Hsing-I. Hsiang, Chih-Cheng Chen, Liang-Fang Fan and Hao-Yin Cheng
The interaction between the silver powder and organic vehicle largely determines the rheological behavior of silver conductive paste. This study aims to prepare silver conductive…
Abstract
Purpose
The interaction between the silver powder and organic vehicle largely determines the rheological behavior of silver conductive paste. This study aims to prepare silver conductive paste with an organic vehicle system consisting of ethyl cellulose (EC) and terpineol/butyl carbitol acetate solvent mixtures. The study also aims to measure the rheological behaviors of the silver conductive pastes with different solvent mixtures, EC molecular weights and silver content, to investigate the interaction among the polymer, solvent and silver powder and determine the main factors affecting the thixotropic index and maximum silver content.
Design/methodology/approach
The rheological behaviors of silver conductive pastes with different solvent mixtures, EC molecular weights and silver content were investigated using viscometer.
Findings
The shear thinning became significant with increasing EC molecular weight. The EC solvation with higher molecular weight in solvent is better than that of EC with lower molecular weight. This leads to a stronger interaction between the silver powder and EC with higher molecular weight and consequently good silver particle dispersion. The relative viscosity of silver conductive paste at 10 s−1 increases significantly with increasing silver content, but the relative viscosity at 100 s−1 is much less sensitive to the silver content. The viscosities at low and high shear rate can be increased by increasing the silver content and EC molecular weight, respectively.
Originality/value
The interaction among the polymer, solvent and silver powder was investigated for the silver paste with high solid content. The main factors affecting the viscosities at high and low shear rates, thixotropic index and maximum silver content were determined.
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Longzhen Ni, Liang Fang and Wenhui Chen
The aim of this study is to depict the spatial pattern of the development level of China's state-owned forest farms, thereby providing theoretical reference and empirical evidence…
Abstract
Purpose
The aim of this study is to depict the spatial pattern of the development level of China's state-owned forest farms, thereby providing theoretical reference and empirical evidence for the improvement of the corresponding development policies.
Design/methodology/approach
A development evaluation index system was established in this paper to comprehensively measure the development level of China's state-owned forest farms based on the Pressure-State-Response (PSR) model analysis framework and the actual situation of state-owned forest farms by using the entropy weight - technique for order preference by similarity to an ideal solution (entropy weight TOPSIS) evaluation method and exploratory spatial analysis method.
Findings
Studies show that the state-owned forest farms in China are generally not well developed. The pressure system that represents the input level displays an apparent restrictive effect on provinces whose comprehensive score <0.15. The response system, which represents development dynamism, has an apparent restrictive function on the provinces whose comprehensive score is 0.35. In terms of the specific spatial characteristics, the V-shape displayed by southwest–northwest and southeast–northwest has an inward trend of gradual reduction, with high-low agglomeration and low-low agglomeration correlation effects as well as apparent basin characteristics.
Originality/value
In this paper, the development level and spatial pattern of state-owned forest farms in China were accurately depicted, and the development path support and decision-making basis were provided for improving the overall development level of state-owned forest farms in China.
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Joanna Golden, Mark Kohlbeck and Zabihollah Rezaee
Purpose – The purpose of this study is to investigate whether a firm’s cost structure (specifically, its cost stickiness) is associated with environmental, social, and governance…
Abstract
Purpose – The purpose of this study is to investigate whether a firm’s cost structure (specifically, its cost stickiness) is associated with environmental, social, and governance (ESG) sustainability factors of performance and disclosure.
Methodology/approach – This study uses MCSI Research KLD Stats (KLD) and Bloomberg databases for the 13-year period from 2003 to 2015 in constructing ESG performance and disclosure variables, respectively. The authors adopt the general cost stickiness models from Anderson, Banker, and Janakiraman (2003) and Banker, Basu, Byzalov, and Chen (2016) to perform the analysis.
Findings – The authors find that a firm’s level of cost stickiness is positively associated with certain sticky corporate social responsibility (CSR)/ESG activities (both overall and when separately classified as strengths or concerns) but not with other nonsticky CSR activities. The authors also show that the association between cost stickiness and ESG disclosure is incrementally stronger for firms with CSR activities classified as sticky. Furthermore, the authors provide evidence that ESG disclosure is greater when both cost stickiness and the degree of sticky CSR activities increase. The authors show that when cost stickiness is high and CSR activities are sticky, management has incentives to increase CSR/ESG sustainability disclosure to decrease information asymmetry.
Originality/value – The findings present new evidence to understand how management integrates cost management strategies with various dimensions of sustainability performance decisions and show that not all ESG activities are equally effective when it comes to cost stickiness. The authors also demonstrate that increased sustainability disclosure helps reduce information asymmetry incrementally more when both costs are sticky and CSR activities are sticky.
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Kun Sun, Bo Li, Liang Fang and Qingguang Ye
Expanded polystyrene (EPS) is a low‐density and cheap material, which has been widely used in commercial areas. As the demand for small‐batch, flexible and quick production…
Abstract
Purpose
Expanded polystyrene (EPS) is a low‐density and cheap material, which has been widely used in commercial areas. As the demand for small‐batch, flexible and quick production increases, producing EPS products with metals moulds has become unaffordable. The purpose of this paper is to describe the development of an EPS rapid prototyping (ERP) process, with an electric heating tool.
Design/methodology/approach
Two new cutting strategies for the ERP process, constant angle mode and constant thickness mode, are proposed. The methods to generate tool path of those models are also discussed. In order to improve accuracy and cutting effectiveness, experiments have been carried out to investigate the thermal characteristics in the ERP process. Consequently, the relationships between the size of material removal area and process parameters are obtained. Suitable processing parameters for the ERP system are also conducted.
Findings
It is found that the ERP process can rapidly produce complex three‐dimensional parts in one‐off clamping without post‐processing procedures as in traditional rapid prototyping, such as, extra support removing, step texture finishing and distortion regulating.
Originality/value
The paper provides several examples to explain and illustrate the applicability and workflow of the ERP system.
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Jingbin Hao, Liang Fang and Robert E. Williams
Rapid prototyping (RP) of large‐scale solid models requires the stereolithographic (STL) file to be precisely partitioned. Especially, the selection of cutting positions is…
Abstract
Purpose
Rapid prototyping (RP) of large‐scale solid models requires the stereolithographic (STL) file to be precisely partitioned. Especially, the selection of cutting positions is critical for the fabrication and assembly of sub‐models. The purpose of this paper is to present an efficient curvature‐based partitioning for selecting the best‐fit loop and decomposing the large complex model into smaller and simpler sub‐models with similar‐shaped joints, which facilitate the final assembly.
Design/methodology/approach
The partition algorithm is benefited from curvature analysis of the model surface, including extracting the feature edges and constructing the feature loops. The efficiency enhancement is achieved by selecting the best‐fit loop and constructing the similar‐shape joints. The utility of the algorithm is demonstrated by the fabrication of large‐scale rapid prototypes.
Findings
By using the proposed curvature‐based partition algorithm, the reasonability and efficiency of STL model partition can be greatly improved, and the complexity of sub‐models has been reduced. It is found that the large‐scale model is efficiently partitioned and the sub‐models are precisely assembled using the proposed partitioning.
Originality/value
The curvature‐based partition algorithm is used in the RP field for the first time. Based on the curvature‐based partitioning, the reasonability and efficiency of large‐scale RP is addressed in this paper.
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The literature on non-traditional classroom environments claims that the changed emphasis in higher education teaching from the lecturer to students has intensified the global…
Abstract
The literature on non-traditional classroom environments claims that the changed emphasis in higher education teaching from the lecturer to students has intensified the global focus on student-centred learning, prompting colleges and universities globally to introspect, re-examine, and re-structure their pedagogical approaches in an attempt to align with national educational policies, and to position themselves favourably with potential students in an increasingly competitive higher education environment. This is an environment that now relies heavily on digital learning technologies, which has provoked scholars such as Heick (2012) to perceive the change to the virtual as one that makes higher education institutions accessible from anywhere – in the cloud, at home, in the workplace, or restaurant. The COVID-19 crisis has reinforced the need for this flexibility. These forces have put universities and colleges under pressure to implement new teaching approaches in non-traditional classroom settings that are appropriate for, and responsive to, the COVID-19 crisis and students in terms of learning and social support. This chapter identified and appraised key teaching approaches. It is evident that there are three key teaching approaches that higher education institutions have adopted for delivering learning in an emergency and in a student-centred fashion. The three approaches, which include the time and place dispersion, transactional distance, and collaborative learning approaches, embrace social support because they are grounded in social constructivism. Academics need to be fully committed to the role of social support giving – that is, emotional, instrumental, informational, and appraisal support – in order to foster student wellbeing and cognitive development as students learn together but apart in non-traditional classrooms. The hurried manner in which teaching and learning practices in many higher education institutions have been moved to the online format has led academics to violate many key principles of the approaches they have adopted. And this situation is borne out in the case study discussed in Chapter 8 of this volume. A review of current remote teaching and learning practices is required if academics are to embrace the full principles of the approaches that are appropriate for teaching and learning in non-traditional classroom contexts.
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Thomas R. Loy and Sven Hartlieb
Purpose – Over the last 15 years, research provided insight into several firm- and country-level determinants of asymmetric cost behavior. Their implicit premise builds on…
Abstract
Purpose – Over the last 15 years, research provided insight into several firm- and country-level determinants of asymmetric cost behavior. Their implicit premise builds on rational trade-off decisions between holding costs of idle resources and adjustment costs. The authors build upon these findings and establish an irrational component – sunlight-induced managerial mood.
Methodology/approach – The authors rely on the established cross-sectional model of asymmetric cost behavior to investigate short-term resource adjustment decisions and extend it by an exogenous proxy for managerial mood (i.e., daily sunshine hours per US county-year).
Findings – Beyond rational trade-off and planning decisions, the authors provide large-sample evidence on the influence of irrational mood on cost decisions. In accordance with research in psychology showing that higher serotine levels, attributable to sunlight, contribute to happiness and optimism, the results suggest that sunlight-induced mood increases the level of asymmetric cost behavior. Managers from firms headquartered in counties with a higher level of sunlight less likely react to a decrease in sales by reducing idle resources. Instead, they seem to be more optimistic about future demand conditions and, thus, more inclined to “sit out” downturns in firm activity until sales recover.
Research limitations/implications – Although the mood proxy is truly exogenous in the setting, the authors are unable to establish causality as the actual cost management decisions could not be observed directly. Moreover, the analyses are limited to the county level, whereas weather undoubtedly oftentimes exhibits intra-county variation.
Originality/value – This study is the first to establish an irrational antecedent of managerial resource adjustment decisions, which adds to the cost stickiness literature by demonstrating the important role of deliberate managerial decisions for corporate cost behavior.
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Jing‐Jing Fang, Yu Ding and Su‐Chin Huang
Based on the knowledge of professional pattern makers, this paper aims to propose an expert‐based automation technique of darts generation by aligning and drawing close meshes in…
Abstract
Purpose
Based on the knowledge of professional pattern makers, this paper aims to propose an expert‐based automation technique of darts generation by aligning and drawing close meshes in basic pattern in Part I. Single dart development, such as waist‐fitting dart, shoulder dart, armscye dart, side dart, and their select combination are also presented.
Design/methodology/approach
In this paper, 3D garment surface is first approximated by a finite number of meshes. Patterns are developed by aligning and rotating of the flattened meshes under the constraint of overlay avoidance. The envelop areas between the developed patterns and the curved surface are dramatically reduced from 5 percent of basic pattern to below 3 percent after darts development.
Findings
The development patterns are varied in their association with the subject's body figures and the designed garment. Darts in a different location can reduce the total area difference between the flattening undevelopable surface and the original curved surface.
Research limitations/implications
At the present stage the pattern development method cannot guarantee the uniqueness of pattern outline. Moreover, the pattern maker's knowledge inputs in this paper can only apply to the subject whose waist girth is less than hip girth in circumference.
Originality/value
The embedded pattern maker knowledge provides certain rules for pattern development from 3D design. Moreover, it is practical to be used and exported to modern 2D pattern software for further editing and revision. The same person is also used as a model after the patterns have been sewn into clothes.
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Yu Liu and Ziming Zeng
Previous research mainly uses graph neural networks on syntactic dependency graphs, often neglecting emotional cues in sarcasm detection and failing to integrate image features…
Abstract
Purpose
Previous research mainly uses graph neural networks on syntactic dependency graphs, often neglecting emotional cues in sarcasm detection and failing to integrate image features for multimodal information effectively. To address these limitations, this study proposes a novel multimodal sarcasm detection model based on the directed graph isomorphism network with sentiment enhancement and multimodal fusion (DGIN-SE-MF).
Design/methodology/approach
The approach extracts image and text features through vision transformer and BERT, respectively. To deeply integrate the extracted features, the author develops a text-guided multi-head attention fusion mechanism module. Subsequently, a directed graph is constructed through SE and the multimodal factorized bilinear pooling method to integrate image features into the graph. The DGIN then fuses the image and text features, using a weighted attention mechanism to generate the final representation.
Findings
The model is validated on three datasets: English, Chinese and an Indonesian–English dataset. The results demonstrate that the proposed model consistently outperforms other baseline models, particularly on the Chinese and English sarcasm datasets, achieving F1 scores of 88.75 % and 83.10 %, respectively.
Originality/value
The proposed model addresses the inadequacies of previous methods by effectively integrating emotional cues and image features into sarcasm detection. To the best of the authors’ knowledge, this is the first work to leverage a DGIN-SE-MF for this task, leading to significant improvements in detection performance across different languages.