Cat Housing: A Case for Inclusive Cohabitation

This major research project (MRP), focused on inclusive industrial design, is a continuation of the "Fumao Jihua" (福猫计划) or the “Cat's Paradise” Project for rescuing stray cats that I was engaged in between 2011 and 2013 in Xi'an, China. The project involved creation of modularized furniture for cats that could be used both at home and in rescue facilities. Primary research conducted in that project informs my MRP. Inspired by the Inclusive Design program, I expanded the idea and the function of the furniture to creating modularized, environment-friendly furniture that provides an inclusive space and environment for both humans and animals to cohabit in crowded city locations. To maximize the design, I created two versions, for use both indoors and outdoors. My designs could also be useful to children with autism, because close habitation with pets is reported to be therapeutic. Future work includes conducting social experiments on the use of the furniture in public places. Keywords: inclusive design, industrial design, animal rescue, cat, furniture, autism therapy, pet therapy

Spillover effects of TTIP on BRICS economies : a dynamic GVC-based CGE model

This paper uses a GVC (Global Value Chain)-based CGE model to assess the impact of TTIP between the U.S. and the EU on their main trading partners who are mainly engaged at the low end in the division system of global value chains, such as BRICS countries. The simulation results indicate that in general the TTIP would positively impact global trade and economies due to the reduction of both tariff and non-tariff barriers. With great increases in the US–EU bilateral trade, significant economic gains for the U.S. and the EU can be expected. For most BRICS countries, the aggregate exports and GDP suffer small negative impacts from the TTIP, except Brazil, but the inter-country trade within BRICS economies increases due to the substitution effect between the US–EU trade and the imports from BRICS countries when the TTIP commences

A Reduced Chemical Kinetic Mechanism for Toluene Reference Fuels Based On DRGEP and QSSA Methods

As a gasoline surrogate fuel, the physical and chemical properties of toluene reference fuel (TRF) are relatively simple and stable, and the TRF chemical kinetic mechanism may be used in simulating combustion processes of gasoline. However, simulations using detailed or semi-detailed mechanisms have been limited due to the computational complexity and long computational time. For the construction of the reduced mechanism, the directed relation graph with error propagation (DRGEP) method is used to wipe out insignificant components efficiently, followed by the use of the quasi-steady state assumption (QSSA) method to separate quasi-steady-state (QSS) species from the kinetic ODEs. In addition, some elementary reactions involving the formation and destruction of H and phenyl methyl radicals are subjected to sensitivity analysis and some kinetic parameters of the relevant elementary reactions are revised. As a result, a reduced mechanism involving 234 reactions and 60 species is developed. Comparing the experimental records with the analog data by utilizing the reduced mechanism, good agreement can be obtained when ignition delay time (τ), laminar flame speed (SL) and molar fraction of vital species are measured. Moreover, the mechanism may predict SL more accurately under lean mixture (equivalence ratio φ < 1.0) conditions. The reduced mechanism is small and reliable in performance, which can commendably reproduce the combustion characteristics of gasoline surrogate

Optimization ACE inhibition activity in hypertension based on random vector functional link and sine-cosine algorithm

Bioactive peptides from protein hydrolysates with antihypertensive properties have a great effect in health, which warrants their pharmaceutical use. Nevertheless, the process of their production may affect their efficacy. In this study, we investigate the inhibitory activities of various hydrolysates on angiotensin-converting enzyme (ACE) in relation to the chemical diversity of corresponding bioactive peptides. This depends on the enzyme specificity and process conditions used for the production of hydrolysates. In order to mitigate the uncontrolled chemical alteration in bioactive peptides, we propose a computational approach using the random vector functional link (RVFL) network based on the sine-cosine algorithm (SCA) to find optimal processing parameters, and to predict the ACE inhibition activity. The SCA is used to determine the optimal configuration of RVFL, improving the prediction performance. The experimental results show that the performance measures of the proposed model are better than the state-of-the-art methods