Miracle-dz/UniFAR-FTUs huggingface dataset:
Benchmarking OLTP/web databases in the cloud: the OLTP-bench framework

Benchmarking is a key activity in building and tuning data management systems, but the lack of reference workloads and a common platform makes it a time consuming and painful task. The need for such a tool is heightened with the advent of cloud computing--with its pay-per-use cost models, shared multi-tenant infrastructures, and lack of control on system configuration. Benchmarking is the only avenue for users to validate the quality of service they receive and to optimize their deployments for performance and resource utilization. In this talk, we present our experience in building several adhoc benchmarking infrastructures for various research projects targeting several OLTP DBMSs, ranging from traditional relational databases, main-memory distributed systems, and cloud-based scalable architectures. We also discuss our struggle to build meaningful micro-benchmarks and gather workloads representative of real-world applications to stress-test our systems. This experience motivates the OLTP-Bench project, a batteries-included benchmarking infrastructure designed for and tested on several relational DBMSs and cloud-based database-as-a-service (DBaaS) offerings. OLTP-Bench is capable of controlling transaction rate, mixture, and workload skew dynamically during the execution of an experiment, thus allowing the user to simulate a multitude of practical scenarios that are typically hard to test (e.g., time-evolving access skew). Moreover, the infrastructure provides an easy way to monitor performance and resource consumption of the database under test. We also introduce the ten included workloads, derived from either synthetic micro benchmarks, popular benchmarks, and real world applications, and how they can be used to investigate various performance and resource-consumption characteristics of a data management system. We showcase the effectiveness of our benchmarking infrastructure and the usefulness of the workloads we selected by reporting sample results from hundreds of side-byside comparisons on popular DBMSs and DBaaS offerings.
The Plenoptic Function and the Elements of Early Vision

What are the elements of early vision? This question might be taken to mean, What are the fundamental atoms of vision? —and might be variously answered in terms ofsuch candidate structures as edges, peaks, corners, and so on. In this chapter we adopt a rather different point of view and ask the question, What are the fundamentalsubstances of vision? This distinction is important becausewe wish to focus on the first steps in extraction of visualinformation. At this level it is premature to talk aboutdiscrete objects, even such simple ones as edges and corners.There is general agreement that early vision involvesmeasurements of a number of basic image properties in-cluding orientation, color, motion, and so on. Figure l.lshows a caricature (in the style of Neisser, 1976), of the sort of architecture that has become quite popular as a model for both human and machine vision. The first stageof processing involves a set of parallel pathways, eachdevoted to one particular-visual property. We propose that the measurements of these basic properties be con-sidered as the elements of early vision. We think of earlyvision as measuring the amounts of various kinds of vi-sual "substances" present in the image (e.g., redness orrightward motion energy). In other words, we are inter- ested in how early vision measures “stuff” rather than in how it labels “things. ”What, then, are these elementary visual substances? Various lists have been compiled using a mixture of intui-tion and experiment. Electrophysiologists have describedneurons in striate cortex that are selectively sensitive tocertain visual properties; for reviews, see Hubel (1988) and DeValois and DeValois (1988). Psychophysicists haveinferred the existence of channels that are tuned for cer- tain visual properties; for reviews, see Graham (1989), Olzak and Thomas (1986), Pokorny and Smith (1986), and Watson (1986). Researchers in perception have foundaspects of visual stimuli that are processed pre-attentive- ly (Beck, 1966; Bergen & Julesz, 1983; Julesz & Bergen,
It takes variety to make a world: diversification in recommender systems

Recommendations in collaborative tagging sites such as del.icio. us and Yahoo! Movies, are becoming increasingly important, due to the proliferation of general queries on those sites and the ineffectiveness of the traditional search paradigm to address those queries. Regardless of the underlying recommendation strategy, item-based or user-based, one of the key concerns in producing recommendations, is over-specialization, which results in returning items that are too homogeneous. Traditional solutions rely on post-processing returned items to identify those which differ in their attribute values (e.g., genre and actors for movies). Such approaches are not always applicable when intrinsic attributes are not available (e.g., URLs in del.icio.us). In a recent paper [20], we introduced the notion of explanation-based diversity and formalized the diversification problem as a compromise between accuracy and diversity. In this paper, we develop efficient diversification algorithms built upon this notion. The algorithms explore compromises between accuracy and diversity. We demonstrate their efficiency and effectiveness in diversification on two real life data sets: del.icio. us and Yahoo! Movies.
Style przywiązania a cechy zaburzeń osobowości

The literature points that attachment is key mechanism in the development of people. According to the attachment theory, the experience of neglect, abandonment and other early traumas have influence on forming the dysfunctions of emotions and personality pathology. The aim of this article is the verification of the thesis about relation between attachment style and personality disorders. The analysis of results of 155 participants has been conducted (persons in the similar age, similar educational level, similar number of females and males). The diagnosis of personality disorder was based on SCID-II (Structured Clinical Interview for Axis – II), and additionally confirmed by PDQ-4 Hyler Inventory. To examine the attachment style the Plopa’s Attachment Styles Questionnaire and the Revised Experiences in Close Relationships Inventory (ECR-R designed by Fraley et al., 2000), were used. The multiple regression model was used to test whether attachment styles maybe the predictors for personality disorders. The current results partly support the Lyddon and Sherry’ thesis. The main predictor for the relations between attachment and personality disorders is the anxious attachment style.
Optimizing the parameters of decoding graphs using new log-based MCE

This paper proposes a new class loss function as an alternative to the standard sigmoid class loss function for optimizing the parameters of decoding graphs using discriminative training based on minimum classification error (MCE) criterion. The standard sigmoid based approach tends to ignore a significant number of training samples that have a large difference between the scores of the reference and their corresponding competing hypotheses and this affects the parameters optimization. The proposed function overcomes this limitation through considering almost all the training samples and thus improved the parameter optimization when tested on large decoding graphs. The decoding graph used in this research is an integrated network of weighted finite state transducers. The primary task examined is 64K words, continuous speech recognition task. The experimental results show that the proposed method outperformed the baseline system based on both the maximum likelihood estimation (MLE) and sigmoid-based MCE and achieved a reduction in the word error rate (WER) of 28.9% when tested on the TIMIT speech database.
The relative contribution of the CD28 and gp39 costimulatory pathways in the clonal expansion and pathogenic acquisition of self-reactive T cells

The zona pellucida (ZP), an ovarian extracellular structure, contains three major glycoproteins: ZP1, ZP2, and ZP3. A ZP3 peptide contains both an autoimmune oophoritis-inducing T cell epitope and a B cell epitope that induces autoantibody to ZP. This study investigates two major T cell costimulation pathways in this disease model. Herein we show that blockage of glycoprotein (gp)39 and CD40 interaction with gp39 monoclonal antibody (mAb) results in the failure to induce both autoimmune oophoritis and autoantibody production. Inhibition of ligand binding to the CD28 receptor with the fusion protein, murine CTLA4- immunoglobulin (Ig), also results in failure to generate antibody to ZP and significantly reduces disease severity and prevalence. Surprisingly, the frequencies of antigen-specific T cells in anti-gp39 mAb-treated mice, CTLA4-Ig treated mice, and in mice given control hamster IgG or control fusion protein L6, were equivalent as determined by limiting dilution analysis (approximately equals 1:5,000). These T cells, which produced comparable amounts of interleukin 4 and interferon gamma in vitro, were able to transfer oophoritis to normal recipients. When anti-gp39 mAb and CTLA4-Ig were given together, the effect was additive, leading to inhibition of T cell activation as determined by in vitro proliferation and limiting dilution analysis (approximately equals 1:190,000); disease and antibody responses were absent in these mice. By studying these two costimulatory pathways in parallel, we have shown that autoimmune disease and autoantibody production are inhibitable by blocking either the gp39 or the CD28 pathway, whereas inhibition of clonal expansion of the effector T cell population occurs only when both pathways are blocked.
Adapting to Learner Errors with Minimal Supervision

This article considers the problem of correcting errors made by English as a Second Language writers from a machine learning perspective, and addresses an important issue of developing an appropriate training paradigm for the task, one that accounts for error patterns of non-native writers using minimal supervision. Existing training approaches present a trade-off between large amounts of cheap data offered by the native-trained models and additional knowledge of learner error patterns provided by the more expensive method of training on annotated learner data. We propose a novel training approach that draws on the strengths offered by the two standard training paradigms—of training either on native or on annotated learner data—and that outperforms both of these standard methods. Using the key observation that parameters relating to error regularities exhibited by non-native writers are relatively simple, we develop models that can incorporate knowledge about error regularities based on a small annotated sample but that are otherwise trained on native English data. The key contribution of this article is the introduction and analysis of two methods for adapting the learned models to error patterns of non-native writers; one method that applies to generative classifiers and a second that applies to discriminative classifiers. Both methods demonstrated state-of-the-art performance in several text correction competitions. In particular, the Illinois system that implements these methods ranked at the top in two recent CoNLL shared tasks on error correction.1 We conduct further evaluation of the proposed approaches studying the effect of using error data from speakers of the same native language, languages that are closely related linguistically, and unrelated languages.
MAC Protocol for Opportunistic Cognitive Radio Networks with Soft Guarantees

Cognitive radio (CR) is the key enabling technology for an efficient dynamic spectrum access. It aims at exploiting an underutilized licensed spectrum by enabling opportunistic communications for unlicensed users. In this work, we first develop a distributed cognitive radio MAC (COMAC) protocol that enables unlicensed users to dynamically utilize the spectrum while limiting the interference on primary (PR) users. The main novelty in COMAC lies in not assuming a predefined CR-to-PR power mask and not requiring active coordination with PR users. COMAC provides a statistical performance guarantee for PR users by limiting the fraction of the time during which the PR users' reception is negatively affected by CR transmissions. To provide such a guarantee, we develop probabilistic models for the PR-to-PR and the PR-to-CR interference under a Rayleigh fading channel model. From these models, we derive closed-form expressions for the mean and variance of interference. Empirical results show that the distribution of the interference is approximately lognormal. Based on the developed interference models, we derive a closed-form expression for the maximum allowable power for a CR transmission. We extend the min-hop routing to exploit the available channel information for improving the perceived throughput. Our simulation results indicate that COMAC satisfies its target soft guarantees under different traffic loads and arbitrary user deployment scenarios. Results also show that exploiting the available channel information for the routing decisions can improve the end-to-end throughput of the CR network (CRN).
A low‐cost real‐time face tracking system for ITSs and SDASs

It is important to track people's face efficiently and accurately in many Intelligent Transportation Systems (ITSs) and Safety Driving Assistant Systems (SDASs). This paper presents a high‐performance and low‐cost real‐time face tracking system, which runs on general onboard computer with very low CPU consumption. The proposed face tracking system is composed of four modules: the motion detector, face detector, face tracker, and face validator. The motion detector extracts motion areas by using a spatial‐temporal bi‐differential method with a very low computational cost. The face detector integrates motions into a cascade face detection framework to reject most of non‐face scanning‐windows to ensure efficient face localization. The face tracker fuses motion feature with color feature to alleviate the drifting problem during tracking. The face validator builds face appearance models online and identifies each specific tracked face to avoid confusion. Experimental results on three challenging video sequences show that the proposed face tracking system outperforms the state‐of‐the‐art face tracker and consumes only 5–13% CPU resources of a low‐spec onboard computer while processing in real time. Copyright © 2016 John Wiley & Sons, Ltd.
Vulnerability of Pathogenic Biofilms to Micavibrio aeruginosavorus

ABSTRACT The host specificity of the gram-negative exoparasitic predatory bacterium Micavibrio aeruginosavorus was examined. M. aeruginosavorus preyed on Pseudomonas aeruginosa, as previously reported, as well as Burkholderia cepacia, Klebsiella pneumoniae, and numerous clinical isolates of these species. In a static assay, a reduction in biofilm biomass was observed as early as 3 hours after exposure to M. aeruginosavorus, and an ∼100-fold reduction in biofilm cell viability was detected following a 24-h exposure to the predator. We observed that an initial titer of Micavibrio as low as 10 PFU/well or a time of exposure to the predator as short as 30 min was sufficient to reduce a P. aeruginosa biofilm. The ability of Micavibrio to reduce an existing biofilm was confirmed by scanning electron microscopy. In static and flow cell experiments, M. aeruginosavorus was able to modify the overall P. aeruginosa biofilm structure and markedly decreased the viability of P. aeruginosa. The altered biofilm structure was likely caused by an increase in cell-cell interactions brought about by the presence of the predator or active predation. We also conducted a screen to identify genes important for P. aeruginosa-Micavibrio interaction, but no candidates were isolated among the ∼10,000 mutants tested.
Schools and Schooling in the Digital Age: A Critical Analysis

Part I: High-tech Hope and Digital Disappointment 1. Revisiting the Promise of Digital Technology and Schools 2. The Messy Realities of Digital Technology Use in Schools 3. Rethinking Digital Technology and Schools Part II: Making Sense of Schools, Schooling and Digital Technology 4. Digital Technology and Education Policymaking 5. Digital Technology and the Privitisations of Schooling 6. Digital Technology and the Organisational Concerns of Schools 7. Digital Technology and the Lived Experiences of Teachers and Students Part III: What to do with Schools in the Digital Age 8. Reconstructing Schools and Schooling in the Digital Age 9. Readjusting Schools and Schooling in the Digital Age
NAD(P)H:quinone oxidoreductase 1 Pro187Ser polymorphism and expression do not cosegregate with clinico-pathological characteristcs of human mammary tumors

Objective The aim of this study was to further clarify the recently reported role of NAD(P)H:quinone oxidoreductase 1 (NQO1) as a strong prognostic and predictive factor in breast cancer. Methods NQO1 transcript levels were monitored in mammary tumors by real-time polymerase chain reaction. NQO1 protein levels were immunohistochemically determined in formalin-fixed paraffin-embedded tissues. NQO1 polymorphism (Pro187Ser, rs1800566) was also assessed. Evaluation (N=52) and validation (N=53) sets were analyzed subsequently. Results Carriers of variant NQO1-Ser allele had significantly more frequently NQO1-negative protein expression (P=0.001) in both sets. NQO1 transcript levels in samples with negative protein expression were significantly lower than in those with positive NQO1 protein expression (P=0.007) in both sets. Patients with stages 0/I/II had more often positive NQO1 protein expression than patients with stages III/IV (P=0.022) in the evaluation set. Significant association between NQO1 protein expression and TP53 protein status was also found (P=0.037). However, both associations were not replicated by analysis of the validation set. Analysis of both sets combined did not show significant association of NQO1 protein expression either with stage (P=0.231) or with TP53 protein status (P>0.999). Thus, the results observed in the evaluation set were effects of small sample size. Conclusion The role of NQO1 in human mammary gland carcinogenesis does not seem to be directly associated with classical clinico-pathological factors.
Calculating rfPred scores with package rfPred

Exome sequencing is becoming a standard tool for gene mapping of monogenic diseases. Given the vast amount of data generated by Next Generation Sequencing techniques, identification of disease causal variants is like finding a needle in a haystack. The impact assessment and the prioritization of potential pathogenic variants are expected to reduce work in biological validation, which is long and costly.
A Comparison of Post-Match Recovery Strategies in Youth Soccer Players

Kinugasa, T and Kilding, AE. A comparison of post-match recovery strategies in youth soccer players. J Strength Cond Res 23(5): 1402-1407, 2009-The aim of this study was to determine the effect of 3 post-match recovery modalities on physical performance, physiological measures, and players' perceptions of recovery after 90-minute soccer match play. On separate days, 28 young (age: 14.3 ± 0.7 years) soccer players played 3 soccer matches each randomly followed by 1 of 3 recovery modalities: (a) CONT-cold (12° C) water immersion and hot (38° C) shower, (b) COMB-cold water immersion and active recovery using a cycle ergometer, and (c) PASS-a passive post-match routine (stretching and leg raise). Performance (vertical jump height), physiological (heart rate and tympanic temperature), and perceptual measures (perceived quality of recovery) were determined before each match, 10 minutes after each match, after each recovery method, and after 24 hours. There was a 0.6 ± 6.7% drop in immediately after a match, but there was no difference in vertical jump height after 24 hours (p = 0.997). Perceived quality of recovery immediately after COMB was substantially higher than CONT and PASS, but the effect did not last more than 24 hours. The players perceived lighter legs after COMB, compared with the PASS, at post-24 hours. In conclusion, a combined recovery modality (cold water immersion and active recovery) after a soccer match did not have a substantial effect on vertical jump height performance when compared with contrast water immersion and passive recovery alone. However, the observed positive effects on perceived recovery (higher quality of recovery and lighter legs) after the combined modality (cold water immersion and active recovery) suggest that this approach may be effective for young players after intense soccer match play.
Comparative Investigation of Diagnosis Media of Stator Voltage Asymmetry and Rotor Broken Bars in Induction Machines

The results of a comparative experimental investigation of various media for non-invasive diagnosis of internal and external unbalanced parameters (rotor faults and unbalanced voltages) in a three-phase squirrel-cage induction machine are presented. Stator voltages, stator currents and stray flux are measured, recorded and used for computation of the current space vector, the input power and the airgap torque. The different waveforms of the stator current, current space vector, stray flux, airgap torque, partial input power and total input power are subsequently analysed using the classical fast Fourier transform (FFT)
Fault Prediction in Object-Oriented Software Using Neural Network Techniques

To remain competitive in the dynamic world of software development, organizations must optimize the usage of their limited resources to deliver quality products on time and within budget. This requires prevention of fault introduction and quick discovery and repair of residual faults. In this paper a new approach for predicting and classification of faults in object-oriented software systems is introduced. In particular, faults due to the use of inheritance and polymorphism are considered as they account for significant portion of faults in object-oriented systems. The proposed fault prediction model is based on supervised learning using Multilayer Perceptron Neural Network. The results of fault prediction are analyzed in terms of classification correctness and some other standard criteria. Based on the results of classification, faulty classes are further analyzed and classified according to the particular type of fault. The classification model is based on clustering using Radial-Basis Function Neural Network. It is concluded, that the proposed model provides high accuracy in discrimination between faulty and fault-free classes.
Identification of perceptual attributes constituting the user’s experience of mechanical switches

The Rep ertory Grid Techn ique was applied to identif y th e perceptual a ttributes cons tituting the users experience of mechanical switches for seven sensory conditions. Participants (105) were subjected to six bimodal and unimodal senso ry combinations c reated b y s electively res tricting the f low of haptic, auditory and visual information, plus one condition with full sensory information. Verbal C lassification analysis and pr incipal components analy sis (PCA) on the ob tained rating data suggest th at the pr imary d imension is associated with the magnitude of the haptic feedback and the second is associated wi th the qu ality of the f eedback, d etermined by combinations of auditory