Miracle-dz/UniFAR-FTUs huggingface dataset:
Analysis from a Cultivation Perspective Media Exposure and Smoking Intention in Adolescents : A Moderated Mediation

The study tested a moderated mediation model to examine the mechanisms underlying the link between media exposure and adolescent smoking intention by utilizing a modification of cultivation theory. A total of 12,586 non-current smoker adolescents in California were included in the analysis. Results showed that media exposure was positively related to smoking intention via perceived prevalence of peer smoking when friend disapproval of cigarette use was low. This study contributes to a better understanding of the mechanisms regarding the media effects on smoking intention, but the findings should be interpreted with caution due to the small effect size.
AGRO-MORPHOLOGICAL AND PHYSIOLOGICAL RESPONSES OF BRASSICA RAPA ECOTYPES TO SALT STRESS

Salt stress is one of the major abiotic stresses that affect normal morpho-physiological and biochemical processes of Brassica rapa. In present study the effect of salt stress on three important ecotypes of B. rapa (brown sarson, yellow sarson and Toria) was studied. The plants were regenerated at four NaCl levels (0, 50,100 and 150 mmol). The effect of salt stress on shoot length, root length, shoot fresh and dry weight, root fresh and dry weight, leaf relative water content (RWC), proline and chlorophyll a, b, a+b contents were recorded. The high salt stress significantly decreased the shoot length, root length, shoot fresh weight, shoot dry weight, and root fresh weight and root dry weight of all three ecotypes. The genotype 25007 (brown sarson) showed better morphological performance followed by Toria as compared to other genotypes. The RWC values and chlorophyll a, b and a+b contents were decreased up to several fold at high salt levels (50,100 and 150 mmol), while proline contents increased at these concentrations. Maximum RWC values and proline contents were recorded in genotype 25007 followed by Toria. The chlorophyll a, b and a+b amounts were higher in Toria followed by 25007 respectively. The brown sarson and Toria ecotypes showed better performance at high salinity levels as compared to yellow sarson. The resulted screened salt tolerant genotypes will be useful for salt affected area.
Improved State Estimation for a Resilient Spacecraft Executive

Autonomous navigation systems that can operate safely without collisions in an unknown environment can have significant applications towards space exploration missions for science discoveries. In this project, we strive to further develop the initial implementation of a resilient risk-aware software architecture that can handle uncertainty in hazardous environments. We propose a model using ROS for real-time dynamic map updates using Hokuyo lidar sensors, and use generated map for autonomous navigation of the rover. We also integrate obstacle avoidance algorithms into the RSE software architecture. Our results demonstrate dynamic map updates for navigation and planning, on both simulation and practical framework using the TurtleBot robot.
for OAH & ACYF Teenage Pregnancy Prevention Grantees December 2014 • Brief 6 Using the Linear Probability Model to Estimate Impacts on Binary Outcomes in Randomized Controlled Trials

M any researchers are unsure of whether the linear probability model (LPM) – that is, using the same linear regression methodology for a binary outcome that is used for a continuous outcome – is appropriate in the context of calculating impacts on binary outcomes in a randomized controlled trial (RCT). The purpose of this brief is to provide those researchers with a technical explanation for why the LPM is appropriate in that context. For less technical readers, we hope that the findings presented at the end of the brief are helpful in selecting an impact estimation method.
Impact of Organizational Culture on Leadership Style and Affective Commitment

Organizational culture as the core of an organization, it is crucial to build a foundational and productive working environment. The objective of this paper is to investigate the impact of organizational culture on leadership and affective commitment in the higher education institutions in China. This research was carried out the five point Likert scale to measure the data. The quantitative survey method was applied and a sample of 400 employees from the higher education institutions of China. Convenience sampling technique is used to be instrument of the study. SPSS software was used to analyze the data collected based on descriptive statistics. The findings indicate that the organizational culture has significant influence on leadership and affective commitment in higher education institutions. The result indicates that organizational culture has moderating effect on the relationship between leadership style and affective commitment.
orpho-anatomy of native species used as substitute of quina Cinchona spp . ) in Brazilian traditional medicine : Esenbeckia febrifuga ádia

Esenbeckia febrifuga (A.St.-Hil.) A. Juss. ex Mart. , Rutaceae, is known by several popular names including quina-do-mato. This name is a reference to the use of its bark as febrifuge and in the past was employed as a substitute of Cinchona sp. for treatment of malaria symptoms. This confusion may have been reinforced by the fact that the bark of these plants are similar in appearance and have a bitter taste. In view thereof
The Research Progress of Parmelioid Lichen and Identification between Its Genus

Parmelioid lichen is an important group in Parmeliaceae, widely distributed in the world. There are 67 species of Parmelioid lichen in the world, and only 30 species are reported in China. This paper summarizes the research progress of the Parmelioid lichen and probes into the difference of the morphological and chemical components of the four genus in the Parmelioid lichen; at the same time, the phylogenetic relationship about the Parmelioid lichen with the help of molecular phylogeny methods was studied. In this paper, we select the Parmelioid lichen distributed in different regions in NCBI database, namely, three species of Melanelia Essl. , four species of Melanelixia, four species of Melanohalea and five species of Montanelia. The phylogenetic research of species is studied by ITS sequences and using ML analyses. Our phylogenetic analyses support traditional genera delimitation based on morphological and chemical traits in most but not all cases.
Query processing in mobile peer-to-peer networks

Mobile local search is a procedure in which a mobile user searches for local resources, i.e., resources that are in geographic proximity to the user (e.g., a person with certain expertise in a convention hall, a ride-share opportunity, a taxi-cab, a parking slot, etc.). A promising approach to mobile local search is mobile peer-to-peer databases (MP2PD). In the MP2PD approach, a database is stored in the peers (PDA's, cell phones, vehicles, sensors, etc.) that communicate with each other via short-range wireless technologies such as IEEE 802.11, Bluetooth, Zigbee, or Ultra Wide Band (UWB). All the local databases maintained by the mobile peers form a mobile P2P database. The characteristics of MP2PD include (i) dynamic network topology, (ii) memory/energy/bandwidth limitations, and (iii) lack of global coordination. The objective of the dissertation is to study query processing in such an environment. The traditional in-network query processing paradigm postulates that a query is routed among peers and collects the answers from the peers. It works for static and connected networks. However, when the network consists of mobile peers and is sparse, a different approach is necessary. We propose a query processing method that uses cooperative caching. It makes the data items satisfying a query flow to its originator. To cope with communication bandwidth and storage constraints, the method prioritizes the data-items in terms of their value, as reflected by supply and demand. The dissertation develops the formula by which a mobile peer dynamically adjusts the number of reports included in a transmission, develops a report prioritization method called MARKET, analyzes the way a report is propagated in geospace and time, the benefit of information dissemination in capturing competitive resources (i.e. resources that can be used by only one user at a time) and provisioning real-time traffic information, how well the average local database reflects the status of physical resources, how our approach compares with the central server model and with existing work on publish/subscribe in wireless ad-hoc networks, how to incentivize mobile devices to relay reports, the application to continuous kNN queries and to transportation mode detection.
Energy and non-energy commodity prices and the Eurozone macroeconomy : a SVAR approach

Abstract This paper deals with the links between the real and financial processes in the euro area and energy and nonenergy commodity prices. We use monthly data spanning from 1997:1 to 2013:9 and the structural VAR model to analyse the relations between global commodity prices and the Eurozone economy. The analysis is performed for three sub-periods in order to capture potential changes in the reactions in time. Our main finding is that though commodity prices are indeed related to real and financial processes in the euro area macroeconomy, the relations have not been stable in time: energy prices and interest rates have departed from the real processes in the precrisis period, whereas the relative importance of real and financial factors have changed for non-energy prices. Additionally, the relations between commodity prices have gradually become tighter, especially the ones running from energy to non-energy prices.
Towards a Sinhala Wordnet

This paper describes the methods adopted and the issues addressed in building a Sinhala Wordnet, based on the Princeton English WordNet (PWN). Its aim is to develop the most important parts of a wordnet for the Sinhala language, in order for it to be of optimal use without being complete. The importance of entries were estimated using the word frequencies of the 10 million word UCSC Sinhala corpus of Contemporary Sinhala, and the relevant lexico-semantic relations extracted from the PWN. The paper describes how the Sinhala Wordnet was developed with a view to presenting a recommended strategy for other languages for which wordnets may be developed in the future.
Supplementary Material for Learning to Exploit Long-term Relational Dependencies in Knowledge Graphs

Figure 5 shows the architecture of RSNs for the entity alignment task. It accepts two KGs as input and adopts an end-toend framework to align the entities between them. Specifically, it first assembles the two KGs as a joint KG, and then repeatedly samples relational paths by the biased random walks on this KG. The generated paths are converted to embedding sequences according to the index of each element in the paths. It uses RSNs to model them and optimizes this process with type-based NCE. Finally, new alignment can be found by comparing the entity embeddings.
Computational Determination Of Binding Energy Of Ethane With [ Mn ( 4-Picoline ) 3 ] 2 + Dication Complex Ion On DFT And PEC Models In The Gas Phase

Ethane is the second most significant hydrocarbon emitted to the atmosphere from oil and gas after methane [1] and is produced mainly via thermogenic processes [2]. A new study led by the University of Colorado Boulder stated that global emissions of ethane, an air pollutant and greenhouse gas, are on the uptick again. According to the study a steady decline of global ethane emissions following a peak in about 1970 ended between 2005 and 2010; in most of the Northern Hemisphere and has since reversed. Currently, research has shown that between 2009 and 2014, ethane emissions in the Northern Hemisphere increased by about 400,000 tons annually, the bulk of it is from North American oil and gas activity. Clearly, about 60 percent drop in the levels of ethane over the past 40 years has already been made up within five years [3]. Ethane pollution can also harm agricultural crops [4]. Using ethanol fuel to power automobiles, results in significantly low levels of toxins in the environment [5]. Ethanol has a higher octane number than gasoline, providing premium blending properties. Minimum octane number requirements for gasoline prevent engine knocking and ensure drivability. Low-octane gasoline is blended with 10% ethanol to attain the standard 87 octane [6]. Over the past years the agenda for many governments, was emphasised on reducing fuel emissions. In an attempt to reduce their collective carbon footprint, many countries have started looking for a way to control their impact on the environment. This initiated a situation where the use of ethanol fuel has increased in many countries. Since the 1920s Abstract: Stimulated by the quest for ways of a more resourceful convention of the abundant, untapped reserves of ethane, topical development in the gas-phase activation of ethane by metal dication complex ion [Mn(4-Picoline)3]2+ i.e [Mn(4-methyl Pyridine)3]2+ is discussed. The gas phase theoretical and experimental analysis on [Mn(4-Picoline)3]2+ was conducted. The ions were prepared using a combination of the pick-up technique and high energy electron impact, and then held in a cold ion trap where they were excited with tuneable UV radiation and further successfully activated with ethane The average calculated binding energy per molecule of 4-Picoline (4-methyl Pyridine) calculated for [Mn(4Picoline)3)2+,lied within the photon energy range over which the photofragmentation spectra were recorded. At the optimised geometry of [Mn(4-Picoline)3)2+ with ethane C1 symmetry was observed. The calculated DFT charge on the manganese metal centre in the optimised geometry was observed to be 20% lower than the potential energy curve (PEC) assumed charge of +2 on the manganese metal. The calculated binding energy of ethane with the Mn(4-Picoline)3]2+ was observed to be overestimated on the PEC by 24% as compare to the calculated DFT.
A LEARNING BASED FRAMEWORK FOR DETECTION OF ANDROID C & C ENABLED APPLICATIONS USING HYBRID ANALYSIS

Smartphone devices, particularly android devices used by billions of people everywhere in the world. Similarly, this increasing rate attracts mobile botnet attackers that is a network of interconnected nodes operated by command and control (C&C) method to expand malicious activities. At present, mobile botnet attacks carried Distributed denial of services (DDoS) that causes to steal sensitive data, remote access, spam generation, etc. Consequently, various approaches are defined in the literature to detect mobile botnet using static or dynamic analysis. In this paper, we have proposed a novel hybrid model, which is a combination of static and dynamic method that relies on machine learning to identify android botnet applications having C&C capability. The results evaluated through machine learning classifiers in which Random forest classifier outperform other ML techniques, i.e. Naïve Bayes, Support Vector Machine, and Simple logistics. Our proposed framework can achieve 97.48% accuracy in detecting such harmful applications. Furthermore, we highlight some research directions and possible solutions regarding botnet attacks for the entire community.
Potential of Infrared Spectrum in Face Recognition: An art of review from 1991 to 2013

The face recognition (FR) is growing as the major research area among the researchers in the fields of computer vision and pattern recognition because of the wide range of applications in the fields of commercial and law enforcement. By continuing research, the rapid improvements are achieved and illustrating benefits in the different ﬁelds including pattern recognition, image processing, computer graphics and physiology. Traditional FR systems based on visible spectrum images in electromagnetic spectrum have faces the different challenges due to illumination, pose variation, expression changes, as well as facial disguises, and all of these limitations decrease the performance of face recognition in terms of accuracy. To overcome all these limitations, the other spectrum such as infrared (IR) of electromagnetic spectrum can be used which has achieved the great significance because of reducing the several limitations arise in the visual spectrum. So it leads to the continuous research in this area for face recognition. The use of hyperspectral images in IR also have become a most research direction by minimizing the several limitations arises in visual spectrum. This paper presents a detailed and time to time review of the literature on face recognition in infrared spectrum. The significance of hyperspectral images for face recognition in infrared spectrum is also studied and reviewed.
ENHANCING RANSAC BY GENERALIZED MODEL OPTIMIZATION Onďrej Chum, Jǐ

An extension of theRANSAC procedure is proposed. By adding a generalized model optimization step (the LO step) applied only to models with a score (quality) better than all previous ones, an algorithm with the following desirable properties is obtained: a near perfect agreement with theoretical (i.e. optimal) performance and lower sensitivity to noise and poor conditioning. The chosen scheduling strategy is shown to guarantee that the optimization step is applied so rarely that it has minimal impact on the execution time. The potential of theLO step is demonstrated on two new matching algorithms that are straightforward implementation of LO-RANSAC: 1. an algorithm for simultaneous estimation of epipolar geometry and radial distortion and 2. an algorithm estimating epipolar geometry from three regionto-region correspondences. Experiments show that the new estimators have performance superior to the state-of-the-art. The latter algorithm speeds up the estimation of epipolar geometry more than thousand times and thus permits solving complex problems with inlier ratio below 10%. The former represents a class of algorithms where theLO step includes switching to a more complex model (with more degrees of freedom). Surprisingly, due to the increased number of inliers of the more complex (and more precise) model, the LO step significantly reduces the execution time.
Detecting Missing-Check Bugs via Semantic- and Context-Aware Criticalness and Constraints Inferences

Missing a security check is a class of semantic bugs in software programs where erroneous execution states are not validated. Missing-check bugs are particularly common in OS kernels because they frequently interact with external untrusted user space and hardware, and carry out error-prone computation. Missing-check bugs may cause a variety of critical security consequences, including permission bypasses, out-of-bound accesses, and system crashes. While missingcheck bugs are common and critical, only a few research works have attempted to detect them, which is arguably because of the inherent challenges in the detection—whether a variable requires a security check depends on its semantics, contexts and developer logic, and understanding them is a hard problem. In this paper, we present CRIX, a system for detecting missing-check bugs in OS kernels. CRIX can scalably and precisely evaluate whether any security checks are missing for critical variables, using an inter-procedural, semanticand context-aware analysis. In particular, CRIX’s modeling and cross-checking of the semantics of conditional statements in the peer slices of critical variables infer their criticalness, which allows CRIX to effectively detect missing-check bugs. Evaluation results show that CRIX finds missing-check bugs with reasonably low false-report rates. Using CRIX, we have found 278 new missing-check bugs in the Linux kernel that can cause security issues. We submitted patches for all these bugs; Linux maintainers have accepted 151 of them. The promising results show that missing-check bugs are a common occurrence, and CRIX is effective and scalable in detecting missing-check bugs in OS kernels.
Computed Tomography Using a Low Tube Voltage Technique for Acute Ischemic Stroke

Computed tomography (CT) is commonly used to assess for cerebral hemorrhage and acute ischemic stroke. We investigated the accuracy of CT using a low tube voltage technique in acute ischemic stroke. We compared the standard deviation (SD), contrast between gray and white matter, and contrast-to-noise ratio (CNR) between three groups (120 kV 500 mAs, 100 kV 850 mAs, and 100 kV 750 mAs using hybrid iterative reconstruction) in 50 patients without lesions, and visual evaluation using the normalized rank approach was also performed. The mean value of SD was 4.02, 4.22, and 4.04, respectively, and the contrast between gray and white matter was 7.08, 8.66, and 8.68 HU, respectively; in addition, the CNR was 1.77, 2.06, and 2.15, respectively. The difference between the 100 kV and 120 kV groups was significant (p < 0.01). Visual evaluation showed a significant difference between the 100 and 120 kV groups (p < 0.05).
Estimating CES Aggregate Production Functions of China and India

We have observed remarkably different patterns in the development processes of China and India. For example, data from our sample show that, comparing with India, China has considerably higher rates of physical capital formation as well as much higher ratios of measured physical to human capital. Motivated by these empirical observations, we estimate the key technological parameters of a CES production function with physical and human capital using panel data at the provincial level for China and at the state level for India, respectively. Our estimation results on the distributional parameter and the elasticity of substitution between the input factors yield implications that match broadly with the above stylized factor accumulation patterns in China and India. Key-Words: CES production function, Physical capital, Human capital, Economic development