Miracle-dz/UniFAR-FTUs huggingface dataset:
Development of Semantic Based Information Retrieval Using Word-Net Approach

semantic-based information retrieval mechanism that handles the processing, recognition, extraction, extensions and matching of content semantics to achieve the following objectives: i) to analyze and determine the semantic feature of the content and to develop a semantic pattern that represent the semantic features of the content. ii) to analyze user’s query and extend its implied semantics through semantic extension to identify more semantic features for matching. iii) to generate contents with approximate semantics by clustering the documents and matching against the extended query to provide correct contents to the querist.
Bayesian prior models for vehicle make and model recognition

Automatic vehicle type recognition (make and model) is very useful in secure access and traffic monitoring applications. It compliments the number plate recognition systems by providing a higher level of security against fraudulent use of number plates in traffic crimes. In this paper we present a simple but powerful probabilistic framework for vehicle type recognition that requires just a single representative car image in the database to recognize any incoming test image exhibiting strong appearance variations, as expected in outdoor image capture e.g. illumination, scale etc. We propose to use a new feature description, local energy based shape histogram 'LESH', in this problem that encodes the underlying shape and is invariant to illumination and other appearance variations such as scale, perspective distortions and color. Our method achieves high accuracy (above 94%) as compared to the state of the art previous approaches on a standard benchmark car dataset. It provides a posterior over possible vehicle type matches which is especially attractive and very useful in practical traffic monitoring and/or surveillance video search (for a specific vehicle type) applications.
Cardiac function in renovascular hypertensive patients with and without renal dysfunction.

BACKGROUND Hypertension impairs left ventricular (LV) diastolic and systolic function, which might be aggravated by inflammation or neurohumoral activation. We hypothesized that LV diastolic dysfunction is more common in patients with renovascular hypertension (RVHT) compared with essential hypertension (EHT). METHODS Hypertensive patients who underwent both renal imaging to exclude RVHT and cardiac echocardiography within a 3-year period were identified retrospectively. Patients with significant renovascular disease were included in the RVHT group (n = 75); those without significant renovascular disease were included in the EHT group (n = 69). Cardiac function and structure were compared. RESULTS Baseline renal function was preserved (serum creatinine ≤ 2mg/dl) in EHT patients and impaired (serum creatinine > 2mg/dl) in only 9 RVHT patients. RVHT patients had higher systolic blood pressure, E/e' ratio, and greater prevalence of concentric hypertrophy but lower estimated glomerular-filtration-rate (eGFR) compared with EHT patients. Increased prevalence of LV diastolic dysfunction remained statistically significant in patients with RVHT after multivariable adjustment for age, sex, blood pressure, eGFR, diabetes, smoking, and statin use, with a relative risk (95% CI) for abnormal E/e' of 1.70 (95% confidence interval = 1.05-2.90; P = 0.03) compared with EHT. RVHT patients with severe renal dysfunction showed greater impairments in cardiac systolic and diastolic function compared with those in EHT patients or preserved renal function RVHT patients. CONCLUSIONS Among hypertensive patients undergoing echocardiography, cardiac structure and diastolic function are impaired in RVHT patients compared with EHT patients and remain different after adjustment for multiple significant covariables. When associated with significant renal dysfunction, RVHT aggravates LV hypertrophy and both systolic and diastolic dysfunction. Hence, identification of RVHT and renal dysfunction warrants development of targeted management strategies.
Ein Gebrauchsbasierter Ansatz zur Analyse von Code-Mixing

Code-mixing, regarded as a characteristic feature of fluent bilingual speech, has been investigated from various perspectives. This article argues for a usage-based approach to code-mixing as a unified theoretical framework, which is capable of integrating the multitude of existing explanations for this phenomenon and of yielding new insights into its structure. Under a usage-based view, linguistic knowledge emerges in language use, which is grounded in social interaction and is affected by cognitive processing. The aspects of human cognition explored in the present article as factors influencing the structure of code-mixing include the perception of similarity between the contact languages’ elements and structures, the frequency of linguistic units in language use and their recency in discourse. I demonstrate that the perception of similarity between the contact languages’ elements and structures opens up possibilities for code-mixing, whereas the frequency and recency of linguistic units influence the probability of their use in code-mixing.
Retrieving, Adapting and Delivering Multimedia Content Using a Mobile Agent Architecture

An integrated, reconfigurable, adaptable and open system for mining, indexing and retrieving multimedia information based on a mobile agent technology scheme is presented. The system consists of three integral subsystems, namely the acquisition, the transformation and the distribution modules. Innovative algorithms are used to extract information from Web sources, transform it and deliver it to the end users. The system supports efficient content adaptation mechanisms, textual and visual summarization schemes (both sequential and hierarchical), automatic language translation, ontological representation, visual processing and Web-based data mining. Experimental analysis on real-life Web sites has been performed to test the efficiency of the proposed scheme and compare it with other approaches presented in the literature
TFIIS Enhances Transcriptional Elongation through an Artificial Arrest Site In Vivo

ABSTRACT Transcriptional elongation by RNA polymerase II has been well studied in vitro, but understanding of this process in vivo has been limited by the lack of a direct and specific assay. Here, we designed a specific assay for transcriptional elongation in vivo that involves an artificial arrest (ARTAR) site designed from a thermodynamic theory of DNA-dependent transcriptional arrest in vitro. Transcriptional analysis and chromatin immunoprecipitation experiments indicate that the ARTAR site can arrest Pol II in vivo at a position far from the promoter. TFIIS can counteract this arrest, thereby demonstrating that it possesses transcriptional antiarrest activity in vivo. Unexpectedly, the ARTAR site does not function under conditions of high transcriptional activation unless cells are exposed to conditions (6-azauracil or reduced temperature) that are presumed to affect elongation in vivo. Conversely, TFIIS affects gene expression under conditions of high, but not low, transcriptional activation. Our results provide physical evidence for the discontinuity of transcription elongation in vivo, and they suggest that the functional importance of transcriptional arrest sites and TFIIS is strongly influenced by the level of transcriptional activation.
A new approach for surface intersection

Evaluating the intersection of two rational parametric surfaces is a recurring operation in solid modeling. However, surface intersection is not an easy problem and continues to be an active topic of research. The main reason lies in the fact that any good surface intersection technique has to balance three conflicting goals of accuracy, robustness and efficiency. In this paper, we formulate the problems of curve and surface intersections using algebraic sets in a higher dimensional space. Using results from Elimination theory, we project the algebraic set to a lower dimensional space. The projected set can be expressed as a matrix determinant. The matrix itself, rather than its symbolic determinant, is used as the representation for the algebraic set in the lower dimensional space. This is a much more compact and efficient representation. Given such a representation, we perform matrix operations for evaluation and use results from linear algebra for geometric operations on the intersection curve. Most of the operations involve evaluating numeric determinants and computing the rank, kernel and eigenvalues of matrices. The accuracy of such operations can be improved by pivoting or other numerical techniques. We use this representation for inversion operation, computing the intersection of curves and surfaces and tracing the intersection curve of two surfaces in lower dimension.
Seroadaptive Practices: Association with HIV Acquisition among HIV-Negative Men Who Have Sex with Men

Background Although efficacy is unknown, many men who have sex with men (MSM) attempt to reduce HIV risk by adapting condom use, partner selection, or sexual position to the partner’s HIV serostatus. We assessed the association of seroadaptive practices with HIV acquisition. Methodology/Principal Findings We pooled data on North American MSM from four longitudinal HIV-prevention studies. Sexual behaviors reported during each six-month interval were assigned sequentially to one of six mutually exclusive risk categories: (1) no unprotected anal intercourse (UAI), (2) having a single negative partner, (3) being an exclusive top (only insertive anal sex), (4) serosorting (multiple partners, all HIV negative), (5) seropositioning (only insertive anal sex with potentially discordant partners), and (6) UAI with no seroadaptive practices. HIV antibody testing was conducted at the end of each interval. We used Cox models to evaluate the independent association of each category with HIV acquisition, controlling for number of partners, age, race, drug use, and intervention assignment. 12,277 participants contributed to 60,162 six-month intervals with 663 HIV seroconversions. No UAI was reported in 47.4% of intervals, UAI with some seroadaptive practices in 31.8%, and UAI with no seroadaptive practices in 20.4%. All seroadaptive practices were associated with a lower risk, compared to UAI with no seroadaptive practices. However, compared to no UAI, serosorting carried twice the risk (HR = 2.03, 95%CI:1.51–2.73), whereas seropositioning was similar in risk (HR = 0.85, 95%CI:0.50–1.44), and UAI with a single negative partner and as an exclusive top were both associated with a lower risk (HR = 0.56, 95%CI:0.32–0.96 and HR = 0.55, 95%CI:0.36–0.84, respectively). Conclusions/Significance Seroadaptive practices appear protective when compared with UAI with no seroadaptive practices, but serosorting appears to be twice as risky as no UAI. Condom use and limiting number of partners should be advocated as first-line prevention strategies, but seroadaptive practices may be considered harm-reduction for men at greatest risk.
Chaotic time series prediction based on fuzzy possibility c-mean and composite kernel support vector regression

A clustering based composite kernels support vector machine ensemble forecasting model is proposed for the chaotic time series prediction. First, fuzzy possibility c-mean clustering algorithm (FPCM) is adopted to partition the input dataset into several subsets, which can overcome the drawback caused by outlier and noise in conventional fuzzy c-mean method. Then, SVMs with composite kernels that best fit partitioned subsets are constructed respectively, which hyperparameters are adaptively evolved by immune clone selection algorithm (ICGA). Finally, a fuzzy synthesis algorithm is employed to combine the outputs of submodels to obtain the final output, in which the degrees of memberships are generated by the relationship between a new input sample data and each subset center. Simulation results on a chaotic benchmark time series indicate that the presented algorithm shows good prediction performance compared to the other existing algorithms for the time series prediction task considered in this paper.
PCFS: Power Credit Based Fair Scheduler Under DVFS for Muliticore Virtualization Platform

In the area of system architecture, there are two most significant trends: multi-core and system virtualization technology. Both of them have quite close relationship with energy efficient computing. Industry turns to integrate more cores on a single chip instead of increasing frequency to solve the heat problem. Meanwhile system virtualization could decrease the total power consumption by sharing the same platform among different operating systems. So the necessity of power management on the multi-core virtualization platform has become increasingly evident. However, traditional virtual machine monitor schedulers could not make efficient use of DVFS, and thus could not take it into considering that the guest OSes may run at different frequency. In order to address this problem, this paper designs a power efficient scheduler which uses the load and the power level of the guest OSes as feedback, and implements a prototype based on Xen virtual machine monitor. This scheduler allocates power credit to VCPU of each guest OS, accounts the power consumption of VCPU sat different speed levels and makes scheduler decision by integrating it to the credit oriented to CPU time slice sharing. It also uses utilization of processors as feedback and sets frequency according to the load change trends instead of the simple static relationship between load and frequency policies, so as to decrease the speed steps required by response to burst load change. Experiment results show that the scheduling fairness of guest OS improved when using DVFS as main power saving method, and the power consumption of the whole system can be reduced by 5 percent - 30 percent. Therefore, this framework for feedback scheduling could make efficient use of varieties of power saving methods and maintain ideal balance between overall system power saving and single core over heat.
Methods for Analyzing Psychotherapy Outcomes: A Review of Clinical Significance, Reliable Change, and Recommendations for Future Directions

The purpose of this article is to provide a brief review of the history, development, and current status of the concepts of clinical significance (CS) and the reliable change index (RCI). I address issues regarding the development, criticisms, and applications of CS and RCI. I review the use of normative data, cutoff points, formula adjustments, and the comparative validity of various RCI methods. An examination of the convergence of multiple domains and multiple measures demonstrates ways to further develop the concepts of reliable change and CS. Finally, I make some recommendations and implications for future research and the development of assessment tools.
ADG: Annotated Dependency Graphs for Software Understanding

Dependency graphs such as call and data usage graphs are often used to study software systems and perform impact analysis during maintenance activities. These graphs show the present structure of the software system ( e.g. In a compiler, an Optimizer function calling a Parser function). They fail to reveal details about the structure of the system that are needed to gain a better understanding. For example, traditional call graphs cannot give the rationale behind an Optimizer function calling Parser function. In this position paper, we advocate a new view on dependency graphs – Annotated Dependency Graphs (ADG). ADG can assist maintainers understand better the current structure of large software systems. We show an example of using an ADG to study Postgres , a large DBMS open source software system.
Data Partition and Job Scheduling Technique for Balancing Load in Cluster of Web Spiders

Search engines primary rely on web spiders to collect large amount of data for indexing and analysis. Data collection can be performed by several agents of web spiders running in parallel or distributed manner over a cluster of workstations. This parallelization is often necessary in order to cope with a large number of pages in a reasonable amount of time. However, while keeping a good parallelism, too many requests should not send from nodes to the same web server in a short period of time. In the environment of a cluster of web spiders, it requires an effective synchronization and scheduling technique between nodes in the cluster. In this paper, we propose a method of URL partition among the node of cluster running web spider and a scheduling technique to dispatch URLs to spider’s thread using a simple but efficient URLs scramble. Our approach guarantees that only one node in the cluster can contact a web server in a time, i.e., avoid overloading remote web servers. Key-Words: Search Engine, Spider, Crawler, Scheduling, Cluster
Bullying among young adolescents: the strong, the weak, and the troubled.

OBJECTIVES Bullying and being bullied have been recognized as health problems for children because of their association with adjustment problems, including poor mental health and more extreme violent behavior. It is therefore important to understand how bullying and being bullied affect the well-being and adaptive functioning of youth. We sought to use multiple data sources to better understand the psychological and social problems exhibited by bullies, victims, and bully-victims. DESIGN, SETTING, AND PARTICIPANTS Analysis of data from a community sample of 1985 mostly Latino and black 6th graders from 11 schools in predominantly low socioeconomic status urban communities (with a 79% response rate). MAIN OUTCOME MEASURES Peer reports of who bullies and who is victimized, self-reports of psychological distress, and peer and teacher reports of a range of adjustment problems. RESULTS Twenty-two percent of the sample was classified as involved in bullying as perpetrators (7%), victims (9%), or both (6%). Compared with other students, these groups displayed school problems and difficulties getting along with classmates. Despite increased conduct problems, bullies were psychologically strongest and enjoyed high social standing among their classmates. In contrast, victims were emotionally distressed and socially marginalized among their classmates. Bully-victims were the most troubled group, displaying the highest level of conduct, school, and peer relationship problems. CONCLUSIONS To be able to intervene with bullying, it is important to recognize the unique problems of bullies, victims, and bully-victims. In addition to addressing these issues directly with their patients, pediatricians can recommend school-wide antibullying approaches that aim to change peer dynamics that support and maintain bullying.
Probing the performance limits of the Escherichia coli metabolic network subject to gene additions or deletions.

An optimization-based procedure for studying the response of metabolic networks after gene knockouts or additions is introduced and applied to a linear flux balance analysis (FBA) Escherichia coli model. Both the gene addition problem of optimally selecting which foreign genes to recombine into E. coli, as well as the gene deletion problem of removing a given number of existing ones, are formulated as mixed-integer optimization problems using binary 0-1 variables. The developed modeling and optimization framework is tested by investigating the effect of gene deletions on biomass production and addressing the maximum theoretical production of the 20 amino acids for aerobic growth on glucose and acetate substrates. In the gene deletion study, the smallest gene set necessary to achieve maximum biomass production in E. coli is determined for aerobic growth on glucose. The subsequent gene knockout analysis indicates that biomass production decreases monotonically, rendering the metabolic network incapable of growth after only 18 gene deletions. In the gene addition study, the E. coli flux balance model is augmented with 3,400 non-E. coli reactions from the KEGG database to form a multispecies model. This model is referred to as the Universal model. This study reveals that the maximum theoretical production of six amino acids could be improved by the addition of only one or two genes to the native amino acid production pathway of E. coli, even though the model could choose from 3,400 foreign reaction candidates. Specifically, manipulation of the arginine production pathway showed the most promise with 8.75% and 9.05% predicted increases with the addition of genes for growth on glucose and acetate, respectively. The mechanism of all suggested enhancements is either by: 1) improving the energy efficiency and/or 2) increasing the carbon conversion efficiency of the production route.
Reading the bed morphology of a mountain stream: a geomorphometric study on high-resolution topographic data

Abstract. High-resolution topographic data expand the potential of quantitative analysis of the earth surface, improving the interpretation of geomorphic processes. In particular, the morphologies of the channel beds of mountain streams, which are characterised by strong spatial variability, can be analysed much more effectively with this type of data. In this study, we analysed the aerial LiDAR topographic data of a headwater stream, the Rio Cordon (watershed area: 5 km 2 ), located in the Dolomites (north-eastern Italy). The morphology of the channel bed of Rio Cordon is characterised by alternating step pools, cascades, and rapids with steps. We analysed the streambed morphology by means of ad hoc developed morphometric indices, capable of highlighting morphological features at a high level of spatial resolution. To perform the analysis and the data interpolation, we carried out a channel-oriented coordinate transformation. In the new coordinate system, the calculation of morphometric indices in directions along and transverse to the flow direction is straightforward. Three geomorphometric indices were developed and applied as follows: a slope index computed on the whole width of the channel bed, directional variograms computed along the flow direction and perpendicular to it, and local anomalies, calculated as the difference between directional variograms at different spatial scales. Directional variograms in the flow direction and local anomalies have proven to be effective at recognising morphologic units, such as steps, pools and clusters of large boulders. At the spatial scale of channel reaches, these indices have demonstrated a satisfactory capability to outline patterns associated with boulder cascades and rapids with steps, whereas they did not clearly differentiate between morphologies with less marked morphological differences, such as step pools and cascades.
On the Probability of Finding Local Minima in Optimization Problems

The standard method in optimization problems consists in a random search of the global minimum: a neuron network relaxes in the nearest local minimum from some randomly chosen initial configuration. This procedure is to be repeated many times in order to find as deep energy minimum as possible. However the question about the reasonable number of such random starts and if the result of the search can be treated as successful remains always open. In this paper by analyzing the generalized Hopfield model we obtain expressions, which yield the relationship between the depth of a local minimum and the size of the basin of attraction. Based on this, we present the probability of finding a local minimum as a function of the depth of the minimum. Such a relation can be used in optimization applications: it allows one, basing on a series of already found minima, to estimate the probability of finding a deeper minimum, and decide in favor of or against further running the program. The theory is in a good agreement with experimental results.