Geometric and Signal Strength Dilution of Precision (DoP)Wi-Fi

The democratization of wireless networks combined to the emergence of mobile devices increasingly autonomous and efficient lead to new services. Positioning services become overcrowded. Accuracy is the main quality criteria in positioning. But to better appreciate this one a coefficient is needed. In this paper we present Geometric and Signal Strength Dilution of Precision (DOP) for positioning systems based on Wi-Fi and Signal Strength measurements.Comment: International Journal of Computer Science Issues (IJCSI), Volume 3, pp35-44, August 200

Detection and quantification of black foot and crown and root rot pathogens in grapevine nursery soils in the Western Cape of South Africa

Black foot disease (BFD) and crown and root rot (CRR) are important soilborne diseases that affect young grapevines in nurseries and vineyards. A 3-year survey (2013–2015) of five open-field grapevine nurseries was conducted in the Western Cape Province of South Africa. The survey involved the isolation of BFD and CRR pathogens from grafted rootstocks (ten plants per nursery, per year) that were rooted in soil for 1 year. In 2013 and 2015, grapevines were sampled, while in 2014, sampling was focused on rotation crops and weeds (ten plants each). The rotation crops included white mustard, lupins, canola, triticale and forage radish. The weed species sampled included Johnson grass, ryegrass, winter grass, Cape marigold and corn spurry. Soil samples from ten sites per nursery were also collected in close proximity to the sampled plants, at depths of 0–30 cm and 30–60 cm (ten samples per depth). Isolations were made from the grapevines, rotation crops and weeds. Pathogen detection and quantification in the soil were determined using quantitative real-time polymerase chain reaction technology. The predominant BFD pathogens isolated from grapevines were Campylocarpon fasciculare, Ca. pseudofasciculare and Dactylonectria macrodidyma. The predominant CRR pathogens were Pythium irregulare and Phytopythium vexans. Dactylonectria macrodidyma, D. novozelandica, D. pauciseptata, Py. irregulare, Py. ultimum var. ultimum and Py. heterothallicum were isolated from triticale roots. Dactylonectria spp. were also isolated from corn spurry, while Py. irregulare and Py. ultimum var. ultimum were isolated from numerous weeds and rotation crops. Mean soil DNA concentrations of Ilyonectria and Dactylonectria were from 0.04 to 37.14 pg μL-1, and for Py. irregulare were between 0.01 and 3.77 pg μL-1. The Phytophthora mean soil DNA concentrations ranged from 0.01 to 33.48 pg μL-1. The qPCR protocols successfully detected and quantified BFD and CRR pathogens in grapevine nursery soil. This is the first report of D. pauciseptata and D. alcacerensis in South African grapevine nurseries

Intraspecific and within-isolate sequence variation in the ITS rRNA gene region of Pythium mercuriale sp. nov. (Pythiaceae)

Sixteen Pythium isolates from diverse hosts and locations, which showed similarities in their morphology and sequences of the internal transcribed spacer (ITS) region of their rRNA gene, were investigated. As opposed to the generally accepted view, within single isolates ITS sequence variations were consistently found mostly as part of a tract of identical bases (A-T) within ITS1, and of GT or GTTT repeats within the ITS2 sequence. Thirty-one different ITS sequences obtained from 39 cloned ITS products from the 16 isolates showed high sequence and length polymorphisms within and between isolates. However, in a phylogenetic analysis, they formed a cluster distinct from those of other Pythium species. Additional sequencing of two nuclear genes (elongation factor 1α and β-tubulin) and one mitochondrial gene (nadh1) revealed high levels of heterozygosity as well as polymorphism within and between isolates, with some isolates possessing two or more alleles for each of the nuclear genes. In contrast to the observed variation in the ITS and other gene areas, all isolates were phenotypically similar. Pythium mercuriale sp. nov. (Pythiaceae) is characterized by forming thin-walled chlamydospores, subglobose to obovoid, papillate sporangia proliferating internally and smooth-walled oogonia surrounded by multiple antheridia. Maximum likelihood phylogenetic analyses based on both ITS and β-tubulin sequence data place P. mercuriale in a clade between Pythium and Phytophthor

Temporal changes in the epidemiology, management, and outcome from acute respiratory distress syndrome in European intensive care units: a comparison of two large cohorts

Background: Mortality rates for patients with ARDS remain high. We assessed temporal changes in the epidemiology and management of ARDS patients requiring invasive mechanical ventilation in European ICUs. We also investigated the association between ventilatory settings and outcome in these patients. Methods: This was a post hoc analysis of two cohorts of adult ICU patients admitted between May 1–15, 2002 (SOAP study, n = 3147), and May 8–18, 2012 (ICON audit, n = 4601 admitted to ICUs in the same 24 countries as the SOAP study). ARDS was defined retrospectively using the Berlin definitions. Values of tidal volume, PEEP, plateau pressure, and FiO2 corresponding to the most abnormal value of arterial PO2 were recorded prospectively every 24 h. In both studies, patients were followed for outcome until death, hospital discharge or for 60 days. Results: The frequency of ARDS requiring mechanical ventilation during the ICU stay was similar in SOAP and ICON (327[10.4%] vs. 494[10.7%], p = 0.793). The diagnosis of ARDS was established at a median of 3 (IQ: 1–7) days after admission in SOAP and 2 (1–6) days in ICON. Within 24 h of diagnosis, ARDS was mild in 244 (29.7%), moderate in 388 (47.3%), and severe in 189 (23.0%) patients. In patients with ARDS, tidal volumes were lower in the later (ICON) than in the earlier (SOAP) cohort. Plateau and driving pressures were also lower in ICON than in SOAP. ICU (134[41.1%] vs 179[36.9%]) and hospital (151[46.2%] vs 212[44.4%]) mortality rates in patients with ARDS were similar in SOAP and ICON. High plateau pressure (> 29 cmH2O) and driving pressure (> 14 cmH2O) on the first day of mechanical ventilation but not tidal volume (> 8 ml/kg predicted body weight [PBW]) were independently associated with a higher risk of in-hospital death. Conclusion: The frequency of and outcome from ARDS remained relatively stable between 2002 and 2012. Plateau pressure > 29 cmH2O and driving pressure > 14 cmH2O on the first day of mechanical ventilation but not tidal volume > 8 ml/kg PBW were independently associated with a higher risk of death. These data highlight the continued burden of ARDS and provide hypothesis-generating data for the design of future studies

Guidelines for the use and interpretation of assays for monitoring autophagy (3rd edition)

In 2008 we published the first set of guidelines for standardizing research in autophagy. Since then, research on this topic has continued to accelerate, and many new scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Accordingly, it is important to update these guidelines for monitoring autophagy in different organisms. Various reviews have described the range of assays that have been used for this purpose. Nevertheless, there continues to be confusion regarding acceptable methods to measure autophagy, especially in multicellular eukaryotes. For example, a key point that needs to be emphasized is that there is a difference between measurements that monitor the numbers or volume of autophagic elements (e.g., autophagosomes or autolysosomes) at any stage of the autophagic process versus those that measure fl ux through the autophagy pathway (i.e., the complete process including the amount and rate of cargo sequestered and degraded). In particular, a block in macroautophagy that results in autophagosome accumulation must be differentiated from stimuli that increase autophagic activity, defi ned as increased autophagy induction coupled with increased delivery to, and degradation within, lysosomes (inmost higher eukaryotes and some protists such as Dictyostelium ) or the vacuole (in plants and fungi). In other words, it is especially important that investigators new to the fi eld understand that the appearance of more autophagosomes does not necessarily equate with more autophagy. In fact, in many cases, autophagosomes accumulate because of a block in trafficking to lysosomes without a concomitant change in autophagosome biogenesis, whereas an increase in autolysosomes may reflect a reduction in degradative activity. It is worth emphasizing here that lysosomal digestion is a stage of autophagy and evaluating its competence is a crucial part of the evaluation of autophagic flux, or complete autophagy. Here, we present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes. These guidelines are not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used. In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multiple assays to monitor autophagy. Along these lines, because of the potential for pleiotropic effects due to blocking autophagy through genetic manipulation it is imperative to delete or knock down more than one autophagy-related gene. In addition, some individual Atg proteins, or groups of proteins, are involved in other cellular pathways so not all Atg proteins can be used as a specific marker for an autophagic process. In these guidelines, we consider these various methods of assessing autophagy and what information can, or cannot, be obtained from them. Finally, by discussing the merits and limits of particular autophagy assays, we hope to encourage technical innovation in the field

Far from any ocean : a novel

Includes abstract

Land Cover Classification Using Multi-Frequency SAR over Semi-Arid and Forested African Landscapes

The potential of using multi-frequency Synthetic Aperture Radar (SAR) for land cover classification is becoming a reality, with multiple SAR satellites utilising different frequencies currently in orbit and more missions planned for the future. This study looks at combining SAR frequencies from L-band (ALOS PALSAR), C-band (ENVISAT ASAR) and X-band (TerraSAR-X) to find the optimum combination of the SAR data for land cover classification of forested and semi-arid ecoregions in Africa. The study site for forested areas is in Cameroon and the semi-arid study site is in Tanzania. Data from both the wet and dry seasons are available. Random forest models, with different combinations of input variables, are compared. Models with the top 30 variables are chosen from the mean decrease accuracy and mean decrease Gini variable importance measures, and compared with the classification accuracies using support vector machines. Some of the findings are that L-band is the best single frequency for land cover classifications for both ecoregions, with X-band the best single frequency if only forested regions are considered. Texture measures lead to an increase of between 15-25% overall classification accuracy compared to using only backscatter coefficients. The recommended dual-frequency combination are LX-bands, although L-band data give overall classification accuracies very close to LX-bands. The use of images from LCX data only marginally improves the classification accuracy from LX-images and L-band images. The benefit from acquisition of all three frequencies would therefore rarely outweigh the cost of acquiring and processing data from all three frequencies. The transferability of the random forest models to an additional geographic site did not produce satisfactory results, however the transferability of the random forest models to additional season data did give satisfactory results. The Kullback-Leibler divergence class difference measure showed potential to give an indication of transferability of the models, although refinement remains necessary

Measuring accurate Angle of Arrival of weak LoRa signals for Indoor Positionning

International audienceIn this paper, we propose an Autocorrelation method for measuring the angle of arrival (AoA) of a weak LoRa signal. A weak LoRa signal has a negative SNR down to-20 dB. The objective is to detect a LoRa signal that operates at low transmission power (TX). Operating at low transmission power (TX) reduces power consumption and extends the battery life of LoRa devices. Besides, the transmission of weak signals strengthens the radio communication protocol, preventing an enemy device from accessing the location coordinates. The detecting algorithm consists of finding Autocorrelation peaks of the LoRa signal. We show that Autocorrelation peaks decrease when the signal is buried in the noise. However, using a large number of Fast Fourier Transform (FFT) will increase the Autocorrelation peaks and the signal-to-noise ratio (SNR). Once the peak of the LoRa signal is detected under the noise, the algorithm will calculate the AoA. All of the proposed algorithms are implemented using a Universal Software Radio Peripheral (USRP), Software Defined Radio (SDR) receiver with the help of GNU Radio software. We, therefore, believe that our Autocorrelation method can detect the LoRa signal accurately and measure the AoA at very low SNR in real-time, being usable for indoor positionning

Measuring accurate Angle of Arrival of weak LoRa signals for Indoor Positionning

International audienceIn this paper, we propose an Autocorrelation method for measuring the angle of arrival (AoA) of a weak LoRa signal. A weak LoRa signal has a negative SNR down to-20 dB. The objective is to detect a LoRa signal that operates at low transmission power (TX). Operating at low transmission power (TX) reduces power consumption and extends the battery life of LoRa devices. Besides, the transmission of weak signals strengthens the radio communication protocol, preventing an enemy device from accessing the location coordinates. The detecting algorithm consists of finding Autocorrelation peaks of the LoRa signal. We show that Autocorrelation peaks decrease when the signal is buried in the noise. However, using a large number of Fast Fourier Transform (FFT) will increase the Autocorrelation peaks and the signal-to-noise ratio (SNR). Once the peak of the LoRa signal is detected under the noise, the algorithm will calculate the AoA. All of the proposed algorithms are implemented using a Universal Software Radio Peripheral (USRP), Software Defined Radio (SDR) receiver with the help of GNU Radio software. We, therefore, believe that our Autocorrelation method can detect the LoRa signal accurately and measure the AoA at very low SNR in real-time, being usable for indoor positionning

Performance Evaluation of the Angle of Arrival of LoRa Signals under Interference

International audienceTracking objects in indoor is always a challenge for a variety of Internet of Things (IoT) applications. Nowadays, many indoor tracking applications use Low-Power Wide-Area Networks (LPWAN) for Machine-to-Machine (M2M) communication. LoRa is a promising LPWAN radio communication technology designed for wide-area coverage and low-power embedded IoT devices. The objective of this paper is to evaluate the performance of the Angle of Arrival (AoA) direction finding approach in an indoor environment. The AoA performance of the LoRa signal is evaluated using different modulation settings, including Channel Bandwidth (BW) and spreading factor (SF). We measure the AoA accuracy of the LoRa signal using an individual Universal Software Radio Peripheral (USRP) B210, Software Defined Radio (SDR) receiver with the help of the GNU radio software development toolkit. In addition, a new approach to measure the AoA of LoRa signal under interference is investigated. We show that by using the Autocorrelation function combined with our direction finding algorithm, the detection and measurement of two simultaneous receptions is possible. The entire experimental setup was implemented in our indoor office environment. Index Terms-Long-Range (LoRa), Low-Power Wide-Area Networks (LPWANs), Software Defined Radio (SDR), Angle of Arrival (AoA)