Miracle-dz/UniFAR-FTUs huggingface dataset:
Mining User Movement Similarity Based on Massive GPS Trajectory Data with Temporal Effects

The pervasive use of mobile devices and location-based services has supported the generation of large spatiotemporal datasets reflecting user movement behavior. However, studies on such type of data have depended heavily on geographic overlapping, and information about the time of day of travel visits has been overlooked. In this paper, we proposed an efficient method for mining user movement similarity based on users’ travel histories as recorded by GPS trajectories. Our approach also allowed consideration of related temporal effects. To that end, first we introduced a partition method to divide the trajectories into a set of line segments that allowed us to explore the correlation between users and their visited territories. Significantly, we proposed a characteristic point mapping method to transform the sparse GPS trajectories into a set of transactional data. Based on this data, we conducted a series of data mining procedures for efficient discovery of the users’ movement information. Second, we proposed a novel, lowrank matrix factorization-based method to cluster users’ movements into groups based on their similarity, including temporal characteristics. The experimental results demonstrated that the proposed method can be used to mine the popular roaming routes of users or similar movements efficiently while including temporal patterns. This approach can prove valuable for the development of location-based social network recommendations and human mobility prediction.
Temperature Dependence of Electrophoretic Mobility and Hydrodynamic Radius of Microgels of Poly(N-isopropylacrylamide)

Electrostatic interactions in charged microgels, which are dominated by the microgel net charge, play a crucial role in colloidal stabilization and loading of small, charged molecules. In this study, the temperature dependences of electrophoretic mobility μ and hydrodynamic radius Rh were measured for a slightly ionized poly(N-isopropylacrylamide) (PNIPA) microgel in a dilute suspension. A decrease in Rh was observed in the temperature range between 30 °C and 35 °C, corresponding to the lower critical solution temperature of PNIPA, and an increase in |μ| was observed in a higher temperature range between 34 °C and 37 °C. The analysis based on electrophoresis theory for spherical polyelectrolytes indicated that the net charge of the microgel decreased as the microgel was deswollen.
Sound Familiar ? Heritage Learners , Phonological Awareness and Literacy Skills

This study explores the impact of the unique motivation and language skills of low-proficiency heritage learners on their performance in dictation tasks. A total of 24 beginner learners of L2 German were monitored for one semester while completing a dictation task in an intelligent computer-assisted language learning (ICALL) environment at a Canadian university. All native speakers of English, the participants were grouped by relationship to the target language community: 12 L2 heritage learners had at least one German parent, and 12 non-heritage learners had neither a German parent nor had travelled to a German-speaking country. Extensive computer log files, augmented by student questionnaires, were examined for learner behaviour and performance patterns. Results indicate that heritage learners on average made significantly more spelling mistakes and were more likely to access additional resources to complete the task than non-heritage language learners. This leads to a tentative conclusion that any benefit of motivational differences, phonological awareness and/or acuity from childhood L2 exposure is outweighed by literacy skills far below their communicative competence. The results of this study add to the growing body of research demonstrating that heritage learners have distinct learner behaviours and language skill sets and their pedagogical needs should be considered separately from traditional foreign language learners in the classroom.
Subjective well-being as a mediator for curiosity and depression

: Curiosity is a personality trait that is inversely related to depression and positively related to subjective well-being. However, the relationship between curiosity and these two outcomes is still unclear which hampers our general understanding of well-being. Based on research within positive psychology that showed character strengths such as curiosity can indirectly decrease depression, we hypothesized that the inverse relationship between curiosity and depression would be mediated by subjective well-being. Two hundred and fifty seven participants, between 18 and 64 years old (M = 24.50, SD = 8.33) completed a web-based survey comprising: The Curiosity and Exploration Inventory – II, Center for Epidemiological Studies – Depression and the Steen Happiness Index. We found that well-being mediated the relationship between curiosity and depression. The results indicate that curious individuals tend to report higher levels of subjective well-being which, in turn, is associated with lower levels of depression. Our findings contribute to the understanding of positive results obtained from clinical samples that underwent positive psychotherapy of depression.
Phytochemical Screening and In Vitro Antibacterial,Antioxidant and Anticancer Activity of AmphiroaFragilissima (Linneaus) J V Lamoroux

Marine natural products have attracted the attention of biologists and chemists the world over for the last five decades. The active metabolites, also known as biogenic compounds, produced by several species of marine macro- and micro-algae, have antibacterial, antialgal, antimacro fouling and antifungal properties, which are effective in the prevention of cancer, and many other diseases have other likely uses, e.g. in therapeutics. The common major compounds like proteins, carbohydrates, steroids, glycosides can be extracted using polar solvents such as Methanol, Ethyl acetate and Hexane during Phytochemical process. These results were compared with the recently reported qualitative phytochemical tests which were used to detect the presence of alkaloids, tannins, saponins, flavonoids, glycosides and phenols from the seaweeds. Of the three solvents tested, Methanol was determined to be the best solvent for isolation of antimicrobial compounds from the tested marine algae followed by Ethyl acetate and Hexane. Among marine the algal extracts tested, some appeared to be specific in their activity against several tested bacteria. This point may be important for the development of specific antibiotics, and further work is needed to identify the compounds causing the activity, to evaluate specific antimicrobial activity against pathogenic bacteria especially those causing the human diseases.
Evaluation of metabolic syndrome in patients with NASH 1

1Nicoleta V. Leach, 2Eleonora Dronca, 3Corina Radu, 3Dana Crisan, 4Monica LupsorPlaton, 1Dorel P. Sampelean, 3Mircea Grigorescu 1 Vth Department of Internal Medicine, “Iuliu Hatieganu” University of Medicine and Pharmacy, Cluj-Napoca, Romania; 2Department of Medical Genetics, Faculty of Medicine, “Iuliu Hatieganu” University of Medicine and Pharmacy, Cluj-Napoca, Romania; 3 Regional Institute of Gastroenterology and Hepatology, “Iuliu Hatieganu” University of Medicine and Pharmacy, Cluj-Napoca, Romania; 4 Medical Imaging Department, “Iuliu Hatieganu” University of Medicine and Pharmacy, Cluj-Napoca, Romania.
Simulation of PEM fuel cells by OpenFOAM

Proton exchange membrane (PEM) fuel cells are known as environmental friendly energy conservation device, and have the potential to be suitable alternative power sources. The cost and durability of a PEM fuel cell are strongly affected by the involved transport phenomena and reactions and there are two of the major challenges to be overcome before commercialization. Modeling and simulation are crucial for the cell design and optimization and various “add-on” fuel cell modules are available in commonly-used commercial CFD codes: FLUENT, STAR-CD and COMSOL Multiphysics. However, the length scale of a PEM fuel cell’s main components ranges from the micro over meso to the macro level. The various transport processes at different scales sometimes cannot be simulated simultaneously by these codes. On the other hand, physical properties of materials used in MEA (membrane electrolyte assembly, consisting of catalyst layers, gas diffusion layers and membrane) play an important role on the cell performance. Therefore coupling the multiscale structural and transport characteristics of the materials will be the most effective way to understand the electrochemical reactions and transient transport phenomena in PEM fuel cell. OpenFOAM (Open Field Operation and Manipulation) is an open source finite volume code and has an object-oriented design written in C++, which allows implementing own models and numerical algorithms. Furthermore, it is possible to insert other models, e.g., particlebased models, to the OpenFOAM CFD Toolbox. Thus OpenFOAM has the potential to meet the requirements faced in PEM fuel cell simulations as mentioned above. In this paper, various literatures simulated by OpenFOAM are outlined and reviewed. The potential methods and challenges coupling OpenFOAM with other modeling techniques are also discussed and highlighted.
Economic Transition and Private-Sector Labor Demand: Evidence from Urban China

This paper studies the policy determinants of economic transition and estimates the demand for labor in the infant private sector in urban China. We show that a reform that untied access to housing in urban areas from working for the state sector accounts for more than a quarter of the overall increase in labor supply to the private sector during 1986-2005. Using the reform to instrument for private-sector labor supply, we find that private-sector labor demand is very elastic. We provide suggestive evidence that the reform equalized wages across sectors and reduced private-sector rents.
Endogeneity in Quantile Regression Models: A Control Function Approach

This paper considers a linear triangular simultaneous equations model with conditional quantile restrictions. The paper adjusts for endogeneity by adopting a control function approach and presents a simple two-step estimator that exploits the partially linear structure of the model. The first step consists of estimation of the residuals of the reduced-form equation for the endogenous explanatory variable. The second step is series estimation of the primary equation with the reduced-form residual included nonparametrically as an additional explanatory variable. This paper imposes no functional form restrictions on the stochastic relationship between the reduced-form residual and the disturbance term in the primary equation conditional on observable explanatory variables. The paper presents regularity conditions for consistency and asymptotic normality of the two-step estimator. In addition, the paper provides some discussions on related estimation methods in the literature and on possible extensions and limitations of the estimation approach. Finally, the numerical performance and usefulness of the estimator are illustrated by the results of Monte Carlo experiments and two empirical examples, demand for fish and returns to schooling.
Coupling characteristics and control of dual mechanical port machine with spoke type permanent magnet arrangement

Dual mechanical port machine(DMPM), as a novel electromechanical energy conversion device, has attracted widespread attention. DMPM with spoke type permanent magnet arrangements(STPM-DMPM), which is one of several types of DMPM, has been of interest recently. The unique coupling characteristics of STPM-DMPM are beneficial to improving system performance, but these same characteristics increase the difficulties of control. Now there has been little research about the control of STPM-DMPM, and this has hindered its practical application. Based on a mathematical model of STPM-DMPM, the coupling characteristics and the merits and demerits of such devices are analyzed as applied to a hybrid system. The control strategies for improving the disadvantages and for utilizing the advantage of coupling are researched. In order to weaken the interaction effect of torque outputs in the inner motor and the outer motor that results from coupling in STPM-DMPM, a decoupling control method based on equivalent current control is proposed, and independent torque control for the inner motor and outer motor is achieved. In order to solve address the problem of adequately utilization of coupling, minimizing the overall copper loss of the inner motor and the outer motor of STPM-DMPM is taken as the optimization objective for optimal control, and the purpose of utilizing the coupling adequately and reasonably is achieved. The verification tests of the proposed decoupling control and optimal control strategies are carried out on a prototype STPM-DMPM, and the experimental results show that the interaction effect of torque outputs in the inner motor and the outer motor can be markedly weakened through use of the control method. The overall copper loss of the inner motor and the outer motor can be markedly reduced through use of the optimal control method, while the power output remains unchanged. A breakthrough in the control problem of STPM-DMPM is accomplished by combining the control methods. Good performance in the control of STPM-DMPM will enhance its practicality, particularly as applied to hybrid systems.
Diffie-Hellman Protocol Based on Elgamal and AES Cryptosystems

This paper presents a communication scheme design for securing messages through local area networks (LAN). This scheme implements a hybrid cryptosystem which is formed by AES-256 in its symmetric part and ElGamal for encryption of keys where the prime has 400 digits and 200 digits for the alpha primitive. It also applies the Diffie-Hellman protocol for key secure distribution. This implementation is targeted at senior management members or groups of any corporate trust where the number of users is small. Key distribution requires a number equal to the number of rounds for at least one user.
New Assessment Technology for the Diagnosis & Control of Salinity in Irrigated Lands

A practical methodology for appraising soil salinity and assessing the adequacy and appropriateness of irrigation, drainage and salinity-control systems and practices is described. This methodology is based upon the use of geophysical-instrumental systems for intensively measuring bulk soil electrical conductivity within irrigated fields/rootzones and associated spatial coordinates, algorithms for multilinear regression data analysis and sensor calibration, and methods for selecting measurement-sites and obtaining salinity ground-truth. The technology package is unique and represents a breakthrough in our ability to rapidly and accurately assess soil salinity in irrigated lands. Results are presented to demonstrate the utility of the technology along with evidence supporting the conclusion that much of the apparent chaos observed in the spatial pattern of soil salinity in irrigated fields is man-induced and explainable in terms of deterministic processes caused by such management practices as irrigation, drainage, cultivation and tillage.
Using satellite radar backscatter to predict above‐ground woody biomass: A consistent relationship across four different African landscapes

Regional‐scale above‐ground biomass (AGB) estimates of tropical savannas and woodlands are highly uncertain, despite their global importance for ecosystems services and as carbon stores. In response, we collated field inventory data from 253 plots at four study sites in Cameroon, Uganda and Mozambique, and examined the relationships between field‐measured AGB and cross‐polarized radar backscatter values derived from ALOS PALSAR, an L‐band satellite sensor. The relationships were highly significant, similar among sites, and displayed high prediction accuracies up to 150 Mg ha−1 (±∼20%). AGB predictions for any given site obtained using equations derived from data from only the other three sites generated only small increases in error. The results suggest that a widely applicable general relationship exists between AGB and L‐band backscatter for lower‐biomass tropical woody vegetation. This relationship allows regional‐scale AGB estimation, required for example by planned REDD (Reducing Emissions from Deforestation and Degradation) schemes.
The role of fiscal sustainability in enhancing sustainable economic growth in South Asia: the case of Bangladesh

The present paper examines the role of fiscal sustainability in achieving sustainable economic growth in the context of South Asia. Excessive government debts have long-term implications and can cause serious intergenerational consequences. In this paper, the role of fiscal sustainability is discussed and the concept of a "just tax system" is analysed. Such a tax system can play an important role in achieving economic growth that is sustainable, rather than being focused on short-term gain. Using the case of Bangladesh, the paper highlights some of the key imminent challenges to transforming a tax system to be more equitable and fair. It finds that current taxation systems are based on short-term frameworks and can leave future generations with the ultimate burden of dealing with the limitations of those systems. Based on the case study, which supports those facts, policymakers in South Asian countries could integrate longterm measures to ensure fiscal sustainability in achieving sustainable economic development.
ENHANCING DBPEDIA QUALITY USING MARKOV LOGIC NETWORKS

The linked data in the Web may be incomplete due to be extracted from semi-structured sources such as Wikipedia, or unstructured such as text. There are various approaches aim to complete the missing data in the linked data sets, including the statistical distributions of properties and types for enhancing the quality of incomplete and noisy Linked Data sets, which obtained good results. In this study, we suggest using of Markov logic networks to improve the quality of the unstructured Linked Data sets without using any external knowledge. Markov Logic Networks (MLNs) is considered one of the most known and proposed methods in the field of Statistical Relational Learning (SRL). It is a first order knowledge base with attaching a weight to each formula. Markov Logic Networks generalize the First order Logic and attach a weight to each equation. Therefore, we rely on RDF(S) and its associating entailment rules which provide a data representation model. We carry out reasoning by transforming the statements and constraints to Markov Logic and compute the most probable consistent state with respect to the defined constraints. Results showed that the proposed algorithm could infer on correct types which the algorithm SDType couldn't. As well, the results were remarkably improved at increasing the number of the steps.
Non-linear Pricing on Information Structure with Application in Platform Design

We study an optimal pricing problem for an intermediary through which transactions between a monopoly and the consumers take place and consumers receive information about the commodity. The intermediary can provide information to the consumers and charge the monopoly accordingly. We characterize the optimal menus and show that a menu consisting of (garbled) upper censorship that displays negative targeting feature is optimal and that surplus reduces comparing to a benchmark where the monopoly has control of the information technology.
Hairy stalagmites, a new biogenic root speleothem from Botswana

(Hill & Forti, 1997). Today, it’s generally accepted that plants (mainly roots) can passively advance the development of speleothems by enhancing capillary migration of water to structures where evaporation occurs (Forti, 2001). Also, it has recently been shown that microbial communities can actively influence the genesis and development of certain subaqueous and/ or vadose speleothems (Melim et al., 2001; Barton & Northup, 2007; Dodge-Wan & Deng Hui Min, 2013). Roots are the single portion of a tree which may somehow contribute towards speleothem development, however, it is presumably rare in deeper parts of caves since roots generally do not reach depths greater than several metres. Nevertheless, the morphological effects induced by roots over speleothems are evident. The surfaces of roots that enter cave voids may serve as pathways for the flow of seeping water and, if environmental conditions are favourable, the precipitation of CaCO3 (calcium carbonate). This mechanism causes the development of peculiar stalactites and columns with a tilted and
Quasiparticles and excitons for the Pfaffian quantum Hall state

We propose trial wave functions for quasiparticle and exciton excitations of the Moore-Read Pfaffian fractional quantum Hall states, both for bosons and for fermions, and study these numerically. Our construction of trial wave functions employs a picture of the bosonic Moore-Read state as a symmetrized double layer composite fermion state. We obtain the number of independent angular momentum multiplets of quasiparticle and exciton trial states for systems of up to 20 electrons. We find that the counting for quasielectrons at large angular momentum on the sphere matches that expected from the conformal field theory (CFT) that describes the Moore-Read state's boundary theory. In particular, the counting for quasielectrons is the same as for quasiholes, in accordance with the idea that the CFT describing both sides of the Fractional Quantum Hall plateau should be the same. We also show that our trial wave functions have good overlaps with exact wave functions obtained using various interactions, including second Landau level Coulomb interactions and the three-body delta interaction for which the Pfaffian states and their quasiholes are exact ground states. We discuss how these results relate to recent work by Sreejith et al. on a similar set of trial wave functions for excitations over the Pfaffian state as well as to earlier work by Hansson et al., which has produced trial wave functions for quasiparticles based on conformal field theory methods and by Bernevig and Haldane, which produced trial wave functions based on clustering properties and ``squeezing. ''
Modified Histogram Based Contrast Enhancement using Homomorphic Filtering for Medical Images

In medical image processing, low contrast image analysis is a challenging problem. In digital image processing contrast enhancement techniques are an important techniques for both human and computer vision. Low contrast digital images reduce the ability of observer in analyzing the image. Histogram based techniques are used to enhance contrast of all type of medical images. Histogram Equalization (HE) is one of the simplest and effective technique to perform contrast enhancement. In histogram equalization we reduce the number of gray levels by combining two or more less frequent neighboring gray levels in one gray level; also we stretch high frequent intensities over high range of gray levels to achieve comparatively more flat histogram. This flattering causes the overall enhancement of contrast of the input image. In histogram equalization we do not have any mechanism to control the enhancement level, due to this sometime output image have over enhanced regions. we propose a new method named “Modified Histogram Based Contrast Enhancement using Homomorphic Filtering" (MH-FIL) for medical images. This method uses two step processing, in first step global contrast of image is enhanced using histogram modification followed by histogram equalization and then in second step homomorphic filtering is used for image sharpening, this filtering if followed by image normalization. To evaluate the effectiveness of our method we choose two widely used metrics Absolute Mean Brightness Error (AMBE) and Entropy. Based on results of these two metrics this algorithm is proved as a flexible and effective way for medical image enhancement and can be used as a pre-processing step for medical image understanding and analysis.