br Conflict of interest br Introduction In hereditary optic

Conflict of interest

In hereditary optic neuropathies, the differential diagnosis is broad. However, Dominant Optic Atrophy (DOA) and Wolfram syndrome (WS) share significant clinical variability, including an association with hearing loss and the presence of optic atrophy at similar ages (first decade of life).

Case reports

DOA typically manifests as the insidious loss of VA in the first decade of life. On ophthalmic examination, pallor of the temporal sector of the optic nerve is demonstrated with excavation that can simulate glaucoma. On visual field testing, central or cecocentral scotomata are characteristic. There are also patients with a phenotype designated DOA plus, which can be associated with sensorineural hearing loss, myopathy, peripheral neuropathy, ataxia, symptoms that mimic multiple sclerosis and spastic paraplegia.
The majority of DOA cases are caused by mutations in the OPA1 gene (50–60% of patients). Specifically, more than 200 pathogenic mutations have been described in the OPA-1 gene. However, in large-scale studies, some purchase GLPG0634 with DOA have had mutations associated with other chromosomal loci: OPA-3, OPA-4, OPA-5, and OPA-7,
The OPA1 gene encodes a protein (dynamin-related GTPase) of the inner mitochondrial membrane. Its absence or dysfunction results in an alteration in the mitochondrial DNA stability as well as the integrity of the mitochondrial respiratory chain.
One of the main clinical characteristics of DOA is its great clinical variability: there are patients with isolated visual repercussions (such as the patient we present here) while others experience legal blindness; there are clinical presentations that exclusively affect the optical nerve, and there are syndromic forms with multiple neurological symptoms (20% of all patients). This interfamilial and intrafamilial phenotype variability is explained in part by the different degrees of penetration of DOA, which has been calculated to be approximately 70%. However, it is also due to the presence of mitochondrial DNA deletions caused by nuclear mutations in the OPA1 gene. Thus, DOA is considered a mitochondrial disease and it reflects the great clinical variability of mitochondrial syndromes.
Regarding WS, in its original description, DM and optic atrophy that are present from an early age in life are mentioned as characteristics. In later descriptions, the presence of DI and hearing loss was added. Thus, this syndrome is also known by the acronym DIDMOAD (diabetes insipidus, diabetes mellitus, optic atrophy and deafness). Approximately 50% of patients present with the complete phenotype.
DM and optic atrophy have an average age of onset of 10years. Hearing loss is present in 66% of individuals with an average age of onset of 12.5years. DI occurs in 72% of individuals with an average age of onset of 15.5years. Other neurological alterations that may be present in these individuals include ataxia, apnea, dementia and psychiatric disorders.
In 1997, the WSF1 gene was identified in the 4p16.1 region. The majority of mutations in patients with WS are inherited recessively and are located in exon 8, but mutations have also been described in exons 3, 4, and 5.
The WFS1 is a transmembrane protein of the endoplasmic reticulum (ER). This organ controls the folding of cellular proteins. Under physiological conditions, the accumulation of unfolded proteins provokes WFS1 to stop translating proteins, activating the chaperones responsible for protein folding. However, if the accumulation of unfolded proteins persists (as is the case in WFS1 deficiency), cell apoptosis is induced.
Mutations in the WFS1 gene are responsible for a wide phenotypic spectrum: in addition to classic WS, they have been described as WS-like (associated with deafness, DM, psychiatric alterations and in some cases, optic atrophy) and the syndrome of sensorineural deafness associated with WFS1 that presents in isolation. Also, WS type 2 has recently been described in 4 Jordanian families, characterized by optic atrophy, DM and deafness but not DI. It is caused by mutations in the CDGSH iron sulfur domain 2 (CISD2) gene (located on chromosome 4q22).

br Discussion In the majority of brachyuran crab

In the majority of brachyuran crab species, the sex ratio is usually close to unity (Hartnoll, 1978; Lawal-Are, 2010), however some variations between different populations and from one year to the other in the same population have been detected (Sastry, 1983; Varisco and Vinuesa, 2011). During the present study the overall sex ratio in S. aspera (with the values of M:F=1:1.25) differed significantly from the expected 1:1 ratio, with most months revealing a higher number of females, i.e. the sex ratio of the Suez Canal spider crab S. aspera is female biased. An overall female bias in the sex has been recorded for many brachyuran crab species (Safaie et al., 2013; Chatterjee and Chakraborty, 2015). There are two main possible reasons for this difference from the expected 1:1 ratio between the two sexes. On the one hand, it may result from differences in habitat preferences and feeding behavior between male and female crabs. Mature crabs are known to display different habitat preferences between male and females. Generally, females migrate from inshore areas toward offshore to spawn (Weng, 1992). Moreover, most female crabs are known to require a sandy substrate for successful egg extrusion (Kangas, 2000). Females of many crab species are more abundant in shallow water (Potter et al., 1983). All the six fishing localities of the Suez Canal exhibited sandy substrates, shallow water depths (5–25m), and most of the fishing process occurred offshore. Alternatively, the unequal sex ratio of S. aspera in the Suez Canal could be attributed to the effects of fishing gear. Fishermen in the Suez Canal use a variety of gears such as gillnets, trammel nets, crab nets and beach seine. Gillnets and trammel nets usually operate in the deeper area, while crab nets and beach seine perform in shallow water. This difference in operating fishing gears produces unequal brachyuran sex ratio (Kangas, 2000; Lawal-Are, 2010; Safaie et al., 2013).
The immature stages of S. aspera were observed through 2012 and 2013, revealing that the mature stages occurred from May and extended to December (Fig. 2). This pattern of ovarian development in S. aspera from the Suez Canal indicates that the third and fourth stages of ovarian development is usually achieved in conjunction with rising sea water temperatures, which in their turn indicate that the development of glycogen synthase kinase 3 and eggs in S. aspera is controlled by water temperatures. Brachyuran crab spawning takes place during the whole year in tropical and subtropical waters, while it appears to be more restricted to the warmer months in the temperate regions (Kangas, 2000; Lawal-Are, 2010; Safaie et al., 2013).
In the present study, the range of the minimum carapace width (CW) of ovigerous female S. aspera was 22–46mm, and the CW at which 50% of all females in the stock of that spider crab are ovigerous was 36mm. According to Campbell and Fielder (1986), Sukumaran and Neelakantan (1996), and Sal-Moyano et al. (2014), the size at first sexual maturity differs with latitude and/or location and within individuals at any location.
The fecundity of brachyuran crabs is usually recognized to be an important parameter for measuring their reproductive output (Mantellatto and Fransozo, 1997). Determination of the fecundity of female S aspera from the Suez Canal showed that each female with a carapace width varying from 28 to 52mm can produce 2349–13,600 eggs. In the Suez Canal water, mean fecundity of S. aspera attained 5149±1367 eggs. The spider crab S. aspera, therefore, seems to be a crab species with relatively low fecundity. Fecundity can vary among crab species from less than 5000 eggs, described for Aratus pisonii (H. Milne Edwards, 1837) in Jamaica (Warner, 1967) to more than 4,000,000 eggs, as reported by Haynes et al. (1976) for Chionoecetes opilio (Fabricius, 1788) in the Gulf of Saint Lawrence, Canada. Fecundity of female crabs is size dependent (Kumar et al., 2003), moreover fecundity is strongly correlated with body size of the crab species and weight within the species (Hartnoll, 1985). The analysis of the relationship between carapace width and fecundity for S. aspera in the Suez Canal with Fecundity=2.2808 (CW)2.09 indicates that the fecundity increases with an increase in carapace width (R2=0.62). Thus, it can be stated that higher fecundity was found in larger female crabs due to the longer inter-molt period between population and egg extrusion. In other words, larger females usually have more time than the smaller ones in order to accumulate the energy reserves. The latter are usually required by female crabs (small and/or large) to produce their eggs. This difference might account for the higher number of eggs often produced by large sized females (De Lestang et al., 2003; Sal-Moyano et al., 2014). As discussed above, fecundity of crabs not only varies from one species to the other, but also varies within the same species. Many factors can affect fecundity in brachyuran crabs including: size, age, climatic regime, nourishment, and even ecological properties of the water body (Arshad et al., 2006; Safaie et al., 2013; Gonzalez-Pisani and Lopez-Greco, 2014).

The pseudo code of the general CA is as follows

The pseudo code of the general CA is as follows:
The following sections of this paper are organized as follows. Section 2 introduces a more general investigation into the potential strength of the modified cultural based real coded genetic algorithm MCBGA. Section 3 covers results and computer simulations after applying the proposed MCBGA on different common applications.

Culture genetic algorithm
The proposed research has employed real-coded GA integrated with culture algorithm. Real coded GA requires low memory to run, has high precision, and easy to search in large space, meanwhile it avoids the troublesome encoding and decoding process of computing the objective function. It has been reported that real coded GA outperforms binary-coded GA in many design problems [21,22]. In the belief space there are multi sources of information that the best individuals along their evolution are stored. The main source of information implemented in the belief space are: The list of best points along all generations (LISTBEST), the ranges of the best performers’ candidates (best range for the 20% best LY2874455 in POP) (BESTRANGE) to create some chromosomes “solution” in this range, and the ranges of feasible regions (FRANGE) in which random individuals are generated in that satisfy the constraint and lead the search away from candidates that violate the constraints. The algorithm is detailed below.
The belief space consists of three different kinds of information sources;

Computer simulation and results

The proposed MCBGA does not implement all the information sources of the belief space as [12]. In addition, there is no mutation parameter used, which reduces large computations. The idea of developing the satisfaction region for constraints gives MCBGA the chance to move far away from the unfeasible region, and as the search progresses we can make sure that we are searching in the feasible region.


Based on ANSI/IEEE C57.117-1986 [1], a transformer is a static electric device consisting of a winding or two or more coupled windings, with or without a magnetic core for introducing mutual coupling between electric circuits. The transformer includes all transformer-related components, such as bushings, load tap-changers, fans, and temperature gauges. It excludes all system-related components such as surge arresters, grounding resistors, high-voltage switches, low-voltage switches and house service equipment. Transformers can be classified into many types such as power transformers, autotransformers, and regulating transformers. Based on their application, transformers are classified into substation transformers, transmission tie transformers, unit transformers, etc. The study in this paper considers power transformers for utility applications. For abbreviation, the term “transformers” will refer to “power transformers” in this paper. Transformers are an integral part of power systems, and their reliability directly affects the reliability of the whole network. Outage of transformers is a failure, since a failure is the termination of the ability of a transformer to perform its specified function [1]. Transformer outages are either forced or scheduled. Both types are caused by switching operations. Forced outages of transformers are mainly due to automatic switching operations performed by protection systems [1–3]. They are caused by either external causes (such as transmission line faults) or internal causes (such as core failure and winding failure). More details about failure statistics of transformer subassemblies are available at references [2,3]. For an abbreviation in this paper, the term ‘outage’ refers to ‘forced outage’.
In general, there are three distinct phases that a complex product goes through in its life cycle [1,4,5]. These phases are infant mortality (or debugging) phase, useful life phase, and wear-out phase. These three characteristics periods are represented by what is called the bathtub curve[4,5]. The chances of failure are much different during each phase, but most assemblies of a large number of component parts exhibit these three characteristic periods in their life. However, for a typical power transformer, the infant mortality phase has been significantly reduced as shown in Fig. 1 by adherence to industry-wide testing standards. In comparison with many products sold today, power transformers offer few, if any, significant problems due to infant mortality [1].