The automatic layout model in the sequencing of construction activities of multi-objective diaphragm wall unit by using self-learning neural network

Foundation construction process has been an important key point in a successful construction engineering. The frequency of using diaphragm wall construction method among many deep excavation construction methods in Taiwan is the highest in the world. The traditional view of managing diaphragm wall unit in the sequencing of construction activities is to establish each phase of the sequencing of construction activities by heuristics. However, it conflicts final phase of engineering construction with unit construction and effects planning construction time. In order to avoid this kind of situation, we use management of science in the study of diaphragm wall unit construction to formulate multi-objective combinational optimization problem. Because the characteristic (belong to NP-Complete problem) of problem mathematic model is multi-objective and combining explosive, it is advised that using the 2-type Self-Learning Neural Network (SLNN) to solve the N=12, 24, 36 of diaphragm wall unit in the sequencing of construction activities program problem. In order to compare the liability of the results, this study will use random researching method in comparison with the SLNN. It is found that the testing result of SLNN is superior to random researching method in whether solution-quality or Solving-efficiency.

Attention through self-synchronisation in the spiking neuron stochastic diffusion network

The paper discusses ensemble behaviour in the Spiking Neuron Stochastic Diffusion Network, SNSDN, a novel network exploring biologically plausible information processing based on higher order temporal coding. SNSDN was proposed as an alternative solution to the binding problem [1]. SNSDN operation resembles Stochastic Diffusin on Search, SDS, a non-deterministic search algorithm able to rapidly locate the best instantiation of a target pattern within a noisy search space ([3], [5]). In SNSDN, relevant information is encoded in the length of interspike intervals. Although every neuron operates in its own time, ‘attention’ to a pattern in the search space results in self-synchronised activity of a large population of neurons. When multiple patterns are present in the search space, ‘switching of at- tention’ results in a change of the synchronous activity. The qualitative effect of attention on the synchronicity of spiking behaviour in both time and frequency domain will be discussed.

Oriented texture classification based on self-organizing neural network and Hough transform

This paper presents a technique for oriented texture classification which is based on the Hough transform and Kohonen's neural network model. In this technique, oriented texture features are extracted from the Hough space by means of two distinct strategies. While the first operates on a non-uniformly sampled Hough space, the second concentrates on the peaks produced in the Hough space. The described technique gives good results for the classification of oriented textures, a common phenomenon in nature underlying an important class of images. Experimental results are presented to demonstrate the performance of the new technique in comparison, with an implemented technique based on Gabor filters.

Synchronization enhancement via an oscillatory bath in a network of self-excited cells

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Complex network classification using partially self-avoiding deterministic walks

Complex networks have attracted increasing interest from various fields of science. It has been demonstrated that each complex network model presents specific topological structures which characterize its connectivity and dynamics. Complex network classification relies on the use of representative measurements that describe topological structures. Although there are a large number of measurements, most of them are correlated. To overcome this limitation, this paper presents a new measurement for complex network classification based on partially self-avoiding walks. We validate the measurement on a data set composed by 40000 complex networks of four well-known models. Our results indicate that the proposed measurement improves correct classification of networks compared to the traditional ones. (C) 2012 American Institute of Physics. [http://dx.doi.org/10.1063/1.4737515]

Estimating the monthly pCO2 distribution in the North Atlantic using a self-organizing neural network

[EN] Here we present monthly, basin-wide maps of the partial pressure of carbon dioxide (pCO2) for the North Atlantic on a latitude by longitude grid for years 2004 through 2006 inclusive. The maps have been computed using a neural network technique which reconstructs the non-linear relationships between three biogeochemical parameters and marine pCO2. A self organizing map (SOM) neural network has been trained using 389 000 triplets of the SeaWiFSMODIS chlorophyll-a concentration, the NCEP/NCAR reanalysis sea surface temperature, and the FOAM mixed layer depth. The trained SOM was labelled with 137 000 underway pCO2 measurements collected in situ during 2004, 2005 and 2006 in the North Atlantic, spanning the range of 208 to 437atm. The root mean square error (RMSE) of the neural network fit to the data is 11.6?atm, which equals to just above 3 per cent of an average pCO2 value in the in situ dataset. The seasonal pCO2 cycle as well as estimates of the interannual variability in the major biogeochemical provinces are presented and discussed. High resolution combined with basin-wide coverage makes the maps a useful tool for several applications such as the monitoring of basin-wide air-sea CO2 fluxes or improvement of seasonal and interannual marine CO2 cycles in future model predictions. The method itself is a valuable alternative to traditional statistical modelling techniques used in geosciences.

Development, degeneration and neural network of the bodily self

The question addressed by this dissertation is how the human brain builds a coherent representation of the body, and how this representation is used to recognize its own body. Recent approaches by neuroimaging and TMS revealed hints for a distinct brain representation of human body, as compared with other stimulus categories. Neuropsychological studies demonstrated that body-parts and self body-parts recognition are separate processes sub-served by two different, even if possibly overlapping, networks within the brain. Bodily self-recognition is one aspect of our ability to distinguish between self and others and the self/other distinction is a crucial aspect of social behaviour. This is the reason why I have conducted a series of experiment on subjects with everyday difficulties in social and emotional behaviour, such as patients with autism spectrum disorders (ASD) and patients with Parkinson’s disease (PD). More specifically, I studied the implicit self body/face recognition (Chapter 6) and the influence of emotional body postures on bodily self-processing in TD children as well as in ASD children (Chapter 7). I found that the bodily self-recognition is present in TD and in ASD children and that emotional body postures modulate self and others’ body processing. Subsequently, I compared implicit and explicit bodily self-recognition in a neuro-degenerative pathology, such as in PD patients, and I found a selective deficit in implicit but not in explicit self-recognition (Chapter 8). This finding suggests that implicit and explicit bodily self-recognition are separate processes subtended by different mechanisms that can be selectively impaired. If the bodily self is crucial for self/other distinction, the space around the body (personal space) represents the space of interaction and communication with others. When, I studied this space in autism, I found that personal space regulation is impaired in ASD children (Chapter 9).

Soft tissues healing at immediate transmucosal implants placed into molar extraction sites with buccal self-contained dehiscences. A 12-month controlled clinical trial

AIM: To assess soft tissues healing at immediate transmucosal implants placed into molar extraction sites with buccal self-contained dehiscences. MATERIAL AND METHODS: For this 12-month controlled clinical trial, 15 subjects received immediate transmucosal tapered-effect (TE) implants placed in molar extraction sockets displaying a buccal bone dehiscence (test sites) with a height and a width of > or =3 mm, respectively. Peri-implant marginal defects were treated according to the principles of Guided Bone Regeneration (GBR) by means of deproteinized bovine bone mineral particles in conjunction with a bioresorbable collagen membrane. Fifteen subjects received implants in healed molar sites (control sites) with intact buccal alveolar walls following tooth extraction. In total, 30 TE implants with an endosseous diameter of 4.8 mm and a shoulder diameter of 6.5 mm were used. Flaps were repositioned and sutured, allowing non-submerged, transmucosal soft tissues healing. At the 12-month follow-up, pocket probing depths (PPD) and clinical attachment levels (CAL) were compared between implants placed in the test and the control sites, respectively. RESULTS: All subjects completed the 12-month follow-up period. All implants healed uneventfully, yielding a survival rate of 100%. After 12 months, statistically significantly higher (P<0.05) PPD and CAL values were recorded around implants placed in the test sites compared with those placed in the control sites. CONCLUSIONS: The findings of this controlled clinical trial showed that healing following immediate transmucosal implant installation in molar extraction sites with wide and shallow buccal dehiscences yielded less favorable outcomes compared with those of implants placed in healed sites, and resulted in lack of 'complete' osseointegration.

ΔNp63 REGULATES A COMPLEX NETWORK OF TARGET GENES IN LIMB AND EPIDERMAL DEVELOPMENT

The skin is composed of two major compartments, the dermis and epidermis. The epidermis forms a barrier to protect the body. The stratified epithelium has self-renewing capacity throughout life, and continuous turnover is mediated by stem cells in the basal layer. p63 is structurally and functionally related to p53. In spite of their structural similarities, p63 is critical for the development and maintenance of stratified epithelial tissues, unlike p53. p63 is highly expressed in the epidermis and previously has been shown to play a critical role in the development and maintenance of the epidermis. The study of p63 has been complicated due to the existence of multiple isoforms: those with a transactivation domain (TAp63) and those lacking this domain (ΔNp63). Mice lacking p63 cannot form skin, have craniofacial and skeletal defects and die within hours after birth. These defects are due to the ability of p63 to regulate multiple processes in skin development including epithelial stem cell proliferation, differentiation, and adherence programs. To determine the roles of these isoforms in skin development and maintenance, isoform specific p63 conditional knock out mice were generated by our lab. TAp63-/- mice age prematurely, develop blisters, and display wound-healing defects that result from hyperproliferation of dermal stem cells. That results in premature depletion of these cells, which are necessary for wound repair, that indicates TAp63 plays a role in dermal/epidermal maintenance. To study the role of ΔNp63, I generated a ΔNp63-/- mouse and analyzed the skin by performing immunofluorescence for markers of epithelial differentiation. The ΔNp63-/- mice developed a thin, disorganized epithelium but differentiation markers were expressed. Interestingly, the epidermis from ΔNp63-/- mice co-expressed K14 and K10 in the same cell suggesting defects in epidermal differentiation and stratification. This phenotype is reminiscent of the DGCR8fl/fl;K14Cre and Dicerfl/fl;K14Cre mice skin. Importantly, DGCR8-/- embryonic stem cells (ESCs) display a hyperproliferation defect by failure to silence pluripotency genes. Furthermore, I have observed that epidermal cells lacking ΔNp63 display a phenotype reminiscent of embryonic stem cells instead of keratinocytes. Thus, I hypothesize that genes involved in maintaining pluripotency, like Oct4, may be upregulated in the absence of ΔNp63. To test this, q-RT PCR was performed for Oct4 mRNA with wild type and ΔNp63-/- 18.5dpc embryo skin. I found that the level of Oct4 was dramatically increased in the absence of ΔNp63-/-. Based on these results, I hypothesized that ΔNp63 induces differentiation by silencing pluripotency regulators, Oct4, Sox2 and Nanog directly through the regulation of DGCR8. I found that DGCR8 restoration resulted in repression of Oct4, Sox2 and Nanog in ΔNp63-/- epidermal cells and rescue differentiation defects. Loss of ΔNp63 resulted in pluripotency that caused defect in proper differentiation and stem cell like phenotype. This led me to culture the ΔNp63-/- epidermal cells in neuronal cell culture media in order to address whether restoration of DGCR8 can transform epidermal cells to neuronal cells. I found that DGCR8 restoration resulted in a change in cell fate. I also found that miR470 and miR145 play a role in the induction of pluripotency by repressing Oct4, Sox2 and Nanog. This indicates that ΔNp63 induces terminal differentiation through the regulation of DGCR8.

Initial orthodontic alignment effectiveness with self-ligating and conventional appliances: a network meta-analysis in practice.

Systematic reviews of well-designed trials constitute a high level of scientific evidence and are important for medical decision making. Meta-analysis facilitates integration of the evidence using a transparent and systematic approach, leading to a broader interpretation of treatment effectiveness and safety than can be attained from individual studies. Traditional meta-analyses are limited to comparing just 2 interventions concurrently and cannot combine evidence concerning multiple treatments. A relatively recent extension of the traditional meta-analytical approach is network meta-analysis, which allows, under certain assumptions, the quantitative synthesis of all evidence under a unified framework and across a network of all eligible trials. Network meta-analysis combines evidence from direct and indirect information via common comparators; interventions can therefore be ranked in terms of the analyzed outcome. In this article, the network meta-analysis approach is introduced in a nontechnical manner using a worked example on the treatment effectiveness of conventional and self-ligating appliances.