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Cotton soliton is a newly introduced notion in the field of Riemannian manifolds. The object of this article is to study the properties of this soliton on certain contact metric manifolds.

The authors consider the notion of Cotton soliton on almost Kenmotsu 3-manifolds. The authors use a local basis of the manifold that helps to study this notion in terms of partial differential equations.

First the authors consider that the potential vector field is pointwise collinear with the Reeb vector field and prove a non-existence of such Cotton soliton. Next the authors assume that the potential vector field is orthogonal to the Reeb vector field. It is proved that such a Cotton soliton on a non-Kenmotsu almost Kenmotsu 3-h-manifold such that the Reeb vector field is an eigen vector of the Ricci operator is steady and the manifold is locally isometric to.

The results of this paper are new and interesting. Also, the Proposition 3.2 will be helpful in further study of this space.

Venture capital and private equity.

This case is suitable for II MBA/Executive MBA (venture capital and private equity/entrepreneurship/business models/managing family business) courses.

Soliton is a technology and software services company with operations in India and the USA providing machine vision products and virtual instrumentation services. Soliton was started by Ganesh Devaraj in 1998 after his return from the United States after higher studies. Ganesh hails from a business family in Coimbatore that had interests in the textile spinning sector. The family had been in the textile business since the early 1940s and had revenues of Rs 400 million and employed about 700 people. Ganesh, not wanting to continue in the traditional family business, ventured into the technology sector using his academic and professional experience. His family was supportive of his venture and funded his company for the first two years of operation and for scaling up operations. Ganesh is now evaluating various sources of raising additional capital at a time when there was general slowdown in the automobile sector as a result of the global financial crisis.

The goal of this case study is to illustrate the complexities that exist in financing growth of companies in uncertain times. This following are the expected learning outcomes: discuss and understand the nuances between different sources of early stage funding: personal wealth, family, and angels; compare and contrast the differences between family funding and venture funding; and highlight the benefits and limitations of family funding.

Teaching notes are available.

This study investigates the impacts of the Russia–Ukraine conflict on the cross-correlation between agricultural commodity prices and crude oil prices.

The authors used MultiFractal Detrended Fluctuation Cross-Correlation Analysis (MF-X-DFA) to explore the correlation behavior before and during conflict. The authors analyzed the price connections between future prices for crude oil and agricultural commodities. Data consists of daily futures price returns for agricultural commodities (Corn, Soybean and Wheat) and Crude Oil (Brent) traded on the Chicago Mercantile Exchange from Aug 3, 2020, to July 29, 2022.

The results suggest that cross-correlation behavior changed after the conflict. The multifractal behavior was observed in the cross correlations. The Russia–Ukraine conflict caused an increase in the series' fractal strength. The study findings showed that the correlations involving the wheat market were higher and anti-persistent behavior was observed.

The study was limited by the number of observations after the Russia–Ukraine conflict.

This study contributes to the literature that investigates the impact of the Russia–Ukraine conflict on the financial market. As this is a recent event, as far as we know, we did not find another study that investigated cross-correlation in agricultural commodities using multifractal analysis.

Flow induced by rotating disks is of great practical importance in several engineering applications such as rotating heat exchangers, turbine disks, pumps and many more. The present research has been freshly displayed regarding the implementation of an engine oil-based Casson tri-hybrid nanofluid across a rotating disk in mass and heat transferal developments. The purpose of this study is to contemplate the attributes of the flowing tri-hybrid nanofluid by incorporating porosity effects and magnetization and velocity slip effects, viscous dissipation, radiating flux, temperature slip, chemical reaction and activation energy.

The articulated fluid flow is described by a set of partial differential equations which are converted into one set of higher-order ordinary differential equations (ODEs) by using convenient conversions. The numerical solution of this transformed set of ODEs has been spearheaded by using the effectual bvp4c scheme.

The acquired results show that the heat transmission rate for the Casson tri-hybrid nanofluid is intensified by, respectively, 9.54% and 11.93% when compared to the Casson hybrid nanofluid and Casson nanofluid. Also, the mass transmission rate for the Casson tri-hybrid nanofluid is augmented by 1.09% and 2.14%, respectively, when compared to the Casson hybrid nanofluid and Casson nanofluid.

The current investigation presents an educative response on how the flow profiles vary with changes in the inevitable flow parameters. As per authors’ knowledge, no such scrutinization has been carried out previously; therefore, our results are novel and unique.

The effective prediction of crude oil futures prices can provide a reference for relevant enterprises to make production plans and investment decisions. To the nonlinearity, high volatility and uncertainty of the crude oil futures price, a matrixed nonlinear exponential grey Bernoulli model combined with an exponential accumulation generating operator (MNEGBM(1,1)) is proposed in this paper.

First, the original sequence is processed by the exponential accumulation generating operator to weaken its volatility. The nonlinear grey Bernoulli and exponential function models are combined to fit the preprocessed sequence. Then, the parameters in MNEGBM(1,1) are matrixed, so the ternary interval number sequence can be modeled directly. Marine Predators Algorithm (MPA) is chosen to optimize the nonlinear parameters. Finally, the Cramer rule is used to derive the time recursive formula.

The predictive effectiveness of the proposed model is verified by comparing it with five comparison models. Crude oil futures prices in Cushing, OK are predicted and analyzed from 2023/07 to 2023/12. The prediction results show it will gradually decrease over the next six months.

Crude oil futures prices are highly volatile in the short term. The use of grey model for short-term prediction is valuable for research. For the data characteristics of crude oil futures price, this study first proposes an improved model for interval number prediction of crude oil futures prices.

The purpose of this paper is to examine the volatility spillover and lead-lag relationship between the Chicago Board Options Exchange volatility index (VIX) and the major agricultural future markets before and during the Coronavirus disease 2019 (COVID-19) outbreak.

The methods used were the vector autoregression-Baba, Engle, Kraft and Kroner-generalized autoregressive conditional heteroskedasticity method, the Wald test and wavelet transform method.

The findings indicate that prior to the COVID-19 outbreak, there was a two-way volatility spillover impact between the majority of the sample markets. In comparison, volatility transmission between the VIX index and the agricultural future market was significantly lower following the COVID-19 outbreak, the authors observed greater coherence at higher frequencies than at lower frequencies, implying that the interdependence between the two VIX indices and the agricultural future market was stronger over a longer time-frequency domain and the VIX’s signalling effect on various agricultural future prices after the COVID-19 outbreak was significantly lower.

The authors conducted the first comprehensive investigation of the VIX’s correlation with major agricultural futures, especially during COVID-19. The findings contribute to a better understanding of the risk transmission mechanism between the VIX and major agricultural commodities futures contracts. And our findings have significant implications for investors and portfolio managers, as well as for policymakers who are concerned about the price of agricultural futures.

The outbreak of the Covid-19 pandemic has tested the resilience of the construction industry, putting the safety of workers and overall businesses at risk. This study aims to explore the different strategies adopted by construction companies to protect the health and well-being of employees, security of the construction sites and projects, and keep the overall business operational amid the Covid-19 pandemic.

A preliminary study that involves field study and survey research was used to collect data for the study. The results from the preliminary analysis served as inputs for constructing the questionnaire, which was analyzed using descriptive statistics, exploratory factor analysis and reliability analysis.

The results reveal that the key underlying measures put in place by construction businesses include restricted site access, support bubbling of office and site staff, enhanced hygiene and social distancing protocol, contract risk identification and mitigation, self-isolation measures and heightened construction site safety. Along with a further discussion of the underlying measures, the top-rated strategies that were adopted by construction firms are also discussed in the paper.

As many construction companies remained opened handling essential projects amid the pandemic, the study presents the effective and efficient strategies that were used in plowing through the trying times. This study provides the opportunity for construction companies that escaped the early impacts of Covid-19 due to site closure and policymakers to learn from the strategies adopted by construction companies that were operational amid the pandemic.

Predicting commodity futures trading volumes represents an important matter to policymakers and a wide spectrum of market participants. The purpose of this study is to concentrate on the energy sector and explore the trading volume prediction issue for the thermal coal futures traded in Zhengzhou Commodity Exchange in China with daily data spanning January 2016–December 2020.

The nonlinear autoregressive neural network is adopted for this purpose and prediction performance is examined based upon a variety of settings over algorithms for model estimations, numbers of hidden neurons and delays and ratios for splitting the trading volume series into training, validation and testing phases.

A relatively simple model setting is arrived at that leads to predictions of good accuracy and stabilities and maintains small prediction errors up to the 99.273th quantile of the observed trading volume.

The results could, on one hand, serve as standalone technical trading volume predictions. They could, on the other hand, be combined with different (fundamental) prediction results for forming perspectives of trading trends and carrying out policy analysis.

This study aims to explore entropy evaluation in the bi-directional flow of Casson hybrid nanofluids within a stagnated domain, a topic of significant importance for optimizing thermal systems. The aim is to investigate the behavior of unsteady, magnetized and laminar flow using a parametric model based on the thermo-physical properties of alumina and copper nanoparticles.

The research uses boundary layer approximations and the Keller-box method to solve the derived ordinary differential equations, ensuring numerical accuracy through convergence and stability analysis. A comparison benchmark has been used to authenticate the accuracy of the numerical outcomes.

Results indicate that increasing the Casson fluid parameter (ranging from 0.1 to 1.0) reduces velocity, the Bejan number decreases with higher bidirectional flow parameter (ranging from 0.1 to 0.9) and the Nusselt number increases with higher nanoparticle concentrations (ranging from 1% to 4%).

This study has limitations, including the assumption of laminar flow and the neglect of possible turbulent effects, which could be significant in practical applications.

The findings offer insights for optimizing thermal management systems, particularly in industries where precise control of heat transfer is crucial. The Keller-box simulation method proves to be effective in accurately predicting the behavior of such complex systems, and the entropy evaluation aids in assessing thermodynamic irreversibilities, which can enhance the efficiency of engineering designs.

These findings provide valuable insights into the thermal management of hybrid nanofluid systems, marking a novel contribution to the field.

Gamification unlocks unprecedented opportunities in healthcare, wellness and lifestyle context. In this scenario, by leveraging on such an approach, information technologies now enabled gamification-based mobile applications primarily employed in health and wellness contexts, focusing on areas such as disease prevention, self-management, medication adherence and telehealth programs. The synergistic integration of gamification-based methodologies in conjunction with the utilization of digital tools, (e.g. as for Internet of Things, mobile applications) for the realm of digital therapeutics (DTx), thus unveiled powerful approaches and paradigms, yielding innovative applications that, through the harnessing of sensors and software-based systems, transform healthcare maintenance, wellness and lifestyle into an engaging pursuit, as a game. This paper explores the factors influencing individuals' intention to autonomously utilize mobile gamification-based apps for self-care and wellness maintenance.

Through explorative research designs an experiment has been conducted among a sample of 376 participants regarding the use of a fictitious gamification-based DTx solution, consisting in a mobile app namely “Health'n’Fit”.

Findings from an experiment conducted with a sample of 460 participants shed light on the possible antecedents and consequents of gamification. Results of the SEM model indicate that customization (CU), trust (TR), mobility (MO) and social value (SV) are the main determinants, although at a different extent of the playful experience; Moreover, gamification positively impacts attitudes and, in turn, perceived usefulness, intention to use and behavioral intentions.

This paper offers a dual-pronged approach that holds practical significance in the realm of healthcare innovation. First, the authors delve into the antecedents shaping individuals' intention to engage with gamification-based DTx, unraveling the factors that influence user adoption. Beyond this, the authors extend their focus to the realm of healthcare service design. By harnessing the potential of gamification and technology, the authors illuminate pathways to conceptualize and create novel healthcare services. This work not only identifies the building blocks of user engagement but also serves as a guide to innovatively craft healthcare solutions that leverage this amalgamation of technology and gamification, contributing to the evolution of modern healthcare paradigms.

In a social context, the paper introduces pioneering technological synergies that merge gamification and DTx to enhance individuals' health and wellness maintenance. By proposing innovative combinations, the authors present novel avenues for promoting healthier lifestyles and behavior change. This not only underscores the potential of technology to positively impact individuals but also highlights the significance of aligning technological advancements with societal well-being. As the research advocates for these innovative solutions, it reinforces the importance of collaborative technological and marketing endeavors, ultimately contributing to the betterment of society as a whole.

This is the first paper exploring the combined effect of gamification and DTx, by shedding light on the peculiarities of both the antecedents of individuals' intention to use such combined technologies.