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This study aims to develop a pH-functional thin-film sensor for non-invasive measurement of spoilage of packed fish.

At first, polymers of natural origin such as hydroxy(propyl)methyl cellulose, potato dextrose agar and starch alongside a pH sensitive-mixed indicator formulation were used to produce thin film sensor. The developed thin film sensor was tested for monitoring the spoilage of seafood stored at 4°C. Using ultraviolet-visible and Fourier-transform infrared spectroscopy, the halochromic sensor was characterised. In addition, the halochromic response of the thin film was directly correlated to the total volatile base nitrogen emitted by the packaged fish, pH, microbial activity and sensory evaluation.

The results suggested the developed biopolymer-based thin film sensor showed different colours in line with the spoilage of the packed fish, which could be well correlated with the total volatile base nitrogen, microbial activity and sensory evaluation. In addition, the thin film sensors exhibited a high degree of biodegradability. The biopolymers-based thin film halochromic sensor has exhibited excellent biodegradability along with sensitiveness towards the spoilage of the packed fish.

In the future, consumers and retailers may prefer seafood containers equipped with such halochromic sensors to determine the degree of food deterioration as a direct indicator of food quality.

This study aims to evaluate the potential of using the in-nozzle impregnation approach to reuse recycled PET (RPET) to develop continuous banana fiber (CBF) reinforced bio-composites. The mechanical properties and fracture morphology behavior are evaluated to establish the relationships between layer spacing–microstructural characteristics–mechanical properties of CBF/RPET composite.

This study uses RPET filament developed from post-consumer PET bottles and CBF extracted from agricultural waste banana sap. RPET serves as the matrix material, while CBF acts as the reinforcement. The test specimens were fabricated using a customized fused deposition modeling 3D printer. In this process, customized 3D printer heads were used, which have a unique capability to extrude and deposit print fibers consisting of a CBF core coated with an RPET matrix. The tensile and flexural samples were 3D printed at varying layer spacing.

The Young’s modulus (E), yield strength (sy) and ultimate tensile strength of the CBF/RPET sample fabricated with 0.7 mm layer spacing are 1.9 times, 1.25 times and 1.8 times greater than neat RPET, respectively. Similarly, the flexural test results showed that the flexural strength of the CBF/RPET sample fabricated at 0.6 mm layer spacing was 47.52 ± 2.00 MPa, which was far greater than the flexural strength of the neat RPET sample (25.12 ± 1.94 MPa).

This study holds significant social implications highlighting the growing environmental sustainability and plastic waste recycling concerns. The use of recycled PET material to develop 3D-printed sustainable structures may reduce resource consumption and encourages responsible production practices.

The key innovation lies in the concept of in-nozzle impregnation approach, where RPET is reinforced with CBF to develop a sustainable composite structure. CBF reinforcement has made RPET a superior, sustainable, environmentally friendly material that can reduce the reliance on virgin plastic material for 3D printing.

We expect to provide a complete theoretical framework and large sample evidence on the impact of corporate social responsibility (CSR) on the efficiency of labor investment. We also hope to provide micro-evidence based on labor investment behavior for the two-sided impact of corporate CSR behavior.

This paper measures labor investment efficiency by estimating the difference between actual and expected net hiring of enterprises. CSR is measured on the basis of the CSR score of Chinese listed companies published by Hexun.com. A regression model is constructed to analyze the relationship between CSR and labor investment efficiency. Possible endogeneity problems are controlled by lagging independent variables, propensity score matching method and difference-in-difference method.

Results show that CSR can improve labor investment efficiency by reducing over-hiring and under-hiring in emerging markets. The existence of the mediating effect of agency cost, information disclosure quality and employment fluctuation confirms that CSR improves labor investment efficiency through two mechanisms of corporate governance and labor market friction. The improvement effect of CSR on labor investment efficiency is more significant in non-state-owned, high CEO shareholding ratio and high-average urban wage enterprises.

In conclusion, our study is an important supplement to the existing research on the factors affecting labor investment efficiency. Our research conclusions will be helpful for enterprises in developing countries or enterprises in labor-intensive industries to improve labor investment inefficiency. The conclusion of the mechanism analysis in this paper provides more complete and reliable microscopic evidence for accurately identifying the specific path of CSR's impact on labor investment efficiency. This paper verifies the positive impact of CSR from the perspective of labor investment efficiency in the context of a developing country, which provides evidence for the theoretical conflicts related to CSR based on the effectiveness of enterprise labor investment decisions.

This study aims to investigate the individual electrochemical transients arising from local anodic events on stainless steel, to uncover the potential mechanisms producing different types of transients and to derive appropriate parameters indicative of the corrosion severity of such transient events.

An equivalent circuit model was used for the transient analysis, which was performed using a local current allocation rule based on the relative instant cathodic resistance of the coupled electrodes, as well as the kinetic parameters derived from the electrochemical polarization measurement.

The shape and size of the electrochemical current transients arising from SS 316 L were influenced by the film stability, local anodic dissolution kinetics and the symmetry of the cathodic kinetics between the coupled electrodes, where the ultralong transient might correspond to the propagation of film damage with a slow anodic dissolution rate. The dynamic cathodic resistance during the final stage of transient current growth can serve as a characteristic parameter that reflects the loss of passive film protection.

Estimation of the local anodic current trace opens a new way for individual electrochemical transient analysis associated with the charges involved, local current densities and changes in film resistance throughout localized corrosion processes.

The purpose of this paper is to systematically analyze the literature around regulatory compliance and market manipulation in capital markets through the use of bibliometrics and propose future research directions. Under the domain of capital markets, this theme is a niche area of research where greater academic investigations are required. Most of the research is fragmented and limited to a few conventional aspects only. To address this gap, this study engages in a large-scale systematic literature review approach to collect and analyze the research corpus in the post-2000 era.

The big data corpus comprising research articles has been extracted from the scientific Scopus database and analyzed using the VoSviewer application. The literature around the subject has been presented using bibliometrics to give useful insights on the most popular research work and articles, top contributing journals, authors, institutions and countries leading to identification of gaps and potential research areas.

Based on the review, this study concludes that, even in an era of global market integration and disruptive technological advancements, many important aspects of this subject remain significantly underexplored. Over the past two decades, research has lagged behind the evolution of capital market crime and market regulations. Finally, based on the findings, the study suggests important future research directions as well as a few research questions. This includes market manipulation, market regulations and new-age technologies, all of which could be very useful to researchers in this field and generate key inputs for stock market regulators.

The limitation of this research is that it is based on Scopus database so the possibility of omission of some literature cannot be completely ruled out. More advanced machine learning techniques could be applied to decode the finer aspects of the studies undertaken so far.

Increased integration among global markets, fast-paced technological disruptions and complexity of financial crimes in stock markets have put immense pressure on market regulators. As economies and equity markets evolve, good research investigations can aid in a better understanding of market manipulation and regulatory compliance. The proposed research directions will be very useful to researchers in this field as well as generate key inputs for stock market regulators to deal with market misbehavior.

This study has adopted a period-wise broad-based scientific approach to identify some of the most pertinent gaps in the subject and has proposed practical areas of study to strengthen the literature in the said field.

This paper aims to characterize the surface film formed on Alloys 800 and 690 in chloride and thiosulfate-containing solution at 300°C.

Alloy 800 and 690 were immersed in chloride and thiosulfate-containing solution at 300°C up to five days, and then the surface film was analyzed by scanning electron microscopy (SEM), X-ray photoelectron spectroscopy (XPS), transmission electron microscopy (TEM) and energy dispersive X-ray spectrometers (EDX).

Through static immersion experiments in a high-temperature and high-pressure water environment, the alloy samples covered by surface film after five days of immersion were obtained. The morphology of the surface film was characterized at both horizontal and cross-sectional scales using SEM and focused ion beam-TEM techniques. It was observed that due to the influence of the quartz lining, the surface film primarily exhibited a bilayered structure. The first layer contained a significant amount of SiO₂, with a higher content of metal hydroxides compared to metal oxides. The second layer was predominantly composed of Fe, Ni and Cr, with a higher content of metal oxides compared to metal hydroxides.

The results showed that the materials of the lining of the autoclave could significantly influence the film composition of the tested material, which should be paid attention when analyzing the corrosion mechanism at high temperature.

This study aims to explore the integration of machine learning (ML) in tribology to optimize lubrication interval decisions, aiming to enhance equipment lifespan and operational efficiency through wear image analysis.

Using a data set of scanning electron microscopy images from an internal combustion engine, the authors used AlexNet as the feature extraction algorithm and the J48 decision tree algorithm for feature selection and compared 15 ML classifiers from the lazy-, Bayes and tree-based families.

From the analyzed ML classifiers, instance-based k-nearest neighbor emerged as the optimal algorithm with a 95% classification accuracy against testing data. This surpassed individually trained convolutional neural networks’ (CNNs) and closely approached ensemble deep learning (DL) techniques’ accuracy.

The proposed approach simplifies the process, enhances efficiency and improves interpretability compared to more complex CNNs and ensemble DL techniques.

The purpose of this study is to investigate the influence of varying concentrations of nano-SiO₂ particle doping on the structure and properties of the micro-arc oxidation (MAO) coating of 7075 aluminum alloy. This research aims to provide novel insights and methodologies for the surface treatment and protection of 7075 aluminum alloy.

The surface morphology of the MAO coating was characterized using scanning electron microscope. Energy spectrometer was used to characterize the elemental content and distribution on the surface and cross section of the MAO coating. The phase composition of the MAO coating was characterized using X-ray diffractometer. The corrosion resistance of the MAO coating was characterized using an electrochemical workstation.

The results showed that when the addition of nano-SiO₂ particles is 3 g/L, the corrosion resistance is optimal.

This study investigated the influence of different concentrations of nano-SiO₂ particles on the structure and properties of the MAO coating of 7075 aluminum alloy.

The purpose of this paper is to investigate what factors can affect individuals’ knowledge sharing on social media from the perspectives of personality traits and social capital.

A theoretical model was developed with reference to the personality traits theory and the social capital theory. Accordingly, a questionnaire was designed to collect the individuals’ ideas on knowledge sharing on social media and further test the model. The questionnaire was then distributed to two LINE groups. Finally, the collected data were analyzed using the partial least squares (PLS) approach.

Personality traits not only directly affect knowledge sharing, but also indirectly influence it via social capital. Of all personality traits, agreeableness, openness and extraversion directly and indirectly influence knowledge sharing.

Knowledge sharing is undertaken by individuals and social groups. It starts with individuals and then diffuses to other members of a group.

Group managers have to identify the members who are friendly, open-minded or extroverted and encourage them to act as the bellwethers for knowledge sharing under an effective regulatory regime, through which intra-group knowledge sharing can be promoted.

This study introduces a new model to explore knowledge sharing on social media from individual and social perspectives. It illustrates what will affect individuals’ knowledge sharing on social media.

The development and evolution of stakeholder collaborative innovation in megaprojects is impacted by various influencing factors. The effect of influencing factors on collaborative innovation performance (CIP) in megaprojects is not a simplistic linear relationship but an iterative and non-linear relationship that requires a dynamic perspective to analyze. Therefore, this paper adopts the system dynamic (SD) approach to investigate the dynamic and interactive relationships between the CIP and the influencing factors.

The study first develops a research framework with the system boundary of “CIP system – organizational collaboration subsystem – knowledge collaboration subsystem – strategic collaboration subsystem”. Then, the causal relationship model, the stock-flow model, and the mathematical equations were determined based on the literature review and the expert interviews. Finally, five performance improvement scenarios were designed according to the practice context of CIP in megaprojects, and simulations were performed using the Vensim PLE software to investigate the CIP from a dynamic perspective.

The findings reveal that the effect of different influencing factors on CIP grows non-linearly, with the cumulative effect becoming more pronounced as time advances. The incentive mechanism has the most significant effect, and the combined effect of multiple influencing factors has a highly significant facilitating effect on improving CIP. Strategic collaboration, organizational collaboration and knowledge collaboration are mutually conditional and reinforcing with each other, which ultimately promotes the improvement of CIP.

This study uncovers the inherent pattern and the interactive dynamic mechanism of factors for improving CIP in the context of megaprojects. It enriches the theoretical research in the area of collaborative innovation in megaprojects and provides practical management strategies for improving CIP.