Enabling transparent technologies for the development of highly granular flexible optical cross-connects

Flexible optical networking is identified today as the solution that offers smooth system upgradability towards Tb/s capacities and optimized use of network resources. However, in order to fully exploit the potentials of flexible spectrum allocation and networking, the development of a flexible switching node is required capable to adaptively add, drop and switch tributaries with variable bandwidth characteristics from/to ultra-high capacity wavelength channels at the lowest switching granularity. This paper presents the main concept and technology solutions envisioned by the EU funded project FOX-C, which targets the design, development and evaluation of the first functional system prototype of flexible add-drop and switching cross-connects. The key developments enable ultra-fine switching granularity at the optical subcarrier level, providing end-to-end routing of any tributary channel with flexible bandwidth down to 10Gb/s (or even lower) carried over wavelength superchannels, each with an aggregated capacity beyond 1Tb/s. © 2014 IEEE.

Pathology of the dentate gyrus in neurodegenerative disease

The dentate gyrus (DG) is an important part of the hippocampal formation and is believed to be involved in a variety of brain functions including episodic and spatial memory and the exploration of novel environments. In several neurodegenerative disorders, significant pathology occurs in the DG which may be involved in the development of clinical dementia. Based on the abundance of pathological change, neurodegenerative disorders can be divided into three groups: (1) those in which high densities of neuronal cytoplasmic inclusions (NCI) are present in DG granule cells, e.g., Pick’s disease (PiD), frontotemporal lobar degeneration with TDP-43-immunoreactive inclusions (FTLD-TDP), and neuronal intermediate filament inclusion disease (NIFID), (2) those in which aggregated protein deposits are distributed throughout the hippocampal formation including the molecular layer of the DG, e.g., Alzheimer’s disease (AD), Down’s syndrome (DS), and variant Creutzfeldt-Jakob disease (vCJD), and (3) those in which in there is significantly less pathology in the DG, e.g., Parkinson’s disease dementia (PD-Dem), dementia with Lewy bodies (DLB), progressive supranuclear palsy (PSP), corticobasal degeneration (CBD), multiple system atrophy (MSA), and sporadic CJD (sCJD). Hence, DG pathology varies significantly among disorders which could contribute to differences in clinical dementia. Pathological differences among disorders could reflect either differential vulnerability of the DG to specific molecular pathologies or variation in the degree of spread of pathological proteins into the hippocampal formation from adjacent regions.

Poly(glycerol adipate-co-ω-pentadecalactone) spray-dried microparticles as sustained release carriers for pulmonary delivery

Purpose: The aim of this work was to optimize biodegradable polyester poly(glycerol adipate-co-ω-pentadecalactone), PGA-co-PDL, microparticles as sustained release (SR) carriers for pulmonary drug delivery. Methods: Microparticles were produced by spray drying directly from double emulsion with and without dispersibility enhancers (L-arginine and L-leucine) (0.5-1.5%w/w) using sodium fluorescein (SF) as a model hydrophilic drug. Results: Spray-dried microparticles without dispersibility enhancers exhibited aggregated powders leading to low fine particle fraction (%FPF) (28.79±3.24), fine particle dose (FPD) (14.42±1.57 μg), with a mass median aerodynamic diameter (MMAD) 2.86±0.24 μm. However, L-leucine was significantly superior in enhancing the aerosolization performance ( L-arginine:%FPF 27.61±4.49-26.57±1.85; FPD 12.40±0.99-19.54±0.16 μg and MMAD 2.18±0.35-2. 98±0.25 μm, L-leucine:%FPF 36.90±3.6-43.38±5. 6; FPD 18.66±2.90-21.58±2.46 μg and MMAD 2.55±0.03-3. 68±0.12 μm). Incorporating L-leucine (1.5%w/w) reduced the burst release (24.04±3.87%) of SF compared to unmodified formulations (41.87±2.46%), with both undergoing a square root of time (Higuchi's pattern) dependent release. Comparing the toxicity profiles of PGA-co-PDL with L-leucine (1.5%w/w) (5 mg/ml) and poly(lactide-co-glycolide), (5 mg/ml) spray-dried microparticles in human bronchial epithelial 16HBE14o-cell lines, resulted in cell viability of 85.57±5.44 and 60.66±6.75%, respectively, after 72 h treatment. Conclusion:The above data suggest that PGA-co-PDL may be a useful polymer for preparing SR microparticle carriers, together with dispersibility enhancers, for pulmonary delivery. © Springer Science+Business Media, LLC 2011.

Progmosis:evaluating risky individual behavior during epidemics using mobile network data

The possibility to analyze, quantify and forecast epidemic outbreaks is fundamental when devising effective disease containment strategies. Policy makers are faced with the intricate task of drafting realistically implementable policies that strike a balance between risk management and cost. Two major techniques policy makers have at their disposal are: epidemic modeling and contact tracing. Models are used to forecast the evolution of the epidemic both globally and regionally, while contact tracing is used to reconstruct the chain of people who have been potentially infected, so that they can be tested, isolated and treated immediately. However, both techniques might provide limited information, especially during an already advanced crisis when the need for action is urgent. In this paper we propose an alternative approach that goes beyond epidemic modeling and contact tracing, and leverages behavioral data generated by mobile carrier networks to evaluate contagion risk on a per-user basis. The individual risk represents the loss incurred by not isolating or treating a specific person, both in terms of how likely it is for this person to spread the disease as well as how many secondary infections it will cause. To this aim, we develop a model, named Progmosis, which quantifies this risk based on movement and regional aggregated statistics about infection rates. We develop and release an open-source tool that calculates this risk based on cellular network events. We simulate a realistic epidemic scenarios, based on an Ebola virus outbreak; we find that gradually restricting the mobility of a subset of individuals reduces the number of infected people after 30 days by 24%.

Aggregating Local Descriptors for Epigraphs Recognition

In this paper, we consider the task of recognizing epigraphs in images such as photos taken using mobile devices. Given a set of 17,155 photos related to 14,560 epigraphs, we used a k-NearestNeighbor approach in order to perform the recognition. The contribution of this work is in evaluating state-of-the-art visual object recognition techniques in this specific context. The experimental results conducted show that Vector of Locally Aggregated Descriptors obtained aggregating SIFT descriptors is the best choice for this task.

The challenges faced by reporting entities on their transition to international financial reporting standards:a qualitative study

This study explores the challenges of implementing International Financial Reporting Standards (IFRS) at the organisational level. Based on interviews with experts with aggregated experience relating to the transition projects of over 170 reporting entities, this paper highlights the main challenges in delivering a successful implementation of IFRS. The findings show that the problems faced in implementation include lack of education and training, securing executive-level support, identifying and responding to the wider business-related implications of the transition, and issues with capturing the necessary information for reporting under IFRS.This paper complements the existing literature and offers a qualitative alternative to considering the transition to IFRS, offering insight into the organisational context of IFRS implementation. These insights are useful not only from a historic perspective, but also for organisations and regulators in the many jurisdictions where IFRS is permitted but not required, where more reporting entities will voluntarily move to IFRS-based reporting in the future. More broadly, they are also applicable to the challenges faced in implementing new and significantly revised IFRSs.

The spatial patterns of β-amyloid (Aβ) deposits and neurofibrillary tangles (NFT) in late-onset sporadic Alzheimer's disease

The spatial patterns of β-amyloid (Aβ) deposits and neurofibrillary tangles (NFT) were studied in areas of the cerebral cortex in 16 patients with the late-onset, sporadic form of Alzheimer's disease (AD). Diffuse, primitive, and classic Aβ deposits and NFT were aggregated into clusters; the clusters being regularly distributed parallel to the pia mater in many areas. In a significant proportion of regions, the sizes of the regularly distributed clusters approximated to those of the cells of origin of the cortico-cortical projections. The diffuse and primitive Aβ deposits exhibited a similar range of spatial patterns but the classic Aβ deposits occurred less frequently in large clusters >6400m. In addition, the NFT often occurred in larger regularly distributed clusters than the Aβ deposits. The location, size, and distribution of the clusters of Aβ deposits and NFT supports the hypothesis that AD is a 'disconnection syndrome' in which degeneration of specific cortico-cortical and cortico-hippocampal pathways results in synaptic disconnection and the formation of clusters of NFT and Aβ deposits. © 2011 Nova Science Publishers, Inc.

Leveraging product adopter information from online reviews for product recommendation

The availability of the sheer volume of online product reviews makes it possible to derive implicit demographic information of product adopters from review documents. This paper proposes a novel approach to the extraction of product adopter mentions from online reviews. The extracted product adopters are the ncategorise into a number of different demographic user groups. The aggregated demographic information of many product adopters can be used to characterize both products and users, which can be incorporated into a recommendation method using weighted regularised matrix factorisation. Our experimental results on over 15 million reviews crawled from JINGDONG, the largest B2C e-commerce website in China, show the feasibility and effectiveness of our proposed frame work for product recommendation.

Discovering biomarkers for antidepressant response:protocol from the Canadian biomarker integration network in depression (CAN-BIND) and clinical characteristics of the first patient cohort

Background: Major Depressive Disorder (MDD) is among the most prevalent and disabling medical conditions worldwide. Identification of clinical and biological markers ("biomarkers") of treatment response could personalize clinical decisions and lead to better outcomes. This paper describes the aims, design, and methods of a discovery study of biomarkers in antidepressant treatment response, conducted by the Canadian Biomarker Integration Network in Depression (CAN-BIND). The CAN-BIND research program investigates and identifies biomarkers that help to predict outcomes in patients with MDD treated with antidepressant medication. The primary objective of this initial study (known as CAN-BIND-1) is to identify individual and integrated neuroimaging, electrophysiological, molecular, and clinical predictors of response to sequential antidepressant monotherapy and adjunctive therapy in MDD. Methods: CAN-BIND-1 is a multisite initiative involving 6 academic health centres working collaboratively with other universities and research centres. In the 16-week protocol, patients with MDD are treated with a first-line antidepressant (escitalopram 10-20 mg/d) that, if clinically warranted after eight weeks, is augmented with an evidence-based, add-on medication (aripiprazole 2-10 mg/d). Comprehensive datasets are obtained using clinical rating scales; behavioural, dimensional, and functioning/quality of life measures; neurocognitive testing; genomic, genetic, and proteomic profiling from blood samples; combined structural and functional magnetic resonance imaging; and electroencephalography. De-identified data from all sites are aggregated within a secure neuroinformatics platform for data integration, management, storage, and analyses. Statistical analyses will include multivariate and machine-learning techniques to identify predictors, moderators, and mediators of treatment response. Discussion: From June 2013 to February 2015, a cohort of 134 participants (85 outpatients with MDD and 49 healthy participants) has been evaluated at baseline. The clinical characteristics of this cohort are similar to other studies of MDD. Recruitment at all sites is ongoing to a target sample of 290 participants. CAN-BIND will identify biomarkers of treatment response in MDD through extensive clinical, molecular, and imaging assessments, in order to improve treatment practice and clinical outcomes. It will also create an innovative, robust platform and database for future research. Trial registration: ClinicalTrials.gov identifier NCT01655706. Registered July 27, 2012.

Mining product adopter information from online reviews for improving product recommendation

We present in this article an automated framework that extracts product adopter information from online reviews and incorporates the extracted information into feature-based matrix factorization formore effective product recommendation. In specific, we propose a bootstrapping approach for the extraction of product adopters from review text and categorize them into a number of different demographic categories. The aggregated demographic information of many product adopters can be used to characterize both products and users in the form of distributions over different demographic categories. We further propose a graphbased method to iteratively update user- and product-related distributions more reliably in a heterogeneous user-product graph and incorporate them as features into the matrix factorization approach for product recommendation. Our experimental results on a large dataset crawled from JINGDONG, the largest B2C e-commerce website in China, show that our proposed framework outperforms a number of competitive baselines for product recommendation.

Spatial patterns of neuronal cytoplasmic inclusions in the tauopathies: A comparative study of five disorders

The tauopathies are a major molecular group of neurodegenerative disorders characterised by the deposition of abnormal cellular aggregates of the microtubule associated protein (MAP) tau in the form of neuronal cytoplasmic inclusions (NCI). Recent research suggests that cell to cell propagation of pathogenic tau may be involved in the neurodegeneration of these disorders. If pathogenic tau spreads along anatomical pathways it may give rise to specific spatial patterns of the NCI in brain tissue. To test this hypothesis, the spatial patterns of NCI in cerebral cortical regions were compared in tissue sections taken from five major tauopathies: (1) argyrophilic grain disease (AGD), (2) Alzheimer's disease (AD), (3) corticobasal degeneration (CBD), (4) Pick's disease (PiD), and (5) progressive supranuclear palsy (PSP). In the cerebral cortex of these disorders, NCI were frequently aggregated into clusters and the clusters were regularly distributed parallel to the pia mater. In a significant proportion of regions, the mean size of the regularly distributed clusters of NCI was in the range 400 – 800 m, measured parallel to the pia mater, approximating to the dimension of cell columns associated with the cortico-cortical anatomical pathways. Hence, the data suggest that cortical NCI in the tauopathies exhibit a spatial pattern in the cortex which could result from the spread of pathogenic tau along anatomical pathways. Treatments designed to protect the cortex from tau propagation may therefore be applicable across several different disorders within this molecular group.

Condensation-enhanced self-assembly as a route to high surface area α-aluminas

High surface area nanosized α-alumina has been obtained by thermally treating a sol-gel-derived mesophase at 1200 C; the mesophase was synthesized by a sol-gel route involving evaporation induced self-assembly (EISA) of a hydrolyzed gel from Al-tri-sec-butoxide in s-BuOH in the presence of a nonionic surfactant (EO20PO70EO20), HCl as catalyst, and water (H2O/Al = 6). The activated material renders moderate surface areas of about 8.4-10 m2 g-1, associated with significant crystallite coarsening. The key aspect to produce smaller crystallites is making the mesophase more resistant to coarsening. This was achieved by enhancing the condensation step by treating the hydrolyzed gel with tetrabutyl ammonium hydroxide (TBAOH) before evaporation. The characteristics of the mesophase indicate condensation of the primary particles with less AlO5 unsaturated sites, at the expense of a lower solid yield due to small crystallites dissolution. The activated TBAOH condensed EISA material is composed of α-alumina aggregated crystallites of about 60-100 nm, and the material possesses surface areas ranging from 16 to 24 m2 g -1 due to the improved resistance to coarsening. At least two aspects are suggested to play a role in this. The worm-hole morphology of the mesophase aggregates yields high particle coordination, which favors densification rather than coarsening. Furthermore, the decrease of the AlO5 defect sites by the TBAOH condensation makes the mesophase less reactive and consequently more resistant to coarsening. © 2013 American Chemical Society.

A spatial pattern analysis of β-amyloid (Aβ) deposition in the temporal lobe in Alzheimer's disease

To determine the factors influencing the distribution of β-amyloid (Aβ) deposits in Alzheimer's disease (AD), the spatial patterns of the diffuse, primitive, and classic Aβ deposits were studied from the superior temporal gyrus (STG) to sector CA4 of the hippocampus in six sporadic cases of the disease. In cortical gyri and in the CA sectors of the hippocampus, the Aβ deposits were distributed either in clusters 200-6400 μm in diameter that were regularly distributed parallel to the tissue boundary or in larger clusters greater than 6400 μm in diameter. In some regions, smaller clusters of Aβ deposits were aggregated into larger 'superclusters'. In many cortical gyri, the density of Aβ deposits was positively correlated with distance below the gyral crest. In the majority of regions, clusters of the diffuse, primitive, and classic deposits were not spatially correlated with each other. In two cases, double immunolabelled to reveal the Aβ deposits and blood vessels, the classic Aβ deposits were clustered around the larger diameter vessels. These results suggest a complex pattern of Aβ deposition in the temporal lobe in sporadic AD. A regular distribution of Aβ deposit clusters may reflect the degeneration of specific cortico-cortical and cortico-hippocampal pathways and the influence of the cerebral blood vessels. Large-scale clustering may reflect the aggregation of deposits in the depths of the sulci and the coalescence of smaller clusters.

Ornamental plants as climatic indicators of arthropod vectors

The importance and risk of vector-borne diseases (eg. leishmaniasis, West Nile Virus, Lyme borreliosis) is going to increase in the European temperate areas due to climate change. Our previous studies have shown that the potential distribution of Leishmania infantum and some Phlebotomus (sand fly) species – a parasite of leishmaniasis, and its vectors – may be expanded even to the southern coastline of the Baltic Sea by the end of the 21st century. The lowland areas of the Carpathian Basin and the main part of Hungary are projected to be suitable for the studied sand fly vectors in the near future. It is important to find some indicator plants to examine whether the sand flies are able to live in a certain climate at a certain time. We studied several Mediterranean and Sub-Mediterranean plant species, and we found that the aggregated distribution of three ligneous species (Juniperus oxycedrus L., Quercus ilex L. and Pinus brutia Ten.) shows high correlation with the union distribution of five sand flies (Phlebotomus ariasi Tonn., Ph. neglectus Tonn., Ph. perfiliewi Parrot, Ph. perniciosus Newst. and Ph. tobbi Adler, Theodor et Lourie). Since these Mediterranean species are highly tolerant of the edaphic characteristics of the planting site, they may prove to be good indicators. The present and upcoming climate of Hungary is seen to be suitable for the selected indicator plant species, and it draws attention to and verifies the potential of the expansion of sand flies, which has been proved by some recent observations of the vectors in Southern Hungary.

Klímaváltozás és az európai lepkeszúnyogok. Az areamodellezés módszertani kérdései

The future northward expansion of the arthropod vectors of leishmaniasis caused by climate change seems to be essential veterinary and medical problem. Our aim was to build and evaluate a Climate Envelope Model (CEM) to assess the potential effects of climate change on five European sandfly species. The studied species – Phlebotomus ariasi Tonn., P. neglectus Tonn., P. papatasi Scop., P. perfiliewi Parrot, P. perniciosus Newst., P. sergenti Parrot, P. similis Perfiliev, P. tobbi Adler, Theodor et Lourie – are important vectors of the parasite Leishmania infantum or other Leishmania species. The projections were based on REMO regional climate model with European domain. The climate data were available in a 25 km resolution grid for the reference period (1961-90) and two future periods (2011-40, 2041-70). The regional climate model was based on the IPCC SRES A1B scenario. Three types of climatic parameters were used for every month (averaged in the 30-years periods). The model was supported by VBORNET digital area database (distribution maps), ESRI ArcGIS 10 software’s Spatial Analyst module (modeling environment), PAST (calibration of the model with statistical method). Iterative model evaluation was done by summarizing two types of model errors based on an aggregated distribution. The results show that the best model results can be achieved by leaving 5-5 percentiles from the two extrema of the mean temperature, 2-2 percentiles from the two extrema of the minimum temperature, 0 percentile from the minimum of and 8 percentiles from the maximum of the precipitation.