The time evaluation of resistance probability of a closed community against to occupation in a Sznajd like model with synchronous updating: A numerical study

In the present paper, we have briefly reviewed Sznajd's sociophysics model and its variants, and also we have proposed a simple Sznajd like sociophysics model based on Ising spin system in order to explain the time evaluation of resistance probability of a closed community against to occupation. Using a numerical method, we have shown that time evaluation of resistance probability of community has a non-exponential character which decays as stretched exponential independent the number of soldiers in one dimensional model. Furthermore, it has been astonishingly found that our simple sociophysics model is belong to the same universality class with random walk process on the trapping space.Comment: 12 pages, 5 figures. Added a paragraph and 1 figure. To be published in International Journal of Modern Physics

Synchronization in Complex Systems Following the Decision Based Queuing Process: The Rhythmic Applause as a Test Case

Living communities can be considered as complex systems, thus a fertile ground for studies related to their statistics and dynamics. In this study we revisit the case of the rhythmic applause by utilizing the model proposed by V\'azquez et al. [A. V\'azquez et al., Phys. Rev. E 73, 036127 (2006)] augmented with two contradicted {\it driving forces}, namely: {\it Individuality} and {\it Companionship}. To that extend, after performing computer simulations with a large number of oscillators we propose an explanation on the following open questions (a) why synchronization occurs suddenly, and b) why synchronization is observed when the clapping period ($T_c$) is $1.5 \cdot T_s < T_c < 2.0 \cdot T_s$ ($T_s$ is the mean self period of the spectators) and is lost after a time. Moreover, based on the model, a weak preferential attachment principle is proposed which can produce complex networks obeying power law in the distribution of number edges per node with exponent greater than 3.Comment: 16 pages, 5 figure

Quantitative identification of functional connectivity disturbances in neuropsychiatric lupus based on resting-state fMRI: a robust machine learning approach

Neuropsychiatric systemic lupus erythematosus (NPSLE) is an autoimmune entity comprised of heterogenous syndromes affecting both the peripheral and central nervous system. Research on the pathophysiological substrate of NPSLE manifestations, including functional neuroimaging studies, is extremely limited. The present study examined person-specific patterns of whole-brain functional connectivity in NPSLE patients (n = 44) and age-matched healthy control participants (n = 39). Static functional connectivity graphs were calculated comprised of connection strengths between 90 brain regions. These connections were subsequently filtered through rigorous surrogate analysis, a technique borrowed from physics, novel to neuroimaging. Next, global as well as nodal network metrics were estimated for each individual functional brain network and were input to a robust machine learning algorithm consisting of a random forest feature selection and nested cross-validation strategy. The proposed pipeline is data-driven in its entirety, and several tests were performed in order to ensure model robustness. The best-fitting model utilizing nodal graph metrics for 11 brain regions was associated with 73.5% accuracy (74.5% sensitivity and 73% specificity) in discriminating NPSLE from healthy individuals with adequate statistical power. Closer inspection of graph metric values suggested an increased role within the functional brain network in NSPLE (indicated by higher nodal degree, local efficiency, betweenness centrality, or eigenvalue efficiency) as compared to healthy controls for seven brain regions and a reduced role for four areas. These findings corroborate earlier work regarding hemodynamic disturbances in these brain regions in NPSLE. The validity of the results is further supported by significant associations of certain selected graph metrics with accumulated organ damage incurred by lupus, with visuomotor performance and mental flexibility scores obtained independently from NPSLE patients. View Full-Text Keywords: neuropsychiatric systemic lupus erythematosus; rs-fMRI; graph theory; functional connectivity; surrogate data; machine learning; visuomotor ability; mental flexibilit

Changing memories by interference: the effect of emotional dimensions in reconsolidation of episodic memories

Episodes with an emotional component preoccupy memory formation and this advantage facilitates their preservation and mitigates the impact of interfering episodes. The present study examined the relation of the emotional dimensions of original and interfering episodes to the memory outcome, using a reconsolidation paradigm. In a between-subjects design, 102 healthy young adults were presented with an emotional or neutral image and learned either an emotional or neutral story, respectively (day 1). On day 2, experimental groups were presented with an image of the opposite emotionality, reactivated the original story, and learned a story of the opposite emotionality. On day 3, experimental and control groups were tested for their memory on target and filler clues of the original story and rated both stories for arousal and valence. Overall, there was evidence of interference on the long-term retention of target clues only for the neutral story (i.e. when the interfering story was emotional), and of filler clues for both types of stories. Moreover, individual target clue retention rates correlated with the arousal ratings for both the original neutral story and the interfering emotional story, while they were not related to arousal ratings for the original emotional story or the interfering neutral one

Patterns of variability in voice onset time: a developmental study of motor speech skills in humans

This study investigated the developmental patterns of variability in the speech parameter voice onset time (VOT) in forty six children. Five groups of children participated in the study as follows: i) Group 1 - aged 5 years 8 months (n=6); ii) Group 2 - 7 years 10 months (n=10); iii) Group 3 - 9 years 10 months (n=10); iv) Group 4 - 11 years 10 months (n=10), and v) Group 5 - 13 years 2 months (n=10). Coefficient of variation (COV) values were examined for the VOT values of both "voiceless" (/p t k/) and "voiced" (/b d g/) plosives to determine patterns of variability. Significant effects of age were revealed for both the voiceless and voiced plosives, and levels of variability leveled off for Group 4. The data suggest that although variability in VOT decreases with age, the presence of residual variability may be a prerequisite for the further refinement of motor speech skills

Hormones and temporal components of speech: sex differences and effects of menstrual cyclicity on speech

Voice onset time (VOT) is a salient acoustic parameter of speech which signals the “voiced” and “voiceless” status of plosives in English (e.g. the initial sound in ‘bat’ vs. the initial sound in ‘pat’). As a micro-temporal acoustic parameter, VOT may be sensitive to changes in hormones which may affect the neuromuscular systems involved in speech production. This study adopted a novel approach by investigating the effects of menstrual cycle phase and sex on VOT. VOT data representing the 6 plosives of English (/p b t d k g/) were examined for 7 women (age 20-23 years) at two phases of the menstrual cycle (day 18-25: High Estrogen and Progesterone; day 2-5: Low Estrogen and Progesterone). Results indicated that menstrual cycle phase had a significant interaction with the identity of the plosive (F (5,30) = 5.869, P .05), or the contrast between voiced and voiceless cognates (F (1,10) = .407, P > .05). In contrast, the high hormone phase VOT samples displayed significant plosive by sex interactions (F (5,50) = 4.442, P < .005). In addition, significant sex differences were found for the contrasts between cognate voiced and voiceless plosives (F (1,10) = 5.019, P < .05); the women displayed a more marked voiced/voiceless contrast. The findings suggest that ovarian hormones play some role in shaping some temporal components of speech

Overview on mixed integer nonlinear programming problems

Many optimization problems involve integer and continuous variables that can be modeled as mixed integer nonlinear programming (MINLP) problems. This has led to a wide range of applications, in particular in some engineering areas. Here, we provide a brief overview on MINLP, and present a simple idea for a future nonconvex MINLP solution technique.Fundação para a Ciência e a Tecnologia (FCT