Governance structures in cooperative slaughterhouses: a study on the chain of differentiated beef in the state of Paraná

This study sought to discuss the governance structures adopted between livestock producers and their cooperative slaughterhouses in the chain of differentiated beef in the state of Paraná. The theoretical basis used was the Transaction Cost Economics and Measurement Costs Economics, complemented by the specificities of cooperatives. We conducted interviews with three key agents and eleven representatives of six cooperative slaughterhouses operating in this system. As result, we observed that the cooperatives have similar objectives and requirements, although there are differences in the levels of formality or flexibility. Although transactions are recurrent and have been successful, they involve a high asset specificity, depend on subjective measurements, and are still exposed to market uncertainties, which leaves room for the generation of conflicts and disincentives to quality. Despite this, the relational and reputational aspects associated with trust and partnership between the parties are elements that enable reduced transaction and measurement costs in these structures. At first, the measurements conducted by the cooperatives had an important role in the construction of trust between the parties and for value distribution. In a second moment, the trust built enabled the reduction of measurement costs.

CALCULATION OF CLIMATE LOADS DESIGN VALUES ACCORDING TO THE PROBABILITY MODEL OF ANNUAL MAXIMUM SERIES

The aim of this work is to improve a method for determining the characteristic values of climatic loads according to a probabilistic model of the annual maxima sequence, by choosing a rational type of generalized extreme value distribution law. An analysis is provided regarding the suitability of using four types of distributions for describing a data collection of maximum values of climatic loads. Using example data from the meteorological stations of Ukraine, it is found that for coefficients of variation smaller than 0.85–1.0, it is advisable to use the double exponential Gumbel distribution (generalized extreme value distribution type-I), and at higher values of the coefficient of variation, it is advisable to use the Weibull distribution (generalized extreme value distribution type-III). Recommendations are provided for considering the accuracy in the estimations of the characteristic values of loads according to the probabilistic model for the annual maximum value series.

Modeling the wind speed in North Morocco

The change of the wind speed is strictly related to several natural factors such as local topographical and the ground cover variations, then any adjustment has to take into account the statistical variation for each specific region under study. Unlike the Weibull distribution, which is most used in wind speed modeling, we investigate two alternative distribution functions for wind speed by using the extreme value theory. The generalized Champernowne distribution function and the mixture Log-normal-Pareto distribution function are considered. We demonstrate that the proper generalized extreme value distribution gives a good fit for wind speed in the North Moroccan. In order to validate the models, a comparison of the produced aggregate wind energy in the aeolian wind turbine was being established. The empirical study shows that the generalized extreme value distribution reflects better the intensity of the wind power energy.

A Study on Estimating Land Value Distribution for the Talingchan District, Bangkok Using Points-of-Interest Data and Machine Learning Classification

Land is an essential factor in real estate developments, and each location has its unique characteristics. Land value is a vital cost of real estate developments. Higher land costs mean that project developers must create higher valued products to cover the higher land costs and to maintain a profit level from their developments. Land values vary according to surrounding factors, such as environment, social, and economic situations. Machine learning is a popular data estimation technique that enables a system to learn from sample data; however, there are few studies on its use for estimating land value distribution. Therefore, we aim to apply the technique of machine learning to estimate land value and to investigate the factors affecting the land value in the Talingchan district, Bangkok., we used land value level as the dependent variable, with other factors affecting land value levels as the independent variables. Ten points of interest were chosen from Google Places API. Then, three machine learning algorithms, namely CART, random forest, support vector machine, were applied. For this study, we selected 45,032 land parcels as the experimental data and randomly divided them into two groups. The first 70% of the land parcels was used to create the training area. The other 30% of the land parcels was used to create the testing area to verify the accuracy of the land value estimation from the applied machine learning techniques. The most accurate machine learning results were produced by random forest, which were then used to measure the factor importance. The academic group factor was school, and the commercial group factors were clothing store, pharmacy, convenience store, hawker stall, grocery store, automatic teller machine, supermarket, restaurant, and company.

Characteristic estimation of differential polynomials

In this paper, we give the characteristic estimation of a meromorphic function f with the differential polynomials $f^{l}(f^{(k)})^{n}$ f l ( f ( k ) ) n and obtain that $$\begin{aligned} T(r,f)\leq M\overline{N} \biggl(r,\frac{1}{f^{l}(f^{(k)})^{n}-a} \biggr)+S(r,f) \end{aligned}$$ T ( r , f ) ≤ M N ‾ ( r , 1 f l ( f ( k ) ) n − a ) + S ( r , f ) holds for $M=\min \{\frac{1}{l-2},6\}$ M = min { 1 l − 2 , 6 } , integers $l(\geq 2)$ l ( ≥ 2 ) , $n(\geq 1)$ n ( ≥ 1 ) , $k(\geq 1)$ k ( ≥ 1 ) , and a non-zero constant a. This quantitative estimate is an interesting and complete extension of earlier results. The value distribution of a differential monomial of meromorphic functions is also investigated.