Miracle-dz/UniFAR-FTUs huggingface dataset:
Real-Time Adaptation of an Artificial Neural Network for Transfemoral Amputees Using a Powered Prosthesis

Objective: We evaluated a two-step method to improve control accuracy for a powered prosthetic leg using machine learning and adaptation, while reducing subject training time. Methods: First, information from three transfemoral amputees was grouped together, to create a baseline control system that was subsequently tested using data from a fourth subject (user-independent classification). Second, online adaptation was investigated, whereby the fourth subject’s data were used to improve the baseline control system in real-time. Results were compared for user-independent classification and for user-dependent classification (data collected from and tested in the same subject), with and without adaptation. Results: The combination of a user-independent classifier with real-time adaptation based on a unique individual’s data produced a classification error rate as low as 1.61% [0.15 standard error of the mean (SEM)] without requiring collection of initial training data from that individual. Training/testing using a subject’s own data (user-dependent classification), combined with adaptation, resulted in a classification error rate of 0.9% [0.12 SEM], which was not significantly different (P $>$ 0.05) but required, on average, an additional 7.52 hours [0.92 SEM] of training sessions. Conclusion and Significance: We found that the combination of a user-independent dataset with adaptation resulted in error rates that were not significantly different from using a user-dependent dataset. Furthermore, this method eliminated the need for individual training sessions, saving many hours of data collection time.
Development of health literacy in persons and caregivers living with dementia: A qualitative directed content analysis

Background Persons living with dementia and their caregivers need health information to understand and manage daily life. Previous studies focused on the associations of health literacy and cognitive impairment with less exploring if and how individuals develop health literacy during the course of the disease. Purpose This descriptive qualitative study aimed to explore the development of health literacy competencies among persons living with dementia and their caregivers. Methods Directed content analysis of six focus groups conducted in the community setting (15 persons living with dementia and 28 caregivers) was completed, using predetermined categories from the Integrated Model of Health Literacy: access, understand, appraise, and apply health information. Findings Participants described developing health literacy competencies over time, moving from a dependence on health care providers to becoming their own experts. Although health care providers were involved in the diagnosis and medication management, most participants admitted that they provided very little information on how to manage their daily life with dementia and often failed to inform them of community resources. Conclusion Participants seemed to find dementia resources on their own for both education and support, often stumbling upon them by accident. Health care providers should promote the health literacy competencies of their patients and caregivers by more intentionally providing dementia health and community resource information.
The ultrastructure of spermatogenic cells and morphological evaluation of testicular development in the silver pomfret (Pampus argenteus)

The silver pomfret (Pampus argenteus) is a widely distributed and economically important marine fish in the Indo‐Pacific. In this study, we acquired the second generation of wild P. argenteus by artificial breeding and further studied the testicular development and ultrastructure of spermatogenesis. The results of gonadosomatic index (GSI) showed the spawning period of this marine fish was from April to June. Besides, through morphological analysis, we found that P. argenteus had an anastomosing tubular testis surrounded by a layer of tunica albuginea, in which spermatogenesis occurred in cysts where the synchronous germ cells were completely surrounded by the cytoplasmic projection of Sertoli cells. Meanwhile, based on submicroscopic characteristics, the germ cells are classified into nine different types. During the ontogenesis of testis, both the early stage of spermatogenesis and sperm were observed in P. argenteus. At sperm maturation stage, different types of spermatozoa and activation of sperms occurred non‐synchronously in the tubules. Cytoplasmic bridges also were observed among synchronous germ cells within the cysts, suggesting an interrelated and differentiated relationship among these germ cells.
Systematic review of productivity loss among healthcare workers due to Covid‐19

Abstract Objective To assess existing evidence on the effects of COVID‐19 on healthcare workers (HCWs) using the health‐related productivity loss approach. Methods A systematic search of online databases including PubMed, Scopus, Ovid, Web of Science, and EMBASE was conducted up to 25 August 2020. Following two screening stages, studies related to the effects of COVID‐19 on healthcare workers were included in the study. Results 82 studies were included in the analysis. The COVID‐19 related death rate among HCWs ranged from 0.00‐0.7%, while the positive test incidence varied between 0.00 and 24.4%. 39 evidences assessed psychological disorders. A wide range of psychological disorders observed among HCWs: 5.2 to 71.2% in anxiety, 1.00 to 88.3% in stress, 8.27 to 61.67% in insomnia, and 4.5 to 50.4% in depression. Conclusions The early evidence suggests that healthcare workers are one of the most vulnerable groups when it comes to positive COVID‐19 infection, mortality, and mental illness.
Classification of amyotrophic lateral sclerosis by brain volume, connectivity, and network dynamics

Emerging studies corroborate the importance of neuroimaging biomarkers and machine learning to improve diagnostic classification of amyotrophic lateral sclerosis (ALS). While most studies focus on structural data, recent studies assessing functional connectivity between brain regions by linear methods highlight the role of brain function. These studies have yet to be combined with brain structure and nonlinear functional features. We investigate the role of linear and nonlinear functional brain features, and the benefit of combining brain structure and function for ALS classification. ALS patients (N = 97) and healthy controls (N = 59) underwent structural and functional resting state magnetic resonance imaging. Based on key hubs of resting state networks, we defined three feature sets comprising brain volume, resting state functional connectivity (rsFC), as well as (nonlinear) resting state dynamics assessed via recurrent neural networks. Unimodal and multimodal random forest classifiers were built to classify ALS. Out‐of‐sample prediction errors were assessed via five‐fold cross‐validation. Unimodal classifiers achieved a classification accuracy of 56.35–61.66%. Multimodal classifiers outperformed unimodal classifiers achieving accuracies of 62.85–66.82%. Evaluating the ranking of individual features' importance scores across all classifiers revealed that rsFC features were most dominant in classification. While univariate analyses revealed reduced rsFC in ALS patients, functional features more generally indicated deficits in information integration across resting state brain networks in ALS. The present work undermines that combining brain structure and function provides an additional benefit to diagnostic classification, as indicated by multimodal classifiers, while emphasizing the importance of capturing both linear and nonlinear functional brain properties to identify discriminative biomarkers of ALS.
The Prevalence of Helicobacter Pylori Infection in Patients with Chronic Kidney Disease Undergoing Hemodialysis

Abstract The aim of this study was to analyze the prevalence of Helicobacter pylori infection and gastroduodenal lesions in Montenegrin patients with chronic kidney disease on hemodialysis. The study included 55 hemodialysis patients with dyspeptic symptoms and 50 control subjects with normal kidney function who had also dyspepsia. After dyspepsia assessment by an interview, all subjects underwent gastroduodenoscopy and histopathological analysis of biopsy specimens, taken from the corpus and antrum of the stomach. Helicobacter pylori was confirmed in 50.9% of corpus mucosa i.e. 60.6% of antrum mucosa of maintenance hemodialysis patients. There were no significantly differences in endoscopic findings of the stomach and bacterial presence between the two study groups of participants (p = 0.451), while duodenal lesions were prevalent in control subjects (p < 0.001). The atrophy of corpus mucosa was more common in hemodialysis patients (p = 0.007), especially in those who have been on hemodialysis for a longer time (p < 0.001) and had lower pH (p = 0.011). The prevalence of Helicobacter pylori infection shown an inverse relationship with dialysis duration. Contrary, a positive relationship between Helicobacter pylori and the concentration of bicarbonate was demonstrated (p = 0.031). The prevalence of Helicobacter pylori and atrophic mucosal changes in Montenegrin hemodialysis patients depends on dialysis duration and acid-base balance.
Description and evaluation of a pathway for unaccompanied asylum-seeking children

Objective (1) To describe a novel integrated pathway for unaccompanied asylum-seeking children (UASC). (2) To evaluate a population engaged with this service. Design Description of the integrated pathway (objective 1) and retrospective evaluation, using data from community paediatrics, infectious diseases (IDs) screening and a sexual health (SH) service (objective 2). Setting Unlinked data were collected from three services across three National Health Service (NHS) trusts in London. Patients All Camden UASC engaged with the service from 01 January 2016 to 30 March 2019. Interventions A multidisciplinary approach prioritising the health needs of UASC including a childre and adolescent mental health service (CAMHS) clinican and a health improvement practitioner. There are low thresholds for onward referral and universal asymptomatic screening of UASC for ID. Main outcome measures Data on demographics, unmet health needs and known outcomes. Results Data were available for 101 UASC, 16% female, median age 16 years (range 14–17). Physical assault/abuse was reported in 67% and 13% disclosed sexual assault/abuse, including 38% of female UASC. Mental health symptoms were documented in 77%. IDs warranting treatment were identified in 41% including latent tuberculosis (25%) and schistosomiasis (13%). Interpreters were required for 97% and initial non-attendance rates at follow-up were 40% (ID) and 49% (SH). Conclusions These data demonstrate high rates of historical physical and sexual assault/abuse, unmet physical, mental and emotional health needs among UASC and significant barriers to engaging with services. An integrated pathway has been successfully implemented and shown to deliver appropriate, joined-up care for UASC, consistent with current recommendations, with the potential to improve outcomes. A study in a clinic for unaccompanied asylum seeking children (UASC) in a single London borough demonstrates a high level of variable needs and pathology. Many of the children had endured physical and sexual abuse and torture. An integrated multidisciplinary pathway is proposed.
Incidence and Types of WPV Affecting Nurses

BACKGROUND: Workplace violence (WPV) is a serious phenomenon affecting nurses in clinical settings around the globe. Like nurses, nursing students are at risk of encountering incidents of WPV, which may lead to negative consequences. WPV training programs are useful in helping nurses and nursing students prevent and manage incidents of WPV. Despite this evidence, the development and implementation of WPV training programs for nursing students pursuing their nursing training in university settings are scarce. AIMS: The purpose of this literature review was to identify and synthesize the evidence about new training programs on prevention and management of WPV implemented exclusively for undergraduate and graduate nursing students published during the years 2012 to 2018. METHOD: The literature review utilized five major databases to identify relevant articles containing WPV training programs implemented in university settings to train undergraduate and graduate nursing students. Appraisal of the evidence was conducted using the Mixed Methods Appraisal Tool. RESULTS: Nine articles included WPV training programs imparted to nursing students in university settings. Overall, nursing students increased their knowledge about WPV and learned practical skills that could be helpful in preventing and managing WPV incidents. WPV training programs were positively accepted by nursing students. CONCLUSIONS: WPV training programs for nursing students should be mandated in all nursing schools. These trainings are vital in equipping them with proper knowledge and practical skills that could be used to prevent and manage incidents of WPV.
Optimized Microbial Recombinant Production of HIV-1 Anti-Envelope Antibody Fragments with Applications to Single Particle Tracking of Virus Assembly

In my findings, I have established a set series of protocols to recombinantly produce, purify and apply various fluorescent probes in vitro for the fluorescent labeling and study of the human immunodeficiency virus type 1 (HIV-1) envelope (Env) protein during HIV viral assembly. There remains insufficient knowledge about the molecular dynamics and interactions of HIV-1 Env protein with its counterpart, Gag, on the inner host cell surface during assembly of a mature virus particle. There also remains an insufficient amount of data for the understanding and clarification of the mechanism of action of a known host cell HIV-1 restriction factor, Serinc5 (SER 5), which is believed to have correlation with Env in fusion events. Using superresolution microscopy to measure and track host–pathogen interfaces that occur on a scale below the resolution limit of the light microscope is becoming increasingly popular. I have used total internal reflection microscopy (TIRF) and Photoactivated Localization Microscopy (PALM) to depict sites of molecular assembly via Env and Gag colocalization as well as measure and track other means of Env such as diffusion rates and host cell restriction factor interactions. Overall, my findings have provided improved strategies and tools for the use in fluorescently labeling and tracking HIV-1 Env and an HIV-1 host cell restriction factor known as SER 5. Superresolution microscopy and single particle tracking can be achieved provided high specificity, brightness and purity while maintaining low KDs. The production and data of these probes are imperative for both understanding the pathological processes of HIV-1 assembly and other stages of the HIV-1 life cycle as well as the various protein-protein interactions.
Stabilometric assessment of vestibular function in children with a medium otitis

Otitis media is one of the most common infectious diseases of the middle ear in preschool age, but its relationship with vestibular dysfunction remains controversial. The aim of the study was to carry out a comparative analysis of stabilometric indicators of preschool children with suppurative and non-suppurative otitis media. Materials and methods: 22 children with suppurative otitis media and 22 children with non-suppurative otitis media at the age from 4 to 7 years were examined by the method of static stabilometry on the device “MPFI Stabilograph 1” (LLC "ASTER IT", Kharkov, Ukraine). We took into account the indices of variation and distribution of the center of pressure, spectral and correlation indices of the stabilogram, as well as integral indices of stability (length, velocity and angle of postural oscillations) and the quality of the balance function in two sensory states (open and closed eyes), which were calculated in the software providing StabiliS. Results. In children with non-suppurative otitis media, the coordinates of the center-of-pressure corresponded (7.04 [2.16–10.09]; -1.14 [-28.90–9.11]), and with suppurative otitis media – (7.04 [3.30–16.16]; -13.72 [(-25.17)–(-10.30)]) with closed eyes. The averaged figure of the projection of the center-of-pressure in the test with eyes closed is actually represented by a circle in both groups, but with open eyes it is represented by an ellipse, which, in case of non-suppurative otitis media, is stretched along the sagittal axis, and in case of suppurative otitis media, along the frontal axis. In both sensory states, children with non-suppurative otitis media were characterized by large (p≤0.05) values of KurtosisX, Length and lower (p≤0.05) values of CC0X, Pup2Sigma compared with non-purulent otitis media. Conclusions: In preschool age, suppurative otitis media more significantly disrupts the balance function compared with non-suppurative otitis media, which was manifested by a significant decrease in the stability of the main stance and the predictability of oscillatory movements compared with non-suppurative otitis media
Non-Volatile Memory Accelerated Geometric Multi-Scale Resolution Analysis

Dimensionality reduction algorithms are standard tools in a researcher’s toolbox. Dimensionality reduction algorithms are frequently used to augment downstream tasks such as machine learning, data science, and also are exploratory methods for understanding complex phenomena. For instance, dimensionality reduction is commonly used in Biology as well as Neuroscience to understand data collected from biological subjects. However, dimensionality reduction techniques are limited by the von-Neumann architectures that they execute on. Specifically, data intensive algorithms such as dimensionality reduction techniques often require fast, high capacity, persistent memory which historically hardware has been unable to provide at the same time. In this paper, we present a re-implementation of an existing dimensionality reduction technique called Geometric Multi-Scale Resolution Analysis (GMRA) which has been accelerated via novel persistent memory technology called Memory Centric Active Storage (MCAS). Our implementation uses a specialized version of MCAS called PyMM that provides native support for Python datatypes including NumPy arrays and PyTorch tensors. We compare our PyMM implementation against a DRAM implementation, and show that when data fits in DRAM, PyMM offers competitive runtimes. When data does not fit in DRAM, our PyMM implementation is still able to process the data.
Consumers’ Intention to Use Mobile Payment: A Case of Quick Response (QR) Code Applications

Many transactions, nowadays such as banking, transportations, online shopping and bills payments, are implemented using mobile payment. To date, many mobile payment services are available in Malaysia, with companies offering their services competitively. However, adoption rates in Malaysia are considered slow due to many reasons. This study investigates the factors that affect consumer intention to use mobile payment based on QR code technology. A proposed model based on the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) model was adapted to identify the factors that affect the use of mobile payments. A survey instrument was developed based on the proposed model. Data were collected from 50 consumers who used QR code mobile payments in Klang Valley. The quantitative analysis method was adopted and the SPSS statistical tool was used to analyze the data using both descriptive and inferential statistics. Results have shown that several factors significantly affect consumer intention to use QR code-based payment namely performance expectancy, effort expectancy, hedonic motivation, habit, and trust. This study provides meaningful insight on the reasons why consumers used QR codebased payment.
Intensive Care Nurses’ Knowledge, Attitude, and Practice of Pressure Injury Prevention in China: A Cross-Sectional Study

Background Pressure injury (PI) remains a critical health issue worldwide. The global incidence of hospital-acquired PI is 8.4%, and among intensive-care unit (ICU) patients, it is even higher, ranging from 6.60% to 36.80%. It is important to investigate ICU nurses’ PI prevention knowledge, attitudes, and practices (KAP). Aim The aim of this study was to describe the level of Chinese ICU nurses’ knowledge, attitudes, and self-reported practices of PI prevention. Materials and Methods From March 31 to April 30, 2019, we recruited a total of 510 ICU nurses into the current study using convenience sampling. The Modified Pressure Ulcer Knowledge Assessment Tool version 2.0, Attitudes toward Pressure Ulcer Prevention instrument, and Questionnaire to evaluate nurses’ Adherence to Recommendations for Preventing Pressure Ulcers were used for data collection. We used one-way analysis of variance, Student’s t-test, and the Mann–Whitney U-test to assess differences in knowledge, attitudes, and self-reported practices of PI prevention among ICU nurses, whom we categorized by their demographic characteristics. Results Mean scores of participants’ knowledge, attitude, and their self-report practice were 65.82 ± 9.29, 76.65 ± 8.62, and 83.35 ± 13.55, respectively. Participants with bachelor’s degrees or higher, who worked in tertiary hospitals, and who had received training on PI prevention over the last year had higher scored on PI prevention knowledge (all P < 0.05). Participants who had received training on PI prevention over the last year scored higher on attitude than those who had not received such training over the last year (P = 0.001). Conclusion ICU nurses surveyed in this study did not demonstrate an acceptable level of knowledge about PI prevention, while their attitudes and self-reported practices were acceptable. Continuing education or in-service training should be provided to enhance ICU nurses’ knowledge of PI prevention.
Automatic Detection Of COVID-19 Using Convolutional Neural Networks And X-Ray Images

The Covid-19 first occurred in Wuhan, China, in December 2019. After that, the virus spread all around the world. The usage of sophisticated artificial intelligence technology (AI) and the radiological images of COVID-19 cases can provide experts with auxiliary diagnosis suggestions, reducing the burden of experts to a certain amount and speeding up the diagnostic process. In this study, transfer learning methods have been implemented, with six pre-trained deep convolutional neural networks models: VGG16, ResNet50, InceptionV3, InceptionResNetV2, MobileNet, and EfficientNetB0 on a dataset of chest X-ray images of patients with COVID-19 disease, viral pneumonia, and normal cases. Transfer learning is an ambitious task, and it results in impressive outcomes for identifying distinct patterns in tiny datasets of medical images. The experimental results show that MobileNet pre-trained model achieved a relatively ideal effect, and the diagnostic accuracy reached 96.05% outperforming all other models.