A Gate-Induced Switch in Zigzag Graphene Naoribbons and Charging Effects

Using non-equilibrium Green's function formalism, we investigate nonlinear transport and charging effects of gated graphene nanoribbons (GNRs) with even number of zigzag chains. We find a negative differential resistance (NDR) over a wide range of gate voltages with on/off ratio $\sim 10^6$ for narrow enough ribbons. This NDR originates from the parity selection rule and also prohibition of transport between discontinues energy bands. Since the external field is well screened close to the contacts, the NDR is robust against the electrostatic potential. However, for voltages higher than the NDR threshold, due to charge transfer through the edges of ZGNR, screening is reduced such that the external potential can penetrate inside the ribbon giving rise to smaller values of off current. Furthermore, on/off ratio of the current depends on the aspect ratio of the length/width and also edge impurity. Moreover, on/off ratio displays a power law behavior as a function of ribbon length.Comment: 8 pages, 9 figure

ERP Correlates of Recognition Memory in Autism Spectrum Disorder

Recognition memory in autism spectrum disorder (ASD) tends to be undiminished compared to that of typically developing (TD) individuals (Bowler et al. 2007), but it is still unknown whether memory in ASD relies on qualitatively similar or different neurophysiology. We sought to explore the neural activity underlying recognition by employing the old/new word repetition event-related potential effect. Behavioural recognition performance was comparable across both groups, and demonstrated superior recognition for low frequency over high frequency words. However, the ASD group showed a parietal rather than anterior onset (300–500 ms), and diminished right frontal old/new effects (800–1500 ms) relative to TD individuals. This study shows that undiminished recognition performance results from a pattern of differing functional neurophysiology in ASD

Electronic structure of nanoscale iron oxide particles measured by scanning tunneling and photoelectron spectroscopies

We have investigated the electronic structure of nano-sized iron oxide by scanning tunnelling microscopy (STM) and spectroscopy (STS) as well as by photoelectron spectroscopy. Nano particles were produced by thermal treatment of Ferritin molecules containing a self-assembled core of iron oxide. Depending on the thermal treatment we were able to prepare different phases of iron oxide nanoparticles resembling gamma-Fe2O3, alpha-Fe2O3, and a phase which apparently contains both gamma-Fe2O3 and alpha-Fe2O3. Changes to the electronic structure of these materials were studied under reducing conditions. We show that the surface band gap of the electronic excitation spectrum can differ from that of bulk material and is dominated by surface effects.Comment: REVTeX, 6 pages, 10 figures, submitted to PR

Statistical properties of a localization-delocalization transition induced by correlated disorder

The exact probability distributions of the resistance, the conductance and the transmission are calculated for the one-dimensional Anderson model with long-range correlated off-diagonal disorder at E=0. It is proved that despite of the Anderson transition in 3D, the functional form of the resistance (and its related variables) distribution function does not change when there exists a Metal-Insulator transition induced by correlation between disorders. Furthermore, we derive analytically all statistical moments of the resistance, the transmission and the Lyapunov Exponent. The growth rate of the average and typical resistance decreases when the Hurst exponent $H$ tends to its critical value ($H_{cr}=1/2$) from the insulating regime. In the metallic regime $H\geq1/2$, the distributions become independent of size. Therefore, the resistance and the transmission fluctuations do not diverge with system size in the thermodynamic limit

Observational Constraints on the Modified Gravity Model (MOG) Proposed by Moffat: Using the Magellanic System

A simple model for the dynamics of the Magellanic Stream (MS), in the framework of modified gravity models is investigated. We assume that the galaxy is made up of baryonic matter out of context of dark matter scenario. The model we used here is named Modified Gravity (MOG) proposed by Moffat (2005). In order to examine the compatibility of the overall properties of the MS under the MOG theory, the observational radial velocity profile of the MS is compared with the numerical results using the $\chi^2$ fit method. In order to obtain the best model parameters, a maximum likelihood analysis is performed. We also compare the results of this model with the Cold Dark Matter (CDM) halo model and the other alternative gravity model that proposed by Bekenstein (2004), so called TeVeS. We show that by selecting the appropriate values for the free parameters, the MOG theory seems to be plausible to explain the dynamics of the MS as well as the CDM and the TeVeS models.Comment: 14 pages, 3 Figures, accepted in Int. J. Theor. Phy

Transcription of toll-like receptors 2, 3, 4 and 9, FoxP3 and Th17 cytokines in a susceptible experimental model of canine Leishmania infantum infection

Canine leishmaniosis (CanL) due to Leishmania infantum is a chronic zoonotic systemic disease resulting from complex interactions between protozoa and the canine immune system. Toll-like receptors (TLRs) are essential components of the innate immune system and facilitate the early detection of many infections. However, the role of TLRs in CanL remains unknown and information describing TLR transcription during infection is extremely scarce. The aim of this research project was to investigate the impact of L. infantum infection on canine TLR transcription using a susceptible model. The objectives of this study were to evaluate transcription of TLRs 2, 3, 4 and 9 by means of quantitative reverse transcription polymerase chain reaction (qRT-PCR) in skin, spleen, lymph node and liver in the presence or absence of experimental L. infantum infection in Beagle dogs. These findings were compared with clinical and serological data, parasite densities in infected tissues and transcription of IL-17, IL-22 and FoxP3 in different tissues in non-infected dogs (n = 10), and at six months (n = 24) and 15 months (n = 7) post infection. Results revealed significant down regulation of transcription with disease progression in lymph node samples for TLR3, TLR4, TLR9, IL-17, IL-22 and FoxP3. In spleen samples, significant down regulation of transcription was seen in TLR4 and IL-22 when both infected groups were compared with controls. In liver samples, down regulation of transcription was evident with disease progression for IL-22. In the skin, upregulation was seen only for TLR9 and FoxP3 in the early stages of infection. Subtle changes or down regulation in TLR transcription, Th17 cytokines and FoxP3 are indicative of the silent establishment of infection that Leishmania is renowned for. These observations provide new insights about TLR transcription, Th17 cytokines and Foxp3 in the liver, spleen, lymph node and skin in CanL and highlight possible markers of disease susceptibility in this model

An unusual case of meningococcal meningitis complicated with subdural empyema in a 3 month old infant: a case report

Subdural empyema is an unusual complication of meningococcal meningitis, and in acute cases can be rapidly fatal. We present a case of an 8 week old infant who presented with atypical Neisseria meningitis with bifrontal subdural empyema formation. Through the utilisation of modern polymerise chain reaction tests on cerebrospinal fluid samples, we were able to confirm the diagnosis and institute appropriate treatment. Early surgical intervention and appropriate intravenous antibiotics meant that the patient fully recovered. In summary, early treatment of meningitis without adequate microbiological investigations can complicate later diagnosis of subdural empyema. Early suspicion of empyema should be considered when patient fails to improve after 48 hrs, seizures are a late sign and gives a poorer prognosis. Computed tomography scanning is still the modality of choice although in this case, magnetic resonance imaging had its benefits. Polymerase chain reaction of cerebrospinal fluid testing may also provide an important confirmatory test in future

A Deep Learning Study on Osteosarcoma Detection from Histological Images

In the U.S, 5-10\% of new pediatric cases of cancer are primary bone tumors. The most common type of primary malignant bone tumor is osteosarcoma. The intention of the present work is to improve the detection and diagnosis of osteosarcoma using computer-aided detection (CAD) and diagnosis (CADx). Such tools as convolutional neural networks (CNNs) can significantly decrease the surgeon's workload and make a better prognosis of patient conditions. CNNs need to be trained on a large amount of data in order to achieve a more trustworthy performance. In this study, transfer learning techniques, pre-trained CNNs, are adapted to a public dataset on osteosarcoma histological images to detect necrotic images from non-necrotic and healthy tissues. First, the dataset was preprocessed, and different classifications are applied. Then, Transfer learning models including VGG19 and Inception V3 are used and trained on Whole Slide Images (WSI) with no patches, to improve the accuracy of the outputs. Finally, the models are applied to different classification problems, including binary and multi-class classifiers. Experimental results show that the accuracy of the VGG19 has the highest, 96\%, performance amongst all binary classes and multiclass classification. Our fine-tuned model demonstrates state-of-the-art performance on detecting malignancy of Osteosarcoma based on histologic images