. The most notable feature of the natural crossover is that it uses the 2D image of a solution itself for chromosomal cutting. We also investigate the usefulness of parents' decision variables such as arrival times during recombination. The suggested genetic algorithm found optimal solutions for 26 out of 31 instances with known optimal solutions.
Cash Ethanol Cross-Hedging Opportunities

Increased use of alternative fuels and low commodity prices have contributed to the recent expansion of the U.S. ethanol industry. As with any competitive industry, some level of output price risk exists in the form of volatility; yet, no actively traded ethanol futures market exists to mitigate output price risk. This study reports estimated minimum variance cross-hedge ratios between Detroit spot cash ethanol and the New York Mercantile Exchange unleaded gasoline futures for 1-, 4-, 8-, 12-, 16-, 20-, 24-, and 28-week hedge horizons. The research suggests that a one-to-one cross-hedge ratio is not appropriate for some horizons.
Complement C2 Receptor Inhibitor Trispanning: A Novel Human Complement Inhibitory Receptor12

The complement system presents a powerful defense against infection and is tightly regulated to prevent damage to self by functionally equivalent soluble and membrane regulators. We describe complement C2 receptor inhibitor trispanning (CRIT), a novel human complement regulatory receptor, expressed on hemopoietic cells and a wide range of tissues throughout the body. CRIT is present in human parasites through horizontal transmission. Serum complement component C2 binds to the N-terminal extracellular domain 1 of CRIT, which, in peptide form, blocks C3 convertase formation and complement-mediated inflammation. Unlike C1 inhibitor, which inhibits the cleavage of C4 and C2, CRIT only blocks C2 cleavage but, in so doing, shares with C1 inhibitor the same functional effect, of preventing classical pathway C3 convertase formation. Ab blockage of cellular CRIT reduces inhibition of cytolysis, indicating that CRIT is a novel complement regulator protecting autologous cells.
Moderation without Change: The Strategic Transformation of Sinn Féin and the IRA in Northern Ireland

This article examines how violent separatist groups moderate. Using the case of Sinn Féin and the IRA in Northern Ireland, it shows that moderation is a multidimensional process, entailing a change in strategic behaviour but not necessarily in the goals or values of a separatist group. For Irish republicans, moderation entailed giving up violent revolution and embracing peaceful reformism, but it did not require changing long-term goals, accepting the legitimacy of British rule in Northern Ireland, or distancing themselves from their history of armed struggle. Moderation was possible because both Irish republicans and the British state distinguished between republicans’ strategic behaviour and their political goals, with the British state neither expecting nor demanding a change in the goals of republicanism, and republicans showing a willingness to change tactics to bring them closer to their long-term goal of a united Ireland. This finding has important implications for the moderation of other radical separatist groups.
A System Developer"S Perspective Of Managing CiRM Implementation In Local Governments: Lessons From Malaysia

This paper proposes a system developer? s perspective of the Citizen Relationship Management (CiRM) system implementation framework in the Malaysian local governments. The framework was developed based upon two in-depth cross-case studies which were conducted in two leading local governments in Malaysia. In addition to confirming the familiar determinants found in the literature, the paper also suggests the significance of "publicity" as a factor which should not be overlooked when CiRM implementation initiative is considered.
Patient Survival in Renal Allograft Failure: A Time-dependent Analysis

Background: To improve patient survival after a renal transplant, it is important to detect which variables affect it. Objectives: This study aimed to assess the effect of renal allograft failure on patient survival. Patients and Methods: This retrospective cohort study included 405 renal transplant patients from Kerman University of Medical Sciences hospital, Kerman, Iran from 2004 to 2010. Kaplan-Meier method was used to estimate survival rates of patients, and time-dependent Cox regression was used to examine the effect of allograft failure on patient survival. Results: During 4.06 years (median) of follow-up 28 (6.9%) patients died and 20 (71.4%) of dead patients had allograft failure. Survival rate of patients with allograft failure at 1-, 3-, 5-, and 7-year were 0.98, 0.8, 0.53, and 0.53, respectively; in patients with allograft function these values were 0.99, 0.98, 0.97, and 0.96, respectively. The unadjusted death rate was 0.5 per 100 patient years for the maintained allograft function, which increased to 9 per 100 patient years for patients following allograft failure. In fully adjusted model the risk of death increased in patients with allograft failure (HR = 2.09; 95% CI: 1.56-2.81), pretransplant diabetes (HR = 2.81; 95% CI: 1.2-6.7), patients with BMI ≥ 25 (vs. 18.5 ≤ BMI < 25) (HR = 3.56; 95% CI: 1.09-11.6). With an increase in recipient age this risk increased (HR = 1.04 per year increase; 95% CI: 1.01-6.7). Receiving a living kidney transplant decreased this risk (HR = 0.52; 95% CI: 0.39-0.69). Conclusions: An increase in recipient age and BMI, affliction with diabetes, allograft failure, and receiving deceased kidney transplant increased the risk of death.
CUDIA: Probabilistic Cross-level Imputation using Individual Side Information

Due to privacy or legal issues, aggregate data publication is a common practice in healthcare and medical research. However, to ﬁnd out valuable individual level relationships from the aggregate data, many data mining algorithms suffer from the aggregation bias and the information loss, or require rather strict assumptions, which are usually unveriﬁable. Furthermore, even if individual level data are available, as many healthcare studies are performed with a pre-speciﬁed goal, a limited scope of variables constraints the range of the research focus. How can one run data mining procedures on such data where different variables are available at different levels of aggregation or granularity? In this paper, we seek a better utilization of variably aggregate datasets, which are possibly from different sources. By modeling the generative process of such datasets using a Bayesian directed graphical model, we propose a novel “cross-level” imputation technique. The imputation is based on the underlying data distribution and shown to be unbiased. This imputation can be further utilized in a subsequent predictive modeling, showing improved performances than just imputing the aggregate information as it is. Experimental results using a simulated dataset and the Behavioral Risk Factor Surveillance System (BRFSS) dataset are provided to illustrate the generality and capabilities of the proposed framework.
Topological origins of chromosomal territories

Using freely jointed polymer model we compare equilibrium properties of crowded polymer chains whose segments are either permeable or not permeable for other segments to pass through. In particular, we addressed the question whether non-permeability of long chain molecules, in the absence of excluded volume effect, is sufficient to compartmentalize highly crowded polymer chains, similarly to what happens during formation of chromosomal territories in interphase nuclei. Our results indicate that even polymers without excluded volume compartmentalize and show strongly reduced intermingling when they are mutually non-permeable. Judging from the known fact that chromatin fibres originating from different chromosomes show very limited intermingling in interphase nuclei, we propose that regular chromatin fibres during chromosome decondensation can hardly serve as a substrate of cellular type II DNA topoisomerases.
Rail Inspection Meets Big Data: Methods and Trends

Rail inspection is one of the most important tasks for rail industry, in order to guarantee the safety of railway systems and control their cost. Rail are systematically inspected for defects using various non-destructive evaluation (NDE) techniques, which include ultrasonic inspection, visual detection, magnetic flux leakage method, acoustic emission inspection etc. The data obtained by these NDE devices are going to increase in both quality and quantity, therefore big data has emerged as a potential challenge for rail inspection. This paper reviews the advanced NDE techniques for rail inspection, and brings forward a new framework of rail inspection based on big data, according to the characteristics of inspection data.