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Deep Learning plays an increasingly important role in device-free WiFi Sensing for human activity recognition (HAR). Despite its strong potential, significant challenges exist and are associated with the fact that one may require a large amount of samples for training, and the trained network cannot be easily adapted to a new environment. To address these challenges, we develop a novel scheme using Matching Network with enhanced channel state information (MatNet-eCSI) to facilitate one-shot learning HAR. We propose a CSI Correlation Feature Extraction (CCFE) method to improve and condense the activity-related information in input signals. It can also significantly reduce the computational complexity by decreasing the dimensions of input signals. We also propose novel training strategy which effectively utilizes the data set from the previously seen environments (PSE). In the least, the strategy can effectively realize human activity recognition using only one sample for each activity from the testing environment and the data set from one PSE. Numerous experiments are conducted and the results demonstrate that our proposed scheme significantly outperforms state-of-the-art HAR methods, achieving higher recognition accuracy and less training time.

BACKGROUND Although deep inspiratory breath-hold (DIBH) is routinely used for left-sided breast cancers, its benefits for right-sided breast cancer (rBC) have yet to be established. We compared free-breathing (FB) and DIBH treatment plans for a cohort of rBC undergoing regional nodal irradiation (RNI) to determine its potential benefits. METHODS AND MATERIALS rBC patients considered for RNI (internal mammary nodal chains, supraclavicular field, with or without axilla) from October 2017 to May 2020 were included in this analysis. For each patient, FB versus DIBH plans were generated and dose volume histograms evaluated the following parameters: mean lung dose, ipsilateral lung V20/V5 (volumes of lung receiving 20 Gy and 5 Gy, respectively); mean heart dose and heart V5 (volumes of heart receiving 5 Gy); liver V20 absolute /V30 absolute (absolute volume of liver receiving 20 Gy and 30 Gy, respectively), liver Dmax, and total liver volume irradiated (TVIliver). The dosimetric parameters were compared using Wilcoxon signed-rank testing. RESULTS Fifty-four patients were eligible for analysis, comparing 108 FB and DIBH plans. DIBH significantly decreased all lung and liver parameters: mean lung dose (19.7 Gy-16.2 Gy, P < .001), lung V20 (40.7%-31.7%, P < .001), lung V5 (61.2%-54.5%, P < .001), TVIliver (1446 cc vs 1264 cc; P = .006) liver Dmax (50.2 Gy vs 48.9 Gy; P = .023), liver V20 (78.8-23.9 cc, P < .001), and liver V30 (58.1-14.6 cc, P < .001) compared with FB. DIBH use did not significantly improve heart parameters, although the V5Heart trended on significance (1.25-0.6, P = .067). CONCLUSIONS This is the largest cohort to date analyzing DIBH for RNI-rBC. Our findings demonstrate significant improvement in all lung and liver parameters with DIBH, supporting its routine consideration for rBC patients undergoing comprehensive RNI.

Effective suppression of inadvertent or deliberate jamming signals is crucial to ensure reliable wireless communication. However, as demonstrated in this paper, when the transmitted jamming signals are highly correlated, and especially when the correlation coefficient varies, nullifying the jamming signals can be challenging. Unlike existing techniques that often assume uncorrelated jamming signals or non-zero but constant correlation, we analyze the impact of the non-zero and varying correlations between transmitted jamming signals on the suppression of the jamming signals. Specifically, we observe that by varying the correlation coefficients between transmitted jamming signals, jammers can “virtually change” the jamming channels hence their nullspace, even when these channels do not physically change. This makes most jamming suppression techniques that rely on steering receiving beams towards the nullspace of jamming channels no longer applicable. To tackle the problem, we develop techniques to effectively track the jamming nullspace and correspondingly update receiving beams. Monte Carlo simulations show that our proposed techniques can suppress/nullify jamming signals for all considered scenarios with non-zero and varying correlation coefficients amongst transmitted jamming signals.

Background Many factors can contribute to the exact makeup of the salivary microbiome. Differences in the oral microbiome occur with old age, which may be due to oral conditions and diseases associated with old age, such as edentulism, as well as other unknown causes. Methods The salivary microbiome was sampled in patients from a large urban clinic. For all subjects age, gender, periodontal status, caries status, presence of edentulism, medications, and tobacco usage were recorded. Multifactor analysis was used to study variation in salivary microbiome profiles linked to these factors. Results In the population sampled, there were significantly higher numbers of edentulous subjects, and increased levels of polypharmacy found with aging. Large differences in alpha diversity and beta diversity of the salivary microbiome in the old age group were largely linked to edentulism. However, multivariable analysis revealed, even after adjusting for differences in edentulism, polypharmacy, tobacco usage, periodontal disease, caries level, and gender, that old age itself was associated with lower levels of taxa Porphyromonas endodontalis, Alloprevotella tannerae, Filifactor alocis, Treponema, Lautropia Mirabilis and Pseudopropionibacterium sp._HMT_194. Surprisingly, of these taxa, most were ones known to reside on or near tooth surfaces. Conclusions Another factor or factors beyond edentulism, polypharmacy and periodontal disease play a role in the differences seen in oral microbiome with old age. The nature of this factor(s) is not known.

In this article, the design of a power amplifier (PA) using a simple but effective architecture, namely, load-modulated balanced amplifier (LMBA), is presented. Using this architecture for PA design, it can achieve not only a relatively high saturated output power but also an excellent efficiency enhancement at the power back-off (PBO) region. To prove that the presented approach is feasible in practice, a PA is designed in a 1- $\mu \text{m}$ gallium arsenide (GaAs) HBT process. Operating under a 5-V power supply, the PA can deliver more than 31-dBm saturated output power with 36% collector efficiency (CE) at 5 GHz. Moreover, it also achieves 1.2 and 1.23 times CE enhancement over an idealistic Class-B PA at 6- and 9-dB PBO levels, respectively. Finally, the designed PA supports 64-quadrature amplitude modulation (QAM) with 80 Msys/s at 22-dBm average output power while still maintaining an error vector magnitude (EVM) and adjacent channel power ratio (ACPR) better than −29.5 dB and −29.4 dBc, respectively.

BACKGROUND Aim: to review outcomes of the 'no zone' approach to penetrating neck injuries (PNIs) with the advent of high-fidelity computed tomography-angiography (CT-A) in order to determine the most appropriate management for stable PNIs. DESIGN Systematic review. POPULATION Retrospective and prospective cohort studies of patients who sustained penetrating neck trauma, as defined by an injury which penetrates the platysma, and whose initial management involved CT-A evaluation. METHODS An extensive literature search was performed in July 2019 using the following databases: Pubmed Central, EMBASE, Medline and Cochrane CENTRAL. Only studies published in English from the last 15 years were included. RESULTS Nine cohort studies met inclusion criteria. There has been an increase in CT-A focussed evaluation of PNIs in recent years. CT-A is a highly sensitive and specific imaging choice and reduces negative neck exploration rates. A new management algorithm for stable patients involving initial radiological assessment using CT-A, and subsequent selective surgical exploration, is safe and effective. CONCLUSION The results of this review provide level 2A evidence that the 'no zone' approach to PNIs, complemented by CT-A and thorough clinical assessment, is a safe management strategy which reduces negative neck exploration rates.

Objective Tuberculosis is the leading cause of death from a single infectious agent. The emergence of antimicrobial resistant Mycobacterium tuberculosis strains makes the problem more severe. Pyrazinamide (PZA) is an important component for short-course treatment regimens and first- and second-line treatment regimens. This research aims for fast diagnosis of M. tuberculosis resistance to PZA and identification of genetic features causing resistance. Materials and Methods We use clinically collected genomic data of M. tuberculosis that are resistant or susceptible to PZA. A machine learning platform is built to diagnose PZA resistance using the whole genome sequence data, and to identify resistance genes and mutations. The platform consists of a deep convolutional neural network (DCNN) model for resistance diagnosis and a support vector machine (SVM) model as a surrogate to identify resistance genes and mutations. Results The DCNN model achieves a PZA resistance diagnosis accuracy of 93%. Each prediction takes less than a second. The SVM has revealed 2 novel genes, embB and gyrA, besides the well-known pncA gene, and 9 mutations that harbor PZA resistance. Discussion The DCNN and SVM machine learning platform, if used together with the real-time genome sequencing machines, could allow for rapid PZA diagnosis, allowing for critical time to ensure good patient outcomes, and preventing outbreaks of deadly infections. Furthermore, identifying pertinent resistance genes and mutations will help researchers better understand the biological mechanisms behind resistance. Conclusions Machine learning can be used to achieve high-accuracy resistance prediction, and identify genes and mutations causing the resistance.

© 1988-2012 IEEE. The attribute-based encryption (ABE) has drawn a lot of attention for fine-grained access control in blockchains, especially in blockchain-enabled tampering-resistant Internet-of-Things (IoT) systems. However, its adoption has been severely hindered by the incompatibility between the immutability of typical blockchains and the attribute updates/revocations of ABE. In this article, we propose a new blockchain-based IoT system, which is compatible with the ABE technique, and fine-grained access control is implemented with the attribute update enabled by integrating Chameleon Hash algorithms into the blockchains. We design and implement a new verification scheme over a multilayer blockchain architecture to guarantee the tamper resistance against malicious and abusive tampering. The system can provide an update-oriented access control, where historical on-chain data can only be accessible to new members and inaccessible to the revoked members. This is distinctively different from existing solutions, which are threatened by data leakage toward the revoked members. We also provide analysis and simulations showing that our system outperforms other solutions in terms of overhead, searching complexity, security, and compatibility.

Angle-of-arrival (AoA) estimation is a challenging problem for analog antenna arrays. Typical schemes use time-consuming beam scanning, and the resolution is limited to the scanning beam width. In this paper, we propose a virtual-subarray based AoA (ViSA) estimation scheme, which divides an analog array into two virtual subarrays and exploits phase difference between one pair of measurements for AoA estimation. The basic ViSA algorithm can obtain a direct AoA estimate from every two temporal measurements. We propose different subarray constructions which can lead to different accuracy of estimation. We provide closed-form expressions for the statistics of the estimation error. Based on the basic ViSA estimator, we develop two methods to combine multiple pairs of measurements, when they are obtained via sequential and multi-resolution scanning, respectively. Near-optimal estimators are derived for both methods, employing the maximum likelihood principle. Novel techniques are also proposed to address the typical phase ambiguity problem due to the periodic phase function. Simulation results demonstrate that the proposed scheme significantly outperforms existing ones.

Analog-to-digital and digital-to-analog conversion devices for signals with very large bandwidth are not always available due to technical or cost issues. This limits the realization of very high data-rate digital communication systems. In this paper, we propose a dual pulse shaping (DPS) transmission scheme, which can achieve full Nyquist rate transmission with only a half of the sampling rate for each of the two data streams. Two classes of ideal complementary Nyquist pulses are formulated assuming raised-cosine (RC) pulse shaping. The condition for cross-symbol interference (CSI) free transmission is derived and validated for the proposed pulses. Structures of the DPS transmitter and receiver are described and low-complexity equalization techniques tailored to DPS are proposed. With DPS, a millimeter wave system with commercially available and affordable data conversion devices is exemplified for achieving high-speed low-cost wireless communications. Simulation results with two sets of practical dual spectral shaping pulses are provided. The results verify the effectiveness of the proposed scheme, with comparison to the benchmark conventional Nyquist pulse shaping system.

In this paper, we develop a framework for a novel perceptive mobile/cellular network that integrates radar sensing function into the mobile communication network. We propose a unified system platform that enables downlink and uplink sensing, sharing the same transmitted signals with communications. We aim to tackle the fundamental sensing parameter estimation problem in perceptive mobile networks, by addressing two key challenges associated with sophisticated mobile signals and rich multipath in mobile networks. To extract sensing parameters from orthogonal frequency division multiple access (OFDMA) and spatial division multiple access (SDMA) communication signals, we propose two approaches to formulate it to problems that can be solved by compressive sensing techniques. Most sensing algorithms have limits on the number of multipath signals for their inputs. To reduce the multipath signals, as well as removing unwanted clutter signals, we propose a background subtraction method based on simple recursive computation, and provide a closed-form expression for performance characterization. The effectiveness of these methods is validated in simulations., Comment: 14 pages, 12 figures, Journal paper

In cellular vehicular communications, high density and mobility of vehicles require frequent resource allocation, which can cause network congestion and large signalling and processing delay. To overcome this problem, we propose a novel semi-persistent resource allocation scheme based on a two-tier heterogeneous network architecture. The architecture includes a central macro base station (MBS) and multiple roadside units (RSU). In the proposed semi-persistent scheme, the MBS pre-allocates persistent resource to RSUs based on predicted traffic, and then allocates dynamic resource upon real-time requests from RSUs while vehicles simultaneously communicate using the pre-allocated resource. A simple Space-Time k-Nearest Neighbour (ST-kNN) method is developed for short-term traffic prediction, and a geometric water-filling algorithm is developed for minimizing the relative latency. Simulation results validate the effectiveness of the proposed semi-persistent scheme in comparison with two benchmark schemes.

Time-domain wireless channels are generally modeled by Tapped Delay Line (TDL) model and its variants. These models are not effective for channel representation and estimation when the number of multipath taps is large. Compressive sensing (CS) provides a powerful tool for sparse channel modeling and estimation. Most of the research has been focusing on sparse channel estimation, while sparse channel modeling (SCM) is rarely considered for centimetre-wave channels. In this paper, we investigate statistical sparse channel modeling, using both measured and simulated channels over a frequency range of 6 to 8.5 GHz. We first introduce the triple equilibrium principle to explore the trade-off between sparsity, modeling accuracy, and algorithm complexity in SCM, and provide a methodology for characterizing the sparsity of time-domain channels using single-measurement-vector compressive sensing algorithms. Using mainly the selected wavelet dictionary and various CS reconstruction (aka recovery) algorithms, we then present comprehensive statistical sparse channel models, including channel sparsity, magnitude decaying profile, sparse coefficient distribution and atomic index distribution. Connections between the parameters of conventional TDL and sparse channel models are mathematically established. We also propose three methods for generating simulated channels from the developed sparse channel models, which validates their effectiveness.

A previously healthy 26-year-old female presented with one month of worsening low back pain radiating to the right lower extremity. Magnetic resonance imaging (MRI) without contrast of the lumbar spine demonstrated enhancement of the right sacroiliac joint. Sacroiliac joint aspiration followed by culture and microbiology revealed Streptomyces griseus as the cause of infectious sacroiliitis. Streptomyces griseus is a part of the normal human flora that produces a plethora of secondary metabolites applied in various medications such as streptomycin. This represents the first described case of infectious sacroiliitis due to Streptomyces griseus in the literature. It is critical for spinal surgeons to consider fastidious organisms, such as Streptomyces griseus, on the differential diagnosis of sacroiliac joint pain, especially in patients with systemic symptoms and elevated inflammatory laboratory markers.

With the application of deep learning (DL) techniques, radar-based human activity recognition (HAR) attracts increasing attention thanks to its high accuracy and good privacy. However, training a DL model requires a large volume of data, and generally the trained model cannot be adapted to a new scenario. In this paper, we propose a supervised few-shot adversarial domain adaptation ( FS-ADA ) method for HAR, where only limited radar training data is collected from a new application scenario. We adopt the domain adaptation method to learn a common feature space between a pre-existing radar dataset and the newly acquired training data. We also design a multi-class discriminator network, which integrates the category classifier and the binary domain discriminator, to employ the supervised label information in the limited radar data for model training. Then, a multitask generative adversarial training mechanism is proposed to optimize FS-ADA . In this way, both domain-invariant and category-discriminative features can be extracted for HAR in a new scenario. Experimental results for two few-shot radar-based HAR tasks show that the proposed FS-ADA method is effective and outperforms state-of-the-art methods.

Objectives Recent case-reports have described an atypical cerebral microbleed (CMB) topography after extracorporeal membrane oxygenation (ECMO). The objective of this study was to examine the prevalence, radiographic patterns, and clinical correlates of possibly-ECMO-related (PER) CMB. Materials and methods We performed a retrospective study of 307 consecutive patients receiving ECMO support at our tertiary-care University Hospital (2013–2018). PER CMB were defined as CMB present in corpus-callosum and/or middle cerebellar peduncle with/without involvement of other lobar/deep structures. Leukoaraiosis was quantified using the Wahlund age-related white matter changes scale. Patient characteristics were compared between cohorts with and without PER CMB. Results Forty patients (median age 60 years; 33% vv-ECMO and 67% va-ECMO) received at-least one MRI-brain within 3 months of ECMO support. CMB were present in 77.5% (n = 31) patients with 39% (n = 12), 17% (n = 5), and 44% (n = 14) having low ( 30 CMB) burden respectively. Among CMB-positive patients, 71% (n = 22) had PER CMB, with 91% of such cases demonstrating involvement of splenium. Leukoaraiosis did not corelate to PER CMB presence (p = 0.267) or burden (ρ = 0.09). Patients with PER CMB had higher rates of ischemic stroke (50 vs. 33%), intracranial hemorrhage (41 vs. 17%), and all-cause mortality (27 vs. 17%); with survivors demonstrating no differences in their discharge disposition or modified Rankin Score. Conclusions Post-ECMO cerebral microbleeds have a distinct distribution pattern that commonly involves the splenium of corpus-callosum. Their etiopathogenesis may be independent of microvascular lipohyalinosis. This requires further study in a larger sample-size.

This paper studies the threat that an aerial eavesdropper can pose to terrestrial wireless communications, from an information-theoretic point of view. The achievable ergodic and the average $\epsilon $ -outage secrecy rates with no channel state information at the transmitter (i.e., with no CSIT) are analyzed for a transmitter–receiver pair on the ground, in the presence of an aerial eavesdropper which flies a random trajectory following a smooth turn (ST) mobility model in a three-dimensional (3D) space. The ST mobility model induces a uniform distribution (of the eavesdropper’s waypoints) within the considered 3D volume. Closed-form asymptotic approximations of the achievable secrecy rates are derived based on the almost sure convergence and non-trivial mathematical manipulations. Validated by simulations, our analysis is tight and reveals that the ground transmission is particularly vulnerable to aerial eavesdropping which can be carried out in a distance without being noticed. 3D spherical regions are identified, within which the secrecy rates vanish. This sheds useful insights to protect terrestrial wireless networks from aerial eavesdropping.

© 2012 IEEE. Licensed-assisted-access (LAA) is used to extend the LTE link into the unlicensed band. How to guarantee the quality-of-service (QoS) for LTE devices in the unlicensed band is a challenging problem due to the listen-before-talk contention access in 5-GHz unlicensed bands. In this letter, we quantitatively analyze the medium access control delay for tagged LAA eNBs and propose a delay-guaranteed admission control scheme. We consider the freezing time of busy slots caused by collision or successful transmission, and introduce the exponential backoff mechanism for delay analysis. Validated by simulation results, our method provides important insights into the system admission performance and fairness of access.

Background: Hematologic toxicity (HT) commonly occurs during chemoradiation therapy (CRT) for esophageal cancer. We sought to determine radiation doses that correlate with declines in blood counts due to vertebral body (VB) irradiation during CRT. Methods: We analyzed 53 esophageal cancer patients who were treated with weekly neoadjuvant carboplatin, paclitaxel and RT with weekly complete blood counts (CBC) available during treatment. HTs were graded according to the Common Terminology Criteria for Adverse Events version 4.0 (CTCAE v4.0). Dose volume histogram (DVH) parameters of Vx, defined as percentage of entire bony vertebra (body, pedicles, laminae, processes) receiving at least x Gy of radiation, were collected for VB V 5 (VBV 5 ), VBV 10 –VBV 60 in increments of 10, and mean vertebral dose (MVD). Linear and logistic regressions were performed to identify associations between leukopenia nadirs and DVH parameters. Receiver operator curves identified thresholds to avoid grade ≥3 leukopenia. Results: A proportion of 32.1% of patients (n=17) developed grade 3 leukopenia and 5.7% (n=3) developed grade 4 leukopenia. VBV 5 , VBV 10 , VBV 20 , VBV 30 , and MVD were significantly associated with worsening leukopenia on univariate and multivariate analysis. Associations with leukopenia were not seen with VBV 40 and VBV 50 DVH values. Thresholds to avoid grade ≥3 leukopenia were VBV 10

We examine the effect of an exogenous increase in information asymmetry (as proxied by late filings of firms' Form 10-K) on bond prices. We find that bondholders react negatively to a late filing announcement but this negative reaction is conditional on whether late filing firms appropriate wealth from bondholders through shareholder distribution. Moreover, we find that the impact of financial distress and covenants on bond values is mainly driven by the wealth appropriation from bondholders. The results are robust to difference-in-difference analysis using treatment (i.e., late filing) and control (i.e., non-late-filing) samples based on propensity score matching. The results provide evidence that shareholder distribution as a specific form of wealth appropriation from bondholders to shareholders has a significant effect on bond values when financial information is not timely provided to capital markets.

BACKGROUND AND PURPOSE: Anterior circulation large-vessel occlusion stroke, one of the most devastating stroke subtypes, is associated with substantial economic burden. We aimed to identify predictors of increased acute care hospitalization costs associated with anterior circulation large-vessel occlusion stroke. MATERIALS AND METHODS: Comprehensive cost-tracking software was used to calculate acute care hospitalization costs for patients with anterior circulation large-vessel occlusion stroke admitted July 2012 to October 2014. Patient demographics and stroke characteristics were analyzed, including final infarct volume on follow-up neuroimaging. Predictors of hospitalization costs were determined using multivariable linear regression including subgroup cost analyses by treatment technique (endovascular, IV tPA-only, and no reperfusion therapy) and sensitivity analyses incorporating patients initially excluded due to early withdrawal of care. RESULTS: Three hundred forty-one patients (median age, 69 years; interquartile range, 57–80 years; median NIHSS score, 16; interquartile range, 13–21) were included in our primary analysis. Final infarct volume, parenchymal hematoma, baseline NIHSS score, ipsilateral carotid stenosis, age, and obstructive sleep apnea were significant predictors of acute care hospitalization costs. Final infarct volume alone accounted for 20.87% of the total cost variance. Additionally, final infarct volume was consistently the strongest predictor of increased cost in primary, subgroup, and sensitivity analyses. CONCLUSIONS: Final infarct volume was the strongest predictor of increased hospitalization costs in anterior circulation large-vessel occlusion stroke. Acute stroke therapies that reduce final infarct volume may not only improve clinical outcomes but may also prove cost-effective.

PURPOSE: To create a succinct yet comprehensive evidence-based structured report template for indeterminate renal masses characterized at CT and MRI. METHODS: This IRB-exempt, iterative, multi-institutional quality improvement project was informed by published data derived from a multi-institutional survey and a multi-institutional review of CT and MRI radiology reports. A two-stage blinded Delphi process by the 16-member 12-institution Society of Abdominal Radiology Disease-Focused Panel on Renal Cell Carcinoma was conducted to create a structured report template for indeterminate renal masses evaluated at CT and MRI. Individual reporting characteristics were scored by members as ‘core,’ ‘optional,’ or ‘exclude.’ Threshold for inclusion was ≥ 80% support. If < 80% members considered a characteristic a ‘core’ feature, but ≥ 80% considered it either ‘core’ or ‘optional,’ it was considered an ‘optional’ feature. If neither was the case, the characteristic was excluded. Free-text comments were permitted. Characteristics considered ‘core’ by 50–99% of respondents in Round 1 (i.e., nonunanimous support) and uninvestigated free-text comments were assessed in Round 2. Core and optional structured reporting templates were derived. RESULTS: The response rate was 100% in Round 1 (16/16) and Round 2 (16/16). In Round 1, 5 characteristics had unanimous support as ‘core’ features. Following Round 2, 13 characteristics had ≥ 80% support as ‘core’ features, and 10 characteristics had ≥ 80% support as ‘optional’ features. Structured report templates were derived. DISCUSSION: Structured ‘core’ and ‘optional’ templates for indeterminate renal masses at CT and MRI were derived, which may improve compliance with reporting preferred and essential imaging characteristics.

© 2020 IEEE. Deep learning has shown a strong potential in device-free human activity recognition (HAR). However, a fundamental challenge is ensuring accuracy, without re-training, when exposing a previously trained architecture to a new or unseen environment. To overcome the aforementioned challenge, this paper proposes an environment-robust channel state information (CSI) based HAR by leveraging the properties of a matching network (MatNet) and enhanced features (HAR-MN-EF). To improve the CSI quality, we propose a CSI cleaning and enhancement method (CSI-CE) that includes two key stages: activity-related information extraction (ARIE) and correlation feature extraction based on principal component analysis (CFE-PCA). The ARIE stage is able to effectively enhance the activity-dependent features whilst mitigating behavior-unrelated information. The CFE-PCA stage further improves the extracted features by filtering out the residual activity-unrelated data and the residual noise contained in signals from the former stage. The extracted features are then sequenced into the MatNet to create an environment-robust HAR. Experimental results confirm that an architecture trained by the proposed HAR-MN-EF can be directly adapted to a new environment, achieving reliable sensing accuracies without requiring additional effort.

This paper presents an access control schema using a WIFI bridge for smart locks and explores its implementation in one such pair of devices. The schema outlines the interaction between a smart lock (SimSim), accompanying WIFI bridge (Freedom), a cloud server, and a group of users operating smartphones. The schema leverages AES256 symmetric encryption, Bluetooth Low Energy, and HTTPS communications to provide enhanced access control for short-term landlords participating in the sharing economy. These additional features include facilitating a larger quantity of users, 24/7 permissions management, 24/7 monitoring, all without requiring physical proximity to the app.

The development of mobile-health technology has the potential to revolutionize personalized medicine. Biomedical sensors (e.g., wearables) can assist with determining treatment plans for individuals, provide quantitative information to healthcare providers, and give objective measurements of health, leading to the goal of precise phenotypic correlates for genotypes. Even though treatments and interventions are becoming more specific and datasets more abundant, measuring the causal impact of health interventions requires careful considerations of complex covariate structures, as well as knowledge of the temporal and spatial properties of the data. Thus, interpreting biomedical sensor data needs to make use of specialized statistical models. Here, we show how the Bayesian structural time series framework, widely used in economics, can be applied to these data. This framework corrects for covariates to provide accurate assessments of the significance of interventions. Furthermore, it allows for a time-dependent confidence interval of impact, which is useful for considering individualized assessments of intervention efficacy. We provide a customized biomedical adaptor tool, MhealthCI, around a specific implementation of the Bayesian structural time series framework that uniformly processes, prepares, and registers diverse biomedical data. We apply the software implementation of MhealthCI to a structured set of examples in biomedicine to showcase the ability of the framework to evaluate interventions with varying levels of data richness and covariate complexity and also compare the performance to other models. Specifically, we show how the framework is able to evaluate an exercise intervention’s effect on stabilizing blood glucose in a diabetes dataset. We also provide a future-anticipating illustration from a behavioral dataset showcasing how the framework integrates complex spatial covariates. Overall, we show the robustness of the Bayesian structural time series framework when applied to biomedical sensor data, highlighting its increasing value for current and future datasets., Author summary In this paper, we propose and describe a robust and flexible modeling framework called MhealthCI based on the Bayesian structural time series, for which we have found to excel at analyzing diverse biosensor data. While Bayesian modeling is often employed in various fields such as finance, marketing, and weather forecasting, it is rarely used in biomedicine, specifically for biosensor and wearable data relating to human health and behavior. We use and apply this framework with the goal of interpreting and quantifying the causal impact of an intervention, a widespread goal of biomedicine. We describe the diversity of data types to which it could apply, provide intuition to its mechanics, collect relevant data in various fields, provide a wrapper tool around well-known R packages that prepares and registers diverse biosensor data to be analyzed, and finally apply the method to showcase its strength in quantifying the impact of interventions.

Metrology measurements of the top copper contact in the main chip area is critical to predict the subsequent electrical performance in advanced 3D NAND technology nodes. Conventional CDSEM is used in the determination of top copper CD while the accurate measurement of copper depth remains challenging. In this paper, we propose a new approach that successfully explored the use of machine learning to combine the advantages of optical Critical Dimension (OCD) and picosecond ultrasonic technology (PULSE™) for high volume manufacturing (HVM) measurements in the main chip area. Results demonstrate that by using machine learning, we were able to combine the PULSE reference with cross-section microscopy results to successfully train the OCD data set. OCD measurements are rapid at

Device-free WiFi sensing utilizing channel state information (CSI) is attractive for human activity recognition (HAR). However, several challenging problems are yet to be resolved, e.g., difficulty in extracting proper features from input signals, susceptibility to the phase shift of CSI and difficulty in identifying similar behaviors (e.g., lying and standing). In this paper, we aim to tackle these problems by proposing a novel scheme for CSI-based HAR that uses activity filter-based deep learning network (HAR-AF-DLN) with enhanced correlation features. We first develop a novel CSI compensation and enhancement (CCE) method to compensate for the timing offset between the WiFi transmitter and receiver, enhance activity-related signals and reduce the dimension of inputs to DLN. Then, we design a novel activity filter (AF) to differentiate similar activities (e.g., standing and lying) based on the enhanced CSI correlation features obtained from CCE. Extensive simulation results demonstrate that our proposed HAR-AF-DLN scheme outperforms state-of-the-art methods with significantly improved recognition accuracy (especially for similar activities) and notably reduced training time.

The novel coronavirus pandemic, also known as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has placed an immense strain on healthcare systems across the entire world. Consequently, multiple federal and state governments have placed restrictions on hospitals such as limiting "elective surgery" and recommending social or physical distancing. We review the literature on several areas that have been affected including surgical selection, inpatient care, and physician well-being. These areas affecting inpatient paradigms include surgical priority, physical or social distancing, file sharing for online clinical communications, and physician wellness. During this crisis, it is important that orthopaedic departments place an emphasis on personnel safety and slowing the spread of the virus so that the department can still maintain vital functions. Physical distancing and emerging technologies such as inpatient telemedicine and online file sharing applications can enable orthopaedic programs to still function while attempting to protect medical staff and patients from the novel coronavirus spread. This literature review sought to provide evidence-based guidance to orthopaedic departments during an unprecedented time. Orthopaedic surgeons should follow the Centers for Disease Control and Prevention guidelines, wear personal protective equipment (PPE) when appropriate, have teams created using physical distancing, understand the department's policy on elective surgery, and engage in routines which enhance physician wellness.

© 2002-2012 IEEE. The sparse code multiple access (SCMA) is a promising candidate for bandwidth-efficient next generation wireless communications, since it can support more users than the number of resource elements. On the same note, faster-than-Nyquist (FTN) signaling can also be used to improve the spectral efficiency. Hence in this paper, we consider a combined uplink FTN-SCMA system in which the data symbols corresponding to a user are further packed using FTN signaling. As a result, a higher spectral efficiency is achieved at the cost of introducing intentional inter-symbol interference (ISI). To perform joint channel estimation and detection, we design a low complexity iterative receiver based on the factor graph framework. In addition, to reduce the signaling overhead and transmission latency of our SCMA system, we intrinsically amalgamate it with grant-free scheme. Consequently, the active and inactive users should be distinguished. To address this problem, we extend the aforementioned receiver and develop a new algorithm for jointly estimating the channel state information, detecting the user activity and for performs data detection. In order to further reduce the complexity, an energy minimization based approximation is employed for restricting the user state to Gaussian. Finally, a hybrid message passing algorithm is conceived. Our Simulation results show that the FTN-SCMA system relying on the proposed receiver design has a higher throughput than conventional SCMA scheme at a negligible performance loss.

Nearly 80% of cirrhotic patients diagnosed with hepatocellular carcinoma (HCC) are not eligible for surgical resection and instead undergo local-regional treatment. After therapy for HCC, patients undergo imaging surveillance to assess treatment efficacy and identify potential sites of progressive tumor elsewhere within the liver. Accurate interpretation of posttreatment imaging is essential for guiding further management decisions, and radiologists must understand expected treatment-specific imaging findings for each of the local-regional therapies. Of interest, expected imaging findings seen after radiation-based therapies (transarterial radioembolization and stereotactic body radiation therapy) are different than those seen after thermal ablation and transarterial chemoembolization. Given differences in expected posttreatment imaging findings, the current radiologic treatment response assessment algorithms used for HCC (modified Response Evaluation Criteria in Solid Tumors classification, European Association for the Study of Liver Diseases criteria, and Liver Imaging and Reporting Data System Treatment Response Algorithm) must be applied cautiously for radiation-based therapies in which persistent arterial phase hyperenhancement in the early posttreatment period is common and expected. This article will review the concept of tumor response assessment for HCC, the forms of local-regional therapy for HCC, and the expected posttreatment findings for each form of therapy. Keywords: Abdomen/GI, Liver, MR-Imaging, Treatment Effects, Tumor Response © RSNA, 2020.

© 2005-2012 IEEE. Motivated to understand the increasingly severe threat of unmanned aerial vehicles (UAVs) to the confidentiality of terrestrial radio links, this paper analyzes the ergodic and ϵ-outage secrecy capacities of the links in the presence of multiple cooperative aerial eavesdroppers flying autonomously in three-dimensional (3D) spaces and exploiting selection combining (SC) or maximal ratio combining (MRC). The 'cut-off' density of the eavesdroppers under which the secrecy capacities vanish is identified. By decoupling the analysis of the random trajectories from the random channel fading, closed-form approximations with almost sure convergence to the secrecy capacities are devised. The analysis is extended to study the impact of the oscillator phase noises and finite memories of the aerial eavesdroppers on the secrecy performance of the ground link. Validated by simulations, the cut-off density only depends on the range of the link in the case of SC eavesdropping, while it depends on the flight region of the eavesdroppers in the case of MRC eavesdropping.

We propose Deterministic Channel Aggregation (DCA) for LTE-Unlicensed, where the LTE eNodeB aggregates a predetermined number of channels in the unlicensed spectrum to achieve high data-rate communications. We introduce the MAC layer design, and analyze the collision probability and channel occupation ratio for DCA. Simulation results validate the effectiveness of DCA and our analytical results, when the eNB coexists with multiple WiFi systems under a range of traffic load conditions. DCA is particularly useful for applications that require high bandwidth and enables efficient access control of mobile broadband applications in the LTE-Unlicensed.

© 1967-2012 IEEE. This paper analyzes the link capacity between autonomous unmanned aerial vehicles (UAVs) with random three-dimensional (3-D) trajectories. This is distinctively different from existing works typically under the assumption of either two-dimensional (2-D) or deterministic trajectories, and particularly interesting to applications such as surveillance and air combat. The key idea is that we geometrically derive the probability distributions of the UAV-to-UAV (U2U) distances which, by exploiting the Jensen's inequality, can be translated to the closed-form bounds for the capacity between UAVs, and between UAVs and ground stations. Another important aspect is that we extrapolate the idea to dense UAV networks, and analyze the impact of network densification, imperfect channel state information, and interference from ground transmitters on the capacity. Corroborated by simulations, our analysis shows that a U2U link with random 2-D trajectories is superior in terms of capacity due to its short average link distance. It is also revealed that a UAV-to-ground link can incur substantially lower capacity than a U2U link even in the case the 3-D coverage of the UAVs is the same, as the result of its longer average link length.

Background Atrial fibrillation (AF) occurs in 30% of patients with mitral regurgitation referred for surgical intervention. However, the underlying mechanisms in this population are poorly understood. This study examined the effects of acute left atrial volume overload on atrial electrophysiology and the inducibility of AF. Methods Ten canines underwent insertion of an atrioventricular shunt between the left ventricle and left atrium. Shunt and aortic flows were calculated, and the shunt was titrated to a shunt fraction to 40% to 50% of cardiac output. An epicardial plaque with 250 bipolar electrodes was used to determine activation and refractory periods. Biatrial pressures and volumes, conduction times, and atrial fibrillation inducibility were recorded. Data were collected at baseline and 20 minutes after shunt opening and closure. Results Mean shunt flow was 1.3 ± 0.5 L/min with a shunt fraction of 43% ± 6% simulating moderate to severe mitral regurgitation. Compared with baseline, left atrial volumes and maximum pressures increased by 27% and 29%, respectively, after shunt opening. Biatrial effective refractory periods did not change significantly after shunt opening or closure. Conduction times increased by 9% with shunt opening and returned to baseline after closure. AF duration or inducibility did not change with shunt opening. Conclusions This canine model of mitral regurgitation demonstrated that acute left atrial volume overload did not increase the inducibility of atrial arrhythmias in contrast with experimental and clinical findings of chronic left atrial volume overload. This suggests that the substrates for AF in patients with mitral regurgitation are a result of chronic remodeling.

Background This study investigates the impact of left ventricular assist device (LVAD) inflow cannula angulation, pump positional change over time, and the incidence of thrombotic pump dysfunction in a large cohort of HeartMate II (HM2) patients. Methods Patients (n = 326) who received primary HM2 LVAD between January 2008 and December 2013 at a single institution were retrospectively reviewed. Patients who underwent pump exchange (PE) for pump dysfunction, patients who had pump dysfunction (PD) but did not require pump exchange, and patients with normal LVAD pump dysfunction (NL) were compared. Pump positional change and angle of the inflow cannula with respect to the angle between inflow cannula and the LVAD body (IL angle) were measured from routine chest radiograph at postoperation, before discharge, and follow-up. Pump positional change was assessed based on pump positional differences between discharge and follow-up. Patients were also grouped by IL acute angulation (less than 65 degrees) and pump positional change. Results There were 21, 15, and 290 patients in the PE group, PD group, and NL group, respectively. There were significant differences in IL angle between PE and NL at all timepoints: postoperation (PD 63.6 ± 12.5, NL 70.6 ± 12.3; p = 0.018), before discharge (PD 64.4 ± 12.8, NL 69.5 ± 10.5; p = 0.039), and follow-up (PD 62.6 ± 14.2, NL 67.9 ± 11.2; p = 0.002). However, the IL angle was insignificant between PE and PD groups and between PD and NL groups. Sixty-seven percent of the PE group had pump positional change as opposed to 36% of the NL group ( p = 0.019). Eighty-four of 101 patients with pump positional change and 75 of 91 patients with acute angulation at postoperation did not have pump dysfunction. Conclusions Pump positional change may contribute to LVAD dysfunction or failure, but it does not entirely account for observed pump dysfunction or failure.

Survivability of wireless communications segments in tactical military networks is an enormous challenge in the present and future defence forces, especially as these networks usually operate in radio frequency (RF) contested environments. Therefore, it is necessary to develop techniques to provide effective and efficient communication in RF contested environments. Massive multiple-input-multiple-output (MIMO) techniques use a large number of antennas enabling higher degrees of freedom that can improve communications network's survivability and efficiency compared to conventional MIMO or single antenna systems. This paper presents a novel massive MIMO communications system which enhances the throughput of the network, reduces the bit-error-rate and mitigates the interference from high powered jammers. Simulation results in contested environments verify the effectiveness of this system.

Chemoradiation therapy plays an important role in both the neoadjuvant and definitive management of esophageal cancer (EC). Prior studies have suggested that advanced planning techniques can better spare organs at risk including the heart. Although multiple toxicities can result from esophageal radiotherapy, one less studied acute toxicity is that of myelosuppression, which can result, in part, from the combination of chemotherapy and incidental radiotherapy administration to the vertebral bodies (VBs), which abut the posterior aspect of the esophagus, especially in the lower thoracic esophagus. Traditionally, VB bone marrow doses are not accounted during EC radiation therapy planning. We sought to compare the doses to VBs between proton and photon radiation therapy as part of chemoradiation therapy for EC treatment. By reducing doses to the vertebrae, radiation therapy can decrease treatment-related myelosuppression, which can avoid delays or chemotherapy dose reductions in therapy, which likely affect long-term patient survival. Dose constraints are not routinely employed for bone marrow in radiation treatment planning. In our previous work, we identified thresholds to avoid grade ≥3 leukopenia, including VB V10Gy, VB V20Gy, and a mean VB dose (MVD) of 18.8 Gy. Herein we perform a retrospective dosimetric planning study comparing passive- or double-scattering proton beam therapy (PS-PBT), volumetric-modulated arc therapy (VMAT) (photon-based), and intensity-modulated radiation therapy (IMRT) (photon-based) in 25 patients with locally advanced EC who were treated originally with photon RT at our institution between 2011 and 2016. The aforementioned dose constraints were included in the retrospective planning process for PS-PBT, VMAT, and IMRT to determine the feasibility of achieving these VB constraints while maintaining reasonable target coverage and planned, consistent constraints to other organs at risk including lungs, spinal cord, and stomach. PS-PBT plans were found to achieve lower doses for VB V10Gy, V20Gy, and MVD than VMAT and static IMRT plans while achieving the same target coverage. PS-PBT resulted in lower organs at risk dosimetric parameters than the photon plans, with p < 0.0001. Student's paired t-test p-values in favor of proton therapy's ability to spare organs were as follows: for PS-PBT vs VMAT and PS-PBT vs IMRT in mean doses for lung, liver, and VB and VB V10Gy and VB V20Gy were all

© 2019 IEEE. Orthogonal time frequency space (OTFS) modulation shows great performance improvement over high-mobility wireless channels compared with traditional orthogonal frequency division multiplexing (OFDM). In this paper, we first derive the input and output relationship of OTFS signal in the delay-time domain, which shows that OTFS can be regarded as a combination of OFDM and single-carrier frequency-division multiple access (SC-FDMA). We then examine the diversity order of an OTFS system through received signal-to-noise ratio analysis and predict that this modulation technique can potentially achieve full diversity in both delay and Doppler domains. Finally, we simulate the OTFS performance based on 5G tapped-delay-line channel models under both slow and fast fading conditions. Extensive simulation results confirm that OTFS performs significantly better than other modulation techniques in fast fading channels.

Objectives: The purpose of the current study is to review the results of meniscus repairs with and without bone marrow aspiration concentrate (BMAC). It is hypothesized that with BMAC, meniscus repair outcomes will be improved when compared to without BMAC at 1 year after surgery. Methods: This is a prospective case control study performed from August 2014 until August 2017. Patients were included if they had a meniscus repair performed with no history of prior meniscus surgery to the operative knee. Patients were excluded if there was a full thickness cartilage tear or International Cartilage Repair Society (ICRS) Grade IV cartilage tear not treated in a single staged surgery. Patients were also excluded if they did not reach the one year follow-up, had a multi-ligamentous knee injury requiring multiple staged procedures. From August 2014 until November 2015, patients had meniscus repair without BMA. Menisci were all repaired arthroscopically using inside-out, outside-in and all-inside techniques. After November 2015, all meniscus repairs were augmented with BMAC. In the BMAC group, all bone marrow was obtained from the ipsilateral femur during the time of surgery. The Biocue BMAC system (Zimmer Biomet, Warsaw Indiana) was used for bone marrow aspiration and BMAC was injected directly into the tear site after repair. Numerical data such as VAS, lysholm and IKDC was analyzed using a 2 sample T-test. Categorical data such as sex, tear location, type of tear and zone of tear were analyzed using a chi-square. Results: A total of 150 patients were initially included in the study. The average age in the control group was 26.3 versus 29.4 in the BMAC group (P=0.27). Thirty seven percent of the control group had an ACL reconstruction versus 40% in the BMAC group (P= .77). The control group improved from an average pain level of 6.1 to 1.2 and the BMAC group improved from an average pain level of 5.9 to 0.7 at the 1 year end point. Both the control group and BMAC group improved with respect to pain with no difference at the 1 year end point (P=.19). There was, however a significantly larger reduction in pain at the 6 week and 3 month time point with BMAC compared to the control group (P=.02 and P=.02 respectively). At the 1-year follow-up, the mean lysholm score improved from 43 to 92 in the control group and 43 to 90 in the BMAC group. The mean IKDC score improved from 37 to 87 in the control group and 36 to 83 in the BMAC group at the one year follow-up. Conclusion: Meniscus repair outcomes were improved at 6 weeks and 3 months post-operatively, when BMAC is used to augment meniscus repair compared to repair without BMAC. Both groups, control group and BMAC meniscus repair group had improved outcomes at 1 year post-operatively with respect to VAS, lysholm and IKDC, with no difference in complication rate.

Hepatocellular carcinoma (HCC) is the second most common cause of cancer death worldwide, with a majority of HCC patients not suitable for curative therapies. Approximately 70% of initially diagnosed patients cannot undergo surgical resection or transplantation due to locally advanced disease, poor liver function/underlying cirrhosis, or additional comorbidities. Local therapeutic options for patients with unresectable HCC, who are not suitable for thermal ablation, include transarterial embolization (bland, chemoembolization, radioembolization) and/or external beam radiation therapy (EBRT). Regarding EBRT specifically, technological advancements provide a means for safe and effective radiotherapy delivery in a wide spectrum of HCC patients. In multiple prospective studies, EBRT delivery in a variety of different fractionation schemes or in combination with transcatheter arterial chemoembolization (TACE) demonstrate improved outcomes, particularly with combination therapy. The Barcelona Clinic Liver Cancer classification provides a framework for treatment selection; however, given the growing complexity of treatment strategies, this classification system tends to simplify decision-making. In this review, we discuss the current literature regarding unresectable HCC and propose a modified treatment algorithm that emphasizes the role of radiation therapy for Child-Pugh score A or B patients with ≤3 nodules measuring >3 cm, multinodular disease or portal venous thrombosis.

A specific mutation (Arg179) of the ACTA2 gene has previously been described to cause a syndrome of multisystemic smooth muscle dysfunction with an extremely characteristic cerebrovascular appearance.1 Accurate neuroimaging diagnosis of this entity is important as this syndrome predisposes to complications such as early-onset ischemic stroke and ascending thoracic aortic aneurysm.2,3 The following case demonstrates a previously undescribed ACTA2 mutation (Met46) with an identical cerebrovascular imaging appearance to that of Arg179 mutations, but a less severe overall phenotype.

© 2019 IEEE. In a dense urban area, conventional cellular V2X communications require frequent and heavy resource allocation, which can lead to processing congestion and large delay. In this paper, we propose a semi- persistent resource allocation scheme using the least minimum mean square error (LMMSE) traffic prediction in a two-tier network. The two-tier network architecture includes a central macro base station (MBS) and multiple roadside units (RSU). In the proposed scheme, the MBS pre-allocates persistent resource to RSUs based on predicted traffic, and then allocate dynamic resource upon real-time requests from vehicles through RSUs. We formulate an optimization problem for minimizing the total bandwidth under latency constraints and provide an optimal solution to the problem. Simulation is conducted for both artificially generated and real-world data, and the results validate the effectiveness of the proposed semi- persistent scheme.

© 2018 IEEE. Blockchain technology has been showing its strong performance on decentralized security when integrating with Internet of Things network. However, the trilemma of scalability-security-decentralization exists in Blockchain-based IoT. Therein the typical round-robin scheduling implemented in the Byzantine Faulty Tolerance (BFT) proposed by Neo's Blockchain has a significant delay when consecutive faulty miners exist. This paper proposes a novel analysis model for evaluating the network performance collapse in general, followed by an optimized round-robin scheduling for the case when the mutual latency difference is not significant enough for ranking. Based on the model, the optimized mechanism is able to increase the block rate for a specific subset of consecutive faulty miners by nearly 50% and provide a linearly positive growth rate of the mitigation with respect to the fail rate of a single miner, which strongly promotes the efficiency of the P2P-based BFT consensus algorithm.

Introduction: The treatment of choice for Unruptured intracranial aneurysms (UICA) is dependent on assessment of several factors including aneurysm size, location, and morphology, along with patient's life expectancy and comorbid conditions. Although multiple studies have deliberated upon the efficacy of surgical and endovascular aneurysm treatment for UICA, the rate of readmission with either technique has not been specifically studied. Methods: We used the Nationwide Readmission database to assess the readmission trends related to various treatment approaches for UICA. The treatment approaches were subdivided into four groups; surgical clipping group and three endovascular approach groups (coil embolization, stent assisted coil embolization and only stent placement groups). All four groups were compared for the characteristics of index hospitalizations and top causes of readmissions. Results: We identified 3533 patients treated with clipping and 4134 (3865 coil embolization, 192 only stent placement and 76 stent assisted coil embolization) patients treated with endovascular approach. Thirty day readmission rate (30RR) was significantly higher with surgical clipping compared to the three endovascular approach groups (8.37% Vs 4.77%, p Conclusion: Patients undergoing endovascular treatment for UICA are less likely to be readmitted and more likely to be discharged home compared to surgical clipping. Given the complex decision making with consideration of anatomic and patient factors for UICA treatment, these findings do not necessarily prove the general superiority of the endovascular approach but do suggest that when a UICA can be safely treated with either technique, the endovascular approach might reduce the chances of readmission.

© 2019, Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers and Springer-Verlag GmbH Germany, part of Springer Nature. Asynchronous switching differing from asynchronous consensus may hinder the system to reach a consensus. This receives very limited attention, especially when the multi-agent systems have a controller fault. In order to analyze the consensus in this situation, this paper studies the consensus of the second-order multi-agent systems under asynchronous switching with a controller fault. We convert the consensus problems under asynchronous switching into stability problems and obtain important results for consensus with the aid of linear matrix inequalities. An example is given to illustrate the effect of asynchronous switching on the consensus, and to validate the analytical results in this paper.

With the development of automated driving vehicles, more and more vehicles will be fitted with more than one automotive radars, and the radar mutual interference will become very significant. Vehicle to everything (V2X) communication is a potential way for coordinating automotive radars and reduce the mutual interference. In this paper, we analyze the positional relation of the two radars that interfere with each other, and evaluate the mutual interference for different types of automotive radars based on Poisson point process (PPP). We also propose a centralized framework and the corresponding algorithm, which relies on V2X communication systems to allocate the spectrum resources for automotive radars to minimize the interference. The minimum spectrum resources required for zero-interference are analyzed for different cases. Simulation results validate the analysis and show that the proposed framework can achieve near-zero-interference with the minimum spectrum resources.

Background and Purpose— Carotid web (CW) is a rare form of focal fibromuscular dysplasia defined as an abnormal shelf-like projection of intimal fibrous tissue into the carotid bulb. It is theorized that CW leads to ischemic stroke secondary to blood flow stasis and subsequent embolization. The natural history and optimal management of CW are unclear. To address this knowledge gap, we performed a systematic literature review (SLR) of CW. Methods— Our librarians performed a SLR for CW and related terminology. Patient-level demographics, stroke risk factors, neuroimaging findings, stroke recurrence or stroke free-duration, and treatment modality were extracted. We used descriptive statistics to characterize our results. When specific patient-level metrics were not reported, the denominators for reporting percentage calculations were adjusted accordingly. Results— Our literature search produced 1150 articles. Thirty-seven articles including 158 patients (median age 46 years [range 16–85], 68% women, 76% symptomatic) met entry criteria and were included in our SLR. Of the symptomatic CW patients: 57% did not have stroke risk factors, 56% who received medical therapy had recurrent stroke (median 12 months, range 0–97), and 72% were ultimately treated with carotid revascularization (50% carotid stenting, 50% carotid endarterectomy). There were no periprocedural complications or recurrent strokes in carotid revascularization patients. Conclusions— CW leads to ischemic stroke in younger patients without conventional stroke risk factors. We found a high stroke recurrence rate in medically managed symptomatic CW patients, whereas carotid revascularization effectively prevented recurrent stroke. Our findings should be interpreted with caution because of risk of publication and reporting bias.

Objectives The literature states that wrist ganglion cysts are most commonly dorsal; however, our experience suggests a volar location is more common. The purpose of this study was to identify the locations of ganglion cysts of the wrist as imaged with sonography. Methods After Institutional Review Board approval with informed consent waived, retrospective review of wrist sonography reports from January to April 2016 was completed. Only patients who had a comprehensive evaluation that included the dorsal and volar wrist were included. Ultrasound images were reviewed to characterize wrist ganglion cysts. Results The study group consisted of 98 subjects (78% female, 22% male) (median age, 51 years; range 13-79) with 124 wrist ganglion cysts, where 69% (86 of 124) were volar and 31% (38 of 124) were dorsal. Ganglion cysts were located between the radial artery and flexor carpi radialis in 63% (78 of 124), followed by a dorsal location superficial to the scapholunate ligament in 20% (25 of 124), other dorsal locations in 11% (13 of 124), and other volar locations in 6% (8 of 124). With dorsal ganglion cysts, the scapholunate ligament when imaged appeared normal in 91% (20 of 22). Ganglion cysts were multilocular/multilobular in all subjects. Conclusions The most common location for wrist ganglion cysts is in the volar wrist, particularly between the radial artery and flexor carpi radialis tendon, appearing multilocular or multilobular with a mean largest dimension of 1.0 cm. Given the propensity of ganglion cysts to occur at this site, attention to this area when imaging the wrist with sonography or magnetic resonance imaging should be considered.

Introduction Some hospitals do not have the technological capabilities of obtaining full 36-inch long-standing films to evaluate patients via proper sagittal balance spinal imaging protocol. Resistance from hospital administration for the purchase of proper hardware and software remains frustrating for spinal surgeons at both community and academic hospitals. Materials and methods Recurring transaction-based revenue streams were applied comparing cost with the different income generation at the hospital level. Cost is fixed cost, attributed to purchasing both the physical radiograph machine as well as the necessary software capabilities. Marginal cost was negligible as both materials and human capital are largely fungible and trivial at the margin. Revenue generation is largely identical to marginal revenue. Income was linked to the Hospital Outpatient Prospective Payment System for radiographic interpretation of films (Current Procedural Terminology (CPT) 72069). Income was also estimated from surgical volume calculation. Results The listed prospective outpatient radiographic reimbursement for the hospital was $24.36 per film. Medicare-defined reimbursements for a complex spinal fusion except cervical with spinal curvature, malignancy or 9+ fusions with a Major Complication or Comorbidity (MCC) was listed at $55,228, and with a Complication or Comorbidity (CC) was noted to be $40,566. Complex spinal fusion except cervical with spinal curvature, malignancy or 9+ fusions without CC/MCC was listed as $30,913. Lumbar spinal fusion except cervical with MCC was $39,164 and with CC was $23,490. University Neurosurgery at Louisiana State University (LSU) Health Sciences Center in Shreveport, LA performed 1,013 thoracolumbar procedures in fiscal year (FY) 2015 with 557 (54.9%) being instrumented procedures. At a minimum, all instrumented procedures could benefit from proper spinal axis imaging, representing $13,568.52 of transaction-based annual gross revenue from radiographs alone. Hypothetical revenue generation of $491,696.42 was calculated. Conclusion There is a significant value proposition to the hospital in obtaining the proper technology for formal standing 36-inch scoliosis imaging. Marginal cost is negligible, while there are significant opportunities for marginal revenue per image obtained through transaction-based gross revenue, as well an immense hypothetical revenue stream from surgery-related gains. More importantly, it ensures a proper and complete delivery of spinal health to the hospital's healthcare population.