Perineurioma: an unusual cause of an external auditory canal polyp

BACKGROUND: Home parenteral nutrition (HPN) is used to treat intestinal failure. A minority of HPN patients are dependent on opiates and benzodiazepines to control pain and anxiety. The aim of this study was to determine what effects such drug dependence had on patient outcomes. METHODS: Ten dependent patients were prospectively compared with 10 well-matched, nondependent HPN patients for the same 12-month period. Episodes of line sepsis and other complications were documented and the cost of treatment estimated. Health status was measured using the SF36 and EuroQol instruments. RESULTS: The dependent group had significantly more episodes of central line sepsis (p = .0007) as well as other complications (p = .0002). This led to significantly longer periods of inpatient care (p = .0004) and therefore higher costs of treatment. Health status was lower in the dependent group; they reported more pain (p = .04) and less energy (p = .04). CONCLUSIONS: The complication rate and increased cost of treatment for opiate- and sedative-dependent patients receiving HPN significantly detract from the overall outcome of this therapy.     

Large cell neuroendocrine carcinoma of the thymus

AIM: We highlight the occurrence of an unusual neuroendocrine tumour, a large cell neuroendocrine carcinoma, arising from the thymus. CASE DETAILS: A 68-year-old man with a history of cigarette smoking had a large mediastinal tumour arising from the thymus removed. Two years later the tumour recurred; it was debulked surgically but the patient died 2 months later: Histological examination of both tumour specimens revealed a tumour with an endocrine pattern, composed of large pleomorphic cells with large nuclei and prominent nucleoli. The mitotic count ranged from 19 to 26 per 10 high-power fields and large tracks of coagulative tumour necrosis were present. The tumour cells were strongly positive for neuron-specific enolase (NSE), chromogranin, CAM5.2 and AE1/3, with cytoplasmic dot-like accentuation for the latter three markers. The tumour fulfilled the criteria for a diagnosis of large cell neuroendocrine carcinoma. CONCLUSIONS: Large cell neuroendocrine carcinoma should be distinguished from atypical carcinoid and small cell carcinoma. It is a distinctive neuroendocrine malignancy with a prognosis between that of atypical carcinoid and small cell carcinoma, and needs to be treated aggressively.     

Maintaining stimulant waveforms in large-volume microfluidic cell chambers

Stimulation of cells with temporal waveforms can be used to observe the frequency-dependent nature of cellular responses. The ability to produce and maintain the temporal waveforms in spite of the broadening processes that occur as the wave travels through the microfluidic system is critical for observing dynamic behaviors. Broadening of waves in microfluidic channels has been examined, but the effect that large-volume cell chambers have on the waves has not. In this report, a sinusoidal glucose wave delivered to a 1-mm diameter cell chamber using various microfluidic channel structures was simulated by finite element analysis with the goal of minimizing the broadening of the waveform in the chamber and maximizing the homogeneity of the concentration in the chamber at any given time. Simulation results indicated that increasing the flow rate was the most effective means to achieve these goals, but at a given volumetric flow rate, geometries that deliver the waveform to multiple regions in the chamber while maintaining a high linear velocity produced sufficient results. A 4-inlet geometry with a 220-μm channel width gave the best result in the simulation and was used to deliver glucose waveforms to a population of pancreatic islets of Langerhans. The result was a stronger and more robust synchronization of the islet population as compared with when a non-optimized chamber was used. This general strategy will be useful in other microfluidic systems examining the frequency-dependence nature of cellular behavior.     

Improved generative semisupervised learning based on finely grained component-conditional class labeling

We introduce new inductive, generative semisupervised mixtures with more finely grained class label generation mechanisms than in previous work. Our models combine advantages of semisupervised mixtures, which achieve label extrapolation over a component, and nearest-neighbor (NN)/nearest-prototype (NP) classification, which achieve accurate classification in the vicinity of labeled samples or prototypes. For our NN-based method, we propose a novel two-stage stochastic data generation, with all samples first generated using a standard finite mixture and then all class labels generated, conditioned on the samples and their components of origin. This mechanism entails an underlying Markov random field, specific to each mixture component or cluster. We invoke the pseudo-likelihood formulation, which forms the basis for an approximate generalized expectation-maximization model learning algorithm. Our NP-based model overcomes a problem with the NN-based model that manifests at very low labeled fractions. Both models are advantageous when within-component class proportions are not constant over the feature space region "owned by" a component. The practicality of this scenario is borne out by experiments on UC Irvine data sets, which demonstrate significant gains in classification accuracy over previous semisupervised mixtures and also overall gains, over KNN classification. Moreover, for very small labeled fractions, our methods overall outperform supervised linear and nonlinear kernel support vector machines.     

Data fusion with flexible message composition in Driver-in-the-Loop vehicular CPS

This work addresses a unique data fusion problem in Vehicular Cyber-Physical Systems (VCPS) arising from Human Factors (HF) considerations. Typically, a VCPS message intended for human drivers is composed of many data elements (DEs), and different messages can be fused by the sender before transmission e.g., by eliminating identical (or redundant) DEs in order to save transmission bandwidth in the wireless network. Still, not all distinct DEs can be received properly due to the limited transmission resources available to the sender and/or transmission errors. Subsequently, some of the messages intended for a driver cannot be delivered. On the other hand, a partially delivered message may still be beneficial (in terms of generating some utility) to a driver. More specifically, when considering HF, the DEs can be grouped into two distinct parts: essential and auxiliary. While a partially reconstructed message missing even a single essential DE fails to produce any benefit (or utility) for a driver, each auxiliary DE can independently produce an additional utility so long as all the essential DEs of the message are also available.In this paper, we deal with a new Driver-in-the-Loop Data Fusion Problem (DDFP) with the primary issue being: given a list of out-going messages and a limit on the number of DEs that can be transmitted, how does the sender choose which DEs (each carrying a different utility) to transmit, in order to maximize the system-wide utility at the receiver. We formulate DDFP mathematically, and prove it to be NP-Complete. We study DDFP in both ideal and lossy communication networks, and propose several efficient algorithms for them. Besides the Single-Sender-Single-Receiver model, we also look into DDFP in Multiple-Sender-Single-Receiver and Single-Sender-Multiple-Receiver models with several practical considerations. Numerical results from large scale simulations are also presented.     

A Fuzzy Logic Based Discrete Mode Power System Stabilizer

A Fuzzy Power System Stabiliser (FPSS) design using discrete inputs is presented. The FPSS basically utilises only one measurable plant signal as input, namely, the generator speed. The speed signal is discretised resulting in three inputs to the FPSS. A simplified power system represented by a single generator transmitting power to the infinite bus is considered for investigations. The system is simulated in simulink while the FPSS is implemented using Fuzzy Logic Toolbox. There are six rules for the fuzzification and two rules for defuzzification. To provide satisfactory behaviour in the entire region of operation of the generator, additional signals namely, generator's active and reactive power are used as inputs to FPSS. Simulation studies show the superior performance of the proposed FPSS compared to an optimally designed Conventional Power System Stabiliser.     

Current Injected Equivalent Circuit Approach to Modeling and Analysis of Current Programmed Switching DC-DC Converters (Discontinuous Inductor Conduction Mode)

The current injected equivalent circuit approach (CIECA) to modeling switching converter power stages is extended to model the current programmed converter power stages operating in fixed frequency discontinuous inductor conduction mode. To demonstrate the method, the modeling is carried out for the buck, boost, and buckboost converters to obtain small signal linear equivalent circuit models that represent both input and output properties. The results of these analyses are presented in the form of linear equivalent circuit models as well as transfer functions.     

PtRu nanoparticles supported on nitrogen-doped multiwalled carbon nanotubes as catalyst for methanol electrooxidation

Nitrogen-doped carbon nanotubes (N-CNT) obtained by plasma treatment were compared to the conventional acid-treated carbon nanotubes (O-CNT) as catalyst support for platinum-ruthenium (PtRu) nanoparticles in the anodic oxidation of methanol in direct methanol fuel cells. PtRu catalysts were prepared by an impregnation-reduction method from chloride precursors with metal loadings of 20 wt.%, and were characterised by scanning electron microscopy, transmission electron microscopy, X-ray diffraction, X-ray photoelectron spectroscopy and electrochemical methods. Voltammetry and chronoamperometry studies showed that the performance of PtRu/N-CNT was significantly higher compared to PtRu/O-CNT and also to the commercial E-TEK PtRu/C catalyst, indicating that N-CNT are an interesting support material for fuel cell electrocatalyst. Nitrogen plasma treatment produced pyridinic and pyrrollic species on the CNT surface, which acts as the anchoring sites for the deposition of PtRu particles. A mechanism for the deposition of PtRu on N-CNT is tentatively proposed and discussed.     

Inductive logic programming for knowledge discovery from MRI data

Describes a tool for quantitatively discriminating between meningioma and astrocytoma tumors. One of the uses of magnetic resonance imaging (MRI) in clinical diagnosis is in-vivo discrimination between tumor and normal tissue and between tumor types in the brain. There is much interest in increasing the qualitative and quantitative information available from these images. This article presents a study that uses the inductive logic programming tool Progol on measurements of signal intensities in clinical scan images of 28 patients (18 with meningiomas and 10 with astrocytomas) to attempt to discover knowledge that quantitatively dissriminates between the two types of tumors