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It is currently difficult to measure temperature and pressure in harsh environments. Such measurements are limited by either the ability of the sensing element or the associated electrical wiring to withstand the operating environment. This is unfortunate as temperature and pressure are important measurands in various engineering structures as they provide critical information on the operating condition of the structure. Hence, there is a need to address this shortcoming. Such a sensor in place would enhance the operating efficiency thereby reducing the pollution burden and its impact on the environment. The purpose of this paper is to present theoretical and preliminary experimental results for a co‐integrated pressure and temperature sensor for harsh environments.

This work describes a co‐integrated pressure‐temperature wireless sensing scheme. The approach presented herein provides the possibility of measuring dynamic pressure and temperature within an enclosed volume using acoustic signals. Resonance tube physics is exploited for the temperature sensing. A microphone is used to obtain the acoustic signal whose frequency is a function of the temperature and the tube geometry.

The dynamic pressure is measured from the calibrated amplitude of the pressure wave signal measured by the microphone. The temperature can be measured through the shift of the standing wave frequency with a resolution of <1°C. The resonance tube can be fabricated using any material that resists harsh environments. The geometry of the tube can be tailored for any specific frequency range, as the application warrants. Also, this provides a means for accurate temperature compensation of pressure sensor data from high temperature environments. A Matlab/Simulink model is developed and presented for the acquisition of acoustic signals through the wall of an enclosed volume. For these applications the standing wave signal transmitted through the enclosure wall becomes a function of the wall material and wall thickness. Preliminary experimental results are presented in which a DC fan is used for generating the dynamic pressure in a varying temperature environment.

The major issue is the separation of the noise from the signal. As various applications yield specific signal noise, the problem needs detailed data to be addressed.

Temperature and dynamic pressure could be recorded/monitored in very harsh environment conditions such as chemical reactors.

This work demonstrates the possibility of employing a co‐integrated acoustic sensing scheme in which both pressure and temperature are measured simultaneously with a sole sensor. The major advantage with acoustic sensing is the wireless transmission of data. This allows for non‐invasive measurement from within enclosed systems. Direct real‐time temperature compensation is possible that does not require any compensation circuitry. Hence, pressure and temperature data may be obtained from caustic operating environments whose access is otherwise not feasible.

The purpose of this paper is to review the diversified existing literature on tourism and carbon emissions using bibliometric analysis to churn down the multiple studies under one paper, which not only provides insights into the evolution and progress of the research area but also sets the future research agenda.

The study adopted the Scientometrics review methodology based on the bibliometric analysis. Bibliometric analysis is conducted through the following techniques, namely, citation analysis, thematic mapping, country collaboration, co-citation analysis and co-occurrence of keywords with the help of R-based bibliometrix and visualization of similarities (VOS) viewer open-source software.

The study identified the most prominent authors, studies, journals, affiliations and countries in the field of sustainable tourism, as well as the most co-cited authors and journals, based on a bibliometric analysis of 398 research papers retrieved from the Scopus database during the past three decades (1990–2021). Moreover, some of the relevant themes identified by the authors are energy use and carbon dioxide (CO₂) emission of the tourism sector, economic impacts of tourism and CO₂ emissions and CO₂ emissions and carbon tax.

The outcome of the selected studies is a unique contribution to the field of sustainable tourism as it is one of the first known studies to review tourism and carbon emissions. It provides in-depth bibliometric analysis of articles and identification of the important research trends.

The purpose of this paper is to investigate the effect of health-care service quality (HCSQ) dimensions on patient satisfaction and behavioural intentions in selected corporate hospitals from South India.

Based on Parasuraman et al.’s SERVQUAL variables, the study tried to identify the effects of each variable to patient satisfaction and behavioural intentions. Data were collected through systematic random sampling among 500 in-patients of corporate hospitals with minimum four days stay were considered for the in-patients’ sample. Structural equation modelling technique was used to investigate the effect of HCSQ dimensions on patient satisfaction and behavioural intention.

The findings suggest that in addition to “patient satisfaction”, the only HCSQ dimension that directly affects behavioural intention is “empathy”. In addition, “empathy” affects “responsiveness”, “assurance” and “tangibles” which, in turn, have only an indirect effect to behavioural intention through “patient satisfaction”.

This research investigated the HCSQ dimensions effects on patient satisfaction and behavioural intention from the perspective of patients and corporate hospitals run by the private players. This paper contributes to the body of academic knowledge by shedding more light into the role of HCSQ dimensions, and especially “empathy”, in the intentions for corporate hospital patients.

An understanding of the direct and indirect effect of HCSQ dimensions on patient satisfaction and behavioural intentions is important to corporate hospital marketing managers because it offers them the opportunity to take certain actions for improving patients’ satisfaction and these actions increase their intention to revisit.

The paper manages to investigate the effects of HCSQ dimensions on patient satisfaction and behavioural intention, especially in the health-care marketing sector.

This paper documents a robust empirical regularity: higher trade openness is associated with a lower unemployment rate. This paper also examines whether or not the effects of trade liberalisation depend on countries' income levels. Further, the dynamic causation between trade openness and unemployment is also examined.

In order to obtain insight into the openness–unemployment nexus, following empirical methods were utilised - static panel models, dynamic panel models and a novel panel Granger causality approach proposed by Juodis et al. (2021).

Results suggest that openness negatively affects unemployment; the extent to which trade liberalisation affects unemployment depends on the income level of each country. The Juodis, Karavias, and Sarafidis (JKS) test confirmed that the past values of trade openness, inflation, foreign direct investment and gross domestic product per capita contain information that helps to predict unemployment in a more robust manner. To simply put, opening upto trade may eventually become a requirement for creating more job opportunities, but this alone may not be enough. The extent to which nations benefit from trade liberalisation is largely dependent on the overall economic conditions and their capability to move up the income scale.

A major difference between this study and those performed previously is that this study does not only examine the impact of trade openness on unemployment, but also investigates whether the unemployment effect of liberalisation is affected by countries' income levels – an issue that has received little attention in the past. Additionally, the unique panel non-causality approach put forth by Juodis et al. (2021) is used in the first instance to look into the causal link between trade openness and unemployment. This method has advantages in that the method enables capturing Granger-causality in homogeneous or heterogeneous panels amongst multiple variables.

This review paper delves into the comprehensive understanding of Ashwagandha, spanning its botanic occurrence, conventional applications, extraction techniques and pivotal role in addressing various disorders.

Introduction Ashwagandha, also known as Withania somnifera, is a remarkable botanical resource with a rich history of use in traditional medicine.

In botany, Withania somnifera thrives in diverse ecosystems, particularly in tropical and subtropical regions. Its extensive distribution across regions, the Canary Islands, South Africa, the Middle East, Sri Lanka, India and China underscores its adaptability and resilience. The traditional uses of Ashwagandha in Ayurvedic and indigenous medicine systems have persisted for over 3,000 years. With over 6,000 plant species utilized historically, India, often regarded as the “botanical garden of the world,” has firmly established Ashwagandha as a cornerstone in traditional healing practices.

Extraction methods play a pivotal role in harnessing the therapeutic potential of Ashwagandha. Ultrasonic-assisted extraction and high-performance liquid chromatography are among the techniques employed to obtain the key bioactive compounds. Ashwagandha’s significance in modern medicine is underscored by its potential to address a spectrum of health issues. The multifaceted bioactivity of Ashwagandha is attributed to its antioxidant, anti-inflammatory, heart conditions, metabolic disorders, renal ailments, hepatic diseases and adaptogenic properties, making it a subject of increasing interest in contemporary medical research. This review synthesizes the assorted perspectives of Ashwagandha, from its botanical roots and conventional employments to its advanced extraction strategies and its intention to basic well-being challenges, advertising important bits of knowledge for analysts, specialists and healthcare experts alike.

Designing a sustainable bituminous concrete with long-term performance is a challenging problem. In addition, strength of the subgrade has a crucial impact on pavement design. This paper aims to concentrate on subgrade soil stabilization with granite dust powder (GDP) and crumb rubber powder (CRP) to improve the engineering properties of the soil. Further design of bituminous concrete pavement with cement-treated layers in base and subbase course layers was carried out with life cycle cost analysis and life cycle assessment for 1 km of a four-lane national highway.

Subgrade soil stabilized with GDP and CRP is characterized as per Indian Standards (IS)-2720 to determine the optimum dosage. Further, the mechanistic-empirical pavement design was carried out using Indian Road Congress-37 (2018), analyzed using IITPAVE software and validated with ANSYS software. The life cycle cost analysis is carried out using the net present value method, and the life cycle assessment is performed according to the cradle-to-grave approach.

A soil mix comprising 10% GDP and 2.5% CRP yielded a soaked California bearing ratio value of 6.58%. In addition, the design of bituminous concrete pavement with cement-treated granular layers showed a 26.9% reduction in life cycle cost and 59.4% reduction in total carbon footprint per kilometer compared to the pavement with traditional aggregate layers.

The research on subgrade stabilization with sustainable materials like GDP and CRP incorporating mechanistic empirical pavement design, life cycle cost analysis and life cycle assessment is limited. Overall, the study recommends the use of GDP and CRP to stabilize soil for subgrade application and incorporate cement-treated granular layers, which offer economic and environmental benefits compared to traditional pavement construction.

The requirement of high-quality government-supported healthcare services has necessitated the significance of recognizing new management practices to enhance patient satisfaction. Hence, the purpose of this study is to address the patient's enhanced custom needs through the implementation of supply chain value stream mapping (SCVSM) in government-supported drug distribution system (DDS) for enhanced patient's satisfaction.

This study elucidates the role of one popular emerging management technique (i.e. SCVSM) in the healthcare sector by an investigative case study. The DDS in Rajasthan (India) was selected for this study. The data for this analysis were gathered in three ways (i.e. direct observation, documentary analysis and semi-structured interviews).

The outcome of this current study reveals that it is possible to apply the tool (SCVSM) to investigate the wastes in DDS to deliver the medicines at right time, right quantity and right quality. The application of SCVSM concluded that the various Kaizens (areas needed to improve) in lead time; transportation and routing should be adopted. The study further implemented kaizen on the current SCVSM and developed future SCVSM.

Although various stages and functions exist in the healthcare supply chain, the current study is focused on the distribution system of drugs. The proposed approach provides a platform for both researchers and academicians to understand the existing DDS and to implement the SCVSM approach in the healthcare environment. The results show that the proposed SCVSM model is able to identify some operational bottlenecks and wastes which interfere in DDS.

It was observed that limited literature related to lean implementation on DDS and implementation of SCVSM on the healthcare environment in general and government-supported or public in specific are available. The current study on the application of SCVSM in DDS is unique in nature and will definitely add value to the existing literature of the application of value stream mapping (VSM) on the healthcare supply chain management field.

The purpose of this paper is to study the leadership style (LS) and decision-making style (DMS) of Indian manufacturing executives, and to explore the association between the LS and DMS.

For this study the sample was drawn from Indian manufacturing organisations’ executives from both public and private sectors. The respondents were lower, middle and senior levels executives involved in leadership and decision-making functions. Correlation, regression and ANOVA were used to pursue the research questions.

Indian manufacturing executives have shown highest rational and least avoidant in their DMSs. Transformational (TFM) leaders are found rational, while the transactional (TSL) leaders are observed to be rational and dependent. Laissez faire style has correlation with avoidant decision making and interactive dependent and avoidant styles.

The study is a cross sectional research with limitations of self-serving bias and common method variance. However, this limitation has been dealt with a statistical test.

The study bears significant implications for Indian executives who are working on LSs and decision making. It also provides the details of decision-making behaviours of the manufacturing executives thereby suggesting the associated benefits and drawbacks of particular styles.

This paper contributes to leadership and decision-making literature. In the recent times, no such study in Indian manufacturing context have been reported. Moreover there are few contrasting and contributing findings in this research.