Dynamic evolving neural fuzzy inference system equalization scheme in mode division multiplexer for optical fiber transmission

The performance of optical mode division multiplexer (MDM) is affected by inter-symbol interference (ISI), which arises from higher-order mode coupling and modal dispersion in multimode fiber (MMF). Existing equalization algorithms in MDM can mitigate linear channel impairments, but cannot tackle nonlinear channel impairments accurately. Therefore, mitigating the noise in the received signal of MDM in the presence of ISI to recover the transmitted signal is important issue. This paper aims at controlling the broadening of the signal from MDM and minimizing the undesirable noise among channels. A dynamic evolving neural fuzzy inference system (DENFIS) equalization scheme has been used to achieve this objective. Results illustrate that nonlinear DENFIS equalization scheme can improve the received distorted signal from an MDM with better accuracy than previous linear equalization schemes such as recursive‐least‐square (RLS) algorithm. Desirably, this effect allows faster data transmission rate in MDM. Additionally, the successful offline implementation of DENFIS equalization in MDM encourages future online implementation of DENFIS equalization in embedded optical systems

Generating and Characterising Knockout and Transgenic Mouse Models of Frontotemporal Dementia Caused by CHMP2B Mutation

A mutation in the charged multivesicular body protein 2B (CHMP2B) gene, identified in a kindred from the Jutland region of Denmark, segregates with affected family members with clinical presentations of frontotemporal dementia (FTD) and is absent in control populations (Gydesen et al., 1987; Gydesen et al., 2002; Skibinski et al., 2005). The mutation is a G>C transition in the splice acceptor site of exon 6 resulting in two novel splice variants CHMP2BInt5 and CHMP2BA10 leading to C-terminal truncation of the CHMP2B protein (Skibinski et al., 2005). Chmp2b knockout (Chmp2b-/-) mice and transgenic mice expressing either wild-type or C-terminally truncated mutant CHMP2B splice variants CHMP2BInt5 and CHMP2BA10 were generated with the aims of examining the normal function of Chmp2b and the effect of mutant CHMP2B species in vivo, as well as providing insight into a potential common FTD mechanism of disease. Quantification of Chmp2b protein in Chmp2b-/- mice demonstrates a significant (85%) depletion of endogenous Chmp2b in the mouse brain. No pathology is identified in the CNS or muscle tissue of these mice however, they do demonstrate significant motor and behavioural abnormalities. CHMP2BInt5 transgenic mice demonstrate neurodegenerative changes including progressive gliosis, accumulation of CHMP2B, p62 and ubiquitin inclusions which are negative for TDP-43 and FUS proteins, consistent with the inclusion pathology observed in patients with CHMP2B mutation. Furthermore, these mice have reduced survival and develop progressive axonopathy characterized by axonal swellings and accumulation of mitochondria and vesicles likely from the endosome¬lysosome and autophagy pathway, implicating altered axonal function in disease pathogenesis. This thesis describes the first mouse models of FTD-3 caused by CHMP2B mutation and presents evidence consistent with a gain-of-function effect unique to the CHMP2BInt5 isoform and provides new insights into the mechanisms of CHMP2B-induced neurodegeneration

Design & investigation of 10x10 gbit/s MDM over hybrid FSO link under different weather conditions and fiber to the home

In this paper, we design and investigate 10-channels of mode division multiplexer (MDM) over hybrid free-space optics (FSO) link in several weather conditions to achieve the maximum possible medium range and fiber to the home (FTTH) for high bandwidth access networks. System capacity can be effectively increased with the use of MDM over hybrid FSO-FTTH. In this study, a 10-channel MDM over FSO-FTTH system has been analyzed in different weather conditions that operate at 1550 nm wavelength. The simulated system has transmitted 100 Gbit/s up for a distance of 3200 meters FSO in superbly clear weather condition. It also transmitted 100 Gbit/s up for a distance of 650 meters FSO during heavy rain. The validation of this study is measures based on eye diagrams bit-error rates (BER) that have been analyzed

Home-based transcranial direct current stimulation in bipolar depression: an open-label treatment study of clinical outcomes, acceptability and adverse events

Current treatments for bipolar depression have limited effectiveness, tolerability and acceptability. Transcranial direct current stimulation (tDCS) is a novel non-invasive brain stimulation method that has demonstrated treatment efficacy for major depressive episodes. tDCS is portable, safe, and individuals like having sessions at home. We developed a home-based protocol with real-time remote supervision. In the present study, we have examined the clinical outcomes, acceptability and feasibility of home-based tDCS treatment in bipolar depression

Neuroprotective activity of ursodeoxycholic acid in CHMP2B Intron5 models of frontotemporal dementia

Frontotemporal dementia (FTD) is one of the most prevalent forms of early-onset dementia. It represents part of the FTD-Amyotrophic Lateral Sclerosis (ALS) spectrum, a continuum of genetically and pathologically overlapping disorders. FTD-causing mutations in CHMP2B, a gene encoding a core component of the heteromeric ESCRT-III Complex, lead to perturbed endosomal-lysosomal and autophagic trafficking with impaired proteostasis. While CHMP2B mutations are rare, dysfunctional endosomal-lysosomal signalling is common across the FTD-ALS spectrum. Using our established Drosophila and mammalian models of CHMP2BIntron5 induced FTD we demonstrate that the FDA-approved compound Ursodeoxycholic Acid (UDCA) conveys neuroprotection, downstream of endosomal-lysosomal dysfunction in both Drosophila and primary mammalian neurons. UDCA exhibited a dose dependent rescue of neuronal structure and function in Drosophila pan-neuronally expressing CHMP2BIntron5. Rescue of CHMP2BIntron5 dependent dendritic collapse and apoptosis with UDCA in rat primary neurons was also observed. UDCA failed to ameliorate aberrant accumulation of endosomal and autophagic organelles or ubiquitinated neuronal inclusions in both models. We demonstrate the neuroprotective activity of UDCA downstream of endosomal-lysosomal and autophagic dysfunction, delineating the molecular mode of action of UDCA and highlighting its potential as a therapeutic for the treatment of FTD-ALS spectrum disorders

FUS pathology defines the majority of tau- and TDP-43-negative frontotemporal lobar degeneration

Through an international consortium, we have collected 37 tau- and TAR DNA-binding protein 43 (TDP-43)-negative frontotemporal lobar degeneration (FTLD) cases, and present here the first comprehensive analysis of these cases in terms of neuropathology, genetics, demographics and clinical data. 92% (34/37) had fused in sarcoma (FUS) protein pathology, indicating that FTLD-FUS is an important FTLD subtype. This FTLD-FUS collection specifically focussed on aFTLD-U cases, one of three recently defined subtypes of FTLD-FUS. The aFTLD-U subtype of FTLD-FUS is characterised clinically by behavioural variant frontotemporal dementia (bvFTD) and has a particularly young age of onset with a mean of 41 years. Further, this subtype had a high prevalence of psychotic symptoms (36% of cases) and low prevalence of motor symptoms (3% of cases). We did not find FUS mutations in any aFTLD-U case. To date, the only subtype of cases reported to have ubiquitin-positive but tau-, TDP-43- and FUS-negative pathology, termed FTLD-UPS, is the result of charged multivesicular body protein 2B gene (CHMP2B) mutation. We identified three FTLD-UPS cases, which are negative for CHMP2B mutation, suggesting that the full complement of FTLD pathologies is yet to be elucidated

Prediction of Municipal Solid Waste Generation by Use of Artificial Neural Network: A Case Study of Mashhad

Accurate prediction of municipal solid waste's quality and quantity is crucial for designing and programming municipal solid waste management system. But predicting the amount of generated waste is difficult task because various parameters affect it and its fluctuation is high. In this research with application of feed forward artificial neural network, an appropriate model for predicting the weight of waste generation in Mashhad, was proposed. For this purpose, a time series of Mashhad's generated waste which have been arranged weekly, from 2004 to 2007, was used. Also, for recognizing the effect of each input data on the waste generation sensitive analysis was performed. Finally, different structures of artificial network were investigated and then the best model for predicting Mashhad's waste generation was chosen based on mean absolute error (MAE), mean absolute relative error (MARE), root mean square error (RMSE), correlation coefficient (R2) and threshold statistics (TS) indexes. After performing of the mentioned model, correlation coefficient (R2) and mean absolute relative error (MARE) in neural network for test have been achieved equal to 0.746 and 3.18% respectively. Results point that artificial neural network model has more advantages in comparison with traditional methods in predicting the municipal solid waste generation