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This paper aims to compare the performance, emission and combustion characteristics of E20 biodiesel with diesel-water emulsion and eucalyptus water emulsion.

This research expounds the trans-esterification process apparently. Various biodiesel blends were made to go through the trans-esterification process to make it suitable for feeding them into the low heat rejection (LHR) engine. E20 biodiesel – 20% of eucalyptus oil by volume with diesel was chosen to carry out the research as it was found to be the best blend with diesel. The volume of water content in diesel water emulsions was varied by 5, 10 and 15% in DWM1 (Diesel Water Mixture1), DWM2 (Diesel Water Mixture2) and DWM3 (Diesel Water Mixture3), respectively. Similarly, the volume of water content in eucalyptus water emulsions was varied with emulsification ratio of E20 biodiesel. Partially stabilized zirconia was coated over top surface of the piston and valve facing of the LHR engine.

From the researches carried out, DWM3 (Diesel Water Mixture3) was found to be superior when compared with other diesel-water emulsions in LHR engine. The overall efficiency was found to be higher for EWM3 than other biofuels tested the in LHR engine.

This investigational experiment can be further extended to multi-cylinder engine and to improve the cetane number, Di ethyl ester (DEE) fuel additives can be added.

This paper aims to synthesize the history of bio-refinery in Thailand and analyze the public policy challenges hindering the industry’s growth and development since year 2000.

The authors assembled dispersed data on the industry structure, history of investment and the current state of bio-refinery in Thailand from numerous public organizations and media outlets. The chronicle covers the initial launching and subsequent market growth of ethanol, biodiesel and bio-chemicals. The most innovative analysis in this study is the identification of the key players in the bio-refinery value chain. The authors supply insights about each player’s stake, bargaining power, strategies and relative success/failure during the past few decades.

Instead of working together to develop bio-refinery, it appears the Thai petroleum companies, policymakers and automotive companies often delay or block developments that would benefit bio-fuel and bio-chemical producers and crop growers. Conflicts of interests have caused policymakers and regulators to favor already overly protected industries. Seventeen years of bio-fuel policy from 2000 to 2016 has shown that the major objectives of the government’s bio-fuel/bio-refinery policies have failed.

Using Thailand as a case study, this paper illustrates the critical role of politics, special interest groups and lobbying in determining the viability of bio-fuel/bio-refinery industries in developing countries.

Some patients with severe mental disorders are refractory to psychotherapeutic or psychopharmacological interventions. We describe a patient with severe symptoms from the age of 16 to 44. Her illness is best described as a schizo-affective disorder. Several series of electroconvulsive therapy (ECT) followed by maintenance once a week for more than six years has kept her out of hospital beds for three years. The patient demonstrates the feasibility of long term ECT and the absence of disturbing cognitive reductions.

Demonstrates the application of spreadsheets in simulating queuing systems with arrivals from a finite population. The problem is referred to as the machine repair problem where the members of the queue are machines that are breaking down and the servers are the technicians repairing the broken machines. The total number of machines are finite and pre‐specified. The technique for the development of the simulation is illustrated with six machines. Describes the approach for developing a generalized simulation model with any number of machines.

The purpose of this paper is to focus on the processes that occur between entrepreneurs’ primary attribution for failure and the emergent learning dimensions from failure, in the context of regenerative failures.

The study focusses on 21 entrepreneurs operating in the producing services sector, a major subsector of the Irish Information and Communication Technology industry. All the entrepreneurs experienced business failure and subsequently re-entered the entrepreneurial sphere at a later date. A qualitative approach examines their attributions for failure, responses to failure, and learning dimensions from failure.

Regenerative entrepreneurs’ primary attributions for business failure are examined in detail; four types of failure attributions are uncovered – internal individual level; external firm level; external market level; and hybrid attributions. Entrepreneurs’ attributions impact their responses to the failure; this in turn affects entrepreneurial learning. When failure is primarily attributed to internal factors, the entrepreneur’s response is affective, leading to deep, personal learning about oneself. External attributions (both firm level and market level) result in a primarily behavioural response, with learning focussed on the venture, and networks and relationships. Those primarily attributing failure to hybrid factors have a largely cognitive response and they learn about venture management.

This study is a retrospective analysis of business failure.

The study contributes to the growing literature on entrepreneurs’ attributions for business failure by focussing on regenerative failure; it links attributions to – responses to, and learning from, failure. The key contribution to knowledge emerges from the development of a model of the underlying processes affecting learning from failure for regenerative entrepreneurs. The research also establishes and identifies clear links between attributions, responses, and lessons learned in the context of regenerative failure.

To examine a simple testing method of measuring the force to pull a fabric through a series of parallel pins to determine the fabric softness property.

A testing system was setup for fabric pulling force measurements and the testing parameters were experimentally determined. The specific pulling forces were compared with the fabric assurance by simple testing (FAST) parameters and subjective softness ranking. Their correlations were also statistically analyzed.

The fabric pulling force reflects the physical and surface properties of the fabrics measured by the FAST instrument and its ability to rank fabric softness appears to be close to the human hand response on fabric softness. The pulling force method can also distinguish the difference of fabrics knitted with different wool fiber contents.

Only 21 woven and three knitted fabrics were used for this investigation. More fabrics with different structures and finishes may be evaluated before the testing method can be put in practice.

The testing method could be used for objective assessment of fabric softness.

The testing method reported in this paper is a new concept in fabric softness measurement. It can provide objective specifications for fabric softness, thus should be valuable to fabric community.

In this paper we give a synoptic view of the growth of the text processing technology of information extraction (IE) whose function is to extract information about a pre‐specified set of entities, relations or events from natural language texts and to record this information in structured representations called templates. Here we describe the nature of the IE task, review the history of the area from its origins in AI work in the 1960s and 70s till the present, discuss the techniques being used to carry out the task, describe application areas where IE systems are or are about to be at work, and conclude with a discussion of the challenges facing the area. What emerges is a picture of an exciting new text processing technology with a host of new applications, both on its own and in conjunction with other technologies, such as information retrieval, machine translation and data mining.

This paper intends to explore and appraise the humanitarian supply chain management enablers (HSCMEs) for efficient and effective humanitarian operations. This research aims to analyze the interaction of enablers for humanitarian supply chain management (HSCM) using a proposed hybrid framework consists of fuzzy Delphi (FD), interpretive structural modeling (ISM)–matriced impacts croises multiplication appliquee a un classement (MICMAC) and revised Simos approach.

This research is deliberate to identify 28 HSCMEs through a literature review and experts' opinions; out of which 20 HSCMEs are selected using FD. ISM is applied to know contextual relationship among the selected HSCMEs for developing a hierarchical model. The MICMAC analysis classifies the HSCMEs based on driving power and dependence power to validate the developed hierarchical ISM structure. The revised Simos technique is used to prioritize the HSCMEs to access its relative significance in humanitarian operations.

The finding of the analysis suggests that government policy and leadership support obtained the highest priority, having high driving power and low dependence power is significantly strategic and emerged as the leading driver for the HSCM implementation.

ISM model presents an insight into interrelationship among HSCMEs, but this cannot quantify the impact of each HSCMEs.

Disaster relief aid agencies and stakeholders may focus on the enablers having high driving power and higher weight in designing and executing an effective and efficient humanitarian supply chain and to improve their activities and strategies of HSCM.

This research helps humanitarian logisticians and humanitarian organizations to make better decisions to improve their operational performance in pre and postdisaster phases.

This paper explores the application of proposed hybrid framework to analyze the HSCMEs that can be considered as the original contribution.

Since Hayek’s pioneering work in the 1930s, the Austrian business cycle theory (ABCT) has been presented as a disequilibrium theory populated by less-than-perfectly rational agents. In contrast, we maintain that (1) the Austrian business cycle theory is consistent with rational expectations and (2) the post-boom adjustment process can be understood in an equilibrium framework. Hence, we offer a new interpretation of the existing theory. In doing so, we also address concerns raised with Garrison’s (2001) diagrammatic approach, wherein the economy moves beyond the production possibilities frontier. Our interpretation might accurately be described as a monetary disequilibrium approach grounded in an implicit general equilibrium framework with positive costs of reallocation.

Lester and Wolff (2013) find little empirical support for the Austrian business cycle theory. According to their analysis, an unexpected monetary shock does not alter the structure of production in a way consistent with the Austrian view. Rather than increasing production in early and late stages relative to middle stages, they find the opposite – a positive monetary shock typically decreases production in early and late stages relative to middle stages. We argue that the measures of production and prices employed by Lester and Wolff (2013) are constructed in such a way that makes them inappropriate for assessing the empirical relevance of the Austrian business cycle theory’s unique features. After describing how these measures are constructed and why using ratios of stages is problematic, we use a structural vector autoregression to consider the effects of a monetary shock on each stage of the production process. We show that, with a clearer understanding of what is actually being measured by the stage of process data, the results are consistent with (but not exclusive to) the Austrian view.