Search results

This study aims to investigate the effects of nano or inorganic fillers on unsaturated polyester’s (UPE) thermal, mechanical, and physical properties. UPE reinforced with nanoparticles shows better properties than the pure polymer itself. Nano or inorganic fillers are used in the polymeric matrix to improve thermal, mechanical and physical properties.

To improve thermal, mechanical and physical properties, UPE resin was modified with silica (S), boron nitride (BN) and S/BN hybrid nanoparticles at different ratios. Viscosity and solids content measurement, Fourier transform infrared spectroscopy, contact angle measurement, scanning electron microscopy (SEM), thermogravimetric analysis (TGA) and thermal conductivity coefficient tests were performed on the samples.

In the SEM analysis, the UPE sample showed a smooth appearance, while all samples containing additives showed phase separation and overall heterogeneous distribution. TGA results demonstrated that the thermal stability of the resin increased in the presence of S and BN additives. According to the results, it was observed that the presence of S and BN additives in the UPE resin and the use of certain ratios improved the resin properties.

As a result of the literature search, to the best of the authors’ knowledge, no study was found in which BN nanoparticles were included in the UPE resin together with S.

This research examines the impact of the National Rural E-commerce Comprehensive Demonstration Project (NRECDP) on poverty reduction and income growth in rural China.

The study develops a theoretical framework, which considers the role of geographical, technological, institutional and cultural factors for the e-commerce poverty alleviation (e-CPA) model. Empirically, this study applies the difference-in-differences (DID) model and the event study approach to evaluate the effectiveness of NRECDP on the basis of large-scale county-level and household-level panel data spanning 2010 to 2020.

The study found that the NRECDP, as a government-led, information and communication technology (ICT)-enabled, market-based program, has led to a significant increase in per capita output of primary industry employees, as well as in the disposable income of rural residents, especially those in national-level poverty-stricken (NP) counties. The interventions of the NRECDP achieved these positive outcomes through transportation and Internet infrastructure improvement, ICT adoption and human capital accumulation in impoverished towns and villages in remote rural areas. These effects are larger in the eastern region of China, followed by the central region, whereas the weakest effects were found in the western region. However, we found little evidence of the NRECDP increasing household developmental expenditure.

The study findings have important practical and policy implications for rural e-commerce development and self-sustained poverty alleviation solutions. The research revealed the significance of government NRECDP interventions for increasing rural income, reducing living costs, and empowering the rural population in its multiple social roles, namely, as consumers, producers, employees and microentrepreneurs. The local cultural context may also play a role in ICT adoption and entrepreneurship cultivation with a downstream effect on the effectiveness of e-CPA practices. Policymakers would need to ensure a supportive entrepreneur-friendly environment for rural e-commerce development and continue implementing progressive policies for poverty alleviation.

This study explores poverty alleviation issues in China by developing for the first time a multi-faceted framework that is subsequently tested by both county-level and household-level large-scale observations. Also, it is the first study to provide nationwide empirical evidence on the effectiveness of e-CPA in narrowing down the spatial and digital divides in China. In addition to the impact of geography, technology and governmental support, this study also sheds light on the role of culture in the adoption and diffusion of digital technologies and as a source of local entrepreneurial opportunities.

For a successful search, all members of the client–headhunter–candidate trio need to step up to the plate. How can clients better prepare for and engage in the search process? What are the current limits of client engagement and their rights vis-á-vis the headhunter? We explain why headhunting is different from recruitment, and why procuring executive search is as serious as other assets. We reveal the depth of questioning and bias management that it takes to reveal and attract the right candidate. We propose five points to build into the profile of the leader of the future. We next take a look at the clients of executive search firms – who come in all shapes and sizes. Van Eijck distinguishes four groups: multinationals, family businesses, private equity firms and public institutions. A tour signals points of attention for each group regarding a search process and some key points that apply across the spectrum – for example, how wildcard candidates can compromise a search process, the persistent problem of “no pay no cure” and why an appointment doesn’t always guarantee success. Finally, we move to the world of the executive candidate. Many make errors (also of judgment) when building their CVs. A seasoned headhunter can easily spot these. We present the keys to forging a robust story, working effectively with an executive search consultant and conclude with the features of the modern educational and work environment that can get in the way of a career.

An earlier form of this chapter by the author was published in Dutch in “Bestemming Boardroom: over zoeken en gevonden worden” (Boom, Amsterdam, 2018).

This study sought to understand which food allergen labeling systems (non-directive, semi-directive, and directive) were attended to and preferred by 34 participants with food hypersensitivity and their perceived corporate social responsibility (CSR) and behavioral intention towards a restaurant that identifies food allergens on menus.

This study used an online survey with open-ended and ranking questions, combined with eye-tracking technology, to explore participants' visual attention and design preferences regarding four menus. This study utilized one-way repeated measures analysis of variance (RM-ANOVA) and heat maps to analyze participants' menu-reading behaviors. A content analysis of survey responses and a ranking analysis of menus were conducted to understand the reasons behind consumers' preferred menu designs.

The advisory statement was not much attended to. Participants identified food allergen information significantly quicker with the directive labeling system (icons) than the other two systems, implying they were eye-catching. Semi-directive labeling system (red text) has lower visit count and was more preferred than two other systems; each labeling system has its strengths and limitations. Participants viewed restaurants that disclosed food allergen information on menus as socially responsible, and they would revisit those restaurants in the future.

This study was one of the first to explore, through use of eye-tracking technology, which food allergen labeling systems were attended to by consumers with food hypersensitivity. The use of triangulation methods strengthened the credibility of the results. The study provided empirical data to restauranteurs in the US on the values of food allergen identification on restaurant menus, although it is voluntary.

This study aims to explore the synergistic effect of oxide nanoparticles (ZnO, Fe₂O₃, SiO₂) and cerium nitrate inhibitor on anti-corrosion performance of epoxy coating. First, cerium nitrate inhibitors are absorbed on the surface of various oxide nanoparticles. Thereafter, epoxy nanocomposite coatings have been fabricated on carbon steel substrate using these oxide@Ce nanoparticles as both nano-fillers and nano-inhibitors.

To evaluate the impact of oxides@Ce nanoparticles on mechanical properties of epoxy coating, the abrasion resistance and impact resistance of epoxy coatings have been examined. To study the impact of oxides@Ce nanoparticles on anti-corrosion performance of epoxy coating for steel, the electrochemical impedance spectroscopy has been carried out in 3% NaCl solution.

ZnO@Ce3+ and SiO2@Ce3+ nanoparticles provide more enhancement in the epoxy pore network than modification of the epoxy/steel interface. Whereas, Fe2O3@Ce3+ nanoparticles have more to do with modification of the epoxy/steel interface than to change the epoxy pore network.

Incorporation of both oxide nanoparticles and inorganic inhibitor into the epoxy resin is a promising approach for enhancing the anti-corrosion performance of carbon steel.

Recovery Colleges were developed to support the recovery of people with mental health difficulties through courses co-produced by professionals and people with lived experience. This study aims to examine the use of Recovery Colleges to support people with dementia.

A survey was circulated to UK Recovery College and memory service staff, exploring provision, delivery and attendance of dementia courses. Open responses provided insight into participant views about recovery in post-diagnostic support and the practicalities of running dementia courses.

A total of 51 Recovery College staff and 210 memory service staff completed the survey. Twelve Recovery College dementia courses were identified across the UK. Three categories emerged from the qualitative data: post-diagnostic support, recovery in the context of dementia, challenges and areas of innovation.

This study highlights the benefits and practicalities of running Recovery College courses with people with dementia. Peer-to-peer learning was seen as valuable in post-diagnostic support but opinions were divided about the term recovery in dementia.

Value-based health care (VBHC) argues that health-care needs to re-focus to maximise value creation, defining value as the quota when dividing the outcomes important for the patient, by the cost for health care to deliver such outcomes. This study aims to explore the perception of value among different stakeholders involved in the process of implementing VBHC at a Swedish hospital to support leaders to be more efficient and effective when developing health care.

Participants comprised 19 clinicians and non-clinicians involved in the implementation of VBHC. Semi-structured interviews were conducted and content analysis was performed.

The clinicians described value as a dynamic concept, dependent on the patient and the clinical setting, stating that improving outcomes was more important than containing costs. The value for non-clinicians appeared more driven by the interplay between the outcome and the cost. Non-clinicians related VBHC to a strategic framework for governance or for monitoring different continuous improvement processes, while clinicians appreciated VBHC, as they perceived its introduction as an opportunity to focus more on outcomes for patients and less on cost containment.

There is variation in how clinicians and non-clinicians perceive the key concept of value when implementing VBHC. Clinicians focus on increasing treatment efficacy and improving medical outcomes but have a limited focus on cost and what patients consider most valuable. If the concept of value is defined primarily by clinicians’ own assumptions, there is a clear risk that the foundational premise of VBHC, to understand what outcomes patients value in their specific situation in relation to the cost to produce such outcome, will fail. Health-care leaders need to ensure that patients and the non-clinicians’ perception of value, is integrated with the clinical perception, if VBHC is to deliver on its promise.

Higher education plays an essential role in achieving the United Nations sustainable development goals (SDGs). However, there are only scattered studies on monitoring how universities promote SDGs through their curriculum. The purpose of this study is to investigate the connection of existing common core courses in a university to SDG education. In particular, this study wanted to know how common core courses can be classified by machine-learning approach according to SDGs.

In this report, the authors used machine learning techniques to tag the 166 common core courses in a university with SDGs and then analyzed the results based on visualizations. The training data set comes from the OSDG public community data set which the community had verified. Meanwhile, key descriptions of common core courses had been used for the classification. The study used the multinomial logistic regression algorithm for the classification. Descriptive analysis at course-level, theme-level and curriculum-level had been included to illustrate the proposed approach’s functions.

The results indicate that the machine-learning classification approach can significantly accelerate the SDG classification of courses. However, currently, it cannot replace human classification due to the complexity of the problem and the lack of relevant training data.

The study can achieve a more accurate model training through adopting advanced machine learning algorithms (e.g. deep learning, multioutput multiclass machine learning algorithms); developing a more effective test data set by extracting more relevant information from syllabus and learning materials; expanding the training data set of SDGs that currently have insufficient records (e.g. SDG 12); and replacing the existing training data set from OSDG by authentic education-related documents (such as course syllabus) with SDG classifications. The performance of the algorithm should also be compared to other computer-based and human-based SDG classification approaches for cross-checking the results, with a systematic evaluation framework. Furthermore, the study can be analyzed by circulating results to students and understanding how they would interpret and use the results for choosing courses for studying. Furthermore, the study mainly focused on the classification of topics that are taught in courses but cannot measure the effectiveness of adopted pedagogies, assessment strategies and competency development strategies in courses. The study can also conduct analysis based on assessment tasks and rubrics of courses to see whether the assessment tasks can help students understand and take action on SDGs.

The proposed approach explores the possibility of using machine learning for SDG classifications in scale.

The purpose of this study is to enhance the functional properties of Hessian fabric through resin finishing. Hessian bags made of lignocellulosic jute fiber are commonly used to pack, store and transport agro-commodities, including horticultural crops such as rice, potato, onion and wheat. However, because of high water affinity, these bags undergo degradation in properties due to moisture release by the stored commodities themselves. Exposure to natural elements, e.g. rain and dew, also causes moisture absorption in hessian bags. Once the bag gets moistened, degradation of jute bags starts due to microbial attack, leading to loss in tensile strength and change in extensibility, leading to ultimate breakage in warp and weft directions of the fabric.

To overcome the degradation in the functional properties of hessian fabric due to exposure to moisture and microbial attack, the application of semi-synthetic polymeric materials was carried out.

Tenacity, bursting strength, puncture resistance, tear strength and breaking load, as well as life cycle of resin-treated jute fabric was found to be better than control jute.

To the best of the authors’ knowledge, no recent reports of resin finishing on jute (hessian) fabric with semi-synthetic resins are presently available, other than coating with rubber.

Three-dimensional (3D)printed skulls for neurosurgical training are increasingly being used due to the widespread access to 3D printing technology, their low cost and accuracy, as well as limitations and ethical concerns associated with using human cadavers. However, little is known about the risks of airborne particles or volatile organic compounds (VOCs) released while drilling into 3D-printed plastic models. The aim of this study is to assess the level of exposure to airborne contaminants while burr hole drilling.

3D-printed skull samples were produced using three different materials (polyethylene terephthalate glycol [PETG], white resin and Bone^STN) across three different 3D print processes (fused filament fabrication, stereolithography [SLA] and material jetting). A neurosurgeon performed extended burr hole drilling for 10 min on each sample. Spot measurements of particulate matter (PM2.5 and PM10) were recorded, and air samples were analysed for approximately 90 VOCs.

The particulate matter for PETG was found to be below the threshold value for respirable particles. However, the particulate matter for white resin and Bone^STN was found to be above the threshold value at PM10, which could be harmful for long periods of exposure without personal protective equipment (PPE). The VOC measurements for all materials were found to be below safety thresholds, and therefore not harmful.

To the best of the authors’ knowledge, this is the first study to evaluate the safety of 3D-printed materials for burr hole surgical drilling. It recommends PETG as a safe material requiring minimal respiratory control measures, whereas resin-based materials will require safety controls to deal with airborne particles.