Analytic approximate solutions of Volterra’s population and some scientific models by power series method

In this paper, we have implement an analytic approximate method based on power series method (PSM) to obtain asolutions for Volterra’s population model of population growth of a species in a closed system. The numerical solution isobtained by combining the PSM and Pad´e technique. The Pad´e approximation that often show superior performance overseries approximation are effectively used in the analysis to capture essential behavior of the population u(t) of identicalindividuals. The results demonstrate that the method has many merits such as being derivative-free, overcome the difficultyarising in calculating Adomian polynomials to handle the nonlinear terms in Adomian Decomposition Method (ADM).It does not require to calculate Lagrange multiplier as in Variational Iteration Method (VIM) and no needs to construct ahomotopy and solve the corresponding algebraic equations as in Homotopy Perturbation Method (HPM). Moreover, weused this method to solve some scientific models, namely, the hybrid selection model, the Riccati model and the logisticmodel to provide the analytic solutions. The obtained analytic approximate solutions of applying the PSM is in fullagreement with the results obtained with those methods available in the literature. The software used for the calculationsin this study was MATHEMATICAr 8.0

Numerical solution for the time-Fractional Diffusion-wave Equations by using Sinc-Legendre Collocation Method

In this paper the numerical solution of fractional diffusion wave equation is proposed. The fractional derivative will be in the Caputo sense. The proposed method will be based on shifted Legendre collocation scheme and sinc function approximation for time and space respectively. The problem is reduced to the problem into a system of algebraic equations after implementing this method. For demonstrating the validity and applicability of the proposed numerical scheme some examples are presented. Keywords: Fractional diffusion equation, Sinc functions, shifted Legendre  polynomials, Collocation method

Analisa Pola Sebaran Sedimen Dasar Muara Sungai Batang Arau Padang

Muara sungai berfungsi sebangai penghubung antara sungai dan laut, pada daerah ini terjadi pertemuan antara arus sungai dan juga arus laut. Pertemuan arus ini nantinya akan menyebabkan terjadi proses sedimentasi pada muara sungai. Sedimen yang tersedimenasi nantinya akan mengalami proses transpor yang disebabkan oleh pengaruh arus diperairan.Tujuan penelitian ini adalah untuk mengetahui pola sebaran ukuran butir sedimen pada muara sungai Batang Arau Padang serta pengaruh arus terhadap pesebaran sedimen di muara sungai Batang Arau. Penelitian ini dilakukan pada bulan Mei 2016 di muara sungai Batang Arau, Padang. Metode penelitian yang digunakan adalah metode kuantitatif. Penentuan lokasi pengambilan titik lokasi dengan menggunakan metode purposive sampling dan pengambilan sampel sedimen dasar pada 25 Mei 2016. Analisis jenis sampel sedimen dasar di laboratorium menggunakan metode granulometri. Peta sebaran sedimen dasar diinterpolasi menggunakan software ArcGIS 10.0 dan pemodelan arus laut menggunakan software MIKE 21. Hasil penelitian menunjukkan bahwa jenis sebaran sedimen dasar pada perairan ialah jenis lanau, lanau pasiran, pasir lanauan, dan pasir. Kondisi arus pada saat pengambilan data terbilang kecil yakni 0,117 – 0,196 m/det dengan arah ke Timur Laut dan Barat Daya. Berdasarkan hasil penelitian dapat disimpulkan bahwa sedimen yang memiliki ukuran butir yang lebih besar terendapkan pada wilayah muara dan semakin mengecil ukurannya menuju laut

On Completeness of Fuzzy Normed Spaces

 In this paper, a new direction has been presented between the subject of domain theory and fuzzy normed spaces to introduce the so called fuzzy domain normed spaces and proved some results related to this subject concerning the completeness of such spaces.domai

Learning Curves of Minimally Invasive Distal Pancreatectomy in Experienced Pancreatic Centers

IMPORTANCE Understanding the learning curve of a new complex surgical technique helps to reduce potential patient harm. Current series on the learning curve of minimally invasive distal pancreatectomy (MIDP) are mostly small, single-center series, thus providing limited data.OBJECTIVE To evaluate the length of pooled learning curves of MIDP in experienced centers.DESIGN, SETTING, AND PARTICIPANTS This international, multicenter, retrospective cohort study included MIDP procedures performed from January 1, 2006, through June 30, 2019, in 26 European centers from 8 countries that each performed more than 15 distal pancreatectomies annually, with an overall experience exceeding 50 MIDP procedures. Consecutive patients who underwent elective laparoscopic or robotic distal pancreatectomy for all indications were included. Data were analyzed between September 1, 2021, and May 1, 2022.EXPOSURES The learning curve for MIDP was estimated by pooling data from all centers.MAIN OUTCOMES AND MEASURES The learning curvewas assessed for the primary textbook outcome (TBO), which is a composite measure that reflects optimal outcome, and for surgical mastery. Generalized additive models and a 2-piece linear model with a break point were used to estimate the learning curve length of MIDP. Case mix-expected probabilities were plotted and compared with observed outcomes to assess the association of changing case mix with outcomes. The learning curve also was assessed for the secondary outcomes of operation time, intraoperative blood loss, conversion to open rate, and postoperative pancreatic fistula grade B/C.RESULTS From a total of 2610 MIDP procedures, the learning curve analysis was conducted on 2041 procedures (mean [SD] patient age, 58 [15.3] years; among 2040 with reported sex, 1249 were female [61.2%] and 791 male [38.8%]). The 2-piece model showed an increase and eventually a break point for TBO at 85 procedures (95% CI, 13-157 procedures), with a plateau TBO rate at 70%. The learning-associated loss of TBO rate was estimated at 3.3%. For conversion, a break point was estimated at 40 procedures (95% CI, 11-68 procedures); for operation time, at 56 procedures (95% CI, 35-77 procedures); and for intraoperative blood loss, at 71 procedures (95% CI, 28-114 procedures). For postoperative pancreatic fistula, no break point could be estimated.CONCLUSION AND RELEVANCE In experienced international centers, the learning curve length of MIDP for TBO was considerable with 85 procedures. These findings suggest that although learning curves for conversion, operation time, and intraoperative blood loss are completed earlier, extensive experience may be needed to master the learning curve of MIDP

Characteristics of Different Systems for the Solar Drying of Crops

Solar dryers are used to enable the preservation of agricultural crops, food processing industries for dehydration of fruits and vegetables, fish and meat drying, dairy industries for production of milk powder, seasoning of wood and timber, textile industries for drying of textile materials. The fundamental concepts and contexts of their use to dry crops is discussed in the chapter. It is shown that solar drying is the outcome of complex interactions particular between the intensity and duration of solar energy, the prevailing ambient relative humidity and temperature, the characteristics of the particular crop and its pre-preparation and the design and operation of the solar dryer

7th Drug hypersensitivity meeting: part two

No abstract availabl

Deployment of AI-based RBF network for photovoltaics fault detection procedure

In this paper, a fault detection algorithm for photovoltaic systems based on artificial neural networks (ANN) is proposed. Although, a rich amount of research is available in the field of PV fault detection using ANN, this paper presents a novel methodology based on only two inputs for the training, validating and testing of the Radial Basis Function (RBF) network achieving unprecedented detection accuracy of 98.1%. The proposed methodology goes beyond data normalisation and implements a ‘mapping of inputs’ approach to the data set before exposing it to the network for training. The accuracy of the proposed network is further endorsed through testing of the network in partial shading and overcast conditions

Anthropogenic intensification of short-duration rainfall extremes

Short- duration (1-3 h) rainfall extremes can cause serious damage to societies through rapidly developing (flash) flooding and are determined by complex, multifaceted processes that are altering as Earth's climate warms. In this Review, we examine evidence from observational, theoretical and modelling studies for the intensification of these rainfall extremes, the drivers and the impact on flash flooding. Both short- duration and long- duration (\textgreater1 day) rainfall extremes are intensifying with warming at a rate consistent with the increase in atmospheric moisture (~7% K-1), while in some regions, increases in short- duration extreme rainfall intensities are stronger than expected from moisture increases alone. These stronger local increases are related to feedbacks in convective clouds, but their exact role is uncertain because of the very small scales involved. Future extreme rainfall intensification is also modulated by changes to temperature stratification and large- scale atmospheric circulation. The latter remains a major source of uncertainty. Intensification of short- duration extremes has likely increased the incidence of flash flooding at local scales and this can further compound with an increase in storm spatial footprint to considerably increase total event rainfall. These findings call for urgent climate change adaptation measures to manage increasing flood risks