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The purpose of this paper is to identify and analyse the fermentative properties of a strain of indigenous Wickerhamomyces anomalus (W. anomalus) from Rosa roxburghii Tratt (R. roxburghii).

Morphological and molecular methods were used to determine the species of the selected strain W. anomalus C11. The physiological tolerances to glucose, ethanol, citric acid and sulphur dioxide (SO₂) were further assessed by checking the growth of cells, and the oenological performances were proved to measure the related fermentative properties of R. roxburghii wines.

The W. anomalus C11 strain could be grown faster than commercial S. cerevisiae X16 in its logarithmic growth period and had preferable tolerances to glucose, ethanol, citric acid and SO₂. Moreover, this strain of native R. roxburghii yeast W. anomalus C11 produced less sulphuretted hydrogen and had a higher β-glucosidase activity. Furthermore, W. anomalus C11 could reduce the volatile acids, reduce the sourness and enhance volatile aroma richness and complexity of R. roxburghii wines including types of aroma and content thereof. Taken together, the R. roxburghii native yeast W. anomalus C11 may have potential for use in R. roxburghii winemaking.

(1) The fermentative properties of a strain of indigenous W. anomalus (named as C11) from R. roxburghii was evaluated. (2) The strain of W. anomalus C11 had preferable tolerances to glucose, ethanol, citric acid and SO₂. (3) This strain of native R. roxburghii yeast W. anomalus C11 produced less sulphuretted hydrogen and had a higher ß-glucosidase activity. (4) W. anomalus C11 could reduce the volatile acids, reduce the sourness and enhance volatile aroma richness and complexity of R. roxburghii wines including types of aroma and content thereof.

The purpose of this paper is to develop and apply accurate and original models to understand and analyze the effects of the fabrication temperatures on thermal-induced stress and speed performance of nano positively doped metal oxide semiconductor (pMOS) transistors.

The speed performances of nano pMOS transistors depend strongly on the mobility of holes, which itself depends on the thermal-induced extrinsic stress σ. The author uses a finite volume method to solve the proposed system of partial differential equations needed to calculate the thermal-induced stress σ accurately.

The thermal extrinsic stress σ depends strongly on the thermal intrinsic stress σ₀, thermal intrinsic strain ε₀, elastic constants C11 and C12 and the fabrication temperatures. In literature, the effects of fabrication temperatures on C11 and C12 needed to calculate thermal-induced stress σ₀ have been ignored. The new finding is that if the effects of fabrication temperatures on C11 and C12 are ignored, then, the values of stress σ₀ and σ will be overestimated and, then, not accurate. Another important finding is that the speed performance of nano pMOS transistors will increase if the fabrication temperature of silicon-germanium films used as stressors is increased.

To predict correctly the thermal-induced stress and speed performance of nano pMOS transistors, the effects of fabrication temperatures on the elastic constants required to calculate the thermal-induced intrinsic stress σ₀ should be taken into account.

There are three levels of originalities. The author considers the effects of the fabrication temperatures on extrinsic stress σ, intrinsic stress σ₀ and elastic constants C11 and C12.

The fundamental idea that we seek to establish in this chapter is that the establishment of regional or local, peace calls forth global peace. In other words, our argument is that local and regional conflicts are partly driven by global factors, especially what is commonly known as international tension. In order to achieve meaningful and sustained peace, there is a reason to believe that it is mandatory to manage and contain international tensions. The main thesis of this chapter is to explain or posit, conflicts as a product of continuing international chasms, splits and differences of political and social ideologies in our modern world. Thus, we argue that conflicts are, to some extent, driven by international tension or global, ideological and geo-political factors. Notwithstanding the global influence, local factors – such as income inequality, income growth or lack of it, political institutions – can and do exacerbate conflicts and a peaceful resolution of conflicts becomes a difficult phenomenon.

The main objective of this paper is to justify the implementation of blockchain (BC) over the traditional method deployed in the supply chain (SC) after using the fuzzy–analytic network process (fuzzy-ANP) application. Over the past two decades, the overall product cost is affected by the SC at a global level. Organizations are working on their existing SC for improving their performance. BC technology is a newly emerging technology and magnetizes the attention of researchers and industrialists. This technology is still at the initial stage, and only little investigation is available in the literature and it has not been much investigated by researchers.

Literature and expert opinion interpretation in BC characteristics are further analyzed and modeled using fuzzy–interpretive structural modeling (fuzzy-ISM), fuzzy-MICMAC and fuzzy-ANP. The combined approach of both fuzzy-ISM and fuzzy-MICMAC is applied to identify the common drivers to integrate the BC technology in the light of efficient supply chain management (SCM).

Comparative analysis between traditional and BC-based supply chain (BCSC) using fuzzy-ANP is carried out, considering the common driving characteristics. The proposed integrated (combined) approach of fuzzy-ISM, fuzzy-MICMAC and Fuzzy-ANP found that integration of BC with SCM is better prioritized than traditional supply chain management (TSCM). The findings in the article endorse that the TSCM can be made efficient by integrating the BC technology considering five most driving characteristics, namely, data safety and decentralization, accessibility, documentation, data management and quality.

The current proposed research work identifies 12 characteristics after studying numerous literature reviews and having a discussion with SC experts with knowledge of BC. The integrated approach of fuzzy-ISM and fuzzy-MICMAC is implemented here. After that, fuzzy-ANP is used to give ranking among BCSCM and TSCM. The study carried out in this article motivates industries to implement BC in their SC system. It will reduce the transaction cost, documentation work, save time and eliminate human error at the national and international levels. The common characteristics identified in this proposed work would help in managerial decisions for the adoption of BC to ensure that the system becomes more transparent, easily traceable and finally improve the performance.

The purpose of this paper is to study the level of importance existing among the indicators that were previously defined for a Performance Measurement Systems (PMS) and are relative to franchises in Brazil, using the Analytic Hierarchy Process (AHP) methodology, together with a series of tests, which are responsible by verifying the degree of reliability, robustness and stability of the parameters used and the results obtained. As a result, the author suggests that the diagnosing of the five delimited indicators have different relevance assigned to them.

This paper reviews extant literatures in Franchise, PMS, Multiple Criteria Decision Making (MCDM), in specific the theory about AHP.

The authors found that it was possible justified, for both the relative and the evaluative method, that the I3 was the main point of the system and, as a consequence, be considered as priority when talking about sectorial development of franchises in Brazil. As for the other indicators, even being located in a level lower than I3, they must be taken into contemplation in these measurements, however, with a relatively inferior importance degree.

It was possible to better comprehend which economics and non-economic factors selected have a more predominance in the Brazilian franchise context, according to characteristics of the companies present.

The absence of scientific papers that describe the relevance level of the main factors that influence in the Brazilian franchise system.

The aim of this study is to analyze the differences between non-standard forms of employment (FoE) (i.e. dependent self-employment/business-to-business/B2B contract and contract of mandate) in terms of investing in the development of future competencies by employees and employers. This study also examined additional factors which influence these investments.

To collect data, the computer-assisted telephone interview technique was used. 200 employees from different companies located in Poland participated in this study, wherein each of the above-mentioned FoEs (i.e. dependent self-employment and contract of mandate) was represented by 100 people. The Chi-Square test and multivariate logistic regression analysis were used in the statistical analyses.

In the case of only 2 out of 14 competencies, there were statistically significant differences between the two groups of respondents: the employers financed training courses for B2B employees more frequently than for mandate contract workers. Moreover, in only one case there was a statistically significant difference: the self-employed financed training courses themselves more often than mandate contract workers. This study revealed an important impact of other variables such as respondents’ age, education level, parental status and industry on the training activities undertaken by employers and employees.

Although the issue of developing future competencies is important, there is little research examining this problem in the context of people who work in non-standard FoE. Moreover, previous research primarily focused on identifying differences between people working under employment contracts and the self-employed. This article fills these research gaps as well as shows that more factors should be considered in the research models to get a deeper insight into the problem of non-standard FoEs.

Consequence prediction is an emerging topic in safety management concerning the severity outcome of accidents. In practical applications, it is usually implemented through supervised learning methods; however, the evaluation of classification results remains a challenge. The previous studies mostly adopted simplex evaluation based on empirical and quantitative assessment strategies. This paper aims to shed new light on the comprehensive evaluation and comparison of diverse classification methods through visualization, clustering and ranking techniques.

An empirical study is conducted using 9 state-of-the-art classification methods on a real-world data set of 653 construction accidents in China for predicting the consequence with respect to 39 carefully featured factors and accident type. The proposed comprehensive evaluation enriches the interpretation of classification results from different perspectives. Furthermore, the critical factors leading to severe construction accidents are identified by analyzing the coefficients of a logistic regression model.

This paper identifies the critical factors that significantly influence the consequence of construction accidents, which include accident type (particularly collapse), improper accident reporting and handling (E21), inadequate supervision engineers (O41), no special safety department (O11), delayed or low-quality drawings (T11), unqualified contractor (C21), schedule pressure (C11), multi-level subcontracting (C22), lacking safety examination (S22), improper operation of mechanical equipment (R11) and improper construction procedure arrangement (T21). The prediction models and findings of critical factors help make safety intervention measures in a targeted way and enhance the experience of safety professionals in the construction industry.

The empirical study using some well-known classification methods for forecasting the consequences of construction accidents provides some evidence for the comprehensive evaluation of multiple classifiers. These techniques can be used jointly with other evaluation approaches for a comprehensive understanding of the classification algorithms. Despite the limitation of specific methods used in the study, the presented methodology can be configured with other classification methods and performance metrics and even applied to other decision-making problems such as clustering.

This study sheds new light on the comprehensive comparison and evaluation of classification results through visualization, clustering and ranking techniques using an empirical study of consequence prediction of construction accidents. The relevance of construction accident type is discussed with the severity of accidents. The critical factors influencing the accident consequence are identified for the sake of taking prevention measures for risk reduction. The proposed method can be applied to other decision-making tasks where the evaluation is involved as an important component.

The construction industry accounts for a large proportion of the economy of developing countries, but the connotation and influencing factors of high-quality development (HQD) are still unclear. This study aims to gain a more comprehensive insight into the current development status of the regional construction industry under China's HQD orientation and the obstructive factors affecting its development and to provide informative suggestions for its HQD prospects.

In this study, the construction industry of 16 cities in the Chengdu-Chongqing economic circle (CCEC), a new region in southwest China, was used as the research object to collect data from the 2006–2019 yearbooks, construct an evaluation index system for HQD of the construction industry, derive the development level of the construction industry using the entropy value method and spatial autocorrelation method and then apply the barrier Diagnostic model was used to compare and analyze the impact level of each index.

In terms of the time dimension, the development of the construction industry in CCEC is characterized by “high in the twin core and low in the surrounding area”, with unbalanced and insufficient development; in terms of spatial correlation, some factors have positive aggregation in spatial distribution, but the peripheral linkage decreases; through barrier analysis, the impact of different barrier factors is different.

This paper will help governments and enterprises in developing countries to make urban planning and management policies to fundamentally improve the development of the construction industry in underdeveloped regions.

Increasingly, dynamic market environments lead to growing complexity in manufacturing and pose a severe threat for the competitiveness of manufacturing companies. Systematic guidance to manage this complexity, especially in the context of Industry 4.0 and the therewith rising trends such as digitalization and data-driven production optimization, is lacking. To address this deficit a case-based reasoning (CBR) system for providing knowledge about managing complexity in Industry 4.0 is presented.

First, the explicit knowledge representation for managing complexity in IT-based manufacturing is introduced. Second, the CBR process step to retrieve knowledge from an artificially composed case base with in total 70 cases of data-based complexity management in the context of Industry 4.0 is set out. Third, knowledge transfer alongside several maturity levels of information technology capabilities of manufacturing systems for reuse in new problem scenarios is introduced.

The paper comprises the conceptual approach for designing a CBR system to support data-based complexity management in manufacturing systems. Furthermore, the appropriateness of the CBR system to provide applicable knowledge for reducing and managing complexity in corporate practice is shown.

The presented research results are evaluated in the course of an embedded single case study and may therefore lack generalizability. Future research to test and enhance the appropriateness of the developed CBR system will strengthen the research contribution.

The paper provides a novel approach to systematically support knowledge transfer for data-based complexity management by transferring the well-known and established methodology of CBR to the rising application domain of manufacturing systems in the context of Industry 4.0.

The purpose of this paper is threefold: first, to present a structural competency model; second, to remark new criteria for personnel selection in Industry 4.0 environment; and third, to contribute to the operations management literature by focusing on recruitment process in Industry 4.0 environment and supporting human resources activities with Industry 4.0 related criteria and point out a new research field in Industry 4.0.

Fuzzy DEMATEL has been used in the implementation. The study is conducted in a high-tech firm, which has started to modify its processes according to Industry 4.0, and introduces a new specific department that is responsible of this transformation. In total, 11 personnel selection criteria were presented and then assessed by experts through a fuzzy linguistic scale. Both importance order and causal relation between criteria are presented at the end of the study.

According to the results, the most important criteria in the selected firm are the ability of dealing with complexity and problem solving, thinking in overlapping process, and flexibility to adapt new roles and work environments. While cause group includes criteria such as knowledge on IT and production technologies, awareness of IT security and data protection, and ability of fault and error recovery, effect group includes flexibility to adapt new roles and work environments, organizational and processual understanding, and the ability to interact with modern interfaces.

Analytical thinking and system approach are the key topics for new supporting personnel selection criteria, which lead to the need for the skills and qualifications in decision making and process management. Results of the cause group criteria also indicate the importance of technical abilities such as coding, IT security and human-machine interfaces. On the other hand, effect group of the study emphasizes on the flexibility and interdisciplinary working structure that suggests the suitability of matrix organization in the companies which follow the Industry 4.0 trends. Moreover, team work comes forward as another key concept for organizations transforming to Industry 4.0.

The originality of this study appears on modeling of a competency structural model for Workforce 4.0 which is proposed as a road map, including the suggested set of related criteria and the fuzzy MCDM-based methodology for companies which alter their organizations according to Industry 4.0.