Miracle-dz/UniFAR-FTUs huggingface dataset:
Greedy Awakens : Efficient and Provable Multi-Query Optimization

Complex queries for massive data analysis jobs have become increasingly commonplace. Many such queries contain common sub-expressions, either within a single query or among multiple queries submitted as a batch. Conventional query optimizers do not exploit these common sub-expressions and produce sub-optimal plans. The problem of multi-query optimization (MQO) is to generate an optimal \textit{combined} evaluation plan by computing common sub-expressions once and reusing them. Exhaustive algorithms for MQO explore an $\mathcal{O}(n^n)$ search space. Thus, this problem has primarily been tackled using various heuristic algorithms, without providing any theoretical guarantees on the quality of the solution obtained. In this paper, instead of the conventional cost minimization problem, we treat the problem as maximizing a linear transformation of the cost function. We propose a greedy algorithm for this transformed formulation of the problem, which under weak, intuitive assumptions, gives an approximation factor with respect to the optimal solution of this formulation. We go on to show that this factor is optimal, unless $\mathsf{P} = \mathsf{NP}$. Another noteworthy point about our algorithm is that it can be easily incorporated into existing transformation-based optimizers. We finally propose optimizations which can be used to improve the efficiency of our algorithm.
A simple technique for structured light calibration in welding robots

Structured light calibration is one of the most crucial parts in a visual sensing system of welding robots. And the main aspect of the structured light calibration is the accuracy. Besides, a practical and simplistic calibration approach is preferable. In this paper, we propose a simple technique for structured light calibration. The vertical and horizontal lines are added to the planar object to facilitate points detection. The information from the camera calibration is fully used to detect the points on the light stripe. Then parameters of the structured light plane are estimated based on three non-collinear points definition. It could be said that the computation in this study is straight forward. Furthermore, it does not require any additional equipment. Thus, it is a truly simple and practical calibration method. According to the experimental results, the calibration errors are less than 0.2 mm. It shows that our proposed method is acceptable to measurement system of welding robots.
Impact of Tandem repeats on the Scaling of nucleotide Sequences

Techniques such as detrended fluctuation analysis (DFA) and its extensions have been widely used to determine the nature of scaling in nucleotide sequences. In this brief communication we show that tandem repeats which are ubiquitous in nucleotide sequences can prevent reliable estimation of possible long-range correlations. Therefore, it is important to investigate the presence of tandem repeats prior to scaling exponent estimation.
If At First You Don't Succeed... What Makes You Try Again?

Optimists have better outcomes than pessimists across a variety of situations (Andersson, 1996; Scheier and Carver, 1992). The underlying assumption for these differences is that because optimists have positive expectancies for future events, they persist longer. Greater persistence, in turn, leads to the more frequent experience of desired outcomes. In the present study, we hypothesized that situational factors will also play a role in persistence. Specifically, when individuals believe that it is important to perform well on a given task, they will persist longer than if they believe the task is unimportant. To investigate the role of these variables, both optimists and pessimists were given an unsolvable task for which we manipulated the perceived importance of the task. We predicted a main effect for optimism, such that optimists would persist longer than pessimists. In addition, we predicted a main effect for level of task importance, such that persistence would be longer for those in the high importance of task condition. Lastly, we examined the possibility of an interaction between the two variables. Results and implications will be discussed.
9 Term Weighting for Information Retrieval Using Fuzzy Logic

The rising quantity of available information has constituted an enormous advance in our daily life. However, at the same time, some problems emerge as a result from the existing difficulty to distinguish the necessary information among the high quantity of unnecessary data. Information Retrieval has become a capital task for retrieving the useful information. Firstly, it was mainly used for document retrieval, but lately, its use has been generalized for the retrieval of any kind of information, such as the information contained in a database, a web page, or any set of accumulated knowledge. In particular, the so-called Vector Space Model is widely used. Vector Space Model is based on the use of
Hacking the DBMS to Prevent Injection Attacks

After more than a decade of research, web application security continues to be a challenge and the backend database the most appetizing target. The paper proposes preventing injection attacks against the database management system (DBMS) behind web applications by embedding protections in the DBMS itself. The motivation is twofold. First, the approach of embedding protections in operating systems and applications running on top of them has been effective to protect this software. Second, there is a semantic mismatch between how SQL queries are believed to be executed by the DBMS and how they are actually executed, leading to subtle vulnerabilities in prevention mechanisms. The approach -- SEPTIC -- was implemented in MySQL and evaluated experimentally with web applications written in PHP and Java/Spring. In the evaluation SEPTIC has shown neither false negatives nor false positives, on the contrary of alternative approaches, causing also a low performance overhead in the order of 2.2%.
Prickle 1 regulates cell movements during gastrulation and neuronal migration in zebrafish

During vertebrate gastrulation, mesodermal and ectodermal cells undergo convergent extension, a process characterised by prominent cellular rearrangements in which polarised cells intercalate along the medio-lateral axis leading to elongation of the antero-posterior axis. Recently, it has become evident that a noncanonical Wnt/Frizzled (Fz)/Dishevelled (Dsh) signalling pathway, which is related to the planar-cell-polarity (PCP) pathway in flies, regulates convergent extension during vertebrate gastrulation. Here we isolate and functionally characterise a zebrafish homologue of Drosophila prickle (pk), a gene that is implicated in the regulation of PCP. Zebrafish pk1 is expressed maternally and in moving mesodermal precursors. Abrogation of Pk1 function by morpholino oligonucleotides leads to defective convergent extension movements, enhances the silberblick (slb)/wnt11 and pipetail (Ppt)/wnt5 phenotypes and suppresses the ability of Wnt11 to rescue the slb phenotype. Gain-of-function of Pk1 also inhibits convergent extension movements and enhances the slb phenotype, most likely caused by the ability of Pk1 to block the Fz7-dependent membrane localisation of Dsh by downregulating levels of Dsh protein. Furthermore, we show that pk1 interacts genetically with trilobite (tri)/strabismus to mediate the caudally directed migration of cranial motor neurons and convergent extension. These results indicate that, during zebrafish gastrulation Pk1 acts, in part, through interaction with the noncanonical Wnt11/Wnt5 pathway to regulate convergent extension cell movements, but is unlikely to simply be a linear component of this pathway. In addition, Pk1 interacts with Tri to mediate posterior migration of branchiomotor neurons, probably independent of the noncanonical Wnt pathway.
The Prehistory of Potyviruses: Their Initial Radiation Was during the Dawn of Agriculture

Background Potyviruses are found world wide, are spread by probing aphids and cause considerable crop damage. Potyvirus is one of the two largest plant virus genera and contains about 15% of all named plant virus species. When and why did the potyviruses become so numerous? Here we answer the first question and discuss the other. Methods and Findings We have inferred the phylogenies of the partial coat protein gene sequences of about 50 potyviruses, and studied in detail the phylogenies of some using various methods and evolutionary models. Their phylogenies have been calibrated using historical isolation and outbreak events: the plum pox virus epidemic which swept through Europe in the 20th century, incursions of potyviruses into Australia after agriculture was established by European colonists, the likely transport of cowpea aphid-borne mosaic virus in cowpea seed from Africa to the Americas with the 16th century slave trade and the similar transport of papaya ringspot virus from India to the Americas. Conclusions/Significance Our studies indicate that the partial coat protein genes of potyviruses have an evolutionary rate of about 1.15×10−4 nucleotide substitutions/site/year, and the initial radiation of the potyviruses occurred only about 6,600 years ago, and hence coincided with the dawn of agriculture. We discuss the ways in which agriculture may have triggered the prehistoric emergence of potyviruses and fostered their speciation.
Enhancement of dynein-mediated autophagosome trafficking and autophagy maturation by ROS in mouse coronary arterial myocytes

Dynein‐mediated autophagosome (AP) trafficking was recently demonstrated to contribute to the formation of autophagolysosomes (APLs) and autophagic flux process in coronary arterial myocytes (CAMs). However, it remains unknown how the function of dynein as a motor protein for AP trafficking is regulated under physiological and pathological conditions. The present study tested whether the dynein‐mediated autophagy maturation is regulated by a redox signalling associated with lysosomal Ca2+ release machinery. In primary cultures of CAMs, reactive oxygen species (ROS) including H2O2 and O2−. (generated by xanthine/xanthine oxidase) significantly increased dynein ATPase activity and AP movement, which were accompanied by increased lysosomal fusion with AP and APL formation. Inhibition of dynein activity by (erythro‐9‐(2‐hydroxy‐3‐nonyl)adenine) (EHNA) or disruption of the dynein complex by dynamitin (DCTN2) overexpression blocked ROS‐induced dynein activation, AP movement and APL formation, and resulted in an accumulation of AP along with a failed breakdown of AP. Antagonism of nicotinic acid adenine dinucleotide phosphate (NAADP)‐mediated Ca2+ signalling with NED‐19 and PPADS abolished ROS‐enhanced lysosomal Ca2+ release and dynein activation in CAMs. In parallel, all these changes were also enhanced by overexpression of NADPH oxidase‐1 (Nox1) gene in CAMs. Incubation with high glucose led to a marked O2−. production compared with normoglycaemic CAMs, while Nox1 inhibitor ML117 abrogated this effect. Moreover, ML117 and NED‐19 and PPADS significantly suppressed dynein activity and APL formation caused by high glucose. Taken together, these data suggest that ROS function as important players to regulate dynein‐dependent AP trafficking leading to efficient autophagic maturation in CAMs.
Textual Similarity: Comparing texts in order to discover how closely they discuss the same topics

This thesis describes the design and implementation of a tool for measuring textual similarity. The thesis looks into different aspects of text processing and graph searching in an attempt to define similarity. Furthermore, a solution for measuring textual similarity is proposed and implemented. Challenges such as disambiguation of word senses, part-of-speech tagging and several graph searching algorithms are described and used in the measurements. The developed tool is tested using human evaluation of textual similarity and it is concluded that the tool to some degree is able to measure textual similarity with the same results as a human being.
The prevalence of occupational burnout among librarians in three African countries

This cross-sectional study was conducted among librarians from Ghana, Nigeria, and South Africa to establish the prevalence of occupational burnout in the library set up. A previously validated self-administered questionnaire [Maslach Burnout Inventory (MBI)] was used to collect information on the prevalence and pattern of job burnout among the respondents. The occurrence of extreme burnout among the respondents, especially those working in the Electronic and Reference Services area of their libraries was found. The findings of this research calls for both professional and personal avenues to deal with or lessen this menace as it is a difficult issue that affects the wellbeing of library staff, which can thwart libraries from accomplishing their points.
Color quantization using c-means clustering algorithms

Color quantization is an important operation with many applications in graphics and image processing. Most quantization methods are essentially based on data clustering algorithms. Recent studies have demonstrated the effectiveness of hard c-means (k-means) clustering algorithm in this domain. Other studies reported similar findings pertaining to the fuzzy c-means algorithm. Interestingly, none of these studies directly compared the two types of c-means algorithms. In this study, we implement fast and exact variants of the hard and fuzzy c-means algorithms with several initialization schemes and then compare the resulting quantizers on a diverse set of images. The results demonstrate that fuzzy c-means is significantly slower than hard c-means, and that with respect to output quality the former algorithm is neither objectively nor subjectively superior to the latter.
MAC Protocol for Energy Efficiency and Service Differentiation with High Goodput in Wireless Sensor Networks

SUMMARY In the sensor networks for surveillance, the requirements of providing energy efficiency and service differentiation, which is to deliver high-priority packets preferentially, while maintaining high goodput, which is to deliver many packets within their deadline are increasing. However, previous works have difficulties in satisfying the requirements simultaneously. Thus, we propose GES-MAC, which satisfies the requirements simultaneously. GES-MAC reduces idle listening energy consumption by using a duty cycle, periodic listen (i.e., turn on radio module) and sleep (i.e. turn off radio module) of sensor nodes. Cluster-based multi-hop scheduling provides high goodput in a duty-cycled environment by scheduling clusters of nodes in the listen period and opportunistically forwarding data packets in the sleep period. Priority-aware schedule switching makes more highpriority packets reach the sink node by letting high-priority packets preempt the schedules of low-priority packets. In experiments with MICA2 based sensor nodes and in simulations, the energy consumption of the radio module is reduced by 70% compared to the approaches without a duty cycle, while providing 80% ∼ 100% goodput of the approaches that provide high goodput. Service differentiation is also supported with little overhead.
Chemical Genomic Study of Endocrine Disrupting Chemicals in Metabolic Pathways

Endocrine disrupting activities in industrial chemicals have been a serious problem, because they are distributed broadly, they are active at very low concentrations, and some of them are difficult to detoxify. Moreover, only a small number of active chemicals are known, while most chemicals have not been examined yet. To reduce the number of examinations required for unknown chemicals, some computational prediction methods have been proposed. In this study, we propose a chemical genomic approach to understand the relationship between activities and chemical structures. Our approach revealed the existence of synthetic and degradation chains in metabolic pathway maps. At the end of the degradation chains, we found certain oxidization enzymes that appeared frequently. We also confirmed our prediction by performing a bioassay experiment. The results would help us to find potential detoxifying microorganisms. In addition, our method can be applied to other types of toxic chemicals, such as cancer-causing agents.
RNA-seq Transcriptional Profiling of Peripheral Blood Leukocytes from Cattle Infected with Mycobacterium bovis

Bovine tuberculosis, caused by infection with Mycobacterium bovis, is a major endemic disease affecting cattle populations worldwide, despite the implementation of stringent surveillance and control programs in many countries. The development of high-throughput functional genomics technologies, including gene expression microarrays and RNA-sequencing (RNA-seq), has enabled detailed analysis of the host transcriptome to M. bovis infection, particularly at the macrophage and peripheral blood level. In the present study, we have analyzed the peripheral blood leukocyte (PBL) transcriptome of eight natural M. bovis-infected and eight age- and sex-matched non-infected control Holstein-Friesian animals using RNA-seq. In addition, we compared gene expression profiles generated using RNA-seq with those previously generated using the high-density Affymetrix® GeneChip® Bovine Genome Array platform from the same PBL-extracted RNA. A total of 3,250 differentially expressed (DE) annotated genes were detected in the M. bovis-infected samples relative to the controls (adjusted P-value ≤0.05), with the number of genes displaying decreased relative expression (1,671) exceeding those with increased relative expression (1,579). Ingenuity® Systems Pathway Analysis (IPA) of all DE genes revealed enrichment for genes with immune function. Notably, transcriptional suppression was observed among several of the top-ranking canonical pathways including Leukocyte Extravasation Signaling. Comparative platform analysis demonstrated that RNA-seq detected a larger number of annotated DE genes (3,250) relative to the microarray (1,398), of which 917 genes were common to both technologies and displayed the same direction of expression. Finally, we show that RNA-seq had an increased dynamic range compared to the microarray for estimating differential gene expression.
Comparing Statistical and Machine Learning Classifiers: Alternatives for Predictive Modeling in Human Factors Research

Multivariate classification models play an increasingly important role in human factors research. In the past, these models have been based primarily on discriminant analysis and logistic regression. Models developed from machine learning research offer the human factors professional a viable alternative to these traditional statistical classification methods. To illustrate this point, two machine learning approaches - genetic programming and decision tree induction - were used to construct classification models designed to predict whether or not a student truck driver would pass his or her commercial driver license (CDL) examination. The models were developed and validated using the curriculum scores and CDL exam performances of 37 student truck drivers who had completed a 320-hr driver training course. Results indicated that the machine learning classification models were superior to discriminant analysis and logistic regression in terms of predictive accuracy. Actual or potential applications of this research include the creation of models that more accurately predict human performance outcomes.
Configuring M-Commerce Portals for Business Success

M-commerce entails transactions conducted via mobile telecommunications networks using communication, information, and payment devices such as mobile phones or palmtop units. Geographic positioning and location capabilities are also being added to such networks and devices. Rather than using general-purpose browsers, customers accessing mobile commerce applications often rely on specific mobile portals, or mportals. These m-portals could be specific to the device that the user has, to the communications infrastructure provider, to the financial infrastructure provider, or to other service aggregators who act as gateways to a variety of mobile services. As the experience of the iMode platform of NTT DoCoMo has already shown, the ability to connect end customers and service providers through an m-portal is a key element for the success of m-commerce. To be commercially viable, such m-portals must attract and retain customers. Success in mobile portal markets will depend on dynamic strategies that blend elements of personalization, permission, and specification of content. This chapter reviews the key differences between traditional e-commerce and the emergent m-commerce. It reviews the core concepts of personalization, permission, and content specification as they apply to e-commerce and m-commerce. The chapter presents a framework for developing effective business strategies for developing and managing mobile portals.
Classifying User Search Intents for Query Auto-Completion

The function of query auto-completion in modern search engines is to help users formulate queries fast and precisely. Conventional context-aware methods primarily rank candidate queries according to term- and query- relationships to the context. However, most sessions are extremely short. How to capture search intents with such relationships becomes difficult when the context generally contains only few queries. In this paper, we investigate the feasibility of discovering search intents within short context for query auto-completion. The class distribution of the search session (i.e., issued queries and click behavior) is derived as search intents. Several distribution-based features are proposed to estimate the proximity between candidates and search intents. Finally, we apply learning-to-rank to predict the user's intended query according to these features. Moreover, we also design an ensemble model to combine the benefits of our proposed features and term-based conventional approaches. Extensive experiments have been conducted on the publicly available AOL search engine log. The experimental results demonstrate that our approach significantly outperforms six competitive baselines. The performance of keystrokes is also evaluated in experiments. Furthermore, an in-depth analysis is made to justify the usability of search intent classification for query auto-completion.
Post‐earthquake crisis communications in Taiwan: An examination of corporate advertising and strategy motives

This study examines gestures, themes, message copy points and imagery, and strategy motives reflected in corporate advertising appearing in the China Times and United Daily News, two leading newspapers, in the month following the devastating Chin‐Chin earthquake in Taiwan in September 1999. The study identified four possible corporate strategy motives in post‐crisis corporate communications: social responsibility, communal relationship building, enlightened self‐interest and impression management. A content analysis of adverts (n=100) suggested communal relationship building drove corporate advertising endeavours. Corporate philanthropy was the most common gesture described in the adverts, and the most frequent themes and message components focused on the restoration of society. No significant differences were found between companies headquartered in Taiwan versus elsewhere, or between companies headquartered in Asia versus the West. Implications for examining crisis communications and underlying motives behind public relations communications are discussed.
Implementability, Walrasian Equilibria and Efficient Matchings

In general screening problems, implementable allocation rules correspond exactly to Walrasian equilibria of an economy in which types are consumers with quasilinear utility and unit demand. Due to the welfare theorems, an allocation rule is implementable if and only if it induces an efficient matching between types and goods.