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1.
BJOG: An International Journal of Obstetrics and Gynaecology ; 129:160-161, 2022.
Article in English | EMBASE | ID: covidwho-1956663

ABSTRACT

Objective: To create, develop and facilitate a group of women and families to shape the work of a national audit of maternity and perinatal care. Design: The National Maternity and Perinatal Audit (NMPA) is a large-scale audit of the NHS maternity services across England, Scotland and Wales which commenced in 2016. Data from each Trust and Board in participating nations are collected, and records of over 550,000 women are included each year, with roughly 90% case ascertainment.Using high quality data, the audit aims to evaluate a range of care processes and outcomes in order to identify good practice and areas for improvement in the care of women and babies. Method: The NMPA Women and Families Involvement Group (WFIG) was created in the early stages of the audit by inviting a broad range of individuals with experience of UK maternity care and relevant stakeholders to form the group. New members are regularly encouraged to ensure that experience is recent and relevant to arising issues. The group takes on a variety of roles offering the perspective of the service user, for example by setting priorities for the audit and contributing commentary or assisting with the accessible design of outputs. Coproduction is an important aspect of the role of the group, building new resources and outputs together with the audit project team. Results: Lay involvement with the NMPA has resulted in the coproduction of a number of accessible report summaries, the 'Family Gateway' -an online resource specifically designed for women and families to facilitate the use of NMPA data, as well as the contribution of qualitative data to NMPA national clinical reports. Engagement with lay groups has increased since the COVID-19 pandemic, with the move to virtual working enabling more frequent meetings, increased virtual communication and an ability to reach groups and individuals from broader geographic regions. Conclusions: Including women and families in service evaluation and national clinical audits provides incredibly valuable insight. Diverse voices contributing to the focus, structure and dissemination of outputs offer an important way of reaching a broad range of stakeholders and ensuring results and publications are accessible.

2.
BJOG: An International Journal of Obstetrics and Gynaecology ; 129:166, 2022.
Article in English | EMBASE | ID: covidwho-1956660

ABSTRACT

Quality Improvement project on postnatal debrief clinic Objective: To evaluate the post-natal debrief clinic service in the Princess of Wales Hospital (Cwm Taf). Design: This project was a service evaluation, which involved the collection of quantitative and qualitative data. The use of multi-modal data was beneficial, as it provided an objective measure of the outcomes of the clinic, whilst also allowing patients to voice their subjective opinions. Additionally, this study design was adopted as it facilitated the measurement of the service without the need for comparison to a universal standard for post-natal debrief, which doesn't exist. Method: Data was manually extracted from clinic letters and quality of the clinic was assessed through patient feedback forms. A total of 84 patient's outcomes and 53 feedback forms were reviewed. The clinic was compared with national guidelines and services. 20 patients' feedback was collected separately to gauge opinions on telephone clinic (introduced since the start of the COVID pandemic) and face-to- face appointments. Patients were interviewed during this research to gain an individual understanding of the challenges posed to women after traumatic birth experiences. Results: Notable risk factors for attending debrief clinic were identified, such as induction of labour and emergency caesarean section. The majority of patients (67%) seen in the debrief clinic were discharged back to GP care and required no further mental health support. Feedback overwhelmingly shows good satisfaction, with patients highlighting the caring and honest staff who provided clear explanations of labour events and reassurance for future pregnancies. Some areas were identified that may require improvement, such as admin support, referrals and waiting times. Many patients noted all mothers should be offered this service. Comparisons indicate that the clinic is exceeding most peer-led services and national guidelines. 60% of patients felt they preferred telephone over face-to- face appointments. Conclusion: Traumatic birth experiences are relatively common. It is vital to review the debrief services available to patients following these experiences. The clinic has been constantly evolving since its inception, to meet the needs of the patients it cares for and will continue to do so in the future. This service evaluation shows the clinic is providing an excellent level of care, however further evaluations needed in future as we recently introduced offering the debrief service to all the postnatal patients.

3.
Journal of Voice ; 2022.
Article in English | ScienceDirect | ID: covidwho-1936901

ABSTRACT

Objectives The COVID-19 pandemic expanded the use of telemedicine, but there is no literature exploring both patient and provider satisfaction specifically in the provision of voice therapy. This study aims to investigate patient and provider satisfaction with virtual voice therapy, its associated factors, and any correlation between the two. Methods Cross-sectional study. Participants included 226 adults who underwent voice therapy delivered via telepractice at the USC Voice Center between April and October 2020. Patients and providers self-reported their level of satisfaction on a visual analog scale (VAS;range 0-100). Patient satisfaction was additionally measured using a previously validated Telemedicine Satisfaction Questionnaire (TSQ;range 1-5), and a binary question about their desire to choose telemedicine over in-person therapy in the future. Three speech-language pathologists rated provider satisfaction for all 226 patients. Patient satisfaction survey was completed by 55 patients. Multivariable linear regression analyses and linear mixed-effects models were used to assess results. Results Patient and provider mean (SD) VAS satisfaction scores were 86.8 (18.6) and 80.6 (19.7), respectively. The mean (SD) TSQ score was 4.4 (0.6). In a multivariable model, patient satisfaction levels were significantly higher for hypofunctional than for hyperfunctional dysphonia diagnoses. Forty-four (73%) patients reported they would prefer telemedicine voice therapy over in-person appointments, which was significantly correlated with internet reliability (p = 0.04). For providers, satisfaction was significantly lower for patients whose diagnosis had changed after initiation of voice therapy (Δ = -16.0 [95% CI: -28.7 to -3.2]) and for encounters with Asian patients compared to White patients (Δ = -11.6 [95% CI: -18.9 to -4.2]). Patient and provider satisfaction scores were weakly correlated (r = 0.19). Conclusions Our findings suggest that virtual voice therapy is not simply an alternative to in-person service, but rather an effective method useful beyond the current pandemic with proper diagnosis and technical support.

4.
Eur Arch Otorhinolaryngol ; 2022 May 06.
Article in English | MEDLINE | ID: covidwho-1941601

ABSTRACT

PURPOSE: Investigating whether the Acoustic Voice Quality Index (AVQI) and the Acoustic Breathiness Index (ABI) are valid and comparable to previous unmasked measurements if the speaker wears a surgical mask or a FFP-2 mask to reduce the risk of transmitting air-borne viruses such as SARS-CoV-2. METHODS: A convenience sample of 31 subjectively healthy participants was subjected to AVQI and ABI voice examination four times: Twice wearing no mask, once with a surgical mask and once with a FFP-2 mask as used regularly in our hospital. The order of the four mask conditions was randomized. The difference in the results between the two recordings without a mask was then compared to the differences between the recordings with each mask and one recording without a mask. RESULTS: Sixty-two percent of the AVQI readings without a mask represented perfectly healthy voices, the largest AVQI without a mask value was 4.0. The mean absolute difference in AVQI was 0.45 between the measurements without masks, 0.48 between no mask and surgical mask and 0.51 between no mask and FFP-2 mask. The results were neither clinically nor statistically significant. For the ABI the resulting absolute differences (in the same order) were 0.48, 0.69 and 0.56, again neither clinically nor statistically different. CONCLUSION: Based on a convenience sample of healthy or only mildly impaired voices wearing CoViD-19 protective masks does not substantially impair the results of either AVQI or ABI results.

5.
Applied Sciences ; 12(13):6470, 2022.
Article in English | ProQuest Central | ID: covidwho-1933958

ABSTRACT

Wavelet transform is a widespread and effective method in seismic waveform analysis and processing. Choosing a suitable wavelet has also aroused many scholars’ research interest and produced many effective strategies. However, with the convenience of seismic data acquisition, the existing wavelet selection methods are unsuitable for the big dataset. Therefore, we proposed a novel wavelet selection method considering the big dataset for seismic signal intelligent processing. The relevance r is calculated using the seismic waveform’s correlation coefficient and variance contribution rate. Then values of r are calculated from all seismic signals in the dataset to form a set. Furthermore, with a mean value μ and variance value σ2 of that set, we define the decomposition stability w as μ/σ2. Then, the wavelet that maximizes w for this dataset is considered to be the optimal wavelet. We applied this method in automatic mining-induced seismic signal classification and automatic seismic P arrival picking. In classification experiments, the mean accuracy is 93.13% using the selected wavelet, 2.22% more accurate than other wavelets generated. Additionally, in the picking experiments, the mean picking error is 0.59 s using the selected wavelet, but is 0.71 s using others. Moreover, the wavelet packet decomposition level does not affect the selection of wavelets. These results indicate that our method can really enhance the intelligent processing of seismic signals.

6.
Indian Journal of Psychological Medicine ; 44(4):399-404, 2022.
Article in English | Academic Search Complete | ID: covidwho-1932967

ABSTRACT

The increased levels of psychological distress in the population and the disruption of traditional mental health services during the COVID-19 pandemic have widened the mental health treatment gap that already existed even prior to the onset of the pandemic.[2] Additionally, there is significant stigma attached to mental-health-treatment seeking, especially in low- and middle-income countries.[3] The culmination of these different factors has provided a fertile ground for the mushrooming of mobile health apps for mental health disorders and wellbeing.[4] People advocating the use of mental health apps (MHapps) often describe the potential of these apps in delivering mental health services discretely to people living in even remote and rural locations, in turn reducing the huge mental health treatment gap. Rapidly increasing smartphone ownership among the majority of the world's population and increasing internet penetration through relatively cheaper mobile data usage plans have led to the development and popularization of various mobile applications (apps).[1] These apps are third-party software apps that utilize mobile and/or other related devices' hardware (e.g., wearable sensors, such as a smartwatch) along with or without internet communication technology and enable users to perform a wide range of different tasks related to varied fields, such as trade, commerce, education, entertainment, or health, through their smartphones. Do mental health mobile apps work: Evidence and recommendations for designing high-efficacy mental health mobile apps. [Extracted from the article] Copyright of Indian Journal of Psychological Medicine is the property of Sage Publications Inc. 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.)

7.
2nd International Conference on Computer, Control and Robotics, ICCCR 2022 ; : 81-85, 2022.
Article in English | Scopus | ID: covidwho-1932090

ABSTRACT

The outbreak of the Covid-19 pandemic has resulted in a surge in the generation of medical waste. Due to the transmissible nature of the Virus and the lack of effort at proper disposal, the safety of the front-line health workers, as well as the disposer, is at risk. Hence, to mitigate the spread of infectious diseases, a system is proposed that uses a robotic arm for segregating medical waste automatically. The robotic arm is operable through voice commands, and the segregating operation could function in automatic and manual mode. The system uses the YOLOv3 (You Only Look Once) algorithm to detect and classify the medical waste and then uses the Robot Operating System (ROS) platform to pick up and drop the waste object into color-coded bins. For this research, the medical waste has been categorized into 4 types, and for each type, a color-coded bin has been used for segregation. Our system has achieved 94% training accuracy for the YOLOv3 model on a custom dataset, whereas the system's overall accuracy in automated mode was 82.1%, derived after 30 trials. In the case of manual mode, an average accuracy of 82.5% has been achieved for the same number of trials. © 2022 IEEE.

8.
1st International Conference on Applied Artificial Intelligence and Computing, ICAAIC 2022 ; : 1086-1090, 2022.
Article in English | Scopus | ID: covidwho-1932086

ABSTRACT

As per recent pandemic situation taken into consideration Corona virus testing is done at the specific center which does not provide safe environment. So there is need of advance system i.e. Contactless Covid Booth Registration system. This system helps to make Covid center automated and contactless which helps to reduce spreading of virus in the Covid testing centers. This system utilizes microcontroller, MATLAB, GSM modem. This system can be useful for all Covid testing centers, hospitals and public health centers. This system having advantages of reduction in spreading rate of virus, Break the chain of virus expansion, reduces patients rate and reduces the risk of infection. This system not only useful for Covid testing centers but help to our nation to minimize the risks of infections and death. © 2022 IEEE.

9.
International Journal of Emerging Markets ; 17(7):1738-1758, 2022.
Article in English | ProQuest Central | ID: covidwho-1932029

ABSTRACT

Purpose>This study defines a three-angled research plan to intensify the knowledge and development undergoing in the retail sector. It proposes a theoretical framework of the customer journey to explain the customers' intent to adopt artificial intelligence (AI) and machine learning (ML) as a protective measure for interaction between the customer and the brand.Design/methodology/approach>This study presents a research agenda from three-dimensional online search, ML and AI algorithms. This paper enhances the readers' understanding by reviewing the literature present in utilizing AI in the customer journey and presenting a theoretical framework.Findings>Using AI tools like Chatbots, Recommenders, Virtual Assistance and Interactive Voice Recognition (IVR) helps create improved brand awareness, better customer relationships marketing and personalized product modification.Originality/value>This study intends to identify a research plan based on investigating customer journey trends in today's changing times with AI incorporation. The research provides a novel model framework of the customer journey by directing customers into different stages and providing different touchpoints in each stage, all supported with AI and ML.

10.
Stud Health Technol Inform ; 290: 919-923, 2022 Jun 06.
Article in English | MEDLINE | ID: covidwho-1933582

ABSTRACT

People with Parkinson's disease (PD) can have dysarthria, a voice disorder that affects speech intelligibility. To fight this disorder people may resort to speech and language therapy. Unfortunately, weekly speech therapy sessions may not be enough, because to achieve and maintain good voice quality, intensive training is required. Additionally, the COVID-19 pandemic brought attention to the need for alternative speech therapy treatments that complement face-to-face appointments. Here, we propose a serious therapy game to improve voice loudness that can be used for intensive therapy or when face-to-face appointments are not possible. The game integrates three voice exercises used in speech therapy sessions for people with PD and aims to provide motivation for patients to perform the exercises on a daily basis. This application evaluates the vocal intensity, vocal frequency and maximum phonation time, offering real-time visual feedback. It also allows pathologists to customize the exercises difficulty to the needs of each patient.


Subject(s)
COVID-19 , Parkinson Disease , Voice , Dysarthria/etiology , Dysarthria/therapy , Humans , Pandemics , Parkinson Disease/complications , Parkinson Disease/therapy , Speech Therapy
11.
7th EAI International Conference on Science and Technologies for Smart Cities, SmartCity360° 2021 ; 442 LNICST:583-601, 2022.
Article in English | Scopus | ID: covidwho-1930338

ABSTRACT

Videoconferencing applications have seen a jump in their userbase owing to the COVID-19 pandemic. The security of these applications has certainly been a hot topic since millions of VoIP users’ data is involved. However, research pertaining to VoIP forensics is still limited to Skype and Zoom. This paper presents a detailed forensic analysis of Microsoft Teams, one of the top 3 videoconferencing applications, in the areas of memory, disk-space and network forensics. Extracted artifacts include critical user data, such as emails, user account information, profile photos, exchanged (including deleted) messages, exchanged text/media files, timestamps and Advanced Encryption Standard encryption keys. The encrypted network traffic is investigated to reconstruct client-server connections involved in a Microsoft Teams meeting with IP addresses, timestamps and digital certificates. The conducted analysis demonstrates that, with strong security mechanisms in place, user data can still be extracted from a client’s desktop. The artifacts also serve as digital evidence in the court of Law, in addition to providing forensic analysts a reference for cases involving Microsoft Teams. © 2022, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

12.
American Journal of Respiratory and Critical Care Medicine ; 205(1), 2022.
Article in English | EMBASE | ID: covidwho-1927839

ABSTRACT

Fungal infection of vocal cord in immunocompetent host is rare and may be missed as the lesion may mimic granulomatous disease, carcinoma, leukoplakia etc. Here we present a case of a healthy male patient. A 77 years old male patient presented to ENT specialist with complaints of hoarseness of voice for last 3 months. The patient was a non-smoker, not immunocompromised or taking immunosuppressive drugs. He was prone to seasonal bouts of cough & cold with sneezing. Video laryngoscopy showed inflamed tonsils and congested vallecula & epiglottis. Both vocal cords showed proliferative mass, white keratotic patch in anterior & middle third portion with restricted movement. Tissue samples from both vocal cords was sent for histopathology (HP). Slide examination revealed necrotic exudate containing broad based aseptate fungal hyphae and a provisional diagnosis of vocal cord fungal infection favoring Mucor mycosis was made. Patient was started on Itraconazole 100 mg twice daily along with treatment for patient's allergic condition. The slides and tissue sample obtained by direct laryngoscopy were sent to a different lab for reconfirmation. Further HP examination showed necrotic exudate and fibrin deposits with abundant fungal spores & hyphae. Grocott methenamine silver (GMS) stain & Periodic acid-Schiff (PAS) staining showed fungal spores and branching septate fungal hyphae confirming a diagnosis of vocal cord aspergillosis. His routine blood tests, serology, ECG reports were normal. RTPCR (Reverse Transcriptase Polymerase Chain Reaction) for SARS-CoV-2 was negative. After final diagnosis, patient was referred to pulmonologist to exclude pulmonary aspergillosis. Medication was changed to Voriconazole 200 mg twice daily along with antileukotrienes & antihistamines for his seasonal allergies. Patient was asked to follow up with CT chest to exclude pulmonary aspergillosis. The CT chest did not show any chest pathology. His voice was normal and other physical examinations were within normal limit. He was prescribed Voriconazole 200 mg twice daily for 3 months along with antihistamines, antileukotrienes, proton pump inhibitors & cough syrup. He was advised to come for follow up with liver function test after 4 weeks. Primary fungal infection of vocal cords is rare. Fungal infection is common in immunocompromised host but to detect such cases in healthy immunocompetent patient requires high level of suspicion and usually oral antifungal therapy for 3-4 weeks results in complete resolution of symptoms & lesion as per the current literature. (Figure Presented).

13.
Human Resource Development International ; : 14, 2022.
Article in English | Web of Science | ID: covidwho-1927211

ABSTRACT

Today's uncertain times have led to paradigm shifts in the world of work. The disruptive nature of unforeseen events (e.g. Covid-1 9) has a harsh impact on organizations' stakeholders, including employees, society and the environment. However, these events pose tougher challenges for vulnerable and weaker workers, particularly in getting access to decent and productive employment. While catering to the changing needs of business, organizations also find it difficult to provide decent work for all and achieve their social bottom lines. This paper aims to understand what role HRD plays, especially Sustainable HRD (S-HRD), in facilitating access to decent work. Conceptual analysis of the literature revealed that S-HRD practices have the potential to promote all the dimensions of DW: employment creation, social protection, employees' fundamental rights and social dialogue. This paper is an important stepping stone in the articulation of how S-HRD can help organizations to promote decent work. The perspectives presented in this study have potential implications for HRD practitioners in understanding the application and implementation of S-HRD practices. Furthermore, managers can also take note of specific S-HRD interventions from this paper to enable decent work in their organizations.

14.
Value in Health ; 25(7):S552, 2022.
Article in English | EMBASE | ID: covidwho-1926735

ABSTRACT

Objectives: There is often an assumption that remote monitoring is challenging to implement among individuals with schizophrenia, due to symptoms such as paranoia and suspicion of technology, however the promise of digital approaches for passive and real-time data collection has recently been emphasized as a result of the COVID-19 pandemic and increased need for digitally-enabled approaches to care and research. This research describes the use of a mHealth app by a self-selected population of users with Schizophrenia to assess the feasibility of using mobile apps for remote monitoring and research. Methods: Data from Health Storylines users between 2016-2021 who self-identified as being diagnosed with Schizophrenia is described. Data includes quantitative tracking and free text journal entries from tools designed to support the self-management of a variety of health conditions, including Schizophrenia. Results: 5,012 app users reported Schizophrenia as a diagnosed condition, all of whom reported having additional comorbidities with 70% reporting two comorbid conditions. The most frequently reported comorbidities are Anxiety disorder, Depression, Bipolar Disorder and ADD/ADHD. The three most commonly used tools were the Medication Tracker, Symptom Tracker, and Daily Moods. The most commonly reported symptoms were Hallucinations, Paranoid behavior, Hearing voices, Anxiety, Depressed mood and Delusions. Among the qualitative data, several broad themes were consistently the most frequently reported across the duration of the time period examined: Psychosocial impact of the condition, Quality of life, and Experience of the condition. Conclusions: This descriptive analysis of patient engagement with the Health Storylines app reveals that many people with Schizophrenia are willing and able to engage in mobile health technology for the purpose of self-monitoring, engagement, and research. Further research is required to understand the degree of representation of the full spectrum of patients’ experience with Schizophrenia, and the role of patient engagement in completeness and quality of data collected using mobile health apps.

15.
J Voice ; 2022 Jul 12.
Article in English | MEDLINE | ID: covidwho-1926740

ABSTRACT

OBJECTIVES: The COVID-19 pandemic has affected the voice assessment protocols for dysphonic patients. In this study, we compared the changes in acoustic measures of the healthy population as well as dysphonic patients due to glottic insufficiency between the pandemic period requiring face masks and the prepandemic period when the masks were not essential. The clinical reliability of the acoustic measures with and without face masks was explored. METHODS: A total of 120 patients (age = 42.3 ± 11.9 yrs) with glottic insufficiencies such as UVFP and sulcus vocalis and 40 healthy population (age = 40.5 ± 11.2 yrs) cohorts were enrolled during the pandemic period. Age- and gender-matched 120 patients and 40 healthy population cohorts who underwent voice assessment without face masks before the pandemic were enrolled as prepandemic controls. Acoustic measures and overall severity estimates of vowel and speech samples were compared, which included cepstral peak prominence (CPP), L/H spectral ratio (SR), their standard deviations, F0, jitter percent (Jitt), shimmer percent (Shim), noise-to-harmonic ratio (NHR), Cepstral Spectral Index of Dysphonia (CSID), and Acoustic Psychometric Severity Index of Dysphonia. RESULTS: Both patients and healthy cohorts showed higher SRv and SRs but lower CSIDv during the pandemic compared to the prepandemic period. F0 of the healthy male controls during the pandemic was higher than during the prepandemic periods, while the CSIDs was lower for the pandemic period. The pandemic patient cohort showed lower σSRs compared to the prepandemic patient cohort. When the acoustic measures of patients were compared to the healthy population cohort, the patient cohort showed lower CPP and σCPPs, while higher σCPPv, Jitt, Shim, and NHR during both pandemic and prepandemic period. Overall, the area under the curve of the acoustic measures and overall severity estimates was similar between the mask and non-mask groups, although the AUC of the SR measures was poor. CONCLUSIONS: Wearing face masks during the pandemic did not compromise the overall reliability of the acoustic analysis in patients with glottic insufficiency, suggesting the current protocol of acoustic analysis can be carried out reliably while wearing a mask to ensure safety in the pandemic era.

16.
Neurology ; 98(18 SUPPL), 2022.
Article in English | EMBASE | ID: covidwho-1925558

ABSTRACT

Objective: To explore triple overlap syndrome and immune effects of COVID-19 vaccination. Background: Neurologic immune related adverse events (nIRAE) are potential complications of Immune Checkpoint Inhibitors (ICI). nIRAE of the Peripheral Nervous System (PNS) can present fulminantly, especially myositis, myasthenia gravis (MG), and overlap syndrome of myositis, MG, and myocarditis. Design/Methods: NA Results: 77-year old male with metastatic melanoma presented to hospital with leg weakness, hoarseness, dyspnea, and ptosis 1 week after first cycle of ipilimumab and nivolumab and 3 days after COVID-19 vaccine. He had bradycardia with heart block, and hepatorenal failure. Exam was remarkable for dysarthria, right eye ptosis, hip flexion weakness 4+/5, without fatigability. Labs showed CK 21,325, Troponin-T 4,888, Aldolase 307, AChR antibody positive, and AntiStriated Muscle Antibody 1:3840. Vital Capacity (VC) was 1.9L and Negative Inspiratory Force (NIF) -20cmH2O. Patient received BiPAP, plasmapheresis, and methylprednisolone 1000mg. After this, he developed fatigability of ocular muscles, voice, and proximal arms;VC dropped to 1.3L. He was diagnosed with triple overlap syndrome, but MG manifested after receiving first dose of high-dose steroids. Heart biopsy showed lymphohystiocytic inflammation. Muscle biopsy showed focal and dispersed lymphomononuclear cell endomysial infiltration. Electromyography demonstrated patchy myositis in lower extremities. Patient completed 3 days of high-dose steroids, 5 days of plasmapheresis, abatacept, and rituximab, followed by slow steroid taper. He did not require intubation despite tenuous respiratory status. Conclusions: nIRAE of the PNS are rare potential complications of immunotherapy, usually presenting by 6 weeks, although overlap syndrome can present hyper-acutely after 1 dose. Our patient presented 1 week after first treatment, perhaps influenced by COVID vaccine. Management of nIRAE is consensus-based, as no standard evidence-based treatment exists. Our patient was successfully treated with plasmapheresis prior to high-dose steroids (obviating steroid-induced myasthenic crisis), abatacept and rituximab. The myasthenic crisis was successfully managed with BiPAP, avoiding intubation, and he ultimately improved.

17.
Scientific and Technical Journal of Information Technologies, Mechanics and Optics ; 22(3):415-432, 2022.
Article in Russian | Scopus | ID: covidwho-1924785

ABSTRACT

In the modern world, wearing masks, respirators and facial clothes is very popular. The novel coronavirus pandemic that began in 2019 has also significantly increased the applicability of masks in public places. The most affective person recognition methods are identification by face image and voice recording. However, person recognition systems are facing new challenges due to masks covering most of the subject’s face. Existence of new problems for intelligent systems determines the relevance of masked person recognition systems research, therefore the subject of the study is the systems and datasets for masked people recognition. The article discusses analysis of the main approaches to masked people identity recognition: masked face recognition, masked voice recognition and audiovisual methods. In addition, this article includes comparative analysis of images and recordings datasets required for person recognition systems. The results of the study showed that among the methods that use face images the most effective are methods based on convolutional neural networks and the mask area feature extraction. The methods of x-vector analysis showed a slight drop in efficiency which allows us to conclude that they are applicable in the tasks of recognizing the identity of a speaker in a mask. Results of this study help with formulation of requirements for perspective masked person recognition systems and determining directions for further research. © 2022, ITMO University. All rights reserved.

18.
8th International Conference on Advanced Computing and Communication Systems, ICACCS 2022 ; : 1649-1653, 2022.
Article in English | Scopus | ID: covidwho-1922647

ABSTRACT

Coronavirus flare-up chances human existence and it challenges the general wellbeing. Hand cleanliness, an extremely basic activity, is very much acknowledged to be one of the essential methods of decreasing medical care-related disease and of improving patient security. These days wearing masks, utilizing hand sanitizers, checking temperatures are being done in all places, and so forth yet at the same time in many spots individuals utilize conventional sanitizer gadgets which build the spread of microorganisms. Normally an individual is in charge of observing the body temperature and sanitizer level by taking a chance with his life. This survey Internet of Things (IoT) based hand sanitizer dispenser with temperature and level monitoring distinguishes the presence of the people and gives out alerts in form of the human voice to sanitize their hands if the dispenser goes unrecognized. Furthermore, we have a contactless sanitizer dispenser to stay away from contact among humans and dispensers which will keep us away from the further spread of infection and microorganisms. © 2022 IEEE.

19.
18th IEEE International Colloquium on Signal Processing and Applications, CSPA 2022 ; : 353-358, 2022.
Article in English | Scopus | ID: covidwho-1922613

ABSTRACT

Coronavirus disease, more famously known as COVID-19, was first discovered in Wuhan, China;it was declared a global pandemic by WHO in March 2020. Due to the threatening characteristics of the virus, certain precautions had to be imposed by the government and health authorities to put the situation under control. To mitigate the further transmission of the virus, the "New Normal"was introduced to the public. This is by practicing the minimum safety protocols: wearing a facemask, frequently washing hands, and observing physical distancing. This study aims to build an autonomous robot that can monitor physical distancing, specifically focusing on people's queues. The robot utilizes the YOLOV4 Algorithm to detect the individuals and determine their Euclidean distance to determine if these people are observing the distance safety protocol that is 1.5 meters apart. The robot also includes a voice alarm that apprehends violators and reminds them to follow the practice. Moreover, the robot has an additional feature of detecting the body temperature of the people detected by the program. In assessing the robot's program, the implemented object detection achieved an accuracy of 93%, a precision of 87.5%, an error rate of 7%, and a recall of 94.6%. Moreover, by determining the constraint distance of the robot, which is 3.5 meters, the physical distancing program obtained a percent error of 4.26%. © 2022 IEEE.

20.
Asia - Pacific Journal of Business Administration ; 14(3):362-379, 2022.
Article in English | ProQuest Central | ID: covidwho-1922457

ABSTRACT

Purpose>The world is witnessing enormous changes due to the outbreak of the COVID-19 epidemic. One of the unkind changes is the increased downsizing and layoffs, which has led to a situation of job insecurity. Moreover, due to the unavailability of a cure for the pandemic, the businesses have started their operations with added safety measures that demand a high level of employee safety behavior. But how job insecurity and safety voice may stay in one sheath is an area that requires attention. Hence, this study investigates the impact of job insecurity on employees' safety voice behavior in a COVID-19 outbreak, through serial mediation mechanisms of organizational support and trust.Design/methodology/approach>Data has been collected through a structured questionnaire from the sample (N = 213) of employees of service organizations.Findings>Findings of the study reveal that job insecurity is not directly linked with safety voice behavior, and therefore full mediation through perceived organizational support and trust is supported is proved.Originality/value>This study covers the investigation of job insecurity, during pandemic COVID-19, and its effects on safety voice. It also explains the mechanism between the variables of interest through perceived organizational support and trust in the organization. The study is a timely contribution to the existing literature and offers both theoretical and managerial implications.

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