Fast insect damage detection in wheat kernels using transmittance images

We used transmittance images and different learning algorithms to classify insect damaged and un-damaged wheat kernels. Using the histogram of the pixels of the wheat images as the feature, and the linear model as the learning algorithm, we achieved a False Positive Rate (1-specificity) of 0.12 at the True Positive Rate (sensitivity) of 0.8 and an Area Under the ROC Curve (AUC) of 0.90 ± 0.02. Combining the linear model and a Radial Basis Function Network in a committee resulted in a FP Rate of 0.09 at the TP Rate of 0.8 and an AUC of 0.93 ± 0.03

Identification of insect damaged wheat kernels using transmittance images

We used transmittance images and different learning algorithms to classify insect damaged and un-damaged wheat kernels. Using the histogram of the pixels of the wheat images as the feature, and the linear model as the learning algorithm, we achieved a False Positive Rate (1-specificity) of 0.2 at the True Positive Rate (sensitivity) of 0.8 and an Area Under the ROC Curve (AUC) of 0.86. Combining the linear model and a Radial Basis Function Network in a committee resulted in a FP Rate of 0.1 at the TP Rate of 0.8 and an AUC of 0.92. © 2004 IEEE

Elevated Expression of Squamous Cell Carcinoma Antigen (SCCA) Is Associated with Human Breast Carcinoma

Squamous cell carcinoma antigen (SCCA) belongs to the serine protease inhibitor (Serpin) family of proteins. Elevated expression of SCCA has been used as a biomarker for aggressive squamous cell carcinoma (SCC) in cancers of the cervix, lung, head and neck, and liver. However, SCCA expression in breast cancer has not been investigated. Immunohistochemical analysis of SCCA expression was performed on tissue microarrays containing breast tumor tissues (n = 1,360) and normal breast epithelium (n = 124). SCCA expression was scored on a tiered scale (0-3) independently by two evaluators blind to the patient's clinical status. SCCA expression was observed in Grade I (0.3%), Grade II (2.5%), and Grade III (9.4%) breast cancers (p<0.0001). Comparing tissues categorized into the three non-metastatic TNM stages, I-III, SCCA positivity was seen in 2.4% of Stage I cancers, 3.1% of Stage II cancers, and 8.6% of Stage III breast cancers (p = 0.0005). No positive staining was observed in normal/non-neoplastic breast tissue (0 out of 124). SCCA expression also correlated to estrogen receptor/progesterone receptor (ER/PR) double-negative tumors (p = 0.0009). Compared to SCCA-negative patients, SCCA-positive patients had both a worse overall survival and recurrence-free survival (p<0.0001 and p<0.0001, respectively). This study shows that SCCA is associated with both advanced stage and high grade human breast carcinoma, and suggests the necessity to further explore the role of SCCA in breast cancer development and treatment

Fatty acid binding protein 4 is expressed in distinct endothelial and non-endothelial cell populations in glioblastoma

AIMS: Glioblastoma (GBM) is the most common and aggressive primary brain tumour in adults. Angiogenesis and vasculogenesis play key roles in progression of GBMs. Fatty acid binding protein 4 (FABP4) is an intracellular chaperone for free fatty acids. FABP4 is detected in microvascular endothelial cells (ECs) in several normal tissues and promotes proliferation of ECs. The goal of this study was to characterize the tissue distribution pattern of FABP4 in GBMs. METHODS: Immunohistochemistry for FABP4 was performed on paraffin-embedded tumour sections and the intensity and distribution of FABP4 immunoreactivity were analysed. Double immunofluorescence was employed for detailed characterization of FABP4-positive cells. RESULTS: FABP4 immunoreactivity was absent in normal brain tissue sections. FABP4-positive cells were detected in 33%, 43%, 64% and 89% of Grade I, Grade II, Grade III and Grade IV glial tumours, respectively. Thus, the percentage of FABP4-positive cells in GBMs was significantly higher than lower-grade gliomas. In general, FABP4-expressing cells were distributed in a non-homogenous pattern, as \u27hot spots\u27 in glial tumours. FABP4 expression was detected in a subset of vascular ECs as well as some non-ECs. CONCLUSION: FABP4 is expressed in a significantly higher percentage of GBMs in comparison to both normal brain tissues and lower-grade glial tumours. FABP4 is expressed in some tumour ECs as well as non-ECs in glial tumours. As FABP4 promotes proliferation of ECs, detection of FABP4 in GBM-ECs, but not normal brain ECs suggests that FABP4 may play a role in the robust angiogenesis associated with GBMs. Neuropathological Society

Genre classification using chords and stochastic language models

Music genre meta-data is of paramount importance for the organisation of music repositories. People use genre in a natural way when entering a music store or looking into music collections. Automatic genre classification has become a popular topic in music information retrieval research both, with digital audio and symbolic data. This work focuses on the symbolic approach, bringing to music cognition some technologies, like the stochastic language models, already successfully applied to text categorisation. The representation chosen here is to model chord progressions as n-grams and strings and then apply perplexity and naiumlve Bayes classifiers, respectively, in order to assess how often those structures are found in the target genres. Some genres and sub-genres among popular, jazz, and academic music have been considered, trying to investigate how far can we reach using harmonic information with these models. The results at different leve! ls of the genre hierarchy for the techniques employed are presented and discussed.This work is supported by the Spanish CICyT PROSEMUS project (TIN2006-14932-C02), the research programme Consolider Ingenio 2010 (MIPRCV, CSD2007-00018) and the Pascal Network of Excellence

Imbalance between Cysteine Proteases and Inhibitors in a Baboon Model of Bronchopulmonary Dysplasia

Rationale: Bronchopulmonary dysplasia (BPD) continues to be a major morbidity in preterm infants. The lung pathology in BPD is characterized by impaired alveolar and capillary development. An imbalance between proteases and protease inhibitors in association with changes in lung elastic fibers has been implicated in the pathogenesis of BPD

Music Genre Classification Using MIDI and Audio Features

We report our findings on using MIDI files and audio features from MIDI, separately and combined together, for MIDI music genre classification. We use McKay and Fujinaga&#39;s 3-root and 9-leaf genre data set. In order to compute distances between MIDI pieces, we use normalized compression distance (NCD). NCD uses the compressed length of a string as an approximation to its Kolmogorov complexity and has previously been used for music genre and composer clustering. We convert the MIDI pieces to audio and then use the audio features to train different classifiers. MIDI and audio from MIDI classifiers alone achieve much smaller accuracies than those reported by McKay and Fujinaga who used not NCD but a number of domain-based MIDI features for their classification. Combining MIDI and audio from MIDI classifiers improves accuracy and gets closer to, but still worse, accuracies than McKay and Fujinaga&#39;s. The best root genre accuracies achieved using MIDI, audio, and combination of them are 0.75, 0.86, and 0.93, respectively, compared to 0.98 of McKay and Fujinaga. Successful classifier combination requires diversity of the base classifiers. We achieve diversity through using certain number of seconds of the MIDI file, different sample rates and sizes for the audio file, and different classification algorithms