scholarly journals The Whole and the Parts—A New Perspective on Production Diseases and Economic Sustainability in Dairy Farming

2021 ◽  
Vol 13 (16) ◽  
pp. 9044
Author(s):  
Susanne Hoischen-Taubner ◽  
Jonas Habel ◽  
Verena Uhlig ◽  
Eva-Marie Schwabenbauer ◽  
Theresa Rumphorst ◽  
...  
Keyword(s):  
Principal Component ◽  
Dairy Farming ◽  
Economic Sustainability ◽  
Replacement Rate ◽  
Accounting Data ◽  
Average Proportion ◽  
Production Diseases ◽  
Point Data ◽  
New Perspective ◽  
Break Even Point

The levels of production diseases (PD) and the cow replacement rate are high in dairy farming. They indicate excessive production demands on the cow and a poor state of animal welfare. This is the subject of increasing public debate. The purpose of this study was to assess the effect of production diseases on the economic sustainability of dairy farms. The contributions of individual culled cows to the farm’s economic performance were calculated, based on milk recording and accounting data from 32 farms in Germany. Cows were identified as ‘profit cows’ when they reached their individual ‘break-even point’. Data from milk recordings (yield and indicators for PD) were used to cluster farms by means of a principal component and a cluster analysis. The analysis revealed five clusters of farms. The average proportion of profit cows was 57.5%, 55.6%, 44.1%, 29.4% and 19.5%. Clusters characterized by a high proportion of cows with metabolic problems and high culling and mortality rates had lower proportions of profit cows, somewhat irrespective of the average milk-yield per cow. Changing the perception of PD from considering it as collateral damage to a threat to the farms’ economic viability might foster change processes to reduce production diseases.

Profitability of dairy farming in relation to the type of feeding system

2011 ◽  
Vol 28 (1) ◽  
pp. 55-59 ◽  
Author(s):  
Jan Frelich ◽  
Martin Šlachta ◽  
František Střeleček ◽  
Jana Lososová
Keyword(s):  
Arable Land ◽  
Principal Component ◽  
Dairy Farming ◽  
Plant Production ◽  
Feeding Strategies ◽  
Feeding System ◽  
Financial Health ◽  
Profit Rate ◽  
Permanent Housing ◽  
Cow Performance

Profitability of dairy farming in relation to the type of feeding systemWe investigated the profitability of dairy farms in relation to the type of feeding system (seasonal pasture vs. permanent housing). An economic analysis was carried out of data on the structure and financial health of 50 farms in 2007 using questionnaires filled in by the farmers. The Principal Component Analysis (PCA) was applied to reveal causal relationships between a number of characteristics of the farms. The two axis of PCA explained 40.48% and 16.13% of the variability among the selected farm characteristics. Profitability related more to the number of subsidies, the area of arable land, the number of livestock and to the milk and plant production than to the area of meadows and pastures. Although a better cow performance was achieved on farms with confined herds, the profit per agricultural area and profit rate did not differ significantly between the two feeding strategies (P>0.05). The profit was 3,259 and 3,655 CZK/ha on average and the profit rate 7.9% and 5.6% on average on farms with pastured herds and on farms with confined herds, respectively. A lowering of input costs and a more effective utilisation of grasslands may further enhance profitability.

scholarly journals Biomimetic Sonar for Electrical Activation of the Auditory Pathway

2017 ◽  
Vol 2017 ◽  
pp. 1-10 ◽  
Author(s):  
D. Menniti ◽  
S. A. Pullano ◽  
M. G. Bianco ◽  
R. Citraro ◽  
E. Russo ◽  
...  
Keyword(s):  
Spatial Information ◽  
Electronic Device ◽  
Principal Component ◽  
Auditory Pathway ◽  
Brain Response ◽  
Implanted Electrodes ◽  
System A ◽  
Signal Features ◽  
New Perspective ◽  
Rate Frequency

Relying on the mechanism of bat’s echolocation system, a bioinspired electronic device has been developed to investigate the cortical activity of mammals in response to auditory sensorial stimuli. By means of implanted electrodes, acoustical information about the external environment generated by a biomimetic system and converted in electrical signals was delivered to anatomically selected structures of the auditory pathway. Electrocorticographic recordings showed that cerebral activity response is highly dependent on the information carried out by ultrasounds and is frequency-locked with the signal repetition rate. Frequency analysis reveals that delta and beta rhythm content increases, suggesting that sensorial information is successfully transferred and integrated. In addition, principal component analysis highlights how all the stimuli generate patterns of neural activity which can be clearly classified. The results show that brain response is modulated by echo signal features suggesting that spatial information sent by biomimetic sonar is efficiently interpreted and encoded by the auditory system. Consequently, these results give new perspective in artificial environmental perception, which could be used for developing new techniques useful in treating pathological conditions or influencing our perception of the surroundings.

Visualization of tax avoidance and tax rate convergence

2019 ◽  
Vol 27 (5) ◽  
pp. 695-724 ◽  
Author(s):  
Chika Saka ◽  
Tomoki Oshika ◽  
Masayuki Jimichi
Keyword(s):  
Tax Avoidance ◽  
Tax Rates ◽  
Cross Sectional ◽  
Effective Tax Rates ◽  
Accounting Data ◽  
Content Type ◽  
Tax Rate ◽  
Objective Evidence ◽  
New Perspective ◽  
Convergence Trend

Purpose This study aims to explore the evidence of the probability of firms’ tax avoidance and the downward convergence trend of national statutory tax rates and firms’ effective tax rates. Design/methodology/approach This research employs exploratory data analysis using interactive data manipulation and visualization tools, namely, R with SparkR, dplyr, ggplot2 and googleVis (GeoChart and Motion Chart) packages. This analysis is based on the world-scale accounting data of all listed firms from 148 countries spanning 30 years. Findings The results reveal the following: three types of evidences on probability of firms’ tax avoidance, showing a non-random distribution of firms’ effective tax rates and return on assets, cross-sectional variation of firms’ effective tax rates in each country, and the trend of difference between effective tax rates and statutory tax rates, and the downward convergence trend of statutory tax rates and firms’ effective tax rates. Practical implications The results highlight the prominent issues of world-scale tax avoidance and tax rate competition and facilitate a collaborative discussion between laymen and professionals using objective evidence. Originality/value A novel methodology is adopted through the visualization of world-scale accounting data, which can facilitate a new perspective, revealing unexpected patterns and trends in otherwise hidden information. This study also highlights the importance of global consideration of firms’ tax avoidance and tax rate competition, using objective evidence.

scholarly journals Gestão dos custos em uma propriedade leiteira familiar do sul de Minas Gerais

ForScience ◽  
2020 ◽  
Vol 8 (2) ◽  
pp. e00528
Author(s):  
Leandro Carvalho Bassotto ◽  
Luiz Kennedy Cruz Machado
Keyword(s):  
Dairy Farming ◽  
Minas Gerais ◽  
Production Costs ◽  
Family Farm ◽  
Economic Costs ◽  
Family Farmers ◽  
Descriptive Research ◽  
Break Even Point ◽  
Better Than

A gestão dos custos é fundamental para contribuir com o bom gerenciamento da atividade leiteira e pode contribuir para que melhores resultados econômicos para propriedades leiteiras familiares sejam alcançados. Este estudo teve por objetivo analisar os custos de produção de uma propriedade familiar produtora de leite e verificar a contribuição da pecuária leiteira para o desenvolvimento econômico para produtores familiares. Foi realizada uma pesquisa quantitativa e descritiva, configurada como estudo de caso em uma propriedade leiteira situada no sul do Estado de Minas Gerais para analisar questões relacionadas aos custos de produção e resultados econômicos da atividade com dados coletados entre os anos de 2010 e 2017. A produção de leite da propriedade esteve a maior parte dos anos abaixo do ponto de equilíbrio. As receitas da atividade não foram capazes de remunerar o custo operacional total (COT) e o custo total (CT) na maioria dos anos analisados. Contudo, os resultados sugerem que a gestão dos custos da propriedade analisada está se desenvolvendo, pois os resultados econômicos dos últimos anos foram melhores que aqueles obtidos nos primeiros anos da pesquisa. A pecuária leiteira se mostrou como uma importante fonte geradora de riqueza e renda para produtores de leite familiares. Palavras-chave: Custos econômicos. Custos de produção. Custos operacionais.   Management of costs in a family milk property of south of Minas Gerais Abstract Cost management is fundamental to contribute to the good management of dairy farming and can contribute to achieving better economic results for family dairy farms. This study aimed to analyze the production costs of a family farm producing milk and to verify the contribution of dairy farming to the economic development for family farmers. A quantitative and descriptive research was carried out, configured as a case study in a dairy property located in the south of the State of Minas Gerais to analyze issues related to production costs and economic results of the activity with data collected between the years 2010 and 2017. A Most of the years' milk production has been below break-even point. The activity's revenues were not able to remunerate the total operational cost (COT) and the total cost (CT) in most of the years analyzed. However, the results suggest that the management of the costs of the analyzed property is developing, since the economic results of the last years were better than those obtained in the first years of the research. Dairy farming proved to be an important source of wealth and income for family milk producers. Keywords: Economic costs. Production costs. Operational costs.

scholarly journals Studying and Clustering Cities Based on Their Non-Emergency Service Requests

Information ◽  
2021 ◽  
Vol 12 (8) ◽  
pp. 332
Author(s):  
Mahdi Hashemi
Keyword(s):  
Baton Rouge ◽  
Emergency Service ◽  
Las Vegas ◽  
Principal Component ◽  
Washington Dc ◽  
Two Dimensional ◽  
Mobility Devices ◽  
Shared Mobility ◽  
New Perspective ◽  
Low Rate

This study offers a new perspective in analyzing 311 service requests (SRs) across the country by representing cities based on the types of their SRs. This not only uncovers temporal patterns of SRs in each city over the years but also detects cities with the most or least similarity to other cities based on their SR types. The first challenge is to gather 311 SRs for different cities and standardize their types since they differ in various cities. Implementing our analyses on close to 42 million SR records in 20 cities from 2006 to 2019 is the second challenge. Representing clusters of cities and outliers effectively, and providing justifications for them, is the last challenge. Our attempt resulted in 79 standardized SR types. We applied the principal component analysis to depict cities on a two-dimensional canvas based on their standardized SR types. Among our main findings are the following: many cities are observing a fall in requests regarding the condition of roads and sidewalks but a rise in requests concerning transportation and traffic; requests regarding garbage, cleaning, rodents, and complaints have also been rising in some cities; new types of requests have emerged and soared in recent years, such as requests for information and regarding shared mobility devices; requests about parking meters, information, sidewalks, curbs, graffities, and missed garbage pick up have the highest variance in their rates across different cities, i.e., they have a large rate in some cities while a low rate in others; the most consistent outliers, in terms of SR types, are Washington DC, Baltimore, Las Vegas, Philadelphia, Chicago, and Baton Rouge.

scholarly journals Hydrochemical assessment of Semarang area using multivariate statistics: A sample based dataset

2016 ◽  
Author(s):  
Dasapta Erwin Irawan ◽  
Thomas Triadi Putranto
Keyword(s):  
Cluster Analysis ◽  
Statistical Treatment ◽  
Principal Component ◽  
Hierarchical Cluster ◽  
Data Set ◽  
Anal Ysis ◽  
R Packages ◽  
Point Data ◽  
Depth Water ◽  
Water Elevation

Abstract. The following paper describes in brief the data set related to our project "Hydrochemical assessment of Semarang Groundwater Quality". All of 58 samples were taken in 1992, 1993, 2003, 2006, and 2007 using well point data from several reports from Ministry of Energy and Min- eral Resources and independent consultants. We provided 20 parameters in each samples (sample id, coord X, coord Y, well depth, water level, water elevation, TDS, pH, EC, K, Ca, Na, Mg, Cl, SO4, HCO3, year, ion balance, screen location, and chemical facies). The chemical composi- tion were tested in the Water Quality Laboratory, Universitas Diponegoro using mas spectrofotometer method. The statistical treatment for the dataset (available on Zenodo doi:10.5281/zenodo.57293) were described as follows: (1) data preparation in to csv file format, load it in to R environment; (2) data treatment, including: correlation matrix, cluster analysis using kmeans and hierarchical cluster analysis, and principal component analysis. For anal- ysis and visualizations, We used the following R packages: ggplot2, dplyr, factomineR, factoExtra, cluster, ggcorrplot, and ape.

Use of the Principal Component Analysis (PCA) to Reduce Data Complexity in Qualitative Research: An Electro-Electronics Case Study

2014 ◽  
Vol 988 ◽  
pp. 526-529
Author(s):  
Fernanda Perreira Lopes ◽  
Adriana de Paula Lacerda Santos ◽  
Nicolle Christine Sotsek
Keyword(s):  
Qualitative Research ◽  
Principal Component Analysis ◽  
Principal Component ◽  
Component Analysis ◽  
Complex Variables ◽  
Metropolitan Region ◽  
Economic Sustainability ◽  
Production Area ◽  
The City

The objective of this paper was to show that the Principal Component Analysis (PCA) quantitative technique is capable of grouping complex variables in correlation groups from qualitative research. Thus, the study proposes a set of indicators for evaluating the production area in electro-electronic transformation industries in the city of Curitiba and Metropolitan Region, under aspects of environmental, social and economic sustainability. By employing the technique, it was observed that the questions were well formulated and truly measured what was proposed by the researchers. However, the way the variables were grouped needs adjustments to facilitate application of the questionnaire and the tabulation and analysis of data.

scholarly journals Identification of Urban Functional Regions Based on Floating Car Track Data and POI Data

2019 ◽  
Vol 11 (23) ◽  
pp. 6541 ◽  
Author(s):  
Beibei Yu ◽  
Zhonghui Wang ◽  
Haowei Mu ◽  
Li Sun ◽  
Fengning Hu
Keyword(s):  
Clustering Algorithm ◽  
Rapid Development ◽  
Research Unit ◽  
Trajectory Data ◽  
Functional Region ◽  
Functional Regions ◽  
Urban Zone ◽  
Point Data ◽  
New Perspective ◽  
The City

Along with the rapid development of China’s economy as well as the continuing urbanization, the internal spatial and functional structures of cities within this country are also gradually changing and restructuring. The study of functional region identification of a city is of great significance to the city’s functional cognition, spatial planning, economic development, human livability, and so forth. Backed by the emerging urban Big Data, and taking the traffic community as the smallest research unit, a method is proposed to identify urban functional regions by combining floating car track data with point of interest (POI) data recorded on an electronic map. It provides a new perspective for the study of urban functional region identification. Firstly, the main functional regions of the city studied are identified through clustering analysis according to the passenger’s spatial-temporal travel characteristics derived from the floating car data. Secondly, the fine-grained identification of the functional region attributes of the traffic communities is achieved using the label information from POI data. Finally, the AND-OR operation is performed on the recognition results derived by the clustering algorithm and the Delphi method, to obtain the identification of urban functional regions. This approach is verified by applying it to the main urban zone within Chengdu’s Third Ring Road. The results show that: (1) There are fewer single functional regions and more mixed functional regions in the main urban zone of Chengdu, and the distribution of the functional regions are roughly concentric centering in the city center. (2) Using the traffic community as a research unit, combined with dynamic human activity trajectory data and static urban interest point data, complex urban functional regions can be effectively identified.

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