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Dear editor, We read the article on “The carotid body and associated tumors: updated review with clinical/surgical significance”, by Butt et al with great interest. 1 In the treatment section of th...

Objective To analyze the temporal trends and state-wide geospatial variations in Vascular and Interventional Radiology (VIR) workforce in the United States. Methods The State Physician Workforce Data from the AAMC website was accessed for years 2015, 2017, and 2019. The variables collected for each state included total number of active physicians, total number of physicians per specialty and total number of female physicians in VIR. Comparative data was obtained for vascular surgery (VS), diagnostic radiology (DR), and radiation oncology (RO). The annual growth rate for total physicians and sub-analysis of female physicians in each state was computed for each specialty. Results From 2015 to 2019, the total number of active physicians in the United States grew by 1.8% per year. Growth of active physicians in VIR grew by 8.3%, DR 0.06%, VS 4.4%, and RO 1.9% per year. Colorado and Minnesota had the highest growth rate for VIR physicians (15%). VIR physicians per 100,000 people increased from 0.84 (2015) to 1.10 (2019) in the US. In comparison, VS physicians increased from 0.99 (2015) to 1.14 (2019), DR physicians decreased from 8.61 (2015) to 8.43 (2019), and RO physicians grew from 1.48 (2015) to 1.56 (2019). Women represented 6.8% of the VIR workforce in the US in 2019 and increased by a rate of 16% annually in the US from 2015 to 2019. In comparison, the number of women in VS has grown by 21%, DR by 2%, and RO by 2.4% during the same period. The state of Maryland has the highest proportion of women in VIR at 18%. Conclusion The number of VIR physicians is increasing at a higher rate than the national overall physician growth, and while female VIR physicians makeup a small fraction of the VIR workforce, their numbers have increased at a faster rate than overall VIR physicians.

In this paper, simplistic and much-awaited solution to the enigma of a secure user authentication system is proposed. For the same, we designed a virtually controllable numpad authentication system. To provide an effortless, immersive, and robust virtual experience which is color recognized, we employed a web camera along with the applied algorithm. The proposed modal intends to accomplish particular objectives, i.e., detection, recognition of an object, specialized graphical user interface, and authentication. Proposed methodology makes use of preprocessing tasks to convert a sequence of frames to detect and recognize a specified color. Numeric keys are placed at random positions in a definitive structure to provide a security feature. As a result, using our system, users can control a virtual numeric keypad by the movements of their color-banded fingertips. The webcam captures the consecutive frames and compares them to detect a difference in the contour, perceiving it as a keypress.

The COVID-19 pandemic has affected every sector of healthcare. Interventional Radiology in many instances continues to provide frontline care during this pandemic. The purpose of this article is to assist Interventional Radiologists in their preparation to face the challenges, by summarizing global experiences and guidelines. We provide a basic framework that can be used to prepare institue specific guidelines in coordination with multidisciplinary teams and hospital administration.

Background The rapid spread of COVID-19 renewed the focus on how health systems across the globe are financed, especially during public health emergencies. Development assistance is an important source of health financing in many low-income countries, yet little is known about how much of this funding was disbursed for COVID-19. We aimed to put development assistance for health for COVID-19 in the context of broader trends in global health financing, and to estimate total health spending from 1995 to 2050 and development assistance for COVID-19 in 2020. Methods We estimated domestic health spending and development assistance for health to generate total health-sector spending estimates for 204 countries and territories. We leveraged data from the WHO Global Health Expenditure Database to produce estimates of domestic health spending. To generate estimates for development assistance for health, we relied on project-level disbursement data from the major international development agencies' online databases and annual financial statements and reports for information on income sources. To adjust our estimates for 2020 to include disbursements related to COVID-19, we extracted project data on commitments and disbursements from a broader set of databases (because not all of the data sources used to estimate the historical series extend to 2020), including the UN Office of Humanitarian Assistance Financial Tracking Service and the International Aid Transparency Initiative. We reported all the historic and future spending estimates in inflation-adjusted 2020 US$, 2020 US$ per capita, purchasing-power parity-adjusted US$ per capita, and as a proportion of gross domestic product. We used various models to generate future health spending to 2050. Findings In 2019, health spending globally reached $8. 8 trillion (95% uncertainty interval [UI] 8.7-8.8) or $1132 (1119-1143) per person. Spending on health varied within and across income groups and geographical regions. Of this total, $40.4 billion (0.5%, 95% UI 0.5-0.5) was development assistance for health provided to low-income and middle-income countries, which made up 24.6% (UI 24.0-25.1) of total spending in low-income countries. We estimate that $54.8 billion in development assistance for health was disbursed in 2020. Of this, $13.7 billion was targeted toward the COVID-19 health response. $12.3 billion was newly committed and $1.4 billion was repurposed from existing health projects. $3.1 billion (22.4%) of the funds focused on country-level coordination and $2.4 billion (17.9%) was for supply chain and logistics. Only $714.4 million (7.7%) of COVID-19 development assistance for health went to Latin America, despite this region reporting 34.3% of total recorded COVID-19 deaths in low-income or middle-income countries in 2020. Spending on health is expected to rise to $1519 (1448-1591) per person in 2050, although spending across countries is expected to remain varied. Interpretation Global health spending is expected to continue to grow, but remain unequally distributed between countries. We estimate that development organisations substantially increased the amount of development assistance for health provided in 2020. Continued efforts are needed to raise sufficient resources to mitigate the pandemic for the most vulnerable, and to help curtail the pandemic for all. For complete list of authors see http://dx.doi.org/10.1016/S0140-6736(21)01258-7

Background Tuberculosis is a major contributor to the global burden of disease, causing more than a million deaths annually. Given an emphasis on equity in access to diagnosis and treatment of tuberculosis in global health targets, evaluations of differences in tuberculosis burden by sex are crucial. We aimed to assess the levels and trends of the global burden of tuberculosis, with an emphasis on investigating differences in sex by HIV status for 204 countries and territories from 1990 to 2019. Methods We used a Bayesian hierarchical Cause of Death Ensemble model (CODEm) platform to analyse 21 505 site-years of vital registration data, 705 site-years of verbal autopsy data, 825 site-years of sample-based vital registration data, and 680 site-years of mortality surveillance data to estimate mortality due to tuberculosis among HIV-negative individuals. We used a population attributable fraction approach to estimate mortality related to HIV and tuberculosis coinfection. A compartmental meta-regression tool (DisMod-MR 2.1) was then used to synthesise all available data sources, including prevalence surveys, annual case notifications, population-based tuberculin surveys, and tuberculosis cause-specific mortality, to produce estimates of incidence, prevalence, and mortality that were internally consistent. We further estimated the fraction of tuberculosis mortality that is attributable to independent effects of risk factors, including smoking, alcohol use, and diabetes, for HIV-negative individuals. For individuals with HIV and tuberculosis coinfection, we assessed mortality attributable to HIV risk factors including unsafe sex, intimate partner violence (only estimated among females), and injection drug use. We present 95% uncertainty intervals for all estimates. Findings Globally, in 2019, among HIV-negative individuals, there were 1·18 million (95% uncertainty interval 1·08–1·29) deaths due to tuberculosis and 8·50 million (7·45–9·73) incident cases of tuberculosis. Among HIV-positive individuals, there were 217 000 (153 000–279 000) deaths due to tuberculosis and 1·15 million (1·01–1·32) incident cases in 2019. More deaths and incident cases occurred in males than in females among HIV-negative individuals globally in 2019, with 342 000 (234 000–425 000) more deaths and 1·01 million (0·82–1·23) more incident cases in males than in females. Among HIV-positive individuals, 6250 (1820–11 400) more deaths and 81 100 (63 300–100 000) more incident cases occurred among females than among males in 2019. Age-standardised mortality rates among HIV-negative males were more than two times greater in 105 countries and age-standardised incidence rates were more than 1·5 times greater in 74 countries than among HIV-negative females in 2019. The fraction of global tuberculosis deaths among HIV-negative individuals attributable to alcohol use, smoking, and diabetes was 4·27 (3·69–5·02), 6·17 (5·48–7·02), and 1·17 (1·07–1·28) times higher, respectively, among males than among females in 2019. Among individuals with HIV and tuberculosis coinfection, the fraction of mortality attributable to injection drug use was 2·23 (2·03–2·44) times greater among males than females, whereas the fraction due to unsafe sex was 1·06 (1·05–1·08) times greater among females than males. Interpretation As countries refine national tuberculosis programmes and strategies to end the tuberculosis epidemic, the excess burden experienced by males is important. Interventions are needed to actively communicate, especially to men, the importance of early diagnosis and treatment. These interventions should occur in parallel with efforts to minimise excess HIV burden among women in the highest HIV burden countries that are contributing to excess HIV and tuberculosis coinfection burden for females. Placing a focus on tuberculosis burden among HIV-negative males and HIV and tuberculosis coinfection among females might help to diminish the overall burden of tuberculosis. This strategy will be crucial in reaching both equity and burden targets outlined by global health milestones. Funding Bill & Melinda Gates Foundation.

proposes a distributed composite adaptive synchronization algorithm for multiple uncertain EulerLagrange (EL) systems, where parameter convergence is achieved under a relaxed mathematical condition as compared to the state-of-the-art. Classical adaptive controllers require an analytical condition, called persistence of excitation (PE), to ensure parameter convergence, which results in better transient performance and robustness to disturbance. The PE condition is extended to Cooperative-PE (C-PE) condition for distributed adaptive controllers with cooperative estimation strategies. The PE and C-PE conditions are restrictive in nature since these conditions are not satisfied in most practical applications. Recent literature in adaptive control has relaxed the PE condition to Initial Excitation (IE), which is shown to be sufficient for parameter convergence. The IE condition is argued to be significantly milder than PE and can be satisfied in many practical setting. The proposed result further extends the IE condition to Cooperative-IE (C-IE) condition in distributed adaptive control architecture in the context of synchronizing multiple EL systems. It is established that the C-IE condition is milder than PE, IE, and C-PE conditions. Two-tier filter based estimation algorithm with strategic switching ensures parameter convergence under the C-IE condition and thereby provides exponential convergence of tracking and parameter estimation error to zero. Simulation results validate the efficacy of the proposed algorithm as compared to conventional distributed adaptive controllers in terms of superior tracking and estimation performance.

Social media use among healthcare providers has been increasing at a rapid pace as it allows them to build their online presence by reaching millions of people worldwide within a matter of seconds. With more and more physicians actively engaging in social media, it is imperative for physicians to know about various ethical principles and legal guidelines governing social media use by healthcare professionals. Radiologists should especially be aware of these guidelines as they frequently share radiological images to share teaching points and new findings.

ObjectiveTo quantify the prediagnostic loss to follow-up (PDLFU) in an active case finding tuberculosis (TB) programme and identify the barriers and enablers in undergoing diagnostic evaluation.DesignExplanatory mixed-methods design.SettingA rural population of 1.02 million in the Samastipur district of Bihar, India.ParticipantsBased on their knowledge of health status of families, community health workers or CHWs (called accredited social health activist or locally) and informal providers referred people to the programme. The field coordinators (FCs) in the programme screened the referrals for TB symptoms to identify presumptive TB cases. CHWs accompanied the presumptive TB patients to free diagnostic evaluation, and a transport allowance was given to the patients. Thereafter, CHWs initiated and supported the treatment of confirmed cases. We included 13 395 community referrals received between January and December 2018. To understand the reasons of the PDLFU, we conducted in-depth interviews with patients who were evaluated (n=3), patients who were not evaluated (n=4) and focus group discussions with the CHWs (n=2) and FCs (n=1).Outcome measuresProportion and characteristics of PDLFU and association of demographic and symptom characteristics with diagnostic evaluation.ResultsA total of 11 146 presumptive TB cases were identified between January and December 2018, out of which 4912 (44.1%) underwent diagnostic evaluation. In addition to the free TB services in the public sector, the key enablers were CHW accompaniment and support. The major barriers identified were misinformation and stigma, deficient family and health provider support, transport challenges and poor services in the public health system.ConclusionFinding the missing cases will require patient-centric diagnostic services and urgent reform in the health system. A community-oriented intervention focusing on stigma, misinformation and patient support will be critical to its success.

Our study proposes a novel method of key frame extraction, useful for video data. Video summarization indicates condensing the amount of data that must be examined to retrieve any noteworthy information from the video. Video summarization [1] proves to be a challenging problem as the content of video varies significantly from each other. Further significant human labor is required to manually summarize video. To tackle this issue, this paper proposes an algorithm that summarizes video without prior knowledge. Video summarization is not only useful in saving time but might represent some features which may not be caught by a human at first sight. A significant difficulty is the lack of a pre-defined dataset as well as a metric to evaluate the performance of a given algorithm. We propose a modified version of the harvesting representative frames of a video sequence for abstraction. The concept is to quantitatively measure the difference between successive frames by computing the respective statistics including mean, variation and multiple standard deviations. Then only those frames are considered that are above a predefined threshold of standard deviation. The proposed methodology is further enhanced by making it user interactive, so a user will enter the keyword about the type of frames he desires. Based on input keyword, frames are extracted from the Google Search API and compared with video frames to get desired frames.

Calcium-dependent protein kinases-related kinases (CDPK-related kinases; CRKs) are Ser/Thr kinases that bind with Ca2+/Calmodulin and play crucial roles in signal transduction pathways during plant growth, development, and responses to multiple stresses. In this study, we have studied detailed organ and tissue-specific expression patterns of rice CRK genes. Our organ-specific RT-PCR analyzes show the differential expression pattern of these genes in various organs of rice. Moreover, our RNA-RNA in situ hybridization study in rice stem base containing developing crown root primordia demonstrates that the expression of CRK genes is spatially restricted to the developing crown root primordia, suggesting their putative role in protein phosphorylation-dependent cellular signaling during rice crown root development. Furthermore, organ-specific differentially expression pattern of CRK genes during floral organogenesis further support for the organ-specific cell signaling during organogenesis. Thus, our study provides a developmentally regulated expression pattern of rice CRK genes, though they are broadly expressed and a basic foundation for functional characterizations of CRK gene members to unravel their specific functions during plant growth and development.

This work proposes a consensus-based novel PI-like parameter estimator for collaborative system identification. Conventional online parameter estimation algorithms, which are used for system identification, require a restrictive condition of persistence of excitation (PE) for the estimates to converge to the true parameters. Some recent works have shown that collaborative system identification using multiple agents can relax the PE condition to a milder condition of collective persistence of excitation (C-PE) for parameter convergence. The C-PE condition implies that the PE condition is cooperatively satisfied by all the agents through sharing information between neighbors using a connected graph architecture, where each individual agent does not require to satisfy the PE condition separately. The proposed work designs a novel collaborative parameter estimator dynamics, which with the help of integral-like component ensures parameter convergence under a further slackened condition; coined as collective Initial Excitation (C-IE). The C-IE condition is an extension of the concept of initial excitation (IE), which is recently proposed in the context of parameter estimation in adaptive control. It has been already established that IE condition is significantly less restrictive than PE. The current work generalizes the concept of IE in a multi-agent settings, where information sharing through connected graph guarantees consensus parameter convergence under the C-IE condition. It can be argued that C-IE condition is milder than all of the other above mentioned conditions of PE, C-PE and IE. Simulation results further validate the efficacy of the proposed estimation algorithm.

I read with great interest the social media vignette by D'Anna et al,[1][1] which describes the analysis of Twitter use during the American Society of Neuroradiology (ASNR) 2018 Annual Meeting. Although the analysis showed a substantial increase in Twitter use during the past 4 years, there is still

DSP48s, BRAMs and URAMs in the Xilinx Ultra-scale+ family support dedicated cascade interconnect for high frequency, nearest-neighbor data movement using hard wiring resources. We demonstrate how to leverage these interconnect structures to effectively support data movement requirements of dense machine learning (ML) workloads at URAM-limited 650MHz frequency (714MHz reported by Vivado). We refor-mulate convolution and matrix-vector multiplication operations to make effective use of cascade interconnect (1) in DSP48s for supporting the common multiply-accumulate chains, and (2) in BRAMs, and URAMs to exploit the data movement and reuse patterns of ML workloads. The use of these dedicated cascade interconnect are an alternative to Versal AI cores that throw away FPGA flexibility in favor of rigid ASIC components with unproven long-term value. Our 650MHz operation on the Xilinx VU37P UltraScale+ FPGA is competitive with the 720 MHz state-of-the-art Xilinx SuperTile design. We use 100% URAM288s, 95% DSP48s, and 77% BRAM in contrast to the 100% URAM288s, 56% DSP48, and 40% BRAM usage of the Xilinx SuperTile array. As a result, we deliver a ?7× superior GoogLeNet inference latency while sacrificing 30% of inference throughput than their design. For MLPerf benchmarks we note inference latencies between 2?s–1.54 ms with corresponding throughputs between 645–456K inf/s.

backgroundDespite active case-finding (ACF) identifying more presumptive and confirmed TB cases, high pre-diagnostic loss to follow-up (PDLFU) among presumptive TB cases referred for diagnostic test remains a concern. We aimed to quantify the PDLFU, and identify the barriers and enablers in undergoing a diagnostic evaluation in an ACF program implemented in 1.02 million rural population in the Samastipur district of Bihar, India.methodsDuring their routine work, Accredited Social Health Activists (ASHA, a community health worker or CHW), informal providers, and community laypersons identified people at risk of TB, and referred them to the program. A field coordinator (FC) screened them for TB symptoms at the patient’s home. The identified presumptive TB cases were accompanied by the CHW to a designated government facility for diagnostics. Those with a confirmed TB diagnosis were put on treatment by the CHW and followed-up till treatment completion. All services were provided free of cost and patients were supported throughout the care pathway, including a transport allowance. We analyzed programmatically collected data, conducted in-depth interviews with patients, and focus group discussions with the CHWs and FCs in an explanatory mixed-methods design.resultsA total of 11146 presumptive TB cases were identified from January 2018 to December 2018, out of which 4912 (44.1%) underwent a diagnostic evaluation. The key enablers were CHW accompaniment and support in addition to the free TB services in the public sector. The major barriers identified were transport challenges, deficient family and health provider support, and poor services in the public system.conclusionIf we are to find missing cases, the health system needs urgent reform, and diagnostic services need to be patient-centric. A strong patient support system engaging all stakeholders and involvement of CHWs in routine TB care is an effective solution.STRENGTHS AND LIMITATIONS OF THIS STUDYFirst such study to explore the reasons for pre-diagnostic loss to follow-upA mixed-method design including the views of both patients and community health workersUses operational data from a routine programmatic setting at an NGO siteNo record of the actual number of people screened intuitively before being referred to the program.No record of patients accessing diagnostics in private sector and those completing the diagnostic process.

Deflection-routed NoCs like Hoplite and HopliteRT take advantage of FPGA-specific features to deliver low-cost, high-frequency, FPGA-friendly communication networks. However, they suffer from long packet deflection penalties, low sustained throughputs, and feature limitations such as out-of-order delivery of packets. In this paper, we introduce the HopliteBuf NoC, and an associated static analysis tool, that eliminates deflections entirely while simultaneously adding in-order delivery feature using (1) small, stall-free FIFOs with provable occupancy bounds, and (2) linearization of vertical rings of the torus Hoplite topology to improve provable link utilization. We implement these FIFOs using cheap LUT SRAMs (Xilinx SRL32s, and Intel MLABs) to absorb packet contention. We evaluate conditions for stall-free behavior using static analysis that compute upper bounds on FIFO occupancy based on the communication pattern. Our static analysis deliver bounds that are not only better (in latency) than HopliteRT but also tighter by 2--3×. Across 100 randomly-generated flowsets mapped to a 5×5 system size, HopliteBuf is able to route a larger fraction of these flowsets with \textless 128-deep FIFOs, boost worst-case routing latency by $\approx$2× for mutually feasible flowsets. At 20% injection rates, HopliteRT is only able to route 1--2% of the flowsets while HopliteBuf can deliver 40--50% sustainability.

The incidence of cerebral aneurysms is rare in children, and it has to be definitively ruled out in all cases of intracranial bleed even if there is associated history of trauma. We report a case of 11-month-old girl who presented with intracranial bleed after a history of minor trauma whose diagnosis of an intracranial aneurysm was initially missed which later led to a rebleed. It was managed emergently with endovascular coiling and the patient showed incredible recovery in the post-operative period.

Monitoring wellbeing of the fetus is one of the challenges faced by obstetrics. The fetal movement will determine the health and growth of fetus for which different techniques have been explored like heart rate monitoring, kick pattern, and other health. With the improvement in technology, several remote monitoring techniques are introduced like accelerometer-based system in form of body worn or fetal kick detection based, etc. All the techniques have been discussed in the paper. Further, the paper presents a new prototype of the fetal kick detection device. The real-time monitoring of fetal kick will be analyzed using a belt worn by the patient consisting of pressure sensitive material and various sensors for detecting the fetal distress based on machine learning mechanism. In the future, the design will be developed and the belt will be analyzed in real time scenario.