Strong Attractors of Hopfield Neural Networks to Model Attachment Types and Behavioural Patterns

Abstract — We study the notion of a strong attractor of a Hopfield neural model as a pattern that has been stored multiple times in the network, and examine its properties using basic mathematical techniques as well as a variety of simulations. It is proposed that strong attractors can be used to model attachment types in developmental psychology as well as behavioural patterns in psychology and psychotherapy. We study the stability and basins of attraction of strong attractors in the presence of other simple attractors and show that they are indeed more stable with a larger basin of attraction compared with simple attractors. We also show that the perturbation of a strong attractor by random noise results in a cluster of attractors near the original strong attractor measured by the Hamming distance. We investigate the stability and basins of attraction of such clusters as the noise increases and establish that the unfolding of the strong attractor, leading to its breakup, goes through three different stages. Finally the relation between strong attractors of different multiplicity and their influence on each other are studied and we show how the impact of a strong attractor can be replaced with that of a new strong attractor. This retraining of the network is proposed as a model of how attachment types and behavioural patterns can undergo change. I

A pilot study to evaluate the efficacy of self-attachment to treat chronic anxiety and/or depression in Iranian women

The aim of this pilot study was to evaluate the efficacy of the new Self-Attachment Technique (SAT) in treating resistant anxiety and depression, lasting at least three years, among Iranian women from different social backgrounds. In this intervention, the participant, using their childhood photos, imaginatively creates an affectional bond with their childhood self, vows to consistently support and lovingly re-raise this child to emotional well-being. We conducted a longitudinal study with repeated measurement to evaluate the efficacy of SAT using ANOVA. Thirty-eight women (N=30) satisfying the inclusion and exclusion criteria were recruited from different parts of Tehran. To describe the SAT protocols, a total of eight one-to-one sessions were offered to the recruits, the first four were weekly while the last four were fortnightly. The participants were expected to practice the protocols for twenty minutes twice a day. Two questionnaires, GAD-7 and PHQ-9, were used to measure anxiety and depression levels before and after the intervention and in a three-month follow-up. Thirty women completed the course. The change in the anxiety level between the pre-test and the post-test was significant at p<0.001 with effect size 2.6. The change in anxiety between pre-test and follow-up test was also significant at p<0.001 with effect size 3.0 respectively. The change in anxiety between the post-test and the follow-up was significant at p<0.05 with effect size 0.6. For depression, the change between the pre-test and the post-test or the follow-up was significant at p<0.001 with effect size 2.5 for each

Behaviour of GFRP-steel reinforced I shape beams with steel fibers as shear reinforcement

This paper evaluates the possibility of developing prefabricated beams without stirrups by using fiber reinforcement for increasing the concrete shear capacity, and a hybrid flexural reinforcement system composed of glass fiber reinforced polymer (GFPR) and steel rebars. A high compressive strength and high post-cracking tensile capacity steel fiber reinforced self-compacting concrete (SFRSCC) was developed, aiming at supressing the need of steel stirrups in this type of beams while providing sufficient ductility for structural applications. The experimental results were analysed in terms of failure mode, deformational and cracking behaviour, as well as load carrying capacity. A constitutive model, capable of simulating three types of material nonlinearities simultaneously in an integration point (IP), was used and its predictive performance was assessed by simulating the experimental tests. The numerical approach was then used to assess the potentialities of this material system and structural concept when applied to relatively large span beams.The authors wish to acknowledge the funding provided by project FOATIDE, reference POCI-01- 0145-FEDER-028112

Orbits and phase transitions in the multifractal spectrum

We consider the one dimensional classical Ising model in a symmetric dichotomous random field. The problem is reduced to a random iterated function system for an effective field. The D_q-spectrum of the invariant measure of this effective field exhibits a sharp drop of all D_q with q < 0 at some critical strength of the random field. We introduce the concept of orbits which naturally group the points of the support of the invariant measure. We then show that the pointwise dimension at all points of an orbit has the same value and calculate it for a class of periodic orbits and their so-called offshoots as well as for generic orbits in the non-overlapping case. The sharp drop in the D_q-spectrum is analytically explained by a drastic change of the scaling properties of the measure near the points of a certain periodic orbit at a critical strength of the random field which is explicitly given. A similar drastic change near the points of a special family of periodic orbits explains a second, hitherto unnoticed transition in the D_q-spectrum. As it turns out, a decisive role in this mechanism is played by a specific offshoot. We furthermore give rigorous upper and/or lower bounds on all D_q in a wide parameter range. In most cases the numerically obtained D_q coincide with either the upper or the lower bound. The results in this paper are relevant for the understanding of random iterated function systems in the case of moderate overlap in which periodic orbits with weak singularity can play a decisive role.Comment: The article has been completely rewritten; the title has changed; a section about the typical pointwise dimension as well as several references and remarks about more general systems have been added; to appear in J. Phys. A; 25 pages, 11 figures, LaTeX2

Computational modelling of wound healing insights to develop new treatments

About 1% of the population will suffer a severe wound during their life. Thus, it is really important to develop new techniques in order to properly treat these injuries due to the high socioeconomically impact they suppose. Skin substitutes and pressure based therapies are currently the most promising techniques to heal these injuries. Nevertheless, we are still far from finding a definitive skin substitute for the treatment of all chronic wounds. As a first step in developing new tissue engineering tools and treatment techniques for wound healing, in silico models could help in understanding the mechanisms and factors implicated in wound healing. Here, we review mathematical models of wound healing. These models include different tissue and cell types involved in healing, as well as biochemical and mechanical factors which determine this process. Special attention is paid to the contraction mechanism of cells as an answer to the tissue mechanical state. Other cell processes such as differentiation and proliferation are also included in the models together with extracellular matrix production. The results obtained show the dependency of the success of wound healing on tissue composition and the importance of the different biomechanical and biochemical factors. This could help to individuate the adequate concentration of growth factors to accelerate healing and also the best mechanical properties of the new skin substitute depending on the wound location in the body and its size and shape. Thus, the feedback loop of computational models, experimental works and tissue engineering could help to identify the key features in the design of new treatments to heal severe wounds

Numerical Model‐Software for Predicting Rock Formation Failure‐Time Using Fracture Mechanics

Real‐time integrated drilling is an important practice for the upstream petroleum industry. Traditional pre‐drill models, tend to offset the data gathered from the field since information obtained prior to spudding and drilling of new wells often become obsolete due to the changes in geology and geomechanics of reservoir‐rocks or formations. Estimating the complicated non‐linear failure‐time of a rock formation is a difficult but important task that helps to mitigate the effects of rock failure when drilling and producing wells from the subsurface. In this study, parameters that have the strongest impact on rock failure were used to develop a numerical and computational model for evaluating wellbore instability in terms of collapse, fracture, rock strength and failure‐time. This approach presents drilling and well engineers with a better understanding of the fracture mechanics and rock strength failureprediction procedure required to reduce stability problems by forecasting the rock/formation failuretime. The computational technique built into the software, uses the stress distribution around a rock formation as well as the rock’s responses to induced stress as a means of analyzing the failure time of the rock. The results from simulation show that the applied stress has the most significant influence on the failure‐time of the rock. The software also shows that the failure‐time varied over several orders of magnitude for varying stress‐loads. Thus, this will help drilling engineers avoid wellbore failure by adjusting the stress concentration properly through altering the mud pressure and well orientation with respect to in‐situ stresses. As observed from the simulation results for the failure time analysis, the trend shows that the time dependent strength failure is not just a function of the applied stress. Because, at applied stress of 6000–6050 psi there was time dependent failure whereas, at higher applied stress of 6350–6400 psi there was no time dependent strength failure

CD8+ T Cells as a Source of IFN-γ Production in Human Cutaneous Leishmaniasis

Cutaneous leishmaniasis (CL) is usually a self-healing skin lesion caused by different species of Leishmania parasite. Resistance and susceptibility of mice to Leishmania major infection is associated with two types of CD4+ T lymphocytes development: Th1 type response with production of cytokine IFN-γ is associated with resistance, whereas Th2 type response with production of cytokines IL-4 and IL-5 is associated with susceptibility. A clear Th1/Th2 dichotomy similar to murine model is not defined in human leishmaniasis and we need as much information as possible to define marker(s) of protection. We purified CD4+/CD8+ T cells, stimulated them with Leishmania antigens and analysed gene and protein expression of Th1/Th2 cytokines in volunteers with a history of self-healing CL who are presumed to be protected against further Leishmania infection. We have seen significant upregulation of IFN-γ gene expression and high IFN-γ production in the Leishmania stimulated CD4+ T cells and CD8+ T cells. We concluded that both antigen-specific IFN-γ producing CD4+ Th1 cells and IFN-γ producing CD8+ T cells contribute to the long term protection in individuals with a history of CL. This proves the importance of CD8+ T cells as a source of IFN-γ in Th1-like immune responses

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Melatonin improves sleep quality in hemodialysis patients

Disturbed sleep is common in end-stage renal disease (ESRD). Exogenous melatonin has somniferous properties in normal subjects and can improve sleep quality (SQ) in several clinical conditions. Recent studies have shown that melatonin may play a role in improving sleep in patients undergoing dialysis. The goal of the present study was to assess the effect of exogenous melatonin administration on SQ improvement in daytime hemodialysis patients. Lipid profile and the required dose of erythropoietin (EPO) are also reported as secondary outcomes. In a 6-week randomized, double-blind cross-over clinical trial, 3 mg melatonin or placebo was administered to 68 patients at bedtime. A 72-h washout preceded the switch from melatonin to placebo, or vice versa. SQ was assessed by the Pittsburgh sleep quality index (PSQI). Sixty-eight patients completed the study protocol and were included in the final analysis. Melatonin treatment significantly improved the global PSQI scores ( P < 0.001), particularly subjective SQ ( P < 0.001), sleep efficiency ( P = 0.005) and sleep duration ( P < 0.001). No differences in sleep latency and daytime sleepiness were observed. Melatonin also increased the high-density lipoprotein (HDL) cholesterol ( P = 0.003). The need for EPO prescription decreased after melatonin treatment ( P < 0.001). We conclude that melatonin can improve sleep in ESRD. The modest increase in HDL cholesterol and decrease in the EPO requirement are other benefits associated with this treatmen