Condition monitoring and fault diagnosis of diesel engines using instantaneous angular speed analysis

Continuous monitoring of diesel engine performance is critical for early detection of fault developments in an engine before they materialize into a functional failure. Instantaneous crank angular speed (IAS) analysis is one of a few nonintrusive condition monitoring techniques that can be utilized for such a task. Furthermore, the technique is more suitable for mass industry deployments than other non-intrusive methods such as vibration and acoustic emission techniques due to the low instrumentation cost, smaller data size and robust signal clarity since IAS is not affected by the engine operation noise and noise from the surrounding environment. A combination of IAS and order analysis was employed in this experimental study and the major order component of the IAS spectrum was used for engine loading estimation and fault diagnosis of a four-stroke four-cylinder diesel engine. It was shown that IAS analysis can provide useful information about engine speed variation caused by changing piston momentum and crankshaft acceleration during the engine combustion process. It was also found that the major order component of the IAS spectra directly associated with the engine firing frequency (at twice the mean shaft rotating speed) can be utilized to estimate engine loading condition regardless of whether the engine is operating at healthy condition or with faults. The amplitude of this order component follows a distinctive exponential curve as the loading condition changes. A mathematical relationship was then established in the paper to estimate the engine power output based on the amplitude of this order component of the IAS spectrum. It was further illustrated that IAS technique can be employed for the detection of a simulated exhaust valve fault in this study.

Critical dependence of blood-borne biomarker concentrations on the half-lives of their carrier proteins

Until recently, the low-abundance (LA) range of the serum proteome was an unexplored reservoir of diagnostic information. Today it is increasingly appreciated that a diagnostic goldmine of LA biomarkers resides in the blood stream in complexed association with more abundant higher molecular weight carrier proteins such as albumin and immunoglobulins. As we now look to the possibility of harvesting these LA biomarkers more efficiently through engineered nano-scale particles, mathematical approaches are needed in order to reveal the mechanisms by which blood carrier proteins act as molecular 'mops' for LA diagnostic cargo, and the functional relationships between bound LA biomarker concentrations and other variables of interest such as biomarker intravasation and clearance rates and protein half-lives in the bloodstream. Here we show, by simple mathematical modeling, how the relative abundance of large carrier proteins and their longer half-lives in the bloodstream work together to amplify the total blood concentration of these tiny biomarkers. The analysis further suggests that alterations in the production of biomarkers lead to gradual rather than immediate changes in biomarker levels in the blood circulation. The model analysis also points to the characteristics of artificial nano-particles that would render them more efficient harvesters of tumor biomarkers in the circulation, opening up possibilities for the early detection of curable disease, rather than simply better detection of advanced disease.

Automated diagnosis of Age-related Macular Degeneration using greyscale features from digital fundus images

Age-related Macular Degeneration (AMD) is one of the major causes of vision loss and blindness in ageing population. Currently, there is no cure for AMD, however early detection and subsequent treatment may prevent the severe vision loss or slow the progression of the disease. AMD can be classified into two types: dry and wet AMDs. The people with macular degeneration are mostly affected by dry AMD. Early symptoms of AMD are formation of drusen and yellow pigmentation. These lesions are identified by manual inspection of fundus images by the ophthalmologists. It is a time consuming, tiresome process, and hence an automated diagnosis of AMD screening tool can aid clinicians in their diagnosis significantly. This study proposes an automated dry AMD detection system using various entropies (Shannon, Kapur, Renyi and Yager), Higher Order Spectra (HOS) bispectra features, Fractional Dimension (FD), and Gabor wavelet features extracted from greyscale fundus images. The features are ranked using t-test, Kullback–Lieber Divergence (KLD), Chernoff Bound and Bhattacharyya Distance (CBBD), Receiver Operating Characteristics (ROC) curve-based and Wilcoxon ranking methods in order to select optimum features and classified into normal and AMD classes using Naive Bayes (NB), k-Nearest Neighbour (k-NN), Probabilistic Neural Network (PNN), Decision Tree (DT) and Support Vector Machine (SVM) classifiers. The performance of the proposed system is evaluated using private (Kasturba Medical Hospital, Manipal, India), Automated Retinal Image Analysis (ARIA) and STructured Analysis of the Retina (STARE) datasets. The proposed system yielded the highest average classification accuracies of 90.19%, 95.07% and 95% with 42, 54 and 38 optimal ranked features using SVM classifier for private, ARIA and STARE datasets respectively. This automated AMD detection system can be used for mass fundus image screening and aid clinicians by making better use of their expertise on selected images that require further examination.

Decision support system for age-related macular degeneration using discrete wavelet transform

Age-related macular degeneration (AMD) affects the central vision and subsequently may lead to visual loss in people over 60 years of age. There is no permanent cure for AMD, but early detection and successive treatment may improve the visual acuity. AMD is mainly classified into dry and wet type; however, dry AMD is more common in aging population. AMD is characterized by drusen, yellow pigmentation, and neovascularization. These lesions are examined through visual inspection of retinal fundus images by ophthalmologists. It is laborious, time-consuming, and resource-intensive. Hence, in this study, we have proposed an automated AMD detection system using discrete wavelet transform (DWT) and feature ranking strategies. The first four-order statistical moments (mean, variance, skewness, and kurtosis), energy, entropy, and Gini index-based features are extracted from DWT coefficients. We have used five (t test, Kullback–Lieber Divergence (KLD), Chernoff Bound and Bhattacharyya Distance, receiver operating characteristics curve-based, and Wilcoxon) feature ranking strategies to identify optimal feature set. A set of supervised classifiers namely support vector machine (SVM), decision tree, k -nearest neighbor ( k -NN), Naive Bayes, and probabilistic neural network were used to evaluate the highest performance measure using minimum number of features in classifying normal and dry AMD classes. The proposed framework obtained an average accuracy of 93.70 %, sensitivity of 91.11 %, and specificity of 96.30 % using KLD ranking and SVM classifier. We have also formulated an AMD Risk Index using selected features to classify the normal and dry AMD classes using one number. The proposed system can be used to assist the clinicians and also for mass AMD screening programs.

miRNAs in head and neck cancer revisited

Head and neck squamous cell carcinoma (HNSCC) is the sixth most common cause of cancer mortality in the world and the 5th most commonly occurring cancer. Tobacco smoking, alcohol consumption and human papilloma virus (HPV) infections have been associated with the occurrence of HNSCC. Despite advances that have been made in HNSCC treatment, smoking-associated HNSCC patients still exhibit a poor 5 year survival rate (30-50 %) and a concomitant poor quality of life. The major clinical challenge to date lies in the early detection of dysplastic lesions,which can progress to malignancy. In addition, there are currently no tools available to monitor HNSCC patients for early stages of local recurrences or distant metastases. In the recent past, micro-RNAs (miRNA) have been assessed for their role in cancer initiation and progression, including HNSCC. It is now well-established that deregulation of these single stranded, small non-coding, 19-25 nt RNAs can e.g. enhance the expression of oncogenes or subdue the expression of tumor suppressor genes. The aims of this review are three-fold: first to retrieve from the literature miRNAs that have specifically been associated with HNSCC, second to group these miRNAs into those regulating tumor initiation, progression and metastasis, and third to discern miRNAs related to smoking-associated HNSCC versus HPV-associated HNSCC development. This review gives an overview on the miRNAs regulating the development of head and neck cancers. The ultimate establishment of miRNA expression profiles that are HNSCC specific, and miRNAs that orchestrate altered gene and protein expression levels in HNSCC, could pave the way for a better understanding of the mechanism underlying its pathogenesis and the development of novel, targeted therapies.

A simple nutrition screening tool for paediatric inpatients

Background: Pediatric nutrition risk screening tools are not routinely implemented throughout many hospitals, despite prevalence studies demonstrating malnutrition is common in hospitalized children. Existing tools lack the simplicity of those used to assess nutrition risk in the adult population. This study reports the accuracy of a new, quick, and simple pediatric nutrition screening tool (PNST) designed to be used for pediatric inpatients. Materials and Methods: The pediatric Subjective Global Nutrition Assessment (SGNA) and anthropometric measures were used to develop and assess the validity of 4 simple nutrition screening questions comprising the PNST. Participants were pediatric inpatients in 2 tertiary pediatric hospitals and 1 regional hospital. Results: Two affirmative answers to the PNST questions were found to maximize the specificity and sensitivity to the pediatric SGNA and body mass index (BMI) z scores for malnutrition in 295 patients. The PNST identified 37.6% of patients as being at nutrition risk, whereas the pediatric SGNA identified 34.2%. The sensitivity and specificity of the PNST compared with the pediatric SGNA were 77.8% and 82.1%, respectively. The sensitivity of the PNST at detecting patients with a BMI z score of less than -2 was 89.3%, and the specificity was 66.2%. Both the PNST and pediatric SGNA were relatively poor at detecting patients who were stunted or overweight, with the sensitivity and specificity being less than 69%. Conclusion: The PNST provides a sensitive, valid, and simpler alternative to existing pediatric nutrition screening tools such as Screening Tool for the Assessment of Malnutrition in Pediatrics (STAMP), Screening Tool Risk on Nutritional status and Growth (STRONGkids), and Paediatric Yorkhill Malnutrition Score (PYMS) to ensure the early detection of hospitalized children at nutrition risk.

A pilot trial of mobile, patient-performed teledermoscopy

BACKGROUND Early detection by skin self-examination (SSE) could improve outcomes from melanoma. Mobile teledermoscopy may aid this process. OBJECTIVES To establish clinical accuracy of SSE plus mobile teledermoscopy compared to clinical skin examination (CSE) and test whether providing people with detailed SSE instructions improves accuracy. METHODS Men and women 50-64 years (n=58) performed SSE plus mobile teledermoscopy in their homes between May and November 2013 and were given technical instructions plus detailed SSE instructions (intervention) or technical instructions only (control). Within three months, they underwent a CSE. Outcome measures included: a) body sites examined, lesions photographed, and missed; b) sensitivityof SSE plus mobile teledermoscopy compared to in-person CSE using either patients or lesions as denominator, and; c) concordance of telediagnosis with CSE. RESULTS: 49 of 58 randomised participants completed the study, and submitted 309 lesions to the teledermatologist (156 intervention; 153 control group). Intervention group participants were more likely to submit lesions from their legs compared to control (p=0.03), no other differences between groups in number or site of missed lesions.11 participants (22%) did not photograph 14 pigmented lesions the dermatologist considered worthwhile photographing or requiring clinical monitoring. Sensitivity of SSE plus mobile teledermoscopy was 81.8% (95% confidence interval 64.5-93.0) using the patient as the denominator and 41.9 (27.6-56.2) using the lesion as denominator.-There was substantial agreement between telediagnosis and CSE (Kappa =0.90) accounting for differential diagnoses. CONCLUSIONS SSE plus mobile teledermoscopy is promising for surveillance of particular lesions even without provision of detailed SSE instructions, but in the format tested in this study, consumers may overlook lesions and send many non-pigmented lesions. This investigation demonstrates that high quality dermoscopic images can be taken by patients at home and for those sent, telediagnosis is highly accurate.

The relationship between emotional intelligence and depression in a clinical sample

Background and Objectives: Although depression is a commonly occurring mental illness, research concerning strategies for early detection and prophylaxis has not until now focused on the possible utility of measures of Emotional Intelligence (EI) as a potential predictive factor. The current study aimed to investigate the relationship between EI and a clinical diagnosis of depression in a cohort of adults. Methods: Sixty-two patients (59.70% female) with a DSM-IV-TR diagnosis of a major affective disorder and 39 aged matched controls (56.40% female) completed self-report instruments assessing EI and depression in a cross-sectional study. Results: Significant associations were observed between severity of depression and the EI dimensions of Emotional Management (r = -0.56) and Emotional Control (r = -0.62). The results show a reduced social involvement, an increased prior institutionalization and an increased incidence of "Schizophrenic Psychosis" and "Abnormal Personalities" in the sub-group of repeated admissions. Conclusions: Measures of EI may have predictive value in terms of early identification of those at risk for developing depression. The current study points to the potential value of conducting further studies of a prospective nature.

Automated melanoma diagnosis system

An automated melanoma diagnosis system, the so-called Skin Polar-probe, was developed to improve the chances of early detection of skin cancers and help save the lives of melanoma victims. The system will offer unique benefits to aid early detection of melanoma - the key to reducing deaths caused by this cancer.

Large-scale interlaboratory study to develop, analytically validate and apply highly multiplexed, quantitative peptide assays to measure cancer-relevant proteins in plasma

There is an increasing need in biology and clinical medicine to robustly and reliably measure tens-to-hundreds of peptides and proteins in clinical and biological samples with high sensitivity, specificity, reproducibility and repeatability. Previously, we demonstrated that LC-MRM-MS with isotope dilution has suitable performance for quantitative measurements of small numbers of relatively abundant proteins in human plasma, and that the resulting assays can be transferred across laboratories while maintaining high reproducibility and quantitative precision. Here we significantly extend that earlier work, demonstrating that 11 laboratories using 14 LC-MS systems can develop, determine analytical figures of merit, and apply highly multiplexed MRM-MS assays targeting 125 peptides derived from 27 cancer-relevant proteins and 7 control proteins to precisely and reproducibly measure the analytes in human plasma. To ensure consistent generation of high quality data we incorporated a system suitability protocol (SSP) into our experimental design. The SSP enabled real-time monitoring of LC-MRM-MS performance during assay development and implementation, facilitating early detection and correction of chromatographic and instrumental problems. Low to sub-nanogram/mL sensitivity for proteins in plasma was achieved by one-step immunoaffinity depletion of 14 abundant plasma proteins prior to analysis. Median intra- and inter-laboratory reproducibility was <20%, sufficient for most biological studies and candidate protein biomarker verification. Digestion recovery of peptides was assessed and quantitative accuracy improved using heavy isotope labeled versions of the proteins as internal standards. Using the highly multiplexed assay, participating laboratories were able to precisely and reproducibly determine the levels of a series of analytes in blinded samples used to simulate an inter-laboratory clinical study of patient samples. Our study further establishes that LC-MRM-MS using stable isotope dilution, with appropriate attention to analytical validation and appropriate quality c`ontrol measures, enables sensitive, specific, reproducible and quantitative measurements of proteins and peptides in complex biological matrices such as plasma.

The respiratory health of urban Indigenous children aged less than 5 years: Study protocol for a prospective cohort study

Background Despite the burden of acute respiratory illnesses (ARI) among Aboriginal and Torres Strait Islander children being a substantial cause of childhood morbidity and associated costs to families, communities and the health system, data on disease burden in urban children are lacking. Consequently evidence-based decision-making, data management guidelines, health resourcing for primary health care services and prevention strategies are lacking. This study aims to comprehensively describe the epidemiology, impact and outcomes of ARI in urban Aboriginal and Torres Strait Islander children (hereafter referred to as Indigenous) in the greater Brisbane area. Methods/design A prospective cohort study of Indigenous children aged less than five years registered with a primary health care service in Northern Brisbane, Queensland, Australia. Children are recruited at time of presentation to the service for any reason. Demographic, epidemiological, risk factor, microbiological, economic and clinical data are collected at enrolment. Enrolled children are followed for 12 months during which time ARI events, changes in child characteristics over time and monthly nasal swabs are collected. Children who develop an ARI with cough as a symptom during the study period are more intensely followed-up for 28(±3) days including weekly nasal swabs and parent completed cough diary cards. Children with persistent cough at day 28 post-ARI are reviewed by a paediatrician. Discussion Our study will be one of the first to comprehensively evaluate the natural history, epidemiology, aetiology, economic impact and outcomes of ARIs in this population. The results will inform studies for the development of evidence-based guidelines to improve the early detection, prevention and management of chronic cough and setting of priorities in children during and after ARI.

Application of higher-order spectra for automated grading of diabetic maculopathy

Diabetic macular edema (DME) is one of the most common causes of visual loss among diabetes mellitus patients. Early detection and successive treatment may improve the visual acuity. DME is mainly graded into non-clinically significant macular edema (NCSME) and clinically significant macular edema according to the location of hard exudates in the macula region. DME can be identified by manual examination of fundus images. It is laborious and resource intensive. Hence, in this work, automated grading of DME is proposed using higher-order spectra (HOS) of Radon transform projections of the fundus images. We have used third-order cumulants and bispectrum magnitude, in this work, as features, and compared their performance. They can capture subtle changes in the fundus image. Spectral regression discriminant analysis (SRDA) reduces feature dimension, and minimum redundancy maximum relevance method is used to rank the significant SRDA components. Ranked features are fed to various supervised classifiers, viz. Naive Bayes, AdaBoost and support vector machine, to discriminate No DME, NCSME and clinically significant macular edema classes. The performance of our system is evaluated using the publicly available MESSIDOR dataset (300 images) and also verified with a local dataset (300 images). Our results show that HOS cumulants and bispectrum magnitude obtained an average accuracy of 95.56 and 94.39 % for MESSIDOR dataset and 95.93 and 93.33 % for local dataset, respectively.

Mobile Romberg test assessment (mRomberg)

Background The diagnosis of frailty is based on physical impairments and clinicians have indicated that early detection is one of the most effective methods for reducing the severity of physical frailty. Maybe, an alternative to the classical diagnosis could be the instrumentalization of classical functional testing, as Romberg test or Timed Get Up and Go Test. The aim of this study was (I) to measure and describe the magnitude of accelerometry values in the Romberg test in two groups of frail and non-frail elderly people through instrumentation with the iPhone 4®, (II) to analyse the performances and differences between the study groups, and (III) to analyse the performances and differences within study groups to characterise accelerometer responses to increasingly difficult challenges to balance. Methods This is a cross-sectional study of 18 subjects over 70 years old, 9 frail subjects and 9 non-frail subjects. The non-parametric Mann–Whitney U test was used for between-group comparisons in means values derived from different tasks. The Wilcoxon Signed-Rank test was used to analyse differences between different variants of the test in both independent study groups. Results The highest difference between groups was found in the accelerometer values with eyes closed and feet parallel: maximum peak acceleration in the lateral axis (p < 0.01), minimum peak acceleration in the lateral axis (p < 0.01) and minimum peak acceleration from the resultant vector (p < 0.01). Subjects with eyes open and feet parallel, greatest differences found between the groups were in the maximum peak acceleration in the lateral axis (p < 0.01), minimum peak acceleration in the lateral axis (p < 0.01) and minimum peak acceleration from the resultant vector (p < 0.001). With eyes closed and feet in tandem, the greatest differences found between the groups were in the minimum peak acceleration in the lateral axis (p < 0.01). Conclusions The accelerometer fitted in the iPhone 4® is able to study and analyse the kinematics of the Romberg test between frail and non-frail elderly people. In addition, the results indicate that the accelerometry values also were significantly different between the frail and non-frail groups, and that values from the accelerometer accelerometer increased as the test was made more complicated.

Diffusion indices on magnetic resonance imaging and neuropsychological performance in amnestic mild cognitive impairment

Background: Magnetic resonance diffusion tensor imaging (DTI) shows promise in the early detection of microstructural pathophysiological changes in the brain. Objectives: To measure microstructural differences in the brains of participants with amnestic mild cognitive impairment (MCI) compared with an age-matched control group using an optimised DTI technique with fully automated image analysis tools and to investigate the correlation between diffusivity measurements and neuropsychological performance scores across groups. Methods: 34 participants (17 participants with MCI, 17 healthy elderly adults) underwent magnetic resonance imaging (MRI)-based DTI. To control for the effects of anatomical variation, diffusion images of all participants were registered to standard anatomical space. Significant statistical differences in diffusivity measurements between the two groups were determined on a pixel-by-pixel basis using gaussian random field theory. Results: Significantly raised mean diffusivity measurements (p<0.001) were observed in the left and right entorhinal cortices (BA28), posterior occipital-parietal cortex (BA18 and BA19), right parietal supramarginal gyrus (BA40) and right frontal precentral gyri (BA4 and BA6) in participants with MCI. With respect to fractional anisotropy, participants with MCI had significantly reduced measurements (p<0.001) in the limbic parahippocampal subgyral white matter, right thalamus and left posterior cingulate. Pearson's correlation coefficients calculated across all participants showed significant correlations between neuropsychological assessment scores and regional measurements of mean diffusivity and fractional anisotropy. Conclusions: DTI-based diffusivity measures may offer a sensitive method of detecting subtle microstructural brain changes associated with preclinical Alzheimer's disease.

Circulating tumour cells in metastatic head and neck cancers

Head and neck squamous cell carcinoma (HNSCC) is the sixth most common cancer with 650,000 new cases p/a worldwide. HNSCC causes high morbidity with a 5-year survival rate of less than 60%, which has not improved due to the lack of early detection (Bozec et al. Eur Arch Otorhinolaryngol. 2013;270: 2745–9). Metastatic disease remains one of the leading causes of death in HNSCC patients. This review article provides a comprehensive overview of literature over the past 5 years on the detection of circulating tumour cells (CTCs) in HNSCC; CTC biology and future perspectives. CTCs are a hallmark of invasive cancer cells and key to metastasis. CTCs can be used as surrogate markers of overall survival and progression-free survival. CTCs are currently used as prognostic factors for breast, prostate and colorectal cancers using the CellSearch® system. CTCs have been detected in HNSCC, however, these numbers depend on the technique applied, time of blood collection and the clinical stage of the patient. The impact of CTCs in HNSCC is not well understood, and thus, not in routine clinical practice. Validated detection technologies that are able to capture CTCs undergoing epithelial–mesenchymal transition are needed. This will aid in the capture of heterogeneous CTCs, which can be compiled as new targets for the current food and drug administration-cleared CellSearch® system. Recent studies on CTCs in HNSCC with the CellSearch® have shown variable data. Therefore, there is an immediate need for large clinical trials encompassing a suite of biomarkers capturing CTCs in HNSCC, before CTCs can be used as prognostic markers in HNSCC patient management.