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In this article, we introduce two new classes of analytic functions Jtanh and JSG which are associated with the activation functions and defined by the ratio of analytic representations of convex and starlike functions. For functions in these classes, our primary goal is to determine the sharp upper bounds of second and third Hankel determinants.

The literature on open innovation (OI) has mainly been focused on the 'bright side' of OI, thus neglecting the limits of OI implementation influencing innovation processes during organizational change. It requires to develop a better understanding about the limits of OI. Therefore, this study explores the limits of OI during organizational change and provides approaches that drive firms to offset these limits. The empirical analysis is based on an in‐depth single case study and data was collected through semi‐structured interviews with the representatives engaged with Partner Campus – an OI initiative developed by a multinational manufacturing company. We have found that during the change process of adapting collaborative and absorptive capabilities, and developing organizational readiness, several internal and external challenges limit the company's drive to open up. Internal challenges arise when organizations start the change process in unfreezing stage. The traditional organizational culture and structure challenge incumbent firms to break the existing silos and utilize knowledge and resources effectively for OI implementation, hindering intra‐organizational collaboration. While external challenges arise when organizations transform their endeavors across organizational boundaries and collaborate with external stakeholders. When firms lack knowledge integration and technological capabilities, OI creates collaborative complexity given the magnitude of involved diverse actors and activities at different levels, which challenges the organizations to maintain the longevity of OI practices, resulting in several risks that limit firms to open up. However, we have identified the capabilities and actions that firms can take to strengthen a collaborative environment by counterbalancing these challenges. We contribute to the literature on OI by identifying and assessing the limits of OI, embedded in the organizational change process, that hinder organizational drive for OI. We also contribute to organizational change literature by identifying specific changes related to organizational processes, structure, and culture, and outlining approaches that can support a smooth transition. [ABSTRACT FROM AUTHOR]

In this article, the present study employs the utilization of the concepts pertaining to (x,y)-symmetrical functions, Janowski type functions, and q-calculus in order to establish a novel subclass within the open unit disk. Specifically, we delve into the examination of convolution properties, which serve as a tool for investigating and inferring adequate and equivalent conditions. Moreover, we also explore specific characteristics of the class S˜qx,y(α,β,λ), thereby further scrutinizing the convolution properties of these newly defined classes.

This study describes the synthesis, characterization, and biological activities of halogenated xanthone, 3-O substituted xanthone, and prenylated xanthone derivatives. The molecular structures of these compounds were identified using 1H NMR, 13C NMR, 2D NMR, FTIR and DIMS. All synthesized compounds were evaluated against two cancer cell lines: breast adenocarcinoma MCF-7 and MDA-MB-231 by application of the MTT assay. With this approach, xanthones 9 and 13 were identified as putative aromatase activating agents through the inhibition of interactions with MCF-7 and MDA-MB-231. The selected compounds, 9 and 13, were further examined for toxicity against the African Green Monkey Kidney cell (VERO) and Non-tumorigenic Lung Epithelial cell lines (BEAS-2B). In addition, in-silico docking studies were conducted to estimate the binding poses and residues implicated in probable MCF-7 and MDA-MB-231 interactions.

One of the challenging tasks in the study of function theory is how to obtain sharp estimates of coefficients that appear in the Taylor–Maclaurin series of analytic univalent functions, and for obtaining these bounds, researchers used the concepts of Carathéodory functions. Among these coefficient-related problems, the problem of the third-order Hankel determinant sharp bound is the most difficult one. The aim of the present study is to determine the sharp bound of the Hankel determinant of third order by using the methodology of the aforementioned Carathéodory function family. Further, we also study some other coefficient-related problems, such as the Fekete–Szegő inequality and the second-order Hankel determinant. We examine these results for the family of bounded turning functions linked with a cardioid-shaped domain.

In numerous geometric and physical applications of complex analysis, estimating the sharp bounds of coefficient-related problems of univalent functions is very important due to the fact that these coefficients describe the core inherent properties of conformal maps. The primary goal of this paper was to calculate the sharp estimates of the initial coefficients and some of their combinations (the Hankel determinants, Zalcman’s functional, etc.) for the class of symmetric starlike functions linked with the sigmoid function. Moreover, we also determined the bounds of second-order Hankel determinants containing coefficients of logarithmic and inverse functions of the same class.

The coefficient problem is an essential topic in the theory of univalent functions theory. In the present paper, we consider a new subclass SQ of analytic functions with f′(z) subordinated to 1/(1−z)2 in the open unit disk. This class was introduced and studied by Răducanu. Our main aim is to give the sharp upper bounds of the second Hankel determinant H2,3f and the third Hankel determinant H3,1f for f∈SQ. This may help to understand more properties of functions in this class and inspire further investigations on higher Hankel determinants for this or other popular sub-classes of univalent functions.

One of the most important problems in the study of geometric function theory is knowing how to obtain the sharp bounds of the coefficients that appear in the Taylor–Maclaurin series of univalent functions. In the present investigation, our aim is to calculate some sharp estimates of problems involving coefficients for the family of convex functions with respect to symmetric points and associated with a hyperbolic tangent function. These problems include the first four initial coefficients, the Fekete–Szegö and Zalcman inequalities, and the second-order Hankel determinant. Additionally, the inverse and logarithmic coefficients of the functions belonging to the defined class are also studied in relation to the current problems.

Some geometric properties of a certain univalent function in the unit disk are considered in this work and the results extend some known results in the literature.

Abstract New exact solutions of the space–time conformable Caudrey–Dodd–Gibbon (CDG) equation have been derived by implementing the conformable derivative. The generalized Riccati equation mapping method is applied to figure out twenty-seven forms of exact solutions, which are soliton, rational, and periodic ones. Also, for some suitable values of parameters, the exact solutions are found, namely dark, bell type, periodic, soliton, singular soliton, and several others, by using the conformable derivative. These types of solutions have not been proclaimed so far. 2D and 3D graphical patterns of some solutions are also given for clarification of physical features. The conformable derivative is one of the excellent choices to solve the nonlinear conformable problems arising in theory of solitons and many other areas. The results are new and very interesting for the large community of researchers working in the field of mathematics and mathematical physics.

In this paper, a unique decomposition technique is implemented along with an auxiliary function for the best implementation. Some new and efficient techniques are introduced and analyzed for nonlinear equations. These techniques are higher ordered in approaching to the root of nonlinear equations. Some existing classical methods such as the Newton method, Halley method, and Traub's approach and their various modified forms are the special cases of these newly purposed schemes. These new iterative schemes are a good addition in existing methods and are also a comprehensive and generalized form for finding the solution of nonlinear equations.

Various problems of pure and applied sciences can be studied in the unified framework of nonlinear equations. In this paper, a new family of iterative methods for solving nonlinear equations is developed by using a new decomposition technique. The convergence of the new methods is proven. For the implementation and performance of the new methods, some examples are solved and the results are compared with some existing methods.

The main concern is to explore an electro-magneto hydrodynamic (EMHD) squeezing flow of Ag-Fe3O4H2O hybrid nanofluid between stretchable parallel Riga plates. The benefits of the use of hybrid nanofluids, and the parameters associated to it, have been analyzed mathematically. This particular problem has a lot of importance in several branches of engineering and industry. Heat and mass transfer along with nonlinear thermal radiation and chemical reaction effects have also been incorporated while carrying out the study. An appropriate selection of dimensionless variables have enabled us to develop a mathematical model for the present flow situation. The resulting mathematical method have been solved by a numerical scheme named as the method of moment. The accuracy of the scheme has been ensured by comparing the present result to some already existing results of the same problem, but for a limited case. To back our results further we have also obtained the solution by anther recipe known as the Runge-Kutta-Fehlberg method combined with the shooting technique. The error analysis in a tabulated form have also been presented to validate the acquired results. Furthermore, with the graphical assistance, the variation in the behavior of the velocity, temperature and concentration profile have been inspected under the action of various ingrained parameters. The expressions for skin friction coefficient, local Nusselt number and local Sherwood number, in case of Ag-Fe3O4H2O hybrid nanofluid, have been derived and the influence of various parameters have also been discussed.

The object of the present paper is to investigate a family of integral operators defined on the space of meromorphic functions. By making use of these novel integral operators, we introduce and investigate several new subclasses of starlike, convex, close-to-convex, and quasi-convex meromorphic functions. In particular, we establish some inclusion relationships associated with the aforementioned integral operators. Several interesting integral-preserving properties are also considered.

The difficulty of allocating a balanced educational syllabus to academic periods of a curriculum, also known as curriculum balancing, has long been a source of consternation for any institution of higher education attempting to connect learners and teachers. The balanced academic curriculum challenge entails assigning courses to academic times while adhering to all load restrictions and prerequisite requirements. The balanced academic curriculum problem (BACP) includes assigning subjects to class hours that fulfill standards even while managing students' burden in terms of credits, course load, and perquisites that includes subjects covered in the previous semesters/periods. The number of credits every semester corresponds to the academic load. As a result, educational frameworks must be "balanced," which means the credits for each period should be equivalent in order for students to bear minimum work. As a result, it is desirable to reduce this cost by developing a study plan that employs an algorithm that conducts this work automatically. Using an optimization method, this article provides a solution to the challenge of curricula balancing based on the discrete firefly algorithm (DFA). In research, FA has already been used to solve the BACP problem. However, the basic FA is modified to DFA with a local search mechanism inbuilt that helps to reach optimum solution in less number of iterations. A series of tests on standard and real data instances are done to check the efficiency of the suggested approach, with the objective of producing a platform that would simplify the procedure of building a curriculum system at institutions of higher learning. The results show that the proposed solution obtained a rather rapid solution and hit the recognized optimum in most of the iterations. [ABSTRACT FROM AUTHOR]

Background Caesarean delivery has a significant role in reducing maternal and child death. However, unnecessary utilization has adverse health effects. This study aimed to assess the prevalence and associated factors of caesarean delivery in Bangladesh. Methods Data from the latest Bangladesh Multiple Indicator Cluster Survey (MICS, 2019) was used in this study. Since MICS data are hierarchical in nature, multilevel modelling was used. Results The prevalence of caesarean section (CS) was 67.4% among Bangladeshi women. Multilevel analysis suggests the age of the women, household wealth status, utilization of antenatal care (ANC) , delivery at a health facility and division were significantly associated with CS. Women who delivered in a private health facility had the highest odds for CS (odds ratio [OR] 10.35 [95% confidence interval {CI} 8.55 to 12.54]). Women 30–34 y of age had a 36% higher likelihood of CS compared with women 15–19 y of age (OR 1.36 [95% CI 1.03 to 1.79]). The odds of CS positively increased with household wealth status. Women who had at least one ANC visit had a 1.7 times higher possibility of CS (OR 1.70 [95% CI 1.26 to 2.30]). Conclusions Policy guidelines on caesarean deliveries are urgently needed in Bangladesh to avoid unnecessary caesarean deliveries and protect mothers from the consequences. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has raised unprecedented challenges for the progressive education community universally. One crucial challenge is the engagement of advanced learners in pandemic times. Their academic interest is retained, their performance does not decline, and they get access to appropriate resources in time. This article will elaborate on the identification mechanism and the categorization of the students grounded on their comforts and performance. The pedagogical framework is developed for advanced learners by focused interventions such as providing exposure to industry-oriented problems, international virtual events, online courses and software, career counseling by industry leaders, and preparation for higher education. In this article, we are discussing obligatory interventions and their outcomes. Adopting blended learning is becoming a boon to learners by effectively using online resources. Working with these advanced learners, the teacher can directly converse the precise space where the scholar needs the support. In this research, student-centric methods are used. A pedagogical framework is proposed for aerospace engineering students. Advanced learners are categorized into specializations based on real-time data analysis such as aerodynamics, propulsion, space technology, and avionics. Analysis suggests that the categorization and targeted pedagogical intervention yields better student performance outcomes. Based on this study, we started offering specialization-based courses at the undergraduate level in coming batches. [ABSTRACT FROM AUTHOR]

We study univalence properties for certain subclasses of univalent functions K, K2, K3, and S(p), respectively. These subclasses are associated with a generalized integral operator. The extended Becker-typed univalence criteria will be studied for these subclasses.

KRAS mutations are among the most common oncogenic abnormalities in cancer. Until recently, drug discovery pursuing KRAS did not produce therapeutic benefits for patients. Specific KRAS inhibitors, such as sotorasib and adagrasib, which bind covalently to codon 12 of substituted glycine to cysteine residue of the protein (G12C), have been approved by the FDA recently for the treatment of lung cancers. Binding of these drugs to the protein inhibits the activation of the GDP-bound inactive state to the GTP-bound active state. Phase 1/2 trials have shown potential anti-tumor activity, particularly in patients with previously treated non-small cell lung cancer. Acquired resistance, on the other hand, is inevitable, and the mechanisms include new KRAS mutations such as Y96D/C and other RASMAPK effector protein abnormalities. "Adaptive Therapy," an ecologically inspired concept, focuses on extending the treatment-free period in a treatment course to delay the emergence of resistance. This review focuses on acquired mechanisms of resistance to KRAS G12C inhibitors, as well as the application of adaptive therapy in the treatment of KRAS-mutated patients to maintain acquired resistance sub-clones and extend progression-free survival. [ABSTRACT FROM AUTHOR]

Peer observation demands the teaching community to observe each other's teaching practice followed in classrooms and to learn from it. It focuses on individual requirements and learning by receiving and providing constructive feedback. This study gives detailed information about the purpose and principle of peer observation along with the steps followed in the peer observation cycle. The data gathered are from postobservation forms and meetings. Feedback from peers is used to demonstrate the importance of peer observation in improving the overall teaching experience. The results indicated that there is a significant improvement in the teaching style of the instructors. The category of attaining student attention and engagement grew by 28.8 percent, while the category of students demonstrating passion and motivation climbed by 15.27 percent. Peer observation is seen as a beneficial tool for teachers' professional development. Teachers stated that peer observation reduced their worry, hesitancy, and pressure throughout the teaching process, making it more dependable and real. However, participants identified time constraints and teachers' lack of observation expertise as barriers to peer observation. [ABSTRACT FROM AUTHOR]

Industrial organizations are responding to new risks and opportunities originating from exponentially growing and disruptive digital technologies, by taking company-wide digital transformation initiatives. However, the key enablers of such digital transformation initiatives that facilitate operational performance outcomes in industrial organizations demand further investigation. Therefore, drawing on the sociotechnical system theory (STS), the objective of this study is to explore the digital transformation enablers and their impact on performance outcomes. Research data was collected from four leading industrial organizations that engaged in digital transformation programmes. Our results indicate that leadership, structures, and culture are the key enablers of digital transformation that help industrial organizations to achieve performance outcomes (i.e. collaboration, customer-centricity, and agility). By providing an empirically grounded integrated framework with future research propositions, this study contributes to the existing literature on digital transformation and sociotechnical system theory. MAD statement This article aims to make a difference by exploring industrial digital transformation in order to identify the key enablers and performance outcomes. We highlight the need for alignment and joint optimization of social and technical systems to effectively capitalize on the digital transformation initiatives. Moreover, we call for urgent attention to the development of leaders, as well as the further identification of supportive digital transformation leadership competencies. Competent leaders assume a central role in correcting outdated and invalid assumptions, conceptualizing new ideas, and reinforcing cultural values. Furthermore, we elaborate the necessity of cultural transformation in industrial organizations for impactful digital transformation. Lastly, our findings confirm the significance of organizational structure in digital transformation and simultaneously warn that too little is happening. [ABSTRACT FROM AUTHOR]

Bitter gourd is one of the important cucurbits and highly liked among both farmers and consumers due to its high net return and nutritional value. However, being monoecious, it exhibits substantial variation in flower bearing pattern. Plant growth regulators (PGRs) are known to influence crop phenology while gibberellic acid (GA3) is one of the most prominent PGRs that influence cucurbits phenology. Therefore, a field trial was conducted at University of Agriculture Faisalabad to evaluate the impact of a commercial product of gibberellic acid (GA3) on growth, yield and quality attributes of two bitter gourd (Momordica charantia L.) cultivars. We used five different concentrations (0.4 g, 0.6 g, 0.8 g, 1.0 g, and 1.2 g per litre) of commercial GA3 product (Gibberex, 10% Gibberellic acid). Results showed that a higher concentration of gibberex (1.0 and 1.20 g L-1 water) enhanced the petiole length, intermodal length, and yield of bitter gourd cultivars over control in Golu hybrid and Faisalabad Long. A significant decrease in the enzyme superoxidase dismutase, peroxidase, and catalase activities were observed with an increasing concentration of gibberex (1.0 and 1.20 gL-1 water) as compared to control. These results indicate that the exogenous application of gibberex at a higher concentration (1.2 g L-1) has a dual action in bitter gourd plant: i) it enhances the plant growth and yield, and ii) it also influenced the antioxidant enzyme activities in fruits. These findings may have a meaningful, practical use for farmers involved in agriculture and horticulture. [ABSTRACT FROM AUTHOR]

Lung and bronchial Cancer is one of the world's leading cause of death. It is world's second deadliest disease which is now getting very common among men and women. Due to rapid deformation of climate, excess use of tobacco and working in hazardous waste side i.e. nuclear waste, explosive demolition centers left traces of harmful gases in air, which later can cause lung cancer and other fatal diseases. Cure of this deadliest disease is only possible by regularly examining of individuals, who are working and are exposed to health hazardous environment. X-rays images and Computed Tomography (CT) scans are the sources to detect nodules in lungs, which are the primary source of lungs cancers. Detection, identification and classification of these nodules are always a challenging job for doctors and researchers in medical imaging field. Researchers have developed many methods for nodules detection. Some of these methods include machine learning and artificial neural network. In this paper we have discusses few of these methods both from machine learning and artificial neural network for the early detection of nodules from CT scan. [ABSTRACT FROM AUTHOR]

We exploit the use of a controller area network (CAN-bus) to monitor sensors on the buses of local public transportation in a big European city. The aim is to advise fleet managers and policymakers on how to reduce fuel consumption so that air pollution is controlled and public services are improved. We deploy heuristic algorithms and exhaustive ones to generate Bayesian networks among the monitored variables. The aim is to describe the relevant relationships between the variables, to discover and confirm the possible cause–effect relationships, to predict the fuel consumption dependent on the contextual conditions of traffic, and to enable an intervention analysis to be conducted on the variables so that our goals are achieved. We propose a validation technique using Bayesian networks based on Granger causality: it relies upon observations of the time series formed by successive values of the variables in time. We use the same method based on Granger causality to rank the Bayesian networks obtained as well. A comparison of the Bayesian networks discovered against the ground truth is proposed in a synthetic data set, specifically generated for this study: the results confirm the validity of the Bayesian networks that agree on most of the existing relationships. [ABSTRACT FROM AUTHOR]