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The mathematical model and computer algorithm reported in a previous issue of this journal have been tested on 21 normal heart moulds by comparing the true volume value, measured by Archimedes' principle, with the predicted theoretical volume.

Proposes a modified Hill model for the oxyhaemoglobin dissociation curve. The model fits normal oxyhaemoglobin dissociation experimental data quite accurately, and can easily be adapted to experimental data of subjects suffering haemoglobinopathies when available. Discusses the Adair equation, as well as correcting factors for varying temperature and pH.

Selective laser sintering (SLS) is a solid freeform fabrication process whereby a part is built layerwise by scanning a powder bed. The processability of metal powder varies depending on the state of the powder prior to SLS. A powder thermal pre‐treatment was developed which involved degassing the powder at an elevated temperature in a vacuum. Without powder thermal pre‐treatment, the powder may flow poorly and may “ball” or form molten clumps during the laser exposure rather than wetting into the present and previous layer. These effects result in SLS parts with poor surface finish, mechanical properties and density. The purpose of this study was to identify for titanium alloy powder the mechanisms responsible for the improvements obtained after powder thermal pre‐treatment and to optimize the thermal excursion.

The area of artificial neural networks, which dates back to the early twentieth century, could only offer positive contributions to technology after the back‐propagation algorithm was proposed in 1986. In this note an alternative algorithm to the gradient descent used in back‐propagation is proposed. This algorithm is based on the discrete central difference. This procedure, as opposed to the back‐propagation algorithm, offers the possibility of true parallel computation.

This paper aims to investigate the changes in living standard among families with different socio-economic status in China with the use of Engel's Coefficient. The authors develop a decomposition methodology to figure out the driving forces behind changes in Engel's Coefficient, and investigate how dramatic economic growth, volatile food price and rapid nutrition transition affect living standard among different families.

The authors propose a statistical method to decompose the changes in living standard measured by Engel's Coefficient into structure effect, price effect, quantity effect and income effect. Using the China Health and Nutrition Survey data between 2000 and 2011, the authors estimate these four effects by employing a decomposition method.

Results show that Engel's Coefficient in China decreased by 8.7 percentage points (hereafter “pp”) during 2000–2011, where structure effect leads to 0.2 pp increase, price effect results in 17.7 pp increase, quantity effect brings about 12.4 pp decline and income effect contributes to 14.2 pp decline. Results indicate that rising food prices are the main obstacle to improve households' living standard. Typically, poor and rural families' living standard is more vulnerable to the rise in food prices, and they benefit less from income growth.

This study proposes a decomposition method to investigate the determinants of change in Engel's Coefficient, which provides a deeper understanding of how economic growth, food price change and nutrition transition affect people's living standard in different socio-economic groups in developing countries. This study also provides valuable insights on how to achieve common prosperity from the perspective of consumption upgrading.

Over the past decade, policy researchers and advocates have called for the decentralization of teacher hiring decisions from district offices to school principals. The purpose of this paper is to document the trends across two and a half decades in principals’ reported influence over teacher hiring decisions in the USA and explore how and whether principal influence varies systematically across contexts.

Regression analysis with secondary data using seven waves of nationally representative data from the Schools and Staffing Survey.

Principals report increased influence over the 25 years that the data span. While principals of urban schools were much more likely to report having less influence over teacher hiring compared to their non-urban counterparts in the late 1980s and early 1990s, their reported influence increased more than that of other principals.

Empowering principals as primary decision-makers assumes that they have the best information on which to make hiring decisions. At the same time, other research suggests that local teacher labor market dynamics contribute to the inequitable sorting of teachers across schools. This study raises questions regarding the implications of the increased influence of principals in teacher hiring on equity of access to quality teachers across schools.

This is the first study to explore whether and how principal influence in teacher hiring decisions has changed over time.

Economic theories on structural change focus on factors such as fluctuations in relative prices and income growth. In addition, China’s reform and opening up has also been accompanied by increasing openness, significant fluctuations in investment rates, and frictions in the labor market. Existing literature lacks a unified theoretical framework to assess the relative importance of all these determinants. The paper aims to discuss these issues.

To incorporate all of the potential determinants of China’s structural change, the authors build a two-country four-sector neoclassical growth model that embeds the multi-sector Eaton and Kortum (2002) model of international trade, complete input-output structure, non-homothetic preference and labor market frictions. The authors decompose the sectoral employment shares into six effects: the Baumol, Engel, investment, international trade, factor intensity and labor market friction effects. Using the data of Chinese economy from 1978 to 2011, the authors perform a quantitative investigation of the six determinants’ effects through the decomposition approach and counterfactual exercises.

Low-income elasticity of demand, high labor intensity, and the existence of the switching costs are the reasons for the high employment share in the agricultural sector. Technological progress, investment and international trade have comparatively less influence on the proportion difference of employment in the three sectors.

Therefore, to examine the impact on China’s structural change, in addition to Baumol effect and the Engel effect, it is also necessary to consider the impact of three more factors: international trade, investment and switching costs. Therefore, the authors decompose the factors that may influence China’s structural change into the Baumol, Engel, investment, international trade, factor intensity effect and switching cost effects. The authors evaluate these six effects using the decomposition approach and counterfactual exercises.

This study aims to evaluate the knowledge and attitudes of dairy farmers about climate change in dairy farms in the Eastern Cape province of South Africa.

The study was conducted following a cross-sectional research design (Bryman, 2012). The study was conducted mainly on dairy farms located on the south-eastern part of the Eastern Cape province in five districts out of the province’s six districts (Figure 1). These districts include Amathole, Chris Hani, OR Tambo and Cacadu; these regions were not included in a recent surveying study (Galloway et al., 2018).

In all, 71.7% of dairy farm workers heard about climate change from the television, and 60.4% of participants reported that they gathered information from radio. Eighty-two out of 106 (77.4%) correctly indicated that climate change is a significant long-term change in expected weather patterns over time, and almost 10% of the study participants had no clue about climate change. Approximately 63% of the respondents incorrectly referred to climate change as a mere hotness or coldness of the day, whereas the remainder of participants correctly refuted that definition of climate change. Most of the study participants correctly mentioned that climate change has an influence on dairy production (92.5%), it limits the dairy cows’ productivity (69.8%) and that dry matter intake of dairy cows is reduced under higher temperatures (75.5%).

The use of questionnaire to gather data limits the study, as respondents relied on recall information. Also, the sample size and study area limits use of the study as an inference for the excluded parts of the Eastern Cape Province. Also, it focused only on dairy farm workers and did not request information from beef farmers.

This study imply that farmers without adequate knowledge of the impact of climate change keep complaining of a poor yield/ animal productivity and changing pattern of livestock diseases. Hence, a study such as the present one helps to bridge that gap and provide relevant governing authority the needed evidence for policy changes and intervention.

Farmers will begin to get help from the government regarding climate change.

This a first study in South Africa seeking to document the knowledge of dairy farm workers about climate change and its impacts on productivity.

The purpose of the paper is to present a scenario‐based approach to river basin planning, and demonstrate how land‐use planning can be utilised as a strong measure in meeting the climate change challenges with new precipitation patterns during the current century.

The current research takes a scenario‐based approach to river basin planning. A modelling framework is defined to assess the effects of active spatial planning to mitigate the negative consequences of climate change in river basin management. In total, three models are included in the framework: a land‐use model, a runoff model, and a flooding screening model.

The research has demonstrated the advantages of using models and scenarios to assess the effects of climate change in river basin management, and how active spatial planning – in the current example afforestation – can mitigate negative consequences of climate change.

The current research demonstrates how to combine models from different fields into one integrated model for impact assessment.

The developed methodology will assist river basin managers to assess the effects of river basin management plans.

The consequences of climate change are mainstream topics discussed by most citizens and results from the models can facilitate a qualified debate.

The paper analyses the feasibility of using active spatial planning to mitigate the negative consequences of climate change, such as flooding along rivers. This work is original, as no such analysis has been carried out before.