Real-time target moving monitoring algorithm in respiration gating system

This study proposes the use of the ScanNet real-time target moving monitoring method that allows the therapist to set up three primary color detection threshold values, the detection range, the automatic compensation of the distance of the device and the angle of the device. Moreover, the real-time images detected are used for reminding the patient to maintain the therapeutic posture. If the displacement exceeds the permitted range, an alert message will be sent out. Moreover, because the operation is simple, and the system requirements are not too demanding, ScanNet, in addition to its use in monitoring displacement during radiation therapy, can be applied to MRI and other treatments that require the patient to maintain a position for a long time or on patients receiving residential respiratory therapy.

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DEVELOPMENT OF MULTIPLEX REAL-TIME PCR ASSAY FOR SIX PATHOGENS: RAPID TOOL FOR DIAGNOSIS OF BACTERIAL MENINGITIS

Journal of Medicine and Pharmacy ◽

10.34071/jmp.2019.3.8 ◽

2019 ◽

pp. 60-66

Author(s):

Viet Quynh Tram Ngo ◽

Thi Ti Na Nguyen ◽

Hoang Bach Nguyen ◽

Thi Tuyet Ngoc Tran ◽

Thi Nam Lien Nguyen ◽

...

Keyword(s):

Bacterial Meningitis ◽

Real Time ◽

Real Time Pcr ◽

Diagnostic Methods ◽

Type B ◽

E Coli ◽

Pcr Assays ◽

Set Up ◽

Etiological Agents ◽

Suis Serotype

Introduction: Bacterial meningitis is an acute central nervous infection with high mortality or permanent neurological sequelae if remained undiagnosed. However, traditional diagnostic methods for bacterial meningitis pose challenge in prompt and precise identification of causative agents. Aims: The present study will therefore aim to set up in-house PCR assays for diagnosis of six pathogens causing the disease including H. influenzae type b, S. pneumoniae, N. meningitidis, S. suis serotype 2, E. coli and S. aureus. Methods: inhouse PCR assays for detecting six above-mentioned bacteria were optimized after specific pairs of primers and probes collected from the reliable literature resources and then were performed for cerebrospinal fluid (CSF) samples from patients with suspected meningitis in Hue Hospitals. Results: The set of four PCR assays was developed including a multiplex real-time PCR for S. suis serotype 2, H. influenzae type b and N. meningitides; three monoplex real-time PCRs for E. coli, S. aureus and S. pneumoniae. Application of the in-house PCRs for 116 CSF samples, the results indicated that 48 (39.7%) cases were positive with S. suis serotype 2; one case was positive with H. influenzae type b; 4 cases were positive with E. coli; pneumococcal meningitis were 19 (16.4%) cases, meningitis with S. aureus and N. meningitidis were not observed in any CSF samples in this study. Conclusion: our in-house real-time PCR assays are rapid, sensitive and specific tools for routine diagnosis to detect six mentioned above meningitis etiological agents. Key words: Bacterial meningitis, etiological agents, multiplex real-time PCR

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Power-Based Non-Intrusive Condition Monitoring for Terminal Device in Smart Grid

Sensors ◽

10.3390/s20133635 ◽

2020 ◽

Vol 20 (13) ◽

pp. 3635 ◽

Cited By ~ 1

Author(s):

Guoming Zhang ◽

Xiaoyu Ji ◽

Yanjie Li ◽

Wenyuan Xu

Keyword(s):

Smart Grid ◽

Power Consumption ◽

Real Time ◽

Condition Monitoring ◽

Resource Constraints ◽

Detection System ◽

Stable Operation ◽

Detection Accuracy ◽

Monitoring Method ◽

Dsp Processors

As a critical component in the smart grid, the Distribution Terminal Unit (DTU) dynamically adjusts the running status of the entire smart grid based on the collected electrical parameters to ensure the safe and stable operation of the smart grid. However, as a real-time embedded device, DTU has not only resource constraints but also specific requirements on real-time performance, thus, the traditional anomaly detection method cannot be deployed. To detect the tamper of the program running on DTU, we proposed a power-based non-intrusive condition monitoring method that collects and analyzes the power consumption of DTU using power sensors and machine learning (ML) techniques, the feasibility of this approach is that the power consumption is closely related to the executing code in CPUs, that is when the execution code is tampered with, the power consumption changes accordingly. To validate this idea, we set up a testbed based on DTU and simulated four types of imperceptible attacks that change the code running in ARM and DSP processors, respectively. We generate representative features and select lightweight ML algorithms to detect these attacks. We finally implemented the detection system on the windows and ubuntu platform and validated its effectiveness. The results show that the detection accuracy is up to 99.98% in a non-intrusive and lightweight way.

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Clutter Cancellation and Long Time Integration for GNSS-Based Passive Bistatic Radar

Remote Sensing ◽

10.3390/rs13040701 ◽

2021 ◽

Vol 13 (4) ◽

pp. 701 ◽

Cited By ~ 1

Author(s):

Binbin Wang ◽

Hao Cha ◽

Zibo Zhou ◽

Bin Tian

Keyword(s):

Fourier Transform ◽

Target Detection ◽

Time Integration ◽

Detection Performance ◽

Bistatic Radar ◽

Detection Range ◽

Robust Detection ◽

Coherent Integration ◽

Long Time ◽

Long Time Integration

Clutter cancellation and long time integration are two vital steps for global navigation satellite system (GNSS)-based bistatic radar target detection. The former eliminates the influence of direct and multipath signals on the target detection performance, and the latter improves the radar detection range. In this paper, the extensive cancellation algorithm (ECA), which projects the surveillance channel signal in the subspace orthogonal to the clutter subspace, is first applied in GNSS-based bistatic radar. As a result, the clutter has been removed from the surveillance channel effectively. For long time integration, a modified version of the Fourier transform (FT), called long-time integration Fourier transform (LIFT), is proposed to obtain a high coherent processing gain. Relative acceleration (RA) is defined to describe the Doppler variation results from the motion of the target and long integration time. With the estimated RA, the Doppler frequency shift compensation is carried out in the LIFT. This method achieves a better and robust detection performance when comparing with the traditional coherent integration method. The simulation results demonstrate the effectiveness and advantages of the proposed processing method.

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Implementation of a deep learning model for automated classification of Aedes aegypti (Linnaeus) and Aedes albopictus (Skuse) in real time

Scientific Reports ◽

10.1038/s41598-021-89365-3 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Song-Quan Ong ◽

Hamdan Ahmad ◽

Gomesh Nair ◽

Pradeep Isawasan ◽

Abdul Hafiz Ab Majid

Keyword(s):

Deep Learning ◽

Aedes Aegypti ◽

Real Time ◽

Aedes Albopictus ◽

Automated Classification ◽

Expert Performance ◽

Deep Convolutional Neural Networks ◽

Significant Difference ◽

Set Up

AbstractClassification of Aedes aegypti (Linnaeus) and Aedes albopictus (Skuse) by humans remains challenging. We proposed a highly accessible method to develop a deep learning (DL) model and implement the model for mosquito image classification by using hardware that could regulate the development process. In particular, we constructed a dataset with 4120 images of Aedes mosquitoes that were older than 12 days old and had common morphological features that disappeared, and we illustrated how to set up supervised deep convolutional neural networks (DCNNs) with hyperparameter adjustment. The model application was first conducted by deploying the model externally in real time on three different generations of mosquitoes, and the accuracy was compared with human expert performance. Our results showed that both the learning rate and epochs significantly affected the accuracy, and the best-performing hyperparameters achieved an accuracy of more than 98% at classifying mosquitoes, which showed no significant difference from human-level performance. We demonstrated the feasibility of the method to construct a model with the DCNN when deployed externally on mosquitoes in real time.

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Operational Research to Assess the Real-Time Impact of COVID-19 on TB and HIV Services: The Experience and Response from Health Facilities in Harare, Zimbabwe

Tropical Medicine and Infectious Disease ◽

10.3390/tropicalmed6020094 ◽

2021 ◽

Vol 6 (2) ◽

pp. 94

Author(s):

Pruthu Thekkur ◽

Kudakwashe C. Takarinda ◽

Collins Timire ◽

Charles Sandy ◽

Tsitsi Apollo ◽

...

Keyword(s):

Hiv Testing ◽

Treatment Outcomes ◽

Real Time ◽

Treatment Success ◽

Health Facilities ◽

Case Detection ◽

Monthly Data ◽

Hiv Services ◽

Tb Treatment ◽

Set Up

When COVID-19 was declared a pandemic, there was concern that TB and HIV services in Zimbabwe would be severely affected. We set up real-time monthly surveillance of TB and HIV activities in 10 health facilities in Harare to capture trends in TB case detection, TB treatment outcomes and HIV testing and use these data to facilitate corrective action. Aggregate data were collected monthly during the COVID-19 period (March 2020–February 2021) using EpiCollect5 and compared with monthly data extracted for the pre-COVID-19 period (March 2019–February 2020). Monthly reports were sent to program directors. During the COVID-19 period, there was a decrease in persons with presumptive pulmonary TB (40.6%), in patients registered for TB treatment (33.7%) and in individuals tested for HIV (62.8%). The HIV testing decline improved in the second 6 months of the COVID-19 period. However, TB case finding deteriorated further, associated with expiry of diagnostic reagents. During the COVID-19 period, TB treatment success decreased from 80.9 to 69.3%, and referral of HIV-positive persons to antiretroviral therapy decreased from 95.7 to 91.7%. Declining trends in TB and HIV case detection and TB treatment outcomes were not fully redressed despite real-time monthly surveillance. More support is needed to transform this useful information into action.

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Acceptance of a Symptom-Based Approach for COVID-19 rtRT-PCR Testing to Conserve Resources in a Lower Middle-Income Setting

Journal of Primary Care & Community Health ◽

10.1177/2150132720987711 ◽

2021 ◽

Vol 12 ◽

pp. 215013272098771

Author(s):

S. M. Rashed Ul Islam ◽

Tahmina Akther ◽

Md. Abdullah Omar Nasif ◽

Sharmin Sultana ◽

Saif Ullah Munshi

Keyword(s):

Primary Method ◽

Chain Reaction ◽

Middle Income ◽

Clinical Recovery ◽

Clinical Presentations ◽

Long Time ◽

Nasopharyngeal Secretion ◽

Polymerase Chain ◽

Set Up

SARS-CoV-2 initially emerged in Wuhan, China in late 2019. It has since been recognized as a pandemic and has led to great social and economic disruption globally. The Reverse Transcriptase Real-Time Polymerase Chain Reaction (rtRT-PCR) has become the primary method for COVID-19 testing worldwide. The method requires a specialized laboratory set up. Long-term persistence of SARS-CoV-2 RNA in nasopharyngeal secretion after full clinical recovery of the patient is regularly observed nowadays. This forces the patients to spend a longer period in isolation and test repeatedly to obtain evidence of viral clearance. Repeated COVID-19 testing in asymptomatic or mildly symptomatic cases often leads to extra workload for laboratories that are already struggling with a high specimen turnover. Here, we present 5 purposively selected cases with different patterns of clinical presentations in which nasopharyngeal shedding of SARS-CoV-2 RNA was observed in patients for a long time. From these case studies, we emphasized the adoption of a symptom-based approach for discontinuing transmission-based precautions over a test-based strategy to reduce the time spent by asymptomatic and mildly symptomatic COVID-19 patients in isolation. A symptom-based approach will also help reduce laboratory burden for COVID-19 testing as well as conserve valuable resources and supplies utilized for rtRT-PCR testing in an emerging lower-middle-income setting. Most importantly, it will also make room for critically ill COVID-19 patients to visit or avail COVID-19 testing at their convenience.

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Real time surveillance of COVID-19 space and time clusters during the summer 2020 in Spain

BMC Public Health ◽

10.1186/s12889-021-10961-z ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Nicolás Rosillo ◽

Javier Del-Águila-Mejía ◽

Ayelén Rojas-Benedicto ◽

María Guerrero-Vadillo ◽

Marina Peñuelas ◽

...

Keyword(s):

Real Time ◽

Scan Statistic ◽

Cluster Aggregation ◽

Space And Time ◽

Spatial Trends ◽

Community Transmission ◽

Low Incidence ◽

Set Up ◽

And Control ◽

Time Scan

Abstract Background On June 21st de-escalation measures and state-of-alarm ended in Spain after the COVID-19 first wave. New surveillance and control strategy was set up to detect emerging outbreaks. Aim To detect and describe the evolution of COVID-19 clusters and cases during the 2020 summer in Spain. Methods A near-real time surveillance system to detect active clusters of COVID-19 was developed based on Kulldorf’s prospective space-time scan statistic (STSS) to detect daily emerging active clusters. Results Analyses were performed daily during the summer 2020 (June 21st – August 31st) in Spain, showing an increase of active clusters and municipalities affected. Spread happened in the study period from a few, low-cases, regional-located clusters in June to a nationwide distribution of bigger clusters encompassing a higher average number of municipalities and total cases by end-August. Conclusion STSS-based surveillance of COVID-19 can be of utility in a low-incidence scenario to help tackle emerging outbreaks that could potentially drive a widespread transmission. If that happens, spatial trends and disease distribution can be followed with this method. Finally, cluster aggregation in space and time, as observed in our results, could suggest the occurrence of community transmission.

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Reducing Culture Reporting Errors in the Microbiology Laboratory

American Journal of Clinical Pathology ◽

10.1093/ajcp/aqz125.009 ◽

2019 ◽

Vol 152 (Supplement_1) ◽

pp. S131-S132

Author(s):

Kathryn Hogan ◽

Beena Umar ◽

Mohamed Alhamar ◽

Kathleen Callahan ◽

Linoj Samuel

Keyword(s):

Real Time ◽

Error Rate ◽

Reporting System ◽

Error Rates ◽

Tracking Errors ◽

Corrective Measures ◽

Safety Awareness ◽

Before And After ◽

Set Up ◽

System Errors

Abstract Objectives There are few papers that characterize types of errors in microbiology laboratories and scant research demonstrating the effects of interventions on microbiology lab errors. This study aims to categorize types of culture reporting errors found in microbiology labs and to document the error rates before and after interventions designed to reduce errors and improve overall laboratory quality. Methods To improve documentation of error incidence, a self-reporting system was changed to an automatic reporting system. Errors were categorized into five types Gram stain (misinterpretations), identification (incorrect analysis), set up labeling (incorrect patient labels), procedures (not followed), and miscellaneous. Error rates were tracked according to technologist, and technologists were given real-time feedback by a manager. Error rates were also monitored in the daily quality meeting and frequently detected errors were discussed at staff meetings. Technologists attended a year-end review with a manager to improve their performance. To maintain these changes, policies were developed to monitor technologist error rate and to define corrective measures. If a certain number of errors per month was reached, technologists were required to undergo retraining by a manager. If a technologist failed to correct any error according to protocol, they were also potentially subject to corrective measures. Results In 2013, we recorded 0.5 errors per 1,000 tests. By 2018, we recorded only 0.1 errors per 1,000 tests, an 80% decrease. The yearly culture volume from 2013 to 2018 increased by 32%, while the yearly error rate went from 0.05% per year to 0.01% per year, a statistically significant decrease (P = .0007). Conclusion This study supports the effectiveness of the changes implemented to decrease errors in culture reporting. By tracking errors in real time and using a standardized process that involved timely follow-up, technologists were educated on error prevention. This practice increased safety awareness in our micro lab.

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