Technical Coefficients Research Articles

Methodological proposal to approximate the sectoral impacts of a carbon tax at the regional level – the case of Chile

This study proposes a methodological approach to approximate the sectoral impacts of carbon taxes in the different regions of Chile through the environmental extension of intraregional input – output models. These models are calibrated by regionalizing technical coefficients using an indirect method called Industry-Specific Flegg Location Quotient. Carbon dioxide emissions at the regional and sectoral levels are obtained mainly from regional inventories of greenhouse gases, although in some sectors, they are calculated indirectly from fuel consumption. Then, tax scenarios are proposed that allow simulation of the effects on sectoral prices, levels of production, and emissions at the regional level. The results show that implementing an identical tax rate at the national level has a very heterogeneous impact on the country’s regions, with the regions of Atacama, Antofagasta, Valparaíso, and Biobío being the most affected economies in relative terms since most of the large thermoelectric power plants are located there.

Profitability, greenhouse gas emissions and feed-food competition of strategies to exploit compensatory growth in Uruguayan weanling-to-beef systems

This study evaluates nutritional and management strategies aimed at exploiting compensatory growth (CG) in weanling-to-beef systems in Uruguay. The evaluation encompassed productivity, economic viability, and environmental impact. The Grange Beef System Model, augmented with Uruguayan national technical coefficients, was used. Four weanling-to-beef systems were modeled: 1) forage only with no CG (FNC), 2) forage only with management improvements to exploit CG (forage with CG; FWC), 3) forage with concentrate supplementation during two winter feeding periods (forage with supplementation; FWS), and 4) forage with supplementation during the first winter followed by feedlot finishing (forage with feedlot; FWF). The systems purchased spring-born Angus calves at 8 months of age and 180 kg live weight (LW) and finished with a slaughter weight of 550 kg. FWS system was used as reference with the performance parameters obtained during 5 years of systems experimentation. FNC used the performance parameters of FWS but during winter periods, LW gain was lower due to the absence of concentrate supplementation. FWC used the previous FNC performance parameters, but increased LW gain after the first and second winter restriction period due to improved grazing management practices thereby exploiting CG. FWF is based on the FWS system but instead of moderate supplementation during the second winter (concentrate: 3.0 kg/d/head), steers are feedlot finished (concentrate: 9.5 kg/d/head) exploiting CG due to previous summer-autumn restriction period. FNC and FWC increased age at slaughter, reducing net beef production by 21 and 11 % relative to FWS, respectively. In contrast, FWF reduced age at slaughter, increasing beef production by 93 % compared to FWS. FWS and FNC had similar profitability expressed in net margin; however, FWC and FWF increased net margin by 33 and 107 % compared to the FWS, respectively. FNC and FWC increased greenhouse gas (GHG) emissions intensity per beef produced by 17 and 3 % relative to FWS, respectively; meanwhile, FWF reduced GHG intensity by 10 % relative to FWS. Due to the inclusion of concentrates in the diet for FWS and FWF systems, the only net producers of human edible energy and protein were the forage-only systems (FNC and FWC). In summary, strategically harnessing CG in both pasture and feedlot finishing stages within a weanling-to-beef system in Uruguay successfully increased profitability. Feedlot finishing reduced GHG emissions per beef produced. However, the forage-only farm systems emerged as the only net producers of human-edible energy and protein.

The Entropy and Energy for Non-Mechanical Work at the Bose-Einstein Transition of a Harmonically Trapped Gas Using an Empirical Global-Variable Method.

Quantum thermal engines have received much attention in recent years due to their potential applications. For a candidate group, harmonically trapped gases under Bose-Einstein condensation (BEC), we see little investigation on the energy transference around that transition. Therefore, we present an empirical study with rubidium-87 gas samples in a magnetic harmonic trap. We developed an empirical equation of state model to fit to our experimental dataset, expressing the pressure parameter in terms of temperature, and six technical coefficients, functions of the volume parameter and the number of atoms. By using standard thermodynamic relations, we determine the system's entropy, shown to be constant at the BEC transition, as expected. Being isentropic makes the BEC transition an energy source for non-mechanical work. Hence, we observed that the enthalpy at the BEC transition, at fixed values of the volume parameter, grows fairly linearly with the number of atoms. We fitted a linear function to that data, finding the specific enthalpy of the BEC transformation and the intrinsic enthalpic loss for BEC. We deem this study to be a step closer to practical quantum-based engines.

Enhancing dairy cow population through decreasing calf mortality and increasing calving rate in Indonesia: a system dynamics approach

Abstract The dairy industry in Indonesia is facing significant challenges due to the rates of calf mortality and low calving rates. Calf mortality and calving rate became critical factors that influence the sustainability of the dairy cow population. This study aimed to assess reproduction management by decreasing calf mortality and increasing calving rates to enhance the dairy cow population in Indonesia. This study employed secondary data in 2022 using technical parameter coefficients from previous research. A causal loop diagram and a simulation model using a system dynamics approach were developed to investigate the dynamics of the dairy cow population under different scenarios of calf mortality and calving rates from 2023 to 2030. The results showed that decreasing calf mortality by 2% may increase dairy cow population by 1,991 head/year (0.31%), heifer population by 417 head/year (0.63%), and adult female dairy cattle population by 389 head/year (0.09%). The finding of this study also showed that increasing calving rate by 5% may increase dairy cow population by 17,854 head/year (2.75%), heifer population by 3,698 head/year (5.56%), and adult female dairy cattle population by 2,137 head/year (0.51%). It is concluded that reducing calf mortality rates and improving calving rates should be prioritized to enhance the dairy cow population in Indonesia.

The Impact of the Change Type of Wagon on the Efficiency of the Single Wagon Consignments

Abstract The transportation of shipments by rail is usually more expensive than other modes of transport. The costs are dependent on different factors, like the length of the train route, energy consumption based on traction, or the number of crew members in the train. The total price for using the railway infrastructure is also calculated, as is the total weight of the railway vehicle—the weight of the shipment and the weight of the wagon. The different types of wagons have different properties. For the operators, it is an ideal situation to have good values of the technical coefficient of tare. In the case of good values, the operator has effectively used their vehicle park. Railway transport should be affordable for customers. By operating non-efficient wagons, transport is more expensive and has low efficiency. By reducing the dead weight of the wagon, it is possible to reduce the cost rate. In synergy with this, more efficient and eco-friendly transportation can be achieved by reducing energy consumption. By reducing energy consumption, it is possible to get closer to the goal of the European Union, which is to reduce greenhouse gases from transport.

OLE! Dairy model

The process of intensification of the dairy sector has been characterized in recent decades by the increase in milk production per hectare, the increase in livestock density, the inclusion of more concentrates in the diet, and the improvement of the genetic merit of dairy cows. The use of models has productive, environmental, and economic advantages. The objectives of the study were to describe a new model, “OLE! Dairy model”, to (a) simulate the biophysical performance of a pasture-based dairy production system; (b) evaluate the predictive capacity of the model with a set of statistical parameters, comparing its results with the biophysical performance of experimental studies of dairy farm systems, and (c) calibrate by adjusting the technical coefficient. The experimental design combines two feeding strategies with a different proportion of pasture in the diet and two animal genotypes. We make a description of the biophysical component and the calculations proposed in the “OLE! Dairy model”. Then a variety of parameters was calculated for model testing, including the Mean Squared Error, the Relative Prediction Error, the square root of the MSE, the Concordance Correlation Coefficient, and the Model Efficiency. The model presented a good predictive capacity for stocking rate and concentrate, pasture, and reserve intake. The predictive capacity of the model for individual production and area production improves after performing a rapid calibration, which allows for avoiding overestimations or underestimations that generate erroneous measurements in the planning and management of milk production systems, and can be adjusted to different conditions of production of the region.

A method for calculating the technical readiness of aviation refuelling vehicles

In the paper a mathematical model of the process of operating aviation refuelling vehicles supplying fuel to aircraft before flight was developed. The present work is a continuation and supplement to the model contained in [52]. The phase space of the process under study was mapped by a 7-state directed graph of the operation process. To calculate the technical readiness index (K_gt) Markov chains and processes were used. Also, in Section 3, Results and discussions, optional methods for determining the technical readiness coefficient of a vehicle were provided k_gt) , based on the total time of the object in individual operating states. This is an alternative in a situation where the analysed process cannot reach a stable average state indefinitely. Two types of measures were used to determine the readiness, i.e. border probabilities and average times of the object in individual states. In both cases, the basis was statistical databases with operational vehicle data, which enabled the calculation of the readiness index and coefficient.

Convergence between Green Technology and Building Construction in the Republic of Korea

This study examines the convergence between green technology and building construction in Korea using both input-output and network analysis from 1990 to 2015. The industry type of the input-output tables used in the Bank of Korea is reclassified into 20 categories. The analytical results are summarized as follows: First, the construction industry is expanding its production area by adopting green technologies (KRW 2245 billion → KRW 7842 billion). Second, the impact of green technologies on the growth rate of the construction industry is greater than that of traditional construction technologies (technical coefficient 0.5410 → 0.5831). Third, the results of the analysis show that smart green technology enhances efficiency in the construction industry (multiplier coefficient 2.3673 → 2.4972). Our input-output model reveals that the smart green technology coefficient input to construction is relatively small, but the output is bigger in effects. Also, the results of the input-output analysis show that both hardware and software smart technologies continuously increase energy demand. Finally, the network analysis demonstrates the rapid convergence of smart technologies in the construction industry (pathway 13 → 22). These results demonstrate that smart green technology leads to a high value-added output in the construction industry.

MELEIRA IMPACTS IN THE PROFITABILITY OF PAPAYA PRODUCTION IN THE EXTREME SOUTH OF BAHIA

This study evaluated the losses caused by meleira in the profitability of the papaya production in the extreme south of Bahia. The evaluation was based on the technical coefficients of the papaya system of integrated production for the south of Bahia, and information obtained from producers and technical consultants in the municipalities of Eunápolis, Itabela and Porto Seguro. The technical coefficients considered present the quantitative needed for one hectare of papaya, from Formosa and Hawaii groups under irrigated conditions. Based on these coefficients, the profitability analysis was performed. For calculations of the damage caused by meleira, losses of 5%, 10%, 20%, 30%, 40%, 50%, and 60% of eradicated plants were considered. The profitability indicators used were NPV, IRR and BCR. Considering the survey of average prices paid to the producer, the profitability indicators for the Hawaii papaya variety were positive for up to 50% of losses, while those in Formosa were up to 60% of losses.

Are input-output coefficients really fixed?

ABSTRACT It is standard practice to treat input-output (I-O) technical coefficients as fixed. The coefficients are fixed when σ , the elasticity of substitution, is zero, a restriction mostly not supported by 25 years of I-O tables for Australia. We offer a simple way of allowing for variable coefficients with a CES approach. Finally, using various values of σ in CGE simulations establishes that taking coefficients as fixed has misleading economic implications.

Analysis of the technical condition of gas turbine plants. Part 3. Application of machine learning methods

A method for estimating the technical condition coefficient of a gas turbine unit for transporting of natural gas using machine learning methods is considered. Archival gas-dynamic parameters recorded by the installation’s automatic control system are used as initial data. The initial data set was created by determining power from the change in enthalpy of natural gas before and after the blower. The software package is implemented in Python; the Scikit-learn library is used for machine learning models. The average absolute error in percentage is chosen as a criterion for the quality of the prediction. The prediction quality of machine learning models is assessed for different sets of parameters-features and sample sizes. Recommendations on the use of models are given. Keywords: gas turbine unit, technical condition, measuring system, data processing, machine learning. v.l.blinov@urfu.ru; deryabingleb.were@gmail.com

МЕТОДИКА ОЦЕНКИ ЭФФЕКТИВНОСТИ ПРИМЕНЕНИЯ ПРЕДУПРЕДИТЕЛЬНОГО РЕМОНТА ДЛЯ ЗАДНЕГО МОСТА АВТОБУСА

The efficiency of operating commercial vehicles is analyzed. Statistical results of failures of parts of the rear axle of the bus are presented and graphs of the probability of failure-free operation of the units are constructed. It is noted that fuzzy formalization will be used in the rear axle reliability model. A technique has been proposed to increase the technical readiness coefficient of the bus. The results of calculations of the technical readiness coefficient are presented, from which it is clear what contribution each detail makes to its change.

Introducing the technical individual contribution coefficient: a metric for evaluating performance in elite volleyball

ABSTRACT This study introduces a new metric, the Technical Individual Contribution Coefficient, that enables the quantification of the individual technical performance in elite volleyball, from the practical perspective of coaches. Additionally, three Relative Individual Contribution Coefficients provide complimentary information on the players’ relative participation. Data from 20 matches of eight teams during the 2019 Club World Championship were provided by Data Volley software. The numerical evaluation of the players’ actions was based on experts’ ratings, and all calculations were carried out using Python programming. Binomial logistic regression and the areas calculated under the receiver operating characteristic curves were utilised to predict set outcomes based on team variables. For individual analysis, Spearman’s rho correlations and multiple descriptive analyses were conducted, and dynamic visualisations in Power BI were employed to enhance interpretation. The proposed coefficients efficiently predict both absolute and relative technical performance, across all game actions. This novel metric offers a comprehensive tool for performance evaluation and has significant potential to benefit not only fans and the media, but also coaches and team managers in their decision-making process for player selection. The dynamic visualisations utilised make it easier to understand multiple comparisons and to identify ways for improving performance.

Optimization of a production unit of the dairy agroin-dustry: Chapingo dairy technology unit case

Objective: To evaluate the optimization level of a dairy production unit (DPU) through a mathematical programming model (MP). It is expected that by maximizing net income by at least 10%, the DPU will be more profitable than without optimized management. Design/Methodology/Approach: The analysis was carried out under the economic approach of agricultural production, taking into consideration 11 decision variables in the objective function (OF), which was subject to 20 constraints. The variables were based on the requirements of the demand for dairy by-products, using technical coefficients (input-output coefficient). Excel® Solver® was used to develop the sensitivity report and to analyze the shadow prices and reduced costs. Results: Three scenarios were modeled. Between the first and third scenario, the income increased to $58,000.00 (41.02%). Between the second and third scenario, the income increased to $63,840.00 (46.16%). Study Limitations/Implications: Dairy food processing is an important industry in the economies of the world. Findings/Conclusions: Panela cheese recorded the highest shadow price ($72.85), which indicates that the DPU should concentrate on this type of dairy product. In conclusion, the optimization of the DPU guarantees the efficient use of scarce resources and therefore generates a higher profit.

Bringing to light a new energy path: the case of the state of Minas Gerais, Brazil

In Brazil, more than 55% of the energy comes from hydroelectricity, making the system highly vulnerable in the context of global climate change, with precipitation and temperature shifts over the years. Characterised by its multiple opportunities in sources and conversion technologies for energy, biomass has a high potential to become responsible for a relevant share of the renewable energy supply. Previous studies on biomass energy production in Brazil confirm promising results. This paper highlights possibilities for biomass power generation in Minas Gerais State. To estimate energy productivity, a Sustainable Technical Coefficient was adopted: a conservative index that considers the portion of residues that could be used to maintain the integrity of the soil. This index was applied with the data on silviculture and selected crop yields. The local energy demand was also calculated and compared to the potential energy production. Results show that 78% of the municipalities could have their basic energy needs and 18% of the demand for productive uses met by crop residues and silviculture production. For the state of Minas Gerais, with its tradition of agriculture, biomass residual energy is viable and should be considered by policymakers.

Determining Leading Industries in Optimizing Downstream Potential of North Sumatra Province: an Input-Output Approach

The economic condition of North Sumatra province due to the COVID-19 pandemic has weakened, especially on the supply side, by a negative growth rate in the productivity of the business sector. Industrial downstream could boost economic recovery and inclusive development by creating solid domestic relations with supporting regional industries and increasing high-value-added exports. This study aims to identify priority sectors and analyze the impact of these priority sectors on the manufacturing industry in North Sumatra based on linkage analysis using data during the economic recovery. The data from the I-O table of North Sumatra province in 2016 was sourced from the Central Statistics Agency (BPS) and covered 50 economic sectors. In addition, this study also used data on the GRDP of North Sumatra in 2021. This study applied the RAS Method to determine the value of the technical coefficient matrix of the input-output table in 2021. Then, this study also calculated the value of forward and backward linkages, output multiplier, value-added multiplier, and inoperability. The results revealed three priority sectors in North Sumatra, the Food and Beverage industry; the Base Metal industry; and the Paper and Paper Goods industry, Printing and Reproduction of Recording Media. The study recommends that the government encourage the acceleration of infrastructure by providing financial and policy support to these leading sectors and facilitating distribution channels so that industrial downstream runs optimally to the overall economy.

Goodness Test of Adaptability to Model of Technical Changes and Test of Forecasting Accuracy

The technical coefficient input-output as an element of the technical coefficient matrix (A) is estimated to have good forecasts for the next several periods . By substituting the final demand (F) for the period into the Input Output (IO) model in the equation the total output for the period will be obtained from the forecasting results. The total output of forecasting results is then compared with the actual total output to see the magnitude of the deviation. In the regression equation, the coefficient of determination is a measure of “goodness of fit” which states how well the regression line explains the independent variable with the dependent variable. The test is carried out by regressing the technical coefficient of input-output in the year against the technical coefficient in the nth year in a simple linear regression equation . This test was conducted to see the validity of the technical coefficients in forecasting the IO model. This research is an empirical study that uses data from the Jambi Province Input Output Tables in 1998, 2007 and 2016, each of which has been collected in a common set to see the comparability between observation periods. The results show that the technical change model is quite well used for forecasting according to the assumption that the technical coefficient level is constant during the planning period. Meanwhile, the estimated output deviation tends to be higher than that of the actual data.

Stochastic Frontier Analysis of Technical Efficiency and Profitability of Dry Season OKRA Production in Nigeria

Food production in Nigeria is almost entirely rain fed despite the great potential of irrigation in Nigeria to boost agricultural productivity. The study assessed the profitability and efficiency of dry season irrigated okra farming in Adamawa State using primary data collected from 180 farmers through a simple random sampling technique. Profit efficiency and stochastic frontier function were used in analyzing the data. The result revealed that labor costs accounted for 48% of average variable cost while a farmer’s total revenue from irrigated okra produce was ₦228,642.56K ($408.2), total fixed cost and variable input cost was ₦102,440.37K ($182.93), resulting in a net farm income (NFI) of ₦126,201.63K ($225.36). The coefficients of farm size, household size, and fertilizer were positive and significant at the 1%, 10%, and 5% levels of probability, respectively, as revealed by the OLS results. Empirical estimate shows that the mean technical efficiency value of vegetable farmers was about 0.73 while Technical inefficiency coefficient of farming experience (−0.420), adjusted household size (−0.193), and extension contacts (−0.162) are variables that increased technical efficiency. Lack of access to water, high cost of equipment, and inadequate finance were identified as lead constraints of the okra farmers. Therefore, recommendations by the study are that farmers be encouraged to establish cooperative organizations so that they can pool their resources to create an irrigation system that is affordable. Also, sustainability of small scale irrigation scheme should be promoted by the government through skill enhanced trainings.

Economic analysis of olivine melilitite powder as an alternative source of nutrients in maize cultivation

Agriculture is characterized by the high use of fertilizers to promote higher income expectations and, due to the representativeness of this input, the cost of agricultural production is strongly affected. The present study aims to evaluate the economic efficiency of the association of olivine melilitite powder with beneficial microorganisms and the reduction of 25% chemical fertilization in maize cultivation. Five treatments were tested under a randomized block design with four replicates, represented by the application of the remineralizer associated with inoculation of bacteria of the genera Bacillus spp. and Azospirillum spp. with a 25% reduction in the recommended basal fertilization, plus fertilization with only formulated fertilizer as control treatment. The economic technical coefficients were evaluated: Gross Revenue (GR), Operating Profit (OP), Total Operating Cost (TOC), Leveling Point (LP), Profitability Index (PI) and Yield (YLD). Application of remineralizer associated with inoculation of bacterial strains of the genera Bacillus spp. and Azospirillum spp. showed the best economic indicators, promoting increments of up to 7% in PI and 15% in OP, and grain yield remained at high levels. However, application of remineralizer without inoculation of microorganisms negatively impacted grain yield, reducing PI, OP and GR. Pearson’s coefficients indicate a strong relationship of the YLD variable with PI and OP, enabling the application of olivine melilitite powder as an alternative source of nutrients in the cultivation of off-season maize. It is concluded that the application of olivine melilitite powder is economically viable and increases the profitability index, while keeping maize yield at high levels when associated with inoculation of bacteria of the genera Bacillus spp. and Azospirillum spp.

Rentabilidade do cultivo orgânico de cenoura sob interferência de plantas espontâneas e métodos de semeadura

ABSTRACT Spontaneous plants in vegetable growing areas significantly impact yield and costs, regardless of the adopted cultivation system. This study aimed to evaluate weed interference periods on the profitability of organic carrot cultivation under different sowing methods. Two experiments were set up [weed control and coexistence, in a randomized block design arranged as split plots (5 × 2), with five cultivation periods: 15, 20, 25, 30 and 35 days after sowing] and two sowing methods were applied: direct and water-conditioned sowing. Based on the production data and technical coefficients, the economic evaluation of production was carried out, with calculation of production costs and revenues. The highest net revenue was obtained when the growing area was kept clean for 19 to 30 days. The total revenue increased linearly by R$ 0.33 m−2 for each day of weed control, while, for the coexistence treatment, it decreased by R$ -0.37 m−2. The water-conditioned sowing increased the economic indicators of the organic carrot cultivation.