Miracle-dz/UniFAR-FTUs huggingface dataset:
Efficient Error-tolerant Query Autocompletion

Query autocompletion is an important feature saving users many keystrokes from typing the entire query. In this paper we study the problem of query autocompletion that tolerates errors in users' input using edit distance constraints. Previous approaches index data strings in a trie, and continuously maintain all the prefixes of data strings whose edit distance from the query are within the threshold. The major inherent problem is that the number of such prefixes is huge for the first few characters of the query and is exponential in the alphabet size. This results in slow query response even if the entire query approximately matches only few prefixes. In this paper, we propose a novel neighborhood generation-based algorithm, IncNGTrie, which can achieve up to two orders of magnitude speedup over existing methods for the error-tolerant query autocompletion problem. Our proposed algorithm only maintains a small set of active nodes, thus saving both space and time to process the query. We also study efficient duplicate removal which is a core problem in fetching query answers. In addition, we propose optimization techniques to reduce our index size, as well as discussions on several extensions to our method. The efficiency of our method is demonstrated against existing methods through extensive experiments on real datasets.
Learning with Violable Constraints

0. Abstract This chapter reviews major results as well as areas of ongoing research on computational models of learning with violable constraints, in the sense of Optimality Theory. The review encompasses learning in classic OT as well as learning in related frameworks that formalize constraint interaction as (probabilistic) weighting or ranking. The learning problem is decomposed into several subproblems, which are considered in turn. The discussion emphasizes the challenges posed by these various subproblems and the insights and differences of the proposed solutions. The chapter first discusses the narrow grammar-learning subproblem, the problem of learning rankings or weightings given data along with their full structural descriptions. Next, the discussion turns to several distinct approaches to the broader grammar-learning subproblem, which makes the more realistic assumption that hidden structure, such as prosodic structure or underlying representations, are not available to the learner and must themselves be learned. The chapter then discusses the subset problem and various approaches that have been proposed for learning restrictive constraint grammars. Finally, the chapter briefly reviews work on acquisition modeling, work that connects the predictions of computational models and the process by which children acquire language. 1. Introduction Learnability is a central problem of linguistics. A complete theory of language must explain how this rich and complex system of knowledge can be learned from the limited available input. Work on learnability seeks to answer this question by developing explicit formal models of the learning process, models that provide concrete hypotheses about how language can be learned. Work on learnability within Optimality Theory (OT; Prince and Smolensky 1993 / 2004) 1 and related frameworks has contributed a great deal to our understanding of language learning. These results contribute not only to our understanding of how language might be learned in principle, but also to our understanding of how language is actually acquired by children. This chapter reviews these important contributions, focusing primarily on major learnability results and challenges, but also reviewing work that relates the predictions of computational models to developmental findings. This chapter discusses the various facets of the learning problem, the challenges they pose for the learner, and the constraint-based approaches that have been developed to address them. Under the standard view in OT, the set of universal constraints defines, via permutation, the space of possible adult languages (the typology). This formal system defines the hypothesis space for learning – the set of languages that …
The Promises of Hybrid Hexagonal/Classical Tiling for GPU

Time-tiling is necessary for efficient execution of iterative stencil computations. But the usual hyper-rectangular tiles cannot be used because of positive/negative dependence distances along the stencil's spatial dimensions. Several prior efforts have addressed this issue. However, known techniques trade enhanced data reuse for other causes of inefficiency, such as unbalanced parallelism, redundant computations, or increased control flow overhead incompatible with efficient GPU execution. We explore a new path to maximize the effectivness of time-tiling on iterative stencil computations. Our approach is particularly well suited for GPUs. It does not require any redundant computations, it favors coalesced global-memory access and data reuse in shared-memory/cache, avoids thread divergence, and extracts a high degree of parallelism. We introduce hybrid hexagonal tiling, combining hexagonal tile shapes along the time (sequential) dimension and one spatial dimension, with classical tiling for other spatial dimensions. An hexagonal tile shape simultaneously enable parallel tile execution and reuse along the time dimension. Experimental results demonstrate significant performance improvements over existing stencil compilers.
SC79 protects retinal pigment epithelium cells from UV radiation via activating Akt-Nrf2 signaling

Excessive Ultra-violet (UV) radiation causes oxidative damages and apoptosis in retinal pigment epithelium (RPE) cells. Here we tested the potential activity of SC79, a novel small molecule activator of Akt, against the process. We showed that SC79 activated Akt in primary and established (ARPE-19 line) RPE cells. It protected RPE cells from UV damages possibly via inhibiting cell apoptosis. Akt inhibition, via an Akt specific inhibitor (MK-2206) or Akt1 shRNA silence, almost abolished SC79-induced RPE cytoprotection. Further studies showed that SC79 activated Akt-dependent NF-E2-related factor 2 (Nrf2) signaling and inhibited UV-induced oxidative stress in RPE cells. Reversely, Nrf2 shRNA knockdown or S40T mutation attenuated SC79-induced anti-UV activity. For the in vivo studies, we showed that intravitreal injection of SC79 significantly protected mouse retina from light damages. Based on these results, we suggest that SC79 protects RPE cells from UV damages possibly via activating Akt-Nrf2 signaling axis.
SPA Resistant Algorithms for Elliptic Curve Cryptography over GF(2m)

Scalar multiplication is the kernel and most timeconsuming operation in elliptic curve cryptosystems. In this paper, efficient and secure scalar multiplication algorithms are proposed over binary field, where the scalar multiplication can be designed and implemented rapidly without arithmetic coprocessor. By using innovative side channel atomicity in point operation formulae, these proposed algorithms can be protected against simple power analysis, and thereby achieve higher security without loss of overall performance. Keywordselliptic curve cryptography; scalar multiplication; simple power analysis; side channel atomicity
Next generation annotation interfaces for adaptive information extraction

The evolution of the Internet into the largest existent digital library is bringing about new challenges. One of the biggest problems is the location of information. The most promising approach seems to be performing searches semantically however this cannot work without semantically annotated documents. These documents are few and the manual annotation process to make them is both time consuming and error prone. To solve this problem Information Extraction (IE) technologies can be used to automatically annotate these documents, but before doing so, IE tools require training examples. These examples are normally created manually by human annotators. Currently, there exist very few tools designed to support such people. This paper proposes a methodology aimed at supporting annotators by reducing the number of annotations required by an IE system therefore having effective learning. The whole methodology is implemented in the Melita system which will also be described in this paper. Finally enhancements to the existing methodology are being proposed in order to make IE accessible to a wider range of users, from inexperienced to expert users.
Improving E-Banking Security with Biometrics: Modelling User Attitudes and Acceptance

Despite the widespread success of online banking, there remains a reluctance to use it primarily because of uncertainty and security concerns. This study evaluates the potential of biometric authentication for online banking (bbanking) as a way of improving adoption and use of online banking. To this end, we extend Davis's core TAM model adding self-efficacy and user perceptions of biometric security. Using structural equation modelling techniques, this study revealed that user perceptions of biometrics security positively influenced their attitude and intention to use biometric banking. It also found that self efficacy in biometric use, positively influenced user's perception of the security of biometrics.
State of Inheritance Rights: Women in a Rural District in Pakistan

ABSTRACT Inheritance is an extremely significant factor in wealth distribution and gender relations. This article provides an area-specific insight on inheritance distribution with respect to women. A total of 144 daughters were interviewed in a feudal society in Pakistan to assess their inheritance. A descriptive analysis was employed to investigate the inheritance shares they received in provision of agricultural land and its annual income for the women that inherited it. The data demonstrated that lack of education, patriarchal practices, and the occurrences of a swap marriage system (where forced exchange marriages are promoted to defer inheritance) limit the ability of these women to get their share of their entitled inheritance. To change this system at a grassroots level, the results indicate the need for a clear understanding of the religious lessons, laws, and social repercussions that lead to these daughters being deprived of their inheritance. Overall, future research supports culturally sensitive strategies that can counterbalance these adverse practices for discrimination in inheritance.
The optimal event-based control of parachute opening problem I: Theory

We propose an event-based controller associated with an optimized strategy of parachute air drop. In a rescue mission or combat, it is important to minimize the drop interval to ensure a fast and accurate landing while a safe landing speed must be guaranteed. Opening the parachute timely is viewed as an optimal event-based control problem. The idea of optimal event-based control design is to identify the key event of the hybrid dynamics where a supervisor triggers the event-based controller at a right time. Perfect timing is given by a particular nonlinear optimization problem. To this end, we propose a method that takes a couple of steps to simplify the optimization via the tools of integration, penalty function and steepest descent algorithm. The method can be used to a range of applications: such as diaster rescue, combat, and space device recycling.
Detection-based ASR in the automatic speech attribute transcription project

We present methods of detector design in the Automatic Speech Attribute Transcription project. This paper details the results of a student-led, cross-site collaboration between Georgia Institute of Technology, The Ohio State University and Rutgers University. The work reported in this paper describes and evaluates the detection-based ASR paradigm and discusses phonetic attribute classes, methods of detecting framewise phonetic attributes and methods of combining attribute detectors for ASR. We use Multi-Layer Perceptrons, Hidden Markov Models and Support Vector Machines to compute confidence scores for several prescribed sets of phonetic attribute classes. We use Conditional Random Fields (CRFs) and knowledge-based rescoring of phone lattices to combine framewise detection scores for continuous phone recognition on the TIMIT database. With CRFs, we achieve a phone accuracy of 70.63%, outperforming the baseline and enhanced HMM systems, by incorporating all of the attribute detectors discussed in the paper. Index Terms: Detection-based ASR
MODELING THE DATA STREAM OF A VEHICLES NETWORK AND ITS COMPRESSING BY THE TSVD

Despite of the evolution of Data Stream Management Systems (DSMS), storage and processing of data flow persists as a major problem, especially if it comes from a network of mobile, including a set of vehicles. One solution proposed for such problems is to summarize the data stream into portions called short summaries. Several selection techniques segmentation of these streams has been proposed based on deterministic or probabilistic algorithms. Our contribution records the proposal of a new method of data modeling. These data emitted by all vehicles using a section of road. The set of data is represented in the model by a matrix which will be compressed by the Truncated Singular Values Decomposition method (TSVD).
An adaptive algorithm for dynamic tuning of MAC parameters in IEEE 802.15.4/ZigBee sensor networks

Recent studies have highlighted that IEEE 802.15. 4 based wireless sensor networks (WSNs) suffer from a severe unreliability problem due to the default MAC parameters setting suggested by the standard, although with a more appropriate choice it is possible to achieve the desired reliability and better energy efficiency. However, such setting is strictly related to the operating conditions which, in general, vary over time and thus cannot be predicted in advance (i.e., before the deployment). In this paper, we propose an ADaptive Access Parameters Tuning (ADAPT) algorithm for dynamically adjusting the MAC parameters, based on the desired level of reliability and actual operating conditions experienced by the sensor nodes. Simulation experiments demonstrate that the ADAPT algorithm is able to provide the desired reliability with a very low energy expenditure, even under operating conditions that dynamically change with time.
INMAP Overexpression Inhibits Cell Proliferation, Induces Genomic Instability and Functions through p53/p21 Pathways

INMAP is a spindle protein that plays essential role for mitosis, by ensuring spindle and centromere integrality. The aim of this study was to investigate the relevant functions of INMAP for genomic stability and its functional pathway. We overexpressed INMAP in HeLa cells, resulting in growth inhibition in monolayer cell cultures, anchorage-independent growth in soft agar and xenograft growth in nude mice. In this system caused micronuclei (MNi) formation, chromosome distortion and γH2AX expression upregulation, suggesting DNA damage induction and genomic stability impairment. As a tumour biochemical marker, lactate dehydrogenase (LDH) isoenzymes were detected to evaluate cell metabolic activity, the results confirming that total activity of LDH, as well as that of its LDH5 isoform, is significantly decreased in INMAP-overexpressing HeLa cells. The levels of p53 and p21 were upregulated, and however, that of PCNA and Bcl-2, downregulated. Indirect immunofluorescence (IIF) and coimmunoprecipitation (CoIP) analyses revealed the interaction between INMAP and p21. These results suggest that INMAP might function through p53/p21 pathways.
Preterm Birth and Body Composition at Term Equivalent Age: A Systematic Review and Meta-analysis

BACKGROUND AND OBJECTIVE: Infants born preterm are significantly lighter and shorter on reaching term equivalent age (TEA) than are those born at term, but the relation with body composition is less clear. We conducted a systematic review to assess the body composition at TEA of infants born preterm. METHODS: The databases MEDLINE, Embase, CINAHL, HMIC, “Web of Science,” and “CSA Conference Papers Index” were searched between 1947 and June 2011, with selective citation and reference searching. Included studies had to have directly compared measures of body composition at TEA in preterm infants and infants born full-term. Data on body composition, anthropometry, and birth details were extracted from each article. RESULTS: Eight studies (733 infants) fulfilled the inclusion criteria. Mean gestational age and weight at birth were 30.0 weeks and 1.18 kg in the preterm group and 39.6 weeks and 3.41 kg in the term group, respectively. Meta-analysis showed that the preterm infants had a greater percentage total body fat at TEA than those born full-term (mean difference, 3%; P = .03), less fat mass (mean difference, 50 g; P = .03), and much less fat-free mass (mean difference, 460 g; P < .0001). CONCLUSIONS: The body composition at TEA of infants born preterm is different than that of infants born at term. Preterm infants have less lean tissue but more similar fat mass. There is a need to determine whether improved nutritional management can enhance lean tissue acquisition, which indicates a need for measures of body composition in addition to routine anthropometry.
Swarm aggregation with a multi-robot system composed of three robotic units: A closed form analysis

In this work we consider a multi-robot system composed of three robotic units running the seminal swarm aggregation control law proposed in [1] for which a pairwise interaction is considered among each couple of units. In particular, we provide a characterization of all the possible equilibria for such a system while varying the parameters of interaction and investigate their stability properties. Simulations along with experimental results are given to corroborate the theoretical analysis.
The Wormhole Routing Attack in Wireless Sensor Networks (WSN)

Abstract —Secure routing is vital to the acceptance and use of Wireless Sensor Networks (WSN) for many applications. However, providing secure routing in WSNs is a challenging task due to the inherently constrained capabilities of sensor nodes. Although a wide variety of routing protocols have been proposed for WSNs, most do not take security into account as a main goal. Routing attacks can have devastating effects on WSNs and present a major challenge when designing robust security mechanisms for WSNs. In this paper, we examine some of the most common routing attacks in WSNs. In particular, we focus on the wormhole routing attack in some detail. A variety of countermeasures have been proposed in the literature for such attacks. However, most of these countermeasures suffer from flaws that essentially render them ineffective for use in large scale WSN deployments. Due to the inherent constraints found in WSNs, there is a need for lightweight and robust security mechanisms. The examination of the wormhole routing attack and some of the proposed countermeasures makes it evident that it is extremely difficult to retrofit existing protocols with defenses against routing attacks. It is suggested that one of the ways to approach this rich field of research problems in WSNs could be to carefully design new routing protocols in which attacks such as wormholes can be rendered meaningless.
An exploratory approach to time perspective theory and research

The Time Perspective theoretical model proposed by Zimbardo & Boyd (1999) has been very prolifi c in the quantity and quality of research produced in the last decade. However, taking into account the defi nition of time perspective of Kurt Lewin (1951), we believe that a negative future dimension is an important component of the individual’s time perspective. The objective of this study is to verify a 7-dimension model of Time Perspective formed by the 5 original dimensions of the Zimbardo Time Perspective Inventory – ZTPI (Zimbardo & Boyd, 1999), the TranscendentalFuture from Transcendental-Future Time Perspective Scale – TFTPS (Boyd & Zimbardo, 1997) and the Negative Future Scale from Inventário de Perspectiva Temporal – IPT (Janeiro, 2012) in a sample of 563 Portuguese college students. Through Exploratory Factor Analysis we found evidence that supports this model. The majority of items load above . 30 in their respective factors, the internal consistency of the 7 dimensions ranges from . 722 to . 865 and the total variance explained is 46.18%.
The meaning of life for unemployed people

The social worker dictionary defines the meaning of life as a regulative term that modifies and explains social norms by which a person should guide themselves. A person’s value system, along with their confrontation with social norms, helps to define the secret of an individual’s existence, also known as the meaning of life (Strieženec 1996). Understanding the meaning of life means understanding ourselves. When we consider the meaning of life it does not have to mean only one thing; therefore we can discuss the socalled plurality of meanings. We assign different meanings to each of our spheres of life. We can deliberate the pathology of the purpose of our existence, as such meanings can strengthen each other (when we reach one meaning we can proceed to reach another one) or contradict each other (Šulavíková, Sejčová 2008). Philosophy regards questions on meaning of life as the basic ones. The everlasting questions that are part of a person ́s life are: Who am I? , Where does my life lead to? , What is my purpose? , and What is the value of my life? (Balogová 2009).
The Feasibility of an Exercise Intervention in Males at Risk of Oesophageal Adenocarcinoma: A Randomized Controlled Trial

Objective To investigate the feasibility and safety of a 24-week exercise intervention, compared to control, in males with Barrett’s oesophagus, and to estimate the effect of the intervention, compared to control, on risk factors associated with oesophageal adenocarcinoma development. Methods A randomized controlled trial of an exercise intervention (60 minutes moderate-intensity aerobic and resistance exercise five days/week over 24 weeks; one supervised and four unsupervised sessions) versus attention control (45 minutes stretching five days/week over 24 weeks; one supervised and four unsupervised sessions) in inactive, overweight/obese (25.0–34.9 kg/m2) males with Barrett’s oesophagus, aged 18–70 years. Primary outcomes were obesity-associated hormones relevant to oesophageal adenocarcinoma risk (circulating concentrations of leptin, adiponectin, interleukin-6, tumour necrosis factor-alpha, C-reactive protein, and insulin resistance [HOMA]). Secondary outcomes included waist circumference, body composition, fitness, strength and gastro-oesophageal reflux symptoms. Outcomes were measured at baseline and 24-weeks. Intervention effects were analysed using generalised linear models, adjusting for baseline value. Results Recruitment was difficult in this population with a total of 33 participants recruited (target sample size: n = 80); 97% retention at 24-weeks. Adherence to the exercise protocol was moderate. No serious adverse events were reported. A statistically significant intervention effect (exercise minus control) was observed for waist circumference (-4.5 [95% CI -7.5, -1.4] cm; p < 0.01). Effects on primary outcomes were not statistically significant. Conclusion This small, exploratory trial provides important information to inform future trial development including recruitment rates and estimates of effect sizes on outcomes related to oesophageal adenocarcinoma risk. Future trials should investigate a combined dietary and exercise intervention to achieve greater weight loss in this population and relax inclusion criteria to maximize recruitment. Trial Registration Australian New Zealand Clinical Trials Registry (ANZCTR) ACTRN12609000401257