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To evaluate the efficiency of complex esters as plasticizers in polyvinyl chloride plastisols and plasticates.

Several poly(vinyl chloride) plastisols and plasticates were prepared with standard phthalate plasticizers and complex esters and were characterised using standard and laboratory methods.

The use of mixtures of three new CE with standard phthalate plasticizers increased the physical, mechanical and electric characteristics of the resulting PVCPs and PVCPl.

The use of three new CE, obtained by esterification of dicarboxylic acids (adipic, sebacic, pelargonic), poly(ethylene glycol) and i‐octanole, as plasticizers of poly(vinyl chloride) plastisols and plasticates was investigated. The use of CE based on other organic acids could be explored.

The results confirmed the efficiency of plasticization of PVC by CE. Such a finding has significant industrial implication.

Several findings are original and are of importance to relevant industry. The new CE with high molecular weights were effective plasticizers of PVC. The efficiency of the plasticizers depended on their chemical structure. The molecular weight of the CE had no influence on the compatibility of plasticizers and other components of the PVC plastisols and plasticates.

This paper seeks to investigate the influence of chemical structure of ester basestock (trimethylolpropane pelargonate) on the viscosity characteristics of formulations obtained and the operating mechanism of two widely used viscosity index improvers – poly(butadiene‐styrene) and poly(alkyl methacrylate).

Oil formulations of trimethylolpropane pelargonate and poly(butadiene‐styrene)/poly(alkyl methacrylate) as viscosity index improvers are prepared. Their kinematic viscosity at different temperatures is measured. Relative, intrinsic and characteristic viscosities are calculated from the experimental data.

The thickening ability of linear polymers from butadiene‐styrene and alkyl methacrylate in a synthetic oil of ester type (trimethylolpropane pelargonate) is clarified. The conformation of these polymers is studied. Results of comparative tests about the influence of the type of polymer and solvent on characteristic and intrinsic viscosity are presented. It has been established that with the increasing of temperature the quality of used synthetic oil decreased and the characteristic viscosity decreased for both polymers. At lower temperatures the intermolecular interaction between the polymeric macromolecules becomes bigger than their interaction with the molecules of solvent. Molecule associates have been possibly formed at low temperature. These associates increase the viscosity of solutions and this increase is bigger at low temperatures in comparison with high temperatures.

Viscosity index improvement of poly(butadiene‐styrene) and poly(alkyl methacrylate) is determined. The information about concentrations and viscosity is of practical interest.

The combination of these synthetic basestock and viscosity index improvers is a new one. The data obtained may have value for the oil production.

The aim of this study is the synthesis and characterization of motor and hydraulic oils based on complex esters of dicarboxylic acids and polyol esters. The esters have been prepared by polyesterification of adipic or sebacic acids with polyethylene glycol and by subsequent reaction with 2‐ethylhexanol using a new high active catalyst tetraoktyltitanate (TOT)‐TlCl. The synthesis of pentaerythritol esters of monocarboxylic acids has also been undertaken in the presence of the same catalyst. The catalyst reduces the time and temperature required for the reaction to produce esters with characteristics of standard motor and hydraulic oils.

This paper aims to propose the new incremental and parallel training algorithm of proximal support vector machines (Inc-Par-PSVM) tailored on the edge device (i.e. the Jetson Nano) to handle the large-scale ImageNet challenging problem.

The Inc-Par-PSVM trains in the incremental and parallel manner ensemble binary PSVM classifiers used for the One-Versus-All multiclass strategy on the Jetson Nano. The binary PSVM model is the average in bagged binary PSVM models built in undersampling training data block.

The empirical test results on the ImageNet data set show that the Inc-Par-PSVM algorithm with the Jetson Nano (Quad-core ARM A57 @ 1.43 GHz, 128-core NVIDIA Maxwell architecture-based graphics processing unit, 4 GB RAM) is faster and more accurate than the state-of-the-art linear SVM algorithm run on a PC [Intel(R) Core i7-4790 CPU, 3.6 GHz, 4 cores, 32 GB RAM].

The new incremental and parallel PSVM algorithm tailored on the Jetson Nano is able to efficiently handle the large-scale ImageNet challenge with 1.2 million images and 1,000 classes.

This study aims to examine the role of the dimensions of entrepreneurial orientation (EO) under turbulent market conditions and reveal the role of an entrepreneur's perception of a crisis in shaping the impact of EO on firm performance.

This study uses partial least squares structural equation modeling (PLS-SEM), multiple linear regression (MLR) and fuzzy-set qualitative comparative analysis (fsQCA). The study sample was comprised of 117 one- and two-star hotels that were operating in Poland.

The results showed that proactiveness and risk-taking significantly affected firm performance. Furthermore, the results revealed that an entrepreneur's perception of a crisis moderated the impact of risk-taking and proactiveness on firm performance. In particular, the findings suggested that, in firms where the crisis strongly influenced their operations, performance was affected by proactiveness, while in those firms where the crisis influenced their operations to a low or moderate degree, performance was affected by risk-taking. Furthermore, fsQCA unveiled the role of innovativeness, which (along with risk-taking) is a sufficient condition that leads to firm performance.

Two characteristics make this study original: first, it investigates EO under turbulent market conditions, and second, it analyzes the role of an entrepreneur's perception of crisis consequences for business operations. The study contributes to the literature on entrepreneurship and crisis management with findings on the different roles of EO dimensions under crisis conditions and an observation about the moderating role of an entrepreneur's perception of the impact of a crisis on operational management and how this perception differentiates the impact of risk-taking and proactiveness on firm performance.

Detailed results of numerical calculations of transient, 2D incompressible flow around and in the wake of a square prism at Re = 100, 200 and 500 are presented. An implicit finite‐difference operator‐splitting method, a version of the known SIMPLEC‐like method on a staggered grid, is described. Appropriate theoretical results are presented. The method has second‐order accuracy in space, conserving mass, momentum and kinetic energy. A new modification of the multigrid method is employed to solve the elliptic pressure problem. Calculations are performed on a sequence of spatial grids with up to 401 × 321 grid points, at sequentially halved time steps to ensure grid‐independent results. Three types of flow are shown to exist at Re = 500: a steady‐state unstable flow and two which are transient, fully periodic and asymmetric about the centre line but mirror symmetric to each other. Discrete frequency spectra of drag and lift coefficients are presented.

The value‐premium is the empirical observation that “value” stocks (low market/book) have higher returns than “growth” stocks (high market/book). The purpose of this paper is to propose a new explanation for the value‐premium that the authors call the limits to growth hypothesis.

To guide the testing, a dynamic equity valuation model was used that has the property that profitability increases risk for value firms in anticipation of future growth‐leverage, whereas, profitability “covers” the capital expenditure costs of growth, which decreases risk for growth firms. Because the authors interpret dividends as a corporate response to growth‐limits, they test for this predicted differential relation between profitability and risk for value versus growth stocks with the returns of profitable dividend‐paying firms.

It is found that profitability increases returns to a greater extent for dividend‐paying value firms compared to dividend‐paying growth firms, which is consistent with a differential relation between profitability and risk. At the same time, it is also found that growth firms have lower returns than value firms.

The authors use the limits‐to‐growth hypothesis to explain why profitability can either increase or decrease risk. High‐profitability dividend‐paying growth firms have lower returns than low‐profitability dividend‐paying value firms. This value‐premium is consistent with the argument that high profitability “covers” the capital expenditure costs of growth, which decreases risk and, thus, returns. At the same time, profitability increases returns to a greater extent for value stocks compared to growth stocks, which is consistent with the hypothesis that profitability increases risk for value firms in anticipation of future growth‐leverage.

The purpose of this paper is to compare investment in innovation (e.g. R&D) between new venture start‐ups before commercialization and operating businesses after commercialization.

Real options methods were used to model a new venture start‐up as a perpetual call option on an operating business that grows with R&D. The operating business uses R&D to improve actual earnings while the start‐up uses R&D to improve prospective earnings. When the start‐up entrepreneur commercializes his/her new product, device, or service with conventional investment (e.g. plant, property, and equipment to begin production), prospective earnings convert into actual earnings.

The ability of the start‐up entrepreneur to avoid commercialization costs upon failed R&D makes R&D more valuable to the start‐up entrepreneur than to the manager of the already operating business (for whom commercialization costs are sunk) and despite R&D costs that the start‐up incurs without the revenues that only commercialization generates. The value of R&D to the start‐up can be so great that the entrepreneur invests in R&D before the manager of an otherwise similar operating business in similar business conditions.

Without favoring either a priori, the authors show that under broad circumstances, a new venture start‐up undertakes R&D before an already operating business. The authors also discuss the empirical implications of the results.

The purpose of this paper is to investigate the ways in which effectiveness of answers in Yahoo! Answers, one of the largest community question answering sites (CQAs), is related to question types and answerer reputation. Effective answers are defined as those that are detailed, readable, superior in quality and contributed promptly. Five question types that were studied include factoid, list, definition, complex interactive and opinion. Answerer reputation refers to the past track record of answerers in the community.

The data set comprises 1,459 answers posted in Yahoo! Answers in response to 464 questions that were distributed across the five question types. The analysis was done using factorial analysis of variance.

The results indicate that factoid, definition and opinion questions are comparable in attracting high quality as well as readable answers. Although reputed answerers generally fared better in offering detailed and high-quality answers, novices were found to submit more readable responses. Moreover, novices were more prompt in answering factoid, list and definition questions.

By analysing variations in answer effectiveness with a twin focus on question types and answerer reputation, this study explores a strand of CQA research that has hitherto received limited attention. The findings offer insights to users and designers of CQAs.

The purpose of this study is to examine the predictors of high‐quality answers in a community‐driven question answering service (Yahoo! Answers).

The identified predictors were organised into two categories: social and content features. Social features refer to the community aspects of the users and are extracted from explicit user interaction and feedback. Content features refer to the intrinsic and extrinsic content quality of answers that could be used to select the high‐quality answers. In total the framework built in this study comprises 17 features from two categories. Based on a randomly selected dataset of 1,600 question‐answer pairs from Yahoo! Answers, high‐quality answer predictors were identified.

The results of the analysis showed the importance of content appraisal features over social and textual content features. The features identified as strongly associated with high‐quality answers include positive votes, completeness, presentation, reliability and accuracy. Features weakly associated with high‐quality answers were high frequency words, answer length, and best answers answered. Features related to the asker's user history were found not to be associated with high‐quality answers.

This work could help in the reuse of answers for new questions. The study identified features that most influence the selection of high‐quality answers. Hence they could be used to select high‐quality answers for answering similar questions posed by users in the future. When a new question is posed, similar questions are first identified, and the answers for these questions are extracted and routed to the proposed quality framework for identifying high‐quality answers. Based on the overall quality index computed, the high‐quality answer could be returned to the asker.

Previous studies in identifying high‐quality answers were conducted using either of two approaches. First using social and textual content features found in community‐driven question answering services and second using content appraisal features by thorough assessment of answer quality provided by experts. However no study had integrated both approaches. Hence this study addresses this gap by developing an integrated generalisable framework to identify features that influence high‐quality answers.