Passive Measurements of the Refractive Index of Liquid Nitrogen and Free-flowing substances by the Prism Method in the Millimeter Wavelength Range

It is proposed to use the classical prism method in the millimeter wavelength range for measuring the refractive index of liquid and free-flowing substances, including mixtures with particle sizes comparable to the wavelength. The method is implemented using a hollow radio transparent rectangular prism filled with a test substance. The measurements were carried out in the thermal radiation mode using radiometers with horn-lens antennas at frequencies of 37.5 and 94 GHz. To measure the deflection of the refracted beam, a linear scanner with a black body mounted on it, cooled with liquid nitrogen, was used. The distance between the prism and the scanner was 1 m. The refractive index of liquid nitrogen, sand, gravel, marble chips and granular polyethylene were measured. Using the refractive formula and the Landau-Lifshitz-Looeng formula for calculating the dependence of the refractive index of binary mixtures on the bulk density of particles, estimates of the refractive index of the material of the particles that make up the substances under study are obtained. They are in satisfactory agreement with the known experimental data for quartz, feldspar, granite, and marble.

Passive Sonar Multiple-Target Tracking with Nonlinear Doppler and Bearing Measurements Using Multiple Sensors

The major advantage of the passive multiple-target tracking is that the sonars do not emit signals and thus they can remain covert, which will reduce the risk of being attacked. However, the nonlinearity of the passive Doppler and bearing measurements, the range unobservability problem, and the measurement to target data association uncertainty make the passive multiple-target tracking problem challenging. To deal with the target to measurement data association uncertainty problem from multiple sensors, this paper proposed a batch recursive extended Rauch-Tung-Striebel smoother- (RTSS-) based probabilistic multiple hypothesis tracker (PMHT) algorithm, which can effectively handle a large number of passive measurements including clutters. The recursive extended RTSS which consists of a forward filter and a backward smoothing is used to deal with the nonlinear Doppler and bearing measurements. The target range unobservability problem is avoided due to using multiple passive sensors. The simulation results show that the proposed algorithm works well in a passive multiple-target tracking system under dense clutter environment, and its computing cost is low.

Just-in-time Adaptive Mechanisms of Popular Mobile Applications for Individuals with Depression: Systematic Review (Preprint)

BACKGROUND There is an increasing number of smartphone applications (apps) focusing on prevention, treatment, and diagnosis of depression. A promising approach to increase the effectiveness while reducing the individual’s burden is the use of just-in-time adaptive intervention (JITAI) mechanisms. OBJECTIVE With this work, we systematically assess the use of JITAI mechanisms in apps for individuals with depression. METHODS We systematically searched for apps addressing depression in the Apple App Store, the Google Play Store, and in curated lists from the Anxiety and Depression Association of America, the United Kingdom National Health Service, and the American Psychological Association in August 2020. Relevant apps were ranked according to the number of reviews (Apple App Store) or downloads (Google Play Store). For each app, two authors separately reviewed all publications concerning the app found within scientific databases (PubMed, Cochrane Register of Controlled Trials, PsycINFO, and Google Scholar), publications cited on the app’s website, information on the app’s website, and the app itself. RESULTS None of the 28 reviewed apps used JITAI mechanisms to tailor content to situations or individuals. Three apps did not use any measurements, 20 apps exclusively used self-reports that are insufficient to leverage the full potential of JITAIs, and the five apps employing self-reports and passive measurements used them as progress or task indicators only. While 23 of the 68 reviewed publications investigated the effectiveness and 14 publications investigated the efficacy of the apps, not one publication mentioned or evaluated JITAI mechanisms. CONCLUSIONS Promising JITAI mechanisms have not yet been translated into mainstream depression apps. The lack of publications investigating whether JITAI mechanisms lead to an increase of the apps’ effectiveness or efficacy highlights the need for further research, especially in real-world apps.

High-Precision Drill Bit Tracking

The lateral well position uncertainty of magnetic/gyro MWD measurements can often exceed the requirements regarding anti-collision, for optimal placement of infill wells between existing producers, or for hitting targets with limited geological extent. The positional uncertainty can be significantly reduced by implementing high-precision drill-bit localization using passive seismic data. Consequently, not only drilling risks can be reduced, but optimal reservoir drainage is ensured as well. By utilizing passive seismic recordings from the seafloor, we can "listen" to the noise generated by the BHA while drilling. Despite various noise sources in the vicinity (e.g. vessels and rigs), advanced data processing and the combination of hundreds of seafloor receivers spread above the ongoing drilling, enable us to detect the drilling signal and locate the drill bit. Whereas the magnetic and gyro MWD tools have errors that accumulate with measured depth, each bit position derived from seismic (usually every 90 seconds) is completely independent. For horizontal sections, the error does not increase with measured depth, and hence can provide improved lateral accuracy. No additional BHA tool is required and the measurements are neither dependent on the magnetic nor gravitational field. Moreover, the passive seismic measurements can be used to obtain an improved lateral well position estimate. This is done by optimizing the azimuth information of the well trajectory in the minimum curvature method. A lateral uncertainty measure can be derived from the residuals between the passive measurements and the updated well path. Since 2018, we have used the continuous stream of passive data from permanent seafloor sensors at the Grane field with its reservoir depth of around 1800 m TVDSS to follow all wells with this drill bit tracking scheme. Lateral deviations from the magnetic/gyro measurements of up to 20m have been observed. The lateral position uncertainty can be as low as a couple of meters under optimal conditions.

Ice cloud retrieval from high spectral resolution measurements in the thermal infrared : Application to IASI and IASI-NG

<p>Besides their strong contribution to weather forecast improvement through data assimilation in clear-sky conditions, thermal infrared sounders on board polar orbiting platforms are now playing a key role in monitoring changes in atmospheric composition. However, it is known that clear sky observations are only a small part of the entire set of measurements, the remaining part <span><span data-language-to-translate-into="fr" data-phrase-index="0">is only slightly</span></span> used as they are contaminated by either aerosols and/or clouds. Moreover, ice or liquid cloud retrieval of column and profile properties from passive and active measurements respectively help us in reaching a better understanding of climate processes. If the information provided by the latter has allowed a significant advance in our knowledge of the vertical distribution of condensed water, it suffers from spatial coverage compared to passive measurements. It is therefore fundamental to better characterize cloud properties from passive measurements by using, for example, high spectral resolution instruments such as IASI and the future IASI-NG.</p><p>An information content analysis based on Shannon's formalism has been used to determine the level and the spectral repartition of the information about the ice cloud properties in the IASI and IASI-NG spectra. Based on this analysis, we have developped and tested an algorithm which allows to retrieve from an optimal estimation approach the cloud integrated ice water content together with the cloud layer altitude. We have taken into account the Signal-to-Noise ratio of each specific instrument and the uncertainties due to the non-retrieved atmospheric and surface parameters. The forward model is the fast radiative transfer model RTTOV which has been developped for satellite data assimilation in Numerical Weather Prediction (NWP) models. The ice cloud microphysical model is based on the ensemble model of Baran and Labonnote (2007), where the bulk ice optical properties have been parametrized as a function of the ice water content (expressed in g/m³) and in cloud temperature.</p><p>The present study aims to quantify the potential and limits of thermal infrared sounders such as IASI or IASI-NG to retrieve ice cloud properties by using a representative dataset from the global operational short range forecast of the european center of medium-range weather forecast.</p>