Miracle-dz/UniFAR-FTUs huggingface dataset:
Predicting the Use of Twitter in Developing Countries: Integrating Innovation Attributes, Uses and Gratifications, and Trust Approaches

Abstract Based on the diffusion of innovation (DOI) theory (Rogers, 2003), the uses and gratifications (UG Lacka & Chong, 2015; Liu, Liu, & Li, 2012; Pere-Latre, Portilla, & Blanco, 2010; Prybutok, 2013). Owing to the differences in SNSs' purposes, users, and interfaces, the characteristics and the motivations for the use of individual SNSs need to be investigated, and additional significant factors in different cultures addressed. In line with the philosophy of informing science, Cohen (2009) provides a way of analyzing the role of SNSs as sufficient informing channels for users to create and share content. SNS users interchange the roles of informers (sources) and clients (recipients), whereas SNS platforms serve as the medium where messages can be created, collaborated, and modified by users. Hardin, Ryan, and Prybutok (2012) extended the framework of Cohen's work and suggested that an informing system had three dimensions: "the informing environment, the delivery system, and the task completion system" (p. 207). They identified SNSs as informing channels or delivery systems for mass and interpersonal communication. Extending the effectiveness of informing channels, SNS platforms, in particular, require transdisciplinary research, in developing countries, to understand the usage and acceptance of informing channels. As a form of SNS, Twitter, which was launched to the public in October 2006, is one of the newest developments, and is currently the most widely used microblogging platform. Twitter, which has elements of both mass and interpersonal communication, enables users to send, distribute, and read short posts of 140 characters in length (Java, Song, Finin, & Tseng, 2007). The service requires users to create a username and a brief online profile to benefit from common elements much like those of email, instant messaging, RSS, texting, blogging, and so forth. Twitter users can send and receive messages--"tweets"--which are in the public domain by default unless a user chooses to keep updates private. …
Quasi-bounded trees and analytic inductions

A tree T on ! is said to be cofinal if for every � 2 ! ω there is some branchof T such that � � �, and quasi-bounded otherwise. We prove that the set of quasi-bounded trees is a complete � 1 -inductive set. In particular, it is neither analytic nor co-analytic.
A Revised MODIS-GPP Algorithm by Incorporating Seasonal Fluctuation of Maximum Light Use Efficiency for Maize and Soybean

Accurate quantification of gross primary production (GPP) in agroecosystems not only improves our ability to understand global carbon budget but also ensures basic human survival supplements. Here, we improved the MODIS-GPP algorithm by two main perspectives: (1) taking the seasonal variations of maximum light use efficiency (LUE) into modeling consideration; (2) separately parameterizing maximum LUE with a recently proposed vegetation index (VI) NIRv during vegetative stage and senescence stage. Performances of the revised and traditional MODIS-GPP algorithms were tested at three FLUXNET crop sites planted with maize and soybean. The revised model was well validated, indicated by the root mean square error (RMSE), coefficient of determination $(\mathrm{R}^{2})$ and Bias being 2.33 $\text{gC m}^{-2}$ day ${}^{-1}, 0.91$ and 0.48 $\text{gC m}^{-2}$ da y -l for maize, respectively, and being 1.51 $\text{gC} \mathrm{m}^{-2}\text{day}^{-1},0.91$ and 0.43 $\text{gC m}^{-2}$ day $-1$ for soybean, respectively. Overall, compared to the traditional MODIS-GPP algorithm, the proposed algorithm reduced RMSE by 29.6% and 27.4%, increased $\mathrm{R}^{2}$ by 10.9% and 10.9%, and reduced Bias by 41.5% and 36.8% for maize and soybean, respectively. This paper demonstrates that incorporating seasonal fluctuations of maximum LUE into MODIS-GPP algorithm and distinguishing the different photosynthesis rates among vegetative and senescence stages significantly benefit the retrieval accuracy of daily model-estimated GPP.
management interventions for people with type 2 diabetes after an acute coronary syndrome : a systematic review

Background: Type 2 diabetes is highly prevalent in patients with acute coronary syndrome and impacts negatively on health outcomes and self-management. Both conditions share similar risk factors. However, there is insufficient evidence on the effectiveness of combined interventions to promote self-management behaviour for people who with diabetes and cardiac problems. Identifying critical features of successful interventions will inform future integrated self-management programmes for patients with both conditions. Objectives: To assess the evidence on the effectiveness of existing interventions to promote self-management behaviour for patients presenting with acute coronary syndrome and type 2 diabetes in secondary care settings and post discharge. Design: We searched Medline, PubMed, CINAHL Plus, PsycInfo, Cochrane Library and AMED for randomised controlled trials published between January 2005 and December 2014. The search was performed using the following search terms of “acute coronary syndrome”, “type 2 diabetes” and “self-management intervention” and their substitutes combined. Results: Out of 4275 articles that were retrieved, only 4 trials met all the inclusion criteria (population, intervention, comparison and outcome) and were analysed. Overall, the results show that providing combined interventions for patients with both conditions including educational sessions supported by multimedia or telecommunication technologies were partially successful in promoting self-management behaviours. Implementation of these combined interventions during patient’s hospitalisation and post discharge was feasible. Intervention group subjects, reported a significant improvement in self-efficacy, level of knowledge, glycated haemoglobin, blood pressure and fasting glucose test. However, there are many threats have been noticed around internal validity of included studies that could compromise the conclusions drawn. Conclusion: With limited research in this area there was no final evidence to support effectiveness of combined interventions to promote self-management behaviour for patients with type 2 diabetes and acute coronary
CAMBRIAN-ORDOVICIAN REMAGNETIZED CARBONATES OF THE ARGENTINE EASTERN PRECORDILLERA: PRELIMINARY RESULTS ON MAGNETIC PROPERTIES

Palaeomagnetic evidence has suggested that the Lower Palaeozoic carbonatic platform of the Argentine Precordillera was affected by a regional event of remagnetization occurred during the Late Palaeozoic, possibly related to the Sanrafaelic Orogeny. Though detailed magnetic mineralogy research in these carbonates could provide clues to the geologic processes involved in this phenomenon, systematic study is still necessary. The present work presents the preliminary results on the magnetic properties of five Middle Cambrian to Early Ordovician carbonatic formations (limestones to dolomites) exposed in the Eastern Precordillera which carry a post-folding magnetization assigned to a Permian age and associated to the Sanrafaelic remagnetizing event.
Reputation and accountability relationships: managing accountability expectations through reputation

Accountability is said to be about the management of expectations. Empirical studies reveal considerable variation in organizational interest, intensity, and investment in accountability relationships. Less is known, however, about what explains these observed variations. Drawing on accountability and reputation-concerned literatures, this article argues that a reputation-based perspective on accountability offers an underlying logic that explains how account-giving actors and account-holding forums actually manage these expectations and how organizations make sense of and prioritize among accountability responsibilities. Reputational considerations act as a filtering mechanism of external demands and help account for variations in degrees of interest in, and intensity of, accountability. The resulting accountability outcomes are coproduced by the reputational investment of both account-giver and account-holder, resulting in distinct accountability constellations and outcomes.
Motif-based Hessian matrix for ab initio geometry optimization of nanostructures

Author(s): Zhao, Zhengji; Wang, Lin-Wang; Meza, Juan | Abstract: A simple method to estimate the atomic degree Hessian matrix of a nanosystem is presented. The estimated Hessian matrix, based on the motif decomposition of the nanosystem, can be used to accelerate ab initio atomic relaxations with speedups of 2 to 4 depending on the size of the system. In addition, the programing implementation for using this method in a standard ab initio package is trivial.
Research on Systems Analysis and Design : The Case of UML

Design science in the IS discipline seeks to create artifacts that embody the ideas, practices, technical capabilities, and products required to efficiently accomplish the analysis, design, implementation, and use of information systems (Hevner et al 2006). SA&D research, being close to the design science paradigm, has suffered from a lack of appreciation from the behavioral science paradigm. To provide a paradigmatic foundation, we propose a conceptual framework for SA&D research. The framework was developed based on several essays that systematically articulate the design science paradigm in the IS field. Using this framework, we reviewed some UML papers that appeared in the proceedings of AMCIS. This preliminary literature analysis indicates that our framework for SA&D research is viable and does manifest itself in the IS literature.
Application of Prisma Hyperspectral Data for PM2.5 Estimation: A Case Study on New Delhi, India

City based pollution monitoring is essential for overall health and sustainability of the concerned city. PM2.5 is one of the most hazardous pollutants whose excessive presence in the urban air makes it unfit to breathe. A study is conducted to estimate PM2.5 (particulate matter with diameter ≤ $2.5\ \mu\mathrm{m}$) using PRISMA (hyperspectral imagery based satellite) hyperspectral bands for the Delhi region in India. By using ground station measurements and simulated PM2.5 concentrations (using Sequential Gaussian Simulation) as a reference, estimates of PM2.5 are created from the PRISMA imagery. Various regression models are developed for PM2.5 estimation from hyperspectral data and deployed for spatial estimation. This study provides a comparative demonstration of ground level PM2.5 prediction for urban areas using various machine learning models from hyperspectral imagery and indicates the importance of it.
Palladium-Catalyzed Hydroarylation of Propiolamides. A Regio- and Stereocontrolled Method for Preparing 3,3-Diarylacrylamides

A general regio- and stereoselective synthesis of 3,3-diarylacrylamides is reported. Palladium-catalyzed coupling reactions of propiolamides with aryl halides provide arylpropiolamides. A subsequent hydroarylation reaction of these arylpropiolamides with aryl halides, catalytic palladium, an amine base, and formic acid in refluxing ethyl acetate provides 3,3-diarylacrylamides regio- and stereoselectively. The unique stereo- and regiocontrol is presumed to proceed through careful reaction parameters that allow intramolecular coordination of the propiolamide amide functionality to the transient palladium−alkyne complex. Palladium-catalyzed hydroarylation of propiolamides has not been studied; however, preliminary results from related systems suggest that regioselective addition can be achieved. The methodology as a synthesis tool is demonstrated in an efficient route to previously difficult-to-prepare potent, benzimidazole antiviral targets. In addition, the synthesis scope is explored where, by judicious c.
Potential applications of affective computing in the surveillance work of CCTV operators

Affective computing is a branch of artificial intelligence that deals with the design of devices which can process human emotions. The data gathered by passive sensors can be compared to the cues humans use to perceive the affective state of others (e.g. a video camera might capture facial expressions, body posture or gestures). An automatic, machine-based emotion recognition system could operate on the basis of the output of these sensors. CCTV surveillance is a potential application for such a system which might be used to constantly monitor for mal-intent through the emotional cues exhibited by surveillance targets and alert CCTV operators as appropriate. Previous research showed that firearms are known to elicit certain emotional states in their bearers. Consequently, these states might be reflected in the change of the individuals body language. The potential for automating the detection of the associated emotional cues in image processing algorithms is discussed.
Multi-Scale Fusion Maximum Entropy Subspace Clustering for Hyperspectral Band Selection

A novel multi-scale fusion maximum entropy subspace clustering (MFMESC) for hyperspectral image (HSI) band selection is proposed in this paper. Subspace clustering is combined as a self-expression layer with stacked convolutional autoencoder, so that subspace clustering working in linear subspaces can deal with complicated HSI data with nonlinear characteristics. Multiple fully-connected linear layers are inserted between the encoder layers and their corresponding decoder layers to promote learning more favorable representations for subspace clustering. A multi-scale fusion module is designed to guide the fusion of multi-scale information extracted from different layers to learn a more discriminative self-expression coefficient matrix. Furthermore, the maximum entropy regularization is introduced in the subspace clustering to promote the connectivity within each subspace. Experimental results demonstrate the superiority of the proposed model against state of-the-art methods.
Dead-time effects on the voltage spectrum of a PWM inverter

An inverter converts a direct-current power supply to an alt ernating-current power supply. This conversion is achieved by switching the output between the inpu ts at high frequency. The resulting output voltage may be described by a high-frequency train of variab le-width pulses. Pulse widths are slowly modulated so that this output waveform contains a prescribe d low-frequency component, which may then be isolated by an appropriate filtering regime. Techniq ues for determining the full harmonic spectrum of input and output voltages and currents are well estab li hed, at least for an idealised mathematical model of the inverter. However, this model assumes that chan ges of inverter configuration can be effected instantaneously, which is not quite the case in pract ice. In fact, a small amount of dead timemust be incorporated into switching regimes in order to avoid sho rt circuits of the input. Although dead time is an important feature of real power conversion devices, it s effects on output voltage spectra have not previously been fully determined (except by imposing rathe r restrictive approximations). This situation is remedied in the present paper, in which we present closedform expressions for the coefficients of the harmonic spectrum, corroborated by simulations.
Testing the Home Market Effect in a Multi-Country World: The Theory

We extend the model by Krugman (1980) to a multi-country set-up and show that the ‘home-market effect’ highlighted with two countries does not readily extend to such a general setting. In particular, we prove that the most important result, namely the disproportionate causation from demand to supply, generalizes only under the fairly implausible assumption of pairwise symmetric trade costs between all countries. We argue, therefore, that the implications of product differentiation for the structure of world trade are better characterized in terms of spatial (‘accessibility’) and non-spatial (‘attraction’) effects, and we provide a theory-based specification that suggests how to test the home market effect in such a general setting.
Reliability/Economic/GHG implications of Grid-Connected Wind Energy System Based on Genetic Algorithm

Greenhouse gas, economic, and reliability issues are becoming more important for the emerging wind markets worldwide. With the interconnection of wind energy system into the electric grid, the fluctuating nature of the energy produced has a different effect on the overall system reliability/economic and GHG emissions as well as the fluctuating nature of energy produced by grid. Optimum reliability/economic and pollutant emission are multi-objective problem because reliability is conflicting with annual cost and GHG emissions. The reliability index is analyzed using probabilistic concept in order to find loss of load probability and annual customer damage cost. Therefore, this paper presents a study to find optimum design of wind energy system with electric grid from reliability/economic and pollutant emission point of view based on genetic algorithm (GA). The methodology is carried out over one year using the hourly data of the load demand and wind speed at Zafarâna site, located on the western coast of the Seuz Gulf, latitude 29.07o N and longitude 31.36o E, Egypt as an example. The optimization results do not just show economic merit but satisfy both of reliability level and environmental issues. Moreover this methodology can be applied at any site in the world to determine the optimal design and impact of reliability and GHG emissions of interconnected renewable energy system with electric grid.
Keeping Found Things Found: The Study and Practice of Personal Information Management: The Study and Practice of Personal Information Management

WE ARE ADRIFT IN A SEA OF INFORMATION. We need information to make good decisions, to get things done, to learn, and to gain better mastery of the world around us. But we do not always have good control of our information - not even in the "home waters" of an office or on the hard drive of a computer. Instead, information may be controlling us - keeping us from doing the things we need to do, getting us to waste money and precious time. The growth of available information, plus the technologies for its creation, storage, retrieval, distribution and use, is astonishing and sometimes bewildering. Can there be a similar growth in our understanding for how best to manage information and informational tools? This book provides a comprehensive overview of personal information management (PIM) as both a study and a practice of the activities people do and need to be doing so that information can work for them in their daily lives. Introductory chapters of Keeping Found Things Found: The Study and Practice of Personal Information Management provide an overview of PIM and a sense for its many facets. The next chapters look more closely at the essential challenges of PIM, including finding, keeping, organizing, maintaining, managing privacy, and managing information flow. The book also contains chapters on search, email, mobile PIM, web-based support, and other technologies relevant to PIM. * Focuses exclusively on one of the most interesting and challenging problems in today's world * Explores what good and better PIM looks like, and how to measure improvements * Presents key questions to consider when evaluating any new PIM informational tools or systems
Electric wind in a Differential Mobility Analyzer

Electric wind -- the movement of gas, induced by ions moving in an electric field -- can be a distorting factor in size distribution measurements using Differential Mobility Analyzers (DMAs). The aim of this study was to determine the conditions under which electric wind occurs in the locally-built VLDMA (Very Long Differential Mobility Analyzer) and TSI Long-DMA (3081) and to describe the associated distortion of the measured spectra. Electric wind proved to be promoted by the increase of electric field strength, aerosol layer thickness, particle number concentration and particle size. The measured size spectra revealed three types of distortion: widening of the size distribution, shift of the mode of the distribution to smaller diameters and smoothing out the peaks of the multiply charged particles. Electric wind may therefore be a source of severe distortion of the spectrum when measuring large particles at high concentrations.
Proper orthogonal decomposition and low-dimensional models for driven cavity flows

A proper orthogonal decomposition (POD) of the flow in a square lid-driven cavity at Re=22,000 is computed to educe the coherent structures in this flow and to construct a low-dimensional model for driven cavity flows. Among all linear decompositions, the POD is the most efficient in the sense that it captures the largest possible amount of kinetic energy (for any given number of modes). The first 80 POD modes of the driven cavity flow are computed from 700 snapshots that are taken from a direct numerical simulation (DNS). The first 80 spatial POD modes capture (on average) 95% of the fluctuating kinetic energy. From the snapshots a motion picture of the coherent structures is made by projecting the Navier–Stokes equation on a space spanned by the first 80 spatial POD modes. We have evaluated how well the dynamics of this 80-dimensional model mimics the dynamics given by the Navier–Stokes equations. The results can be summarized as follows. A closure model is needed to integrate the 80-dimensional system .
Effect of silicon fertilization on mineral composition of rice under Typic Ustochrept soils

A pot experiment was conducted in 2012 in the greenhouse of the Anand Agricultural University Anand Gujarat, India. Treatments were arranged in a factorial completely randomized complete design with silicon factor at four levels (0, 100, 200 and 300 ppm) with three replicates. Indian improved and high -yielding variety Gurajari was used. The Si application up to 200 mg kg-1 soil significantly increased grain and straw yields of rice over the control under low (< 25 mg Si kg-1 soil) and medium (25 - 50 mg Si kg-1 soil) category soils, while it was up to 100 mg Si kg-1 soil in high category soils. The soil, grain and straw samples were analyzed for their Si, P, K, S and Na content at harvest. The Si content in grain ranged from 1.77 to 2.69% in untreated plots, whereas in treating plots, it ranged from 1.85 to 3.40%. The average value of Si content in straw was 7.78, 7.46 and 7.82% in low, medium and high category soils, respectively. Key words: Silicon, yield, mineral composition, content, rice.
Stream Mining : A Review on Windowing Approach

In the data stream model the data arrive at high speed so that the algorithms used for mining the data streams must process them in very strict constraints of space and time. This raises new issues that need to be considered when developing association rule mining algorithms for data streams. So it is important to study the existing stream mining algorithms to open up the challenges and the research scope for the new researchers. In this paper we are discussing different type windowing techniques and the important algorithms available in this mining process.