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As Chinese massage is increasingly popular, many physicians are needed these days. In order to promote the experience and skills of experts and reduce labour intensity during massage, a massage robot, which could reproduce the expert techniques with individualized manipulation parameters and enhanced safety control strategies, is presented in this paper.

The kinematic and force features of key massage techniques, such as Thumb Kneading, Pressing, Rolling, Vibrating and Pinching, are summarized by analyzing the massage processes of expert physicians, and a mathematical model for robotic massage is established. With safety issues taken into account, the overall system structure of the massage robot is proposed. The system generally consists of a positioning platform and a massage end‐effector which implements the massage techniques, and the end‐effector is further divided into a parallel mechanism and a massage hand to accommodate different techniques. Visual tracking is used for positioning acupuncture points by recognizing markers on a massage vest worn by the patient. A pain threshold value is introduced to individualize therapy schemes and a force‐position control method based on the pain threshold is presented.

VAS (Visual Analogue Scale) tests for lumbar muscle strain are carried out using the massage robot, and the treatment effect of the massage robot based on traditional Chinese massage therapy theory is initially validated.

The treatment effect of the massage robot needs to be assessed clinically for more occasions and more clinical experiments will be conducted, to optimize the configuration and control strategy to meet the clinical needs in future work.

The robotic massage system presented in this paper is acting on acupuncture points based on traditional Chinese massage therapy theory, with human manipulation techniques reproduced and expert experiences incorporated. The massage robot can take the place of a massager to perform Chinese massage. Most of the massage robotic systems published in the world perform only one massage technique and the whole massage process is not completely considered. By comparison, the authors' massage robot could perform five techniques. Furthermore, the authors have designed the procedure of robotic massage specifically for patients who suffer from lumbar muscle strain.

Images taken from construction site interiors often suffer from low illumination and poor natural colors, which restrict their application for high-level site management purposes. The state-of-the-art low-light image enhancement method provides promising image enhancement results. However, they generally require a longer execution time to complete the enhancement. This study aims to develop a refined image enhancement approach to improve execution efficiency and performance accuracy.

To develop the refined illumination enhancement algorithm named enhanced illumination quality (EIQ), a quadratic expression was first added to the initial illumination map. Subsequently, an adjusted weight matrix was added to improve the smoothness of the illumination map. A coordinated descent optimization algorithm was then applied to minimize the processing time. Gamma correction was also applied to further enhance the illumination map. Finally, a frame comparing and averaging method was used to identify interior site progress.

The proposed refined approach took around 4.36–4.52 s to achieve the expected results while outperforming the current low-light image enhancement method. EIQ demonstrated a lower lightness-order error and provided higher object resolution in enhanced images. EIQ also has a higher structural similarity index and peak-signal-to-noise ratio, which indicated better image reconstruction performance.

The proposed approach provides an alternative to shorten the execution time, improve equalization of the illumination map and provide a better image reconstruction. The approach could be applied to low-light video enhancement tasks and other dark or poor jobsite images for object detection processes.

This paper aims to present an engineering computational method for fatigue life evaluation of welded structures on large-scale equipment under random vibration load.

Based on a case study of the traction transformers, virtual fatigue test (VFT) was proposed via numerical simulation approach. Static analysis was conducted to identify the risky zone and then dynamic response of the risky welds under random vibration load was calculated based on frequency-domain structural stress method (FDSSM) theory, life distribution and associated survivability at various locations of the structure were obtained. Structural modification was finally performed according to the evaluation results. Moreover, experimental test was carried out and compared with the virtual test result.

By applying the virtual test, fatigue life of the complex welded structures on large-scale equipment can be accurately and efficiently obtained considering dynamic effect under random vibration load. Meanwhile, risky welds can be directly determined and targeted modification scheme can be accordingly concluded. Validity of the VFT result was proved by comparing with the experimental test.

The proposed method can help obtain equivalent structural stress and fatigue life distribution of the welded structure at any position with various survivability and make quantitative evaluation on the life-extending effect of the structural modification. This method shows significant cost and efficiency advantages over experimental test during design stage of the large-scale structures in numerous manufacturing industries.

Reinforced concrete slabs in fire have been heavily studied over the last three decades. However, most experimental and numerical work focuses on long-duration uniform exposure to standard fire. Considerably less effort has been put into investigating the response to localised fires that result in planarly non-uniform temperature distribution in the exposed elements.

In this paper, the OpenSees for Fire framework for modelling slabs under non-uniform fire exposure is presented, verified against numerical predictions by Abaqus and then validated against experimental tests. The thermal wrapper developed within OpenSees for Fire is then utilised to apply localised fire exposure to the validated slab models using the parameters of an experimentally observed localised fire. The effect of the smoke layer is also considered in this model and shown to significantly contribute to the thermal and thus thermo-mechanical response of slabs. Finally, the effect of localised fire heat release rate (HRR) and boundary conditions are studied.

The analysis showed that boundary conditions are very important for the response of slabs subject to localised fire, and expansive strains may be accommodated as deflections without severely damaging the slab by considering the lateral restraint.

This work demonstrates the capabilities of OpenSees for Fire in modelling structural behaviours subjected to non-uniform fire conditions and investigates the damage pattens of flat slabs exposed to localised fires. It is an advancing step towards understanding structural responses to realistic fires.

Following the standard practice of using nutrition claims to denote food functionality, this study empirically explores Chinese consumers’ willingness-to-pay for functional processed meat products by using three nutrition claims (namely “increased calcium,” “containing omega-3”, and “reduced salt”) made on pork sausages. It also aims to outline the typical characteristics of Chinese consumer segments based on preferences.

A choice-based choice experiment is utilized to investigate Chinese consumers’ valuation on attributes of interest regarding functional sausage products. First-hand data was collected in the two cities of Xi'an and Beijing.

There are market potentials for domestic and/or imported functional processed meat products among Chinese consumers. Nutrition claims made on pork sausages are appealing to Chinese consumers, and therefore, monetarily rewarded by them. Being imported from a more developed country of origin could both positively and negatively impact consumers’ WTP for nutrition claims made on pork sausages. Furthermore, specific functional modification strategies should be taken into account when addressing different segments of the Chinese market. In addition, regional impacts between Xi'an and Beijing are implied in terms of consumers’ valuation for functional pork sausages.

Limitations in the current study are mainly two folds. First, the WTP estimation magnitudes are subject to a hypothetical bias by using a stated preference approach. Second, this study only focuses on pork sausages to explore consumers’ perceptions and selects three nutrition claims among many other relevant options.

Implications are provided for meat marketers and for Chinese official food policymakers, such that promoting meat products with a nutrition claim is an attractive marketing strategy for foreign food manufacturers in China, and more reformulated meat products with better nutritional compositions should be allowed in the Chinese market.

To the best of the author’s knowledge, this research is the first to fill in the literature blank on investigating the consumers’ valuation for functional meat in the emerging market of China. Because when taking Chinese consumers as a target market and evaluating their perceptions of food quality-related labeling and certifications, the existing literature is mainly limited to topics of product safety, organic/green products, and geographical origins. However, nutrition claims, as marketable credence attributes that associate closely to the main characteristics of the functional food products, have been explored to a much lesser extent among Chinese consumers.

To investigate a new approach for making soy‐based adhesive having appropriate properties for potential application in wood industry.

Three chemicals were used for modifying protein contained in soy flour. According to orthogonal experiment design, nine soy‐based adhesives were prepared. Shearing strength of plywood bonded with these adhesives was measured to evaluate the bonding strength of nine formulas. Based on statistic analysis, the main effect factor and an optimised formula were determined. Further investigation on the modification effect to protein molecule was conducted by Fourier Transform Infrared Spectroscopy. In order to facilitate practical application, the viscosity of optimum formula adhesive was measured to determine possible working life. Three additives were added to optimise formula for reducing mould growth.

Based on soy‐flour mass, the best combination of lime milk, sodium hydroxide (NaOH) and sodium silicate was 10, 2, and 20 per cent, respectively. NaOH was considered the main effect factor on bonding strength, and sodium silicate was of the second importance. The viscosity of the optimised adhesive changed lightly in 2 h, and significantly increased from 2 to 4 h. However, it still could spread on veneer, which indicated a reasonable working life for practical application. Based on soy flour mass, when 0.5 per cent sodium benzoate or 25 per cent phenol formaldehyde was added, mould growth could be restrained after early stage.

Though the studied soy‐based adhesive had a good bonding strength and comparative water resistance, its pH was a little too high, which may cause risks of discolour of light coloured wood. Further study is needed to solve this problem.

The approach provided a bio‐adhesive with good bonding strength, comparative water resistance, reasonable working life, and without formaldehyde emission. Soy‐based adhesive is considered a promising alternate adhesive in wood industry and other applications because of the above mentioned advantages.

It provided a potential way to utilise by‐product of agriculture, soy‐flour, as industrial raw material. This will benefit farmers significantly. Meanwhile, the modified soy‐based adhesive is promising to partly or completely replace urea formaldehyde resin that are mainly used in wood industry, avoiding formaldehyde emission and reducing the dependence on petroleum products.

Addressing global warming challenge, carbon emissions reduction potential of the construction industry has received additional attentions. The decoupling of construction industry and carbon emissions through policies, technologies and model innovations is an effective way for reducing environmental pollution and achieve eco-urban target. The paper aims to discuss these issues.

Within the scope of green building carbon emissions (GB-CO₂) research, a large number of scientific literature has been published in construction discipline over the past few decades. However, it seems that a systematic summary of strategies, techniques, models and scientific discussion of future direction of GB-CO₂ is lacking. Therefore, this paper carries out data mining on authoritative journals, identified the key research topics, active research areas and further research trends through visualization studies.

This study contributes to the body of knowledge in GB-CO₂ by critically reviewing and summarizing: professional high-quality journals have a greater influence in the scope of research, developed countries and developing countries are all very concerned about sustainable buildings, and the current hot topics of research focus on the application of the life cycle models, energy efficiency, environmental performance of concrete material, etc. Moreover, further research areas that could expand the knowledge of cross-national long-term carbon mechanisms, develop comprehensive life cycle carbon emissions assessment models, build technical standards and tests for the sustainable building material and systems, and exploit multi-objective decision models considering decarbonizing design and renewable energy.

This study is of value in systematic insight the state-of-the-art of GB-CO₂ research in the more recent decade. A more vividly and effectively method is documented in extending the traditional bibliometric review to a deeper discussion. This study can also benefit construction practitioners by providing them a focused perspective of strategy and technologies innovations for emerging practices in green building projects.

The study aims to carry out the production of a bulk heterojunction organic solar cell in a laboratory scale using a blend of poly (3-hexylthiopene) (P3HT) and [6, 6]-phenyl (C61) butyric acid methyl ether (PCBM).

Four inverted geometry organic solar cells were prepared based on 1:1 ratio of P3HT to PCBM and subjected to post annealing at different temperatures of 32, 120, 130 and 140°C. Solar cells were fabricated with structure glass/ITO/P3HT:PCBM/PEDOT:PSS/Au and characterized using Keithley 2400 series sourcemeter and a multimeter interfaced to a computer system with a LabVIEW software, which showed both dark and illumination current–voltage characteristic curves. Four reference cells were also fabricated with structure soda lime glass/P3HT:PCBM and annealed at different temperatures of 32, 120, 130 and 140°C.

The third organic solar cell prepared, Sample CITO, had the best performance with power conversion efficiency (PCE) of 2.0281 per cent, fill factor (FF) of 0.392, short circuit current of −0.0133 A and open circuit voltage of 0.389 V. Annealing of active layer was found to improve cell morphology, FF and PCE. Annealing of the active layer at 140°C resulted in a decrease of the PCE to 2.01 per cent.

These findings are in good agreement with previous investigation in literature which reported that best annealing temperature for a 1:1 ratio blend of active material is 130°C. Ultraviolet–visible spectra on reference cells showed that sample CITO had wider absorption spectra with peak absorbance at a wavelength of 508 nm.

This research is purely original.

Construction progress monitoring (CPM) is considered a difficult and tedious task in construction projects, which focuses on identifying discrepancies between the as-built product and the as-planned design. Computer vision (CV) technology is applied to automate the CPM process. However, the synergy between the CV and CPM in literature and industry practice is lacking. This study aims to fulfil this research gap.

A Delphi qualitative approach was used in this study by conducting two interview rounds. The collected data was analysed using manual content analysis.

This study identified seven stages of CPM; data acquisition, information retrieval, verification, progress estimation and comparison, visualisation of the results and schedule updating. Factors such as higher accuracy in data, less labourious process, efficiency and near real-time access are some of the significant enablers in instigating CV for CPM. Major challenges identified were occlusions and lighting issues in the site images and lack of support from the management. The challenges can be easily overcome by implementing suitable strategies such as familiarisation of the workforce with CV technology and application of CV research for the construction industry to grow with the technology in line with other industries.

This study addresses the gap pertaining to the synergy between the CV in CPM literature and the industry practice. This research contributes by enabling the construction personnel to identify the shortcomings and the opportunities to apply automated technologies concerning each stage in the progress monitoring process.

People often face constraints such as a lack of time or information in taking decisions, which leads them to use heuristics. In these situations, fast and frugal rules may be useful for making adaptive decisions with fewer resources, even if it leads to suboptimal choices. When applied to financial markets, the recognition heuristic predicts that investors acquire the stocks that they are aware of, thereby inflating the price of the most recognized stocks. This paper aims to study the profitability against the market of the most recognized stocks in Europe.

In this paper, the authors perform a survey and use Google Trends to study the profitability against the market of the most recognized stocks in Europe.

The authors conclude that a recognition heuristic portfolio yields poorer returns than a market portfolio. In contrast, from the data collected on Google Trends, weak evidence was found that strong increases in companies monthly search volumes may lead to abnormal returns in the following month.

The applied investment strategy does not account for transaction costs, which may jeopardize its profitability given the fact that it is necessary to revise the portfolio on a monthly basis. Despite the results obtained, they are useful to understanding the performance of recognition heuristic strategies over a comprehensive time horizon, and it would be interesting to depict its viability during different market conditions. This analysis could provide additional information about a preferable scenario for employing our strategies and, ultimately, enhance the profitability of recognition heuristic strategies.

Through the exhaustive analysis performed here on the recognition heuristic in the European stock market, it is possible to conclude that no evidence was found for the viability of exploring this type of strategy. In fact, the investors would always gain better returns when adopting a passive investment strategy. Therefore, it would be wise to assume that the European market presents at least a degree of efficiency where no investment would yield abnormal returns following the recognition heuristic.

The main objective of this paper is to study the performance of the recognition heuristic in the financial markets and to contribute to the knowledge in this field. Although many authors have already studied this heuristic when applied to financial markets, there is a lack of consensus in the literature.