Miracle-dz/UniFAR-FTUs huggingface dataset:
Churn Prediction in a Real Online Social Network Using Local CommunIty Analysis

Prediction of user behavior in Social Networks is important for a lot of applications, ranging from marketing to social community management. In this paper, we develop and test a model to estimate the propensity of a user to stop using the social platform in a near future. This problem is called churn prediction and has been extensively studied in telecommunication networks. We focus here on building a statistical model estimating the probability that a user will leave the social network in the near future. The model is based on graph attributes extracted in the user's vicinity. We present a novel algorithm to accurately detect overlapping local communities in social graphs. Our algorithm outperforms the state of the art methods and is able to deal with pathological cases which can occur in real networks. We show that using attributes computed from the local community around the user allows to build a robust statistical model to predict churn. Our ideas are tested on one of the largest French social blog platform, Sky rock, where millions of teenagers interact daily.
Benefits of physical exercise training on cognition and quality of life in frail older adults.

OBJECTIVES Frailty is a state of vulnerability associated with increased risks of fall, hospitalization, cognitive deficits, and psychological distress. Studies with healthy senior suggest that physical exercise can help improve cognition and quality of life. Whether frail older adults can show such benefits remains to be documented. METHOD A total of 83 participants aged 61-89 years were assigned to an exercise-training group (3 times a week for 12 weeks) or a control group (waiting list). Frailty was determined by a complete geriatric examination using specific criteria. Pre- and post-test measures assessed physical capacity, cognitive performance, and quality of life. RESULTS Compared with controls, the intervention group showed significant improvement in physical capacity (functional capacities and physical endurance), cognitive performance (executive functions, processing speed, and working memory), and quality of life (global quality of life, leisure activities, physical capacity, social/family relationships, and physical health). Benefits were overall equivalent between frail and nonfrail participants. DISCUSSION Physical exercise training leads to improved cognitive functioning and psychological well-being in frail older adults.
Optogenetically induced sleep spindle rhythms alter sleep architectures in mice

Sleep spindles are rhythmic patterns of neuronal activity generated within the thalamocortical circuit. Although spindles have been hypothesized to protect sleep by reducing the influence of external stimuli, it remains to be confirmed experimentally whether there is a direct relationship between sleep spindles and the stability of sleep. We have addressed this issue by using in vivo photostimulation of the thalamic reticular nucleus of mice to generate spindle oscillations that are structurally and functionally similar to spontaneous sleep spindles. Such optogenetic generation of sleep spindles increased the duration of non-rapid eye movement (NREM) sleep. Furthermore, the density of sleep spindles was correlated with the amount of NREM sleep. These findings establish a causal relationship between sleep spindles and the stability of NREM sleep, strongly supporting a role for the thalamocortical circuit in sleep regulation.
Preparation and mechanism of charge carrier transportation of MsO/LDPE nanocomposites

With the development of high-voltage direct current (HVDC) transmission, LDPE nanocomposites have attracted more attention for fabricating HVDC cables instead of oil-filled cables and mass impregnated cables. However, the HVDC cable insulating materials with high-performance electrical properties are urgent to realize and the mechanism of charge carrier transportation is still unclear. In this work, LDPE nanocomposites filled with multi-layer structure MgO was prepared by means of melt blending. As the MgO is considered as the ideal nanofillers owing to execellent electric properties in dc materials. Few studies have reported the special structure of nanofiller on suppressing space charge and mechanism of charge carriers transportation. The multi-layer structure MgO was prepared through a solvothermal method, which is low density, high aspect ratio. The microstructures, as well as the space charge distribution and thermally stimulated current (TSC) were studied. The mechanism of charge carrier injection and transportation in MgO/LDPE nanocomposites under HVDC transmission condition were also explored. Results showed that the multi-layer structure of MgO nanoparticles were homogeneously dispersed in LDPE matrix, which enhanced the overall electrical properties of the MgO/LDPE nanocomposites. Moreover, the hypothesis model of charge carrier transport in solid dielectrics coupling with experimental results were used to explore the mechanism of charge carrier injection and transportation under HVDC condition.
CFORB: Circular FREAK-ORB Visual Odometry

We present a novel Visual Odometry algorithm entitled Circular FREAK-ORB (CFORB). This algorithm detects features using the well-known ORB algorithm [12] and computes feature descriptors using the FREAK algorithm [14]. CFORB is invariant to both rotation and scale changes, and is suitable for use in environments with uneven terrain. Two visual geometric constraints have been utilized in order to remove invalid feature descriptor matches. These constraints have not previously been utilized in a Visual Odometry algorithm. A variation to circular matching [16] has also been implemented. This allows features to be matched between images without having to be dependent upon the epipolar constraint. This algorithm has been run on the KITTI benchmark dataset and achieves a competitive average translational error of $3.73 \%$ and average rotational error of $0.0107 deg/m$. CFORB has also been run in an indoor environment and achieved an average translational error of $3.70 \%$. After running CFORB in a highly textured environment with an approximately uniform feature spread across the images, the algorithm achieves an average translational error of $2.4 \%$ and an average rotational error of $0.009 deg/m$.
Degenerate stochastic differential equations for catalytic branching networks

On prouve l'unicite d'un probleme de martingale correspondant a une EDS degeneree, qui apparait comme un modele de reseaux avec branchement catalytique. Ce travail est une extension des resultats de Dawson et Perkins [Illinois J. Math. 50 (2006) 323―383] au cas de reseaux generaux. On obtient en particulier des estimees pour le semi-groupe des reseaux generaux, sous forme de normes de Holder ponderees; et on etablit l'equivalence de ces normes avec des normes de semi-groupe dans ce contexte general.
Instant Web Retrieval for Instance-Attribute Queries

As the Web becomes the major information source of our daily activities, tools for finding various information on it are indispensable. This paper addresses theWeb retrieval of instance-attribute information, e.g., the contact addresses and research interests (attributes) of faculty and students (instances). This kind of information need is very common but cannot be directly supported by current keywordmatching-based search engines. People commonly use a two-phase search: First, locate the candidate pages, e.g., a faculty page, and then search within them for the desired information, e.g., contact information. Based on the stimulation of such human search behavior, we design a retrieval engine, upon general search engines, to help find the instance-attribute information from the Web. The experiment on several faculty members has shown the feasibility of the approach.
2 A Multi-Scale Model of Visual Organization 2 . 1 Motivation : Importance of Multiple Scales

We propose a new method for assessing the perceptual organization of information graphics, based on the premise that the visual structure of an image should match the structure of the data it is intended to convey. The core of our method is a new formal model of perceptual structure, based on classical machine vision techniques for analyzing an image at multiple resolutions. The model takes as input an arbitrary grayscale image and returns a lattice structure describing the visual organization of the image. We show how this simple model captures several aspects of traditional design aesthetics, and we describe a software tool that implements the model to help designers analyze and refine visual displays. Our emphasis here is demonstrating the model’s potential as a design aid rather than as a description of human perception, but given its initial promise we propose that it merits further study and describe a variety of ways in which the model could be extended and validated.
Functional Morphology of Mastication in Musteloid Carnivorans

DAVIS, JILLIAN S. , Ph.D., August 2014, Biological Sciences Functional Morphology of Mastication in Musteloid Carnivorans Director of Dissertation: Susan H. Williams Masticatory morphology, jaw muscle activity pattern, and kinematics were studied in two species of musteloid carnivorans: the ferret (Mustela putorius furo), a carnivorous mustelid, and the kinkajou (Potos flavus), a frugivorous procyonid. Morphology of the jaw adductors was studied using gross dissection and Lugol’s iodineenhanced microCT scanning, jaw muscle activity patterns were studied using electromyography, and kinematics were studied using XROMM (X-ray Reconstruction of Moving Morphology; Brainerd et al., 2010). These closely-related but dietarily divergent species were used to identify shared characteristics in masticatory form and function among carnivorans and test hypotheses about adaptation and constraint in the masticatory apparatus. For example, although kinkajous are derived from carnivorous ancestors, their frugivorous diet places different mechanical demands on their masticatory apparatus, which may be expected to correlate with differences in form and function. Ferrets and kinkajous were found to have many general similarities in masticatory form and function. For example, both species have general similarities in craniofacial morphology, near-simultaneous activity of all jaw adductor muscles during mastication, and predominantly vertical jaw movements during mastication. However, we also identified some functionally important differences in masticatory form and function in the kinkajou. Kinkajous differ from ferrets morphologically in that have increased the
Effect of Phage on the Infectivity of Vibrio cholerae and Emergence of Genetic Variants

ABSTRACT Seasonal epidemics of cholera in Bangladesh are self-limited in nature, presumably due to phage predation of the causative Vibrio cholerae during the late stage of an epidemic, when cholera patients excrete large quantities of phage in their stools. To further understand the mechanisms involved, we studied the effect of phage on the infectivity and survival of V. cholerae shed in stools. The 50% infectious dose of stool vibrios in infant mice was ∼10-fold higher when the stools contained a phage (1.8 × 103 to 5.7 × 106 PFU/ml) than when stools did not contain a detectable phage. In competition assays in mice using a reference strain and phage-negative cholera stools, the infectivity of biofilm-like clumped cells was 3.9- to 115.9-fold higher than that of the corresponding planktonic cells. However, the difference in infectivity of these two cell populations in phage-positive stools was significantly less than that in phage-negative stools (P = 0.0006). Coculture of a phage and V. cholerae or dilutions of phage-positive cholera stools in nutrient medium, but not in environmental water, caused rapid emergence of phage-resistant derivatives of the bacteria, and these derivatives lost their O1 antigen. In cholera stools and in intestinal contents of mice prechallenged with a mixture of V. cholerae and phage, the bacteria remained completely phage susceptible, suggesting that the intestinal environment did not favor the emergence of phage-resistant derivatives that lost the O1 antigen. Our results indicate that phages lead to the collapse of epidemics by modulating the required infectious dose of the bacteria. Furthermore, the dominance of phage-resistant variants due to the bactericidal selective mechanism occurs rarely in natural settings, and the emerging variants are thus unable to sustain the ongoing epidemic.
Measurement of the CP-violating phase in B [ superscript 0 ]

Citation " Measurement of the CP-Violating Phase in B[superscript 0] [J over [superscript +] [superscript-]] Decays and Limits on Penguin Effects. The MIT Faculty has made this article openly available. Please share how this access benefits you. Your story matters. Measurement of the CP-violating phase β in B 0 → J /ψπ + π − decays and limits on penguin effects . LHCb Collaboration a r t i c l e i n f o a b s t r a c t Time-dependent CP violation is measured in the (—) B 0 → J /ψπ + π − channel for each π + π − resonant final state using data collected with an integrated luminosity of 3.0 fb −1 in pp collisions using the LHCb detector. The final state with the largest rate, J /ψρ 0 (770), is used to measure the CP-violating angle 2β eff to be (41.7 ± 9.6 +2.8 −6.3) •. This result can be used to limit the size of penguin amplitude contributions to CP violation measurements in, for example, (—) B 0 s → J /ψφ decays. Assuming approximate SU(3) flavour symmetry and neglecting higher order diagrams, the shift in the CP-violating phase φ s is limited to be within the interval [−1.05 • , +1.18 • ] at 95% confidence level. Changes to the limit due to SU(3) symmetry breaking effects are also discussed. Measurements of CP violation in neutral B meson decays are used either to search for physics beyond the Standard Model (SM) [1] or set limits on combinations of Cabibbo–Kobayashi–Maskawa couplings (V ij) [2]. Interpretations of the measurement of the CP-violating phase 2β via the interference of mixing and decays in the (—) B 0 → J /ψ K 0 S channel, and the phase φ s in (—) B 0 s → J /ψφ and J /ψπ + π − decays, 1 are made assuming that the decays are dominated by tree-level processes. However, penguin processes are also possible, and they may have amplitudes large enough to influence the results. Here we use (—) B 0 → J /ψπ + π − decays to set limits on possible changes due to penguin contributions. This mode has both tree and penguin diagrams, as shown in Fig. 1. Theoretical models, to be discussed later, predict that the ratio of penguin to tree amplitudes is greatly enhanced in this decay relative to (—) …
A PPBACS : A N A PPLICATION B EHAVIOR A NALYSIS AND C LASSIFICATION S YSTEM

Number and complicacy of malware attack has increased multiple folds in recent times. Informed Internet users generally keep their computer protected but get confused when it comes to execute the untrusted applications. In such cases users may fall prey to malicious applications. There are malware behavior analyzers available but leave report analysis to the user. Common users are not trained to understand and analyze these reports, and generally expect direct recommendation whether to execute this application on their computer. This research paper tries to analyze behavior and help the common users and analysts to quickly classify an application as safe or malicious.
Fibromyalgia Patients Had Normal Distraction Related Pain Inhibition but Cognitive Impairment Reflected in Caudate Nucleus and Hippocampus during the Stroop Color Word Test

The mechanisms causing cognitive problems in chronic pain patients are not well understood. We used the Stroop color word task (SCWT) to investigate distraction-induced analgesia, cognitive performance, and cerebral activation patterns in 29 fibromyalgia (FM) patients (mean age 49.8 years, range 25–64 years) and 31 healthy controls (HC) (mean age 46.3 years, range 20–63 years). In the first study, SCWT was used to investigate distraction-induced analgesia in FM patients. Two versions of the task were applied, one with only congruent color-word images and one with incongruent images. Pressure pain thresholds were assessed using a pressure algometer before, during, and following SCWT. In the second study, reaction times (RTs) were assessed and functional magnetic resonance imaging (fMRI) was used to investigate cerebral activation patterns in FM patients and HC during the SCWT. An event-related task mixing incongruent and congruent images was used. In study one, we found reduced pressure pain sensitivity during SCWT in both groups alike and no statistically significant differences were seen between the incongruent and congruent conditions. The study two revealed longer RTs during the incongruent compared to the congruent condition in both groups. FM patients had longer RTs than HC in both conditions. Furthermore, we found a significant interaction between group and congruency; that is, the group differences in RTs were more pronounced during the incongruent condition. This was reflected in a reduced activation of the caudate nucleus, lingual gyrus, temporal areas, and the hippocampus in FM patients compared to HC. In conclusion, we found normal pain inhibition during SWTC in FM patients. The cognitive difficulties seen in FM patients, reflected in longer RTs, were related to reduced activation of the caudate nucleus and hippocampus during incongruent SCWT, which most likely affected the mechanisms of cognitive learning in FM patients.
A Node Splitting Neural Network with Integer Inputs and Application to a Pattern Recognition Problem in Mobile Radio Communications I. Node Splitting Network for Integer Values

A node splitting network that classiies binary patterns by Hamming distance has been presented in 5]. There it has been shown that the node splitting training algorithm can produce a network with much fewer connections than Lippmann's Hamming net 9]. Now this network (NOSDIC) has been further developed to process integer values. For a pattern recognition problem in mobile radio communications traces of quantized signal levels have been used as input to the NOSDIC network. In this application the new version taking integer input vectors has resulted in a much smaller and more eecient network. The Node Splitting Distance Classifying Network (NOSDIC) originally designed for binary patterns 5] has been extended to take integer input values. Basically, the network consists of two layers of neurons whose number grows during training. In the rst layer, neurons take their input from selected pattern components and partially compute the distances between the test pattern and all trained (exemplar) patterns. The outputs of the rst layer are combined by summing nodes in the second layer to give the total distances. Classiication is achieved by nding the minimum distance, which may be implemented by decrementing devices 3] or a recurrent network 9]. The neuron model applied here is a summing node without threshold and saturation. Yet the rst layer nodes do not have a linear transfer function, because each input connection computes an absolute diierence, rather than a dot product as in classical neural network models. The current network has been innuenced by weightless neural systems, some of which react to pattern overlap (WISARD 2]) or classify binary patterns by Hamming distance, see 7] and in particular the Generalizing Random Access Memory, GRAM 1]. The computation of vector distances is an alternative to the notion of vector similarity based on dot products as in the McCulloch-Pitts neuron model 13] and has been used for a neuron model before 10]. The neuron function used here is: d n n = X i je i ? p i j n (1) where p i are input pattern components, e i refers to the exemplar pattern, and d n n relates to the n th order vector distance d n by the n th power. Because of the linear sum in (1) the computation of the distances between patterns can be distributed over many nodes. Taking the n th root may be omitted for comparison of distances, because …
User-in-a-context: A blueprint for context-aware identification

In human history, the dependency on secret phrases - passwords - known to only a selected few in a group has mostly ensured that only those are authorised to access certain resources or information. However, such passwords have also spelled disasters when compromised. Beyond passwords, multi-factor authentication requires the knowledge of or the possession of things other than a password to complete an authentication procedure. The process of uniquely identifying a user has also been achieved through biometric authentication. Any user and her actions are, however, not devoid of context; and may reflect a specific persona of the user. In this short position paper, we describe the blueprint of a generalised context-aware identification - user-in-a-context - that is based on various parameters obtained by sensing the environment and the user; and is, therefore, able to recognise as an entity a particular individual with situational awareness. While such identification can be used in authentication, identifying persona can also help devise better tailored services.
Revamped Market-Basket Analysis using In-Memory Computation framework

Data sets are growing day by day as they are being captured by information sensing devices such as mobiles, computers, wireless sensor networks, cameras, software logs, weblogs, remote sensing in various fields such as medical, engineering, science and many more. These large data sets are now called Big Data. Working with Big Data is not a common task. As this large data set has information hidden within them, researchers cannot and they have not ignored the large data set. Data mining is an interdisciplinary field in Computer Science which extracts information or the hidden patterns from data. Association rule mining and frequent itemset mining are popular data mining techniques that requires entire data to be in main memory. But large datasets does not fit into main memory. To handle this drawback, Hadoop MapReduce approach is used which has scalability and robustness features to handle large datasets. Apriori, Eclat and FP Growth are well known Frequent Itemset Mining algorithms. These algorithms are revised to work with Big Data using Hadoop MapReduce. But MapReduce framework has problems such as it stores the intermediate data in local disk. So the data needs to be accessed from the local disk which results in high latency problem. To address this issue Spark follows a general execution model that helps in in-memory computing and optimization of arbitrary operator graphs so that querying data becomes much faster when compared to the disk based engines like MapReduce. Thus the paper focuses on enhancing the performance of Frequent Itemset Mining using Apache Spark architecture and study the performance of this Revamped Market Basket Analysis based on FP-Growth by comparing it with Hadoop MapReduce implementation of Frequent Itemset Mining task, BigFIM and also with different datasets.
Web-service enabledwireless sensors in SOA environments

Enterprise applications support business activities in companies, so that they can manage complexity and be more effective. The service oriented architecture (SOA) concepts empower modern enterprises and provide them with flexibility and agility. These concepts nowadays expand towards the shop-floor activities, down to the device level. By implementing web services on the devices natively, we are able to push down at item level SOA concepts. In this work we focus on implementing web services on the SunSPOT wireless sensor nodes and coupling it with enterprise level services. The presented methods could be used as experimental platform to evaluate new SOA-based paradigm for factory automation and enterprise computing. The goal is to seamlessly integrate heterogeneous hardware on the shop floor and the business intelligence via the SOA approach.