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Purpose: The importance of creativity and innovation can’t be overstressed today. Especially in the context of volatility, uncertainty, complexity, and ambiguity (VUCA) world, firms cutting across businesses have to pay special attention to building a culture of creativity and innovation around business processes.

Design/Methodology/Approach: The study uses an extant literature review and practical cases to highlight the parameters required to build a culture of creativity and innovation in companies. These parameters lead to the development of the conceptual framework that can help firms sustain innovation even amidst a fast-changing business environment.

Findings: The findings suggest that focus on internal and external forces is required to keep up innovation efforts in the VUCA world. Being agile with a discrete focus on learning is essential to remain creative and innovative for business sustainability.

Research Limitations/Implications: The study is crucial for academicians, practitioners, and policy makers. It is expected to open new avenues of research for further contributing to the body of knowledge related to the field of creativity and innovation while expected to help society by bringing them more innovative products at pocket-friendly prices.

Originality/Value: The study is unique as it delineates the relationship between creativity and innovation in the context of the VUCA world. The research also offers an innovation framework that is a valuable addition to both fields of academia and corporate.

The purpose of this paper is to improve autonomous flight performance of a fixed-wing unmanned aerial vehicle (UAV) via simultaneous morphing wingtip and control system design conducted with optimization, computational fluid dynamics (CFD) and machine learning approaches.

The main wing of the UAV is redesigned with morphing wingtips capable of dihedral angle alteration by means of folding. Aircraft dynamic model is derived as equations depending only on wingtip dihedral angle via Nonlinear Least Squares regression machine learning algorithm. Data for the regression analyses are obtained by numerical (i.e. CFD) and analytical approaches. Simultaneous perturbation stochastic approximation (SPSA) is incorporated into the design process to determine the optimal wingtip dihedral angle and proportional-integral-derivative (PID) coefficients of the control system that maximizes autonomous flight performance. The performance is defined in terms of trajectory tracking quality parameters of rise time, settling time and overshoot. Obtained optimal design parameters are applied in flight simulations to test both longitudinal and lateral reference trajectory tracking.

Longitudinal and lateral autonomous flight performances of the UAV are improved by redesigning the main wing with morphing wingtips and simultaneous estimation of PID coefficients and wingtip dihedral angle with SPSA optimization.

This paper originally discusses the simultaneous design of innovative morphing wingtip and UAV flight control system for autonomous flight performance improvement. The proposed simultaneous design idea is conducted with the SPSA optimization and a machine learning algorithm as a novel approach.

The paper aims to clarify the distribution of excess pore pressure during cone penetration in two-layered clay and its influence on penetrometer resistance.

An arbitrary Lagrangian–Eulerian scheme is adopted to preserve the quality of mesh throughout the numerical simulation. Simplified methods of layered penetration and coupled pore pressure analysis of cone penetration have been proposed and verified by previous studies. The investigation is then extended by the present work to study the cone penetration test in a two-layered clay profile assumed to be homogeneous with the modified Cam clay model.

The reduction of the range of pore pressure with decreasing PF will cause a decrease of the sensing distance. The PF of the underlying soil is one of the factors that determine the development distance. The interface can be obtained by taking the position of the maximum curvature of the penetrometer resistance curve in the case of stiff clay overlying soft clay. In the case of soft clay overlying stiff clay, the interface locates at the maximum curvature of the penetrometer resistance curve above about 1.6D.

The cone penetration analyses in this paper are conducted assuming smooth soil-cone contact.

A simplified method based on ALE in Abaqus/Explicit is proposed for layered penetration, which solves the problem of mesh distortion at the interface between two materials. The stiffness equivalent method is also proposed to couple pore pressure during cone penetration, which achieves efficient coupling of pore water pressure in large deformations.

This paper aims to present numerical simulations for a series of flight processes for the postlaunching stage of the “balloon-borne UAV system.” It includes the balloon further ascent motion after airborne launching. In terms of unmanned aerial vehicles (UAVs), the tailspin state and the charge-out process with an anti-tailspin parachute-assisted suspending are analyzed. Then, the authors conduct trajectory optimization simulations for the long-distance gliding process.

The balloon kinematics model and the parachute Kane multibody dynamic model are established. Using steady-state tailspin to reduced-order analysis and achieving change-out simulation by parachute suspension dynamic model. A reentry optimization control problem is developed and the Radau pseudo-spectral method is used to calculate the glide trajectory.

The established dynamic model and trajectory optimization method can effectively simulate the motion process of balloons and UAVs. The system mass reduction for launching UAVs will not cause damage to the balloon structure. The anti-tailspin parachute can reduce the UAV attack angles effectively. The UAV can glide to the designated target position by adjusting the attack angle and sideslip angle. The farthest flight distance after launching from 20 km height is 94 km and the gliding time is 40 min, which demonstrates the potential application advantage of high-altitude launching.

The research content and related conclusions of this article achieve a closed-loop analysis of the flight mission chain for the “balloon-borne UAV system,” which provides simulation references for relevant balloon launching experiments.

This paper establishes a complete set of numerical simulation models and can effectively analyze various postlaunching behaviors.

In this paper, the authors aim to study the effect of hydrogen on the pitting corrosion behavior of Incoloy 825, a commonly used material for heat exchanger tubes in hydrogenated heat exchangers.

The pitting initiation and propagation behaviors were investigated by electrochemical and chemical immersion experiments and observed and analyzed by scanning electron microscope and energy dispersive spectrometer methods.

The results show that hydrogen significantly affects the electrochemical behavior of Incoloy 825; the self-corrosion potential decreased from −197 mV before hydrogen charging to −263 mV, −270 mV and −657 mV after hydrogen charging, and the corrosion current density increased from 0.049 µA/cm² before hydrogen charging to 2.490 µA/cm², 2.560 µA/cm² and 2.780 µA/cm² after hydrogen charging. The pitting susceptibility of the material increases.

Hydrogen is enriched on the precipitate, and the pitting corrosion also initiates at that location. The synergistic effect of hydrogen and precipitate destroys the passive film on the metal surface and promotes pitting initiation.

The aim of this paper is to solve the toxic and harmful problems caused by traditional volatile corrosion inhibitor (VCI) and to analyze the effect of the layered structure on the enhancement of the volatile corrosion inhibition prevention performance of amino acids.

The carbon dots-montmorillonite (DMT) hybrid material is prepared via hydrothermal process. The effect of the DMT-modified alanine as VCI for mild steel is investigated by volatile inhibition sieve test, volatile corrosion inhibition ability test, electrochemical measurement and surface analysis technology. It demonstrates that the DMT hybrid materials can improve the ability of alanine to protect mild steel against atmospheric corrosion effectively. The presence of carbon dots enlarges the interlamellar spacing of montmorillonite and allows better dispersion of alanine. The DMT-modified alanine has higher volatilization ability and an excellent corrosion inhibition of 85.3% for mild steel.

The DMT hybrid material provides a good template for the distribution of VCI, which can effectively improve the vapor-phase antirust property of VCI.

The increased volatilization rate also means increased VCI consumption and higher costs.

Provides a new way of thinking to replace the traditional toxic and harmful VCI.

For the first time, amino acids are combined with nano laminar structures, which are used to solve the problem of difficult volatilization of amino acids.

This study aims to investigate the daily performance of the proposed microgrid (MG) that comprises photovoltaic, wind turbines and is connected to the main grid. The load demand is a residential area that includes 20 houses.

The daily operational strategy of the proposed MG allows to vend and procure utterly between the main grid and MG. The smart metre of every consumer provides the supplier with the daily consumption pattern which is amended by demand side management (DSM). The daily operational cost (DOC) CO2 emission and other measures are utilized to evaluate the system performance. A grey wolf optimizer was employed to minimize DOC including the cost of procuring energy from the main grid, the emission cost and the revenue of sold energy to the main grid.

The obtained results of winter and summer days revealed that DSM significantly improved the system performance from the economic and environmental perspectives. With DSM, DOC on winter day was −26.93 ($/kWh) and on summer day, DOC was 10.59 ($/kWh). While without considering DSM, DOC on winter day was −25.42 ($/kWh) and on summer day DOC was 14.95 ($/kWh).

As opposed to previous research that predominantly addressed the long-term operation, the value of the proposed research is to investigate the short-term operation (24-hour) of MG that copes with vital contingencies associated with selling and procuring energy with the main grid considering the environmental cost. Outstandingly, the proposed research engaged the consumers by smart meters to apply demand-sideDSM, while the previous studies largely focused on supply side management.

Reducing the number of generated mutants by clustering redundant mutants, reducing the execution time by decreasing the number of generated mutants and reducing the cost of mutation testing are the main goals of this study.

In this study, a method is suggested to identify and prone the redundant mutants. In the method, first, the program source code is analyzed by the developed parser to filter out the effectless instructions; then the remaining instructions are mutated by the standard mutation operators. The single-line mutants are partially executed by the developed instruction evaluator. Next, a clustering method is used to group the single-line mutants with the same results. There is only one complete run per cluster.

The results of experiments on the Java benchmarks indicate that the proposed method causes a 53.51 per cent reduction in the number of mutants and a 57.64 per cent time reduction compared to similar experiments in the MuJava and MuClipse tools.

Developing a classifier that takes the source code of the program and classifies the programs' instructions into effective and effectless classes using a dependency graph; filtering out the effectless instructions reduces the total number of mutants generated; Developing and implementing an instruction parser and instruction-level mutant generator for Java programs; the mutant generator takes instruction in the original program as a string and generates its single-line mutants based on the standard mutation operators in MuJava; Developing a stack-based evaluator that takes an instruction (original or mutant) and the test data and evaluates its result without executing the whole program.

The psychological foundations of consumers’ reasons for product choices are analyzed in the field of marketing. The purpose of this research is to identify the implicit reasons for white meat consumption in the UK and Turkey.

In the scope of the means-end chain theory, in-depth interviews were conducted with individuals, and the reasons for consumers’ product preferences were revealed by moving from concrete to abstract.

It has been determined that the white meat consumption of Muslims in the UK is primarily shaped by their religious approach. In Turkey, on the contrary, both consumption patterns and reasons for preference are changing. It has been found that white meat consumption is associated with values such as security needs, satisfaction with life, self-fulfillment and happiness.

This research has contributed to the marketing literature by examining consumers’ implicit consumption reasons for white meat in the context of religion and culture.

Marketing strategies should focus on building trust in halal certification, particularly in the UK. Brands should associate their promotion strategies with feelings of security and happiness, which are associated in the minds of consumers.

This study is a new study in terms of revealing the connotations of consumers about consuming chicken and fish and showing the implicit needs that the brands can emotionally associate with.

The purpose of this paper is to investigate the impact of the COVID-19 pandemic on doctoral education. Pandemics throughout history have generated new educational theories and practices, accelerated some trends and signalled the abrupt end of others. The unpredictable effects of the COVID-19 pandemic have particularly impacted upon First Nations and transcultural communities and People of Colour throughout the globe. A second significant recent global trend that occurred at the height of the pandemic was the reignited #BlackLivesMatter (#BLM) protest campaign. This campaign drew attention to the vast inequities faced by black, transcultural (migrant, refugee, culturally diverse and international) and Indigenous peoples and triggered rapid action in higher education institutions against racism and unconscious bias.

This conceptual paper draws upon postcolonial/decolonial theory to demonstrate how the COVID pandemic and #BLM movement prompts us to revitalise doctoral education.

These two issues have created renewed urgency around the need to decolonise higher education and a desire to transform the “business-as-usual” geopolitical power dynamics that continue to privilege Northern knowledge over culturally diverse knowledge systems from First Nations and transcultural contexts. A key site where special opportunities exist to effect this transformation lies in doctoral education. Doctoral education is a significant location of new knowledge creation and the development of the world’s future researchers.

Applying post/decolonial theory enables one to rethink how doctoral education should be changed to work towards greater decolonisation.

This study applies Santos’ ideas about “the sociologies of emergence” in the global South to think about how doctoral education should be reconstructed as a liberated zone of decolonisation and epistemic justice.