Miracle-dz/UniFAR-FTUs huggingface dataset:
+ Image features Text features × × Softmax

Hashtags can greatly facilitate content navigation and improve user engagement in social media. Meaningful as it might be, recommending hashtags for photo sharing services such as Instagram and Pinterest remains a daunting task due to the following two reasons. On the endogenous side, posts in photo sharing services often contain both images and text, which are likely to be correlated with each other. Therefore, it is crucial to coherently model both image and text as well as the interaction between them. On the exogenous side, hashtags are generated by users and different users might come up with different tags for similar posts, due to their different preference and/or community effect. Therefore, it is highly desirable to characterize the users’ tagging habits. In this paper, we propose an integral and effective hashtag recommendation approach for photo sharing services. In particular, the proposed approach considers both the endogenous and exogenous effects by a content modeling module and a habit modeling module, respectively. For the content modeling module, we adopt the parallel co-attention mechanism to coherently model both image and text as well as the interaction between them; for the habit modeling module, we introduce an external memory unit to characterize the historical tagging habit of each user. The overall hashtag recommendations are generated on the basis of both the post features from the content modeling module and the habit influences from the habit modeling module. We evaluate the proposed approach on real Instagram data. The experimental results demonstrate that the proposed approach significantly outperforms the state-of-theart methods in terms of recommendation accuracy, and that both content modeling and habit modeling contribute significantly to the overall recommendation accuracy.
Contemporaneous IUE, EUVE, and High-Energy Observations of 3C 273

We present the results of our 1994 January and 1995 January observations of the quasar 3C 273 obtained with the International Ultraviolet Explorer (IUE) and the Extreme-Ultraviolet Explorer (EUVE). These observations were part of a large multiwavelength campaign to observe 3C 273 from radio through γ-rays. Our 1995 January photometric observations with the EUVE Lexan/B Deep Survey (DS) instrument indicate strong evidence for variability, at a 99% confidence level, during the 12 day observing period. We have utilized ROSAT PSPC soft X-ray power-law models to correlate with EUVE count rates. Besides variations in the normalization level between both observations, our EUV count rates are consistent with a simple power-law model with spectral index α ~ 1.77 (Fν ~ ν-α) that can be extrapolated from the soft X-rays to the EUV range. The active galactic nucleus 3C 273 is an important blazar to study because in our picture it reveals the presence of both disk and relativistic beam spectral contributions.
A local defect resonance for linear and nonlinear ultrasonic thermography

An efficient wave-defect interaction is the key to a high thermal response of flaws in ultrasonic thermography. To selectively enhance defect vibrations a concept of local defect resonance is developed and applied to ultrasonic activation of defects. The frequency match between the defect resonance frequency and the probing ultrasonic wave results in a substantial rise of a local defect temperature. The defect resonance is accompanied by depletion of the excitation frequency vibration due to nonlinear frequency conversion to higher harmonics. The local generation of higher frequency components provides a high thermal defect response in such an acoustically nonlinear thermography mode.
Characterisation of atmospheric aerosol by SEM-EDX and Ion-chromatography techniques for eastern Indo-Gangetic plain location, Varanasi, India

Atmospheric aerosol consists of both natural and anthropogenic origin. Studies have shown that continuous exposure to these particles is associated with a high percentage of death from respiratory and cardiovascular disease. In the present study, we have first time used both SEM-EDX analysis as well as chemical analysis to understand the differences in morphology and elemental composition of aerosols sample from a suburban clean and green area of Banaras Hindu University campus and some much polluted urban areas of the Varanasi city situated in the eastern Indo-Gangetic plain. The analysis was done by using scanning electron microscope (SEM) coupled with energy dispersive X-ray microanalyzer (EDX) and ionchromatography (IC). Analyses show that C, Ca, Na, S, Si, Al have dominated the samples
Component structure of the configuration model: Barely supercritical case

We study near‐critical behavior in the configuration model. Let Dn be the degree of a random vertex and νn=E[Dn(Dn−1)]/E[Dn] ; we consider the barely supercritical regime, where νn→1 as n→∞, but νn−1≫n−1/3(E[Dn3])2/3 . Let Dn∗ denote the size‐biased version of Dn. We prove that there is a unique giant component of size nρnEDn(1+o(1)) , where ρn denotes the survival probability of a branching process with offspring distribution Dn∗−1 . This extends earlier results of Janson and Luczak, as well as those of Janson, Luczak, Windridge, and House, to the case where the third moment of Dn is unbounded. We further study the size of the largest component in the critical regime, where νn−1=O(n−1/3(EDn3)2/3) , extending and complementing results of Hatami and Molloy.
A New Support Vector Machine Optimized by Simulated Annealing for Global Optimization

SA-SVM model was proposed in which parameters were optimized by simulated annealing. Parameter  (the kernel function) and C (the error discipline) are the key factors to the precision of SVM. Simulated annealing was used to optimize the key parameters of SVM to make enhancement on the forecasting effect of SVM. By applying this proposed model for several function optimizations, results of which demonstrate the improvement of SA-SVM on the high model accuracy in the optimization searching, and it can overcome the blindness of the model parameters.
HAT-P-30b: A TRANSITING HOT JUPITER ON A HIGHLY OBLIQUE ORBIT

We report the discovery of HAT-P-30b, a transiting exoplanet orbiting the V = 10.419 dwarf star GSC 0208-00722. The planet has a period P = 2.810595 ± 0.000005 days, transit epoch Tc = 2455456.46561 ± 0.00037 (BJD), and transit duration 0.0887 ± 0.0015 days. The host star has a mass of 1.24 ± 0.04 M☉, radius of 1.21 ± 0.05 R☉, effective temperature of 6304 ± 88 K, and metallicity [Fe/H] = +0.13 ± 0.08. The planetary companion has a mass of 0.711 ± 0.028 MJ and radius of 1.340 ± 0.065 RJ yielding a mean density of 0.37 ± 0.05 g cm−3. We also present radial velocity measurements that were obtained throughout a transit that exhibit the Rossiter–McLaughlin effect. By modeling this effect, we measure an angle of λ = 73. °5 ± 9. °0 between the sky projections of the planet's orbit normal and the star's spin axis. HAT-P-30b represents another example of a close-in planet on a highly tilted orbit, and conforms to the previously noted pattern that tilted orbits are more common around stars with Teff⋆ ≳ 6250 K.
Analysis of Student Demographic Information Using Data Mining classification with Decision Tree

The purpose of this study was to process Student Demographic Information using data mining analysis using decision tree technique. This study retrieved data from 50 students with visual data attributes verbal preferences, self-efficacy, gender, and interest. This study uses orange data mining to process data with decision tree technique. The study found that decision node as the best predictors are visual preferences, in which visuals had a 76% of 50 attributes. Female students had a 100% distribution as a visual preference, while male had 68.4% of the distribution as a visual preference. The results found that the attributes that predictor were visual preferences. The decision tree gets the rule from the root node to the leaf nodes as many as four rules are R1, R2, R3, and R4.
Acquisition and Maintenance of Enterotoxin Plasmids in Wild-type Strains of Escherichia coli

Enterotoxigenic strains of Escherichia coli (ETEC) may produce a heat-labile enterotoxin (LT), a heat-stable enterotoxin (ST) or both enterotoxins. Certain serogroups are represented more frequently than others in ETEC isolated from humans. The transfer of three plasmids encoding enterotoxin production (Ent) to 22 non-toxigenic E. coli strains of many different 0 : H serotypes was studied. The Ent plasmids encoded ST (TP276), or LT (TP277), or ST + LT (TP214), and all carried antibiotic-resistance determinants. Twenty-one recipient strains acquired TP2 14, 18 acquired TP277 and 14 acquired TP276. Strains of those serotypes to which ETEC in diarrhoeal studies commonly belong neither acquired nor maintained Ent plasmids with a higher frequency than strains of those serotypes to which ETEC rarely belong. The recipient strains, with one exception, all expressed ST, or LT, or ST and LT, when they had acquired the appropriate plasmid ; a non-motile strain belonging to 0 serogroup 88 expressed LT but failed to express ST when it acquired TP214 or TP277.
Analysis of Supervised Feature Selection Techniques on Animal Husbandry Dataset

Data mining techniques have become an obvious need of today’s high-dimensional animal industry data. In the last decade almost every aspect of animal related activities are being captured and stored either in local or central data repositories. Due to complex animal traits such as efficiency, growth, health, stress, behavior and adaptation, data mining is an area of challenge which can be optimally performed only with reduced number of relevant features. In this paper, a comparative analysis of various feature selection techniques based on some performance measuring parameter is presented using animal husbandry dataset. This research work finds J48 classifier to perform better in comparison to other traditional classification approaches.
RP-HPLC METHOD DEVELOPMENT AND VALIDATION FOR THE SIMULTANEOUS QUANTITATIVE ESTIMATION OF PREGABALIN, MECOBALAMIN AND ALPHA LIPOIC ACID IN CAPSULES

Objective: To develop a simple, precise, accurate, linear and rapid Reverse Phase High Performance Liquid Chromatographic (RP-HPLC) method for the simultaneous quantitative estimation of Pregabalin 75mg, Mecobalamin 750µg and Alpha lipoic acid 100mg in capsules as per ICH guidelines. Methods: The optimized method uses a reverse phase C18 column, Enable Make C18G (250 X4.6mm, 5µm), mobile phase of a mixture of potassium dihydrogen orthophosphate buffer (20mM, pH adjusted to 6 using 0.1N potassium hydroxide solution), methanol and acetonitrile in ratio of 75:10:15v/v, flow rate of 1.2 ml/min and a detection wavelength of 210 nm using a UV detector. Results: The developed method resulted in pregabalin eluting at 2.6 min, mecobalamin eluting at 6.4 min and alpha lipoic acid eluting at 11.3 min. The method exhibited linearity over the range of 187.5-750µg/ml, 1.87-7. 5µg/ml and 250-1000µg/ml for pregabalin, mecobalamin and alpha lipoic acid respectively. The method precision is exemplified by relative standard deviations of 0.84% for pregabalin, 1.07% for mecobalamin and 0.85% for alpha lipoic acid. Accuracy studies revealed % mean recoveries during spiking experiments between 98 and 102. The limit of detection was obtained as 3µg/ml for pregabalin, 800ng/ml for mecobalamin and 500ng/ml for alpha lipoic acid, while the limit of quantitation was obtained as 6 µg/ml for pregabalin, 2µg/ml for meocobalamin and 1. 5µg/ml for alpha lipoic acid. Conclusion: A simple, precise, accurate, linear and rapid RP-HPLC method was developed and validated as per ICH guidelines and hence can be applicable in routine analysis for tablets in various pharmaceutical industries.
Moral hypocrisy and the hedonic shift: A goal-framing approach

The most investigated form of moral hypocrisy is pragmatic hypocrisy in which people fake moral commitment for their own advantage. Yet there is also a different form of hypocrisy in which people take a moral stance with regard to norms they endorse without thereby also expressing a commitment to act morally. Rather they do it in order to feel good. We call this hedonic moral hypocrisy. In our research, we posit that this kind of hypocrisy comes about when people’s overarching goals are shifted in a hedonic direction, that is, in the direction of focusing on the way one feels, rather than on moral obligation. Hedonic shifts come about by cues in the environment. People are sometimes sincere when expressing a moral stance (i.e. they mean it and also act on it), and sometimes, when they are subject to a hedonic shift, they express a moral stance just to make them feel good. This also implies that they then decline to do things that make them feel bad, such as behaving morally when it takes unrewarded effort to do so. In two experimental studies, we find that there is such a thing as hedonic moral hypocrisy and that it is indeed brought about by hedonic shifts from cues in the environment. This seriously undermines the meaning of a normative consensus for norm conformity. Seemingly, for norm conformity without close social control, it is not enough that people endorse the same norms, they also have to be exposed to situational cues that counteract hedonic shifts. In the discussion, it is suggested that societal arrangements that foster the focus on the way one feels and nurture a chronic wish to make oneself feel better (for example, in the fun direction through advertisements and entertainment opportunities, or in the fear direction by populist politicians, social media, economic uncertainties, crises, or wars and displacements) are likely to increase hedonic hypocrisy in society.
Sidewalk delivery robot navigation: a pedestrian-based approach

In this paper, we propose a novel navigation system for mobile robots in pedestrian-rich sidewalk environments. Sidewalks are unique in that the pedestrian-shared space has characteristics of both roads and indoor spaces. Like vehicles on roads, pedestrian movement often manifests as flows in opposing directions. On the other hand, pedestrians also form crowds and can exhibit much more random movements than vehicles. Classical algorithms are insufficient for safe navigation around pedestrians and remaining on the sidewalk space. Thus, our approach takes advantage of natural human motion to allow a robot to adapt to sidewalk navigation in a safe and socially-compliant manner. We developed a group surfing method which aims to imitate the optimal pedestrian group for bringing the robot closer to its goal. For pedestriansparse environments, we propose a sidewalk edge detection and following method. Underlying these two navigation methods, the collision avoidance scheme is human-aware. Components of the navigation stack are demonstrated in simulation and an integrated simulation and real-world experiment are discussed.
SCIAMACHY WFM-DOAS X CO 2 : reduction of scattering related errors

Abstract. Global observations of column-averaged dry air mole fractions of carbon dioxide (CO2), denoted by XCO2 , retrieved from SCIAMACHY on-board ENVISAT can provide important and missing global information on the distribution and magnitude of regional CO2 surface fluxes. This application has challenging precision and accuracy requirements. In a previous publication (Heymann et al., 2012), it has been shown by analysing seven years of SCIAMACHY WFM-DOAS XCO2 (WFMDv2.1) that unaccounted thin cirrus clouds can result in significant errors. In order to enhance the quality of the SCIAMACHY XCO2 data product, we have developed a new version of the retrieval algorithm (WFMDv2.2), which is described in this manuscript. It is based on an improved cloud filtering and correction method using the 1.4 μm strong water vapour absorption and 0.76 μm O2-A bands. The new algorithm has been used to generate a SCIAMACHY XCO2 data set covering the years 2003–2009. The new XCO2 data set has been validated using ground-based observations from the Total Carbon Column Observing Network (TCCON). The validation shows a significant improvement of the new product (v2.2) in comparison to the previous product (v2.1). For example, the standard deviation of the difference to TCCON at Darwin, Australia, has been reduced from 4 ppm to 2 ppm. The monthly regional-scale scatter of the data (defined as the mean intra-monthly standard deviation of all quality filtered XCO2 retrievals within a radius of 350 km around various locations) has also been reduced, typically by a factor of about 1.5. Overall, the validation of the new WFMDv2.2 XCO2 data product can be summarised by a single measurement precision of 3.8 ppm, an estimated regional-scale (radius of 500 km) precision of monthly averages of 1.6 ppm and an estimated regional-scale relative accuracy of 0.8 ppm. In addition to the comparison with the limited number of TCCON sites, we also present a comparison with NOAA's global CO2 modelling and assimilation system CarbonTracker. This comparison also shows significant improvements especially over the Southern Hemisphere.
Topological optimization design for additive manufacturing, taking into account flexion and vibrations during machining post processing operations

This article focuses on including into the topological optimization method, all the mechanical stresses applied during the part lifetime and especially during machining phase. Thus, in addition to the part technical specifications, we consider static and vibratory forces during machining, and also forces during mounting and unmounting in the machine tool and then in the aircraft. Results show that taking into account handling and machining forces, static and vibratory, strongly impact topological optimization, thus shapes and weight, and should be considered during the early stage of the design in order to optimize the additive manufactured parts costs.
Theoretical study of Ga-based nanowires and the interaction of Ga with single-wall carbon nanotubes

Gallium displays physical properties which can make it a potential element to produce metallic nanowires and high-conducting interconnects in nanoelectronics. Using first-principles pseudopotential plane method we showed that $\mathrm{Ga}$ can form stable metallic linear and zigzag monatomic chain structures. The interaction between individual $\mathrm{Ga}$ atom and single-wall carbon nanotube (SWNT) leads to a chemisorption bond involving charge transfer. Doping of SWNT with $\mathrm{Ga}$ atom gives rise to donor states. Owing to a significant interaction between individual $\mathrm{Ga}$ atom and SWNT, continuous $\mathrm{Ga}$ coverage of the tube can be achieved. $\mathrm{Ga}$ nanowires produced by the coating of carbon nanotube templates are found to be stable and high conducting.
Chapter 0 Magnetoelastic Energy Harvesting : Modeling and Experiments

Magnetoelastic materials belong to the wide category of smart materials because of their capability of coupling mechanical quantities (force, strain) to magnetic ones (field, induction) and viceversa. Recently, they have received a lot of interest for actuating and sensing purposes. Moreover, in the general framework of recovering some environmental energy, this kind of smart materials have been considered to recover the mechanical energy of vibrations [51].
Reverse DNS Geolocation

IP geolocation databases map IP addresses to their geographical locations. These databases are used in a variety of online services to serve local content to users. Here we present methods for extracting locations from the reverse DNS hostnames assigned to IP addresses. We summarize a machine learning based approach which, given a hostname, aims to extract and rank potential location candidates, which can then potentially be fused with other geolocation signals. We show that this approach significantly outperforms a state-of-the-art academic baseline, and it is competitive and complementary to commercial baselines. Since extracting locations from more than a billion reverse DNS hostnames at once poses a significant computational challenge, we develop a distributed version of our algorithm. We perform experiments on a cluster of 2,000 machines to demonstrate that our distributed implementation can scale. We show that compared to the single machine version, our distributed approach can achieve a speedup of more than 150X.
The Impact of Dynamic Retrieval Emissivity on the Microwave Surface-sensitive Channels over Land

In addition to the traditionally complex land surface emissivity models, it is possible to direct real-time retrieve emissivity over land surface in a large-scaled temporal and spatial region from satellite microwave observations. We investigated the performance of the real-time dynamic retrieval emissivity against the monthly averaged emissivity atlas. As indicated by the results, the dynamic retrieval algorithm can obviously reduce the first guess departure of low-level channels which are sensitive to the surface and the simulated background brightness temperatures with real-time dynamic emissivity against the observations have a better agreement over the land surface and higher correlation. Therefore, the dynamic retrieval emissivity algorithm has the potential to improve the effect of satellite data assimilation.
Title : Three-year change in diet quality and associated changes in BMI among schoolchildren 1 living in socioeconomically disadvantaged neighbourhoods

1 Findings from research assessing the influence of dietary factors on child obesity have been 2 equivocal. We aimed to test the hypothesis that a positive change in diet quality is associated with 3 favourable changes in BMI z-scores in schoolchildren from low socio-economic backgrounds; and 4 to examine whether this effect is modified by BMI category at baseline. This study utilized data 5 from a subsample (n=216) of the Resilience for Eating and Activity Despite Inequality (READI) 6 study, a longitudinal cohort with data collected in 2007-08 (T1) and 2010-11 (T2) in socio7 economically disadvantaged women and children (5-12 years at T1). Dietary data was collected 8 using a food frequency questionnaire, and diet quality index (DQI) scores derived at both times. 9 Objective measures of weight, height and physical activity (accelerometers) were included. The 10 other variables were reported in questionnaires. We examined the association between change in 11 DQI and change in zBMI, with linear regression analysis adjusted for physical activity, screen 12 sedentary behaviour and maternal education, both in the whole sample, and stratified by overweight 13 status at baseline. After accounting for potential covariates, change in diet quality was inversely 14 associated with change in zBMI only in children who were overweight at baseline (P=0.035), thus 15 supporting the hypothesis that improvement in diet quality is associated with a concurrent 16 improvement in zBMI among already overweight children, but not those of normal BMI status. The 17 identification of modifiable behaviours such as diet quality that affect zBMI longitudinally is 18 valuable to inform future weight gain prevention interventions in vulnerable groups. 19 20 21