Miracle-dz/UniFAR-FTUs huggingface dataset:
LORE: exploiting sequential influence for location recommendations

Providing location recommendations becomes an important feature for location-based social networks (LBSNs), since it helps users explore new places and makes LBSNs more prevalent to users. In LBSNs, geographical influence and social influence have been intensively used in location recommendations based on the facts that geographical proximity of locations significantly affects users' check-in behaviors and social friends often have common interests. Although human movement exhibits sequential patterns, most current studies on location recommendations do not consider any sequential influence of locations on users' check-in behaviors. In this paper, we propose a new approach called LORE to exploit sequential influence on location recommendations. First, LORE incrementally mines sequential patterns from location sequences and represents the sequential patterns as a dynamic Location-Location Transition Graph (L2TG). LORE then predicts the probability of a user visiting a location by Additive Markov Chain (AMC) with L2TG. Finally, LORE fuses sequential influence with geographical influence and social influence into a unified recommendation framework; in particular the geographical influence is modeled as two-dimensional check-in probability distributions rather than one-dimensional distance probability distributions in existing works. We conduct a comprehensive performance evaluation for LORE using two large-scale real data sets collected from Foursquare and Gowalla. Experimental results show that LORE achieves significantly superior location recommendations compared to other state-of-the-art recommendation techniques.
On the Boltzmann equation for long‐range interactions

We study the Boltzmann equation without Grad's angular cutoff assumption. We introduce a suitable renormalized formulation that allows the cross section to be singular in both the angular and the relative velocity variables. Angular singularities occur as soon as one is interested in long‐range interactions, while singularities in the relative velocity variable occur in the study of soft potentials, in particular, Coulomb interaction. Together with several new estimates, this new formulation enables us to prove existence of weak solutions and to give a proof of a conjecture by Lions (appearance of strong compactness) under general, fully realistic assumptions. © 2001 John Wiley & Sons, Inc.
A Combined Frequency Assignment and AP Scheduling for Throughput Maximization in IEEE 802.11 WLAN

Frequency channels are allocated to the access-points (APs) satisfying the co-channel interference in an IEEE 802.11 WLAN. Very few APs can be activated simultaneously with a conflict-free frequency assignment to them, due to limited number of frequencies. This may lead to a reduced aggregate throughput. We argue that aggregate throughput can significantly be improved by allowing some of the selected interfering APs to be activated with the same frequency but to operate in a fairly time-scheduled manner to satisfy the co-channel interference. We introduce the notion of class and cluster and based on it propose a combined frequency assignment, AP scheduling and association algorithm with the objective of maximizing the aggregate throughput. Simulation results show that the proposed algorithm is superior than both the algorithms that ignores the co-channel interference altogether by assuming proper frequency planning and that allows to activate only those APs for which a conflict-free frequency assignment exists.
Early Warning Signals of Financial Crises with Multi-Scale Quantile Regressions of Log-Periodic Power Law Singularities

We augment the existing literature using the Log-Periodic Power Law Singular (LPPLS) structures in the log-price dynamics to diagnose financial bubbles by providing three main innovations. First, we introduce the quantile regression to the LPPLS detection problem. This allows us to disentangle (at least partially) the genuine LPPLS signal and the a priori unknown complicated residuals. Second, we propose to combine the many quantile regressions with a multi-scale analysis, which aggregates and consolidates the obtained ensembles of scenarios. Third, we define and implement the so-called DS LPPLS Confidence™ and Trust™ indicators that enrich considerably the diagnostic of bubbles. Using a detailed study of the “S&P 500 1987” bubble and presenting analyses of 16 historical bubbles, we show that the quantile regression of LPPLS signals contributes useful early warning signals. The comparison between the constructed signals and the price development in these 16 historical bubbles demonstrates their significant predictive ability around the real critical time when the burst/rally occurs.
3-D bathymetric reconstruction in multi-path and reverberant underwater environments

In this paper a 3-D reconstruction method is proposed of sea bottom topography, i.e. bathymetry, for sonar data in highly reverberant and multi-path underwater environments. Recent publications showcase the negative impact of waves involving sea surface reflections on the sea bottom imaging process. The novelty of our proposal is twofold: firstly it relies on the use of Markovian-model based processors for bahymetric reconstruction and involves data association filters. Secondly, we propose a nearest neighbor version of the Integrated Probabilistic Data Association filter, capable of filtering several echo trajectories in the presence of clutter with a relatively reduced complexity compared to other existent methods.
Dependency Based Embeddings for Sentence Classification Tasks

We compare different word embeddings from a standard window based skipgram model, a skipgram model trained using dependency context features and a novel skipgram variant that utilizes additional information from dependency graphs. We explore the effectiveness of the different types of word embeddings for word similarity and sentence classiﬁcation tasks. We consider three common sentence classiﬁcation tasks: question type classiﬁcation on the TREC dataset, binary sentiment classiﬁcation on Stanford’s Sentiment Treebank and semantic relation classiﬁcation on the SemEval 2010 dataset. For each task we use three different classiﬁcation methods: a Support Vector Machine, a Convolutional Neural Network and a Long Short Term Memory Network. Our experiments show that dependency based embeddings outperform standard window based embeddings in most of the settings, while using dependency context embeddings as additional features improves performance in all tasks regardless of the classiﬁcation method. Ourembeddings and code are available at https:
On the maximum achievable rates in the decode-forward diamond channel

This paper studies the problem of two-hop transmission from a single-antenna source to a single-antenna destination via two single-antenna relays. The relays operate in a full-duplex mode and they are not capable of buffering data. The links from the source to the relays and from the relays to the destination are considered to be Rayleigh block fading and there is no direct link between the source and the destination. There is also no link between the relays. Consequently, the half-duplex mode is a direct result of the full-duplex mode with frequency or time division. All nodes are assumed to be oblivious to their forward-channel gains, however, they have perfect information about their backward-channel gains. We also assume a stringent decoding delay constraint of one fading block that makes the definition of ergodic (Shannon) capacity meaningless. Hence, we adopt the broadcast approach (multi-layer coding) to maximize the expected-rate received at the destination. For this purpose, the decode-forward (DF) relaying adopting the broadcast approach is proposed. The main feature of the proposed scheme is that the layers being decoded at both relays are added coherently at the destination although each relay has no information about the number of layers being successfully decoded by the other relay. It is proved that the optimum strategy maximizing the throughput and expected-rate is to send uncorrelated signals over the relays. The maximum throughput is analytically formulated. An achievable rate as well as upper-bounds are presented for the maximum expected-rate of the channel.
Effect of Disulfide Bonds in Antifungal Peptide from Petunia Hybrida: A Molecular Dynamics Study

The solution structure of a novel plant defensin (PhD1) contains a fifth disulfide bond, unlike other plant defensins, which have four disulfide bonds. The present study aims to better understand the stability, thermal dependence and the role of disulfide bonds in the tertiary structure of PhD1 using Molecular Dynamics (MD) simulations. The secondary structures are intact in the native structure simulated at 300 K. However, in the mutant structures a small variation is observed. A significant shift in the peptide conformation is observed when the additional fifth disulfide bond (Cys7-Cys23) is mutated. No large change in the tertiary structure conformation is observed till 400 K, which demonstrates the high thermal stability of the protein. Here, we also show that the mutation of disulfide bonds did not result in a drastic conformational change. The antifungal property along with high structural stability of the plant defensin protein makes it a promising candidate for the development of novel fungicides.
The Elliptic Solutions to the Friedmann equation and the Verlinde's Maps

We considered the solutions of the Friedmann equation in several setups, arguing that the Weierstra$\ss$ form of the solutions leads to connections with some Conformal Field Theory on a torus. Thus a link with the Cardy entropy formula is obtained in a quite natural way. The argument is shown to be valid in a four dimensional radiation dominated universe with a cosmological constant as well as in four further different Universes.
Perception of Patients With HIV/AIDS From Stigma and Discrimination

Background: Stigma and discrimination among patients with HIV/AIDS cause various problems for the patients and their health systems. Objectives: The purpose of this study was to explain the perceived experiences of the patients from stigma and discrimination and their roles on health-seeking services among patients. Patients and Methods: This was a qualitative research using content analysis approach and semi-structured interviews, conducted on patients living with HIV/ADS, during 2013 - 2014 in Iran. Sampling started purposefully and continued in a snowball. Results: The experiences of patients with HIV/AIDS from stigma and discrimination led to exploring three main themes and nine subthemes. The main themes were multidimensional stigma, rejection, and insult and discrimination in receiving health services. Conclusions: Stigma and discrimination play an important role in patients' lives and hinder them from accessing the treatment. The patients' responses to this event by secrecy strategy can be an important factor in the disease prevalence.
Multiobjective Service Restoration Considering Primary Customers using Hybrid GA-ACO Algorithm

To restore electricity service in healthy area outside the faulted zone in power distribution system is known as service restoration. In this paper, a technique based on hybrid Genetic Algorithm-Ant Colony Optimization (GA-ACO) is presented for solving the service restoration problem in electric power distribution system. Due the presence of various conflicting objectives and constraints, the task of service restoration is multi-objective and multi-constraint optimization problem. In contrast to conventional optimization technique, this approach does not require tunable weighting factors to convert multiple objectives into equivalent single objective. In this work various practical distribution systems issues such as presence of priority customers, remotely and manually controlled switches etc have been considered as objective functions. Based on simulation results on four different distribution networks, the performance of hybrid GA-ACO is found significantly better than Non Dominated Sorting of Genetic Algorithm-II (NSGA-II) and conventional Genetic Algorithm.
An Integration of Motivation and Cognition

Motivation and cognition are commonly modeled as distinct processes: motivation as some form of initiating and directing — pushing and pulling — behavior, and cognition as the manipulation of encoded representations in memory. This produces grave difficulties in understanding the interrelationships between them, and their interactions in behavior and development. I argue for a model of representation and motivation in which they emerge as different aspects of one underlying organization of interactive process. This natural integration yields an equally natural model of the joint development of higher order motivation and cognition, as interactions with learning and emotional processes are taken into account. Models of motivation and cognition often have little intrinsic relationship with each other. If, for example, cognition consists of manipulating encoded symbols (such as in the standard information processing paradigm) while motivation is concerned with energizing and directing an action system (such as in the Freudian paradigm), the interface between them is likely to be relatively ad hoc. Furthermore, such a fragmented model of mental phenomena is almost certainly false: motivation and cognition have evolved together and develop together and, consequently, must be more strongly integrated in order for their co-evolution and co-development to remain coordinated. If so, such models necessarily misrepresent the nature and interrelationships of motivation and cognition, and provide flawed guidance for developmental and educational policies and interventions. I will argue, in fact, that such models of cognition and motivation are false in themselves, independent of any issues regarding their interrelationships. The encoding paradigm, for example, including both its symbolic and its connectionist incarnations, faces myriads of fatal problems, including the fundamental fact that it cannot account for representational content, and, thus, cannot account for representation at all. The energizing conception of motivation, in turn, is incompatible with the basic fact that motivated action only occurs in systems that are, of ontological necessity, open and in ongoing interaction with their environment. Inertness that must be 'energized' is not an option. Nevertheless, I will argue, such fragmented models of mind are not only common, but are forced by dominant theoretical approaches and their presuppositions. I outline an alternative model in which motivation and cognition are tightly — ontologically, not merely ontogenetically — integrated and illustrate some of its consequences. The alternative model, however, requires changes in theoretical presuppositions, not just their contents. The presuppositions of a theoretical approach — even to the level of metaphysical presuppositions …
The age of the main population of the Sagittarius dwarf spheroidal galaxy. Solving the "M giant conundrum"

We present a statistically decontaminated Color Magnitude Diagram of a $1\degr\times 1\degr$ field in the core of the Sagittarius dSph galaxy. Coupling this CMD with the most recent metallicity distributions obtained from high resolution spectroscopy we derive robust constraints on the mean age of the stellar population that dominates the galaxy (Pop A). Using three different sets of theoretical isochrones in the metallicity range $-0.4\le [{\rm M/H}]\le -0.7$ and taking into consideration distance moduli in the range $16.90\le (m-M)_0\le 17.20$ we find that the mean age of Pop A is larger than 5 Gyr, and the best-fit value is age = $8.0\pm 1.5$ Gyr. Since Pop A provides the vast majority of the M giants that traces the tidal stream of Sgr dSph all over the sky, our estimate resolves the so called “M giant conundrum” (Majewski et al. 2003, ApJ, 599, 1082). The time needed by the M giants that currently populates the stream to diffuse within the main body of Sgr and to reach the extremes of the tidal tails once torn apart from the parent galaxy ($\simeq$$3{-}4$ Gyr) can be easily accommodated into the time lapsed since their birth ($\simeq$$5.5{-}9.5$ Gyr).
Interaction Issues in Malaysia Open Distance Learning(ODL)

Open Distance Learning calls upon an impressive range of technologies to enable distance teachers and distance learners (DLs) who are separated by distance to communicate with each other in real time (synchronous) and delayed time (asynchronous) which means DLs can access education and learning opportunities at a time, place, and pace to suit their individual lifestyles, learning preferences and personal developments plans. Such separation according to (Idrus & Lateh,2000) give rise to “an impressive and innovative array of media mix resulting in the application of technology in education”(p.197). Such development offers a radical new direction for DE enthusiasts, teachers and learners alike. They incorporate flexible and open learning methods as well as modified and specially created learning resources.
Temporal Risk for Unwanted Sex Among College Students

The “red zone” usually refers to the first few weeks of the first semester at college, when female students are believed to be at greatest risk for experiencing unwanted sex. We tested this notion using data from a survey study of 207 firstand second-year students (121 women, 84 men) at a small, liberal arts university. Results demonstrated only one significant elevation in incidence rates of firstand second-year women’s unwanted sexual experiences (sexual touching, attempted and completed anal, oral, and vaginal sex), between the end of the first month and fall break (mid-October) during the second year at school. Previous research and local information about the relevant behaviors of sorority and fraternity members is discussed in light of these findings to provide heuristic material for further empirical testing. Because risk may involve both temporal and situational factors, systematic collection and dissemination of local data are recommended.
Visualization of Magnetoencephalographic Data Using Minimum Current Estimates

The locations of active brain areas can be estimated from the magnetic field the neural current sources produce. In this work we study a visualization method of magnetoencephalographic data that is based on minimum[symbol: see text] (1)-norm estimates. The method can represent several local or distributed sources and does not need explicit a priori information. We evaluated the performance of the method using simulation studies. In a situation resembling typical magnetoencephalographic measurement, the mean estimated source strength exceeded baseline level up to 2 cm from the simulated point-like source. The method can also visualize several sources, activated simultaneously or in a sequence, which we demonstrated by analyzing magnetic responses associated with sensory stimulation and a picture naming task.
Challenging Heteronormativity in Elementary classrooms

Heteronormativity is the positioning of heterosexuality as normal and nonheterosexuality as abnormal and deviant. Heteronormativity in schools can be devastating for students and teachers alike. This study focused on challenging heteronormativity in elementary classrooms; specifically, how elementary school teachers are challenging heteronormativity in their classrooms and their perspectives on how their students respond. Four elementary school educators from the Greater Toronto Area participated in semi-structured interviews. The interviewees made it clear that the cycle of heteronormativity is still alive and well in elementary schools; this leads to the oppression and marginalization of both staff and students. It is clear that something must be done. The interviewees spoke about the LGBTQ topics they taught, the resources they used to support their teaching, their students’ responses to their pedagogy, the challenges they faced when challenging heteronormativity in their schools, and the overall importance of challenging heteronormativity. The information outlined in this study is a valuable resource for any staff member looking to challenge heteronormativity in their classroom, school, or school board. If everyone does their part, the bullying, shame, hiding, and hurting can end.
Toll-Like Receptor 4 Promotes Autonomic Dysfunction, Inflammation and Microglia Activation in the Hypothalamic Paraventricular Nucleus: Role of Endoplasmic Reticulum Stress

Background & Purpose Toll-like receptor 4 (TLR4) signaling induces tissue pro-inflammatory cytokine release and endoplasmic reticulum (ER) stress. We examined the role of TLR4 in autonomic dysfunction and the contribution of ER stress. Experimental approach Our study included animals divided in 6 experimental groups: rats treated with saline (i.v., 0.9%), LPS (i.v., 10mg/kg), VIPER (i.v., 0.1 mg/kg), or 4-PBA (i.p., 10 mg/kg). Two other groups were pretreated either with VIPER (TLR4 viral inhibitory peptide) LPS + VIPER (i.v., 0.1 mg/kg) or 4-Phenyl butyric acid (4-PBA) LPS + PBA (i.p., 10 mg/kg). Arterial pressure (AP) and heart rate (HR) were measured in conscious Sprague-Dawley rats. AP, HR variability, as well as baroreflex sensitivity (BrS), was determined after LPS or saline treatment for 2 hours. Immunofluorescence staining for NeuN, Ib1a, TLR4 and GRP78 in the hypothalamic paraventricular nucleus (PVN) was performed. TNF-α, TLR4 and GRP78 protein expression in the PVN were evaluated by western blot. Plasma norepinephrine levels were determined by ELISA. Key Results Acute LPS treatment increased HR and plasma norepinephrine concentration. It also decreased HR variability and high frequency (HF) components of HR variability, as well BrS. Acute LPS treatment increased TLR4 and TNF-α protein expression in the PVN. These hemodynamic and molecular effects were partially abrogated with TLR4 blocker or ER stress inhibitor pretreatment. In addition, immunofluorescence study showed that TLR4 is co-localized with GRP78in the neurons. Further inhibition of TLR4 or ER stress was able to attenuate the LPS-induced microglia activation. Conclusions & Implications TLR4 signaling promotes autonomic dysfunction, inflammation and microglia activation, through neuronal ER stress, in the PVN.
Hydration mechanisms of mineral trioxide aggregate.

AIM To report the hydration mechanism of white mineral trioxide aggregate (White MTA, Dentsply, Tulsa Dental Products, Tulsa, OK, USA). METHODOLOGY The chemical constitution of white MTA was studied by viewing the powder in polished sections under the scanning electron microscope (SEM). The hydration of both white MTA and white Portland cement (PC) was studied by characterizing cement hydrates viewed under the SEM, plotting atomic ratios, performing quantitative energy dispersive analyses with X-ray (EDAX) and by calculation of the amount of anhydrous clinker minerals using the Bogue calculation. RESULTS Un-hydrated MTA was composed of impure tri-calcium and di-calcium silicate and bismuth oxide. The aluminate phase was scarce. On hydration the white PC produced a dense structure made up of calcium silicate hydrate, calcium hydroxide, monosulphate and ettringite as the main hydration products. The un-reacted cement grain was coated with a layer of hydrated cement. In contrast MTA produced a porous structure on hydration. Levels of ettringite and monosulphate were low. Bismuth oxide was present as un-reacted powder but also incorporated with the calcium silicate hydrate. CONCLUSIONS White MTA was deficient in alumina suggesting that the material was not prepared in a rotary kiln. On hydration this affected the production of ettringite and monosulphate usually formed on hydration of PC. The bismuth affected the hydration mechanism of MTA; it formed part of the structure of C-S-H and also affected the precipitation of calcium hydroxide in the hydrated paste. The microstructure of hydrated MTA would likely be weaker when compared with that of PC.