Miracle-dz/UniFAR-FTUs huggingface dataset:
Agricultural Trade Bias in Exchange Rate Volatility Effect Estimation: An Application of Meta-Regression Analysis

Econometric estimates of the effect of exchange rate volatility on international trade are mixed and often wildly divergent, resulting in an ambiguous average effect. It is hypothesized that agricultural trade in particular is more sensitive to exchange rate volatility resulting in more consistent effect estimates. Meta-regression analysis is performed on a sample of 351 econometric exchange rate effect estimates, controlling for study specific characteristics including identification of agricultural sector studies. Results indicate that agricultural trade studies report more consistently significant and negative estimates than non-agriculture or aggregate trade studies, revealing a less ambiguous effect in this sector.
Interactive Query-Based Debugging of ASP Programs

Broad application of answer set programming (ASP) for declarative problem solving requires the development of tools supporting the coding process. Program debugging is one of the crucial activities within this process. Modern ASP debugging approaches allow efficient computation of possible explanations of a fault. However, even for a small program a debugger might return a large number of possible explanations and selection of the correct one must be done manually. In this paper we present an interactive query-based ASP debugging method which extends previous approaches and finds the preferred explanation by means of observations. The system automatically generates a sequence of queries to a programmer asking whether a set of ground atoms must be true in all (cautiously) or some (bravely) answer sets of the program. Since some queries can be more informative than the others, we discuss query selection strategies which - given user's preferences for an explanation - can find the most informative query reducing the overall number of queries required for the identification of a preferred explanation.
Energy efficient clustering algorithm for WSN

Wireless Sensor Networks (WSNs) in recent years have become prominent research areas with an immense effect on practical application developments. It consist of huge quantity of minute sensor nodes connected all the way through wireless medium that are used for sensing the environment and collecting information correctly. Due to resource constrained environment of sensor nodes, a number of issues have come out; network connectivity and energy consumption are the significant topic of concern. From power consumption perspective in Wireless Sensor Networks (WSNs), path routing for nodes is a difficult and tricky task. Clustering techniques in routing protocols play a crucial role to increase the stability and network lifetime. To reduce the energy consumption and increase the network connectivity, we proposed a novel routing algorithm for WSNs. The proposed routing algorithm is based on static clustering concept and dynamic cluster heads (CHs) selection technique, which divides the entire network area into a number of fixed regions. CHs are selected on the basis of residual energy, degree (number of surrounding nodes) and the distance of the sensor node from the sink. Simulation results show that our protocol outperform its counterpart routing protocols LEACH, LEACH-C and DR protocol in terms of network connectivity and power consumption.
Risk Pooling, Commitment, and Information: An experimental test of two fundamental assumptions

This paper presents rigorous and direct tests of two assumptions relating to limited commitment and asymmetric information that current underpin current models of risk pooling. A specially designed economic experiment involving 678 subjects across 23 Zimbabwean villages is used to solve the problems of observability and quantification that have frustrated previous attempts to conduct such tests. I find that more extrinsic commitment is associated with more risk pooling, but that more information is associated with less risk pooling.The first of these results accords with our expectations and assumptions.The second does not. I offer two explanations as to the origin of the second result and discuss their implications for how we view the assumptions made elsewhere in the literature. I also conduct a test of the relevance or external validity of the experimental results to our understanding of real risk pooling behaviour. In four out of the five villages for which the test could be conducted the networks of risk pooling contracts constructed during the experiment and the networks existing in real life were significantly correlated.
Understanding Program Dependencies

This paper reports on an experiment in trying to understand an unfamiliar program of some complexity and to record the authors’ understanding of it. The goal was to simulate a practicing programmer in a program maintenance environment using the techniques of program design adapted to program understanding and documentation; that is, given a program, a specification and correctness proof were developed for the program. The approach points out the value of correctness proof ideas in guiding the discovery process. Toward this end, a variety of techniques were used: direct cognition for smaller parts, discovering and verifying loop invariants for larger program parts, and functions determined by additional analysis for larger program parts. An indeterminate bounded variable was introduced into the program documentation to summarize the effect of several program variables and simplify the proof of correctness. Basili90 Basili, Victor. “Viewing Maintenance as Reuse-Oriented Software Development. ” IEEE Software 7, 1 (Jan. 1990), 19-25.
Facial expressions as game input with different emotional feedback conditions

We propose a game design approach that utilizes facial expressions as an input method under different emotional feedback configurations. A study was conducted in a shopping centre to assess our game "EmoFlowers" focusing on user experience and user effectiveness. The study revealed that interaction with a game via facial expression is perceived naturally, is easy to learn, and provides a positive user experience.
Direct Analysis of Spectra of the Peculiar Type Ia Supernova 2000cx

The Type Ia supernova (SN) 2000cx exhibited multiple peculiarities, including a lopsided B-band light-curve peak that does not conform to current methods for using shapes of light curves to standardize SN Ia luminosities. We use the parameterized SN synthetic-spectrum code SYNOW to study line identifications in the photospheric-phase spectra of SN 2000cx. Previous work established the presence of Ca II infrared triplet features forming above velocity ~20,000 km s-1, much higher than the photospheric velocity of ~10,000 km s-1. We find Ti II features forming at the same high velocity. High-velocity line formation is partly responsible for the photometric peculiarities of SN 2000cx: for example, B-band flux blocking by Ti II absorption features that decreases with time causes the B light curve to rise more rapidly and decline more slowly than it otherwise would. SN 2000cx contains an absorption feature near 4530 Å that may be Hβ, forming at the same high velocity. The lack of conspicuous Hα and Paα signatures does not necessarily invalidate the Hβ identification if the high-velocity line formation is confined to a clump that partly covers the photosphere and the Hα and Paα source functions are elevated relative to that of resonance scattering. The Hβ identification is tentative. If it is correct, the high-velocity matter must have come from a nondegenerate companion star.
Mass transfer during low-mass X-ray transient decays

The outbursts of low-mass X-ray binaries are prolonged relative to those of dwarf nova cataclysmic variables as a consequence of X-ray irradiation of the disc. We show that the time-scale of the decay light curve and its luminosity at a characteristic time are linked to the radius of the accretion disc. Hence, a good X-ray light curve permits two independent estimates of the disc radius. We apply this to a number of sources: 4U 1543–475, SAX J1808.4–3658, XTE J1751–305, XTE J0929–314, XTE J1807–294, GRO J1744–28, GX339–4, XTE J1550–564, GRO J1655–40 and 4U 1705–44. In the case of the millisecond pulsars SAX J1808.4−3658 and XTE J0929−314, the agreement between these estimates is very strong. Our analysis allows new determinations of distances and accretion disc radii. Our analysis will allow determination of accretion disc radii for sources in external galaxies, and hence constrain system parameters where other observational techniques are not possible. We also use the X-ray light curves to estimate the mass transfer rate. The broken exponential decay observed in the 2002 outburst of SAX J1808.4−3658 may be caused by the changing self-shadowing of the disc.
Applicability of MIMO to satellite communications

This paper presents achievements of an on‐going activity where the applicability of MIMO to satellite communications with Digital Video Broadcasting – Satellite services to Handhelds as the key application is studied. The potential satellite and hybrid satellite‐terrestrial MIMO scenarios are described, and the applicable MIMO schemes for each scenario are selected. The performance of the MIMO schemes was studied by performing comprehensive computer simulations, and the main results are presented in this paper. Copyright © 2013 John Wiley & Sons, Ltd.
Testing for Long Memory and Nonlinear Time Series: A Demand for Money Study

This paper draws attention to the limitations of the standard unit root/cointegration approach to economic and financial modelling, and to some of the alternatives based on the idea of fractional integration, long memory models, and the random field regression approach to nonlinearity. Following brief explanations of fractional integration and random field regression, and the methods of applying them, selected techniques are applied to a demand for money dataset. Comparisons of the results from this illustrative case study are presented, and conclusions are drawn that should aid practitioners in applied time-series econometrics.
Contrast invariant registration of images

We propose a method for image registration which seems to be useful under the three following conditions. First, both images are globally and roughly the result of a translation and rotation. Second, some occlusions due to moving objects occur from image 1 to image 2. Third, because of changes of illumination, contrast may have changed globally and even locally. Under such unfavorable conditions, correlation-based global registration may become inaccurate, because of the global compromise it yields between several displacements. Our method avoids these difficulties by defining a set of local contrast invariant features in order to achieve contrast invariant matching. A voting procedure allows one to eliminate "wrong" matching features due to the displacement of small objects and yields sub-pixel accuracy. This method was tested successfully for registration of watches with moving hands and for road control applications.
Celastrus orbiculatus extract triggers apoptosis and autophagy via PI3K/Akt/mTOR inhibition in human colorectal cancer cells

Celastrus orbiculatus is used as a folk medicine in China for the treatment of numerous diseases. The ethyl acetate extract of Celastrus orbiculatus (COE) also displays a wide range of anti-cancer activities in the laboratory. However, the effectiveness of COE-induced autophagy and its mechanism of action in colorectal cancer cells have not been investigated thus far. The present study analyzed the effect of COE on HT-29 cell viability, apoptosis and autophagy using MTT assay, flow cytometry, transmission electron microscopy and western blotting. Additionally, the autophagy inhibitor 3-methyladenine and the autophagy inducer rapamycin were used to further explore the effects of COE-induced autophagy in HT-29 cells. The present study also examined whether the phosphatidylinositol-4,5-bisphosphate 3-kinase (PI3K)/Akt/mechanistic target of rapamycin (mTOR)/p70 ribosomal protein S6 kinase (p70S6K) signaling pathway was involved in the regulation of COE-induced autophagy. The results revealed that COE inhibited HT-29 cell proliferation and decreased cell survival in a time- and dose-dependent manner, and that COE possessed the ability to induce both apoptosis and autophagy in HT-29 cells. Furthermore, autophagy and apoptosis induced by COE synergized to inhibit colorectal cancer growth. In addition, COE treatment decreased the phosphorylation of Akt and its downstream effectors mTOR and p70S6K. Taken together, these results demonstrate that both autophagy and apoptosis were activated during COE treatment of HT-29 cells, and that COE-induced autophagy decreases the viability of HT-29 cells via a mechanism that may depend on the PI3K/Akt/mTOR/p70S6K signaling pathway. Furthermore, compounds that induce autophagy administered in combination with COE may be an attractive strategy for enhancing the anti-tumor potency of COE in colorectal cancer.
Exploiting Process Locality of Reference in RTL Simulation Acceleration

With the increased size and complexity of digital designs, the time required to simulate them has also increased. Traditional simulation accelerators utilize FPGAs in a static configuration, but this paper presents an analysis of six register transfer level (RTL) code bases showing that only a subset of the simulation processes is executing at any given time, a quality called executive locality of reference. The efficiency of acceleration hardware can be improved when it is used as a process cache. Run-time adaptations are made to ensure that acceleration resources are not wasted on idle processes, and these adaptations may be affected through process migration between software and hardware. An implementation of an embedded, FPGA-based migration system is described, and empirical data are obtained for use in mathematical and algorithmic modeling of more complex acceleration systems.
Impedance-Based Analysis of Active Frequency Drift Islanding Detection for Grid-Tied Inverter System

Islanding detection is critical to the safety of grid-tied inverters. This paper presents an impedance-based analysis of the active frequency drift (AFD) islanding detection method. To study this method, the output impedance of a grid-tied inverter is modeled. The Zqq of the inverter impedance features a negative incremental resistor, whose magnitude is equal to the dc impedance magnitude of the local load defined by the test standard. With a large value of feedforward gain N in the AFD method, the phase of Zqq is shown to drop below 180°. Under an islanding condition, due to a lack of phase margin, the inverter system becomes unstable with a frequency drift away from its steady state. The islanding condition is then identified by a frequency detection unit. Experimental results verify the analysis.
An Empirical Study on Factors Affecting Customer Intention in Mobile Commerce Contexts

With the good customer foundation and increasing revenue, m-commerce is on the growing development stage. Although there are many literatures about the factors affecting customer intention in internet-based e-commerce contexts, it is necessary to do an empirical validation in m-commerce contexts. Factors of trust and social influence integrated to TAM were used in the conceptual model. Empirical data in the method of questionnaire collected from university students were analyzed to exam the relationship between these factors and customer intention. Results from CFA and SEM showed all of the factors had a positive effect on intention, in which trust had the strongest effect on intention. The findings have practical implications for m-commerce vendors from a consumer point of view.
Breast tissue segmentation on MR images using KFCM with spatial constraints

Accurate segmentation of breast on MR images is an essential and crucial step for computer-aided breast disease diagnosis and surgical planning. In this paper, an effective approach is proposed for segmenting the breast image into different regions, each corresponding to a different tissue. The segmentation work flow comprises two key steps. Firstly, we use the threshold-based method and morphological operations to determine the breast-air boundary and breast-chest wall so that the breast region can be extracted. Then a kernelled fuzzy C-means algorithm with spatial information (SKFCM) is used to separate the fibroglandular tissues from the fat. The proposed method is used to segment the clinical breast MR images. Experimental results have been shown visually and achieve reasonable consistency. The SKFCM method is appropriate for the problem of breast tissue segmentation.
Deriving an ontology for human gene expression sources from the CYTOMER? database on human organs and cell types

CYTOMER is a relational database of organs/tissues, cell types, physiological systems and developmental stages that currently focuses on the human system. From this database, we have derived an ontology for anatomical and morphological structures for the human organism which includes all embryonal stages and the cell types constituting these structures. The ontology has been transferred to the OWL format and is freely available for download at http://cytomer/bioinf.med.uni-goettingen.de.
Visual hull surface estimation

This paper describes a technique used to approximate the surface of an object’s visual hull. The hull’s basic structure is initially represented by a partitioned 3D space using voxels. The marching cubes algorithm then assigns polygonal patches to surface voxels depending on a certain criteria. It is less computationally intensive to manipulate a few triangular patches than a number of six-faced voxels. The visual hull model is further refined by applying a binary search to the vertices of each surface that improves the positional accuracy of each vertex. The method is applied to a small plastic cat using a 5-camera system and results are shown.
Voice conversion using conditional restricted Boltzmann machine

In this paper, we proposed a new method for voice conversion using conditional restricted Boltzmann machine (Conditional RBM, CRBM). The joint distribution of source and target acoustic features are modeled by the RBM part of the model. Short-term temporal constraints are introduced by conditioning on contextual frames, say, the past and future frames of the source speaker. In contrast to conventional methods, temporal structure of the data could be modeled without using dynamic features. Objective and subjective experiments were conducted to evaluate the method. Experimental results show that short-term temporal structure could be modeled well by CRBM, and the proposed method outperforms conventional joint density Gaussian mixture models based method significantly.
Effects of thalidomide on angiogenesis and tumor growth and metastasis of human hepatocellular carcinoma in nude mice.

AIM To investigate the effects of thalidomide on angiogenesis, tumor growth and metastasis of hepatocellular carcinoma in nude mice. METHODS Twenty-four nude mice were randomly divided into therapy group and control group, 12 mice in each group. Thalidomide dissolved in 0.5% sodium carboxyl methyl cellulose (CMC) suspension was administered intraperitoneally once a day at the dose of 200 mg/kg in therapy group, and an equivalent volume of 0.5% CMC in control group. Mice were sacrificed on the 30th d, tumor size and weight and metastases in liver and lungs were measured. CD34 and VEGF mRNA in tumor tissue were detected by immunohistochemistry and semi-quantitative RT-PCR respectively and microvessel density (MVD) was counted. Serum concentrations of TNF-alpha and ALT and AFP were also tested. RESULTS MVD and VEGF mRNA in therapy group were less than those in control group (31.08+/-16.23 vessels/HP vs 80.00+/-26.27 vessels/HP, 0.0538+/-0.0165 vs 0.7373+/-0.1297, respectively, P<0.05). No statistical difference was observed in tumor size and weight and metastases in liver and lungs. TNF-alpha was significantly lower in therapy group than in control group (28.64+/-4.64 ng/L vs 42.69+/-6.99 ng/L, P<0.05). No statistical difference in ALT and AFP was observed between groups. CONCLUSION Thalidomide can significantly inhibit angiogenesis and metastasis of hepatocellular carcinoma. It also has inhibitory effects on circulating TNF-alpha.
Benchmarking model for reverse logistics entry by third-party providers

Reverse logistics has gradually become a very important economic activity in 21 century. In general, in addition to retrieval, transportation and disposition as three distinct reverse logistics activities, value-added services such as JIT, quick response, program solutions are most important. The entry of third-party providers for reverse logistics is to strengthen core competences, lower costs and operating risks as well as improve competitiveness of the supply chain. Since reverse logistics is much more specialized, it's not easy for a third-party provider to enter the reverse logistics market. Benchmarking is one of the most important management methodologies for a company's decision-making. The benchmarking decision-making model is composed of six key steps: research of existing reverse logistics issues and identification of customers, survey of existing repeat customer needs, survey of competitors and competitors' customers, gap analysis, feasibility studies and development of positioning strategy. This model puts insights into Chinese third-party logistics providers who would like to pursue reverse logistics as a new market.
A Sampling Filter for Non-Gaussian Data Assimilation

Data assimilation combines information from models, measurements, and priors to estimate the state of a dynamical system such as the atmosphere. The Ensemble Kalman filter (EnKF) is a family of ensemble-based data assimilation approaches that has gained wide popularity due its simple formulation, ease of implementation, and good practical results. Most EnKF algorithms assume that the underlying probability distributions are Gaussian. Although this assumption is well accepted, it is too restrictive when applied to large nonlinear models, nonlinear observation operators, and large levels of uncertainty. Several approaches have been proposed in order to avoid the Gaussianity assumption. One of the most successful strategies is the maximum likelihood ensemble filter (MLEF) which computes a maximum a posteriori estimate of the state assuming the posterior distribution is Gaussian. MLEF is designed to work with nonlinear and even non-differentiable observation operators, and shows good practical performance. However, there are limits to the degree of nonlinearity that MLEF can handle. This paper proposes a new ensemble-based data assimilation method, named the "sampling filter", which obtains the analysis by sampling directly from the posterior distribution. The sampling strategy is based on a Hybrid Monte Carlo (HMC) approach that can handle non-Gaussian probability distributions. Numerical experiments are carried out using the Lorenz-96 model and observation operators with different levels of non-linearity and differentiability. The proposed filter is also tested with shallow water model on a sphere with linear observation operator. The results show that the sampling filter can perform well even in highly nonlinear situations were EnKF and MLEF filters diverge.