Conformable fractional heat equation with fractional translation symmetry in both time and space

We investigate the fractional heat equation with fractional translation in both time and position with different fractional orders.As examples,we consider a rod and anα-disk with an initial constant temperature and discuss their cooling processes in the examined formalism.

Analysis and Power Quality Improvement in Hybrid Distributed Generation System with Utilization of Unified Power Quality Conditioner

This paper presents a comprehensive study that includes the sizing and power flow by series and parallel inverters in a distributed generation system(DGs)that integrates the system of hybrid wind photovoltaic with a unified power quality conditioner(UPQC).In addition to supplying active power to the utility grid,the system of hybrid wind photovoltaic functions as a UPQC,compensating reactive power and suppressing the harmonic load currents.Additionally,the load is supplied with harmonic-free,balanced and regulated output voltages.Since PVWind-UPQC is established on a dual compensation scheme,the series inverter works like a sinusoidal current source,while the parallel inverter works like a sinusoidal voltage source.Consequently,a smooth alteration from interconnected operating modes to island operating modes and vice versa can be achieved without load voltage transients.Since PV-Wind-UPQC inverters handle the energy generated through the hybrid wind photovoltaic system and the energy demanded through the load,the converters should be sized cautiously.A detailed study of the flow of power via the PV-Wind-UPQC is imperative to gain a complete understanding of the system operation and the proper design of the converters.Thus,curves that allow the sizing of the power converters according to the power flow via the converters are presented and discussed.Simulation results are presented to assess both steady state and dynamic performances of the grid connected hybrid system of PV-Wind-UPQC.This investigation is verified by simulating and analyzing the results with Matlab/Simulink.

Influence of Tea Leaf Particle Size on Catechin Extraction and Green Tea Sensory Acceptance

The intensity of the bitterness of catechins increases with increased concentration, but the taste palatability decreased in green tea extract. The aim of this study was to investigate whether a blend of tea leaf particles of various sizes would result in a good balance between catechin content and appreciable taste. The control is common tea (CT) with 6 - 10 mm long leaves. Blend tea (BT) was prepared by mixing 5 mm and 120 - 130 mm long tea leaves in a ratio of 3:2. The catechin content of hot water extracts was analyzed by HPLC, and the sensory test was conducted with 99 volunteers. In BT, the total catechin content was significantly higher than that in CT. The sensory test results revealed that BT was less bitter and had more preferable color than CT. More catechins were extracted from BT, but it tasted less bitter. Thus, the recalibration of the tea leaf particle size can result in good balance between catechin content and palatability.

Bayesian machine learning-based method for prediction of slope failure time

The data-driven phenomenological models based on deformation measurements have been widely utilized to predict the slope failure time(SFT).The observational and model uncertainties could lead the predicted SFT calculated from the phenomenological models to deviate from the actual SFT.Currently,very limited study has been conducted on how to evaluate the effect of such uncertainties on SFT prediction.In this paper,a comprehensive slope failure database was compiled.A Bayesian machine learning(BML)-based method was developed to learn the model and observational uncertainties involved in SFT prediction,through which the probabilistic distribution of the SFT can be obtained.This method was illustrated in detail with an example.Verification studies show that the BML-based method is superior to the traditional inverse velocity method(INVM)and the maximum likelihood method for predicting SFT.The proposed method in this study provides an effective tool for SFT prediction.

Topography Image Segmentation Based on Improved Chan-Vese Model

Aiming to solve the inefficient segmentation in traditional C-V model for complex topography image and time-consuming process caused by the level set function solving with partial differential, an improved Chan-Vese model is presented in this paper. With the good per）brmances of maintaining topological properties of the traditional level set method and avoiding the numerical so- lution of partial differential, the same segmentation results could be easily obtained. Thus, a stable foundation tbr rapid segmenta- tion-based on image reconstruction identification is established.

Artificial Neural Networks for Prediction of COVID-19 in Saudi Arabia

In this study,we have proposed an artificial neural network(ANN)model to estimate and forecast the number of confirmed and recovered cases of COVID-19 in the upcoming days until September 17,2020.The proposed model is based on the existing data(training data)published in the Saudi Arabia Coronavirus disease(COVID-19)situation—Demographics.The Prey-Predator algorithm is employed for the training.Multilayer perceptron neural network(MLPNN)is used in this study.To improve the performance of MLPNN,we determined the parameters of MLPNN using the prey-predator algorithm(PPA).The proposed model is called the MLPNN–PPA.The performance of the proposed model has been analyzed by the root mean squared error(RMSE)function,and correlation coefficient(R).Furthermore,we tested the proposed model using other existing data recorded in Saudi Arabia(testing data).It is demonstrated that the MLPNN-PPA model has the highest performance in predicting the number of infected and recovering in Saudi Arabia.The results reveal that the number of infected persons will increase in the coming days and become a minimum of 9789.The number of recoveries will be 2000 to 4000 per day.

Modeling the Surface Ozone Concentration in Campo Grande (MS)—Brazil Using Neural Networks

The estimation of the surface ozone concentration promotes the creation of data useful for planning the air quality forecast, which is a key element for the management of public health. The aim of this study is to develop an Artificial Neural Network (ANN) to estimate the concentration of surface ozone from daily climate data. ANN is an equivalent form of Feedforward Multilayer Perceptron whose data has been inserted from the daily concentration of measured ozone. In the intermediate and output layers activation functions like tan-sigmoid and linear have been used, respectively. The performance of the developed ANN is actually very good and it can be considered like part of the set of indirect methods to estimate the concentration of surface ozone. The proposed model may be used by governmental agencies as a tool to enable the public interventional actions during the period of atmospheric stagnation, when ozone levels in the atmosphere represent risks to the public health.

Pseudo-Linear Mechanics with Pseudo-Translation Symmetry

In this paper, we will consider the simplest pseudo-addition where pseudo-multiplication and pseudo-division are the same as the ordinary ones and distributivity hold. Using this we consider a special type of the non-uniform discrete times with the pseudo-translation symmetry. Besides, we demand that the displacement should be invariant under the pseudo-translation. From these, we obtain the new definition of the instantaneous velocity which is pseudo-translation symmetry in both time and position and formulate the mechanics which are pseudo-linear and pseudo-translation invariant.

Annulohypoxylon stygium,a Pandanus simplex-associated fungal endophyte withα-glucosidase inhibitory activity

Fungal endophytes offer structurally diverse and unique secondary metabolites with interesting biological activities.Several reports have shown the potential of fungal endophytes as sources ofα-glucosidase inhibitors to alleviate diabetes.In this study,the fungal endophyte Annulohypoxylon stygium(Xylariales,Ascomycota)was identified for the first time from the leaves of the endemic tropical plant,Pandanus simplex Merr.Crude extract was obtained by fermenting the fungal endophyte in Potato Dextrose Broth for 30 days at room temperature.The A.stygium crude extract exhibited good inhibition to theα-glucosidase enzyme with an IC_(50) of 31.88±2.86μg/mL.Purification of the crude extract afforded 8-methoxynaphthol with an IC_(50) value of 676.3±1.03μg/mL.The isolation of 8-methoxynaphthol from A.stygium is reported herein for the first time.This study highlights the ability of A.stygium to produce metabolites that may be useful as antidiabetic drugs.

Climatic Variations and Consumption of Urban Water

This study aims to develop a statistical modelling framework of urban water consumption forecast for the city of Aquidauana, Brazil from year 2005 to 2014, monthly data, using multiple linear regression, cluster analysis, and principal component analysis. These forecasts were based on historical data collected through SANESUL System (Water Systems of South Mato Grosso). The meteorological data were provided by the Water Resources Monitoring Center of South Mato Grosso—CEMTEC. The statistical model developed explains 71.5% of the variance with three factors: number of consumers (19.3%), seasonality (37.8%), and climate regression (14.3%). The model was further validated using an independent set of data from January 2005 to November 2014, with an R2 of 86% and error of 1.7%. The results indicated no intervention of climate variables in the phenomenon. This tool, combined with the perception of the potential and limitations of managers of water resources and public policy makers, can be used in the regulation of per capita consumption, and thereby achieve the optimization of available resources and also contribute to the sustainable perspective of water resources.

Natural selection on flower size in invasive Cytisus scoparius along an elevation gradient

已建群的入侵植物物种在其本地生长范围内比单一种群具有更多样化的基因库。这种遗传和表型变异可以使入侵植物与群落的其他成员相互作用,从而进行自然选择,并形成快速适应机制。对于入侵的开花植物,与传粉者的相互作用可能使其适应异质性的传粉者群落。入侵地内传粉昆虫群落的变化与本地范围内的变化相似,这表明适应性可能反映了在本地范围内看到的模式。在本论文中,我们研究了在华盛顿州的国会国家森林公园内的一种入侵豆科灌木金雀儿(Cytisus scoparius)花的大小沿海拔梯度的变化。我们在每个样地中测量了10株植物花的宽度和传粉花的比例。我们对沿海拔梯度分布样地的金雀儿在单株水平下的物候变化进行三次测定。研究发现,尽管没有呈现出明显的高海拔具有高选择性的规律,但对于花的大小呈现正选择效应。从授粉昆虫的造访率和种子产量两方面,可以看出自然选择的模式。我们还发现,造成种子产量变化的最大因素不是海拔高度或花的大小,而是管理措施。

Dirac Oscillator Under the New Generalized Uncertainty Principle From the Concept Doubly Special Relativity

We discuss one-dimensional Dirac oscillator, by using the concept doubly special relativity. We calculate the energy spectrum by using the concept doubly special relativity. Then, we derive another representation that the coordinate operator remains unchanged at the high energy while the momentum operator is deformed at the high energy so that it may be bounded from the above. Actually, we study the Dirac oscillator by using of the generalized uncertainty principle version and the concept doubly special relativity.

Investigation of Conformable Fractional Schr¨odinger Equation in Presence of Killingbeck and Hyperbolic Potentials

In this article, conformable fractional form of Schrdinger equation has been presented. Then in this formalism two different and well-known potential have been come in. Wave function of these potential are obtained in terms of Heun function and energy eigen values of each case is determined as well.

Quasi-periodic variations of low energy cosmic rays

Cosmic rays(CR)play an important role in space weather-related studies.Their temporal variability,both of a quasi-periodic character as well as an irregular one,has been studied from ground-based direct measurements,as well as from cosmogenic nuclides,over a long time.We attempt to describe the current knowledge of selected quasi-periodicities in CR flux in the energy range above the atmospheric threshold,from direct measurements.The power spectrum density(PSD)of the CR time series as measured by neutron monitors(NMs)and by muon detectors has a rather complicated character.Along with the shape(slope)of the PSD,knowledge of the contribution of quasi-periodic variations(q-per)to the CR signal is of importance for the modulation,as well as for checking the links of CR to space weather,and/or to space climate effects.The rotation of the Earth and solar rotation cause two types of mechanisms behind the certain q-per observed in secondary CR on the Earth’s surface.Solar activity and solar magnetic field cyclicities contribute to the q-per signals in CR if studied over a longer time.The complexity of the spatial structure of the interplanetary magnetic field(IMF)and its evolution within the heliosphere,in addition to the changes in the geomagnetic field,cause variability in contributions of the q-per in CR.Wavelet spectra are useful tools for checking the fine structure of q-per and their temporal behaviour.Over a long time NMs and muon telescopes provide information about q-per in CR.

Determining the spatial distribution of environmental and socio-economic suitability for human leptospirosis in the face of limited epidemiological data

Background:Leptospirosis is among the leading zoonotic causes of morbidity and mortality worldwide.Knowledge about spatial patterns of diseases and their underlying processes have the potential to guide intervention efforts.However,leptospirosis is often an underreported and misdiagnosed disease and consequently,spatial patterns of the disease remain unclear.In the absence of accurate epidemiological data in the urban agglomeration of Santa Fe,we used a knowledge-based index and cluster analysis to identify spatial patterns of environmental and socioeconomic suitability for the disease and potential underlying processes that shape them.Methods:We geocoded human leptospirosis cases derived from the Argentinian surveillance system during the period 2010 to 2019.Environmental and socioeconomic databases were obtained from satelite images and publicly available platforms on the web.Two sets of human leptospirosis determinants were considered according to the level of their support by the literature and expert knowledge.We used the Zonation algorithm to build a knowledge-based index and a clustering approach to identify distinct potential sets of determinants.Spatial similarity and correlations between index,clusters,and incidence rates were evaluated.Results:We were able to geocode 56.36%of the human leptospirosis cases reported in the national epidemiological database.The knowledge-based index showed the suitability for human leptospirosis in the UA Santa Fe increased from downtown areas of the largest cities towards peri-urban and suburban areas.Cluster analysis revealed downtown areas were characterized by higher levels of socioeconomic conditions.Peri-urban and suburban areas encompassed two clusters which differed in terms of environmental determinants.The highest incidence rates overlapped areas with the highest suitability scores,the strength of association was low though(CSc r=0.21,P<0.001 and ESc r=0.19,P<0.001).Conclusions:We present a method to analyze the environmental and socioeconomic suitability for human leptospirosis based on literature and expert knowledge.The methodology can be thought as an evolutive and perfectible scheme as more studies are performed in the area and novel information regarding determinants of the disease become available.Our approach can be a valuable tool for decision-makers since it can serve as a baseline to plan interventionmeasures.

Investigation of Heisenberg algebra for a modified anti-de Sitter and modified antiSnyder models

In this paper,we consider a possible modification of the de Sitter and anti-de Sitter space for the extended uncertainty principle.For the modified anti-de Sitter model we discuss the representation and wave functions of the momentum operator for a one-dimensional box problem.Also,we consider modified Snyder and anti-Snyder models for the generalized uncertainty principle.Then,we assume the Hamiltonian with different potential and solve the Heisenberg algebra for the modified(anti)-de Sitter and(anti)-Snyder models in both position and in the momentum space.

Achmatowicz approach to the asymmetric synthesis of(+)-and(−)-monanchorin

The full account of our development of a de novo asymmetric total synthesis of(+)-monanchorin has been reported.The optimized synthesis provided access to either enantiomer of the guanidine alkaloid natural product in nine steps from the commodity chemicals furan and caproic acid.The route relied upon the asymmetric Noyori hydrogen transfer reduction of an achiral acylfuran to introduce the absolute stereochemistry.In addition,an Achmatowicz rearrangement,a diastereoselective palladium-catalyzed glycosylation,a reductive amination and an acid-catalyzed bicyclic guanidine mixed acetal formation were used to complete the synthesis.