The dynamic nearest neighbor policy for the multi-vehicle pick-up and delivery problem

In this paper, a dynamic nearest neighbor (DNN) policy is proposed for operating a fleet of vehicles to serve customers, who place calls in a Euclidean service area according to a Poisson process. Each vehicle serves one customer at a time, who has a distinct origin and destination independently and uniformly distributed within the service area. The new DNN policy is a refined version of the nearest neighbor (NN) policy that is well known to perform sub-optimally when the frequency of customer requests is high. The DNN policy maintains geographically closest customer-to-vehicle assignments, due to its ability to divert/re-assign vehicles that may be already en-route to pick up other customers, when another vehicle becomes available or a new customer call arrives. Two other pertinent issues addressed include: the pro-active deployment of the vehicles by anticipating in which regions of the service area future calls are more likely to arise; and, imposition of limits to avoid prohibitively long customer wait times. The paper also presents accurate approximations for all the policies compared. Extensive simulations, some of which are included herein, clearly show the DNN policy to be tangibly superior to the first-comefirst-served (FCFS) and NN policies

A Distorted Body Image: Cognitive Behavioral Therapy for Body Dysmorphic Disorder

Body dysmorphic disorder (BDD) is one of the mental disorders that warrant more research due to the current challenges and complexity of human life. A search through Medline, Academic Search Premier, PsycINFO, and PsyArticles, using “body dysmorphic disorder” and “intervention” keywords, showed that a total of 186 articles had been published for the past 25 years. BDD was added to the obsessive-compulsive and related disorder spectrum in the Diagnostic and Statistical Manual of Mental Disorder-5 (2013). BDD is a preoccupation with an imagined defect in physical appearance by individual who looks normal which causes low self-esteem and co-morbids with other mental health problems. Individuals with BDD often end up with dermatological treatment and cosmetic surgery. However, in most cases, they frequently experience a dissatisfaction with the results and worsen the individual condition. Therefore, psychological intervention is needed to treat individuals with BDD to combat their negative perceptions on physical appearance. Research has shown that one of the effective interventions in treating individuals with BDD is cognitive behavioral therapy (CBT). Some techniques that are recommended are psychoeducation, restructuring cognitive, exposure and ritual prevention, and others. This paper aims to discuss the clinical diagnosis and CBT intervention as a treatment for individual with BDD

Automating commercial video game development using computational intelligence

Problem statement: The retail sales of computer and video games have grown enormously during the last few years, not just in United States (US), but also all over the world. This is the reason a lot of game developers and academic researchers have focused on game related technologies, such as graphics, audio, physics and Artificial Intelligence (AI) with the goal of creating newer and more fun games. In recent years, there has been an increasing interest in game AI for producing intelligent game objects and characters that can carry out their tasks autonomously. Approach: The aim of this study is an attempt to create an autonomous intelligent controller to play the game with no human intervention. Our approach is to use a simple but powerful evolutionary algorithm called Evolution Strategies (ES) to evolve the connection weights and biases of feed-forward Artificial Neural Networks (ANN) and to examine its learning ability through computational experiments in a non-deterministic and dynamic environment, which is the well-known arcade game, called Ms. Pac-man. The resulting algorithm is referred to as an Evolution Strategies Neural Network or ESNet. Results: The comparison of ESNet with two random systems, Random Direction (RandDir) and Random Neural Network (RandNet) yields promising results. The contribution of this work also focused on the comparison between the ESNet with different mutation probabilities. The results show that ESNet with a high probability with high mean scores recorded compared to the mean scores of RandDir, RandNet and ESNet with a low probability. Conclusion: Overall, the proposed algorithm has a very good performance with a high probability of automatically generating successful game AI controllers for the video game

Phospholipase A2 regulation of bovine endometrial (BEND) cell prostaglandin production

Background Prostaglandins (PG), produced by the uterine endometrium, are key regulators of several reproductive events, including estrous cyclicity, implantation, pregnancy maintenance and parturition. Phospholipase A2 (PLA2) catalyzes the release of arachidonic acid from membrane phospholipids, the rate-limiting step in PG biosynthesis. The bovine endometrial (BEND) cell line has served as a model system for investigating regulation of signaling mechanisms involved in uterine PG production but information concerning the specific PLA2 enzymes involved and their role in regulation of this process is limited. The objectives of this investigation were to evaluate the expression and activities of calcium-dependent group IVA (PLA2G4A) and calcium-independent group VI (PLA2G6) enzymes in the regulation of BEND cell PG production. Methods Cells were grown to near-confluence and treated with phorbol 12, 13 dibutyrate (PDBu), interferon-tau (IFNT), the PLA2G4A inhibitor pyrrolidine-1 (PYR-1), the PLA2G6 inhibitor bromoenol lactone (BEL) and combinations of each. Concentrations of PGF2alpha and PGE2 released into the medium were determined. Western blot analysis was performed on cellular protein to determine effects of treatment on expression of PLA2G4A, PLA2G6 and PLA2G4C. PLA2 assays were performed on intact cells by measuring arachidonic acid and linoleic acid release and group-specific PLA2 activity assays were performed on cell lysates. Results BEND cells produced about 10-fold more PGE2 than PGF2alpha under resting conditions. Production of both PGs increased significantly in response to PDBu-stimulation. PYR-1 significantly diminished production of both PGs by resting cells and abolished the stimulatory effect of PDBu. BEL stimulated production of both PGs. IFNT reduced both PGE2 and PGF2alpha production by resting cells and diminished PDBu stimulation of PG production. Conversely, IFNT did not significantly reduce BEL stimulation of PG production. Cellular expression of PLA2G4A was enhanced by PDBu and this response was diminished by IFNT. Expression of PLA2G6 was not observed to be affected by treatments and no PLA2G4C expression was observed. Arachidonic acid release from intact cells was significantly increased by PDBu and this effect was attenuated by PYR-1 but not by BEL. Release of linoleic acid from intact cells was stimulated by PDBu and inhibited by BEL but not PYR-1. Group specific PLA2-activity assays demonstrated both PLA2G4A and PLA2G6 activity. Conclusion Results from this study demonstrate that PGE2 and PGF2-alpha production by BEND cells is mediated by the activity and expression of PLA2G4A. Interferon-tau treatment diminished expression of PLA2G4A and PG production. BEND cells were shown to express PLA2G6 but, unlike primary or early passage luminal bovine endometrial cells, stimulation of PLA2G6 activity was not associated with increased PG production

Distinct phospholipase A2 enzymes regulate prostaglandin E2 and F2alpha production by bovine endometrial epithelial cells

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Polycyclic aromatic hydrocarbons present in cigarette smoke cause endothelial cell apoptosis by a phospholipase A2dependent mechanism

Smoking is a major risk factor for endothelial cell injury and subsequent coronary artery disease. Epidemiological studies implicate the phospholipase A2/arachidonic acid cascade in the mechanism by which smoking causes heart disease. However, specific components of cigarette smoke that activate this pathway have not been identified. The purpose of this study was to investigate the effects of polycyclic aromatic hydrocarbons contained in cigarette smoke on phospholipase A2 (PLA2) activity and apoptosis of human coronary artery endothelial cells. 1methylanthracene (1â MA), phenanthrene (PA), and benzo(a)pyrene (B(a)P) caused significant release of 3Hâ arachidonate from endothelial cells. 1â MA and PA, but not B(a)P, also caused significant release of 3Hâ linoleic acid. Release of fatty acids from membrane phospholipids preceded the onset of apoptosis. 3Hâ arachidonate release and apoptosis induced by 1â MA, B(a)P, and PA were inhibited by methylarachidonoylâ fluorophosphonate, an inhibitor of Groups IV and VI PLA2s. Bromoenol lactone, an inhibitor of Group VI enzymes, inhibited both 3Hâ arachidonate release and apoptosis induced by 1â MA and PA, but not B(a)P. MJ33, an inhibitor of the acidic calciumâ independent PLA2, attenuated 3Hâ arachidonate release and apoptosis by PA, but not 1MA or B(a)P. The presence of Groups IV and VI and the acidic iPLA2 in endothelial cells was demonstrated by reverse transcriptaseâ polymerase chain reaction and Western analysis. These data suggest that 1â MA, B(a)P and PA induce apoptosis of endothelial cells by a mechanism that involves activation of these three distinct isoforms of PLA2.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/154505/1/fsb2fasebj16110092-sup-0001.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154505/2/fsb2fasebj16110092.pd

Nature-Inspired cognitive evolution to play Ms. Pac-Man

Recent developments in nature-inspired computation have heightened the need for research into the three main areas of scientific, engineering and industrial applications. Some approaches have reported that it is able to solve dynamic problems and very useful for improving the performance of various complex systems. So far however, there has been little discussion about the effectiveness of the application of these models to computer and video games in particular. The focus of this research is to explore the hybridization of nature-inspired computation methods for optimization of neural network-based cognition in video games, in this case the combination of a neural network with an evolutionary algorithm. In essence, a neural network is an attempt to mimic the extremely complex human brain system, which is building an artificial brain that is able to self-learn intelligently. On the other hand, an evolutionary algorithm is to simulate the biological evolutionary processes that evolve potential solutions in order to solve the problems or tasks by applying the genetic operators such as crossover, mutation and selection into the solutions. This paper investigates the abilities of Evolution Strategies (ES) to evolve feed-forward artificial neural network’s internal parameters (i.e. weight and bias values) for automatically generating Ms. Pac-man controllers. The main objective of this game is to clear a maze of dots while avoiding the ghosts and to achieve the highest possible score. The experimental results show that an ES-based system can be successfully applied to automatically generate artificial intelligence for a complex, dynamic and highly stochastic video game environment

Pareto Ensembles for evolutionary Synthesis of Neurocontrollers in a 2D Maze-based video game

In this paper, we present a study of evolving artificial neural network controllers for autonomously playing maze-based video game. A system using multi-objective evolutionary algorithm is developed, which is called as Pareto Archived Evolution Strategy Neural Network(PAESNet), with the attempt to find a set of Pareto optimal solutions by simultaneously optimizing two conflicting objectives. The experiments are designed to address two research aims investigating: (1) evolving weights (including biases) of the connections between the neurons and structure of the network through multi-objective evolutionary algorithm in order to reduce its runtime operation and complexity, (2) improving the generalization ability of the networks by using neural network ensemble model. A comparative analysis between the single network model as the baseline system and the model built based on the neural ensemble are presented. The evidence from this study suggests that Pareto multi-objective paradigm and neural network ensembles can be effective for creating and controlling the behaviors of video game characters

Polysialylated NCAM and EphrinA/EphA regulate synaptic development of gabaergic interneurons in prefrontal cortex

A novel function for the neural cell adhesion molecule (NCAM) was identified in ephrinA/EphA-mediated repulsion as an important regulatory mechanism for development of GABAergic inhibitory synaptic connections in mouse prefrontal cortex. Deletion of NCAM, EphA3, or ephrinA2/3/5 in null mutant mice increased the numbers and size of perisomatic synapses between GABAergic basket interneurons and pyramidal cells in the developing cingulate cortex (layers II/III). A functional consequence of NCAM loss was increased amplitudes and faster kinetics of miniature inhibitory postsynaptic currents in NCAM null cingulate cortex. NCAM and EphA3 formed a molecular complex and colocalized with the inhibitory presynaptic marker vesicular GABA transporter (VGAT) in perisomatic puncta and neuropil in the cingulate cortex. EphrinA5 treatment promoted axon remodeling of enhanced green fluorescent protein-labeled basket interneurons in cortical slice cultures and induced growth cone collapse in wild-type but not NCAM null mutant neurons. NCAM modified with polysialic acid (PSA) was required to promote ephrinA5-induced axon remodeling of basket interneurons in cortical slices, likely by providing a permissive environment for ephrinA5/EphA3 signaling. These results reveal a new mechanism in which NCAM and ephrinAs/EphA3 coordinate to constrain GABAergic interneuronal arborization and perisomatic innervation, potentially contributing to excitatory/inhibitory balance in prefrontal cortical circuitry. © 2012 The Author