Survival-of-the-fittest Research Articles

114 - The Phenotype of a Bone Marrow Transplant Nurse: Survival of the Fittest

114 - The Phenotype of a Bone Marrow Transplant Nurse: Survival of the Fittest

Survival of the Fittest: Hypomethylating Agent/BCL-2 Inhibitor Combination Versus Intensive Chemotherapy As Frontline Treatment for Acute Myeloid Leukemia

Survival of the Fittest: Hypomethylating Agent/BCL-2 Inhibitor Combination Versus Intensive Chemotherapy As Frontline Treatment for Acute Myeloid Leukemia

Au-delà de la réciprocité négative : la femme-gangster Madame St-Clair, reine de Harlem de Raphaël Confiant

This article seeks to examine representations of the female gangster commonly known as “Madame Queen,” or simply “Queenie,” who was a formidable and ingenious figure in 1920s-40s New York. Confiant calls to mind the curiously ethical and troubled roots of this Antillaise activist and “miraculous survivor” who subverts the order of power by, more often than not, producing disorder in the form of negative reciprocity, that is to say vengeance. Her story will be determined by the First World War, the start of the Civil Rights Movement, the Great Depression and the Second World War. Queenie’s agency, or shall we say, with a knowing smile, her “social engagement,” will manifest itself in the projection of a life that is fully-thought out and which, mysteriously or instinctively, unites itself to one pole or another of calculated vengeance or indefinite and radical revenge. Out of what begins as a minefield, she very nearly reconciles these opposites by opening up a field of possibilities for future generations. Thus, this woman gangster gives herself the chance to consider anew the manifestations of violence and the knots of oppression that have been omnipresent in her life. From a political, economic, judicial and cultural perspective, marginalised communities live according to the survival of the fittest. Yet who can carry the standard of liberty, of peace and of dignity without a heightened awareness that allows us to define those human values? Raphael Confiant brings a critical examination of the gaze to a world of effervescence, to forces which have barely been linked let alone brought head to head in the past. From the revenge of laughter to the questioning of the link between positive and negative reciprocity, Confiant’s search for a path to liberation by means of creation is unwavering and also inexhaustible, for from it flows the future and the map of possibilities for “the damned of the earth.”

Identifying people based on physiognomy: Explanations from cognitive perspective

<p id="p00005">Physiognomy is an important factor in identifying and inferring the individual traits and behaviors. However, its internal mechanism still needs to be further explored. Physiognomy usually refers to individual facial features, mainly including partial features and overall features. The partial features of facial features include the size and shape of the five sense organs, and the thickness of hair, while the overall features of facial features include objective facial width-to-height ratio and subjective facial attractiveness. Based on general cognitive perspective and evolutionary cognitive perspective, then combined with the local and overall features of physiognomy, this paper expounds the process and effect of judging people by physiognomy. <p id="p00008">The general cognitive perspective emphasizes that people study the process of cognition from the perspective of information processing, which emphasizes the process of perception. The individual’s response to physiognomy is mainly a by-product of the brain’s processing of information, which is the processing mechanism for general information. Based on stereotypes, halo effects, status generalization theory, and social information processing theory, scholars use different cognitive processing systems to illustrate the process of getting to know people and their effects. Specifically, local features such as the size and shape of the five sense organs, the thickness of the hair, and overall features such as the facial width-to-height ratio and facial attractiveness can affect individual recognition of traits such as empathy, friendliness, extroversion, self-confidence, narcissism, aggression, dominance and criminological inheritance through different cognitive processing systems. Observers’ subsequent behaviors is based on the individual traits’ information recognized by the physiognomy. On the one hand, people will judge their income, ability, and social level based on the identified individual traits. On the other hand, these individual traits play an important role in the trust decision-making, the recruitment and promotion decision-making process. All in all, physiognomy affects the recognition of individual traits through various cognitive processing systems, and these traits play important roles in judgment (ability, income, social hierarchy) and decision-making (trust, recruitment, promotion). <p id="p00007">Compared with the general cognitive perspective, the evolutionary cognitive perspective emphasizes that in the process of processing information, people will identify which cues are related to health, survival, propagation and adaptation to the environment according to the evolutionary needs. Based on evolutionary theory, evolutionary intrasexual competition theory and the good genes theory, scholars have discussed how to know people and its effect through two different evolutionary selection mechanisms: natural selection and sexual selection. The observer uses the gene as the driving force to identify the observed physiognomy. Observers assessed marital satisfaction, life satisfaction and happiness based on the health and genetic status they identified. In order to meet the needs of evolution and survival, people will choose a mate according to the health and genetic status of the individual identified when observing facial features, combined with the evolutionary law of "survival of the fittest". In conclusion, physiognomy plays an important role in evaluating individual health and genetic status through various evolutionary selection mechanisms, and thus has an important influence on judgment (marriage satisfaction, happiness, life satisfaction) and mate selection decision. <p id="p00006">In addition, the effect of physiognomy on individual life depends on the situations and individual traits. The decision situation of the face viewer, the cultural context of the face owner, and the individual traits of the face viewer and the face owner all influence the effect of physiognomy’s identification. Future research should investigate the interaction among different physiognomy features, and explore the boundary conditions that influence the effect of facial recognition. Furthermore, it is necessary to improve the external validity of the research through big data analysis, and pay more attention to physiognomy features modified by epigenetics on individuals. It is also important to conduct research within the domestic context. In doing so, it will help enrich physiognomy-related research and build a more systematic physiognomy theory.

Survival of the fittest: the multiple paths of entrepreneurial leadership driving adaptive innovation in uncertain environment

PurposeThis study aims to investigate the multiple influence paths or underlying mechanisms of entrepreneurial leadership (EL) on adaptive innovation from the perspectives of organizational learning and resource management, drawing on complex adaptive system theory.Design/methodology/approachWith a questionnaire survey of 317 senior and middle managers from different firms in China, structural equation modeling was used to test the hypothesized conceptual model, and bootstrapping method was employed to examine the multiple mediating effects.FindingsResults indicate that EL has a significant and positive effect on adaptive innovation. This relationship is partially mediated through exploitative learning, exploratory learning, resource bricolage and boundary-spanning integration, respectively. The impact of EL on adaptive innovation is also sequentially transmitted through exploitative learning and resource bricolage or exploratory learning and boundary-spanning integration.Originality/valueAdaptive innovation has become a firm competition strategy to cope with dynamic changes in current uncertain environment where EL can play its effectiveness to engage firms in such innovation activities. However, the question of why and how EL drives adaptive innovation has yet to be discussed. This study highlights the innovation effectiveness of EL and the triggering process of adaptive innovation, and contributes to several countermeasures for firms to implement leadership and innovation practices responding to uncertain environment.

An improved adaptive genetic algorithm

Genetic algorithm is a classic intelligent bionic algorithm, which is evolved according to the genetic evolution process of organisms in nature, and has strong global optimization ability. Firstly, this paper expounds the basic principle of genetic algorithm, which comes from the viewpoint of “survival of the fittest and survival of the fittest” in Darwin’s theory of evolution, introduces the main characteristics of the algorithm, and summarizes the shortcomings of the algorithm. Based on the specific running steps of genetic algorithm, aiming at the shortcomings of genetic algorithm, an improved adaptive genetic algorithm is proposed. Finally, an example is used for simulation. The simulation results show that the improved algorithm has certain advantages.

Survival of the Fittest

What is driving the change in Operational Technology threats across industrial manufacturing - and how can firms adapt to mitigate against them?

Structure Optimization of Carbon Nanotubes Based on Swarm Intelligence Algorithm and Evolutionary Computation

Swarm intelligence algorithm is an emerging evolutionary computing technology, which has become the focus of more and more researchers. It has a very special connection with artificial life, especially evolutionary strategies and genetic algorithms. The swarm intelligence algorithms you see include genetic algorithm, particle swarm optimization algorithm, and ant colony algorithm. This part of the content has been supplemented in the article. Evolutionary computing is a group‐oriented random search technology and method produced by simulating the evolutionary process of organisms in nature. Evolutionary computing is based on natural selection strategy: survival of the fittest, elimination of the unfit, and individuals with large fitness values have a higher survival probability than individuals with small fitness values. The purpose of this paper is to study the structure optimization of carbon nanotubes based on swarm intelligence algorithm and evolutionary computation. It is expected to optimize the structure of carbon nanotube materials with the help of intelligent evolution algorithm, so that it can be used in more fields. In this paper, the preparation process and principle of carbon nanotube‐based gas sensors are studied, and the preparation process of the side‐heated gas sensor is selected. This paper focuses on the strain sensing performance of carbon nanotubes, analyzes various parameters that characterize the sensing performance, and proposes feasible technical routes for improvement, optimization and improvement. The experimental results in this paper show that when different proportions of oxides are added, the tensile strength of carbon nanotube materials is increased by about 8%, and the elastic modulus is increased by up to 40%. After adding CNFs, the tensile strength increased by up to 18%, and the elastic modulus increased by up to 50%.

Is Evolution a Causal, Yet Not-Predetermined Process?

It is demonstrated that “survival of the fittest” approach suffers fundamental flaw planted in its very goal: reaching a uniform state starting from a minor random event. Simple considerations prove that a generic property of any such state is its global instability. That is why a new approach to the evolution is put forward. It conjectures equilibrium for systems put in an ever-changing environment. The importance of this issue lies in the view that an ever-changing environment is much closer to the natural environment where the biological species live in. The major goal of the present paper is to demonstrate that a specific form of dynamical equilibrium among certain mutations is established in each and every stable in a long-run system. Major result of our considerations is that neither mutation nor either kind dominates forever because a temporary dynamical equilibrium is replaced with another one in the time course. It will be demonstrated that the evolution of those pieces of equilibrium is causal, yet not predetermined process.

Powerful CEOs in Uncertain Times: Survival of the Fittest

Powerful CEOs in Uncertain Times: Survival of the Fittest

Flowing Water Algorithm: A New Approach for Combinatorial Optimization Problems

Being greatly inspired by the natural flowing regulation of water, we propose a new meta-heuristic algorithm — <i>Flowing Water Algorithm</i> (FWA) for the solution of combinatorial optimization problems (COPs). Since the solution space of COPs is multidimensional, complex and has many local extreme values, according to our proposed method, it appears to be similar to an endless hilly area with mountains, valleys and plateaus. The downward-flowing water in such area finds its way to the lowest point in the hill. Water always flows downward and eventually converges at the lowest place without any outside intervention except for gravity. Such a flowing course can be deemed as a process for the water to seek for the lowest point. The proposed algorithm is derived from such a water flow process. This algorithm combines a local search strategy with a population-based search strategy to improve both local and global search abilities. Four operators, including the local search, water overflow, drilling water tunnel and evaporation-rain are included in FWA, making this algorithm successfully perform tabu search, positive feedback, “survival of the fittest”, and local optimum escape. Two examples of its application in the traveling salesman problem (TSP) show that FWA outperforms the benchmark methods for both solution quality and convergence speed.

‘Survival of the fittest’? Perceptions of wellbeing at The Bar of Northern Ireland

This article, based on a qualitative study conducted in June–July 2019, assesses how barristers at the Bar of Northern Ireland perceive wellbeing and mental ill-health within their profession. It will argue that the Bar can be a competitive and potentially hostile workplace environment, leading to detrimental impacts on wellbeing. It will also contend that being a barrister in Northern Ireland provides its own unique challenges for practitioners due to the self-employed independent nature of the role, where practitioners do not work in chambers or stables like their counterparts in England &amp; Wales and Scotland. At the same time, barristers spoke positively about the flexibility of their roles and beneficial forms of collegiality, as well as an evolving culture which places greater emphasis on wellbeing. This article will argue, using the ‘job demands and resources’ model, that efforts should be made to decrease job demands and increase the job resources of barristers of the Bar of Northern Ireland to improve levels of wellbeing. This model could also be applied to the Bar in other jurisdictions to assess the impact of both shared and unique challenges and opportunities.

Selected Genetic Algorithms for Vehicle Routing Problem Solving

The traveling salesman problem (TSP) consists of finding the shortest way between cities, which passes through all cities and returns to the starting point, given the distance between cities. The Vehicle Routing Problem (VRP) is the issue of defining the assumptions and limitations in mapping routes for vehicles performing certain operational activities. It is a major problem in logistics transportation. In specific areas of business, where transportation can be perceived as added value to the product, it is estimated that its optimization can lower costs up to 25% in total. The economic benefits for more open markets are a key point for VRP. This paper discusses the metaheuristics usage for solving the vehicle routing problem with special attention toward Genetic Algorithms (GAs). Metaheuristic algorithms are selected to solve the vehicle routing problem, where GA is implemented as our primary metaheuristic algorithm. GA belongs to the evolutionary algorithm (EA) family, which works on a “survival of the fittest” mechanism. This paper presents the idea of implementing different genetic operators, modified for usage with the VRP, and performs experiments to determine the best combination of genetic operators for solving the VRP and to find optimal solutions for large-scale real-life examples of the VRP.

Improving Homeostatic Set-Point through Proper Training Adaptations for Better Sporting Outcome

The concept of homeostasis is based on Darwin’s theory of survival of the fittest. In order to survive one has to maintain a stable internal and external environment. For attaining positive change of an individual’s physical, physiological, psychological, and mechanical performance stress is required in a systematic and scientific planned way. Regular upsetting the homeostatic set point, a new set-point is able to create within the body, which can be termed as adaptation. In the case of sports performance, the training load must be adopted by an athlete through the process of super-compensation in order to exhibit better performance in the competitive sports arena. Adaptation is facilitated the positive reinforcement through a negative feedback loop in physical, physiological, and psychological areas of any individual and able to develop the concept of feed-forward mechanism. If adaptation stimuli are applied properly, training can be expected to have accumulative effect. The sporting world depends upon the positive adaptation of training load through improving the sporting performance by elevating the homeostatic set point. Long term training has also positive impact on health sports performance by modifying the qualitative and quantitative physiological component. A physiological adaptation refers to the metabolic or physiologic adjustment within the cell, or tissues, of an organism in response to an environmental stimulus resulting in the improved ability of that organism to cope with its changing environment adaptation. The purpose of the present study is to critically discuss the various aspects of homeostatic regulations and the way to create a new set point of an athlete for better performance through the adaptation process.

Zo(o)graphies: Darwinian ‘Evolutions’ of a Fictional Bestiary

The essay puts to the test Darwinian evolutionist theories, especially the key concepts of adaptation, natural selection and survival of the fittest, in the reading of several plots and fictions (some of them Ark-related animal fictions) concerned with evolution, trauma, adaptability, mimicry/mimesis and survival: Julian Barnes’s Flaubert Parrot and A History of the World in 10½ Chapters, Timothy Findley’s Not Wanted on the Voyage, Robert Kroetsch’s The Studhorse Man and John Fowles’s The French Lieutenant’s Woman. Weaving its critical argument with reference to several of Derrida’s reflections – on the impossibility of a pure origin, the proximity between commencement and commandment, the logic of obsequence, or relation between being and following (je suis), applied deconstructively to the traditional hierarchy between the human and the animal, mastery and monstrosity, and logos and bêtise, etc. – ‘Zo(o)graphies’ is structured in a series of interlinked tableaux, bestiaries as well as insets (Thomas Pynchon’s Gravity’s Rainbow, Jacques Derrida’s Glas). Following from the opening evocation of Peter Greenaway’s Vermeer-themed film A Zed and Two Noughts, which introduces the joint semantics of zographein: to paint from life, and zoon: animal, discreetly at work throughout, this study will eventually attempt to recast the problematic of the evolution of literature and literary forms as involution and regression.

Social Darwinism discourse in the USA fiction at the turn of the 19–20&lt;sub&gt; th&lt;/sub&gt; centuries

This paper presents an attempt to analyze the relationship between social Darwinism ideology and American literature at the turn of the 1920th centuries. According to philologists, critical realism was customary of that period in literature. The famous authors nowadays such as Theodore Dreiser and Jack London or less well-known, for example, Edward Bellamy and Robert Herrick, presented their plots against the same intellectual background and described them using similar expressions and clichs. Such expressions as struggle for existence, natural selection, survival of the fittest became the usual ones in American public life at the turn of the 1920th centuries. Social Darwinism rhetoric united the worlds of politics, science and literature. The language determines our ideas about what can be right or wrong, fair and unfair. Ideology and the language played a fundamental role in shaping behavior in the context of the American dream especially. The American dream contained an idea of equality of opportunities for individuals, provided that they have talent and diligence. The author analyzes the language used in American literature and the influence of social Darwinism ideology on public consciousness. This discourse reveals the essence of social problems and attitudes of the American society in that historical period.

Banking System Paradox

Banking system has been the backbone of Indian economy. Banking industry has seen a drastic transformation in past two and half decades with emergence of new players in the form of new generation private sector bank, payment banks, non banking financial companies. Competition among service providers has lead to sustainability issues. Balancing between business expansion, risk absorbing capacity and profitability is important. Survival of the fittest is the rule of the game. Nationalization of private banks was done to expand the service base for common masses. Since independence public sector banks have played a key role in the development and balanced growth of all sections of the society. Public sector banks were supported by a league of few old generation banks that catered the niche segments across India. Kerala is the birth place of many old generation private sector banks. Old generation banks worked in line to the practices followed by the leading public sector banks. Indian Banking Association (IBA) was formed for bringing standardization among peer players across industry. Post liberalization era has originated many new generation banks are genetically modified hybrids. New variants are designed for specific objectives of profit maximization en-cashing available opportunities. Business expansion is based on profit criteria rather than social requirements. Ideologies have differed a lot across generations. Public sector banks and new generation private sector banks are operating with diverse organizational goals. This case study highlights the comparative scenario of private sector banks with that of public sector banks to understand the market dynamics in the game of performance and survival.

COVID-19 pandemic and "survival of the fittest".

Occurrence and recurrence of COVID-19 cases have been observed globally. The complex relationship of host-pathogen and the environment plays a vital role in understanding the widespread recurrence of the SARS-CoV-2 among humans. Though the pathobiology of the disease is not completely understood, it is well established that COVID-19 poses a greater threat to individuals with co-morbidities and a weakened immune system. The article deals with the notion of innate immunity, natural selection, and the survival of the fittest during the COVID-19 outbreak. The article also attempts to introduce the concept of "lifestyle and cultural immunity" that needs to be addressed and incorporated at an early stage of childhood to boost up the human immune system. The communication further discusses the role of vaccination and micro-organisms pre-existing in the environment which are required to enhance the immunity of an individual.

Sensitivity calibration of a three-axis accelerometer under different temperature conditions using the hybrid GA–PSO–BPNN algorithm

PurposeThree-axis accelerometers play a vital role in monitoring the vibrations in aircraft machinery, especially in variable flight temperature environments. The sensitivity of a three-axis accelerometer under different temperature conditions needs to be calibrated before the flight test. Hence, the authors investigated the efficiency and sensitivity calibration of three-axis accelerometers under different conditions. This paper aims to propose the novel calibration algorithm for the three-axis accelerometers or the similar accelerometers.Design/methodology/approachThe authors propose a hybrid genetic algorithm–particle swarm optimisation–back-propagation neural network (GA–PSO–BPNN) algorithm. This method has high global search ability, fast convergence speed and strong non-linear fitting capability; it follows the rules of natural selection and survival of the fittest. The authors describe the experimental setup for the calibration of the three-axis accelerometer using a three-comprehensive electrodynamic vibration test box, which provides different temperatures. Furthermore, to evaluate the performance of the hybrid GA–PSO–BPNN algorithm for sensitivity calibration, the authors performed a detailed comparative experimental analysis of the BPNN, GA–BPNN, PSO–BPNN and GA–PSO–BPNN algorithms under different temperatures (−55, 0 , 25 and 70 °C).FindingsIt has been showed that the prediction error of three-axis accelerometer under the hybrid GA–PSO–BPNN algorithm is the least (approximately ±0.1), which proved that the proposed GA–PSO–BPNN algorithm performed well on the sensitivity calibration of the three-axis accelerometer under different temperatures conditions.Originality/valueThe designed GA–PSO–BPNN algorithm with high global search ability, fast convergence speed and strong non-linear fitting capability has been proposed to decrease the sensitivity calibration error of three-axis accelerometer, and the hybrid algorithm could reach the global optimal solution rapidly and accurately.

Quantum circuit design search

This article explores search strategies for the design of parameterized quantum circuits. We propose several optimization approaches including random search plus survival of the fittest, reinforcement learning both with classical and hybrid quantum classical controllers, and Bayesian optimization as decision makers to design a quantum circuit in an automated way for a specific task such as multi-labeled classification over a dataset. We introduce nontrivial circuit architectures that are arduous to be hand-designed and efficient in terms of trainability. In addition, we introduce reuploading of initial data into quantum circuits as an option to find more general designs. We numerically show that some of the suggested architectures for the Iris dataset accomplish better results compared to the established parameterized quantum circuit designs in the literature. In addition, we investigate the trainability of these structures on the unseen dataset Glass. We report meaningful advantages over the benchmarks for the classification of the Glass dataset which supports the fact that the suggested designs are inherently more trainable.