Miracle-dz/UniFAR-FTUs huggingface dataset:
Cross-cultural adaptation and validity evidence of the Brazilian version of the State Mindfulness Scale for Physical Activity ( SMS-PA )

The objective of this study was to perform a cross-cultural adaptation to the Brazilian Portuguese language and to estimate validity evidence of the State Mindfulness Scale for Physical Activity (SMS-PA) in the Brazilian context. The sample consisted of 288 subjects participating in physical and sports activities (mean age: 21.1±4.8; 56.6% women). Exploratory and Confirmatory Factor Analyzes were conducted to assess the internal structure and the invariance of the factorial model between men and women. Cronbach’s alpha was employed to assess internal consistency, and the Pearson correlation to assess the pattern of correlation between the SMS-PA and the intrinsic motivation/amotivation measures, and between the SMS-PA and the Reason for Exercise scale. The results showed adequacy of the bi-factor structure with two specific factors (mental and body mindfulness), and one general factor (state mindfulness for physical activity), as per the theoretical hypothesis (WLSMV χ2= 95.951; df= 33; χ2/df= 2.91; CFI= .997; TLI= .962; RMSEA= .072 CI-90% .053-.091); desirable internal consistency indices for all factors (.882 ≤ α ≤ .887), and invariance of the SMS-PA’s internal structure to assess men and women. Moreover, positive correlation of the SMS-PA was observed with intrinsic motivation and internal reasons for exercise, with negative correlations for amotivation, as per the theoretical hypothesis. It can be concluded from this study that the Brazilian version of the SMS-PA is a suitable measurement tool for assessing state mindfulness in Brazilians who practice physical activities and sports. Key-words: sport psychology, psychometric, exercise, intrinsic motivation, bi-factor model.
Core-Periphery Model of Urban Economic Growth : Empirical Evidence from Chinese City-Level Data ( 1990-2006 )

The geographic nature and openness of China since 1990s make it a feasible application of the Core-Periphery (CP) model, which has hardly explained urban systems in existing studies. Using Chinese citylevel data from 1990 to 2006, this paper estimates the impact of spatial interactions in China’s urban system on urban economic growth. Our results verify the nonlinearity of the CP Model of urban system, present agglomeration shadow in Chinese urban economies. We also find “border effect” of administrative boundaries among Chinese provinces, which prevents urban economic activities from being absorbed by big cities in other provinces, while limiting inter-city agglomeration.
Degradation of front-back spectral cues induced by tactical communication and protective systems

Tactical communication and protective systems (TCAPS) correctly protect the listener's ears from hazardous sounds and preserve intelligibility, thus allowing low-level speech communication. Our actual problematic deals with the conservation of the sound localization capability when wearing TCAPS. A previous subjective experiment, in which listeners were asked to localize sound sources in the horizontal plane with and without acoustically transparent earmu s, highlighted that wearing this hearing protection signi cantly degraded the listeners' localization capability. This degradation was mainly caused by front-back confusions. It has therefore been concluded that the hearing protector altered the spectral cues used in open ear condition for the resolution of front-back ambiguities. In order to characterize the TCAPS-induced degradation of the spectral cues, directional transfer functions (DTFs) have been measured in the horizontal plane on an arti cial head with and without di erent TCAPS. DTFs are rst averaged in each quadrant and the number of measurement positions which are needed in each quadrant is discussed. Front-back spectral cues are then de ned, separately for ipsilateral and contralateral side, as the di erence between front and back mean DTF. Results show that wearing TCAPS a ects not only ipsilateral but contralateral spectral cues. A quantitative study con rms that ipsilateral cues are preponderant for the resolution of front-back ambiguities in open ear condition. Finally, an index characterizing the alteration of the spectral cues allows the ranking of the di erent TCAPS according to how they induce degradation of the sound localization
BGP hijacking classification

Recent reports show that BGP hijacking has increased substantially. BGP hijacking allows malicious ASes to obtain IP prefixes for spamming as well as intercepting or blackholing traffic. While systems to prevent hijacks are hard to deploy and require the cooperation of many other organizations, techniques to detect hijacks have been a popular area of study. In this paper, we classify detected hijack events in order to document BGP detectors output and understand the nature of reported events. We introduce four categories of BGP hijack: typos, prepending mistakes, origin changes, and forged AS paths. We leverage AS hegemony – a measure of dependency in AS relationship – to identify forged AS paths in a fast and efficient way. Besides, we utilize heuristic approaches to find common operators’ mistakes such as typos and AS prepending mistakes. The proposed approach classifies our collected ground truth into four categories with 95.71% accuracy. We characterize publicly reported alarms (e.g. BGPMon) with our trained classifier and find 4%, 1%, and 2% of typos, prepend mistakes, and BGP hijacking with a forged AS path, respectively.
Effects of bike lane features on cyclists ’ exposure to black carbon and ultrafine particles

Cyclists might experience increased exposure to air pollution due to their active travel mode and to the proximity to traffic. Several local factors, like meteorology, road and traffic features, and bike lanes features, affect cyclists’ exposure. This paper investigates the effect of the features of the bike lanes on cyclists’ exposure to airborne fine and ultrafine particulate matter and black carbon in the mid-sized city of Piacenza, located in the middle of the Po Valley, Northern Italy. Monitoring campaigns were performed by means of portable instruments along a 40-min urban bike route with bike lanes, characterized by different distances from the traffic source (on-road cycle lane, separated cycle lane, green cycle path), during morning and evening workday rush hours. The proximity to traffic significantly affected cyclists’ exposure to UFP and BC: exposure concentrations measured for the separated lane and for the green path were 1-2 times and 2-4 times lower for the on-road lane. Conversely, exposure concentrations to PM10, PM2.5 and PM1 particle mass were not influenced by traffic proximity, without any significant variation between on-road cycle lane, separated lane or green cycle path.
rtocarpus lakoocha roxb . : An untapped bioresource of resveratrol rom North East India , its extractive separation and antioxidant ctivity irok

Now a day, the demand of naturally occurring biomolecules in the present society and global market is well known. Artocarpus lakoocha Roxb. is an untapped bioresource of resveratrol, a phenolic compound that is used for its anti-aging, cardioprotective and anticancer activities among many others, from North East India. This work evaluates the effect of parameters such as solvent, time, temperature, speed of agitation, solid to solvent ratio and particle size on the extraction yield of resveratrol from this bioresource. Under the optimized conditions of the process parameters stated above, 85,000 mg/kg resveratrol could be extracted from 90,000 mg/kg Artocarpus lakoocha Roxb. within 7 h using ethanol as the solvent. Extracrtocarpus lakoocha Roxb. olvent to solid ratio iffusion inetic model cavenging activity tion kinetics was estimated using two different kinetic models. The results showed that the extraction process was dependent on diffusional effect inside the sample. Thermodynamic parameters for extraction process were determined and the process was found to be spontaneous. The compound so extracted showed a significant antioxidant activity with IC50 value of 53.24 g/ml. Thus the extracted resveratrol can be used as therapeutic agent. © 2016 Elsevier B.V. All rights reserved.
CDNN-CRNN JOINED MODEL FOR ACOUSTIC SCENE CLASSIFICATION Technical Report

This work proposes a deep learning framework applied for Acoustic Scene Classification (ASC), targeting DCASE2019 task 1A. In general, the front-end process shows a combination of three types of spectrograms: Gammatone (GAM), log-Mel and Constant Q Transform (CQT). The back-end classification presents a joined learning model between CDNN and CRNN. Our experiments over the development dataset of DCASE2019 challenge task 1A show a significant improvement, increasing 11.2% compared to DCASE2019 baseline of 62.5%. The Kaggle reports the classification accuracy of 74.6% when we train all development dataset.
ACCOMMODATION CHANGE DURING BYPASS ACROSS A LATE-STAGE FAN IN THE SHALLOW AUGER BASIN

ABSTRACT: Apron 1 in the Shallow Auger Fan System records the transition from ponded deposition in the lobe complex to bypass at the top of the channel complex. The lobe complex, at the base of Apron 1, exhibits characteristics typical of ponded apron deposits: it onlaps the basin margin, exhibits a concentric isopach pattern, has a lobe geometry in amplitude extraction, and is composed of continuous seismic reflections that have uniform thickness. The transition from ponded deposition to bypass is recorded with increasing gradients along the four channels in the channel complex. Healed-slope accommodation is filled as these channels aggrade at the sediment entry point. In the proximal reaches, the channels have thick levee deposits and minimal incision. Downdip, the levee deposit thickness decreases and incision increases. Each channel aggrades to a single gradient; once this gradient is achieved, the channel avulses to an area of greater accommodation. As healed-slope accommodation fills, channel gradients in the proximal reaches decrease and sinuosity increases. In the distal reaches of the channel, greater incision depths may compartmentalize the underlying ponded deposits.
Deep Defocus Map Estimation Using Domain Adaptation

In this paper, we propose the first end-to-end convolutional neural network (CNN) architecture, Defocus Map Estimation Network (DMENet), for spatially varying defocus map estimation. To train the network, we produce a novel depth-of-field (DOF) dataset, SYNDOF, where each image is synthetically blurred with a ground-truth depth map. Due to the synthetic nature of SYNDOF, the feature characteristics of images in SYNDOF can differ from those of real defocused photos. To address this gap, we use domain adaptation that transfers the features of real defocused photos into those of synthetically blurred ones. Our DMENet consists of four subnetworks: blur estimation, domain adaptation, content preservation, and sharpness calibration networks. The subnetworks are connected to each other and jointly trained with their corresponding supervisions in an end-to-end manner. Our method is evaluated on publicly available blur detection and blur estimation datasets and the results show the state-of-the-art performance.In this paper, we propose the first end-to-end convolutional neural network (CNN) architecture, Defocus Map Estimation Network (DMENet), for spatially varying defocus map estimation. To train the network, we produce a novel depth-of-field (DOF) dataset, SYNDOF, where each image is synthetically blurred with a ground-truth depth map. Due to the synthetic nature of SYNDOF, the feature characteristics of images in SYNDOF can differ from those of real defocused photos. To address this gap, we use domain adaptation that transfers the features of real defocused photos into those of synthetically blurred ones. Our DMENet consists of four subnetworks: blur estimation, domain adaptation, content preservation, and sharpness calibration networks. The subnetworks are connected to each other and jointly trained with their corresponding supervisions in an end-to-end manner. Our method is evaluated on publicly available blur detection and blur estimation datasets and the results show the state-of-the-art performance.
Investor Behavior and Stock Returns

It is common in the empirical literature to test the predictability of individual stock returns assuming that investors are all rational thinkers. We provide empirical evidence that the nding that stock returns are predictable to some degree based on past returns alone may be overstated. Correcting the investors beliefs about future stock returns for overcon dence in that the next day return will be close to a target return, especially when combined with pessimism/optimism, reverses the evidence of the predictability of individual stock returns. This evidence holds for all quantiles of the return distribution and groups of size-sorted stocks. JEL Classi cation: G12. Keywords: behavioral heuristic, random walk, subjective probability, the e¢ cient market hypothesis, weighted quantile regression. The authors gratefully acknowledge nancial support from the Humanities Research Council of Canada (SSHRC) and the York University Faculty of Liberal Arts & Professional Studies Seed Grant for Collaborative Research Initiatives, International Collaboration Grant, and Minor Research Grant. yPhD student. Department of Economics, York University, 4700 Keele St., Vari Hall 1049, Toronto, Ontario M3J1P3, Canada, Tel. : 1-416-7362100, Fax: 1-416-7365987, E-mail: orianar@yorku.ca zCorresponding author. Department of Economics, York University, 4700 Keele St., Vari Hall 1028, Toronto, Ontario M3J1P3, Canada, Tel. : 1-416-7362100 x77025, Fax: 1-416-7365987, E-mail: asemenov@yorku.ca
Paired Measures of Competence and Confidence Illuminate Impacts of Privilege on College Students

We seek to understand how the experiences of groups that differ in gender, ethnicity, and sexual orientation produce college-level educational performances that differ from the experiences of the dominant majority group. We employ two datasets: a National Database of 24,701 participants and a Paired-Measures Database with 3,323 participants. Both datasets provide demographic information, socioeconomic conditions of status as first-generation student, English as a first language, and interest in majoring in science, and competency scores on understanding science as a way of knowing obtained from the Science Literacy Concept Inventory. The Paired-Measures Database includes additional selfassessed competence ratings that enabled quantifying affective confidence. We meld the ways of knowing of ethics, numeracy, and social justice, especially the social justice concept of Othering, to interpret our data. Two of three competing hypotheses about self-assessment encourage Othering. Our data strongly support the third—that all groups are good at self-assessment and merit equal respect. Women and men are equally competent in science literacy. Women, on average, are more accurate in their self-assessments whereas men, on average, are overconfident. Those with minority sexual orientations register higher competence than the binary-sexual majority but are less confident of their competency. Minority ethnicities, on average, produce significantly lower science literacy scores. With one exception (Middle Eastern), groups produce mean self-assessed competence ratings that are remarkably accurate predictors of their mean competence scores. The three socioeconomic conditions exert significant and unequal impacts across ethnic groups, with Hispanic, Middle Eastern and Pacific Islander data providing some unique results.
EFFICIENT HIGH QUALITY VIDEO ASSESSMENT USING SALIENT FEATURES

High Definition (HD) devices requires HD-videos for the effective uses of HD devices. However, it consists of some issues such as high storage capacity, limited battery power of high definition devices, long encoding time, and high computational complexity when it comes to the transmission, broadcasting and internet traffic. Many existing techniques consists these above-mentioned issues. Therefore, there is a need of an efficient technique, which reduces unnecessary amount of space, provides high compression rate and requires low bandwidth spectrum. Therefore, in the paper we have introduced an efficient video compression technique as modified HEVC coding based on saliency features to counter these existing drawbacks. We highlight first, on extracting features on the raw data and then compressed it largely. This technique makes our model powerful and provides effective performance in terms of compression. Our experiment results proves that our model provide better efficiency in terms of average PSNR, MSE and bitrate. Our experimental results outperforms all the existing techniques in terms of saliency map detection, AUC, NSS, KLD and JSD. The average AUC, NSS and KLD value by our proposed method are 0.846, 1.702 and 0.532 respectively which is very high compare to other existing technique.
Towards a correlation of form, use and meaning of German ge-prefixed predicative participles

We argue for a split semantics of German predicative participle constructions, depending on whether or not the formation of the participle involves prefixation with the dedicated morpheme ge-. Against the background of the analysis of participles of German be-prefixed verbs proposed in Pross (2019), and using the licensing of superlative constructions and ung-nominalizations as tests, we show that ge-prefixed participles denote a result relation between a property of an event and an individual. In contrast, be-prefixed participles, like adjectives, denote properties of individuals. We cast the distinction between event properties and individual properties in a compositional semantics of ge-and be-prefixed participles and show how the resulting semantic distinction allows to predict the distinction between target and resultant state participles drawn in Kratzer (2000) without using the questionable immer noch ‘still’ test.
MSB PREDICTION-BASED METHOD FOR HIGH-CAPACITY REVERSIBLE DATA HIDING IN ENCRYPTED IMAGES

-Reversible data hiding (RDH) in images aims to exactly recover both the embedded secret information and the original cover image. It has attracted intensive research interests. Military, medical and legal scenarios are its typical examples, in which even a slight distortion is not tolerable. Many RDH algorithms have already been developed, such as image compression-based, difference expansion based, histogram shift (HS)-based, image pixel pair based, and dual/multi-image hiding methods. Recently, due to the requirement of privacy protection, the cover owner usually encrypts the original content before transferring it to the data manager. Meanwhile, the data manager may want to embed additional messages into the encrypted image for authentication or steganography, even though the content of the original image is unknown to him. In this situation, hiding data in the encrypted image is an intuitive and effective way to meet such requirement. To hide data in encrypted domains, some digital watermarking based schemes are proposed. Keywords— Reversible Data Hiding (RDH), Most Significant Bit (MSB)
Development of a Community-Based Dissemination Scheme for Improved Cowpea Varieties

Introduction Cowpea (Vigna unguiculata) is an important crop for food security, livelihood improvement and cash income for farmers throughout sub-Saharan Africa. In West Africa, cowpea is well adapted to the drier savanna eco-regions, and is mostly produced there (Mortimore et al. 1997). Available data indicate that cowpea is an important cash crop in Burkina Faso, Ghana, Nigeria, Mali, Mauritania, Niger, and Senegal (Kormawa et al. 2002). Therefore, cowpea breeding programs of national agricultural research systems have developed and released various improved cowpea varieties in sub-Saharan African countries. Though improved varieties possess various advantages, such as high yield and resistance to various biotic and abiotic stresses, dissemination of these improved varieties and implementation of modern cultivation techniques continue to be slow. To overcome these difficulties, a community-based dissemination scheme, “Accelerated dissemination system of improved cowpea varieties via empowered communities in Burkina Faso (AVEC-BF)” was designed with intensive interaction of three major components: (1) Establishment of community seed producers, (2) Selection of suitable improved varieties via farmers’ participatory varietal selection (FPVS), and (3) Organizing farmers’ schools (FS) for improved management practices (Figure 1). Here, the results obtained through a 3-year demonstration of the scheme in 5 villages of Burkina Faso, as well as the expected impact of the scheme, are discussed.
STRATIFIED TIME-FREQUENCY FEATURES FOR CNN-BASED ACOUSTIC SCENE CLASSIFICATION Technical Report

Acoustic scene signal is a mixture of diverse sound events, which are frequently overlapped with each other. The CNN models for acoustic scene classification usually suffer from model overfitting because they might memorize the overlapped sounds as the representative patterns for acoustic scenes, and might fail to recognize the scene when only one of the sound is present. Based on a standard CNN setup with log-Mel feature as input, we propose to stratify the log-Mel image to several component images based on sound duration, and each component image should contain a specific type of time-frequency patterns. Then we emphasize the independent modeling of time-frequency patterns to better utilize the stratified features. The experiment results on TAU Urban Acoustic Scenes 2019 development dataset [1] show that the use of stratified feature can significantly improve the classification performance.
MT-DP – 2018 / 26 Who runs first to the bank ?

We study how lines form endogenously in front of banks when depositors differ in their liquidity needs. Our model has two stages. In the first one, depositors choose the level of costly effort they want to exert to arrive early at the bank which determines the order of decisions. In the second stage, depositors decide whether to withdraw or to keep the funds deposited. We consider two different informational environments (simultaneous and sequential) that differ in whether or not depositors can observe the decision of others during the second stage of the game. We show theoretically that the informational environment affects the emergence of bank runs and thus should influence the willingness to rush to the bank. We test the predictions in the lab, where we gather extensive data on individual traits to account for depositors' heterogeneity; e.g. socio-demographics, uncertainty attitudes or personality traits. We find no significant differences in the costly effort to arrive early at the bank neither across the informational environments, nor according to the liquidity needs of the depositors. In the sequential environment, some depositors rush to the bank because they are irrational and do not recognize the benefits of observability in fostering the coordination on the no-bank run outcome. There is also evidence that some depositors rush to keep their funds deposited and to facilitate coordination on the efficient outcome. Finally, we document that loss aversion is an important factor in the formation of the line.