A probabilistic study of monsoon daily rainfall at Calcutta by Markovian model and trend of rainfall during monsoon season

One-step transitional probability matrices are obtained by Markovian model from one transitional state to other for different rainfall characteristics (such as, non-rainy days, light rains, moderate rains, heavy rains and very heavy rains) at Calcutta (Alipore) for different monsoon months. The disorderness (unvertainty) of the transitional system of the monsoon rainfall characteristics are studied by Shannon’s model. The favourable or unfavourable condition of different states are also studied by redundancy test during monsoon period at Caluctta. A Long-run probability vectors of such rainfall characteristics are found out from probability matrices. A trend in rainfall amounts during monsoon period at Calcutta for each of the monsoon month, June to September, has also been studied here.

A Characteristic Polynomial for the Transition Probability Matrix of Correlated Random Walks on a Graph

We define a correlated random walk (CRW) induced from the time evolution matrix (the Grover matrix) of the Grover walk on a graph $G$, and present a formula for the characteristic polynomial of the transition probability matrix of this CRW by using a determinant expression for the generalized weighted zeta function of $G$. As an application, we give the spectrum of the transition probability matrices for the CRWs induced from the Grover matrices of regular graphs and semiregular bipartite graphs. Furthermore, we consider another type of the CRW on a graph.

Spatial Transformation of the Pig Sector in Hungary and Slovenia: A Comparative Analysis

This paper presents a comparative analysis of the spatial transformation in the Hungarian and Slovenian pig sectors at the level of local administrative units (LAU). Concentration and inequality measures were applied in the empirical analyses, along with Markov transition probability matrices, to examine the stability and/or mobility over time and the presence of clustering effects. Both countries experienced a rapid decline in pig population. This profound structural change has led to a smaller number of more concentrated pig farms and increased territorial concentration. The degree of farm and territorial concentration and inequality in Hungary has been much higher than in Slovenia, and the concentration gap between the countries has increased. Between 2000 and 2010, the degree of concentration was much higher in Hungary than in Slovenia; average herd size per holding increased by 68 percent in Hungary, and only seven percent in Slovenia. In Hungary, clustering effects were particularly significant, with the pig sector moving towards large-scale concentration. The former effect was also confirmed in the Slovenian pig sector, but significantly weakened during the period under investigation. The exploitation and policy management of spatial externalities justifies these agricultural, economic, and agri-environmental practices.

ASSORTMENT DOWNGRADE CORRECTION FOR CLEAR CUT OF Pinus taeda L. WITH USE OF TRANSITION MATRIX

It is very important that the quantification of a forest's stock is determined efficiently and accurately, in such a way that more detailed information is desirable for the knowledge of the different multiproducts originated. However, the use of taper functions, a precise adjustment method for determining the assortments, does not foresee the appearance of defects in the stem that could disqualify the logs during the forest harvest. This study aimed to use the transition matrix method, a model traditionally used for predict the diametric structure of uneven-aged forests, to correct assortment estimates made by tapering functions, such as failures in tree processing, that provide a disqualification of the logs in the market values. Adapting the concept of the Markov Chain, for the correction of the assortment downgrade, the transition of the assortment classes can be obtained by dividing the actual volume obtained after the operation of the harvesting machine by the volume estimated by the tapering function. In this case, applying this alternative to the clear cut of a 16-year-old Pinus taeda plantation, it was possible to verify the existence of changes, mainly in assortment classes with a thin end diameter of 24 and 18 cm and presenting efficient correction in the estimates. In order to make realistic corrections to the assortment transition, probability matrices must be built for each compartment or forest site to be estimated. Divergences between processing machines or forestry operator’s qualifications can be decisive for the calibration of the model.

Profitability of fungicide applications for managing soybean rust in scenarios of variable efficacy and costs: a stochastic simulation

Soybean rust (SBR) in Brazil is controlled with fungicides, which have shown variable, eventually declining, efficacy. A Monte Carlo simulation framework was proposed to approximate profitability depending on the fungicide program's efficacy and total cost. Probability distributions were fitted to slopes and intercepts of the disease-yield relationship and severity in the untreated plots reported in the literature, as well as historical records of soybean price. Simulations of disease reduction conditioned to predefined control efficacy and total application costs were split into scenarios that combined two categories of severity (high and low) and two attainable yield classes (high and low). These categories were defined based on the median of severity (57.8%) and median of the intercept (yield when severity is zero, 2995.1 kg/ha). Probability matrices were constructed relating fungicide efficacy and costs. A higher frequency of break-even events occurred in scenarios of high disease pressure and higher yield. Yearly simulations, starting with 79.4% efficacy, assuming two rates of decline determined for tebuconazole (high decline), showed that the program may remain profitable during the first 5 to 7 years of use. Contrasting to cyproconazole, a fungicide that would be profitable during the entire decade. These simulations can be useful to aid in decision-making when planning fungicide programs. This approach can be adapted to other diseases of soybean and other crops as long as damage functions are available. An interactive web app was developed to perform the simulations accessible at alvesks.shinyapps.io/rusty-profits/.

Export Competitiveness of Indian Mango: Determinants and Empirical Evidences

The main objective of the present study was to work out the export competitiveness of Indian mango and policy recommendations for improvement in its export and the destinations as well. To achieve the objectives, various tools such as net terms of the trade revealed comparative advantage, and Markov chain analysis was applied to mango export data from 1999-2019. The estimations of net terms of trade and revealed comparative advantage discovered that India has a comparative advantage for exporting mango. It is evident from the transitional probability matrices developed through Markov chain analysis that Qatar was the most loyal buyer for Indian mango during this period. The attention should be focused on the market requirement and specifications of Qatar, Bangladesh, UAE and the UK as they were the most stable buyers of Indian mango.

Assessing Aircraft Performance in a Warming Climate

Increases in maximum and minimum air temperatures resulting from anthropogenic climate change will present challenges to aircraft performance. Elevated density altitude (DA) reduces aircraft and engine performance and has a direct impact on operational capabilities. The frequency of higher DA will increase with the combination of higher air temperatures and higher dewpoint temperatures. The inclusion of dewpoint temperature in DA projections will become increasingly critical as minimum air temperatures rise. High DA impacts aircraft performance in the following ways: reduction in power because the engine takes in less air; reduction in thrust because a propeller is less efficient in less dense air; reduction in lift because less dense air exerts less force on the airfoils. For fixed-wing aircraft, the performance impacts include decreased maximum takeoff weight and increased true airspeed, which results in longer takeoff and landing distance. For rotary-wing aircraft, the performance impacts include reduced power margin, reduced maximum gross weight, reduced hover ceiling, and reduced rate of climb. In this research, downscaled and bias-corrected maximum and minimum air temperatures for future time periods are collected and analyzed for a selected site: Little Rock Air Force Base, Arkansas. Impacts corresponding to DA thresholds are identified and integrated into risk probability matrices enabling quantifiable comparisons. As the magnitude and frequency of high DA occurrences are projected to increase as a result of climate change, it is imperative for military mission planners and acquisition officers to comprehend and utilize these projections in their decision-making processes.

Empirical vulnerability curves for Italian mansory buildings: evolution of vulnerability model from the DPM to curves as a function of accelertion

In the framework of the emergency management in the case of seismic events, the evaluation of the expected damage represents a basic requirement for risk informed planning. Seismic risk is defined by the probability to reach a level of damage on given exposed elements caused by seismic events occurring in a fixed period and in a fixed area. To this purpose, the expected seismic input, the exposed elements and their vulnerability have to be correctly evaluated. The aim of the research is to define a correct model of vulnerability curves, in PGA, for masonry structures in Italy, by heuristic approach starting from damage probability matrices (DPMs). To this purpose, the PLINIVS database, containing data on major Italian seismic events, has been used and supported by “critical” assumption on missing data. To support the reliability of this assumption, two vulnerability models, considering or not the hypothesis on the missing data, have been estimated and used to calculate the seismic scenario of the L’Aquila 2009 earthquake through the IRMA (Italian Risk MAp) platform. Finally, a comparison between the outcomes elaborated by IRMA platform and the observed damage collected in the AEDES forms, has been done.

An analysis of direction of trade in select Indian agricultural commodities

An attempt is made in this paper to assess the dynamics of changes in exports of agricultural commodities namely, maize, chilli and Bengal gram, from India to different export markets by employing Markov chain model. The study is based on a set of countries importing agricultural commodities namely Nepal, others (pooled countries except selected countries) and Bangladesh were the most stable importers of the Indian maize with a probability of retention of 88.52 per cent, 68.90 percent and 61.09 per cent, respectively. The changing pattern of chilli exports through transitional probability matrices indicated that Thailand, other countries (pooled countries) and Vietnam were stable in importing Indian chilli with a probability of retention of 80.52 per cent, 69.02 per cent and 67.09 per cent, respectively. In case of Bengal gram, Pakistan was one of the stable countries as revealed by a probability of retention of its share i.e., 61.35 per cent. Algeria was also another stable importer as it retained its original share of 45.54 per cent followed by Turkey 41.13 per cent. The overall conclusion that emerges from present study is that Nepal, Thailand and Pakistan turned out to be the most stable countries in respect of importing Indian maize, chilli and Bengal gram.