An efficient hybrid approach for design of automotive wheel bearings

Wheel bearings play a crucial role in the mobility of a vehicle by minimizing motive power loss and providing stability in cornering maneuvers. Detailed engineering analysis of a wheel bearing subsystem under dynamic conditions poses enormous challenges due to the nonlinearity of the problem caused by multiple factional contacts between rotating and stationary parts and difficulties in prediction of dynamic loads that wheels are subject to. Commonly used design methodologies are based on equivalent static analysis of ball or roller bearings in which the latter elements may even be represented with springs. In the present study, an advanced hybrid approach is suggested for realistic dynamic analysis of wheel bearings by combining lumped parameter and finite element modeling techniques. A validated lumped parameter representation serves as an efficient tool for the prediction of radial wheel load due to ground reaction which is then used in detailed finite element analysis that automatically accounts for contact forces in an explicit formulation.

EFFECT OF OFF-STOICHIOMETRY AND TERNARY ADDITIONS ON PLANAR FAULT ENERGIES IN Ni3Al

First principles calculations were done to evaluate the lattice parameter, cohesive energy and stacking fault energies of ordered gamma' (Ll(2)) precipitates in superalloys as a function of composition. It was found that addition of Ti and Ta lead to an increase in lattice parameter and decrease in cohesive energy, while Ni antisites had the opposite effect. Ta and Ti addition to stoichiometric Ni3Al resulted in an initial increase in the energies of APB((111)), CSF(111), APB((001)) and SISF(111). However, at higher concentrations, the fault energies decreased. Addition of Ni antisites decreased the energy of all four faults monotonically. A model based on nearest neighbor bonding was used for Ni-3(Al, Ta), Ni-3(Al, Ti) and Ni-3(Al, Ni) pseudo-binary systems and extended to pseudo- ternary Ni-3(Al, Ta, Ni) and Ni-3(Al, Ti, Ni) systems. Recipes were developed for predicting lattice parameters, cohesive energies and fault energies in pseudo- ternary systems on the basis of coefficients derived from simpler pseudobinary systems. The model predictions were found to be in good agreement with first principles calculations for lattice parameters, cohesive energies, and energies of APB((111)) and CSF(111).

Identification of a biomarker panel for colorectal cancer diagnosis

Background: Malignancies arising in the large bowel cause the second largest number of deaths from cancer in the Western World. Despite progresses made during the last decades, colorectal cancer remains one of the most frequent and deadly neoplasias in the western countries. Methods: A genomic study of human colorectal cancer has been carried out on a total of 31 tumoral samples, corresponding to different stages of the disease, and 33 non-tumoral samples. The study was carried out by hybridisation of the tumour samples against a reference pool of non-tumoral samples using Agilent Human 1A 60- mer oligo microarrays. The results obtained were validated by qRT-PCR. In the subsequent bioinformatics analysis, gene networks by means of Bayesian classifiers, variable selection and bootstrap resampling were built. The consensus among all the induced models produced a hierarchy of dependences and, thus, of variables. Results: After an exhaustive process of pre-processing to ensure data quality–lost values imputation, probes quality, data smoothing and intraclass variability filtering–the final dataset comprised a total of 8, 104 probes. Next, a supervised classification approach and data analysis was carried out to obtain the most relevant genes. Two of them are directly involved in cancer progression and in particular in colorectal cancer. Finally, a supervised classifier was induced to classify new unseen samples. Conclusions: We have developed a tentative model for the diagnosis of colorectal cancer based on a biomarker panel. Our results indicate that the gene profile described herein can discriminate between non-cancerous and cancerous samples with 94.45% accuracy using different supervised classifiers (AUC values in the range of 0.997 and 0.955).

Diagnosis and the management constituency of small-scale fisheries

Diagnosis and adaptive management can help improve the ability of small-scale fisheries (SSF) in the developing world to better cope with and adapt to both external drivers and internal sources of uncertainty. This paper presents a framework for diagnosis and adaptive management and discusses ways of implementing the first two phases of learning: diagnosis and mobilising an appropriate management constituency. The discussion addresses key issues and suggests suitable approaches and tools as well as numerous sources of further information. Diagnosis of a SSF defines the system to be managed, outlines the scope of the management problem in terms of threats and opportunities, and aims to construct realistic and desired future projections for the fishery. These steps can clarify objectives and lead to development of indicators necessary for adaptive management. Before management, however, it is important to mobilize a management constituency to enact change. Ways of identifying stakeholders and understanding both enabling and obstructive interactions and management structures are outlined. These preliminary learning phases for adaptive SSF management are expected to work best if legitimised by collaborative discussion among fishery stakeholders drawing on multiple knowledge systems and participatory approaches to assessment. (PDF contains 33 pages)

On the Selection of Non-Invasive Methods Based on Speech Analysis Oriented to Automatic Alzheimer Disease Diagnosis

The work presented here is part of a larger study to identify novel technologies and biomarkers for early Alzheimer disease (AD) detection and it focuses on evaluating the suitability of a new approach for early AD diagnosis by non-invasive methods. The purpose is to examine in a pilot study the potential of applying intelligent algorithms to speech features obtained from suspected patients in order to contribute to the improvement of diagnosis of AD and its degree of severity. In this sense, Artificial Neural Networks (ANN) have been used for the automatic classification of the two classes (AD and control subjects). Two human issues have been analyzed for feature selection: Spontaneous Speech and Emotional Response. Not only linear features but also non-linear ones, such as Fractal Dimension, have been explored. The approach is non invasive, low cost and without any side effects. Obtained experimental results were very satisfactory and promising for early diagnosis and classification of AD patients.

Vibration response of a wind-turbine planetary gear set in the presence of a localized planet bearing defect

In a wind-turbine gearbox, planet bearings exhibit a high failure rate and are considered as one of the most critical components. Development of efficient vibration based fault detection methods for these bearings requires a thorough understanding of their vibration signature. Much work has been done to study the vibration properties of healthy planetary gear sets and to identify fault frequencies in fixed-axis bearings. However, vibration characteristics of planetary gear sets containing localized planet bearing defects (spalls or pits) have not been studied so far. In this paper, we propose a novel analytical model of a planetary gear set with ring gear flexibility and localized bearing defects as two key features. The model is used to simulate the vibration response of a planetary system in the presence of a defective planet bearing with faults on inner or outer raceway. The characteristic fault signature of a planetary bearing defect is determined and sources of modulation sidebands are identified. The findings from this work will be useful to improve existing sensor placement strategies and to develop more sophisticated fault detection algorithms. Copyright © 2011 by ASME.

Planning the deployment of fault-tolerant wireless sensor networks

Since Wireless Sensor Networks (WSNs) are subject to failures, fault-tolerance becomes an important requirement for many WSN applications. Fault-tolerance can be enabled in different areas of WSN design and operation, including the Medium Access Control (MAC) layer and the initial topology design. To be robust to failures, a MAC protocol must be able to adapt to traffic fluctuations and topology dynamics. We design ER-MAC that can switch from energy-efficient operation in normal monitoring to reliable and fast delivery for emergency monitoring, and vice versa. It also can prioritise high priority packets and guarantee fair packet deliveries from all sensor nodes. Topology design supports fault-tolerance by ensuring that there are alternative acceptable routes to data sinks when failures occur. We provide solutions for four topology planning problems: Additional Relay Placement (ARP), Additional Backup Placement (ABP), Multiple Sink Placement (MSP), and Multiple Sink and Relay Placement (MSRP). Our solutions use a local search technique based on Greedy Randomized Adaptive Search Procedures (GRASP). GRASP-ARP deploys relays for (k,l)-sink-connectivity, where each sensor node must have k vertex-disjoint paths of length ≤ l. To count how many disjoint paths a node has, we propose Counting-Paths. GRASP-ABP deploys fewer relays than GRASP-ARP by focusing only on the most important nodes – those whose failure has the worst effect. To identify such nodes, we define Length-constrained Connectivity and Rerouting Centrality (l-CRC). Greedy-MSP and GRASP-MSP place minimal cost sinks to ensure that each sensor node in the network is double-covered, i.e. has two length-bounded paths to two sinks. Greedy-MSRP and GRASP-MSRP deploy sinks and relays with minimal cost to make the network double-covered and non-critical, i.e. all sensor nodes must have length-bounded alternative paths to sinks when an arbitrary sensor node fails. We then evaluate the fault-tolerance of each topology in data gathering simulations using ER-MAC.

Raman microscopy in the diagnosis and prognosis of surgically resected nonsmall cell lung cancer

The main curative therapy for patients with nonsmall cell lung cancer is surgery. Despite this, the survival rate is only 50%, therefore it is important to more efficiently diagnose and predict prognosis for lung cancer patients. Raman spectroscopy is useful in the diagnosis of malignant and premalignant lesions. The aim of this study is to investigate the ability of Raman microscopy to diagnose lung cancer from surgically resected tissue sections, and predict the prognosis of these patients. Tumor tissue sections from curative resections are mapped by Raman microscopy and the spectra analzsed using multivariate techniques. Spectra from the tumor samples are also compared with their outcome data to define their prognostic significance. Using principal component analysis and random forest classification, Raman microscopy differentiates malignant from normal lung tissue. Principal component analysis of 34 tumor spectra predicts early postoperative cancer recurrence with a sensitivity of 73% and specificity of 74%. Spectral analysis reveals elevated porphyrin levels in the normal samples and more DNA in the tumor samples. Raman microscopy can be a useful technique for the diagnosis and prognosis of lung cancer patients receiving surgery, and for elucidating the biochemical properties of lung tumors. (C) 2010 Society of Photo-Optical Instrumentation Engineers. [DOI: 10.1117/1.3323088]

Clinical Utility of Microarray-Based Gene Expression Profiling in the Diagnosis and Subclassification of Leukemia: Report From the International Microarray Innovations in Leukemia Study Group

The Microarray Innovations in Leukemia study assessed the clinical utility of gene expression profiling as a single test to subtype leukemias into conventional categories of myeloid and lymphoid malignancies. METHODS: The investigation was performed in 11 laboratories across three continents and included 3,334 patients. An exploratory retrospective stage I study was designed for biomarker discovery and generated whole-genome expression profiles from 2,143 patients with leukemias and myelodysplastic syndromes. The gene expression profiling-based diagnostic accuracy was further validated in a prospective second study stage of an independent cohort of 1,191 patients. RESULTS: On the basis of 2,096 samples, the stage I study achieved 92.2% classification accuracy for all 18 distinct classes investigated (median specificity of 99.7%). In a second cohort of 1,152 prospectively collected patients, a classification scheme reached 95.6% median sensitivity and 99.8% median specificity for 14 standard subtypes of acute leukemia (eight acute lymphoblastic leukemia and six acute myeloid leukemia classes, n = 693). In 29 (57%) of 51 discrepant cases, the microarray results had outperformed routine diagnostic methods. CONCLUSION: Gene expression profiling is a robust technology for the diagnosis of hematologic malignancies with high accuracy. It may complement current diagnostic algorithms and could offer a reliable platform for patients who lack access to today's state-of-the-art diagnostic work-up. Our comprehensive gene expression data set will be submitted to the public domain to foster research focusing on the molecular understanding of leukemias

Seasonality of cutaneous melanoma diagnosis in Northern Ireland with a review

In light-skinned populations, the incidence of cutaneous melanoma is highest in summer and lowest in winter. We analyzed the seasonal variation of melanoma incidence in Northern Ireland from 1984 to 2006 according to the Breslow thickness and body site. We also reviewed earlier studies on seasonal variation in the diagnosis of melanoma. Two-thirds of melanomas in women (2028 cases) and one-third of melanomas in men (1230 cases) were diagnosed on the limbs. In both sexes, pronounced seasonal variations were observed in the incidence of invasive melanomas less than 2mm arising on the limbs. These seasonal variations were mainly noticeable in women of all ages, to a lesser degree in men aged below 50 years, and not in men aged above 50 years. No seasonal variation was observed for melanomas less than 2mm arising on the trunk or the head and neck nor for melanomas 2mm thickness or more, irrespective of the age, sex, and body site. Seasonal variations of thin melanomas were less noticeable in men because of the axial predominance of melanoma occurrence in this sex. The review of 15 earlier studies found by a systematic search of Medline supported the likelihood of our findings. This analysis suggests that ultraviolet radiation has a short-term promotional effect on melanocytes or nevocytes of the limbs, and is not associated with progression from thin to thick melanoma. Melanoma Res 21:144-151 (C) 2011 Wolters Kluwer Health vertical bar Lippincott Williams & Wilkins.

Increased diagnosis and detection rates of carcinoma in situ of the breast

The purpose of this study was to identify trends in the diagnosis of carcinoma in situ (CIS) of the breast in the United Kingdom (UK) and the Republic of Ireland (ROI) and to examine the impact of mammography. Data on cases of newly diagnosed CIS of the breast and mode of detection (screen detected or not) were obtained, where available, from regional cancer registries between 1990 and 2007. Age-standardised diagnosis rates for the UK and the ROI, and regional screen detected diagnosis rates were compared by calculating the annual percentage change (APC) over time. The APC of the diagnosis rate amongst women aged 50-64 years (original screening age group) showed a significant 5.9% increase in the UK (1990-2007) and 11.5% increase in the ROI (1994-2007). The rate of diagnosis (50-64 years) stabilized in the UK between 2005 and 2007 and was substantially higher than in other western populations with national screening programmes. The APC of the diagnosis rate amongst those aged 65-69 years showed a significant 12.4% increase in the UK (1990-2007) and 10.3% increase in the ROI (1994-2007). amongst women aged 50-74 years in the UK, approximately 4,300 cases of CIS (˜90% ductal carcinoma in situ) were diagnosed in 2007. Our analyses have shown that screen detected CIS contributed primarily to the increase in diagnosis of CIS of the breast. The high diagnosis rate of screen detected CIS of the breast underlines the need for further research into lesion and patient characteristics that are related to progression of CIS to invasive disease to better target treatment. © 2012 Springer Science+Business Media, LLC.

The accuracy of accredited glaucoma optometrists in the diagnosis and treatment recommendation for glaucoma

Aim: To compare the diagnostic performance of accredited glaucoma optometrists (AGO) for both the diagnosis of glaucoma and the decision to treat with that of routine hospital eye care, against a reference standard of expert opinion (a consultant ophthalmologist with a special interest in glaucoma). Methods: A directly comparative, masked, performance study was undertaken in Grampian, Scotland. Of 165 people invited to participate, 100 (61%) were examined. People suspected of having glaucoma underwent, within one month, a full ophthalmic assessment in both a newly established community optometry led glaucoma management scheme and a consultant led hospital eye service. Results: Agreement between the AGO and the consultant ophthalmologist in diagnosing glaucoma was substantial (89%; ? = 0.703, SE = 0.083). Agreement over the need for treatment was also substantial (88%; ? = 0.716, SE = 0.076). The agreement between the trainee ophthalmologists and the consultant ophthalmologist in the diagnosis of glaucoma and treatment recommendation was moderate (83%, ? = 0.541, SE = 0.098, SE = 0.98; and 81%, ? = 0.553, SE = 0.90, respectively). The diagnostic accuracy of the optometrists in detecting glaucoma in this population was high for specificity (0.93 (95% confidence interval, 0.85 to 0.97)) but lower for sensitivity (0.76 (0.57 to 0.89)). Performance was similar when accuracy was assessed for treatment recommendation (sensitivity 0.73 (0.57 to 0.85); specificity 0.96 (0.88 to 0.99)). The differences in sensitivity and specificity between AGO and junior ophthalmologist were not statistically significant. Conclusions: Community optometrists trained in glaucoma provided satisfactory decisions regarding diagnosis and initiation of treatment for glaucoma. With such additional training in glaucoma, optometrists are at least as accurate as junior ophthalmologists but some cases of glaucoma are missed.

Fault Diagnostics for Internal Combustion Engines – Current and Future Techniques

The adoption of each new level of automotive emissions legislation often requires the introduction of additional emissions reduction techniques or the development of existing emissions control systems. This, in turn, usually requires the implementation of new sensors and hardware which must subsequently be monitored by the on-board fault detection systems. The reliable detection and diagnosis of faults in these systems or sensors, which result in the tailpipe emissions rising above the progressively lower failure thresholds, provides enormous challenges for OBD engineers. This paper gives a review of the field of fault detection and diagnostics as used in the automotive industry. Previous work is discussed and particular emphasis is placed on the various strategies and techniques employed. Methodologies such as state estimation, parity equations and parameter estimation are explained with their application within a physical model diagnostic structure. The utilization of symptoms and residuals in the diagnostic process is also discussed. These traditional physical model based diagnostics are investigated in terms of their limitations. The requirements from the OBD legislation are also addressed. Additionally, novel diagnostic techniques, such as principal component analysis (PCA) are also presented as a potential method of achieving the monitoring requirements of current and future OBD legislation.

Achalasia: A review of clinical diagnosis, epidemiology, treatment and outcomes

Achalasia is a neurodegenerative motility disorder of the oesophagus resulting in deranged oesophageal peristalsis and loss of lower oesophageal sphincter function. Historically, annual achalasia incidence rates were believed to be low, approximately 0.5-1.2 per 100000. More recent reports suggest that annual incidence rates have risen to 1.6 per 100000 in some populations. The aetiology of achalasia is still unclear but is likely to be multi-factorial. Suggested causes include environmental or viral exposures resulting in inflammation of the oesophageal myenteric plexus, which elicits an autoimmune response. Risk of achalasia may be elevated in a sub-group of genetically susceptible people. Improvement in the diagnosis of achalasia, through the introduction of high resolution manometry with pressure topography plotting, has resulted in the development of a novel classification system for achalasia. This classification system can evaluate patient prognosis and predict responsiveness to treatment. There is currently much debate over whether pneumatic dilatation is a superior method compared to the Heller's myotomy procedure in the treatment of achalasia. A recent comparative study found equal efficacy, suggesting that patient preference and local expertise should guide the choice. Although achalasia is a relatively rare condition, it carries a risk of complications, including aspiration pneumonia and oesophageal cancer. The risk of both squamous cell carcinoma and adenocarcinoma of the oesophagus is believed to be significantly increased in patients with achalasia, however the absolute excess risk is small. Therefore, it is currently unknown whether a surveillance programme in achalasia patients would be effective or cost-effective.