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Surface acoustic wave (SAW) sensors have attracted great attention worldwide for a variety of applications in measuring physical, chemical and biological parameters. However, stability has been one of the key issues which have limited their effective commercial applications. To fully understand this challenge of operation stability, this paper aims to systematically review mechanisms, stability issues and future challenges of SAW sensors for various applications.

This review paper starts with different types of SAWs, advantages and disadvantages of different types of SAW sensors and then the stability issues of SAW sensors. Subsequently, recent efforts made by researchers for improving working stability of SAW sensors are reviewed. Finally, it discusses the existing challenges and future prospects of SAW sensors in the rapidly growing Internet of Things-enabled application market.

A large number of scientific articles related to SAW technologies were found, and a number of opportunities for future researchers were identified. Over the past 20 years, SAW-related research has gained a growing interest of researchers. SAW sensors have attracted more and more researchers worldwide over the years, but the research topics of SAW sensor stability only own an extremely poor percentage in the total researc topics of SAWs or SAW sensors.

Although SAW sensors have been attracting researchers worldwide for decades, researchers mainly focused on the new materials and design strategies for SAW sensors to achieve good sensitivity and selectivity, and little work can be found on the stability issues of SAW sensors, which are so important for SAW sensor industries and one of the key factors to be mature products. Therefore, this paper systematically reviewed the SAW sensors from their fundamental mechanisms to stability issues and indicated their future challenges for various applications.

Climate change is one of our time’s most pressing global environmental challenges, and environmental innovation is critical to addressing it. This study aims to investigate the relationship between environmental innovation and carbon emission in the healthcare industry in Europe while also examining the moderating role of environmental governance.

Data for this study were collected from publicly listed healthcare companies in ten European countries spanning the years 2012–2021. The selected countries encompassed Belgium, Denmark, France, Germany, Italy, Netherlands, Spain, Sweden, Switzerland and the United Kingdom. The research encompassed all healthcare companies for which data were accessible, resulting in a comprehensive dataset comprising 1,210 companies. The authors collected data from multiple sources, including annual reports, the World Bank and Eikon databases, to ensure a robust and extensive dataset.

The results of this study indicate that environmental governance plays a significant moderating role in the relationship between environmental innovation and carbon emission within the healthcare sector in Europe, but when combined with high levels of environmental innovation, strong environmental governance leads to enhanced efforts to reduce carbon emissions. This combination also contributes to meeting the expectations of a broader range of stakeholders and maintaining legitimacy.

The study’s findings have practical implications for healthcare regulators, policymakers and various stakeholders. It underscores the importance of integrating solid environmental governance and innovation to address climate change challenges in the healthcare sector effectively. This integrated approach not only helps reduce carbon emissions but also contributes to achieving sustainable outcomes while satisfying a wider range of stakeholders.

This study adds to the existing body of knowledge by highlighting the significant role of environmental governance as a moderator in the relationship between environmental innovation and carbon emission in the healthcare industry. The research findings provide valuable insights for academics, practitioners and decision-makers, emphasizing the need to combine governance and innovation for sustainable outcomes in healthcare sectors.

This paper aims to investigate the relationship between information technology (IT) capabilities, information integration and supply chain resilience within the context of a developing country.

Employing a structured questionnaire survey, the study collected cross-sectional data from 205 agro-food processing firms in Uganda, drawn from a sample of 248. The data were subsequently analyzed using SPSS version 27 to validate the hypothesized relationships.

The study findings revealed that IT capabilities and information integration are positively and significantly associated with supply chain resilience. Moreover, it established a positive and significant link between IT capabilities and information integration. The results further revealed both IT capabilities and information integration account for 62.2% of the variance in supply chain resilience (SCRES) in agro-food processing firms in Uganda. Notably, the findings revealed the partial mediating role of information integration, addressing the need to understanding the mechanisms through which IT capabilities influence SCRES.

First, the study used a cross-sectional design which makes it difficult to test causality. Some of the study variables need to be studied over time due to their inherent behavioral elements such as collaboration and information sharing. Hence, future research that could, where possible, collect longitudinal data on the study variables would add value to the findings. Second, the study was limited to agro-food processing firms in Uganda in selected districts of Kampala, Wakiso, Mukono and Jinja. Further research needs to be done in other sectors such as service industry and other geographical locations in Uganda and other developing economies to provide more generality of the findings. Third, the study was based on IT capabilities, information integration and supply chain resilience. There are other variables that affect supply chain resilience such as business continuity planning strategy, interactions between teams within an organization in building resilience, supply chain velocity, system orientation and flexibility among others which can be interesting for further research.

Managers are advised to motivate their IT-related personnel. Efficient use of IT systems by staff, especially who are skillful at self-study, enhances their ability to respond to disruptions accordingly. This enhances SCRES. Additionally, to get feedback from supply chain stakeholders, agro-food processing firms should assess the quality of their supply chain services through using IT capabilities as well as integrating their information.

This study contributes to existing literature by adopting information processing perspective to provide an empirical understanding of IT capabilities and information integration as key resources and capabilities essential for information processing in building SCRES. Furthermore, the study introduces the novel insight of the mediating role of information integration as a pathway in which IT capabilities enhance SCRES in agro-food processing firms in Uganda.

This study aims to develop an experimentally validated three-dimensional numerical model for predicting different flow patterns produced with a gas dynamic virtual nozzle (GDVN).

The physical model is posed in the mixture formulation and copes with the unsteady, incompressible, isothermal, Newtonian, low turbulent two-phase flow. The computational fluid dynamics numerical solution is based on the half-space finite volume discretisation. The geo-reconstruct volume-of-fluid scheme tracks the interphase boundary between the gas and the liquid. To ensure numerical stability in the transition regime and adequately account for turbulent behaviour, the k-ω shear stress transport turbulence model is used. The model is validated by comparison with the experimental measurements on a vertical, downward-positioned GDVN configuration. Three different combinations of air and water volumetric flow rates have been solved numerically in the range of Reynolds numbers for airflow 1,009–2,596 and water 61–133, respectively, at Weber numbers 1.2–6.2.

The half-space symmetry allows the numerical reconstruction of the dripping, jetting and indication of the whipping mode. The kinetic energy transfer from the gas to the liquid is analysed, and locations with locally increased gas kinetic energy are observed. The calculated jet shapes reasonably well match the experimentally obtained high-speed camera videos.

The model is used for the virtual studies of new GDVN nozzle designs and optimisation of their operation.

To the best of the authors’ knowledge, the developed model numerically reconstructs all three GDVN flow regimes for the first time.

The study aims to examine the impact of three types of supply chain integration (SCI) on supply chain flexibility (SCF), investigate the impact of SCF on supply chain performance (SCP) and analyse the indirect impact of SCI on SCP by considering the mediating role of SCF within the manufacturing sector of Jordan.

This study used a quantitative approach to validate the study model. An online self-completed questionnaire was used to gather data from 219 participants from managers in various Jordanian manufacturing firms. SmartPLS software was used to perform structural equation modelling to test the formulated hypotheses.

Based on the findings of the study, firms in Jordan's manufacturing sector would benefit from developing an integrative and flexible supply chain to boost SCP in the present volatile, uncertain, complex and speculative market. In addition, SCP was significantly influenced by investments in supply chain management practices related to SCI and SCF. Moreover, SCF significantly moderated the relationship between SCI and SCP. Thus, SCI and SCF assisted firms in reaching their highest potential performance through increased productivity, decreased expenses and increased satisfaction of their customers.

The study employed a cross-sectional design using SCF as a single construct. Future research should look into the specific type of SCFs that have an immense effect on SCP and how these types are affected by the three types of SCI. Furthermore, future research ought to employ probability sampling techniques to improve the generalizability of results or using a longitudinal data-collection design. Finally, additional research should be conducted to validate the findings of this study by replicating it in other specific industries or countries.

The study fills an identified gap based on previous studies by exploring the linkages between SCI, SCF and SCP in the context of manufacturing sector. Moreover, based on the relational view theory, the study proposed an assessment mechanism for SCP for firms based on the link between three types of SCI and SCF.

The environment in which users acquire medical and health information has changed dramatically, with online health communities (OHCs) emerging as an essential means for accessing health information. It is imperative to comprehend the factors that shape the users' compliance willingness (UCW) to health information in OHCs.

This study adopted the information adoption model (IAM) and theory of planned behavior (TPB) to investigate the influence of argument quality (AQ), source credibility (SC) and subjective norms (SN) on UCW while considering the two types of online health information – mature and emerging treatments. The authors conducted an explanatory-predictive study based on a 2 (treatment types: mature vs. emerging) * 2 (AQ: high vs. low) * 2 (SC: high vs. low) scenario-based experiment, using the partial least squares structural equation modeling (PLS-SEM).

SC positively influences AQ. AQ, SC and SN contribute to information usefulness (IU). These factors positively affect UCW through the mediation of IU. SN were found to improve UCW directly. Moreover, the moderating effect of SC on AQ and IU was more substantial for emerging treatments.

The research model integrates IAM and TPB, considering information types as an additional variable. The approach and findings provide a valuable explanation for UCW to health information in OHCs.

Public–Private Partnerships (PPPs) are crucial to the procurement of global infrastructure projects. Moreover, a price mode based on a cluster of core concessionary items is key to the delivery of value-for-money and successful project outcomes. However, existing research has yet to fully identify PPP concessionary items, nor yet described the range of practical price modes. This study provides taxonomy of core concessionary items impacting PPP projects, systematically classifies price modes, and assesses the applicability and risk impacts of those price modes on PPP projects.

This study adopts a comparative case study method in analyzing core concessionary items and alternative price modes. China is taken as the context, as it is one of the world’s largest PPP markets. In ensuring research validity and reliability, diverse data sources are utilized, with a graphic content analysis tool developed to capture the structure of price modes.

Eight PPP price modes are identified. These are: (1) UP (Unit Price) mode, (2) ALS (Annual Lump Sum) mode, (3) IRR (Internal Rate of Return) mode, (4) RP (Return for Investing Capital (RIC) - Profit Rate of O&M (PROM)) mode, (5) RFP (RIC - Financing Interest Rate (FR) - PROM) mode, (6) RFPL (RIC - FR - PROM - Lower Limit of User Charge (LLoUC)) mode, (7) RFL (RIC - FR - Lump Sum/Fixed Unit Price O&M Contract (LSOM/FUP)) mode, and (8) RFLL (RIC - FR - LSOM/FUP - LLoUC) mode. Other main findings are as follows: (1) Five risk allocation configurations can be achieved via these price modes. Yet while different price modes enable the allocation of specific risks, these do not always align with contracting parties’ original intentions. (2) IRR and RP modes may be less applicable in general because of their vulnerability in allocating critical risks and capacity for spurring opportunistic behavior.

By depicting the paths by which concessionary items in price modes affect cash flow, a systematic analysis of price modes was conducted exposing structural characteristics, along with risk allocation choice implications. The study is unique in: (1) Providing a systematic classification of PPP price modes used in PPP projects, (2) Presenting a comprehensive identification and streamlining of concessionary items in PPP practice, and (3) Analyzing the risk effects of different price modes. Together, these outcomes offer a hitherto unavailable perspective on PPP project risk management. The value of the study lies in the following: (1) Existing studies employ diverse concessionary items, but their applicability varies. This study offers an overarching framework facilitating decision-making in selecting appropriate PPP price modes and in determining concessionary items. (2) This study adds to the understanding of PPP price modes in significant ways that will aid local governments and potential sponsors in crafting and administrating more workable contract designs.

Restaurant operators often use auspicious connotations embedded in the names and shapes of dishes to increase consumers’ purchase intentions. However, the interaction effect of multiple auspicious cues (i.e. food name and shape) on purchase intentions has rarely been examined in the restaurant context. Thus, grounded in processing fluency theory, this study investigates the direct influence of the two-way interaction effect of food name (auspicious vs nonauspicious) and shape (auspicious vs. nonauspicious) on purchase intentions and its indirect influence via perceived auspiciousness and positive emotions.

Utilizing a 2 (food name: auspicious name vs. nonauspicious name) × 2 (food shape: auspicious shape vs. nonauspicious shape) between-subjects design, the authors conducted two experimental studies with 356 Chinese customers. In Study 1, which focused on a main dish, we investigated the two-way interaction effect food name × food shape on purchase intentions. In Study 2, we replicated this experimental study by focusing on a different food type (i.e. dessert) to test the direct and indirect influences of the two-way interaction of food name × food shape on purchase intentions through perceived auspiciousness and positive emotions.

The results reveal that the congruity condition of auspicious names and shapes significantly influences consumers’ purchase intentions. Congruity with auspicious food cues also indirectly affects purchase intentions through consumers’ perceived auspiciousness and positive emotions. These effects were consistently observed in two experimental studies analyzing different dish types (main dish and dessert).

Restaurateurs should consider utilizing auspicious food cues to attract customers. Specifically, they should combine both food name and shape to increase their perceived auspiciousness and sales.

This study tested processing fluency theory using auspicious food cues. This study contributes to the hospitality literature by improving our understanding of the congruence effect by exemplifying the conceptual alignment between food name and food shape.

This paper aims to concentrate on recent innovations in flexible wearable sensor technology tailored for monitoring vital signals within the contexts of wearable sensors and systems developed specifically for monitoring health and fitness metrics.

In recent decades, wearable sensors for monitoring vital signals in sports and health have advanced greatly. Vital signals include electrocardiogram, electroencephalogram, electromyography, inertial data, body motions, cardiac rate and bodily fluids like blood and sweating, making them a good choice for sensing devices.

This report reviewed reputable journal articles on wearable sensors for vital signal monitoring, focusing on multimode and integrated multi-dimensional capabilities like structure, accuracy and nature of the devices, which may offer a more versatile and comprehensive solution.

The paper provides essential information on the present obstacles and challenges in this domain and provide a glimpse into the future directions of wearable sensors for the detection of these crucial signals. Importantly, it is evident that the integration of modern fabricating techniques, stretchable electronic devices, the Internet of Things and the application of artificial intelligence algorithms has significantly improved the capacity to efficiently monitor and leverage these signals for human health monitoring, including disease prediction.

This study aims to improve the maneuverability and stability of four-wheel chassis in a small paddy field; a front axle swing steering four-wheel chassis with optimal steering is designed.

When turning, the front inner wheel stops and the rear inner wheel is in the following state. The hydraulic drive system of the walking wheel adopts a driving mode in which two front-wheel motors are connected in series and two rear wheel motors in parallel. The chassis uses a combination of a gasoline engine with a water cooling system, a CVT continuously variable transmission and a hydraulic drive system to increase the control capability. The front axle rotary chassis adopts a step-less variable speed engine and a hydraulic control system to solve the hydraulic stability of the chassis in uphill and downhill conditions so as to effectively control the over-speed of the wheel-side drive motors. Through the quadratic orthogonal rotation combination design test, the mathematical models of uphill and downhill front-wheel pressures and test factors are established.

The results show that the chassis stability is optimal when the back pressure is 0.5 MPa, and the rotating slope is 4°. The uphill and downhill pressures of the front wheels are 2.38 MPa and 1.5 MPa, respectively.

The influence of external changes on the pressure of hydraulic motors is studied through experiments, which lays the foundation for further research.