Miracle-dz/UniFAR-FTUs huggingface dataset:
Multimodal Context-Aware Recommender for Post Popularity Prediction in Social Media

Millions of multimodal posts are uploaded, shared, viewed and liked every day in different social networks, where users express their opinions about different items such as products and places. While, some user posts become popular, others are ignored. Even different posts related to the same items shared by different users receive different number of likes and views. Existing research on popularity prediction aggregate all user posts related to different items without considering the preferences of individual user for the items in training a popularity model. This often results in limited success. We hypothesize that popularity of posts differs from one user to the other user, one item to the other items, and posts related to the similar users or similar items may be received the same number of likes. In this paper, we present an approach for predicting the popularity of user posts by considering preferences of individual users to the items. We factorize the popularity of posts to the user-item-context and propose a multimodal context-aware recommender for predicting the popularity of posts. Using our proposal we have the ability of predicting the popularity of posts related to different items which are shared by a specific user. Moreover we are able to predict the popularity of posts shared with different users for a specific item. We evaluate our approach on an Instagram user posts dataset with over 600K posts in total related to different touristic places, as items, in The Netherlands for the task of popularity prediction.
La gestion des situations à haut risque de létalité afin de prévenir l'homicide de la conjointe

This article reports the results of two researches, conducted in Quebec on the prevention of domestic homicides. The first focused on a better understanding of interventions made during incidents of domestic violence with high lethality risk. In the second project, the authors developed with the results of this research an intervention guide for the prevention of domestic homicide.
A software development methodology for sustainable ICTD solutions

Information and Communication Technology continue to be increasingly used in social development and poverty alleviation projects, known as Information and Communication Technology for Development (ICTD) projects. However, most interventions either fail completely as a result of attempting to use inappropriate software development approaches and technology concepts in the different ICTD context or they only execute small scale prototypes without positive long-term social impact. We present a case study on how we combined and adapted, using an iterative action research refinement approach, established interaction design methods into a software development methodology supporting scalable long-term ICTD software projects: the Technical ICTD Methodology (TIM). Our case study is based on the experiences of a series of ICTD projects executed within a major software corporation over a period of more than five years.
Simulating Smooth Tutorial Dialogue with Pedagogical Value

This paper describes the design of AutoTutor, a fully automated computer tutor that simulates dialogue moves of normal human tutors and that will eventually incorporate sophisticated tutoring strategies. Autolhtot follows a curriculum script that presents subtopics in different forms, such as didactic content, graphic displays, questions, and problems. The tutor selects dialogue moves that assist the learner in the active coustruction of knowledge as the learner ans~ers questions or solves problems posed by the tutor. The goal is to have the tutor produce dialogue moves that fit the conversational context, that are sensitive to the learner’s abilities, and that have pedagogical value. The di~dogue rnoves include immediate feedback, pumping, prompting, splicing, hinting, requestioning, and summarizing. The tutor’s moves are delivered by a talking head with appropriate facial expressions and synthe.4zed speech. The first version of Auto~ltor should be completed in the spring of 1998 on the topic of comput.er literacy.
Iterative detection for pretransformed OFDM by subcarrier reconstruction

In this paper, an iterative detection method for an uncoded pretransformed (PT) orthogonal frequency division multiplexing (OFDM) system where the channel is not known at the transmitter is proposed. The iterative detection starts with linear detection. The noiseless received signal at the weakest subcarrier (corresponding to the smallest channel amplitude) is estimated based on all the detected data symbols using a hard or soft decision. Then, the actual received signal at the weakest subcarrier is replaced by the estimated one. This process is referred to as reconstruction here. After reconstruction, linear detection is carried out again to generate the next set of symbol estimates. The whole process proceeds iteratively to reconstruct the received signal at the next-weakest subcarrier. The transform coefficients and the iterative process are designed to maximize the minimum signal-to-noise power ratio. Under the assumption that the previous detection is error free, it is shown analytically that the iterative method achieves a diversity advantage of i+1 in the ith iteration, thus providing an explanation of its superior performance. Due to the flexibility of the transform design, the analysis conducted is applicable for other common systems as well. Simulations in realistic channels are carried out, and the bit-error rate performance of the iterative detection is superior as compared to that of the conventional detectors for the PT-OFDM or OFDM system.
Drug provocation testing in the diagnosis of drug hypersensitivity reactions: general considerations

A drug provocation test (DPT) is the controlled administration of a drug in order to diagnose drug hypersensitivity reactions. DPTs are performed under medical surveillance, whether this drug is an alternative compound, or structurally/pharmacologically related, or the suspected drug itself. DPT is sometimes termed controlled challenge or reexposure (1), drug challenge (2), graded (2) or incremental challenge (3), test dosing (2), W. Aberer, A. Bircher, A. Romano, M. Blanca, P. Campi, J. Fernandez, K. Brockow, W. J. Pichler, P. Demoly for ENDA, and the EAACI interest group on drug hypersensitivity Department of Environmental Dermatology, University of Graz, Graz, Austria; Department of Dermatology, Basle, Switzerland; Allergy Service, Catholic University of Rome, Italy; Allergy Service, University La Paz, Madrid, Spain; Clinic for Allergy and Immunology, Florence, Italy; Allergy Section, Dept. Clin. Med., UMH, Elche, Spain; Klinik und Poliklinik f1r Dermatologie und Allergologie, Muenchen, Germany; Clinic for Rheumatology and Clinical Immunology/Allergology, Inselspital, Bern, Switzerland; Maladies Respiratoires-INSERM U454, H7pital Arnaud de Villeneuve, Montpellier, France
Molecular complexity of leukocyte surface glycoproteins related to the macrophage differentiation antigen Mac-1

Monoclonal antibodies have been obtained that react with the murine leukocyte surface glycoproteins bearing the macrophage differentiation antigen Mac-1. Structural and antigenic analysis shows that related glycoproteins are found on other murine hematopoietic cell types. The data not only illustrate the complexity of cell surface structures that can be detected by means of monoclonal antibodies, but also raise questions as to the functional significance of this family of molecules within the hematopoietic system.
The Roles of APOBEC3G Complexes in the Incorporation of APOBEC3G into HIV-1

Background The incorporation of human APOBEC3G (hA3G) into HIV is required for exerting its antiviral activity, therefore the mechanism underlying hA3G virion encapsidation has been investigated extensively. hA3G was shown to form low-molecular-mass (LMM) and high-molecular-mass (HMM) complexes. The function of different forms of hA3G in its viral incorporation remains unclear. Methodology/Principal Findings In this study, we investigated the subcellular distribution and lipid raft association of hA3G using subcellular fractionation, membrane floatation assay and pulse-chase radiolabeling experiments respectively, and studied the correlation between the ability of hA3G to form the different complex and its viral incorporation. Our work herein provides evidence that the majority of newly-synthesized hA3G interacts with membrane lipid raft domains to form Lipid raft-associated hA3G (RA hA3G), which serve as the precursor of mature HMM hA3G complex, while a minority of newly-synthesized hA3G remains in the cytoplasm as a soluble LMM form. The distribution of hA3G among the soluble LMM form, the RA LMM form and the mature forms of HMM is regulated by a mechanism involving the N-terminal part of the linker region and the C-terminus of hA3G. Mutagenesis studies reveal a direct correlation between the ability of hA3G to form the RA LMM complex and its viral incorporation. Conclusions/Significance Together these data suggest that the Lipid raft-associated LMM A3G complex functions as the cellular source of viral hA3G.
An experimental protocol for in situ colorectal liver metastases ablation by radiofrequency toward a standard procedure

Background: Radiofrequency ablation (RF) is already a viable alternative to surgical resection for focal liver tumors treatment. The use of RF ablation in combination with surgery or chemotherapy and the large panel of RF tools need new experimental models to develop new opportunities for this kind of therapy. Purpose: The purpose of this study was to identify the optimal RF parameters that will allow in situ colic cancer liver metastases destruction with minimal secondary effects. Materials and Methods: The CC531s colic cancer tumor cells were used to induce liver metastases in 30 synergic Wag/Rij rats. When metastases reached at least 1 cm in diameter, RF generator RITA 1500X, and expandable tip RF probe Starburst SDE (Angiodynamics, USA) was used for the RF ablation. The animal survival rate and the RF-induced lesions have been studied, while only the generator delivered power has been modified (90W, 20W, and 10W, respectively). Results: Survival was significantly low in the group with 90W-delivered power RF. Moreover, statistically significant differences were revealed between groups with high and low RF power, regarding the morphological changes of the liver parenchyma and the adjacent organs, without significant difference on the RF therapeutically effect. Conclusions: In an experimental setting, an increased RF generator power induces important lesions of the abdominal organs with subsequently important mortality rate, without improving the RF therapeutic efficiency.
Real-time collision detection for multiple packaging robots using monotonicity of configuration subspaces

Due to the increasing demand for higher performance (throughput and efficiency) of robotic packaging systems, and the need to keep the system's footprint as small as possible, robots must operate closer to each other. This gives rise to progressively more difficult variants of the problems of collision detection and collision avoidance. In this work we focus on designing algorithms for collision detection between multiple parallel (Delta) robots, which are widely used in the packaging industry. The algorithms must operate in a real-time controller, which puts additional constraints on the processing power and memory requirements. We identify certain monotonicity properties in the composite configuration space of the underlying robots, which help us to devise highly effective collision detection algorithms for them. We lay out the theoretical basis of our development, describe the new algorithms, and report on simulation results. The results show that two of the new algorithms can reduce the memory requirements by 45% and 90%, respectively, without any loss of information as opposed to an approach based on solely existing techniques. Furthermore, our solution easily satisfies the real-time constraint with a typical query time of 3 microseconds. Finally, we demonstrate the real-time capabilities of our algorithms in an industrial setup.
SM4AM: A Semantic Metamodel for Analytical Metadata

Next generation BI systems emerge as platforms where traditional BI tools meet semi-structured and unstructured data coming from the Web. In these settings, the user-centric orientation represents a key characteristic for the acceptance and wide usage by numerous and diverse end users in their data analysis tasks. System and user related metadata are the base for enabling user assistance features. However, current approaches typically store these metadata in ad-hoc manners. In this paper, we propose a generic and extensible approach for the definition and modeling of the relevant metadata artifacts. We present SM4AM, a Semantic Metamodel for Analytical Metadata created as an RDF formalization of the Analytical Metadata artifacts needed for user assistance exploitation purposes in next generation BI systems. We consider the Linked Data initiative and its relevance for user assistance functionalities. We discuss the metamodel benefits and present directions for future work.
Two Methods of Object Designing by Rational Splines

Object designing has a significance importance in the field of Computer-Aided Design (CAD), Computer-Aided Geometric Design (CAGD) and Computer-Aided Manufacturing (CAM). In this paper, two techniques for the designing of 2D objects are developer. These are based on rational cubic spline interpolant and rational quadratic spline interpolant with shape parameters controlling the shape of the curve in the description of rational functions. It is shown that a piece of curve designed using rational cubic spline interpolant can be presented by two segments of rational quadratic spline interpolant. The developed schemes are simple, local and computationally inexpensive.
Wait-learning : intelligent systems for making productive use of wait time

Every day, millions of people set long-term goals, such as learning a skill, developing a habit, or completing a project. Yet, in our busy, time-crunched world, most have difficulty making progress towards these goals. Despite this lack of time, there are numerous moments in a day when people wait, such as waiting for the elevator or waiting for an instant message reply. These fleeting moments could instead be used for completing short, concrete microtasks towards accomplishing long-term goals. This thesis presents novel systems and approaches that enable wait-time productivity. First, WaitChatter enables wait-learning, by automatically detecting when a user is awaiting an instant message reply, and presenting foreign language vocabulary exercises during that time. Second, WaitSuite is a suite of systems that expand wait-learning to diverse kinds of waiting scenarios. Furthermore, given a variety of microtasks, I also demonstrate how chains of microtasks can be ordered in a way that maximizes efficiency and minimizes mental workload. Finally, Deadspace Finder enables peripheral microtasks to be displayed less intrusively, by automatically detecting and placing them into unused screen space. Taken together, these systems demonstrate that wait-time productivity is both feasible and more effective than traditional reminders, making meaningful use of time we didn’t know we had. Thesis Supervisor: Robert C. Miller Title: Professor of Electrical Engineering and Computer Science
An obstacle avoidance method for two wheeled mobile robot

In this paper, we proposed an obstacle avoidance method of mobile robot by using lobula giant movement detector (LGMD) method. The LGMD is an identified neuron in the locust brain that responds most strongly to the image of an approaching object such as a predator. As an assistance to the avoidance method, we add a distance measurement algorithm to LGMD method. The measurement algorithm is based on information from camera to detect obstacles and calculate the route for two wheeled mobile robot. Simulation result confirmed the effectiveness of the proposed method.
Tighter Low-rank Approximation via Sampling the Leveraged Element

In this work, we propose a new randomized algorithm for computing a low-rank approximation to a given matrix. Taking an approach different from existing literature, our method first involves a specific biased sampling, with an element being chosen based on the leverage scores of its row and column, and then involves weighted alternating minimization over the factored form of the intended low-rank matrix, to minimize error only on these samples. Our method can leverage input sparsity, yet produce approximations in spectral (as opposed to the weaker Frobenius) norm; this combines the best aspects of otherwise disparate current results, but with a dependence on the condition number κ = σ1/σr. In particular we require O(nnz(M)+nκ2r5/e2) computations to generate a rank-r approximation to M in spectral norm. In contrast, the best existing method requires O(nnz(M)+nr2/e4) time to compute an approximation in Frobenius norm. Besides the tightness in spectral norm, we have a better dependence on the error e. Our method is naturally and highly parallelizable. Our new approach enables two extensions that are interesting on their own. The first is a new method to directly compute a low-rank approximation (in efficient factored form) to the product of two given matrices; it computes a small random set of entries of the product, and then executes weighted alternating minimization (as before) on these. The sampling strategy is different because now we cannot access leverage scores of the product matrix (but instead have to work with input matrices). The second extension is an improved algorithm with smaller communication complexity for the distributed PCA setting (where each server has small set of rows of the matrix, and want to compute low rank approximation with small amount of communication with other servers).
Tolrestat in the Primary Prevention of Diabetic Neuropathy

OBJECTIVE To compare the effects of tolrestat and placebo in patients with subclinical diabetic neuropathy. RESEARCH DESIGN AND METHODS Non-insulin-dependent diabetes mellitus (NIDDM) patients with early involvement of the autonomic nervous system were identified by only one pathological (outside the 99% confidence interval of the normal population) squatting test (vagal or sympathetic). Fifty-seven patients entered a randomized, placebo-controlled, double-blind, parallel 52-week study of tolrestat at a dose of 200 mg/day. Cardiovascular reflex tests (squatting vagal and sympathetic tests, pressure gain, deep breathing, lying-to-standing, Valsalva maneuver, and orthostatic hypertension), vibration thresholds, tendon reflexes, and muscle strength were assessed throughout the study. RESULTS At 12 months, nerve function significantly improved in patients receiving tolrestat and deteriorated in patients taking placebo. At baseline, the squatting vagal test was normal in 16 patients in the tolrestat group and in 15 patients in the placebo group. At 12 months, 25 patients taking tolrestat had a normalized squatting test, but only 6 patients taking placebo did (P = 0.02). Vibration perception threshold improved by a value of 6 ± 3 V in the tolrestat group (P < 0.001) and deteriorated by a value of 3 ± 1.8 V (P < 0.001) in the placebo group. CONCLUSIONS Tolrestat may be useful in the primary prevention of diabetic neuropathy.
Assessing the impact of a university teaching development programme

Four different indicators are used to assess the impact of a year‐long university teaching development programme in an Australian research‐led university. All four indicators show small positive outcomes. Teachers who complete the programme have higher rates of receipt of teaching awards and teaching development grants than their colleagues who do not participate in the programme. Students in the classes of teachers who complete the programme report, on average, higher satisfaction scores than students in the classes of the same teacher before she/he completed the programme. Students in the faculties where the programme is completed by a higher proportion of academic staff report greater change to levels of satisfaction in the quality of their degree over the seven‐year period of the study. The methodology adopted involves several new approaches to evaluation and confirms the need for the use of an evaluation framework and multi‐indicator strategy.
Comparison of Numerical Methods for Solving Initial Value Problems for Stiff Differential Equations

Special classes of Initial value problem of differential equations termed as stiff differential equations occur naturally in a wide variety of applications including the studies of spring and damping systems, chemical kinetics, electrical circuits, and so on. Most realistic stiff systems do not have analytical solutions so that a numerical procedure must be used. In this paper we have discussed the phenomenon of stiffness and the general purpose procedures for the solution of stiff differential equation. Because of their applications in many branches of engineering and science, many algorithms have been proposed to solve such problems. In this study we have focused on some conventional methods namely Runge-Kutta method, Adaptive Stepsize Control for Runge-Kutta and an ODE Solver package, EPISODE. We describe the characteristics shared by these methods. We compare the performance and the computational effort of such methods. In order to achieve higher accuracy in the solution, the traditional numerical methods such as Euler, explicit Runge-Kutta and Adams –Moulton methods step size need to be very small. This however introduces enough round-off errors to cause instability of the solution. To overcome this problem we have used two other algorithms namely Adaptive Stepsize Control for Runge-Kutta and EPISODE. The results are compared with exact one to determine the efficiency of the above mentioned method. GANIT J. Bangladesh Math. Soc. (ISSN 1606-3694) 30 (2010) 121-132 DOI: http://dx.doi. org/10.3329/ganit.v30i0. 8509
Missed Shots at the Free-Throw Line

Choking under pressure represents a phenomenon in which individuals faced with a high-pressure situation do not perform as well as would be expected were they performing under normal conditions. In this article, I identify determinants that predict a basketball player’s susceptibility to choking under pressure. Identification of these determinants adds to our understanding of players’ psychology at pivotal points in the game. My analysis draws on play-by-play data from ESPN.com that feature over 2 million free-throw attempts in women’s and men’s college and professional basketball games from the 2002-2013 seasons. Using regression analysis, I explore the impact of both gender and level of professionalism on performance in high-pressure situations. I find that in the final 30 seconds of a tight game, Women’s National Basketball Association and National Basketball Association players are 5.81 and 3.11 percentage points, respectively, less likely to make a free throw, while female and male college players are 2.25 and 2.09 percentage points, respectively, less likely to make a free throw, though statistical significance cannot be established among National Collegiate Athletic Association women. The discrepancy in choking between college and professional players is pronounced when comparing male college players who do and do not make it to the professional level; the free-throw performance of those destined to go pro falls 6 percentage points more in high-pressure situations. Finally, I find that women and men do not differ significantly in their propensity to choke.