Intuitionistic fuzzy-based TOPSIS method for multi-criterion optimization problem: a novel compromise methodology

The decision-making process is characterized by some doubt or hesitation due to the existence of uncertainty among some objectives or criteria. In this sense, it is quite difficult for decision maker(s) to reach the precise/exact solutions for these objectives. In this study, a novel approach based on integrating the technique for order preference by similarity to ideal solution (TOPSIS) with the intuitionistic fuzzy set (IFS), named TOPSIS-IFS, for solving a multi-criterion optimization problem (MCOP) is proposed. In this context, the TOPSIS-IFS operates with two phases to reach the best compromise solution (BCS). First, the TOPSIS approach aims to characterize the conflicting natures among objectives by reducing these objectives into only two objectives. Second, IFS is incorporated to obtain the solution model under the concept of indeterminacy degree by defining two membership functions for each objective (i.e., satisfaction degree, dissatisfaction degree). The IFS can provide an effective framework that reflects the reality contained in any decision-making process. The proposed TOPSIS-IFS approach is validated by carrying out an illustrative example. The obtained solution by the approach is superior to those existing in the literature. Also, the TOPSIS-IFS approach has been investigated through solving the multi-objective transportation problem (MOTP) as a practical problem. Furthermore, impacts of IFS parameters are analyzed based on Taguchi method to demonstrate their effects on the BCS. Finally, this integration depicts a new philosophy in the mathematical programming field due to its interesting principles

Sarcoplasmic reticulum Ca2+ dynamics in aging Drosophila and correlation with sarcopenia

Aging still remains a mystery of biology and one of the most affected tissues in aging is skeletal muscle, whose loss of muscle mass and strength is called sarcopenia. Age-dependent sarcopenia is not restricted to mammals, as it affects other animal species including nematodes or flies. Cytosolic Ca2+ ion is the intracellular second messenger that triggers muscle contraction. The sarcoplasmic reticulum is the store of Ca2+ in the muscle cell, and it releases Ca2+ to the cytosol when muscle contracts. Sarcopenia has been linked to the loss of Ca2+ homeostasis that trigger muscle contraction, but mechanistic details remain unsolved. Here we explore the hypothesis that an alteration of the Ca2+ content within the sarcoplasmic reticulum (SR) is at the origin of this loss of Ca2+ homeostasis observed in sarcopenia. For investigating this hypothesis, we generated transgenic flies that express the ratiometric low affinity Ca2+ indicator GAP3 targeted to the muscle sarcoplasmic reticulum (erGAP3), and we developed a new method to calibrate erGAP3 fluorescent signals into SR/ER Ca2+ concentrations ([Ca2+]SR/ER). With these tools we measured resting [Ca2+]SR in vivo along the fly life, and found a progressive decrease with aging that results in a tenfold reduction in the [Ca2+]SR in the oldest flies. Then, to explore the molecular mechanisms involved in this decrease of [Ca2+]SR we studied the expression levels of the main proteins involved in [Ca2+]SR resting levels. In old muscle, we found a slight non-significant increase in the ryanodine receptors (RyR) and in the immunoglobulin protein (BiP) expression whereas the expression of the sarco/endoplasmic reticulum Ca2+- ATPase (SERCA) decreased by 35%. Moreover, the loss of function of the skeletal muscle was monitored by the well-characterized climbing assay, and found a strong correlation between the Ca2+ content of the sarcoplasmic reticulum and fly climbing ability with aging. Furthermore, to assess whether the reduction of [Ca2+]SR content in the aged flies also affected the [Ca2+]C transients, we studied the cytosolic Ca2+ dynamics during muscle contraction in transgenic flies expressing the cytosolic Ca2+ sensor GCaMP in the muscle tissue. This experiments showed that old flies released less Ca2+ to the cytosol in comparison to young flies and, thus, these results validated those obtained in the SR. In order to investigate whether the reduction of SR Ca2+ content observed in muscle was a universal phenomenon of aging that occurred also in other tissues we studied the progression of [Ca2+]ER in brain neurons and in the peripheral sensory wing neurons using the pan neuronal transgenic line, which expresses erGAP3 in all types of neurons. The [Ca2+]ER of the brain neurons did not change significantly with age, and remained stable along the whole fly life. However, the behaviour is different in other neurons as we can also appreciate a decrease in the [Ca2+]ER of the sensory wing neurons, similar to what occurs in the skeletal muscle. Regarding the key molecular players, in contrast to the muscle, SERCA levels remained unchanged in brain neurons whereas BiP and RyR levels are increased in the aging brain.Departamento de Bioquímica y Biología Molecular y FisiologíaDoctorado en Investigación Biomédic

Modelling Neuron Morphology: Automated Reconstruction from Microscopy Images

Understanding how the brain works is, beyond a shadow of doubt, one of the greatest challenges for modern science. Achieving a deep knowledge about the structure, function and development of the nervous system at the molecular, cellular and network levels is crucial in this attempt, as processes at all these scales are intrinsically linked with higher-order cognitive functions. The research in the various areas of neuroscience deals with advanced imaging techniques, collecting an increasing amounts of heterogeneous and complex data at different scales. Then, computational tools and neuroinformatics solutions are required in order to integrate and analyze the massive quantity of acquired information. Within this context, the development of automaticmethods and tools for the study of neuronal anatomy has a central role. The morphological properties of the soma and of the axonal and dendritic arborizations constitute a key discriminant for the neuronal phenotype and play a determinant role in network connectivity. A quantitative analysis allows the study of possible factors influencing neuronal development, the neuropathological abnormalities related to specific syndromes, the relationships between neuronal shape and function, the signal transmission and the network connectivity. Therefore, three-dimensional digital reconstructions of soma, axons and dendrites are indispensable for exploring neural networks. This thesis proposes a novel and completely automatic pipeline for neuron reconstruction with operations ranging from the detection and segmentation of the soma to the dendritic arborization tracing. The pipeline can deal with different datasets and acquisitions both at the network and at the single scale level without any user interventions or manual adjustment. We developed an ad hoc approach for the localization and segmentation of neuron bodies. Then, various methods and research lines have been investigated for the reconstruction of the whole dendritic arborization of each neuron, which is solved both in 2D and in 3D images

Analysis of molecular forces transmitted by Talin during muscle development in vivo

The muscle-tendon system built during the development of an animal is essential to allow the body to move, breath or keep the heart beating for a lifetime. The muscle is the most important force producing tissue in an animal and, at the same time, it is also dependent on forces built up in the muscle-tendon tissue, especially during its development. Using the Drosophila musculature as a model system, it had been shown that tension is built up in the muscle-tendon tissue during development and that this tension is required for myofibrillogenesis, the process of building myofibrils, which are long chains of the contractile units of muscles called sarcomeres. The main focus of this thesis was to analyze how tension in tissues is transmitted across proteins at the molecular level to understand how proteins sense and respond to mechanical forces in vivo. As a model system, the developing Drosophila flight muscles were used that form in the pupal stage of the Drosophila life cycle. During development, these muscles attach to tendon cells and the connections between these two cells, called muscle attachment sites, need to bear the forces built up in the tissue. Muscle attachments are cell-extracellular matrix (ECM)-cell contacts that require receptor molecules in the cell membrane called integrins to connect the ECM between the cells with the contractile actin cytoskeleton inside the cells. Since integrins cannot directly connect to actin themselves, they require an adaptor protein called Talin that can bind to both integrin and actin filaments. Thus, Talin is in the ideal position to transmit and sense forces at muscle attachments. Previous studies on Talin force transduction demonstrated that Talin indeed bears forces in the piconewton (pN) range using Förster resonance energy transfer (FRET)-based molecular tension sensors. However, these studies were based on analyzing Talin in focal adhesions in cells cultured in vitro in an artificial environment. Therefore, we aimed to analyze Talin force transmission for the first time in vivo in the natural mechanical environment in the intact organism. In a first step, different FRET-based tension sensor modules and various control constructs were inserted in Drosophila into the endogenous talin (rhea) gene, taking advantage of the newly established clustered regularly interspaced short palindromic repeats/CRISPR-associated protein 9 (CRISPR/Cas9) system to achieve precise modification of the genome. After demonstrating that the Talin protein is still fully functional after insertion of the tension sensor modules, forces across Talin were first quantified—as a proof of concept—in primary muscle fibers in vitro using fluorescence lifetime imaging microscopy (FLIM) to measure FRET. In a second step, forces transmitted by Talin at muscle attachments during flight muscle development were analyzed in detail in living pupae. We discovered that a surprisingly small proportion of Talin molecules at developing muscle attachments transmit forces at the same time (Paper I). Nevertheless, a large pool of Talin molecules need to be recruited to muscle attachment sites during development, as quantified by fluorescence correlation spectroscopy (FCS), to prepare for the forces generated by active muscle contractions in the adult fly. If the accumulation of Talin at flight muscle attachments is reduced during development by RNA interference (RNAi), the muscle attachments rupture in young adults, likely during the first flight attempts. In conclusion, recruitment of a high number of Talin molecules during development is physiologically relevant to enable the muscle to adapt to sudden changes in tissue forces, likely by dynamically sharing the load among the Talin molecules. This mechanical adaptation concept is important to ensure that the muscle-tendon connections are stable and last for a lifetime. During the course of the thesis, I also discovered that flight muscles contract spontaneously during development. Characterization of these contractions in wild-type animals compared to a knockdown condition provided a functional readout for myofibrillogenesis during development (Paper IV). Furthermore, a review article on the role of mechanical forces during muscle development (Paper II) and a video article explaining how to perform in vivo imaging in Drosophila pupae (Paper III) were published

Renewable Energy

This book discusses renewable energy resources and systems as well as energy efficiency. It contains twenty-three chapters over six sections that address a multitude of renewable energy types, including solar and photovoltaic, biomass, hydroelectric, and geothermal. The information presented herein is a scientific contribution to energy and environmental regulations, quality and efficiency of energy services, energy supply security, energy market-based approaches, government interventions, and the spread of technological innovation

Lycium barbarum (wolfberry) polysaccharide facilitates ejaculatory behaviour in male rats

Poster Session AOBJECTIVE: Lycium barbarum (wolfberry) is a traditional Chinese medicine, which has been considered to have therapeutic effect on male infertility. However, there is a lack of studies support the claims. We thus investigated the effect of Lycium barbarum polysaccharide (LBP), a major component of wolfberry, on male rat copulatory behavior. METHOD: Sprague-Dawley rats were divided into two groups (n=8 for each group). The first group received oral feeding of LBP at dosage of 1mg/kg daily. The control group received vehicle (0.01M phosphate-buffered saline, served as control) feeding daily for 21 days. Copulatory tests were conducted at 7, 14 and 21 days after initiation of treatment. RESULTS: Compared to control animals, animals fed with 1mg/kg LBP showed improved copulatory behavior in terms of: 1. Higher copulatory efficiency (i.e. higher frequency to show intromission rather than mounting during the test), 2. higher ejaculation frequency and 3. Shorter ejaculation latency. The differences were found at all time points (Analyzed with two-tailed student’s t-test, p<0.05). There is no significant difference found between the two groups in terms of mount/intromission latency, which indicates no difference in time required for initiation of sexual activity. Additionally, no difference in mount frequency and intromission frequency was found. CONCLUSION: The present study provides scientific evidence for the traditional use of Lycium barbarum on male sexual behavior. The result provides basis for further study of wolfberry on sexual functioning and its use as an alternative treatment in reproductive medicine.postprintThe 30th Annual Meeting of the Australian Neuroscience Society, in conjunction with the 50th Anniversary Meeting of the Australian Physiological Society (ANS/AuPS 2010), Sydney, Australia, 31 January-3 February 2010. In Abstract Book of ANS/AuPS, 2010, p. 177, abstract no. POS-TUE-19

Models for reinforcement learning and design of a soft robot inspired by Drosophila larvae

Designs for robots are often inspired by animals, as they are designed mimicking animals’ mechanics, motions, behaviours and learning. The Drosophila, known as the fruit fly, is a well-studied model animal. In this thesis, the Drosophila larva is studied and the results are applied to robots. More specifically: a part of the Drosophila larva’s neural circuit for operant learning is modelled, based on which a synaptic plasticity model and a neural circuit model for operant learning, as well as a dynamic neural network for robot reinforcement learning, are developed; then Drosophila larva’s motor system for locomotion is studied, and based on it a soft robot system is designed. Operant learning is a concept similar to reinforcement learning in computer science, i.e. learning by reward or punishment for behaviour. Experiments have shown that a wide range of animals is capable of operant learning, including animal with only a few neurons, such as Drosophila. The fact implies that operant learning can establish without a large number of neurons. With it as an assumption, the structure and dynamics of synapses are investigated, and a synaptic plasticity model is proposed. The model includes nonlinear dynamics of synapses, especially receptor trafficking which affects synaptic strength. Tests of this model show it can enable operant learning at the neuron level and apply to a broad range of NNs, including feedforward, recurrent and spiking NNs. The mushroom body is a learning centre of the insect brain known and modelled for associative learning, but not yet for operant learning. To investigate whether it participates in operant learning, Drosophila larvae are studied with a transgenic tool by my collaborators. Based on the experiment and the results, a mushroom body model capable of operant learning is modelled. The proposed neural circuit model can reproduce the operant learning of the turning behaviour of Drosophila larvae. Then the synaptic plasticity model is simplified for robot learning. With the simplified model, a recurrent neural network with internal neural dynamics can learn to control a planar bipedal robot in a benchmark reinforcement learning task which is called bipedal walker by OpenAI. Benefiting efficiency in parameter space exploration instead of action space exploration, it is the first known solution to the task with reinforcement learning approaches. Although existing pneumatic soft robots can have multiple muscles embedded in a component, it is far less than the muscles in the Drosophila larva, which are well-organised in a tiny space. A soft robot system is developed based on the muscle pattern of the Drosophila larva, to explore the possibility to embed a high density of muscles in a limited space. Three versions of the body wall with pneumatic muscles mimicking the muscle pattern are designed. A pneumatic control system and embedded control system are also developed for controlling the robot. With a bioinspired body wall will a large number of muscles, the robot performs lifelike motions in experiments

Behavioral biology of mammalian reproduction and development for a space station

Space Station research includes two kinds of adaption to space: somatic (the adjustments made by an organism, within its lifetime, in response to local conditions), and transgenerational adaption (continuous exposure across sequential life cycles of genetic descendents). Transgenerational effects are akin to evolutionary process. Areas of a life Sciences Program in a space station address the questions of the behavioral biology of mammalian reproduction and development, using the Norway rat as the focus of experimentation

Evolutionary Computation 2020

Intelligent optimization is based on the mechanism of computational intelligence to refine a suitable feature model, design an effective optimization algorithm, and then to obtain an optimal or satisfactory solution to a complex problem. Intelligent algorithms are key tools to ensure global optimization quality, fast optimization efficiency and robust optimization performance. Intelligent optimization algorithms have been studied by many researchers, leading to improvements in the performance of algorithms such as the evolutionary algorithm, whale optimization algorithm, differential evolution algorithm, and particle swarm optimization. Studies in this arena have also resulted in breakthroughs in solving complex problems including the green shop scheduling problem, the severe nonlinear problem in one-dimensional geodesic electromagnetic inversion, error and bug finding problem in software, the 0-1 backpack problem, traveler problem, and logistics distribution center siting problem. The editors are confident that this book can open a new avenue for further improvement and discoveries in the area of intelligent algorithms. The book is a valuable resource for researchers interested in understanding the principles and design of intelligent algorithms