Energy Disaggregation Using Elastic Matching Algorithms.

In this article an energy disaggregation architecture using elastic matching algorithms is presented. The architecture uses a database of reference energy consumption signatures and compares them with incoming energy consumption frames using template matching. In contrast to machine learning-based approaches which require significant amount of data to train a model, elastic matching-based approaches do not have a model training process but perform recognition using template matching.

Gauge Fixing the Standard Model Effective Field Theory.

We gauge-fix the standard model effective field theory in a manner invariant under background-field gauge transformations using a geometric description of the field connections.

Introducing dAUTObase: a first step towards the global scale geoepidemiology of autoimmune syndromes and diseases.

Motivation: An autoimmune disorder occurs when the immune system mistakenly attacks and destroys its own healthy body tissues. The initiation of a geoepidemiological database, for recording autoimmune incidents with a focus to clinical manifestations, demographic parameters and geographic background is crucial to detect correlations.

Results: The dAUTObase collects an ever increasing number of publications-currently counting 435-on autoimmune diseases' frequencies in various populations and ethnic groups.

Premalignant cervical lesions are characterized by dihydrofolate reductase gene amplification and c-Myc overexpression: possible biomarkers.

Objective: The c-Myc oncoprotein deregulation is associated with overall genomic instability and locus-specific genomic instability involving the dihydrofolate reductase (DHFR) locus. This study analyzes c-Myc protein levels and the stability of the DHFR gene in cervical tissue biopsies.

Materials And Methods: The stability of the DHFR gene was examined by fluorescence in situ hybridization (FISH).

Infrared spectroscopy of exfoliated cervical cell specimens. Proceed with caution.

Objective: To determine whether diagnostic information may be recovered from the infrared spectra of exfoliated cell specimens by using a novel spectral feature extraction method, in conjunction with linear and quadratic discriminant analysis, for spectral classification.

Study Design: Over 800 infrared spectra were included in the study, with corresponding clinical diagnoses based upon cytology and, when available, histology reports. Three sets of classification trials were carried out with the aim of distinguishing the spectra corresponding to normal specimens from CIN 1, 2 and 3.