Miracle-dz/UniFAR-FTUs huggingface dataset:
Attentive Geo-Social Group Recommendation

Social activities play an important role in people's daily life since they interact. For recommendations based on social activities, it is vital to have not only the activity information but also individuals' social relations. Thanks to the geo-social networks and widespread use of location-aware mobile devices, massive geo-social data is now readily available for exploitation by the recommendation system. In this paper, a novel group recommendation method, called attentive geo-social group recommendation, is proposed to recommend the target user with both activity locations and a group of users that may join the activities. We present an attention mechanism to model the influence of the target user $u_T$ in candidate user groups that satisfy the social constraints. It helps to retrieve the optimal user group and activity topic candidates, as well as explains the group decision-making process. Once the user group and topics are retrieved, a novel efficient spatial query algorithm SPA-DF is employed to determine the activity location under the constraints of the given user group and activity topic candidates. The proposed method is evaluated in real-world datasets and the experimental results show that the proposed model significantly outperforms baseline methods.
Correlated Feature Selection for Tweet Spam Classification using Artificial Neural Networks

Identification of spam messages is a very challenging task for social networks due to its large size and complex nature. The purpose of this paper is to undertake the analysis of spamming on Twitter. To classify spams efficiently it is necessary to first understand the features of the spam tweets as well as identify attributes of the spammer. We extract both tweet based features and user based features for our analysis and observe the correlation between these features. This step is necessary as we can reduce the training time if we combine the features that are highly correlated. To perform our analysis we use artificial neural networks and train the model to classify the tweets as spam or non-spam. Using Correlational Artificial Neural Network gives us the highest accuracy of 97.57\% when compared with four other classifiers SVM, Kernel SVM, K Nearest Neighbours and Artificial Neural Network.
Kinetic equations for sterile neutrinos from thermal fluctuations

We obtain non-linear kinetic equations for sterile neutrino occupancies and lepton minus baryon numbers by matching real time correlation functions of thermal fluctuations computed in an effective description to those computed in thermal quantum field theory. After expanding in the sterile-neutrino Yukawa couplings, the coefficients in the equations are written as real time correlation functions of Standard Model operators. Our kinetic equations are valid for an arbitrary number of sterile neutrinos of any mass spectrum. They can be used to describe, e.g., low-scale leptogenesis via neutrino oscillations, or sterile neutrino dark matter production in the Higgs phase.
Exploiting Satellite Broadcast Despite HTTPS

HTTPS enhances end-user privacy and is often preferred or enforced by over-the-top content providers, but renders inoperable all intermediate network functions operating above the transport layer, including caching, content/protocol optimization, and security filtering tools. These functions are crucial for the optimization of integrated satellite-terrestrial networks. Additionally, due to the use of end-to-end and per- session encryption keys, the advantages of a satellite's wide- area broadcasting capabilities are limited or even negated completely. This paper investigates two solutions for authorized TLS interception that involve TLS splitting. We present how these solutions can be incorporated into integrated satellite- terrestrial networks and we discuss their trade-offs in terms of deployment, performance, and privacy. Furthermore, we design a solution that leverages satellite broadcast transmission even in the presence of TLS (i.e. with the use of HTTPS) by exploiting application layer encryption in the path between the satellite terminal and the TLS server. Our findings indicate that even if no other operation than TLS splitting is performed, TLS handshake time, which involves roundtrips through possibly a Geosynchronous satellite, can be reduced by up to 94%. Moreover, by combining an application layer encryption solution with TLS splitting, broadcast transmissions can be exploited as well as proactive caching, content pushing, request aggregation, and other optimizations.
High-speed Digital Image Correlation as a Tool for 3D Motion Analysis of Mechanical Systems

The contribution deals with the use of high-speed digital image correlation in a measurement and motion analysis of relatively big objects such as robots or manipulators. Digital image correlation method is an optic non-contact technique, which can be used in a wide range of applications in experimental mechanics. This method uses two precise CCD cameras for measuring. Cameras are usually placed stereoscopically, what allows to determine displacements and deformations in 3D space. In this contribution the theoretical basis of this method as well as the practical aspects concerning high-speed measurements are contained. As an example the experimental measurement of the motion of manipulator arm is mentioned. The output of the measurement is in the form of trajectories of its investigated points and the displacements of oscillation as well.
Melt Inclusions in Minerals as a Source of Principle Petrological Information

Secondary ion mass spectrometry and electron microprobe studies demonstrated that melt inclu- sions in magnesian olivine bear evidence of the composition and formation conditions of the primary melts and their mixing products, including the initial water contents of the mantle melts. This information is partially or completely obliterated in the compositions of rocks and glasses by later processes of mixing, contamination, degassing, and crystal fractionation. The typical oceanic basalt of the Mid-Atlantic Ridge is shown to have formed through the mixing of primary melts that were derived by the critical melting of a mantle column, more than 50 km thick. The melting began in the presence of garnet and proceeded in an open system which could retain no more than 2-3 wt % melt. The mixing of the primary melts took place both in magma chambers, simultaneously with crystallization and, probably, during melt transport through the mantle. The initial concen- trations of H 2 O in the mantle magmas of suprasubduction zones were as high as 2-3 wt %, which is significantly higher than was estimated previously. No correlation was found between the concentrations of H 2 O in the pri- mary MORB magmas and those of elements with a similar incompatibility degree (La, Ce, K). This fact may indicate the continuous interaction of the melts with H 2 O-bearing CO 2 -rich fluid.
Methodologies of Cost-of-Illness Studies on Alcohol by InternationalSystematic Review and Costs Impacted by Intervention of Reduced Drinkingin Japan

Objectives: This study was aimed to analyze cost components and underlying methods of cost-of-illness (COI) studies on alcohol in Japan and overseas by international systematic review, to estimate direct and indirect costs attributable to alcohol in Japan with new data, and to estimate costs impacted by reduced drinking among high-risk drinkers in Japan. Methods: Relevant publications concerning COI studies on alcohol published during the years 2005-2014 were identified through PubMed and Embase. Google search was conducted to identify relevant studies based on references of other relevant publications. Japanese COI studies on alcohol were identified through Igaku-Chuo-Zasshi (Ichushi) database without limiting the publication year. Cost components and underlying methods were analyzed, and medical costs attributed to alcohol were calculated based on 2012 government data and alcohol-attributed fractions (AAFs), then costs impacted by reduced drinking in Japan were estimated. Results: Seven eligible studies on 7 countries including Japan met inclusion criteria. All the countries calculated direct and indirect costs associated with alcohol, while only 2 foreign countries further calculated intangible costs. Indirect and intangible costs were 2.5-4 times larger than direct costs in all countries. Medical care costs attributed to alcohol in Japan based on 2012 data and AAFs were 1.5 times higher than 25 years ago. Furthermore, decreased number of high-risk drinkers in Japan in achieving the second term goal of Health Japan 21 was estimated to save 363.1 billion yen per year. Conclusions: Despite methodological challenges of COI studies, it is still valuable to estimate direct and indirect costs attributable to alcohol in Japan, and related costs possibly saved by reduced drinking highlighted the importance of expanding brief interventions in a clinical setting in Japan.
Kriging Prediction with Isotropic Matern Correlations: Robustness and Experimental Designs

We investigate the prediction performance of the kriging predictors. We derive some non-asymptotic error bounds for the prediction error under the uniform metric and $L_p$ metrics when the spectral densities of both the true and the imposed correlation functions decay algebraically. The Matern family is a prominent class of correlation functions of this kind. We show that, when the smoothness of the imposed correlation function exceeds that of the true correlation function, the prediction error becomes more sensitive to the space-filling property of the design points. In particular, we prove that, the above kriging predictor can still reach the optimal rate of convergence, if the experimental design scheme is quasi-uniform. We also derive a lower bound of the kriging prediction error under the uniform metric and $L_p$ metrics. An accurate characterization of this error is obtained, when an oversmoothed correlation function and a space-filling design is used.
Pancharatnam-Zak phase.

The geometric phase acquired by an electron in a one-dimensional periodic lattice due to weak electric perturbation is found and referred to as the Pancharatnam-Zak phase. The underlying mathematical structure responsible for this phase is unveiled. As opposed to the well-known Zak phase, the Pancharatnam-Zak phase is a gauge invariant observable phase, and correctly characterizes the energy bands of the lattice. We demonstrate the gauge invariance of the Pancharatnam-Zak phase in two celebrated models displaying topological phases. A filled band generalization of this geometric phase is constructed and is observed to be sensitive to the Fermi-Dirac statistics of the band electrons. The measurement of the single-particle Pancharatnam-Zak phase in individual topological phases, as well as the statistical contribution in its many-particle generalization, should be accessible in various controlled quantum experiments.
The K2 M67 Study: A Curiously Young Star in an Eclipsing Binary in an Old Open Cluster

We present an analysis of a slightly eccentric (e = 0.05), partially eclipsing, long-period (P = 69.73 days) main-sequence binary system (WOCS 12009, Sanders 1247) in the benchmark old open cluster M67. Using Kepler K2 and ground-based photometry, along with a large set of new and reanalyzed spectra, we derived highly precise masses (1.111 ± 0.015 and 0.748 ± 0.005 M⊙) and radii (1.071 ± 0.008 ± 0.003 and 0.713 ± 0.019 ± 0.026 R⊙, with statistical and systematic error estimates) for the stars. The radius of the secondary star is in agreement with theory. The primary, however, is approximately 15% smaller than reasonable isochrones for the cluster predict. Our best explanation is that the primary star was produced from the merger of two stars, as this can also account for the nondetection of photospheric lithium and its higher temperature relative to other cluster main-sequence stars at the same V magnitude. To understand the dynamical characteristics (low measured rotational line broadening of the primary star and low eccentricity of the current binary orbit), we believe that the most probable (but not the only) explanation is the tidal evolution of a close binary within a primordial triple system (possibly after a period of Kozai–Lidov oscillations), leading to merger approximately 1 Gyr ago. This star appears to be a future blue straggler that is being revealed as the cluster ages and the most massive main-sequence stars die out.
Measurement of social net benefit of climate stabilization policy

To evaluate the social welfare of climate stabilization policy from perspectives of cost–benefit analysis in a optimal economic growth framework based on macroeconomic theory, the purposes of this study are to show theoretically that the equivalent variation is divisible into a public-welfare effect, an income-change effect, and changes in investment in consideration of non-market effects of temperature change on utility. Then each effect of climate stabilization policy must be measured using simulation analysis. Consequently, it is concluded that the framework that this study has adopted is theoretically consistent with traditional cost-benefit framework and can measure each effect of climate stabilization policy.
Diagnosis of Pediatric Obstructive Sleep Apnea via Face Classification with Persistent Homology and Convolutional Neural Networks

Obstructive sleep apnea is a serious condition causing a litany of health problems especially in the pediatric population. However, this chronic condition can be treated if diagnosis is possible. The gold standard for diagnosis is an overnight sleep study, which is often unobtainable by many potentially suffering from this condition. Hence, we attempt to develop a fast non-invasive diagnostic tool by training a classifier on 2D and 3D facial images of a patient to recognize facial features associated with obstructive sleep apnea. In this comparative study, we consider both persistent homology and geometric shape analysis from the field of computational topology as well as convolutional neural networks, a powerful method from deep learning whose success in image and specifically facial recognition has already been demonstrated by computer scientists.
Anther culture performance in selected high yielding indica (of Sri Lanka) and japonica rice varieties and their inter sub-specific hybrids

Abstract: The ability to improve anther culture response of some high yielding commercially grown indica rice varieties by crossing them with a high anther culture responding japonica rice variety was studied. Performance of japonica rice variety Hu lo tao, indica rice varieties Bg 90-2, Bg 379-2, Bg 94-1 and their F1 hybrids and F2 plants were investigated for callus induction and plant regeneration. Panicles were stored at 8 0C for 14 days as the cold pre-treatment and anthers were cultured in Chu's N6 medium with 5% (w/v) sucrose, 2.0 mg L-1 2,4 - dichloro phenoxy acetic acid (2,4 D) and 0.5 mg L-1 Kinetin. The cultures were kept in the dark at 28 + 2 oC for callus induction. Induced calli of 1-2 mm diameter were transferred to half strength Murashige and Skoog (MS) medium supplemented with 2.0 mg L-1 Kinetin and 0.5 mg L-1 naphthalene acetic acid (NAA). Of the parental varieties, Hu lo tao is more responsive to anther culture. F2 plants, compared to F1 hybrids and parental rice varieties, had greater callus induction frequencies and plant regeneration. Calli from F1 hybrids and F2 plants of Bg 90-2 ×Hu lo tao showed the highest green plant regeneration (63.3% and 69.7% respectively). The regeneration of F1hybrids and F2 plants were higher than in the parents. According to the results, it is possible to improve the anther culture performance of F1 hybrids and F2 plants by crossing high yielding indica rice varieties with high anther culture responding japonica varieties. Keywords: Anther culture , callus induction, indica , japonica , plant regeneration, rice. Doi: 10.4038/jnsfsr.v39i2. 3175 J.Natn. Sci.Foundation Sri Lanka 2011 39 (2): 149-154
Extracting 2D weak labels from volume labels using multiple instance learning in CT hemorrhage detection

Multiple instance learning (MIL) is a supervised learning methodology that aims to allow models to learn instance class labels from bag class labels, where a bag is defined to contain multiple instances. MIL is gaining traction for learning from weak labels but has not been widely applied to 3D medical imaging. MIL is well-suited to clinical CT acquisitions since (1) the highly anisotropic voxels hinder application of traditional 3D networks and (2) patch-based networks have limited ability to learn whole volume labels. In this work, we apply MIL with a deep convolutional neural network to identify whether clinical CT head image volumes possess one or more large hemorrhages (> 20cm3), resulting in a learned 2D model without the need for 2D slice annotations. Individual image volumes are considered separate bags, and the slices in each volume are instances. Such a framework sets the stage for incorporating information obtained in clinical reports to help train a 2D segmentation approach. Within this context, we evaluate the data requirements to enable generalization of MIL by varying the amount of training data. Our results show that a training size of at least 400 patient image volumes was needed to achieve accurate per-slice hemorrhage detection. Over a five-fold cross-validation, the leading model, which made use of the maximum number of training volumes, had an average true positive rate of 98.10%, an average true negative rate of 99.36%, and an average precision of 0.9698. The models have been made available along with source code1 to enabled continued exploration and adaption of MIL in CT neuroimaging.
Active particles as mobile microelectrodes for selective bacteria electroporation and transport

Active particles as mobile microelectrodes for selective bacteria trapping and releasing, transport, and electroporation. Self-propelling micromotors are emerging as a promising micro- and nanoscale tool for single-cell analysis. We have recently shown that the field gradients necessary to manipulate matter via dielectrophoresis can be induced at the surface of a polarizable active (“self-propelling”) metallodielectric Janus particle (JP) under an externally applied electric field, acting essentially as a mobile floating microelectrode. Here, we successfully demonstrated that the application of an external electric field can singularly trap and transport bacteria and can selectively electroporate the trapped bacteria. Selective electroporation, enabled by the local intensification of the electric field induced by the JP, was obtained under both continuous alternating current and pulsed signal conditions. This approach is generic and applicable to bacteria and JP, as well as a wide range of cell types and micromotor designs. Hence, it constitutes an important and novel experimental tool for single-cell analysis and targeted delivery.
Parents and/or young males’ beliefs, attitudes and opinions regarding male HPV Vaccine: a systematic review

Objectives: To measure the acceptability, beliefs and attitudes on the Human papillomavirus (HPV) vaccine among adolescents and their parents. Methods: Relevant questionnaire-based articles, published in peer-reviewed journals, were retrieved from Medline (through Pubmed and EBSCO) and the Cumulative Index to Nursing and Allied Health Literature (CINAHL) databases. The quality of shortlisted articles was assessed using the CEBMa checklist. Data were extracted and systematically reviewed. Results: Twelve studies (6529 survey participants) were included in the final analysis. The quality of included studies was high (most of the parameters were satisfied according to the CEBMa tool). Of the participants, 187 (2.86 %) were adolescent males, and the rest 6342 (97.14%) were parents of adolescent males. The knowledge of disease severity and benefits of vaccination was low among parents in all studies. The willingness to vaccinate adolescent males was higher among highly educated parents, those with a previously HPV vaccinated female children, and those with a history of recommendation from a physician. Conclusion: A significant gap between actual vaccine uptake and willingness to vaccinate male children was noted in all included studies, mostly due to lack of recommendation by the treating physician. The primary motive to vaccinate sons was the understanding of vaccine benefits and willingness to protect the future partners.
Learning Motion Priors for Efficient Video Object Detection

Convolution neural networks have achieved great progress on image object detection task. However, it is not trivial to transfer existing image object detection methods to the video domain since most of them are designed specifically for the image domain. Directly applying an image detector cannot achieve optimal results because of the lack of temporal information, which is vital for the video domain. Recently, image-level flow warping has been proposed to propagate features across different frames, aiming at achieving a better trade-off between accuracy and efficiency. However, the gap between image-level optical flow with high-level features can hinder the spatial propagation accuracy. To achieve a better trade-off between accuracy and efficiency, in this paper, we propose to learn motion priors for efficient video object detection. We first initialize some motion priors for each location and then use them to propagate features across frames. At the same time, Motion priors are updated adaptively to find better spatial correspondences. Without bells and whistles, the proposed framework achieves state-of-the-art performance on the ImageNet VID dataset with real-time speed.
Devices (CEDs) to Hands- and Weapon-Based Tactics Police Use of Force and Officer Injuries: Comparing Conducted Energy

The widespread adoption of conducted energy devices (CEDs) across American police departments over the last decade has been mired in public controversy. It is generally accepted, from a police perspective, that CEDs are safer for officers who can use the weapon at a greater distance, avoiding much of the harm associated with close physical struggles with citizens. Research has generally supported the notion that aggregate levels of officer injuries are reduced following the implementation of CEDs. Unfortunately, multivariate examinations that, in varying degrees, have attempted to compare CED applications to other forms of force (while controlling for rival causal factors) have yet to produce the same consistent results as the preand post-CED adoption studies. The current research adds to recent multivariate inquiries by using data collected as part of a national multiagency use of force project to assess the independent effect of CEDs on officer injuries. Based on a series of multivariate models, our results generally find evidence of increased benefits (i.e., lower probability of officer injury) of CEDs when used by themselves. By contrast, in some instances when CEDs were used in combination with other forms of force, there was an increased probability of officer injury. The implications of these findings for police researchers and practitioners are considered. Articles by Paul Brennan on October 15, 2012 pqx.sagepub. com Downloaded from 116 Policy Quarterly 15(2)