Miracle-dz/UniFAR-FTUs huggingface dataset:
Influence of Familiarity on the Driving Behavior, Route Risk, and Route Choice of Older Drivers

For older adults, familiarity plays an important role in reducing driving errors, improving wayfinding, and maintaining driving confidence. However, only a few studies have explored the influence of familiarity on driving behavior, route risk, and route choice among older drivers. The vehicles of 29 drivers age 65 and older were instrumented with on-board diagnostic devices for four months to record their routes driven, and risky driving behavior events. For each route driven, trip diaries were used to provide participants with retrospective feedback of their risky driving behaviors, alternate low-risk routes, and record answers to three questions pertaining to: familiarity with the route driven, suggested low-risk route alternative, and reasons for choosing a route. When familiarity responses were regressed on the number of risky driving behavior events, results showed that for every 10% increase in familiarity with driven routes, a 0.07 increase in risky driving behavior incidents per trip was estimated. Results from the generalized mixed effects regression showed that older drivers were less likely to drive a suggested low-risk route when they were more familiar with the alternate routes. Content analysis conducted on the reasons for choosing a familiar route showed that older drivers preferred routes that were direct, had less traffic, and depended on the trip purpose, such as running multiple errands. These results provide important insights on the influence of familiarity on route choice, preferences, and driving behaviors of older drivers and provide opportunities for developing targeted route choice models for navigation systems that can include factors such as familiarity.
Compressed Training Based Massive MIMO

Massive multiple-input-multiple-output (MIMO) scheme promises high spectral efficiency through the employment of large scale antenna arrays in base stations. In time division duplexed implementations, co-channel mobile terminals transmit training information such that base stations can estimate and exploit channel state information to spatially multiplex these users. In the conventional approach, the optimal choice for training length was shown to be equal to the number of users, <inline-formula><tex-math notation="LaTeX">$K$</tex-math></inline-formula>. In this paper, we propose a new semiblind framework, named as “MIMO Compressed Training,” which utilizes information symbols in addition to training symbols for adaptive spatial multiplexing. We show that this framework enables us to reduce (compress) the training length down to a value close to <inline-formula><tex-math notation="LaTeX">$\log _2(K)$</tex-math></inline-formula>, i.e., the logarithm of the number of users, without any sparsity assumptions on the channel matrix. We also derive a prescription for the required packet length for proper training. The framework is built upon some convex optimization settings that enable efficient and reliable algorithm implementations. The numerical experiments demonstrate the strong potential of the proposed approach in terms of increasing the number of users per cell and improving the link quality.
Fuzzy Control Systems: Past, Present and Future

More than 40 years after fuzzy logic control appeared as an effective tool to deal with complex processes, the research on fuzzy control systems has constantly evolved. Mamdani fuzzy control was originally introduced as a modelfree control approach based on expert? s experience and knowledge. Due to the lack of a systematic framework to study Mamdani fuzzy systems, we have witnessed growing interest in fuzzy model-based approaches with Takagi-Sugeno fuzzy systems and singleton-type fuzzy systems (also called piecewise multiaffine systems) over the past decades. This paper reviews the key features of the three above types of fuzzy systems. Through these features, we point out the historical rationale for each type of fuzzy systems and its current research mainstreams. However, the focus is put on fuzzy model-based approaches developed via Lyapunov stability theorem and linear matrix inequality (LMI) formulations. Finally, our personal viewpoint on the perspectives and challenges of the future fuzzy control research is discussed.
An Evolutionary Method to Optimize OSNR Margin in Elastic Optical Channels Subject to Nonlinear Physical Impairments

This paper proposes a metaheuristic optimization method based on Particle Swarm Optimization (PSO) that can be conveniently used to determine launch power profiles of elastic optical channels subject to nonlinear physical impairments. The method focuses on optimizing the overall OSNR margin of heterogeneous connections in a single-link network. The evolutionary method is contrasted to an analytical process widely used for WDM channels and shows a disruptive behavior to what is expected as well as a relevant gain in terms of additional propagated spans when applied to flexible-grid links.
Indium–Gallium–Zinc–Oxide Schottky Synaptic Transistors for Silent Synapse Conversion Emulation

Silent synapses play an important role in synaptic plasticity and the nervous system development. In this letter, indium–gallium–zinc–oxide (IGZO) Schottky electric-double-layer transistors were proposed for silent synapse conversion emulation. Silent to active conversion of such neuromorphic devices was realized by applying voltage pulses on the gate electrode of the synaptic transistor. In addition, some important synaptic behaviors, such as paired-pulse facilitation and dynamic high-pass filtering, were also emulated in the IGZO-based Schottky synaptic transistor after electric pulse activation.
MISR Radiance Anomalies Induced by Stratospheric Volcanic Aerosols

The 16-year MISR monthly radiances are analyzed in this study, showing significant enhancements of anisotropic scattering at high latitudes after several major volcanic eruptions with injection heights greater than 14 km. The anomaly of deseasonalized radiance anisotropy between MISR’s DF and DA views (70.5° forward and aft) is largest in the blue band with amplitudes amounting to 5–15% of the mean radiance. The anomalous radiance anisotropy is a manifestation of the stronger forward scattering of reflected sunlight due to the direct and indirect effects of stratospheric volcanic aerosols (SVAs). The perturbations of MISR radiance anisotropy from the Kasatochi (August 2008), Sarychev (June 2009), Nabro (June 2011) and Calbuco (April 2015) eruptions are consistent with the poleward transported SVAs observed by CALIOP and OMPS-LP. In a particular scene over the Arctic Ocean, the stratospheric aerosol mid-visible optical depth can reach as high as 0.2–0.5. The enhanced global forward scattering by SVAs has important implications for the shortwave radiation budget.
Full-Duplex RF Front Ends : From Antennas and Circulators to Leakage Cancellation

With the increasing demands of wireless communication and sensing such as mobile cellular networks and the Internet of Things, radio spectrum is becoming a scarcer resource more than ever. The electromagnetic waves emitted from a radio transmitter typically occupy a certain information channel that is divided into either time [e.g., time division duplex (TDD)] or frequency [e.g. frequency division duplex (FDD)], and, within this channel, all of the receivers or sensors colocated with the transmitter are normally paralyzed.
Seasonal Local Temperature Responses to Paddy Field Expansion from Rain-Fed Farmland in the Cold and Humid Sanjiang Plain of China

Numerous studies have documented the effects of irrigation on local, regional, and global climate. However, most studies focused on the cooling effect of irrigated dryland in semiarid or arid regions. In our study, we focused on irrigated paddy fields in humid regions at mid to high latitudes and estimated the effects of paddy field expansion from rain-fed farmland on local temperatures based on remote sensing and observational data. Our results revealed much significant near-surface cooling in spring (May and June) rather than summer (July and August) and autumn (September), which was −2.03 K to 0.73 K and −1.08 K respectively. Non-radiative mechanisms dominated the local temperature response to paddy field expansion from rain-fed farmland in the Sanjiang Plain. The contributions from the changes to the combined effects of the non-radiative process were 123.6%, 95.5%, and 66.9% for spring (May and June), summer (July and August), and autumn (September), respectively. Due to the seasonal changes of the biogeophysical properties for rain-fed farmland and paddy fields during the growing season, the local surface temperature responses, as well as their contributions, showed great seasonal variability. Our results showed that the cooling effect was particularly obvious during the dry spring instead of the warm, wet summer, and indicated that more attention should be paid to the seasonal differences of these effects, especially in a region with a relatively humid climate and distinct seasonal variations.
Investigation of Erase Cycling Induced TSG Vt Shift in 3D NAND Flash Memory

Erase cycling induced Vt shift of top select gate transistor (TSG) and its physical mechanism are studied in 3D NAND flash memory. It is found that the distribution of TSG Vt shifts higher during memory cells erase cycling. Furthermore, the TSG Vt shift can recover after the removal of cycling stress. A physical model of trap generation induced by hot holes is proposed for above observations. It is considered that hot holes generated by high channel potential gradient during erase can break the <inline-formula> <tex-math notation="LaTeX">$\equiv $ </tex-math></inline-formula>Si–H bonds at the poly-Si grain boundary and the poly-Si/SiO<sub>2</sub> interface, causing TSG Vt tail shift and parallel shift, respectively. And the degradation can recover due to re-passivation of <inline-formula> <tex-math notation="LaTeX">$\equiv $ </tex-math></inline-formula>Si–H bonds after stress removal. A TSG bias optimization scheme is demonstrated to reduce the hot holes generation and suppress the TSG abnormal Vt shift during cell erase cycling.
Sidelobe Supression in Modulated Surface Reactance Antennas

This paper proposes a method for suppressing the sidelobe of a modulated surface antenna in a given direction. It is based on synthesizing two beams, one pointing at the desired direction, and the other at the interfering direction, so that this second has the same amplitude as the sidelobe that must be suppressed and it presents a 180° phase shift. A one-dimension modulated surface reactance antenna is designed and sidelobe reductions of 14.5 dB and above 8 dB are shown in simulations and measurements, respectively.
MsRi-CCF: Multi-Scale and Rotation-Insensitive Convolutional Channel Features for Geospatial Object Detection

Geospatial object detection is a fundamental but challenging problem in the remote sensing community. Although deep learning has shown its power in extracting discriminative features, there is still room for improvement in its detection performance, particularly for objects with large ranges of variations in scale and direction. To this end, a novel approach, entitled multi-scale and rotation-insensitive convolutional channel features (MsRi-CCF), is proposed for geospatial object detection by integrating robust low-level feature generation, classifier generation with outlier removal, and detection with a power law. The low-level feature generation step consists of rotation-insensitive and multi-scale convolutional channel features, which were obtained by learning a regularized convolutional neural network (CNN) and integrating multi-scaled convolutional feature maps, followed by the fine-tuning of high-level connections in the CNN, respectively. Then, these generated features were fed into AdaBoost (chosen due to its lower computation and storage costs) with outlier removal to construct an object detection framework that facilitates robust classifier training. In the test phase, we adopted a log-space sampling approach instead of fine-scale sampling by using the fast feature pyramid strategy based on a computable power law. Extensive experimental results demonstrate that compared with several state-of-the-art baselines, the proposed MsRi-CCF approach yields better detection results, with 90.19% precision with the satellite dataset and 81.44% average precision with the NWPU VHR-10 datasets. Importantly, MsRi-CCF incurs no additional computational cost, which is only 0.92 s and 0.7 s per test image on the two datasets. Furthermore, we determined that most previous methods fail to gain an acceptable detection performance, particularly when they face several obstacles, such as deformations in objects (e.g., rotation, illumination, and scaling). Yet, these factors are effectively addressed by MsRi-CCF, yielding a robust geospatial object detection method.
Estimation of Leaf Nitrogen Content in Wheat Using New Hyperspectral Indices and a Random Forest Regression Algorithm

Novel hyperspectral indices, which are the first derivative normalized difference nitrogen index (FD-NDNI) and the first derivative ratio nitrogen vegetation index (FD-SRNI), were developed to estimate the leaf nitrogen content (LNC) of wheat. The field stress experiments were conducted with different nitrogen and water application rates across the growing season of wheat and 190 measurements were collected on canopy spectra and LNC under various treatments. The inversion models were constructed based on the dataset to evaluate the ability of various spectral indices to estimate LNC. A comparative analysis showed that the model accuracies of FD-NDNI and FD-SRNI were higher than those of other commonly used hyperspectral indices including mNDVI705, mSR, and NDVI705, which was indicated by higher R2 and lower root mean square error (RMSE) values. The least squares support vector regression (LS-SVR) and random forest regression (RFR) algorithms were then used to optimize the models constructed by FD-NDNI and FD-SRNI. The p-R2 values of the FD-NDNI_RFR and FD-SRNI_RFR models reached 0.874 and 0.872, respectively, which were higher than those of the exponential and SVR model and indicated that the RFR model was accurate. Using the RFR inversion model, remote sensing mapping for the Operative Modular Imaging Spectrometer (OMIS) image was accomplished. The remote sensing mapping of the OMIS image yielded an accuracy of R2 = 0.721 and RMSE = 0.540 for FD-NDNI and R2 = 0.720 and RMSE = 0.495 for FD-SRNI, which indicates that the similarity between the inversion value and the measured value was high. The results show that the new hyperspectral indices, i.e., FD-NDNI and FD-SRNI, are the optimal hyperspectral indices for estimating LNC and that the RFR algorithm is the preferred modeling method.
Ground Deformation and Source Geometry of the 30 October 2016 Mw 6.5 Norcia Earthquake (Central Italy) Investigated Through Seismological Data, DInSAR Measurements, and Numerical Modelling

We investigate the Mw 6.5 Norcia (Central Italy) earthquake by exploiting seismological data, DInSAR measurements, and a numerical modelling approach. In particular, we first retrieve the vertical component (uplift and subsidence) of the displacements affecting the hangingwall and the footwall blocks of the seismogenic faults identified, at depth, through the hypocenters distribution analysis. To do this, we combine the DInSAR measurements obtained from coseismic SAR data pairs collected by the ALOS-2 sensor from ascending and descending orbits. The achieved vertical deformation map displays three main deformation patterns: (i) a major subsidence that reaches the maximum value of about 98 cm near the epicentral zones nearby the town of Norcia; (ii) two smaller uplift lobes that affect both the hangingwall (reaching maximum values of about 14 cm) and the footwall blocks (reaching maximum values of about 10 cm). Starting from this evidence, we compute the rock volumes affected by uplift and subsidence phenomena, highlighting that those involved by the retrieved subsidence are characterized by significantly higher deformation values than those affected by uplift (about 14 times). In order to provide a possible interpretation of this volumetric asymmetry, we extend our analysis by applying a 2D numerical modelling approach based on the finite element method, implemented in a structural-mechanic framework, and exploiting the available geological and seismological data, and the ground deformation measurements retrieved from the multi-orbit ALOS-2 DInSAR analysis. In this case, we consider two different scenarios: the first one based on a single SW-dipping fault, the latter on a main SW-dipping fault and an antithetic zone. In this context, the model characterized by the occurrence of an antithetic zone presents the retrieved best fit coseismic surface deformation pattern. This result allows us to interpret the subsidence and uplift phenomena caused by the Mw 6.5 Norcia earthquake as the result of the gravitational sliding of the hangingwall along the main fault plane and the frictional force acting in the opposite direction, consistently with the double couple fault plane mechanism.
Seasonal Variations in the Flow of Land-Terminating Glaciers in Central-West Greenland Using Sentinel-1 Imagery

Land-terminating sectors of the Greenland ice sheet flow faster in summer after surface meltwater reaches the subglacial drainage system. Speedup occurs when the subglacial drainage system becomes saturated, leading to a reduction in the effective pressure which promotes sliding of the overlying ice. Here, we use observations acquired by the Sentinel-1a and b synthetic aperture radar to track changes in the speed of land-terminating glaciers across a 14,000 km2 sector of west-central Greenland on a weekly basis in 2016 and 2017. The fine spatial and temporal sampling of the satellite data allows us to map the speed of summer and winter across the entire sector and to resolve the weekly evolution of ice flow across the downstream portions of five glaciers. Near to the ice sheet margin (at 650 m.a.s.l.), glacier speedup begins around day 130, persisting for around 90 days, and then peaks around day 150. At four of the five glaciers included in our survey the peak speedup is similar in both years, in Russell Glacier there is marked interannual variability of 32% between 2016 and 2017. We present, for the first time, seasonal and altitudinal variation in speedup persistence. Our study demonstrates the value of Sentinel-1’s systematic and frequent acquisition plan for studying seasonal changes in ice sheet flow.
DPI: The Data Processing Interface for Modern Networks

As data processing evolves towards large scale, distributed platforms, the network will necessarily play a substantial role in achieving efficiency and performance. Increasingly, switches, network cards, and protocols are becoming more flexible while programmability at all levels (aka, software defined networks) opens up many possibilities to tailor the network to data processing applications and to push processing down to the network elements. In this paper, we propose DPI, an interface providing a set of simple yet powerful abstractions flexible enough to exploit features of modern networks (e.g., RDMA or in-network processing) suitable for data processing. Mirroring the concept behind the Message Passing Interface (MPI) used extensively in high-performance computing, DPI is an interface definition rather than an implementation so as to be able to bridge different networking technologies and to evolve with them. In the paper we motivate and discuss key primitives of the interface and present a number of use cases that show the potential of DPI for data-intensive applications, such as analytic engines and distributed database systems.
Continuously Tunable and Bandwidth Variable Optical Notch/Band-Pass Filters Over 500 nm Spectral Range Using Cholesteric Liquid Crystals

We report continuously tunable and bandwidth variable optical notch and band-pass filters created by combining four left- and right-handed circular cholesteric liquid crystal cells without extra optical components. Filter performance was greatly improved by introducing an anti-reflection layer on the filter device. The filter comprised cholesteric liquid crystal wedge cells with continuous pitch gradient. The band wavelength position was spatially tuned from 470 nm to 1000 nm. The notch filters are polarization-independent in the spectral ranges. The band pass filters can be designed to be polarization-independent or polarization-dependent via cell alignment and the bandwidth can be reversibly controlled from the original bandwidth (60∼18 nm). These tunable filter strategies could make a paved road to wavelength tunable spectroscopic instruments applications in the VIS and near infrared response spectral range.
Capabilities of Chinese Gaofen-3 Synthetic Aperture Radar in Selected Topics for Coastal and Ocean Observations

Gaofen-3 (GF-3), the first Chinese spaceborne synthetic aperture radar (SAR) in C-band for civil applications, was launched on August 2016. Some studies have examined the use of GF-3 SAR data for ocean and coastal observations, but these studies generally focus on one particular application. As GF-3 has been in operation over two years, it is essential to evaluate its performance in ocean observation, a primary goal of the GF-3 launch. In this paper, we offer an overview demonstrating the capabilities of GF-3 SAR in ocean and coastal observations by presenting several representative cases, i.e., the monitoring of intertidal flats, offshore tidal turbulent wakes and oceanic internal waves, to highlight the GF-3’s full polarimetry, high spatial resolution and wide-swath imaging advantages. Moreover, we also present a detailed analysis of the use of GF-3 quad-polarization data for sea surface wind retrievals and wave mode data for sea surface wave retrievals. The case studies and statistical analysis suggest that GF-3 has good ocean and coastal monitoring capabilities, though further improvements are possible, particularly in radiometric calibration and stable image quality.
Unravelling the Potential of Density Functional Theory through Integrated Computational Environments: Recent Applications of the Vienna Ab Initio Simulation Package in the MedeA® Software

The development of density functional theory and the tremendous increase of compute power in recent decades have created a framework for the incredible success of modern computational materials engineering (CME). CME has been widely adopted in the academic world and is now established as a standard tool for industrial applications. As theory and compute resources have developed, highly efficient computer codes to solve the basic equations have been implemented and successively integrated into comprehensive computational environments leading to unprecedented increases in productivity. The MedeA software of Materials Design combines a set of comprehensive productivity tools with leading computer codes such as the Vienna Ab initio Simulation Package (VASP), LAMMPS, GIBBS and the UNiversal CLuster Expansion code (UNCLE), provides interoperability at different length and time scales. In the present review, technological applications including microelectronic materials, Li-ion batteries, disordered systems, high-throughput applications and transition-metal oxides for electronics applications are described in the context of the development of CME and with reference to the MedeA environment.