Designing an Intelligent System to Detect Stress Levels During Driving

In addition to the devastating effects of anxiety and stress on the development and exacerbation of the cardiovascular disease, lack of stress control increases drivers' risk of accidents. This paper aims to identify the stress of drivers in various driving situations to warn the driver to control the tense conditions during driving. In order to detect stress while driving, we used the heart signals in the Physionet database. To analyze the conditions of the electrocardiogram (ECG) under various driving situations, linear and non-linear features were used. The characteristics of the RRIs are the only able to identify driver stress in different driving modes relative to rest periods, while the return mapping features, in addition to identifying driver stress while resting, have the ability to identify stress between different driving positions also brought. The results showed that driver's stress level during driving in city 1 and highway 1 with a P-value of 0.028 and also in city 3 and highway 2 with a P-value of 0.041 can be distinguished. The accuracy obtained from the proposed detection method is 98±2% for 100 iterations. The result indicated an efficiency of our proposed method and enhanced the reliability.

Internal Structure of the 2019 April 2 CME

We present the first analysis of internal coronal mass ejection (CME) structure observed very close to the Sun by the Wide-field Imager for Solar PRobe (WISPR) instrument on board the Parker Solar Probe (PSP). The transient studied here is a CME observed during PSP’s second perihelion passage on 2019 April 2, when PSP was only 40 R ⊙ from the Sun. The CME was also well observed from 1 au by the STEREO-A spacecraft, which tracks the event all the way from the Sun to 1 au. However, PSP/WISPR observes internal structure not apparent in the images from 1 au. In particular, two linear features are observed, one bright and one dark. We model these features as two loops within the CME flux rope (FR) channel. The loops can be interpreted as bundles of field lines, with the brightness of the bright loop indicative of lots of mass being loaded into those field lines, and with the dark loop being devoid of such mass loading. It is possible that these loops are actually representative of two independent FR structures within the overall CME outline.

A Precisely One-Step Registration Methodology for Optical Imagery and LiDAR Data Using Virtual Point Primitives

The registration of optical imagery and 3D Light Detection and Ranging (LiDAR) point data continues to be a challenge for various applications in photogrammetry and remote sensing. In this paper, the framework employs a new registration primitive called virtual point (VP) that can be generated from the linear features within a LiDAR dataset including straight lines (SL) and curved lines (CL). By using an auxiliary parameter (λ), it is easy to take advantage of the accurate and fast calculation of the one-step registration transformation model. The transformation model parameters and λs can be calculated simultaneously by applying the least square method recursively. In urban areas, there are many buildings with different shapes. Therefore, the boundaries of buildings provide a large number of SL and CL features and selecting properly linear features and transforming into VPs can reduce the errors caused by the semi-discrete random characteristics of the LiDAR points. According to the result shown in the paper, the registration precision can reach the 1~2 pixels level of the optical images.

Surface Fault Rupture and Slip Distribution of the Jordan-Kekerengu-Needles Fault Network during the 2016 Mw 7.8 Kaikōura Earthquake, New Zealand

<p>During the 2016, Mw 7.8 Kaikōura earthquake the Kekerengu fault ruptured the ground surface producing a maximum of ~12 m of net displacement (dextral-slip with minor reverse- slip), one of the largest five co-seismic surface rupture displacements so far observed globally. This thesis presents the first combined onshore to offshore dataset of co-seismic ground-surface and vertical seabed displacements along a near-continuous ~83 km long strike-slip dominated earthquake surface rupture of large slip magnitude. Onshore on the Kekerengu, Jordan Thrust, Upper Kowhai, and Manakau faults, we measured the displacement of 117 cultural and natural markers in the field and using airborne LiDAR data. Offshore on the dextral-reverse Needles fault, multibeam bathymetric and high-resolution seismic reflection data image a throw of the seabed of up to 3.5±0.2 m. Mean net slip on the total ~83 km rupture was 5.5±1 m, this is an unusually large mean slip for the rupture length compared to global strike-slip surface ruptures. Surveyed linear features that extend across the entire surface rupture zone show that it varies in width from 13 to 122 m. These cultural features also reveal the across-strike distribution of lateral displacement, 80% of which is, on average, concentrated within the central 43% of the rupture zone. Combining the near-field measurements of fault offset with published, far-field InSAR, continuous GPS, and coastal deformation data, suggests partitioning of oblique plate convergence, with a significant portion of co-seismic contractional deformation (and uplift) being accommodated off-fault in the hanging-wall crust to the northwest of the main rupturing faults. This thesis also documents in detail the onshore extent of surface fault rupture on the Kekerengu, Jordan Thrust, Upper Kowhai and Manakau faults. I present large-scale maps (up to 1:3,000) and documentary field photographs of this 53 km-long onshore surface rupture zone utilizing field data, post-earthquake LiDAR-derived Digital Elevation Models (DEMs), and post-earthquake ortho-rectified aerial photography. Ground deformation data is most detailed near the Marlborough coast where the 2016 rupture trace is well-exposed on agricultural grassland on the Kekerengu fault. In the southwest, where surface fault rupture traversed the alpine slopes of the Seaward Kaikoura ranges, fault mapping relied heavily on the LiDAR-derived DEMs. At 24 sites along the Kekerengu fault, I document co-seismic wear striae that were formed during the earthquake and were preserved on free face fault exposures. Nearly all of these striae were distinctly curved along their length, demonstrating that the direction of near-surface fault slip changed with time during rupture of the Kekerengu fault. Co-seismic displacement on the Kekerengu fault initiated as oblique-dextral (mainly dextral-reverse), and subsequently rotated to become nearly-pure dextral slip. These slip trajectories agree with directions of net displacements derived from offset linear features at nearby sites. Temporal rotation of the slip direction may suggest a state of low shear stress on the Kekerengu fault before the earthquake, and a near-complete reduction in stress during the earthquake, as has been inferred for other historic earthquakes that show evidence for changing slip direction with time.</p>

Surface Fault Rupture and Slip Distribution of the Jordan-Kekerengu-Needles Fault Network during the 2016 Mw 7.8 Kaikōura Earthquake, New Zealand

<p>During the 2016, Mw 7.8 Kaikōura earthquake the Kekerengu fault ruptured the ground surface producing a maximum of ~12 m of net displacement (dextral-slip with minor reverse- slip), one of the largest five co-seismic surface rupture displacements so far observed globally. This thesis presents the first combined onshore to offshore dataset of co-seismic ground-surface and vertical seabed displacements along a near-continuous ~83 km long strike-slip dominated earthquake surface rupture of large slip magnitude. Onshore on the Kekerengu, Jordan Thrust, Upper Kowhai, and Manakau faults, we measured the displacement of 117 cultural and natural markers in the field and using airborne LiDAR data. Offshore on the dextral-reverse Needles fault, multibeam bathymetric and high-resolution seismic reflection data image a throw of the seabed of up to 3.5±0.2 m. Mean net slip on the total ~83 km rupture was 5.5±1 m, this is an unusually large mean slip for the rupture length compared to global strike-slip surface ruptures. Surveyed linear features that extend across the entire surface rupture zone show that it varies in width from 13 to 122 m. These cultural features also reveal the across-strike distribution of lateral displacement, 80% of which is, on average, concentrated within the central 43% of the rupture zone. Combining the near-field measurements of fault offset with published, far-field InSAR, continuous GPS, and coastal deformation data, suggests partitioning of oblique plate convergence, with a significant portion of co-seismic contractional deformation (and uplift) being accommodated off-fault in the hanging-wall crust to the northwest of the main rupturing faults. This thesis also documents in detail the onshore extent of surface fault rupture on the Kekerengu, Jordan Thrust, Upper Kowhai and Manakau faults. I present large-scale maps (up to 1:3,000) and documentary field photographs of this 53 km-long onshore surface rupture zone utilizing field data, post-earthquake LiDAR-derived Digital Elevation Models (DEMs), and post-earthquake ortho-rectified aerial photography. Ground deformation data is most detailed near the Marlborough coast where the 2016 rupture trace is well-exposed on agricultural grassland on the Kekerengu fault. In the southwest, where surface fault rupture traversed the alpine slopes of the Seaward Kaikoura ranges, fault mapping relied heavily on the LiDAR-derived DEMs. At 24 sites along the Kekerengu fault, I document co-seismic wear striae that were formed during the earthquake and were preserved on free face fault exposures. Nearly all of these striae were distinctly curved along their length, demonstrating that the direction of near-surface fault slip changed with time during rupture of the Kekerengu fault. Co-seismic displacement on the Kekerengu fault initiated as oblique-dextral (mainly dextral-reverse), and subsequently rotated to become nearly-pure dextral slip. These slip trajectories agree with directions of net displacements derived from offset linear features at nearby sites. Temporal rotation of the slip direction may suggest a state of low shear stress on the Kekerengu fault before the earthquake, and a near-complete reduction in stress during the earthquake, as has been inferred for other historic earthquakes that show evidence for changing slip direction with time.</p>

SVDNVLDA: predicting lncRNA-disease associations by Singular Value Decomposition and node2vec

Background Numerous studies on discovering the roles of long non-coding RNAs (lncRNAs) in the occurrence, development and prognosis progresses of various human diseases have drawn substantial attentions. Since only a tiny portion of lncRNA-disease associations have been properly annotated, an increasing number of computational methods have been proposed for predicting potential lncRNA-disease associations. However, traditional predicting models lack the ability to precisely extract features of biomolecules, it is urgent to find a model which can identify potential lncRNA-disease associations with both efficiency and accuracy. Results In this study, we proposed a novel model, SVDNVLDA, which gained the linear and non-linear features of lncRNAs and diseases with Singular Value Decomposition (SVD) and node2vec methods respectively. The integrated features were constructed from connecting the linear and non-linear features of each entity, which could effectively enhance the semantics contained in ultimate representations. And an XGBoost classifier was employed for identifying potential lncRNA-disease associations eventually. Conclusions We propose a novel model to predict lncRNA-disease associations. This model is expected to identify potential relationships between lncRNAs and diseases and further explore the disease mechanisms at the lncRNA molecular level.

Satellite and aerial imagery geo-referencing using ground features

The method of geo-referencing satellite- and aerial imagery using reference points, linear and non-linear features, and segments of geodetic tracks as elements of a plan-altitude basis is discussed in this article. The method can be used for any mathematical model of satellite- and aerial imagery. The parametric description of the features, that can be used for the geo-referencing and various mathematical models of the above-mentioned imagery are presented. The mathematical formulation of the matter of satellite and aerial imagery geo-referencing using terrain objects and reference points is presented. A list of linear and non-linear features that can be included in a high-raised basis along with reference points is made. A generalized algorithm for geo-referencing satellite and aerial imagery using reference points and terrain features is given. The algorithm includes making a nonlinear system of equations for reference points and items, linearizing the system and solving by the sequential approximation technique according to the least squares method. An example of clarifying the satellite RPC-model and aerial imagery using reference points, linear and non-linear features is given. The advantages of the proposed method of using features created according to the measurements on satellite and aerial imagery compared with method, when the model of the feature is created according to the measurements on the ground are described.