Forest fires cluster detection with space-time scan statistics

Forest fires are defined as uncontrolled fires often occurring in wildland areas, but that can also affect houses or agricultural resources. Causes are both natural (e.g.,lightning phenomena) and anthropogenic (human negligence or arsons).Major environmental factors influencing the fire ignition and propagation are climate and vegetation. Wildfires are most common and severe during drought period and on windy days. Moreover, under water-stress conditions, which occur after a long hot and dry period, the vegetation is more vulnerable to fire. These conditions are common in the United State and Canada, where forest fires represent a big problem. We focused our analysis on the state of Florida, for which a big dataset on forest fires detection is readily available. USDA Forest Service Remote Sensing Application Center, in collaboration with NASA-Goddard Space Flight Center and the University of Maryland, has compiled daily MODIS Thermal Anomalies (fires and biomass burning images) produced by NASA using a contextual algorithm that exploits the strong emission of mid-infrared radiation from fires. Fire classes were converted in GIS format: daily MODIS fire detections are provided as the centroids of the 1 kilometer pixels and compiled into daily Arc/INFO point coverage.

Detection of neuronal activity and metabolism in a model of dehydration-induced anorexia in rats at 14.1 T using manganese-enhanced MRI and 1H MRS.

In this study, hypothalamic activation was performed by dehydration-induced anorexia (DIA) and overnight food suppression (OFS) in female rats. The assessment of the hypothalamic response to these challenges by manganese-enhanced MRI showed increased neuronal activity in the paraventricular nuclei (PVN) and lateral hypothalamus (LH), both known to be areas involved in the regulation of food intake. The effects of DIA and OFS were compared by generating T-score maps. Increased neuronal activation was detected in the PVN and LH of DIA rats relative to OFS rats. In addition, the neurochemical profile of the PVN and LH were measured by (1) H MRS at 14.1T. Significant increases in metabolite levels were measured in DIA and OFS relative to control rats. Statistically significant increases in γ-aminobutyric acid were found in DIA (p=0.0007) and OFS (p<0.001) relative to control rats. Lactate increased significantly in DIA (p=0.03), but not in OFS, rats. This work shows that manganese-enhanced MRI coupled to (1) H MRS at high field is a promising noninvasive method for the investigation of the neural pathways and mechanisms involved in the control of food intake, in the autonomic and endocrine control of energy metabolism and in the regulation of body weight.

Coulier, Paul-Jean (1824-1890) : a precursor in the history of fingermark detection and their potential use for identifying their source (1863)

An online copy of a 1863 French book, The Scientific and Industrial Year (English translation of the title), that predates other historically significant writings about fingerprints suggests the use of iodine stains to reproduce papillary lines of the skin and suggests the feasibility of identifying suspects by touch. It also suggests the use of a magnifying glass for comparing those impressions whose origins need to be determined.

Automated four-color interphase fluorescence in situ hybridization approach for the simultaneous detection of specific aneuploidies of diagnostic and prognostic significance in high hyperdiploid acute lymphoblastic leukemia.

In high hyperdiploid acute lymphoblastic leukemia (ALL), the concurrence of specific trisomies confers a more favorable outcome than hyperdiploidy alone. Interphase fluorescence in situ hybridization (FISH) complements conventional cytogenetics (CC) through its sensitivity and ability to detect chromosome aberrations in nondividing cells. To overcome the limits of manual I-FISH, we developed an automated four-color I-FISH approach and assessed its ability to detect concurrent aneuploidies in ALL. I-FISH was performed using centromeric probes for chromosomes 4, 6, 10, and 17. Parameters established for nucleus selection and signal detection were evaluated. Cutoff values were determined. Combinations of aneuploidies were considered relevant when each aneuploidy was individually significant. Results obtained in 10 patient samples were compared with those obtained with CC. Various combinations of aneuploidies were identified. All clones detected by CC were observed also by I-FISH, and I-FISH revealed numerous additional abnormal clones in all patients, ranging from < or =1% to 31.6% of cells analyzed. We conclude that four-color automated I-FISH permits the identification of concurrent aneuploidies of potential prognostic significance. Large numbers of cells can be analyzed rapidly. The large number of nuclei scored revealed a high level of chromosome variability both at diagnosis and relapse, the prognostic significance of which is of considerable clinical interest and merits further evaluation.

Rapid detection of MRSA in screening specimens during a hospital outbreak.

Objectives: To compare the results of rapid PCR screening for MRSA using the GeneXpert system with those of cultures in an outbreak setting. Methods: GeneXpert was used for screening MRSA in nose, throat, groin, and other clinical samples during a 6-month period. Samples were performed using a double-swab transystem. When >1 sample was found positive in a screening set, all second swabs of the set were analysed by culture. Results: From June to October 2009, 7568 rapid tests were performed, among which 432 (5.7%) were positive (nose: 149/2090, 7.1%; throat: 98/2078, 4.7%; groin: 152/2080, 7.3%; urine: 14/1090, 1.3%; wounds: 18/150, 12%; and others:1/27, 3.7%), and 84 (1.1%) were invalid. A total of 1517 samples were analyzed by both rapid PCR and culture. Rapid tests had a sensitivity of 0.896 compared to cultures, a specificity of 0.769, a PPV of 0.763, and a NPV of 0.899. The rapid test was found to be less sensitive in throat samples (0.81) than in nose or inguinal samples (0.93 for both). In 32/192 (16%) patients a positive rapid PCR result was not confirmed by culture, despite several subsequent screening samples in some patients. Cycle threshold (Ct) for SCCmec of these PCR positive reactions were all >30. Conclusions: GeneXpert MRSA was found to be suitable for the rapid detection in nose, inguinal, and throat samples, however with a lower sensitivity in the later. Negative cultures in 16% of our PCR-positive patients raised the question of false positivity or higher sensitivity of GeneXpert. Further work is needed to investigate these cases.

Mass detection on mammograms: influence of signal shape uncertainty on human and model observers.

We studied the influence of signal variability on human and model observers for detection tasks with realistic simulated masses superimposed on real patient mammographic backgrounds and synthesized mammographic backgrounds (clustered lumpy backgrounds, CLB). Results under the signal-known-exactly (SKE) paradigm were compared with signal-known-statistically (SKS) tasks for which the observers did not have prior knowledge of the shape or size of the signal. Human observers' performance did not vary significantly when benign masses were superimposed on real images or on CLB. Uncertainty and variability in signal shape did not degrade human performance significantly compared with the SKE task, while variability in signal size did. Implementation of appropriate internal noise components allowed the fit of model observers to human performance.

Detection, Determination of Chemical Composition and Chemical Profiling of Counterfeit Medicines by Raman Spectroscopy.

Raman spectroscopy has become a widespread technique for the analysis ofpharmaceutical solid forms. The application proposed here is the investigationof counterfeit medicines. This serious global issue requires quick and accurateidentification methods to fight against this phenomenon. Thanks to its chemicalselectivity, rapidity of analysis and potential of generating repeatable spectralprofiles, Raman spectroscopy presents distinct advantages for the analysis ofcounterfeits. Combined with chemometric tools, the technique enablesthe detection, the determination of chemical composition and the profiling ofmedicine counterfeits.

Detection of the movement of the humerus during daily activity.

A new ambulatory technique for qualitative and quantitative movement analysis of the humerus is presented. 3D gyroscopes attached on the humerus were used to recognize the movement of the arm and to classify it as flexion, abduction and internal/external rotations. The method was first validated in a laboratory setting and then tested on 31 healthy volunteer subjects while carrying the ambulatory system during 8 h of their daily life. For each recording, the periods of sitting, standing and walking during daily activity were detected using an inertial sensor attached on the chest. During each period of daily activity the type of arm movement (flexion, abduction, internal/external rotation) its velocity and frequency (number of movement/hour) were estimated. The results showed that during the whole daily activity and for each activity (i.e. walking, sitting and walking) the frequency of internal/external rotation was significantly higher while the frequency of abduction was the lowest (P < 0.009). In spite of higher number of flexion, abduction and internal/external rotation in the dominant arm, we have not observed in our population a significant difference with the non-dominant arm, implying that in healthy subjects the arm dominance does not lie considerably on the number of movements. As expected, the frequency of the movement increased from sitting to standing and from standing to walking, while we provide a quantitative value of this change during daily activity. This study provides preliminary evidence that this system is a useful tool for objectively assessing upper-limb activity during daily activity. The results obtained with the healthy population could be used as control data to evaluate arm movement of patients with shoulder diseases during daily activity.

Coronary magnetic resonance angiography for the detection of coronary stenoses.

BACKGROUND: An accurate, noninvasive technique for the diagnosis of coronary disease would be an important advance. We investigated the accuracy of coronary magnetic resonance angiography among patients with suspected coronary disease in a prospective, multicenter study. METHODS: Coronary magnetic resonance angiography was performed during free breathing in 109 patients before elective x-ray coronary angiography, and the results of the two diagnostic procedures were compared. RESULTS: A total of 636 of 759 proximal and middle segments of coronary arteries (84 percent) were interpretable on magnetic resonance angiography. In these segments, 78 (83 percent) of 94 clinically significant lesions (those with a > or = 50 percent reduction in diameter on x-ray angiography) were also detected by magnetic resonance angiography. Overall, coronary magnetic resonance angiography had an accuracy of 72 percent (95 percent confidence interval, 63 to 81 percent) in diagnosing coronary artery disease. The sensitivity, specificity, and accuracy for patients with disease of the left main coronary artery or three-vessel disease were 100 percent (95 percent confidence interval, 97 to 100 percent), 85 percent (95 percent confidence interval, 78 to 92 percent), and 87 percent (95 percent confidence interval, 81 to 93 percent), respectively. The negative predictive values for any coronary artery disease and for left main artery or three-vessel disease were 81 percent (95 percent confidence interval, 73 to 89 percent) and 100 percent (95 percent confidence interval, 97 to 100 percent), respectively. CONCLUSIONS: Among patients referred for their first x-ray coronary angiogram, three-dimensional coronary magnetic resonance angiography allows for the accurate detection of coronary artery disease of the proximal and middle segments. This noninvasive approach reliably identifies (or rules out) left main coronary artery or three-vessel disease.

Multi-modal Change Detection, Application to the Detection of Flooded Areas: Outcome of the 2009-2010 data fusion contest

The 2009-2010 Data Fusion Contest organized by the Data Fusion Technical Committee of the IEEE Geoscience and Remote Sensing Society was focused on the detection of flooded areas using multi-temporal and multi-modal images. Both high spatial resolution optical and synthetic aperture radar data were provided. The goal was not only to identify the best algorithms (in terms of accuracy), but also to investigate the further improvement derived from decision fusion. This paper presents the four awarded algorithms and the conclusions of the contest, investigating both supervised and unsupervised methods and the use of multi-modal data for flood detection. Interestingly, a simple unsupervised change detection method provided similar accuracy as supervised approaches, and a digital elevation model-based predictive method yielded a comparable projected change detection map without using post-event data.

Illuminating the detection chain of bacterial bioreporters.

Engineering bacteria for measuring chemicals of environmental or toxicological concern (bioreporter bacteria) has grown slowly into a mature research area. Despite many potential advantages, current bioreporters do not perform well enough to comply with environmental detection standards. Basically, the reasons for this are the lack of engineering principles in the detection chain in the bioreporters. Here, we dissect critical steps in the detection chain and illustrate how bioreporter design could be improved by mutagenizing specificity and selectivity of the sensing and regulatory proteins, by newer expression strategies and application of different signalling networks. Furthermore, we describe how redesigning bioreporter assays with respect to pollutant transport into the cells and application of other detection devices can decrease detection limits and increase the speed of detection.

Detection of millimetric deformation using a terrestrial laser scanner: experiment and application to a rockfall event

Abstract. Terrestrial laser scanning (TLS) is one of the most promising surveying techniques for rockslope characteriza- tion and monitoring. Landslide and rockfall movements can be detected by means of comparison of sequential scans. One of the most pressing challenges of natural hazards is com- bined temporal and spatial prediction of rockfall. An outdoor experiment was performed to ascertain whether the TLS in- strumental error is small enough to enable detection of pre- cursory displacements of millimetric magnitude. This con- sists of a known displacement of three objects relative to a stable surface. Results show that millimetric changes cannot be detected by the analysis of the unprocessed datasets. Dis- placement measurement are improved considerably by ap- plying Nearest Neighbour (NN) averaging, which reduces the error (1σ ) up to a factor of 6. This technique was ap- plied to displacements prior to the April 2007 rockfall event at Castellfollit de la Roca, Spain. The maximum precursory displacement measured was 45 mm, approximately 2.5 times the standard deviation of the model comparison, hampering the distinction between actual displacement and instrumen- tal error using conventional methodologies. Encouragingly, the precursory displacement was clearly detected by apply- ing the NN averaging method. These results show that mil- limetric displacements prior to failure can be detected using TLS.

Development of bacteria-based bioassays for arsenic detection in natural waters.

Arsenic contamination of natural waters is a worldwide concern, as the drinking water supplies for large populations can have high concentrations of arsenic. Traditional techniques to detect arsenic in natural water samples can be costly and time-consuming; therefore, robust and inexpensive methods to detect arsenic in water are highly desirable. Additionally, methods for detecting arsenic in the field have been greatly sought after. This article focuses on the use of bacteria-based assays as an emerging method that is both robust and inexpensive for the detection of arsenic in groundwater both in the field and in the laboratory. The arsenic detection elements in bacteria-based bioassays are biosensor-reporter strains; genetically modified strains of, e.g., Escherichia coli, Bacillus subtilis, Staphylococcus aureus, and Rhodopseudomonas palustris. In response to the presence of arsenic, such bacteria produce a reporter protein, the amount or activity of which is measured in the bioassay. Some of these bacterial biosensor-reporters have been successfully utilized for comparative in-field analyses through the use of simple solution-based assays, but future methods may concentrate on miniaturization using fiberoptics or microfluidics platforms. Additionally, there are other potential emerging bioassays for the detection of arsenic in natural waters including nematodes and clams.