Miracle-dz/UniFAR-FTUs huggingface dataset:
DESIGN, DEVELOPMENT AND DEPLOYMENT OF AN INTELLIGENT, PERSONALIZED RECOMMENDATION SYSTEM

Personalization and recommendation systems are a solution to the problem of content overload, especially in large information systems. In this thesis, a personalized recommendation system enhanced with semantic knowledge has been developed in order to overcome the most common limitations of traditional approaches: the cold-start and the sparsity problems. The recommender consists of the following two main components. A user-profile learning algorithm combines user’s feedback from different channels and employs domain inferences to construct accurate user profiles. A recommendation algorithm, using content-based filtering, exploits the semantic structure of the domain to obtain accurate predictions and generate the corresponding recommendations. The system’s design proposed is flexible enough to be potentially applied to applications of any domain that can be properly described using ontologies. In addition to the development of the recommendation system, an existing Web-application in the tourism domain has been extended and adapted in order to be able to integrate the recommender into it. The overall recommendation system has been evaluated and the results obtained indicate that it satisfies the requirements established.
Extending the Analogy : Enhancing Genetic Algorithms with Further Biological Constructs

Traditional genetic algorithm implementations are discussed and compared with modified implementations which include additional biological components. Experiments with diploidy, dominance and codon GAs are evaluated. In addition, several emerging ideas in GAs and evolutionary computation are briefly discussed. Conclusions indicate that making genetic algorithms more biologically plausible can increase their effectiveness as well as provide insight into some of the mechanisms by which natural evolution occurs.
Murine Models of B-Cell Lymphomas: Promising Tools for Designing Cancer Therapies

Human B-cell lymphomas, the fourth most common hematologic malignancy, are currently the subject of extensive research. The limited accessibility of biopsies, the heterogeneity among patients, and the subtypes of lymphomas have necessitated the development of animal models to decipher immune escape mechanisms and design new therapies. Here, we summarize the cell lines and murine models used to study lymphomagenesis, the lymphoma microenvironment, and the efficacy of new therapies. These data allow us to understand the role of the immune system in the fight against tumors. Exploring the advantages and limitations of immunocompetent versus immunodeficient models improves our understanding of the molecular and cellular mechanisms of tumor genesis and development as well as the fundamental processes governing the interaction of tumors and their host tissues. We posit that these basic preclinical investigations will open up new and promising approaches to designing better therapies.
Term frequency and term value

It has long been recognized that the collection frequency of an index term, that is the number of documents to which it is assigned, is potentially of value in retrieval. In particular, some use has been made of term weighting functions which use (either alone or in combination with other information) term frequency data. There is much experimental evidence that such weighting schemes improve performance. At the conference organized by this group jointly with its British counterpart, in Britain last year, Salton presented a paper (Salton and Wu, forthcoming) in which he surveyed a number of different models of the relationship between term weight and term value. He gathered together an impressive array of models to suggest that this relationship is a peaked one: that is, the best index terms are those in a middling range of frequencies; terms with frequencies outside this range are likely to be of lesser value. Sparck Jones, in the U.K., has long been using a term-frequency based weighting function which assumes that the most valuable terms are those of least frequency. Salton presented this function as simply a reasonable approximation to the peaked curve over the most important part of the range. There is, however, some evidence for the Sparck Jones monotonic function. The object of this paper is to review this evidence and at the same time to compare the two models. I had hoped, when I set out on this paper, to come to some firm answers. As it turns out, as we shall see, I came up only with a curious puzzle. Permission to copy without fee all or part of this material is granted provided that the copies are not made or distributed for direct commercial advantage, the ACM copyright notice and the title of the publication and its date appear, and notice is given that copying is by permission of the Association for Computing Machinery. To copy otherwise, or to republish, requires a fee and/or specific permission. Sparck Jones' (1972) monotonic function was initially suggested by the Zipfian charcter of the distribution of term frequencies. In particular, the distribution suggests a logarithmic function for the weighting formula. Such a function was tried by Sparck Jones and found to give improvements in retrieval performance over simple(unweighted) retrieval. The Zipf argument was not intended as a theoretical justification for the function; the only justification suggested was retrieval performance. Salton (1975) proposed …
Attention Distributed across Sensory Modalities Enhances Perceptual Performance

This study investigated the interaction between top-down attentional control and multisensory processing in humans. Using semantically congruent and incongruent audiovisual stimulus streams, we found target detection to be consistently improved in the setting of distributed audiovisual attention versus focused visual attention. This performance benefit was manifested as faster reaction times for congruent audiovisual stimuli and as accuracy improvements for incongruent stimuli, resulting in a resolution of stimulus interference. Electrophysiological recordings revealed that these behavioral enhancements were associated with reduced neural processing of both auditory and visual components of the audiovisual stimuli under distributed versus focused visual attention. These neural changes were observed at early processing latencies, within 100–300 ms poststimulus onset, and localized to auditory, visual, and polysensory temporal cortices. These results highlight a novel neural mechanism for top-down driven performance benefits via enhanced efficacy of sensory neural processing during distributed audiovisual attention relative to focused visual attention.
Functionality of Endothelial Cells and Pericytes From Human Pluripotent Stem Cells Demonstrated in Cultured Vascular Plexus and Zebrafish Xenografts

Objective— Endothelial cells (ECs), pericytes, and vascular smooth muscle cells (vSMCs) are essential for vascular development, and their dysfunction causes multiple cardiovascular diseases. Primary vascular cells for research are, however, difficult to obtain. Human-induced pluripotent stem cells (hiPSCs) derived from somatic tissue are a renewable source of ECs and vSMCs; however, their use as disease models has been limited by low and inconsistent efficiencies of differentiation and the lack of phenotypic bioassays. Approach and Results— Here, we developed defined conditions for simultaneous derivation of ECs and pericytes with high efficiency from hiPSCs of different tissue origin. The protocol was equally efficient for all lines and human embryonic stem cells (hESCs). The ECs could undergo sequential passage and were phenotypically indistinguishable, exhibiting features of arterial-like embryonic ECs. Moreover, hiPSC-derived ECs formed an authentic vascular plexus when cocultured with hiPSC-derived pericytes. The coculture system recapitulated (1) major steps of vascular development including EC proliferation and primary plexus remodeling, and (2) EC-mediated maturation and acquisition of contractile vSMC phenotype by pericytes. In addition, hiPSC-derived ECs integrated into developing vasculature as xenografts in zebrafish. This contrasts with more widely used ECs from human umbilical vein, which form only unstable vasculature and were completely unable to integrate into zebrafish blood vessels. Conclusions— We demonstrate that vascular derivatives of hiPSC, such as ECs and pericytes, are fully functional and can be used to study defective endothelia–pericyte interactions in vitro for disease modeling and studies on tumor angiogenesis.
Two-time scale force and position control of flexible manipulators

The problem of controlling force and position of a flexible link manipulator in contact with a compliant environment is considered in this paper. Using the singular perturbation theory, a slow subsystem associated with rigid motion dynamics and a fast sub-system associated with link flexible dynamics are identified. Hence, a two-time scale control strategy is adopted, consisting of a force and position control action for the slow sub-system and a stabilizing action for the fast subsystem. Both regulation and tracking problems are considered for the position, while the contact force is kept to a constant desired value. Simulations are presented for a two-link planar manipulator under gravity.
Compressed SuÆx Arrays and SuÆx Trees with Applications to Text Indexing and String Matching

The proliferation of online text, such as on the World Wide Web and in databases, motivates the need for space-eÆcient text indexing methods that support fast string searching. In this scenario, consider a text T that is made up of n symbols drawn from a xed alphabet and that is represented in n log j j bits by encoding each symbol with log j j bits. The goal is to support quick search queries of any string pattern P of m symbols, with T being fully scanned only once, namely, when the index is created. Text indexing schemes published in the literature are greedy of space and require additional (n logn) bits in the worst case. For example, suÆx trees and suÆx arrays need (n) memory words of (logn) bits in the standard unit cost RAM. These indexes are larger than the text itself by a factor of (log j j n), which is signi cant when is of constant size, such as ascii or unicode. On the other hand, they support fast searching either in O(m log j j) time or in O(m + logn) time, plus an output-sensitive cost O(occ) for listing the pattern occurrences. We present a new text index that is based upon new compressed representations of suÆx arrays and suÆx trees. It achieves O(m= log j j n + log j j n) search time in the worst case, for any constant 0 < 1, with at most 1 + O(1) n log j j bits of storage; that is, the index size is comparable to the text size in the worst case. The above bounds improve both time and space of previous indexing schemes. Listing the pattern occurrences introduces a sublogarithmic slowdown factor in the output-sensitive cost, giving O(occ log j j n) time as a result. When the patterns are suÆciently long, we can use auxiliary data structures in O(n log j j) bits to obtain a total search bound of O(m= log j j n+ occ) time, which is optimal. A preliminary and shortened version of the results has been presented in the Thirty-Second Annual ACM Symposium on the Theory of Computing [GV00]. yWork supported in part by the United Nations Educational, Scienti c and Cultural Organization (UNESCO) under contract UVO-ROSTE 875.631. 9 and by the Italian Ministry of Research and Education (MURST). zPart of this work was done while the author was on sabbatical at I.N. R.I. A. in Sophia Antipolis, France. It was supported in part by Army Research OÆce MURI grant DAAH04{96{1{0013 and grant DAAD19{01{1{0725 and by National Science Foundation research grant CCR{9877133.
Learning-based super-resolution of 3D face model

Super resolution technique could produce a higher resolution image than the originally captured one. However, nearly all super-resolution algorithms arm at 2D images. In this paper, we focus on generating the 3D face model of higher resolution from one input of 3D face model. In our method, the 3D face models firstly are all regularized via resampling in cylindrical representation. The super resolution then performs in the regular domain of cylindrical coordinate. The experiments using USF HumanID 3D face database of 137 3D face models are carried out, and demonstrate the presented algorithm is promising.
Effect of Carbon Source Injection Rate on CNT Film via Floating Catalyst CVD Method

A floating catalyst CVD system was utilized to synthesis CNT film. The morphological of the synthesized CNT film was characterized using field emission scanning electron microscope (FESEM) and high resolution transmission electron microscope (HRTEM). While, graphitization and crystallinity of CNT film was determined by thermogravimetric analysis and Raman spectroscopy. The injection rate of carbon source was the main variable parameter in this work shown great contribution influencing morphological structure of materials. A suitable optimization parametric study of injection rate was determined. This work shows an overview of synthesis CNT film using floating catalyst and the effect of injection carbon source solution on properties of CNT film which is useful for future work.
Achievable rates and schedules for half duplex phase fading multiple-relay networks

We present part of our work on the capacity upper bound, achievable rates, and scheduling for the half duplex multiple-relay channel (HD MRC) where every node can either transmit or listen, but not both, at any time. We derive a capacity upper bound based on the cut-set argument, and achievable rates based on the decode-forward coding strategy (DF). We discover that the upper bound and achievable rates are functions of the transmit state vector (a description of which nodes transmit and which receive). More precisely, they are functions of the time fraction of different transmit state vectors, which we term a schedule. We formulate the optimal scheduling problem to find the best schedule, one that maximizes the DF rate. For the phase fading HD MRC, surprisingly, we show that the expressions for the capacity upper bound and for DF rate can be transformed into linear programming problems.
Evaluating and tuning a static analysis to find null pointer bugs

Using static analysis to detect memory access errors, such as null pointer dereferences, is not a new problem. However, much of the previous work has used rather sophisticated analysis techniques in order to detect such errors.In this paper we show that simple analysis techniques can be used to identify many such software defects, both in production code and in student code. In order to make our analysis both simple and effective, we use a non-standard analysis which is neither complete nor sound. However, we find that it is effective at finding an interesting class of software defects.We describe the basic analysis we perform, as well as the additional errors we can detect using techniques such as annotations and inter-procedural analysis.In studies of both production software and student projects, we find false positive rates of around 20% or less. In the student code base, we find that our static analysis techniques are able to pinpoint 50% to 80% of the defects leading to a null pointer exception at runtime.
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Critical Dimension in Data Mining

Data mining is an increasingly important means of knowledge acquisition for many applications in diverse fields such as biology, medicine, management, engineering, etc. When tackling a large-scale problem that involves a multitude of potentially relevant factors but lacking a precise formulation or mathematical characterization to allow formal approaches to solution, the available data collected for the application can often be mined to extract knowledge about the problem. Feature ranking and selection, thereby, are immediate issues to consider when one prepares to perform data mining, and the literature contains numerous theoretical and empirical methods of feature selection for a variety of problems. This work in progress paper concerns the related question of critical dimension, i.e., for a specific data mining task, does there exist a minimum number (of features) which is required for a specific learning machine to achieve satisfactory performance? As a first step in addressing this question, a simple ad-hoc method is employed for experiment and it is shown that the phenomenon of critical dimension indeed exists for several of the datasets studied. The implications are that each of these datasets contains irrelevant features or input attributes, which can be eliminated to achieve higher accuracy in model building using learning machines. Keywords-feature selection; critical dimension; machine learning.
Research on Multi-colony Diploid Genetic Algorithm for Production Logistics Scheduling Optimization

In this paper, we present a Multi-Colony Diploid Genetic Algorithm (MCDGA) for Flexible Job-Scheduling Problem (FJSP), a simulation model is presented to solve the FJSP. The proposed model has been coded by Matlab which is a special mathematical computation language. After modeling the pending problem, the model is validated by a representative instances based on practical data. The result obtained from the computational study has shown that the proposed approach is a feasible and effective approach for the FJSP.
An Evaluation of Web Plagiarism Detection Systems for Student Essays

This study uses purpose-built test data and empirical experiments to report on the performance of four web plagiarism detection systems: TurnitIn, SafeAssignment, Plagiarism-Finder and EVE. In addition to measuring accuracy of detection, we evaluated the extent to which these systems produce false detections. We obtained the test data from multiple sources and edited it in several ways to conceal the plagiarisms in the texts. Our results indicate that SafeAssignment was the best overall performer.
Microinjection of Glycine into the Hypothalamic Paraventricular Nucleus Produces Diuresis, Natriuresis, and Inhibition of Central Sympathetic Outflow

Strychnine-sensitive glycine receptors and glycine-immunoreactive fibers are expressed in the hypothalamic paraventricular nucleus (PVN), yet the functional significance of this innervation is unclear. Therefore, these studies examined the changes in cardiovascular and renal function and renal sympathetic nerve activity (RSNA) produced by the microinjection of glycine (5 and 50 nmol) into the PVN of conscious Sprague-Dawley rats. Microinjection of glycine into, but not outside of, the PVN dose-dependently increased urine flow rate and urinary sodium excretion and decreased RSNA. At the higher dose, PVN glycine also decreased heart rate; neither 5 nor 50 nmol PVN glycine altered mean arterial pressure. The glycine (50 nmol)-evoked diuresis and natriuresis were abolished in rats continuously infused intravenously with [Arg8]-vasopressin. Furthermore, chronic bilateral renal denervation prevented the bradycardia and diuresis to PVN glycine and blunted the natriuresis. In other studies, unilateral PVN pretreatment with the glycine receptor antagonist strychnine (1.6 nmol) prevented the effects of PVN glycine (50 nmol) on heart rate, RSNA, and renal excretory function. When microinjected bilaterally, PVN strychnine (1.6 nmol per site) evoked a significant increase in heart rate and RSNA without altering renal excretory function. These findings demonstrate that in conscious rats glycine acts in the PVN to enhance the renal excretion of water and sodium and decrease central sympathetic outflow to the heart and kidneys. Although endogenous PVN glycine inputs elicit a tonic control of heart rate and RSNA, the renal excretory responses to PVN glycine seem to be caused primarily by the inhibition of arginine vasopressin secretion.
An 0(n log n) sorting network

The purpose of this paper is to describe a sorting network of size 0(n log n) and depth 0(log n). A natural way of sorting is through consecutive halvings: determine the upper and lower halves of the set, proceed similarly within the halves, and so on. Unfortunately, while one can halve a set using only 0(n) comparisons, this cannot be done in less than log n (parallel) time, and it is known that a halving network needs (½)n log n comparisons. It is possible, however, to construct a network of 0(n) comparisons which halves in constant time with high accuracy. This procedure (&egr;-halving) and a derived procedure (&egr;-nearsort) are described below, and our sorting network will be centered around these elementary steps.
Constraints on ship NO x emissions in Europe using GEOS-Chem and OMI satellite NO 2 observations

Abstract. We present a top-down ship NO x emission inventory for the Baltic Sea, the North Sea, the Bay of Biscay and the Mediterranean Sea based on satellite-observed tropospheric NO 2 columns of the Ozone Monitoring Instrument (OMI) for 2005–2006. We improved the representation of ship emissions in the GEOS-Chem chemistry transport model, and compared simulated NO 2 columns to consistent satellite observations. Relative differences between simulated and observed NO 2 columns have been used to constrain ship emissions in four European seas (the Baltic Sea, the North Sea, the Bay of Biscay and the Mediterranean Sea) using a mass-balance approach, and accounting for non-linear sensitivities to changing emissions in both model and satellite retrieval. These constraints are applied to 39 % of total top-down European ship NO x emissions, which amount to 0.96 Tg N for 2005, and 1.0 Tg N for 2006 (11–15% lower than the bottom-up EMEP ship emission inventory). Our results indicate that EMEP emissions in the Mediterranean Sea are too high (by 60%) and misplaced by up to 150 km, which can have important consequences for local air quality simulations. In the North Sea ship track, our top-down emissions amount to 0.05 Tg N for 2005 (35% lower than EMEP). Increased top-down emissions were found for the Baltic Sea and the Bay of Biscay ship tracks, with totals in these tracks of 0.05 Tg N (131% higher than EMEP) and 0.08 Tg N for 2005 (128% higher than EMEP), respectively. Our study explicitly accounts for the (non-linear) sensitivity of satellite retrievals to changes in the a priori NO 2 profiles, as satellite observations are never fully independent of model information (i.e. assumptions on vertical NO 2 profiles). Our study provides for the first time a space-based, top-down ship NO x emission inventory, and can serve as a framework for future studies to constrain ship emissions using satellite NO 2 observations in other seas.