Use of artificial neural networks as explicit finite difference operators

Results of a numerical exercise, substituting a numerical operator by an artificial neural network (ANN) are presented in this paper. The numerical operator used is the explicit form of the finite difference (FD) scheme. The FD scheme was used to discretize the one-dimensional transport equation, which included both the advection and dispersion terms. Inputs to the ANN are the FD representation of the transport equation, and the concentration was designated as the output. Concentration values used for training the ANN were obtained from analytical solutions. The numerical operator was reconstructed from a back calculation of the weights of the ANN. Linear transfer functions were used for this purpose. The ANN was able to accurately recover the velocity used in the training data, but not the dispersion coefficient. This capability was improved when numerical dispersion was taken into account; however, it is limited to the condition: C/P<0.5 , where C is the Courant number and P , the Peclet number (i.e., the restriction imposed by the Neumann stability condition).

Nutritional psychiatry research: an emerging discipline and its intersection with global urbanization, environmental challenges and the evolutionary mismatch

In 21st-century public health, rapid urbanization and mental health disorders are a growing global concern. The relationship between diet, brain function and the risk of mental disorders has been the subject of intense research in recent years. In this review, we examine some of the potential socioeconomic and environmental challenges detracting from the traditional dietary patterns that might otherwise support positive mental health. In the context of urban expansion, climate change, cultural and technological changes and the global industrialization and ultraprocessing of food, findings related to nutrition and mental health are connected to some of the most pressing issues of our time. The research is also of relevance to matters of biophysiological anthropology. We explore some aspects of a potential evolutionary mismatch between our ancestral past (Paleolithic, Neolithic) and the contemporary nutritional environment. Changes related to dietary acid load, advanced glycation end products and microbiota (via dietary choices and cooking practices) may be of relevance to depression, anxiety and other mental disorders. In particular, the results of emerging studies demonstrate the importance of prenatal and early childhood dietary practices within the developmental origins of health and disease concept. There is still much work to be done before these population studies and their mirrored advances in bench research can provide translation to clinical medicine and public health policy. However, the clear message is that in the midst of a looming global epidemic, we ignore nutrition at our peril.

Maximum power point tracking of partial shaded photovoltaic array using an evolutionary algorithm: a particle swarm optimization technique

 Partial shading is one of the unavoidable complications in the field of solar power generation. Although the most common approach in increasing a photovoltaic (PV) array’s efficiency has always been to introduce a bypass diode to the said array, this poses another problem in the form of multi-peaks curves whenever the modules are partially shaded. To further complicate matters, most conventional Maximum Power Point Tracking methods develop errors under certain circumstances (for example, they detect the local Maximum Power Point (MPP) instead of the global MPP) and reduce the efficiency of PV systems even further. Presently, much research has been undertaken to improve upon them. This study aims to employ an evolutionary algorithm technique, also known as particle swarm optimization, in MPP detection. VC 2014 Author(s).

The role of general and specific stressors in the health and well-being of call centre operators

The call centre industry has developed a reputation for generating a highly stressful work environment with high absenteeism and turnover rates. Research has identified role ambiguity, role conflict, role overload, and work-family conflict as common stressors in other settings. Call centre research has additionally identified performance monitoring, job design and job opportunities as call centre specific stressors.OBJECTIVE AND METHODS: This study investigated the impact of the identified stressors on burnout, somatic symptomology, and turnover intent among 126 call centre representatives (CCRs) from 11 call centres in metropolitan Melbourne, Australia.

International perspectives on psychosocial working conditions, mental health, and stress of dairy farm operators

Dairy farm operators-farmers, workers, and family members-are faced with many demands and stressors in their daily work and these appear to be shared across countries and cultures. Dairy operators experience high psychosocial demands with respect to a hard work and production ethos, economic influences, and social and environmental responsibility. Furthermore, both traditional and industrial farms are highly dependent on external conditions, such as weather, fluctuating markets, and regulations from government authorities. Possible external stressors include disease outbreaks, taxes related to dairy production, and recent negative societal attitudes to farming in general. Dairy farm operators may have very few or no opportunities to influence and control these external conditions, demands, and expectations. High work demands and expectations coupled with low control and lack of social support can lead to a poor psychosocial work environment, with increased stress levels, ill mental health, depression, and, in the worst cases, suicide. Internationally, farmers with ill mental health have different health service options depending on their location. Regardless of location, it is initially the responsibility of the individual farmer and farm family to handle mental health and stress, which can be of short- or long-term duration. This paper reviews the literature on the topics of psychosocial working conditions, mental health, stress, depression, and suicide among dairy farm operators, farm workers, and farm family members in an international perspective.

Image reduction operators as aggregation functions: Fuzzy transform and undersampling

After studying several reduction algorithms that can be found in the literature, we notice that there is not an axiomatic definition of this concept. In this work we propose the definition of weak reduction operators and we propose the properties of the original image that reduced images must keep. From this definition, we study whether two methods of image reduction, undersampling and fuzzy transform, satisfy the conditions of weak reduction operators.

Effectiveness of evolutionary algorithms for optimization of heat exchangers

This paper comprehensively investigates performance of evolutionary algorithms for design optimization of shell and tube heat exchangers (STHX). Genetic algorithm (GA), firefly algorithm (FA), and cuckoo search (CS) method are implemented for finding the optimal values for seven key design variables of the STHX model. ε-NTU method and Bell-Delaware procedure are used for thermal modeling of STHX and calculation of shell side heat transfer coefficient and pressure drop. The purpose of STHX optimization is to maximize its thermal efficiency. Obtained results for several simulation optimizations indicate that GA is unable to find permissible and optimal solutions in the majority of cases. In contrast, design variables found by FA and CS always lead to maximum STHX efficiency. Also computational requirements of CS method are significantly less than FA method. As per optimization results, maximum efficiency (83.8%) can be achieved using several design configurations. However, these designs are bearing different dollar costs. Also it is found that the behavior of the majority of decision variables remains consistent in different runs of the FA and CS optimization processes.

Evolutionary history and leaf succulence as explanations for medicinal use in aloes and the global popularity of Aloe vera

BACKGROUND: Aloe vera supports a substantial global trade yet its wild origins, and explanations for its popularity over 500 related Aloe species in one of the world's largest succulent groups, have remained uncertain. We developed an explicit phylogenetic framework to explore links between the rich traditions of medicinal use and leaf succulence in aloes. RESULTS: The phylogenetic hypothesis clarifies the origins of Aloe vera to the Arabian Peninsula at the northernmost limits of the range for aloes. The genus Aloe originated in southern Africa ~16 million years ago and underwent two major radiations driven by different speciation processes, giving rise to the extraordinary diversity known today. Large, succulent leaves typical of medicinal aloes arose during the most recent diversification ~10 million years ago and are strongly correlated to the phylogeny and to the likelihood of a species being used for medicine. A significant, albeit weak, phylogenetic signal is evident in the medicinal uses of aloes, suggesting that the properties for which they are valued do not occur randomly across the branches of the phylogenetic tree. CONCLUSIONS: Phylogenetic investigation of plant use and leaf succulence among aloes has yielded new explanations for the extraordinary market dominance of Aloe vera. The industry preference for Aloe vera appears to be due to its proximity to important historic trade routes, and early introduction to trade and cultivation. Well-developed succulent leaf mesophyll tissue, an adaptive feature that likely contributed to the ecological success of the genus Aloe, is the main predictor for medicinal use among Aloe species, whereas evolutionary loss of succulence tends to be associated with losses of medicinal use. Phylogenetic analyses of plant use offer potential to understand patterns in the value of global plant diversity.

Evolutionary perspective of cancer: myth, metaphors, and reality

The evolutionary perspective of cancer (which origins and dynamics result from evolutionary processes) has gained significant international recognition over the past decade and generated a wave of enthusiasm among researchers. In this context, several authors proposed that insights into evolutionary and adaptation dynamics of cancers can be gained by studying the evolutionary strategies of organisms. Although this reasoning is fundamentally correct, in our opinion, it contains a potential risk of excessive adaptationism, potentially leading to the suggestion of complex adaptations that are unlikely to evolve among cancerous cells. For example, the ability of recognizing related conspecifics and adjusting accordingly behaviors as in certain free-living species appears unlikely in cancer. Indeed, despite their rapid evolutionary rate, malignant cells are under selective pressures for their altered lifestyle for only few decades. In addition, even though cancer cells can theoretically display highly sophisticated adaptive responses, it would be crucial to determine the frequency of their occurrence in patients with cancer, before therapeutic applications can be considered. Scientists who try to explain oncogenesis will need in the future to critically evaluate the metaphorical comparison of selective processes affecting cancerous cells with those affecting organisms. This approach seems essential for the applications of evolutionary biology to understand the origin of cancers, with prophylactic and therapeutic applications.

Popularity of reinforcement-based and belief-based learning models: an evolutionary approach

In an evolutionary model, players from a given population meet randomly in pairs each instant to play a coordination game. At each instant, the learning model used is determined via some replicator dynamics that respects payoff fitness. We allow for two such models: a belief-based best-response model that uses a costly predictor, and a costless reinforcement-based one. This generates dynamics over the choice of learning models and the consequent choices of endogenous variables. We report conditions under which the long run outcomes are efficient (or inefficient) and they support the exclusive use of either of the models (or their co-existence).

Evolutionary biology of the invasive Northern Pacific seastar, Asterias amurensis

 Mark investigated the genetic basis of environmental adaptation in invasive and native A. amurensis larvae. He showed rapid changes in genetic architecture and gene expression underlie different physiological responses to elevated temperatures in invasive larvae. These findings are the first step in understanding the potential for range expansion within Australia.

Writing scientific papers, with special reference to evolutionary ecology

© 2015, Springer International Publishing Switzerland. The advancement of science, as well as scientific careers, depends upon good and clear scientific writing. Science is the most democratic of human endeavours because, in principle, anyone can replicate a scientific discovery. In order for this to continue, writing must be clear enough to be understood well enough to allow replication, either in principle or in fact. In this paper I will present data on the publication process in Evolutionary Ecology, use it to illustrate some of the problems in scientific papers, make some general remarks about writing scientific papers, summarise two new paper categories in the journal which will fill gaps that appear to be expanding in the literature, and summarise new journal policies to help mitigate existing problems. Most of the suggestions about writing would apply to any scientific journal.