Mixup-Inf-Net: A data augmentation algorithm for segmentation of new coronary pneumonia infections

In 2020, the global spread of Coronavirus Disease 2019 exposed entire world to a severe health crisis. This has limited fast and accurate screening of suspected cases due to equipment shortages and and harsh testing environments. The current diagnosis of suspected cases has benefited greatly from the use of radiographic brain imaging, also including X-ray and scintigraphy, as a crucial addition to screening tests for new coronary pneumonia disease. However, it is impractical to gather enormous volumes of data quickly, which makes it difficult for depth models to be trained. To solve these problems, we obtained a new dataset by data augmentation Mixup method for the used chest CT slices. It uses lung infection segmentation (Inf-Net [1]) in a deep network and adds a learning framework with semi-supervised to form a Mixup-Inf-Net semi-supervised learning framework model to identify COVID-19 infection area from chest CT slices. The system depends primarily on unlabeled data and merely a minimal amount of annotated data is required;therefore, the unlabeled data generated by Mixup provides good assistance. Our framework can be used to improve improve learning and performance. The SemiSeg dataset and the actual 3D CT images that we produced are used in a variety of tests, and the analysis shows that Mixup-Inf-Net semi-supervised outperforms most SOTA segmentation models learning framework model in this study, which also enhances segmentation performance. © 2023 SPIE.

The DRACO Door: Design, Test, and Integration of the Mechanism on the DART Spacecraft

The Double Asteroid Redirection Test (DART) mission is NASA's first planetary defense mission to demonstrate the viability of kinetically impacting an asteroid and deflecting its trajectory. The DART spacecraft successfully launched on November 24, 2021 from the Vandenberg Space Force Base and successfully made impact on Dimorphos, the smaller asteroid in the Didymos system, on September 26, 2022. The DART spacecraft has one instrument called Didymos Reconnaissance and Asteroid Camera for Optical navigation (DRACO). DRACO is an imaging telescope that, in conjunction with the SMART Navigation algorithm, autonomously guided the DART spacecraft to the asteroid. Because DRACO is a mission critical and light sensitive instrument, the DRACO Door mechanism was designed as the protective cover. The door functions to shield DRACO from stray light during launch, to deploy in space once when commanded, and to stay 180 degrees open for the duration of the mission. The DRACO Door went through several iterations during the design phase with decisions on various components such as Frangibolts ®, torsion springs, hardstops, and latches. After fabrication and assembly, the door went through a rigorous environmental testing plan, which included deployment testing, vibration testing, and thermal vacuum testing. After successful qualification of the mechanism, the door was installed and integrated into the DART spacecraft. It should be noted that during the fabrication of the mechanism piece-parts, the COVID-19 pandemic began, and the effects of the pandemic were seen in the challenges faced during the DRACO door assembly and testing. Under the constraints of the pandemic, the DART spacecraft was successfully built, tested, and launched, and the DRACO door was successfully deployed on December 7, 2021. The door has continued to function as intended. This paper will discuss the design choices behind the door components, the environmental qualification test program, and the installation of the door onto the DART spacecraft. In addition, this paper will discuss the lessons learned and the challenges of fabricating and testing the flight hardware. © 2023 IEEE.

Covid-19: Rest and PPE reassurance are needed before NHS services can restart, MPs hear

At a Health and Social Care Select Committee evidence session on 14 May the King's Fund, the Nuffield Trust, and the Health Foundation warned that it would take many more months before core health and care services were able to fully restart. Limited capacity Jennifer Dixon, chief executive officer at the Health Foundation, told the committee that capacity within hospitals would be severely limited because of the need for social distancing, separating out covid and non-covid patients, and more time for deep cleaning of equipment and facilities. Chris Hopson, chief executive officer at NHS Providers, told the committee that NHS staff had worked incredibly hard in the past few months, with leave cancelled, and were very tired as a result.

Improving Clinical Decisions Via Remote Blood Sampling

3 An important component for the provision of patient-centric healthcare is the ability to collect blood samples remotely in a manner that delivers samples of a quality comparable to that of current standard phlebotomy collection, enabling routine clinical testing, monitoring disease progression and testing drug concentrations.2-4-г, This blood sampling could be performed at the patient's home, at a nearby pharmacy, or at a local clinic, rather than a centralized facility. Examples of commercially available devices include the Neoteryx Mitra,13 Tasso-M20, SST and Tasso+,14 SeventhSense TAP and TAP II,15 Trajan hemaPEN,16 Labcorp Pixel,17 Capitainer qDBS,1" HemaXis DB10 and DX,19 and Drawbridge OneDraw.20 These devices are capable of collecting from as little as 20 microliters (approximately half a drop) to several hundred microliters of blood and have been widely used to determine clinical parameters,21 drug concentrations,5'22 therapeutic drug monitoring,23 and, more recently, COVID antibody levels.24,25 Some of these devices enable the collection of a fixed volume of blood, collected as dried blood, which can then be shipped and handled at room temperatures-avoiding the need for freezers and dry ice for storing and shipping samples-enabling its adoption even in remote areas with limited infrastructure. Patient-centric blood sampling techniques have been gaining popularity for use in pharmaceutical drug development;however, to date they have not been broadly accessible to the general public.26 This can be partially attributed to the "cliniccentric" healthcare model, where reimbursement is dependent on in-person visits and sample collection. [...]the status quo remains and anyone who needs a blood test is required to go to the doctor's office or clinic. [...]studies have demonstrated that the overall cost to society will be lower, by improving health outcomes and allowing broader access and patient convenience.27 The availability and adoption of patient-centric approaches can provide access and treatment options to clinical trial participants not geographically co-located with the investigative sites and improving access in rural or lesser developed communities, globally, potentially improving the health of the general population.

Investigation of demographic implicit discrimination and disparate impact in chest radiography image-based AI for COVID-19 severity prediction

It is important to evaluate medical imaging artificial intelligence (AI) models for possible implicit discrimination (ability to distinguish between subgroups not related to the specific clinical task of the AI model) and disparate impact (difference in outcome rate between subgroups). We studied potential implicit discrimination and disparate impact of a published deep learning/AI model for the prediction of ICU admission for COVID-19 within 24 hours of imaging. The IRB-approved, HIPAA-compliant dataset contained 8,357 chest radiography exams from February 2020-January 2022 (12% ICU admission within 24 hours) and was separated by patient into training, validation, and test sets (64%, 16%, 20% split). The AI output was evaluated in two demographic categories: sex assigned at birth (subgroups male and female) and self-reported race (subgroups Black/African-American and White). We failed to show statistical evidence that the model could implicitly discriminate between members of subgroups categorized by race based on prediction scores (area under the receiver operating characteristic curve, AUC: median [95% confidence interval, CI]: 0.53 [0.48, 0.57]) but there was some marginal evidence of implicit discrimination between members of subgroups categorized by sex (AUC: 0.54 [0.51, 0.57]). No statistical evidence for disparate impact (DI) was observed between the race subgroups (i.e. the 95% CI of the ratio of the favorable outcome rate between two subgroups included one) for the example operating point of the maximized Youden index but some evidence of disparate impact to the male subgroup based on sex was observed. These results help develop evaluation of implicit discrimination and disparate impact of AI models in the context of decision thresholds © COPYRIGHT SPIE. Downloading of the is permitted for personal use only.

DEBATE ACCELERATES OVER WHO GETS COVID VACCINE FIRST

At the agencies' request, the National Academy of Sciences, Engineering and Medicine iNASEMi has formed a blue-ribbon committee of leading bioethicists, economists, geneticists, and public health authorities to quickly develop a framework for priority vaccine access to assist policymakers in the U.S. and other nations achieve equitable distribution of anticipated vaccines (see: https://bit.ly/33jTCds). Individuals at higher risk will include those in higher age groups, with underlying health conditions, engaged in high-risk occupations, affected by racial and ethnic disparities, and in hardhit geographic locations. State and public health officials are wary of federal pandemic planning efforts so fair given the lack of coordination and effectiveness in distributing COVID-19 test kits and personal protective equipment to healthcare providers and facilities.

CLINICAL TRIAL REFORM

[...]CURES' BILL PROMOTES PANDEMIC PREPAREDNESS Congressional leaders are developing the next version of the 21st Century Cures Act, including provisions to advance research related to the COVID-19 crisis as part of initiatives for bringing innovative therapies to market faster (see https://bit.ly/2SKfA4S). Cures 2.0 continues and updates some of the main themes of the first Cures Act: support development of treatments for rare diseases, patient-focused drug development, diversity in clinical trials, expanded use of digital health systems, increased health literacy, and utilization of real-world data. A public education campaign, moreover, would aim to counter concerns about the safety of vaccines to promote widespread vaccination. Because these treatments are costly and unprofitable for biopharma companies to test and market, the legislation proposes additional financial support for both pre-market studies and post-market production and subsidized higher reimbursement rates for antibiotics that address critical needs.

Predicting Student's Satisfaction towards Hybrid Learning in Informatics

This paper used regression and moderation approaches to evaluate the student's satisfaction with informatics towards the hybrid learning in their study. Multiple Linear Regression (MLR) identified student satisfaction based on hybrid learning difficulty and benefit ($p < 0.001$). Linear Regression (LR) found hybrid learning benefits impacted the student's satis-faction significantly $(p < 0.001$). Student's $t$-test also revealed that Overall Satisfaction (OS) significantly affected hybrid learning's satisfaction ($p < 0.001$). Analysis of Co-variants (ANCOVA) also proved that hybrid learning's benefit ($p < 0.001$) and OS ($p < 0.05$) significantly influenced student satisfaction. The paper also proved that hybrid learning's benefits positively correlate with student satisfaction (0.596). The slopes of 'Yes' and 'No' are substantially different from one another when the probability value of 0.22 $(p > 0.05$). Hence, no moderator (OS) affects the relationship's strength between the benefit and satisfaction of hybrid learning. The paper also revealed that hybrid learning's difficulty has a negative correlation (-.18), and the benefit of hybrid learning is positively associated with student satisfaction (.66). Implementing a hybrid learning mode during Covid-19 periods significantly impacted student satisfaction and the decision taken by the administration was also meaningful. © 2023 IEEE.

Evaluating the Federal Innovative Assessment Demonstration Authority: Early Implementation and Progress of State Efforts to Develop New Statewide Academic Assessments. Evaluation Report. NCEE 2023-004

Education officials have long hoped that the statewide academic assessments most students take each year could be used not only for accountability but also to guide instruction. Congress established the Innovative Assessment Demonstration Authority (IADA) program in 2015 to help address this goal, offering up to seven states temporary flexibility from federal testing requirements so that they may more easily make progress toward replacing their current assessments with more innovative ones. The key incentive to participate in IADA is that students trying out the innovative assessment are not required to also take the state's current assessment. However, states approved for IADA must still show that their innovative assessments meet most requirements for federal accountability, and they are expected to implement the new assessments statewide within 5 years. This report describes the progress of the first five assessment systems approved under IADA in order to help policymakers consider expanding the program to more states. The report is primarily based on an analysis of states' IADA applications and performance reports to the U.S. Department of Education through the 2020-2021 school year and is part of a broader evaluation of IADA required by Congress. [For the Appendix, see ED627873. For the Study Highlights, see ED627880.]

New care settings and innovation will usher diagnostic testing into the future

The article focuses on the future of diagnostic testing in healthcare, highlighting the importance of testing in tracking and treating diseases like COVID-19. It discusses the advancements in diagnostic technology, including combination tests for multiple respiratory diseases and the rise of at-home testing, which will increase access to testing and empower patients to manage their health.

Perception and Practice Towards Hand Hygiene during Pandemic among Patients Visiting OPD in A Private Institution

One of the most significant and well-publicized prevention practises for Covid 19 is hand cleanliness. Face masks and social withdrawal are useless without good hand hygiene. The healthcare professionals can only intervene and raise awareness to enhance the public's hand hygiene practises after they are aware of the public's perceptions of and barriers to hand hygiene. A private dental facility had 150 outpatients participate in this cross-sectional questionnaire survey. Ten questions addressing various facets of hand hygiene and perceived obstacles made up the survey. The information from Google Forms was then imported into SPSS Version 15 using Excel. Data were presented as frequencies and percentages after the chi square test, and a p value of 0.05 or less was regarded as statistically significant.. In our study, 92.62 percent of outpatients at a private facility said that they continue to take measures against COVID19. 83.89% of our patients agreed that good hand hygiene habits are crucial for preventing COVID19. Whereas 38.26% of outpatients claimed to only wash their hands for 30 seconds, 33.56% of outpatients claimed to wash their hands for a full minute. In contrast to the 48.32 percent who said hand sanitizer is best and important for hand hygiene, 51.68 percent of outpatients said soap and water is best and essential for hand hygiene. According to the study's findings, the participants had a reasonable understanding of hand hygiene and its significance. Yet, there is a need for greater awareness of the finishing details on touch surfaces. Thus, it is advised that media-based propaganda and awareness campaigns have a positive impact and should be kept up, with a stronger focus on the finer points. © 2023 IEEE.

Non-trauma uses of viscoelastic hemostatic assays in critical care: A narrative review and primer for pharmacists

Thromboelastography (TEG) and rotational thromboelastometry (ROTEM) are point-of-care viscoelastic tests of whole blood that provide real-time analyses of coagulation. TEG and ROTEM are often used to guide blood product administration in the trauma and surgical settings. These tests are increasingly being explored for their use in other disease states encountered in critically ill patients and in the management of antithrombotic medications. As the medication experts, pharmacists should be familiar with how to interpret and apply viscoelastic tests to disease state and medication management. The purpose of this narrative review is to provide a primer for pharmacists on viscoelastic tests and their interpretation and to explore non-trauma indications for viscoelastic testing in critical care. Literature evaluating the use of TEG and ROTEM for patients with acute and chronic liver disease, ischemic and hemorrhagic stroke, myocardial infarction, cardiac arrest, coronavirus disease 2019, and extracorporeal membrane oxygenation are described. Current applications of viscoelastic tests by pharmacists and potential future roles of critical care pharmacists in expanding the use of viscoelastic tests are summarized.Copyright © 2023 The Authors. JACCP: Journal of the American College of Clinical Pharmacy published by Wiley Periodicals LLC on behalf of Pharmacotherapy Publications, Inc.

Assessing Robustness of a Deep Learning Model for COVID-19 Classification on Chest Radiographs

The COVID-19 pandemic has made a dramatic impact on human life, medical systems, and financial resources. Due to the disease's pervasive nature, many different and interdisciplinary fields of research pivoted to study the disease. For example, deep learning (DL) techniques were employed early to assess patient diagnosis and prognosis from chest radiographs (CXRs) and computed tomography (CT) scans. While the use of artificial intelligence (AI) in the medical sector has displayed promising results, DL may suffer from lack of reproducibility and generalizability. In this study, the robustness of a pre-trained DL model utilizing the DenseNet-121 architecture was evaluated by using a larger collection of CXRs from the same institution that provided the original model with its test and training datasets. The current test set contained a larger span of dates, incorporated different strains of the virus, and included different immunization statuses. Considering differences in these factors, model performance between the original and current test sets was evaluated using area under the receiver operating characteristic curve (ROC AUC) [95% CI]. Statistical comparisons were performed using the Delong, Kolmogorov-Smirnov, and Wilcoxon rank-sum tests. Uniform manifold approximation and projection (UMAP) was used to help visualize whether underlying causes were responsible for differences in performance between test sets. In the task of classifying between COVID-positive and COVID-negative patients, the DL model achieved an AUC of 0.67 [0.65, 0.70], compared with the original performance of 0.76 [0.73, 0.79]. The results of this study suggest that underlying biases or overfitting may hinder performance when generalizing the model. © 2023 SPIE.

Deep-learning models for Covid-19 Detection Using Chest X-Ray Images

Deep Convolutional Neural Networks are a form of neural network that can categorize, recognize, or separate images. The problem of COVID-19 detection has become the world's most complex challenge since 2019. In this research work, Chest X-Ray images are used to detect patients' Covid Positive or Negative with the help of pre-trained models: VGG16, InceptionV3, ResNet50, and InceptionResNetV2. In this paper, 821 samples are used for training, 186 samples for validation, and 184 samples are used for testing. Hybrid model InceptionResNetV2 has achieved overall maximum accuracy of 94.56% with a Recall value of 96% for normal CXR images, and a precision of 95.12% for Covid Positive images. The lowest accuracy was achieved by the ResNet50 model of 92.93% on the testing dataset, and a Recall of 93.93% was achieved for the normal images. Throughout the implementation process, it was discovered that factors like epoch had a considerable impact on the model's accuracy. Consequently, it is advised that the model be trained with a sufficient number of epochs to provide reliable classification results. The study's findings suggest that deep learning models have an excellent potential for correctly identifying the covid positive or covid negative using CXR images. © 2023 IEEE.

The inspiratory activity of respiratory center and respiratory muscles strength after COVID-19.

The respiratory pump that provides pulmonary ventilation includes the respiratory center, peripheral nervous system, chest and respiratory muscles. The aim of this study was to evaluate the activity of the respiratory center and the respiratory muscles strength after COVID-19 (COronaVIrus Disease 2019). Methods. The observational retrospective cross-sectional study included 74 post-COVID-19 patients (56 (76%) men, median age - 48 years). Spirometry, body plethysmography, measurement of lung diffusing capacity (DLCO), maximal inspiratory and expiratory pressures (MIP and MEP), and airway occlusion pressure after 0.1 sec (P0.1) were performed. In addition, dyspnea was assessed in 31 patients using the mMRC scale and muscle strength was assessed in 27 of those patients using MRC Weakness scale. Results. The median time from the COVID-19 onset to pulmonary function tests (PFTs) was 120 days. The total sample was divided into 2 subgroups: 1 - P0.1 <= 0.15 kPa (norm), 2 - > 0.15 kPa. The lung volumes, airway resistance, MIP, and MEP were within normal values in most patients, whereas DLCO was reduced in 59% of cases in both the total sample and the subgroups. Mild dyspnea and a slight decrease in muscle strength were also detected. Statistically significant differences between the subgroups were found in the lung volumes (lower) and airway resistance (higher) in subgroup 2. Correlation analysis revealed moderate negative correlations between P0.1 and ventilation parameters. Conclusion. Measurement of P0.1 is a simple and non-invasive method for assessing pulmonary function. In our study, an increase in P0.1 was detected in 45% of post-COVID-19 cases, possibly due to impaired pulmonary mechanics despite the preserved pulmonary ventilation as well as normal MIP and MEP values.Copyright © Savushkina O.I. et al., 2023.

Assessment of Psychological Needs in an Egyptian Sample of Healthcare Providers during the COVID-19 Pandemic

Objectives: The current study aims to identify the psychosocial needs of frontline Healthcare Workers (HCWs) during the COVID-19 pandemic and investigate the factors contributing to their psychosocial well-being. Methods: We conducted a cross-sectional study using an online survey designed specifically for the aim of this study. Data was collected from 315 frontline healthcare workers during the COVID-19 pandemic. Results: Up to 90 % of the responders reported a range of symptoms related to psychological distress such as worry, insomnia, lack of motivation, negative thoughts, inability to achieve goals, and burnout. Psychological support, religion-based support, communicating with family, and good sleep are among the stress-relieving factors most mentioned by HCWs. The change in work conditions and increased awareness of the need to use different strategies to overcome stress was associated with decreased levels of perceived stress among health care providers. Conclusion: The change in work conditions, the increased awareness of HCWs to their needs, and the use of different strategies to overcome were associated with decreased levels of perceived stress among HCWs. The increased number of working hours per day and younger age of the participants were the only significant independent variables detecting the need for psychological support. This research is a call for designing and implementing tailored needs-based interventions that address the different aspects of HCWs' well-being during public health emergencies. [ FROM AUTHOR] Copyright of Arab Journal of Psychiatry is the property of Arab Federation of Psychiatrists and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

New Sample Prep Products and Accessories for 2023

[...]instrument-based sample preparation technologies are presented. [...]attention is turned to other sample preparation accessories and supporting technologies. First is the Swift HLB-DPX tips. First is the Thermo Scientific AccelerOme sample preparation platform automating sample preparation for liquid chroma-tography-mass spectrometry (LC-MS) proteomics.

Enhanced Role of EMA in EU Crisis Response

The regulation also sets out obligations on marketing authorization holders (MAHs) and medical devices manufacturers, authorized representatives, importers, distributors, and notified bodies duties to: * Provide information that will assist with the monitoring by the MSSG/MDSSG of shortages of medicinal products and devices contained in the critical medicines list and updating this when necessary * Provide a justification for any failure to provide the requested information by the established deadlines * Immediately provide any evidence of an actual or potential shortage of medicinal products or devices * Provide information to EMA by 2 Sep. 2022 that will enable the establishment of a Single Point of Contact (SPOC) network, and the industry Single Point of Contact (iSPOC) network, with mandates to updating this when necessary (7). Enhanced advisory role In addition to the measures designed to address medicinal and medical device shortages, an Emergency Task Force (ETF) will also be established within EMA to provide scientific advice and review evidence on medicines that have the potential to address public health emergencies, offer scientific support to facilitate clinical trials, and support existing EMA committees with their authorization and safety monitoring of medicines (8). According to the document published by EMA on Crisis Preparedness and Management, the key benefits for EMA of having these responsibilities include: * Accelerated evaluation and access to safe and effective medicines which could treat or prevent a disease causing, or likely to cause, a public health emergency * Improved quality of data and the effective use of resources through increased support at EU level towards the conducting of clinical trials in preparation for, and during a public health emergency * Improved coordination and harmonization at EU level in preparation for and during a public health emergency (7).