Miracle-dz/UniFAR-FTUs huggingface dataset:
Molecular Methods in Plant Pathology

Biophysical Methods X-Ray Microanalysis, W.M. Hess, C.Z. Hess, and M.D. Standing Immuno-Electron Microscopy, N. Benhamou and R. Belanger Diagnosing Plant Virus Diseases by Light Microscopy, R.G. Christie, J.R. Edwardson, and G.W. Simone Use of DNA Binding Fluorochromes for Nuclear Staining in Fungi, U.S. Singh, A. Sachan, J. Kumar, and P. Singh Virion Gel Electrophoresis, R.P. Singh and N.R.M. Watts On the Mechanism of Viroid Strain Separation in Gel Electrophoresis, N.R.M. Watts and R.P. Singh Electrophoretic Karyotyping: Method and Applications, D. Mills, K. McCluskey, B.W. Russell, and J. Agnan Biochemical Methods Biochemical Markers for Disease Resistance, R. Reuveni Isozymes: Methods and Applications, J.A. Micales and M.R. Bonde Biomolecular Methods Nucleic Acid Hybridization Methods in Diagnosis of Plant Viruses and Viroids, O.V. Nikolaeva Tissue Print Hybridization for the Detection and Localization of Plant Viruses, T. -F. Chia, Y. -S. Chan, and N. -H. Chua Transposon and Marker Exchange Mutagenesis, G.H. Lacy and V.K. Stromberg Polymerase Chain Reaction Technology in Plant Pathology, A. Hadidi, L. Levy, and E.V. Podleckis Gene Transfer to Higher Plants, R.R. Mendel and R.M. Hansch Arabidopsis as a Model Host in Molecular Plant Pathology, R. Innes Isolation and Cloning of Plant Disease Resistance Genes, N.D. Young Molecular Strategies to Develop Virus Resistant Plants, J.N. Culver Engineering Disease Resistance in Plants, R.A. Dixon, N.L. Paiva, and M.K, Bhattacharyya Biotechnological Methods Present Problems in and Aspects of Breeding for Disease Resistance, J.E. Parlevliet Dual Culture: Fungi, O.K. Sinha Dual Culture: Nematodes, S. Verdejo-Lucas Protoplast Culture: Viruses and Viroids, A. Gera ELISA Methodology, R.K. Khetrapal and C.A. Kumar Methods for the Production of Mouse Monoclonal Antibodies, R. Mernaugh and G. Mernaugh Phage Displayed Recombinant Antibodies: An Overview, R. Mernaugh and G. Mernaugh Direct Tissue Blot Immunoassay for Analysis of Plant Pathogens, H. -T. Hsu, R.H. Lawson, N. -S. Lin, and Y. -H.H. Hsu Monoclonal Antibodies to Fungal Pathogens: Basic and Applied Aspects, K. Wycoff and L.M. Brill Production and Application of Monoclonal Antibodies to Plant Pathogenic Bacteria, Spiroplasma, and Mycoplasma-Like Organisms, R. Jordan Monoclonal Antibodies: Viruses, K. Ohshima Monoclonal Antibodies: Nematodes, J.M.S. Forrest Immunological Methods for the Detection of Toxins and Pesticides, T. -C. Tseng Plant Disease Diagnosis: Biotechnological Approaches, S.A. Miller Monitoring of Biocontrol Agents and Genetically Engineered Microorganisms in the Environment: Biotechnological Approaches, M.H. Ryder Monitoring of Fungicide Resistance in Fungi: Biological to Biotechnological Approaches, H. Ishii
Spatiotemporal variations of public opinion on social distancing in the Netherlands: Comparison of Twitter and longitudinal survey data

Background Social distancing has been implemented by many countries to curb the COVID-19 pandemic. Understanding public support for this policy calls for effective and efficient methods of monitoring public opinion on social distancing. Twitter analysis has been suggested as a cheaper and faster-responding alternative to traditional survey methods. The current empirical evidence is mixed in terms of the correspondence between the two methods. Objective We aim to compare the two methods in the context of monitoring the Dutch public's opinion on social distancing. For this comparison, we quantified the temporal and spatial variations in public opinion and their sensitivities to critical events using data from both Dutch Twitter users and respondents from a longitudinal survey. Methods A longitudinal survey on a representative Dutch sample (n = 1,200) was conducted between July and November 2020 to measure opinions on social distancing weekly. From the same period, near 100,000 Dutch tweets were categorized as supporting or rejecting social distancing based on a model trained with annotated data. Average stances for the 12 Dutch provinces and over the 20 weeks were computed from the two data sources and were compared through visualizations and statistical analyses. Results Both data sources suggested strong support for social distancing, but public opinion was much more varied among tweets than survey responses. Both data sources showed an increase in public support for social distancing over time, and a strong temporal correspondence between them was found for most of the provinces. In addition, the survey but not Twitter data revealed structured differences among the 12 provinces, while the two data sources did not correspond much spatially. Finally, stances estimated from tweets were more sensitive to critical events happened during the study period. Conclusions Our findings indicate consistencies between Twitter data analysis and survey methods in describing the overall stance on social distancing and temporal trends. The lack of spatial correspondence may imply limitations in the data collections and calls for surveys with larger regional samples. For public health management, Twitter analysis can be used to complement survey methods, especially for capturing public's reactivities to critical events amid the current pandemic.
Exploring the Effect of an Entrepreneurship Awareness-raising Intervention on ELT Learners’ Entrepreneurial Intention, Mindset, Self-efficacy and Outcome Expectations

This experimental study aimed to explore the effect of entrepreneurship education among English language teaching (ELT) learners in Iran. To this end, an entrepreneurship awareness-raising intervention was designed and evaluated through a mixed-method explanatory sequential design with hypotheses rooted in social cognitive career theory. The effectiveness of the intervention was first investigated quantitatively through pre-test and post-test among 41 ELT learners. Then, semi-structured interviews were conducted among 15 participants to triangulate and further explain the quantitative findings. The results of repeated measures of MANOVA revealed that ELT learners’ entrepreneurial intention, entrepreneurial self-efficacy, entrepreneurial mindset, and entrepreneurial outcome expectations improved significantly from pre-test to post-test under the effect of the intervention. Further, the findings of qualitative data analysis confirmed the quantitative results and revealed that all of the participants took great satisfaction in the course, and they believed that the effectiveness of the course was even beyond their expectations. Implications are discussed.
The k-Yamabe problem on CR manifolds ∗†

We introduce the notion of pseudohermitian k-curvature, which is a natural extension of the Webster scalar curvature, on an orientable manifold endowed with a strictly pseudoconvex pseudohermitian structure (referred here as a CR manifold) and raise the k-Yamabe problem on a compact CR manifold. When k = 1, the problem was proposed and partially solved by Jerison and Lee for CR manifolds non-locally CR-equivalent to the CR sphere. For k > 1, the problem can be translated in terms of the study of a fully nonlinear equation of type complex k-Hessian. We provide some partial answers related to the CR k-Yamabe problem. We establish that its solutions with null Cotton tensor are critical points of a suitable geometric functional constrained to pseudohermitian structures of unit volume. Thanks to this variational property, we establish a Obata type result for the problem and also compute the infimum of the functional on the CR sphere. Furthermore, we show that this value is an upper bound for the corresponding one on any compact CR manifolds and, assuming the CR Yamabe invariant is positive, we prove that such an upper bound is only attained for compact CR manifolds locally CR-equivalent to the CR sphere. In the Riemannian field, recent advances have been produced in a series of outstanding works.
Data-Driven Methods of Machine Learning in modeling the Smart Grids

Electricity demand is rising in lockstep with global population growth. The present power system, which is almost a century old, faces numerous issues in maintaining a steady supply of electricity from huge power plants to customers. To meet these issues, the electricity industry has enthusiastically embraced the new smart grid concept proposed by engineers. If we can provide a secure smart grid, this movement will be more useful and sustainable. Machine learning, which is a relatively recent era of information technology, has the potential to make smart grids extremely safe. This paper is a literature survey of the application of machine learning in different areas of smart grids. This paper concludes by mentioning the best machine learning algorithms that can be used in different aspects of the smart grid.
Continuity and differentiability of regression M-estimates

This paper deals with the weak continuity, Fisher-consistency and differentiability of estimating functionals corresponding to a class of both linear and nonlinear regression high breakdown M estimates, which includes \ S and MM estimates. A restricted type of differentiability, called weak differentiability, is defined, which suffices to prove the asymptotic normality of estimates based on the functionals. This approach allows to prove the consistency, asymptotic normality and qualitative robustness of estimates under more general conditions than those required in standard approaches.
Control Optimization of Scenic Spot Navigation System Based on Map Matching Algorithm

In order to solve the problem that the smart phone GPS positioning technology cannot guarantee the location accuracy in the scenic spot navigation system, a tourist spot matching method based on the improved HMM model was proposed. Firstly, the traditional linear road model is improved in electronic map design. Secondly, the concept of minimum peripheral error rectangle is proposed based on the theory of error ellipse. Then, combined with location data, road data, and scenic spot data, the improved HMM model is used to calculate the matching road. Finally, Matlab simulation experiment and comparison experiment are carried out. The results show that the accuracy of the map matching algorithm based on the improved HMM model can reach 94.5%, and the average accuracy can reach 93.1%, which is 3.6% higher than that of the traditional HMM model. The test results show that the proposed algorithm is correct and practical and has a good application prospect.
Estimating Carbon Sequestration Potential of Forest and Its Influencing Factors at Fine Spatial-Scales: A Case Study of Lushan City in Southern China

Accurate prediction of forest carbon sequestration potential requires a comprehensive understanding of tree growth relationships. However, the studies for estimating carbon sequestration potential concerning tree growth relationships at fine spatial-scales have been limited. In this paper, we assessed the current carbon stock and predicted sequestration potential of Lushan City, where a region has rich vegetation types in southern China, by introducing parameters of diameter at breast height (DBH) and tree height in the method of coupling biomass expansion factor (BEF) and tree growth equation. The partial least squares regression (PLSR) was used to explore the role of combined condition factors (e.g., site, stand, climate) on carbon sequestration potential. The results showed that (1) in 2019, the total carbon stock of trees in Lushan City was 9.22 × 105 t, and the overall spatial distribution exhibited a decreasing tendency from northwest to south-central, and the carbon density increased with elevation; (2) By 2070, the carbon density of forest in Lushan City will reach a relatively stable state, and the carbon stock will continue to rise to 2.15 × 106 t, which is 2.33 times of the current level, indicating that Lushan forest will continue to serve as a carbon sink for the next fifty years; (3) Excluding the effect of tree growth, regional forest carbon sequestration potential was significantly influenced on site characteristics, which achieved the highest Variable Importance in Projection (VIP) value (2.19) for slope direction. Our study provided a better understanding of the relationships between forest growth and carbon sequestration potential at fine spatial-scales. The results regarding the condition factors and how their combination characteristics affect the potential for carbon sequestration could provide crucial insights for Chinese carbon policy and global carbon neutrality goals.
Complete mitochondrial genomes of four deep-sea echinoids: conserved mitogenome organization and new insights into the phylogeny and evolution of Echinoidea

Echinoids are an important component in benthic marine environments, which occur at all depths from the shallow-water hard substrates to abyssal depths. To date, the phylogeny of the sea urchins and the macro-evolutionary processes of deep-sea and shallow water groups have not yet been fully resolved. In the present study, we sequenced the complete mitochondrial genomes (mitogenomes) of four deep-sea sea urchins (Echinoidea), which were the first representatives of the orders Aspidodiadematoida, Pedinoida and Echinothurioida, respectively. The gene content and arrangement were highly conserved in echinoid mitogenomes. The tRNA-SerAGY with DHU arm was detected in the newly sequenced echinoid mitogenomes, representing an ancestral structure of tRNA-SerAGY. No difference was found between deep-sea and shallow water groups in terms of base composition and codon usage. The phylogenetic analysis showed that all the orders except Spatangoida were monophyletic. The basal position of Cidaroida was supported. The closest relationship of Scutelloida and Echinolampadoida was confirmed. Our phylogenetic analysis shed new light on the position of Arbacioida, which supported that Arbacioida was most related with the irregular sea urchins instead of Stomopneustoida. The position Aspidodiadematoida (((Aspidodiadematoida + Pedinoida) + Echinothurioida) + Diadematoida) revealed by mitogenomic data discredited the hypothesis based on morphological evidences. The macro-evolutionary pattern revealed no simple onshore-offshore or an opposite hypothesis. But the basal position of the deep-sea lineages indicated the important role of deep sea in generating the current diversity of the class Echinoidea.
Technical barriers to trade and China’s exports: firm-level evidence

ABSTRACT This paper studies the trade-restriction and trade-promotion effects that technical barriers to trade (TBTs) have on export performances of Chinese firms over the period 2001–2006. Different from tariffs and most traditional non-tariff measures, TBTs can impose both positive and negative impacts on exports. On the one hand, TBTs increase the compliance costs and have the trade-restriction effect. On the other hand, TBTs improve product quality and mitigate uncertainty, which enhances demand and promotes trade. We investigate how TBTs influence the extensive and intensive margins of a firm’s exports and how the impact varies with the size, productivity, and ownership of a firm. Specifically, we look into a firm’s entry and exit decisions, export value, unit price, and quantity. The estimated results show that TBTs decrease both the extensive and intensive margins of small firms, and they improve the export performances of large firms. The finding indicates that while small firms that cannot meet the technical standards will leave their markets, large firms will stay in their markets and expand their export volumes. The trade effects of TBTs also change by characteristics of the importing country and sector.
A Lazer-Mckenna type problem with measures

In this paper we are concerned with a general singular Dirichlet boundary value problem whose model is the following $$ \begin{cases} -\Delta u = \frac{\mu}{u^{\gamma}} & \text{in}\ \Omega, u=0 &\text{on}\ \partial\Omega, u>0 &\text{on}\ \Omega\,. \end{cases} $$ Here $\mu$ is a nonnegative bounded Radon measure on a bounded open set $\Omega\subset\mathbb{R}^N$, and $\gamma>0$.
Sistema de alerta temprana para previsión de avenidas en la ciudad de Durazno

Desde Mayo de 2011, el Centro Coordinador de Emergencias Departamentales (CECOED) de Durazno cuenta con un Sistema de Alerta Temprana operativo para prevision de las avenidas del rio Yi. Este sistema fue desarrollado, en el marco de un proyecto de la red PROHIMET (financiado por la Organizacion Meteorologica Mundial-OMM), por el Instituto de Mecanica de los Fluidos e Ingenieria Ambiental (IMFIA)-Facultad de Ingenieria, con la coparticipacion del Instituto de Teoria y Urbanismo (ITU)-Facultad de Arquitectura, la Direccion Nacional de Aguas (DINAGUA-MVOTMA), el Sistema Nacional de Emergencias (SINAE), la Administracion Nacional de Usinas y Transmisiones Electricas (UTE), el Instituto Nacional de Meteorologia (INUMET), y el Ministerio de Ganaderia agricultura y Pesca (MGAP). En este trabajo se describen las principales caracteristicas del Sistema de Alerta Temprana instalado y se presenta la metodologia empleada, informacion de base y como ha sido su desempeno y eficacia en la gestion de las emergencias frente a tormentas extremas de diferentes caracteristicas ocurridas entre los anos 2011 a 2014.
The Neural Basis of Tonal Processing in Music: An ALE Meta-Analysis

Music is used as an important medium for communication in human societies, often times to enhance the emotional meaning of narrative scenarios and ritual events. Music has a number of domain-specific tonal devices for doing this, spanning from scale structure to harmonic progressions and beyond. In order to explore the neural basis of tonal processing in music, we carried out an activation likelihood estimation (ALE) meta-analysis of 20 published functional magnetic resonance imaging studies of tonal cognition, with an emphasis on harmony processing. The most concordant areas of activation across these studies occurred at the junction of the inferior frontal gyrus, anterior insula, and orbitofrontal cortex in Brodmann areas 47 and 13 in the right hemisphere. This region is associated not only with emotion in general, but with the conveyance of affective meanings during communication processes, including speech prosody and music.
The Dynamics of the Inverse Pinch.

Experiments are performed on the plasma produced in a large inverse pinch using argon with no applied magnetic fields or preheating. A direct observation is made of the precursor ionization which initially raises the electron temperature and electrical conductivity. Calculations show that most of the mass is entrained in the current sheet, but that less than complete sweeping occurs at the lower velocities. The shock which is embedded in the current sheet closely resembles an ordinary gasdynamic shock. Consideration of the shock jump condition derived from the induction equation is shown to determine the frequent inability of the shock to separate from the current sheet.
Meta-heuristic Search Algorithms for Solving the Economic Load Dispatch Problem

Economic load dispatch (ELD) is a challenge optimization problem to minimize the total cost of the thermally generated power that satisfies a set of equality and inequality constraints. We need to maximize the power network load under several operational constraints to solve this problem. Meanwhile, we need to minimize the cost of power generation and minimize the loss in the network transmission. Traditional optimization methods were used to solve such problems as linear programming. Meta-heuristic search algorithms have shown encouraging performance in solving various real-life engineering problems. This paper attempts to provide a comprehensive comparison between nine meta-heuristic search algorithms, including Genetic Algorithms (GAs), Particle Swarm Optimization (PSO), Crow Search Algorithm (CSA), Differential Evolution (DE), Salp Swarm Algorithm (SSA), Harmony Search (HS), Sine Cosine Algorithm (SCA), Multi-Verse Optimizer (MVO), and Moth-Flame Optimization Algorithm (MFO) for solving the economic load dispatch problem. Our developed results demonstrated that meta-heuristics search algorithms (i.e., CSA and DE) offer the optimal power set for each power station. These computed power fulfill the supply needs and maintain both minimum power costs and power losses in power transmission.
Physicochemical Characterization of Detarium microcarpum Seeds from Northern Benin

The objective of this work is to determine the physicochemical characteristics of the Detarium microcarpum seeds from North Benin, specially the proximate composition, colour, minerals, and antinutritional factors using standard analytical methods. The results show that the contents of moisture, protein, total sugars, lipid, crude fiber, and ash ranged, respectively, from 10.85 to 14.69%, from 13.54 to 17.82%, from 19.69 to 32.04%, from 8.68 to 11.90%, from 19.78 to 34.24%, and from 1.5 to 3.49%. The luminance (l∗), red saturation (a∗), and yellow saturation (b∗) have, respectively, ranged from 60.45 to 67.64, from 5.44 to 8.86, and from 8.24 to 9.28. Seeds contain interesting contents of potassium, calcium, magnesium, manganese, sodium, and iron; they have, respectively, varied from 6141.88 to 12305.16 mg/kg, from 1254.47 to 2168.62 mg/kg, from 1298.87 to 2533.06 mg/kg, from 75.18 to 307.23 mg/kg, from 53.52 to 136.19 mg/kg, and from 28.46 to 181.42 mg/kg. The investigation of antinutritional factors indicates the presence of oxalates, phytates, total phenolic compounds, and saponins with contents that have varied, respectively, from 1.01 to 2.36%, from 0.37 to 0.87%, from 3.13 to 7.61%, and from 1.35 to 4.59%. On average, the physicochemical characteristics of the Sudanian and Sudano-Guinean zones are similar, except for total sugar content.
Role of pressure and pore microstructure on seismic attenuation and dispersion of fluid-saturated rocks: laboratory experiments and theoretical modelling

Understanding the effects of pressure and rock microstructure on seismic elastic properties of fully saturated rocks is of considerable importance in a range of geophysical applications, especially at seismic frequency range. A recently proposed theoretical model of squirt attenuation and dispersion can be employed to interpret the stress and frequency dependence of elastic properties on the basis of a triple porosity structure. The poroelastic model requires the knowledge of a variety of pore microstructure parameters, in particular, the compliant pores with a discrete distribution of aspect ratio. We performed laboratory measurements of (compressional and shear wave) velocity dispersion and attenuation, associated with the pressure-related closure of compliant pores on three dry and wet sandstones, to verify the effects of squirt flow arising from compressibility heterogeneities in the rock microstructure on the pressure dependence of dynamic elastic moduli and attenuation. Ultrasonic velocities experimentally measured on dry rocks were applied to extract pressure-dependent pore aspect distribution of compliant pores and the effective porosity of three types of pores with distinct aspect ratios, via fitting of the poroelastic model to the pressure dependence of elastic compressibilities. Under the assumption of frequency-independent dry elastic properties, inferred velocities and the associated attenuation of the saturated rocks from the forced oscillation experiments, which are still scarcely investigated, are in fairly good agreement with the predictions of the squirt model of three porosity types at seismic frequencies. The Gassmann's relation was found, nevertheless, underpredicts the ultrasonic saturated velocity measurements. The results validate applicability of the recently developed squirt model to account for dispersion and attenuation of phase velocities at varying effective pressures.