A Hierarchical and Geographically Weighted Regression Model and Its Backfitting Maximum Likelihood Estimator (Short Paper)

Spatial heterogeneity is a typical and common form of spatial effect. Geographically weighted regression (GWR) and its extensions are important local modeling techniques for exploring spatial heterogeneity. However, when dealing with spatial data sampled at a micro-level but the geographical locations of them are only known at a higher level, GWR-based models encounter several problems, such as difficulty in establishing the bandwidth. Because data with this characteristic exhibit spatial hierarchical structures, such data can be suitably handled using hierarchical linear modeling (HLM). This model calibrates random effects for sample-level variables in each group to address spatial heterogeneity. However, it does not work when exploring spatial heterogeneity in some group-level variables when there is insufficient variance in each group. In this study, we therefore propose a hierarchical and geographically weighted regression (HGWR) model, together with a back-fitting maximum likelihood estimator, that can be applied to examine spatial heterogeneity in the regression relationships of data where observations nest into high-order groupings and share the same or very close coordinates within those groups. The HGWR model divides coefficients into three types: local fixed effects, global fixed effects, and random effects. Results of a simulation experiment show that HGWR distinguishes local fixed effects from others and also global effects from random effects. Spatial heterogeneity is reflected in the estimates of local fixed effects, along with the spatial hierarchical structure. Compared with GWR and HLM, HGWR produces estimates with the lowest deviations of coefficient estimates. Thus, the ability of HGWR to tackle both spatial and group-level heterogeneity simultaneously suggests its potential as a promising data modeling tool for handling the increasingly common occurrence where data, in secure settings for example, remove the specific geographic identifiers of individuals and release their locations only at a group level

Hsa_circ_0026344 suppresses gastric cancer progression via modulating the miR-1290/FBP2 axis

Background. Circular RNAs (circRNAs) are a novel type of noncoding RNAs and play important roles in tumorigenesis, including gastric cancer (GC). However, the functions of most circRNAs remain poorly understood. In our study, we mainly learn the influence of hsa_circ_0026344 (circ_0026344) in GC progression. Methods. Circ_0026344, miR-1290 and Fructose1,6-bisphosphatase 2 (FBP2) expression was determined by quantitative real-time polymerase chain reaction (qRT-PCR). GC cell proliferation, migration, and invasion were detected by colony formation, 5-ethynyl2’-deoxyuridine (EdU), and transwell assays, respectively. The interaction between circ_0026344 and miR-1290 complex was evaluated by RNA pull-down assay. The interaction of miR-1290 with circ_0026344 or FBP2 was detected using dual-luciferase reporter assay. A xenograft model was established to determine the effect of circ_0026344 on GC tumor growth in vivo. Results. Circ_0026344 expression was dramatically decreased in GC cells and tissues. Circ_0026344 overexpression inhibited GC cell proliferation, migration and invasion. MiR-1290 was predicted as a target of circ_0026344 and miR-1290 overexpression attenuated the anti-tumor effect of circ_0026344 on GC cells. Furthermore, we predicted FBP2 as the target of miR1290. FBP2 knockdown reversed the effects of circ_0026344 knockdown on GC cell malignant behaviors. Functional analysis showed that circ_0026344 upregulated FBP2 expression via miR1290. Additionally, in vivo studies demonstrated that circ_0026344 suppressed GC tumor progression. Conclusion. In conclusion, circ_0026344 inhibited GC cell proliferation via the miR-1290/FBP2 axis, which might provide a new therapeutic target for GC patients

Security and Energy-aware Collaborative Task Offloading in D2D communication

Device-to-device (D2D) communication technique is used to establish direct links among mobile devices (MDs) to reduce communication delay and increase network capacity over the underlying wireless networks. Existing D2D schemes for task offloading focus on system throughput, energy consumption, and delay without considering data security. This paper proposes a Security and Energy-aware Collaborative Task Offloading for D2D communication (Sec2D). Specifically, we first build a novel security model, in terms of the number of CPU cores, CPU frequency, and data size, for measuring the security workload on heterogeneous MDs. Then, we formulate the collaborative task offloading problem that minimizes the time-average delay and energy consumption of MDs while ensuring data security. In order to meet this goal, the Lyapunov optimization framework is applied to implement online decision-making. Two solutions, greedy approach and optimal approach, with different time complexities, are proposed to deal with the generated mixed-integer linear programming (MILP) problem. The theoretical proofs demonstrate that Sec2D follows a [O(1∕V),O(V)] energy-delay tradeoff. Simulation results show that Sec2D can guarantee both data security and system stability in the collaborative D2D communication environment

Estimation of horizontal-to-vertical spectral ratios (ellipticity) of Rayleigh waves from multistation active-seismic records

The horizontal-to-vertical spectral-ratio (HVSR) analysis of ambient noise recordings is a popular reconnaissance tool used worldwide for seismic microzonation and earthquake site characterization. We have expanded this single-station passive HVSR technique to active multicomponent data. We focus on the calculation of the HVSR of Rayleigh waves from active-seismic records. We separate different modes of Rayleigh waves in seismic dispersion spectra and then estimate the HVSR for the fundamental mode. The mode separation is implemented in the frequency-phase velocity (f-v) domain through the high-resolution linear Radon transformation. The estimated Rayleigh-wave HVSR curve after mode separation is consistent with the theoretical HVSR curve, which is computed by solving the Rayleigh-wave eigenproblem in the laterally homogeneous layered medium. We find that the HVSR peak and trough frequencies are very sensitive to velocity contrast and interface depth and that HVSR curves contain information on lateral velocity variations. Using synthetic and field data, we determine the validity of estimating active Rayleigh-wave HVSR after mode separation. Our approach can be a viable and more accurate alternative to the empirical HVSR analysis method and brings a novel approach for the analysis of active multicomponent seismic data

Online Camera-to-ground Calibration for Autonomous Driving

Online camera-to-ground calibration is to generate a non-rigid body transformation between the camera and the road surface in a real-time manner. Existing solutions utilize static calibration, suffering from environmental variations such as tire pressure changes, vehicle loading volume variations, and road surface diversity. Other online solutions exploit the usage of road elements or photometric consistency between overlapping views across images, which require continuous detection of specific targets on the road or assistance with multiple cameras to facilitate calibration. In our work, we propose an online monocular camera-to-ground calibration solution that does not utilize any specific targets while driving. We perform a coarse-to-fine approach for ground feature extraction through wheel odometry and estimate the camera-to-ground calibration parameters through a sliding-window-based factor graph optimization. Considering the non-rigid transformation of camera-to-ground while driving, we provide metrics to quantify calibration performance and stopping criteria to report/broadcast our satisfying calibration results. Extensive experiments using real-world data demonstrate that our algorithm is effective and outperforms state-of-the-art techniques

Caching-based Multicast Message Authentication in Time-critical Industrial Control Systems

Attacks against industrial control systems (ICSs) often exploit the insufficiency of authentication mechanisms. Verifying whether the received messages are intact and issued by legitimate sources can prevent malicious data/command injection by illegitimate or compromised devices. However, the key challenge is to introduce message authentication for various ICS communication models, including multicast or broadcast, with a messaging rate that can be as high as thousands of messages per second, within very stringent latency constraints. For example, certain commands for protection in smart grids must be delivered within 2 milliseconds, ruling out public-key cryptography. This paper proposes two lightweight message authentication schemes, named CMA and its multicast variant CMMA, that perform precomputation and caching to authenticate future messages. With minimal precomputation and communication overhead, C(M)MA eliminates all cryptographic operations for the source after the message is given, and all expensive cryptographic operations for the destinations after the message is received. C(M)MA considers the urgency profile (or likelihood) of a set of future messages for even faster verification of the most time-critical (or likely) messages. We demonstrate the feasibility of C(M)MA in an ICS setting based on a substation automation system in smart grids.Comment: For viewing INFOCOM proceedings in IEEE Xplore see https://ieeexplore.ieee.org/abstract/document/979676

Monitoring of atopic dermatitis using leaky coaxial cable

In our daily life, inadvertent scratching may increase the severity of skin diseases (such as atopic dermatitis, etc.). However, people rarely pay attention to this matter, so the known measurement behavior of the movement is also very little. Nevertheless, the behavior and frequency of scratching represent the degree of itching, and the analysis of scratching frequency is helpful to the doctor's clinical dosage. In this paper, a novel system is proposed to monitor the scratching motion of a sleeping human body at night. The core device of the system are just a Leaky coaxial cable (LCX) and a router. Commonly, LCX is used in the blind field or semi blind field in wireless communication. The new idea is that the leaky cable is placed on the bed, then the state information of physical layer of wireless communication channels is acquired to identify the scratching motion and other small body movements in the human sleep process. The results show that it can be used to detect the movement and its duration. Channel state information (CSI) packet is collected by card installed in the computer based on the 802.11n protocol. The characterization of the scratch motion in the collected channel state information is unique, so it can be distinguished from the wireless channel amplitude variation trend