Miracle-dz/UniFAR-FTUs huggingface dataset:
Cassava Production, Prices and Related Policy in Thailand

The objectives of this study were to compare farmer’s perception regarding different schemes, calculate break even price of cassava production, analyze supply respond of cassava production and analyze co-integration on cassava prices. The paper found that farmers preferred income guarantee scheme to pledging scheme. Since 2003, farm prices had increased above break even price. Supply response of cassava mainly depended on price received in the previous year. This price related to government policy in two different schemes: income guarantee scheme to pledging scheme and cassava used as alternative energy. This study applied co-integration analysis for farm price with wholesale price and F.O. B. price for cassava. Farm price was affected positively by wholesale price and F.O. B. price. The estimated coefficients associated with explanatory variable agreed with a priori expectations, and were statistically significant. Signs of all estimated coefficients agreed with expectations and were statistically significant.
The Pull of the Parties for Immigrants in the United States

Immigrants in the United States frequently express a desire to return to their country of birth, an attitude that could undermine political acculturation and democratic inclusion in the American context. This mindset has been labeled an “ideology of return. ” Drawing from original surveys of the Mexican-born population conducted during the 2006 and 2008 elections, we show that partisan competition during major national campaigns has the potential to pull immigrants towards U.S. civic life and make the prospect of remaining in the country over the long-term a more attractive option.
On Path-Dependent Structured Funds: Complexity Does Not Always Pay (Asian versus Average Performance Funds)

As emphasized by the U.S. Dodd-Frank Act and the European MiFID directive, financial institutions are required to ? categorise their clients and assess their suitability for each type of investment product. In this framework, this paper examines several standard financial structured products whose performances are based on smoothing the return of an underlying risky asset and providing a guarantee at maturity. We use various criteria such as probabilities of providing merely the guarantee at maturity and Kappa measures. Surprisingly, our study reveals that funds based on averages of calls generally do better than Asian funds.
The H3K4 methyltransferase Setd1a is first required at the epiblast stage, whereas Setd1b becomes essential after gastrulation

Histone 3 lysine 4 (H3K4) methylation is a universal epigenetic mark. In mammals, there are six H3K4 methyltransferases related to yeast Set1 and fly Trithorax, including two orthologs of Set1: Setd1a and Setd1b. Here we show that mouse Setd1a is required for gastrulation, whereas Setd1b-deficient embryos survive to E11.5 but are grossly retarded. Setd1a knockout embryos implant but do not proceed past the epiblast. Furthermore, Setd1a is not required until the inner cell mass has formed, at which stage it has replaced Mll2 as the major H3K4 methyltransferase. Setd1a is required for embryonic, epiblast and neural stem cell survival and neural stem cell reprogramming, whereas Setd1b is dispensable. Deletion of Setd1a in embryonic stem cells resulted in rapid losses of bulk H3K4 methylation, pluripotency gene expression and proliferation, with G1 pileup. Setd1b overexpression could not rescue the proliferation defects caused by loss of Setd1a in embryonic stem cells. The precise developmental requirement for Setd1a suggests that gastrulation is regulated by a switch between the major H3K4 methyltransferases.
Practical Applications of Fact, Fiction, and Momentum Investing

Though momentum investing has been around for a long time, it has endured a number of widely held misconceptions. Some common errors are that it works mainly on the short side, that its returns are small and sporadic, that it is limited to small-cap securities, and that it has trading costs that are too high. But investors need to study the academic literature, apply publicly available empirical data and connect the dots: The momentum premium persists. The authors of Fact, Fiction, and Momentum Investing , from The Journal of Portfolio Management’s 40th Anniversary Issue , dispel some of the common misconceptions about momentum investing. Read this Practical Applications report for insights into how to best approach momentum investing.
Sub-band modulation spectrum compensation for robust speech recognition

This paper proposes a novel scheme in performing feature statistics normalization techniques for robust speech recognition. In the proposed approach, the processed temporal-domain feature sequence is first converted into the modulation spectral domain. The magnitude part of the modulation spectrum is decomposed into non-uniform sub-band segments, and then each sub-band segment is individually processed by the well-known normalization methods, like mean normalization (MN), mean and variance normalization (MVN) and histogram equalization (HEQ). Finally, we reconstruct the feature stream with all the modified sub-band magnitude spectral segments and the original phase spectrum using the inverse DFT. With this process, the components that correspond to more important modulation spectral bands in the feature sequence can be processed separately. For the Aurora-2 clean-condition training task, the new proposed sub-band spectral MVN and HEQ provide relative error rate reductions of 18.66% and 23.58% over the conventional temporal MVN and HEQ, respectively.
A rewrite-based computational model for functional logic programming

Functional logic programming extends the functional programming style with two important features: the possibility to define nondeterministic operations with overlapping rules, and the usage of logic variables in both defining rules and expressions to evaluate. Conditional constructor-based term rewrite systems (CB-CTRSs) emerged as a suitable model for functional logic programs, because they can be easily transformed into an equivalent program in a core language where computations can be performed more efficiently. We consider a recent proposal by Antoy and Hanus, of translating CB-CTRSs into an equivalent class of programs where computation can be performed by mere rewriting. His computational model has the limitation of computing only ground answer substitutions for equations with strict semantics interpreted as joinability to a value. We propose two adjustments of their computational models, which are capable to compute non-ground answers.
Comparison of the H+/ATP ratios of the H+-ATP synthases from yeast and from chloroplast

F0F1-ATP synthases use the free energy derived from a transmembrane proton transport to synthesize ATP from ADP and inorganic phosphate. The number of protons translocated per ATP (H+/ATP ratio) is an important parameter for the mechanism of the enzyme and for energy transduction in cells. Current models of rotational catalysis predict that the H+/ATP ratio is identical to the stoichiometric ratio of c-subunits to β-subunits. We measured in parallel the H+/ATP ratios at equilibrium of purified F0F1s from yeast mitochondria (c/β = 3.3) and from spinach chloroplasts (c/β = 4.7). The isolated enzymes were reconstituted into liposomes and, after energization of the proteoliposomes with acid–base transitions, the initial rates of ATP synthesis and hydrolysis were measured as a function of ΔpH. The equilibrium ΔpH was obtained by interpolation, and from its dependency on the stoichiometric ratio, [ATP]/([ADP]·[Pi]), finally the thermodynamic H+/ATP ratios were obtained: 2.9 ± 0.2 for the mitochondrial enzyme and 3.9 ± 0.3 for the chloroplast enzyme. The data show that the thermodynamic H+/ATP ratio depends on the stoichiometry of the c-subunit, although it is not identical to the c/β ratio.
A Comparative Study of Malware Detection Techniques Using Machine Learning Methods

In the past few years, the amount of malicious software increased exponentially and, therefore, machine learning algorithms became instrumental in identifying clean and malware files through (semi)-automated classification. When working with very large datasets, the major challenge is to reach both a very high malware detection rate and a very low false positive rate. Another challenge is to minimize the time needed for the machine learning algorithm to do so. This paper presents a comparative study between different machine learning techniques such as linear classifiers, ensembles, decision trees or various hybrids thereof. The training dataset consists of approximately 2 million clean files and 200.000 infected files, which is a realistic quantitative mixture. The paper investigates the above mentioned methods with respect to both their performance (detection rate and false positive rate) and their practicability. Keywords—Detection Rate, False Positives, Perceptron, One Side Class, Ensembles, Decision Tree, Hybrid methods, Feature Selection.
Quantification of Uncertainty in Creep Failure of RF-MEMS Switches

We present simulations of the failure of radio-frequency micro-electro-mechanical systems switches due to diffusional creep that include the quantification of uncertainty in the geometry, material parameters, and residual stress. The switch is modeled as an Euler–Bernoulli beam that is actuated electrostatically in a fluid medium. The fluid damping is modeled by a squeeze-film model and the beam model incorporates stretching nonlinearity in addition to Coble creep. The resulting nonlinear dynamic model is solved using a Ritz–Galerkin-based modal expansion and explicit time integration. The focus of this paper is on the effect of creep as a failure mechanism and the implications of uncertainty in the device geometry, material parameters, and boundary conditions. The degradation of the device performance is evidenced by decreases in the pull-in voltage, the pull-out voltage, and the impact velocity. We find that the variability in the experimentally measured pull-in voltage is accounted for by the inclusion of uncertainty in the material and geometric properties. [2015-0191]
Real External Predictivity of QSAR Models: How To Evaluate It? Comparison of Different Validation Criteria and Proposal of Using the Concordance Correlation Coefficient

The main utility of QSAR models is their ability to predict activities/properties for new chemicals, and this external prediction ability is evaluated by means of various validation criteria. As a measure for such evaluation the OECD guidelines have proposed the predictive squared correlation coefficient Q(2)(F1) (Shi et al.). However, other validation criteria have been proposed by other authors: the Golbraikh-Tropsha method, r(2)(m) (Roy), Q(2)(F2) (Schüürmann et al.), Q(2)(F3) (Consonni et al.). In QSAR studies these measures are usually in accordance, though this is not always the case, thus doubts can arise when contradictory results are obtained. It is likely that none of the aforementioned criteria is the best in every situation, so a comparative study using simulated data sets is proposed here, using threshold values suggested by the proponents or those widely used in QSAR modeling. In addition, a different and simple external validation measure, the concordance correlation coefficient (CCC), is proposed and compared with other criteria. Huge data sets were used to study the general behavior of validation measures, and the concordance correlation coefficient was shown to be the most restrictive. On using simulated data sets of a more realistic size, it was found that CCC was broadly in agreement, about 96% of the time, with other validation measures in accepting models as predictive, and in almost all the examples it was the most precautionary. The proposed concordance correlation coefficient also works well on real data sets, where it seems to be more stable, and helps in making decisions when the validation measures are in conflict. Since it is conceptually simple, and given its stability and restrictiveness, we propose the concordance correlation coefficient as a complementary, or alternative, more prudent measure of a QSAR model to be externally predictive.
Evaluation of an Early Intervention System at a Law Enforcement Agency

All rights reserved. This publication is intended for use solely by faculty, students, and staff of Nova Southeastern University. No part of this publication may be reproduced, distributed, or transmitted in any form or by any means, now known or later developed, including but not limited to photocopying, recording, or other electronic or mechanical methods, without the prior written permission of the author or the publisher.
Proteomic analysis of proteins differentially expressed in uterine lymphocytes obtained from wild‐type and NOD mice

Non‐obese diabetic (NOD) mice exhibit impaired fertility and decreased litter size when compared to wild type (WT) mice. However, it is unclear why allogeneic pregnant NOD mice are prone to spontaneous embryo loss. Herein, two‐dimensional gel electrophoresis (2‐DE) and mass spectrometry (MS) were used to detect differentially expressed proteins in the uterine lymphocytes isolated from these mice and WT BALB/c controls. We found 24 differentially expressed proteins. The differential expression of 10 of these proteins was further confirmed by Western blot analysis. Out of the 24 identified proteins, 20 were expressed in uterine lymphocytes of WT mice at a level at least 2 times higher than in NOD mice, whereas 4 were down‐regulated. Western blot analysis confirmed that 8 proteins were up‐regulated and 2 proteins were down‐regulated in WT mice compared with NOD mice, consistent with the results of 2‐DE and MS. Additionally, most of the highly expressed proteins in WT uterine lymphocytes were expressed at a significantly lower level in the corresponding splenic group (17/20). These results suggest that up‐regulated expression of these proteins may be specific to uterine lymphocytes. Reported functions of the highly expressed proteins affect key functions during pregnancy, including cell movement, cell cycle control, and metabolisms. Finally, we analyzed the constitutional ratio of CD3+ and CD49b+ cells in the isolated lymphocytes by flow cytometry. Our results suggest that the differentially expressed proteins may participate in the modulation of embryo implantation and early‐stage development of embryos, and subsequently influence pregnancy outcome. J. Cell. Biochem. 108: 447–457, 2009. © 2009 Wiley‐Liss, Inc.
Estimating wheat leaves chlorophyll content using hyperspectral technology and integrated inversion approach

Leaf chlorophyll content (LCC) is an important indicator for wheat growth monitor. In this paper, the integrated inversion approach was developed to estimate the wheat LCC. Based on the PROSAIL simulation data set, three hyperspectral vegetation indices (VIs), PRI, TCARI and TCARI/OSVAI, were comparative analyzed to screen out optimal VI for wheat LCC estimation. The integrated inversion models to estimate wheat LCC were built using the curve fit and least squares support vector regression (LS-SVR) algorithms as the modeling methods, respectively. Finally, using the observation dataset, the accuracy of LS-SVR model for wheat LCC inversion was verified. The result showed that TCARI/OSVAI was an optimal VI for LCC estimating, as it not only exhibit a good sensitivity to the change of LCC but also showed a least sensitivity to the change of LAI values among the three indices and therefore least affected by canopy density when used to estimate the wheat LCC; Comparative curve fitting algorithm, LS-SVR was a optimal algorithm for modeling, as indicated by higher R2 (0.932 for LS-SVR model and 0.923 for curve fitting model) and lower RMSE (3.065 for LS-SVR model and 3.209 for curve fitting model); The R2 of the fitting model between the estimated values and measured values reached 0.763, indicated the similarity between estimated and measured value was high, and it was feasible to obtain the wheat LCC accurately by using hyperspectral VIs and integrated inversion approach.
Tumor-targeted delivery of siRNA by non-viral vector: safe and effective cancer therapy

RNA interference technology has been developed as a potential therapeutic agent for many indications, including cancer. Silencing a specific oncogene in tumor cells brings about cell death both in vitro and in vivo. However, there is a great need for powerful delivery strategies to enhance the therapeutic effect of small interfering RNA (siRNA). This review summarizes different signaling pathways inhibited by siRNA and the advantages of targeted siRNA as a delivery system.
Electric field assisted ion exchange of silver in soda-lime glass: A study of ion depletion layers and interactions with potassium

The introduction of silver ions into glass by diffusion from an external source is of interest in modifying the optical and electrical properties of glass for device applications. Silver is introduced to fabricate in-glass waveguides, while potassium ions are introduced to pattern the silver diffusion by locally impeding the diffusion. Electric fields assist the silver diffusion, leading to faster diffusion rates of ions and allowing greater concentrations of silver without a metallic cluster formation. However, ion depletion layers are formed in the glass as a result of the application of electric field. Here, we study the nature of these depletion layers using depth profiles of composition after electric field diffusion, using cross-sectional energy dispersive x-ray spectroscopy analysis and infrared spectroscopy (Fourier transform infrared attenuated total reflection spectroscopy). We confirm the accelerated diffusion of silver by an electric field and show that potassium impedes the diffusion of silver even when a field is present. We find that an ion depletion layer is formed below the glass surface by the applied electric field which leads to a thermal relaxation and depolarization process when the samples are reheated. Observation of this process enables activation energies and threshold temperatures for the diffusion of Ag, K, and Na to be evaluated and compared with values obtained by composition profiles. Potassium was found to increase the initially low temperature threshold for silver diffusion, increase the activation energy, and also impede sodium diffusion.The introduction of silver ions into glass by diffusion from an external source is of interest in modifying the optical and electrical properties of glass for device applications. Silver is introduced to fabricate in-glass waveguides, while potassium ions are introduced to pattern the silver diffusion by locally impeding the diffusion. Electric fields assist the silver diffusion, leading to faster diffusion rates of ions and allowing greater concentrations of silver without a metallic cluster formation. However, ion depletion layers are formed in the glass as a result of the application of electric field. Here, we study the nature of these depletion layers using depth profiles of composition after electric field diffusion, using cross-sectional energy dispersive x-ray spectroscopy analysis and infrared spectroscopy (Fourier transform infrared attenuated total reflection spectroscopy). We confirm the accelerated diffusion of silver by an electric field and show that potassium impedes the diffusion of silve.
‘Just open your eyes a bit more’: the methodological challenges of researching black and minority ethnic students' experiences of physical education teacher education

In this paper we discuss some of the challenges of centralising ‘race’ and ethnicity in Physical Education (PE) research, through reflecting on the design and implementation of a study exploring Black and minority ethnic students' experiences of their teacher education. Our aim in the paper is to contribute to ongoing theoretical and methodological debates about intersectionality, and specifically about difference and power in the research process. As McCorkel and Myers notes, the ‘researchers’ backstage'—the assumptions, motivations, narratives and relations—that underpin any research are not always made visible and yet are highly significant in judging the quality and substance of the resulting project. As feminists, we argue that the invisibility of ‘race’ and ethnicity within Physical Education Teacher Education (PETE), and PE research more widely, is untenable; however, we also show how centralising ‘race’ and ethnicity raised significant methodological and epistemological questions, particularly given our position as White researchers and lecturers. In this paper, we reflect on a number of aspects of our research ‘journey’: the theoretical and methodological challenges of operationalising concepts of ‘race’ and ethnicity, the practical issues and dilemmas involved in recruiting participants for the study, the difficulties of ‘talking race’ personally and professionally and challenges of representing the experiences of ‘others’.
Estrogen receptors in canine mammary tumors.

The presence of estrogen receptor in 67 canine mammary lesions was correlated with pathological features of the disease. All tissue specimens were analyzed for estrogen receptor content by a sucrose gradient ultracentrifugation method previously used in analyzing human breast cancer cytosols. Pathological features of the tissues were assessed by a veterinary pathologist without knowledge of results of estrogen receptor analysis. Sixty-two (92.5%) of the tissue samples analyzed were classified as epithelial neoplastic lesions, and 38 of these (61.3%), including 24 adenocarcinomas, were estrogen receptor for positive (i.e., estrogen receptor concentration equal to or greater than 10 fmol/mg cytosol protein). All five of the nonepithelial neoplastic lesions were estrogen receptor negative. Canine and human breast cancers share common histological types and have similar biological behavior. If a significant percentage of canine mammary cancer is also estrogen dependent, the dog may be a useful model for hormonal studies and for the development of models of endocrine therapy for human breast cancer.
Improving airborne radar performance using multiple conformal receive apertures

Adaptive airborne processing has mainly focused on planar arrays with equally spaced elements and equally spaced sub-apertures. However, current airborne platforms could provide greater capability with limited system impact, if their current radars were complemented with multiple receive-only conformal apertures. Because of aerodynamic constraints, these receive-only apertures must be unevenly spaced. Simulation results demonstrate the degradation in space-time adaptive processing (STAP) performance caused by the unevenly spaced sub-apertures. The impact of overall antenna distortion is also investigated. A STAP compensation algorithm is developed and its performance quantified.