The Reciprocal Influences among Motivation,Personality Traits,and Game Habits for Playing Pokémon GO

This article reports a study exploring motivations of Pokémon Game use, individual differences related to personality traits, and game habits. First, it analyzed Pokémon GO motivations through exploratory factor analysis (EFA) by administering online the Pokémon GO Motivational Scale to a group of Italian gamers (N = 560). Successively, a Confirmatory Factor Analysis (CFA) was conducted testing three factorial models of Pokémon Game motivations on a selected random sample (N = 310). Results showed a three-factor model of Pokémon GO Game motivations (i.e. Personal Needs, Social Needs and Recreation), accounting for 68.9% of total variance plus a general higher order factor that best fits the data. Individual differences in Pokémon GO motivations and personality traits have been explored showing that high involved Pokémon GO players are introverted, low agreeableness, and conscientiousness people, driven by personal social and recreational needs. Reciprocal influences on motivational involvement, personality, and game habits were discussed.     

Enoxaparin in the prevention of deep venous thrombosis after major surgery: multicentric study. The Italian Study Group

Four hundred forty-six patients with Tourette Syndrome (TS) and/or their parents completed a 52-item self-report survey about vocal and motor tics, and the frequency of associated co-morbid conditions of aggression, obsessions and compulsions, attentional problems, sleep disturbance, mood disturbance, anxiety, and self-mutilative behaviours which have been frequently reported in the literature on TS. Respondents also responded to an open-ended question regarding the most disabling aspects of TS. Results were analyzed within two age groups; under 18 years of age (N = 245) and 18 years of age or older (N = 177). Tics and associated conditions were the most frequently reported disabling aspect by both age groups. Subjects under age 18, however, reported significantly more frequent problems with hyperactivity, temper control, aggressive behaviours and sleepwalking than adults with TS.     

The 70 kDa subunit of replication protein A is required for the G1/S and intra-S DNA damage checkpoints in budding yeast

The rfa1-M2 and rfa1-M4 Saccharomyces cerevisiae mutants, which are altered in the 70 kDa subunit of replication protein A (RPA) and sensitive to UV and methyl methane sulfonate (MMS), have been analyzed for possible checkpoint defects. The G1/S and intra-S DNA damage checkpoints are defective in the rfa1-M2 mutant, since rfa1-M2 cells fail to properly delay cell cycle progression in response to UV irradiation in G1 and MMS treatment during S phase. Conversely, the G2/M DNA damage checkpoint and the S/M checkpoint are proficient in rfa1-M2 cells and all the checkpoints tested are functional in the rfa1-M4 mutant. Preventing S phase entry by alpha-factor treatment after UV irradiation in G1 does not change rfa1-M4 cell lethality, while it allows partial recovery of rfa1-M2 cell viability. Therefore, the hypersensitivity to UV and MMS treatments observed in the rfa1-M4 mutant might only be due to impairment of RPA function in DNA repair, while the rfa1-M2 mutation seems to affect both the DNA repair and checkpoint functions of Rpa70.     

On the evolution of homogeneous two-robot teams: clonal versus aclonal approaches

This study compares two different evolutionary approaches (clonal and aclonal) to the design of homogeneous two-robot teams (i.e. teams of morphologically identical agents with identical controllers) in a task that requires the agents to specialise to different roles. The two approaches differ mainly in the way teams are formed during evolution. In the clonal approach, a team is formed from a single genotype within one population of genotypes. In the aclonal approach, a team is formed from multiple genotypes within one population of genotypes. In both cases, the goal is the synthesis of individual generalist controllers capable of integrating role execution and role allocation mechanisms for a team of homogeneous robots. Our results diverge from those illustrated in a similar comparative study, which supports the superiority of the aclonal versus the clonal approach. We question this result and its theoretical underpinning, and we bring new empirical evidence showing that the clonal outperforms the aclonal approach in generating homogeneous teams required to dynamically specialise for the benefit of the team. The results of our study suggest that task-specific elements influence the evolutionary dynamics more than the genetic relatedness of the team members. We conclude that the appropriateness of the clonal approach for role allocation scenarios is mainly determined by the specificity of the collective task, including the evaluation function, rather than by the way in which the solutions are evaluated during evolution.     

Geiringer theorems: from population genetics to computational intelligence, memory evolutive systems and Hebbian learning

The classical Geiringer theorem addresses the limiting frequency of occurrence of various alleles after repeated application of crossover. It has been adopted to the setting of evolutionary algorithms and, a lot more recently, reinforcement learning and Monte-Carlo tree search methodology to cope with a rather challenging question of action evaluation at the chance nodes. The theorem motivates novel dynamic parallel algorithms that are explicitly described in the current paper for the first time. The algorithms involve independent agents traversing a dynamically constructed directed graph that possibly has loops and multiple edges. A rather elegant and profound category-theoretic model of cognition in biological neural networks developed by a well-known French mathematician, professor Andree Ehresmann jointly with a neurosurgeon, Jan Paul Vanbremeersch over the last thirty years provides a hint at the connection between such algorithms and Hebbian learning.     

Combining stochastic programming and optimal control to decompose multistage stochastic optimization problems

The paper suggests a possible cooperation between stochastic programming and optimal control for the solution of multistage stochastic optimization problems. We propose a decomposition approach for a class of multistage stochastic programming problems in arborescent form (i.e. formulated with implicit non-anticipativity constraints on a scenario tree). The objective function of the problem can be either linear or nonlinear, while we require that the constraints are linear and involve only variables from two adjacent periods (current and lag 1). The approach is built on the following steps. First, reformulate the stochastic programming problem into an optimal control one. Second, apply a discrete version of Pontryagin maximum principle to obtain optimality conditions. Third, discuss and rearrange these conditions to obtain a decomposition that acts both at a time stage level and at a nodal level. To obtain the solution of the original problem we aggregate the solutions of subproblems through an enhanced mean valued fixed point iterative scheme.     

On the second-order sliding mode control of nonlinear systems with uncertain control direction

This note deals with the implementation of a second-order sliding mode control algorithm for a class of nonlinear systems in which the sign of the high-frequency gain, though constant, is unknown. A specific second-order sliding mode control algorithm, the “Suboptimal” algorithm, is properly modified in order to face the uncertainty in the control direction. It is shown that after a finite time the uncertain sign is identified and the standard finite time convergence takes place from that time on. Simulation results are provided.     

Contact force regulation in wire-actuated pantographs via variable structure control and frequency-domain techniques

One of the main problems in high-speed-train transportation systems is related to the current collection quality, that can dramatically decrease because of oscillations of the pantograph-catenary system. This problem has been addressed by means of active pantographs. In this paper we present some results about the possible implementation of variable structure control (VSC) techniques on a wire actuated symmetric pantograph. Such an actuator was suggested in the literature as a viable solution to building an active pantograph by modifying a passive pantograph currently used by Italian Railways. The use of VSC with sliding modes was considered in order to cope with the system uncertainties due to the overhead suspended catenary. Recent results about the frequency-based analysis of VSC systems featuring second-order sliding modes are exploited to avoid the performance-destroying effect of the resonant wire actuator and to get a continuous control force without using observers. We show by simulations that the contact force results are very close to the desired set-point also in the presence of measurement noise.