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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 transportation sector is frequently criticized for its adverse environmental impacts. Industrial managers and decision-makers in the transportation sector have difficulty embracing sustainable transportation. Taking this difficulty into consideration, this study intends to locate and evaluate the enablers of sustainable transportation.

Using the Pareto analysis, the study finalized 20 enablers from the list of 25 enablers. The finalized enablers are prioritized, and their causal inter-relationships are revealed using the grey-decision-making trial and evaluation laboratory (grey-DEMATEL) method. A sensitivity analysis is performed to determine the influence of experts' weight in the final results.

Findings reveal enhancement of cross-departmental cooperation, decision synchronization, technology cooperation, policy cooperation and route optimization as the five most critical enablers of sustainable transportation. Based on the results, the study proposes some policy implications for the decision-makers to proactively incorporate sustainability concepts.

This paper is the first of its kind to evaluate the enablers of sustainable transportation in the Indian leather industry. This paper proposes a comprehensive list of enablers of sustainable transportation and reveals their causal interrelationships using grey-DEMATEL. The weight of the provided enablers will help the industrial managers to more proactively take sequential actions to incorporate sustainable transportation.

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.

The purpose of this study is to understand the specific reasons why developed countries could easily start implementing innovative alternative fuel vehicles (e.g. electric vehicles or EVs) while the implementation in developing countries looks so far-fetched, with respect to infrastructure and downstream activities, and suggest the steps that can be taken to effectively address these issues.

This research undertakes case study – Tesla (USA), Mahindra and Mahindra (India) and Tata Motors to bring out the problems being faced by manufacturers from developing countries vis-a-vis the developed countries. The consumers’ side has been adequately represented though an in-depth survey. An analysis is also carried out as to how Tesla has accrued competitive leverage by innovating and vertical integration of up as well as downstream systems.

EV infrastructure remains grossly inadequate in developing countries like India. Two key areas that remain significantly unexplored are the installation of charging stations at parking lots and at the housing clusters and lack of competitive leverage in the services, processes and other downstream systems due to limited research and development capabilities. The performance metrics of domestic EVs lag those of conventional vehicles as well as foreign competitors like Tesla. Range anxiety is ranked as number one in the major concerns among the potential mass buyers of electric vehicles in India.

The value of the paper lies in an in-depth analysis of the relationship between horizontal and vertical perspectives as well as the impact of the product eco-system innovation on both the upstream as well as downstream nodes in the supply chain. Whereas the consumer attitudes and perspectives on e-mobility are inferred from a survey, the impact analysis matrix is used for analyzing the competitive leverage of Tesla through several features in the upstream, downstream and servitization.

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.