Miracle-dz/UniFAR-FTUs huggingface dataset:
Imaging Techniques for Evaluation of Drug Distribution in Solid Tumor

Imaging drug distribution inside a tumor is an important tool to support strategies to improve penetration of anticancer drugs and consequently the outcome of chemotherapy. Methods for mapping the distribution of pharmaceutical compounds and their metabolites in situ are of great interest to researchers and to the pharmaceutical industry. There is a particular interest in the distribution of anti-cancer agents within solid tumors. Direct assessment of the distribution of drugs in tumor tissue is technically challenging, and requires the quantification of drug exposure to cells at specific locations relative to blood vessels. The quantification of drugs in plasma, as well as in tissue homogenates, has relied extensively on well-established analytical methods of high-performance liquid chromatography (HPLC) and liquid chromatography–tandem mass spectrometry (LC-MS-MS). In the last 20 years, imaging techniques such as positron emission tomography (PET), magnetic resonance spectroscopy (MRS), mass spectrometry imaging (MSI), fluorescence microscopy (FM), and autoradiography have evolved as powerful tools for the noninvasive study of drug distribution in vivo as well as for studying drug effects at their target sites. In this article, we review the current state of knowledge of the available imaging techniques to measure intratumor drug
A COMPARATIVE STUDY OF ASSOCIATION RULE MINING TECHNIQUES AND PREDICTIVE MINING APPROACHES FOR ASSOCIATION CLASSIFICATION

: Association Rule Mining ( ARM) and classification are integrated together to build competitive classifier models called Associative Classifiers and this approach is known as Association Classification (AC). AC leads to the formation of accurate classifier consisting of significant rules capable of predicting the class of the data. This paper presents the evolution of ARM to AC highlighting the development and improvements in ARM techniques followed by AC techniques. The goal of this paper is to survey and understand different ARM and AC techniques and comparing their performance. In the literature a variety of AC algorithms have be proposed such as CBA, CMAR, MCAR, CPAR etc each adopting some or the other approach for rule learning in the initial stages. This paper also presents the importance of the rule pruning methodology with the brief survey of different methods discussed in the literature. This paper also enlightens the learning approaches adopted by different AC techniques in different domains.
Where does Earth’s atmosphere get its energy?

The Sun is Earth’s primary source of energy. In this paper, we compare the magnitude of the Sun to all other external (to the atmosphere) energy sources. These external sources were previously identified in ; here, we quantify and update them. These external sources provide a total energy to the Earth that is more than 3700 times smaller than that provided by the Sun, a vast majority of which is provided by heat from the Earth’s interior. After accounting for the fact that 71% of incident solar radiation is deposited into the earth system, the Sun provides a total energy to Earth that is still more than 2600 times larger than the sum of all other external sources.
An analysis of vulnerability and the method to secure on Android SNS applications from alteration of the code segments

According to the rapid growth of the number of SNS(Social Networking Service) applications based on Android OS, the importance of its security is also raised. Especially, many applications using KaKaoTalk platform has been released in these days, and these are top ranked in the relative markets. However, security issues on SNS applications have not been resolved clearly. Therefore, it is crucial to provide means to cope with the security threats posed by code-segment modification in the development stage of Android OS based SNS applications. In this paper, we analyze the security threats by modifying SNS application code segments and suggest effective security techniques.
Differential uses of okay, right, and alright, and their function in signaling perspective shift or maintenance in a map task

L'A. propose une etude des marqueurs du discours anglais okay, right, alright et de leurs fonctions. Comment ces trois marqueurs different-ils les uns des autres, et comment les locuteurs les utilisent-ils pour signaler un changement de direction dans le contexte particulier d'une interaction dont le but est d'indiquer un itineraire a quelqu'un sur une carte. L'A. propose alors une approche fonctionnelle de ces trois marqueurs et utilise des outils d'analyse de conversation pour mettre a jour les strategies utilisees dans les descriptions spatiales.
Combining satellite radar altimetry, SAR surface soil moisture and GRACE total storage changes for hydrological model calibration in a large poorly gauged catchment

Abstract. The availability of data is a major challenge for hydrological modelling in large parts of the world. Remote sensing data can be exploited to improve models of ungauged or poorly gauged catchments. In this study we combine three datasets for calibration of a rainfall-runoff model of the poorly gauged Okavango catchment in Southern Africa: (i) surface soil moisture (SSM) estimates derived from radar measurements onboard the Envisat satellite; (ii) radar altimetry measurements by Envisat providing river stages in the tributaries of the Okavango catchment, down to a minimum river width of about one hundred meters; and (iii) temporal changes of the Earth's gravity field recorded by the Gravity Recovery and Climate Experiment (GRACE) caused by total water storage changes in the catchment. The SSM data are shown to be helpful in identifying periods with over-respectively underestimation of the precipitation input. The accuracy of the radar altimetry data is validated on gauged subbasins of the catchment and altimetry data of an ungauged subbasin is used for model calibration. The radar altimetry data are important to condition model parameters related to channel morphology such as Manning's roughness. GRACE data are used to validate the model and to condition model parameters related to various storage compartments in the hydrological model (e.g. soil, groundwater, bank storage etc.). As precipitation input the FEWS-Net RFE, TRMM 3B42 and ECMWF ERA-Interim datasets are considered and compared.
Exploring emotional response to gesture in product interaction using Laban ’ s 1 movement analysis 2 3

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Liquidity changes around bonus and rights issue announcements: Evidence from manufacturing and service sectors in India

This paper examines the stock price liquidity changes before and after the bonus and rights issue announcements. Liquidity measured using raw trading volume ratio, relative trading volume ratio and liquidity ratio suggest that raw trading volume and relative trading volume have decreased around bonus and rights announcements. Market depth, as measured by the liquidity ratio, has significantly decreased after the bonus and rights issue announcement in the Indian stock market. There is evidence of negative and significant decrease in stock price liquidity for bonus and rights issue announcements similar to other issue announcements in US, UK and other emerging economies. The results support cash substitution hypothesis and signaling theory but rejects liquidity hypothesis with respect to bonus and rights issue announcements.
Performance Analysis of Direct Torque Controlled BLDC motor using Fuzzy Logic

The Brushless DC motor (BLDC) control is used in many of the applications as it is small in size and with low power which can drive in high speed and lighter compared to other motors.The electric vehicles are built with BLDC motors and also in ships, aerospace etc., The control of BLDC motors is done with sensors like hall effect sensor for sensing the positions. The speed control can be done with normal PI and PID controllers. Direct torque control (DTC) of the BLDC motor is important in many applications. In this paper BLDC motor is controlled with DTC using PI, PID and Fuzzy logic control. The comparison of the performance of the motor is analyzed with the Matlab simulation software.
Physiological Signals based Day-Dependence Analysis with Metric Multidimensional Scaling for Sentiment Classification in Wearable Sensors

The interaction of the affective has emerged in implicit human-computer interaction. Given the physiological signals in the recognition process of the affective, the different positions by which the physiological signal sensors are installed in the body, along with the daily habits and moods of human beings, influence the affective physiological signals. The scalar product matrix was calculated in this study based on metric multidimensional scaling with dissimilarity matrix. Subsequently, the matrix of individual attribute reconstructs was obtained using the principal component factor. The method proposed in this study eliminates day dependence, reduces the effect of time in the physiological signals of the affective, and improves the accuracy of affection classification.
High Power Self-Aligned, Trench-Implanted 4H-SiC JFETs

The process technology for the fabrication of 4H-SiC trenched-implanted-gate 4H–SiC vertical-channel JFET (TI-VJFET) has been developed. The optimized TIVJFETs have been fabricated with self-aligned nickel silicide source and gate contacts using a process sequence that greatly reduces process complexity as it includes only four lithography steps. A source-pillars sidewall oxidation and subsequent removal of the metallization from the top of the sidewall oxide ensured isolation between gate and source. Optimum planarization of the source pillars top has been performed by cyclotene spin coating and etch back. The effect of the channel geometry on the electrical characteristics has been studied by varying its length (0.3 and 1.2μm) and its width (1.5-5μm). The voltage blocking exhibits a triode shape, which is typical for a static-induction transistor (SIT) operation. The transistors exhibited high ON current handling capabilities (Direct Current density >1kA/cm2 ) and values of RON ranging from 6 - 12 mΩ•cm2 depending on the channel length. Maximum voltage blocking was 800V limited by the edge termination. The maximum voltage gain was 51. Most transistors were normally-on. Normally-off operation has been observed for transistors lower than 2μm channel width (mask level) and deep implantation.
FIRE SUPPRESSANT DISTRIBUTION IN AN ENGINE NACELLE

The flow inside an engine nacelle ground test simulator is studied for the purpose of understanding and optimizing the distribution of suppressant. One objective of this study is to identify conditions for which suppression will and will not be successful in order to test the model’s ability to discriminate between various scenarios. To do this, the distribution of suppressant during cold flow is studied to identify regions of low concentration. Available measurements are coupled with predictions using Sandia National Laboratories’ Vulcan fire-field model. Some measurements are required to help design the computational model, such as the inlet and outlet flows, which are boundary conditions for the simulation. Specific suppressant-concentration profiles as a function of time are helpful in evaluating the model’s performance. To create scenarios with insufficient distribution in regions of potential fire, the removal or capping of individual agent nozzles is used. The test matrix has been constructed by varying the loci and number of discharge nozzles, the mass of suppressant, and the air flows. Vulcan’s predictions of suppressant-concentration profiles to date are in qualitative agreement with test measurements and show that the suppressant is well-distributed. Empirical Boundary Conditions In the autumn of 2002 tests were conducted on the ground in a full-scale ‘iron bird’ nacelle simulator to determine the distribution of air flows, without fire, across the boundary of the fire test nacelle. [1] (numbers in brackets denote references ). These data were to provide the boundary conditions for the Computational Fluid Dynamic (CFD) and Vulcan models of this nacelle simulator effected by Sandia National Laboratory. It was found that the distribution of 1 This work was conducted at Sandia National Laboratories, a multiprogram laboratory operated by Sandia Corporation, a Lockheed Martin Company, for the United States Department of Energy’s National Nuclear Security Administration under Contract DE-AC04-94AL85000. This research is part of the Department of Defense's Next Generation Fire Suppression Technology Program, funded by the Department of Defense Strategic Environmental Research and Development Program. We also gratefully acknowledge the cooperation of the Naval Air Systems Command, Fire Protection Group in sharing test data for the validation of our models. 2 Corresponding and presenting author: dkeyser@pax.i-n-s.com. 3 jchewso@sandia.gov.
Dynamic Relational Contracts with Credit Constraints

This paper considers a long-term relationship between two agents who undertake costly actions or investments which produce a joint benefit. Agents have an opportunity to expropriate some of the joint benefit for their own use. The question asked is how to structure the investments and division of the surplus over time so as to avoid expropriation. It is shown that investments may be either above or below the efficient level and that actions and the division of the surplus converges to a stationary solution at which either both investment levels are efficient or both are below the efficient level.
Moderator effect of reading proficiency on science performance across 15-year-old boys and girls in the Netherlands, Finland, and Singapore

The major aim of the present study is to investigate students’ science self-efficacy and its relationship with science performance across 15-year-old boys and girls in the Netherlands, Finland and Singapore. On the other hand, whether and in what way students’ reading proficiency moderates the relationship between science self-efficacy and science performance was explored across boys and girls in the three countries Data analysis based on PISA 2015 dataset reveals a significant gender difference in science self-efficacy in favor of boys across the Netherlands, Finland and Singapore. In addition, Dutch girls demonstrate lower science self-efficacy than Finnish girls and Singaporean girls. Significant gender difference in science performance in favor of boys is demonstrated except Finland. Significant gender difference in reading performance in favor of girls is demonstrated across the three countries. A significant and positive relationship between science self-efficacy and science performance was found across 15-year-old boys and girls in the three countries. Moreover, moderator effect of reading proficiency is satisfied across boys and girls in the three countries. As reading proficiency increases, the relationship between science self-efficacy and science performance is strengthened across gender in the three countries.
Evaluating Partnership

Partnerships are increasingly seeking tools that enable stakeholders to reflect on their own effectiveness, benchmark the status of their partnership and provide a framework for development. Drawing on the evaluation of two Health Action Zones, this article focuses on the use of one such formal assessment tool, adapted from the Nuffield Partnership Assessment Tool and the Verona Benchmark, to explore the contribution of formal tools to our understanding of partnership. It outlines some key methodological limitations and stresses the continued importance of an understanding of context alongside any measurement of partnership effectiveness. It is suggested that formal assessment tools can be extremely valuable in terms of the learning that can result both from the process itself and from the outcomes of the assessment. However, as a stand-alone device they are open to misinterpretation and unlikely to foster development other than in those partnerships prepared to invest the necessary resources in a broad-based evaluation.
Issues of Implementing Electronic Supply Chain Management (E-SCM) In Enterprise

The integrated supply chain management with internet and technology brings new innovation management changes in enterprise. It called electronic supply chain management (E-SCM), to be able to reach the maximum result, the implementation of E-SCM need the ability to create, acquire, capture store, maintain and disseminate the organization's knowledge. This paper is literatures study that discussed about the issues related of benefits and constraints on E-SCM implementation in enterprise. Enterprise that implement E-SCM will have a competitive advantages which can be affecting the increase in performance of enterprise also be more sensitive to market environment changes rather than the competitor. This paper findings the success of E-SCM implemented in enterprise need support from knowledge management (KM).
Tourism Product Involvement and Information Search

One of the major factors influencing consumer decisions to purchase a product or service is information sources about the product or service. Awareness of a particular product or service and resulting purchase decisions largely depend on the information consumers are able to gather and the credibility of such information. Often, purchase decisions that are considered risky or about which consumers have more uncertainty result in information search. Travel purchase decisions generally have attributes that encourage consumers to engage in information search. Numerous factors may influence a consumer's information seeking behavior. Several researchers suggest one factor influencing information search is a consumer’s level of product involvement. This purpose of this paper is to investigate the relationship between product involvement and information search with respect to a tourism destination. A survey was conducted with prospective travelers to a destination in the U.S. Results suggest there is a relationship between involvement and information search, with more involved travelers having an interest in more information about a destination.
A latent force model based on the wave equation for describing the electric propagation in deep brain stimulation

Deep brain stimulation is a surgical treatment of Parkinson Disease. Its fundamental purpose is to deliver electrical stimulation in a target brain structure using implanted electrodes, through which voltage or current square pulses are applied to stimulate the surrounding neural tissue. Static models based on the quasi-static approximation are the most common approach used for deep brain stimulation modeling. While this simplification has been validated for bioelectric sources, its application to rapid stimulation pulses, which contain more high-frequency power, may not be appropriate, as therapeutic results of deep brain stimulation are quite dependent on stimulus parameters such as frequency and pulse width, which are related to time variations of the electric field. In this project we propose an alternative hybrid approach based on probabilistic models and partial differential equations, by using Gaussian processes and the wave equation. Our model avoids the quasi-static approximation, moreover, it is able to describe dynamic behavior inherent to deep brain stimulation. Therefore, the proposed model may be used to obtain a more realistic phenomena description. This is quite important because errors induced by the quasi-static assumption may be significant in deep brain simulation context, where 1mm changes in spread of activation can have dramatic consequences on therapeutic effects induced by the stimulation.
An Experimental Analysis of Parallel Multiple Auctions

At online auction platforms we often observed that substitutable goods are auctioned concurrently with auctions ending at the same time. I introduce an experimental setup of three sellers and four buyers in an ascending second price auction environment where every seller runs one auction with a homogeneous good and the buyers are confronted with single unit demand. I find that sellers revenue is significantly lower than theory predicts due to the fact that some auctions did not receive bids whereas other auctions concentrated the bids of all bidders. Moreover, I observe a statistically higher revenue of sellers setting the minimum starting price. Furthermore, my study shows that the buyers submit bids which are significantly lower than the private valuation every buyer receives. Comparing the efficiency of the parallel multiple auction setup to a double auction control experiment, I find a significant lower efficiency in parallel multiple auctions due to the coordination failure of the buyers.
Some Properties for Convolutions of Generalized Hypergeometric Functions

With the convolution products of generalized hypergeometric functions $pqF(z)$ and analytic functions $f(z)$ in the open unit disk, the operator $I_{b_{1},b2}^{a_{1},a2},\cdot’. ,’(b_{\sigma}f)a_{\mathrm{p}}$ is introduced. The object of the present paper is to derive some interesting properties of operator $I_{b_{1},2,l}^{a1}$
Exploring Learning Experience in a Total Enterprise Simulation Based on Means-End Theory

The primary purpose of this study was to obtain empirical evidence and provide a methodological alternative for helping understand how simulation serves to learning. Well-structured system design and unstructured learning implementation bring complexity to dealing with learning in total enterprise simulation, specially, how to investigate learning emanated from the simulation game’s structure and decision-making requirements has studied very few. Due to the multiple aspects of individual learning situation and the inevitable structural design differences in simulations, student authored reports were used as data source to analyze the connections of learning-performance based on means-ends theory and the model was constructed with the components, namely Attributes, Consequences, and Values. With limitations of research, the study provides practical evidence and student insight into logic and structure of the simulated firm experienced, as well as demonstrates the use of means-ends approach for research on the issue of simulation-based learning and performance.
Quasiclassical theory of the dynamical E  ×  E Jahn–Teller effect including spin–orbit interaction

The dynamical Jahn–Teller effect including spin–orbit coupling is considered in the coordinate and momentum representations of the nuclear motion. The momentum representation is used for the asymptotical solution of the dynamical equations in the quasiclassical Landau–Zener parametric limiting case. Vibronic energy levels of the E × E Jahn–Teller effect with spin–orbit coupling are calculated from the quasiclassical secular equation. They are compared with numerically exact energy levels obtained by the diagonalization of the Hamiltonian matrix in a harmonic oscillator basis. The comparison reveals reasonable accuracy of the quasiclassical approximation for a wide range of quantum numbers and system parameters. The quasiclassical analysis provides insight into the nature of the non-adiabatic dynamics of E × E Jahn–Teller systems with spin–orbit coupling.