Rapid learning system

Metal organic frameworks (MOFs) are crystalline, three-dimensional structures with high surface areas and tunable porosities. Made from metal nodes connected by organic linkers, the exact properties of a given MOF are determined by node and linker choice. MOFs hold promise for numerous applications, including gas capture and storage. M2(4,4'-dioxidobiphenyl-3,3'-dicarboxylate)-henceforth simply M2(dobpdc), with M = Mg, Mn, Fe, Co, Ni, Cu, or Zn-is regarded as one of the most promising structures for CO2 capture applications...

OBJECTIVE: Osteoporosis is a systemic bone disease characterized by low bone mass, damaged bone microstructure, increased bone fragility, and susceptibility to fractures. With the rapid development of artificial intelligence, a series of studies have reported deep learning applications in the screening and diagnosis of osteoporosis. The aim of this review was to summary the application of deep learning methods in the radiologic diagnosis of osteoporosis. METHODS: We conducted a two-step literature search using the PubMed and Web of Science databases...

Despite global recommendations that surveillance systems should capture malaria case data from both private and public sectors, the integration of private sector data into national systems remains a challenge for national malaria programs in high-burden settings. The WHO's Malaria Surveillance, Monitoring & Evaluation: A Reference Manual suggests eight general guidelines for conducting private sector surveillance. Practical operational guidance is needed to implement private sector surveillance and service delivery interventions...

Soil, particularly in agricultural regions, has been recognized as one of the significant reservoirs for the emerging contaminant of MPs. Therefore, developing a rapid and efficient method is critical for their identification in soil. Here, we coupled HSI systems [i.e., VNIR (400-1000 nm), InGaAs (800-1600 nm), and MCT (1000-2500 nm)] with machine learning algorithms to distinguish soils spiked with white PE and PA (average size of 50 and 300 µm, respectively). The soil-normalized SWIR spectra unveiled significant spectral differences not only between control soil and pure MPs (i...

PURPOSE OF REVIEW: Telemedicine quickly became integrated into healthcare caused by the Coronavirus 19 (COVID-19) pandemic. Rapid use of telemedicine into healthcare systems was supported by the World Health Organization and other prominent national organizations to reduce transmission of the virus while continuing to provide access to care. In this review, we explored the effect of this swift change in care and its impact on older adults with cancer. RECENT FINDINGS: Older adults are susceptible to the COVID-19 virus caused by various risk factors, such as comorbidity, frailty, decreased immunity, and cancer increases vulnerability to infection, hospitalization, and mortality...

The progress of research focused on cholangiocytes and the biliary tree during development and following injury is hindered by limited available quantitative methodologies. Current techniques include two-dimensional standard histological cell-counting approaches, which are rapidly performed error-prone and lack architectural context; or three-dimensional analysis of the biliary tree in opacified livers, which introduce technical issues along with minimal quantitation. The present study aims to fill these quantitative gaps with a supervised machine learning model (BiliQML) able to quantify biliary forms in the liver of anti-Keratin 19 antibody-stained whole slide images...

Rapid eye movement sleep is associated with distinct changes in various biomedical signals that can be easily captured during sleep, lending themselves to automated sleep staging using machine learning systems. Here, we provide a perspective on the critical characteristics of biomedical signals associated with rapid eye movement sleep and how they can be exploited for automated sleep assessment. We summarise key historical developments in automated sleep staging systems, having now achieved classification accuracy on par with human expert scorers and their role in the clinical setting...

Hepatitis B and C viruses (HBV and HCV) are significant causes of chronic liver diseases, with approximately 350 million infections globally. To accelerate the finding of effective treatment options, we introduce HBCVTr, a novel ligand-based drug design (LBDD) method for predicting the inhibitory activity of small molecules against HBV and HCV. HBCVTr employs a hybrid model consisting of double encoders of transformers and a deep neural network to learn the relationship between small molecules' simplified molecular-input line-entry system (SMILES) and their antiviral activity against HBV or HCV...

Major histocompatibility complex Class II (MHCII) proteins initiate and regulate immune responses by presentation of antigenic peptides to CD4+ T-cells and self-restriction. The interactions between MHCII and peptides determine the specificity of the immune response and are crucial in immunotherapy and cancer vaccine design. With the ever-increasing amount of MHCII-peptide binding data available, many computational approaches have been developed for MHCII-peptide interaction prediction over the last decade...

The combination of lifelong learning algorithms with autonomous intelligent systems (AIS) is gaining popularity due to its ability to enhance AIS performance, but the existing summaries in related fields are insufficient. Therefore, it is necessary to systematically analyze the research on lifelong learning algorithms with autonomous intelligent systems, aiming to gain a better understanding of the current progress in this field. This paper presents a thorough review and analysis of the relevant work on the integration of lifelong learning algorithms and autonomous intelligent systems...

With the rapid development of international communication, the number of English courses has shown an explosive growth trend, which has caused a serious problem of information overload, resulting in poor teaching performance of recommended English courses. To solve this problem, this paper proposes a graph convolutional neural network model based on College English course texts, students' major, English foundation and network structure characteristics. First, by analyzing the relevant data of College English courses and combining with graph neural network, an English course recommendation algorithm model based on the College English learning strategy of proximity comparison is proposed...

Hepatitis C, a particularly dangerous form of viral hepatitis caused by hepatitis C virus (HCV) infection, is a major socio-economic and public health problem. Due to the rapid development of deep learning, it has become a common practice to apply deep learning to the healthcare industry to improve the effectiveness and accuracy of disease identification. In order to improve the effectiveness and accuracy of hepatitis C detection, this study proposes an improved denoising autoencoder (IDAE) and applies it to hepatitis C disease detection...

The magnetic levitation (maglev) ball system is a prototypical Single-Input-Single-Output (SISO) system, characterized by its pronounced nonlinearity, rapid response, and open-loop instability. It serves as the basis for many industrial devices. For describing the dynamics of the maglev ball system precisely in the pseudo linear model, the long short-term memory (LSTM) based auto-regressive model with exogenous input variables (LSTM-ARX) is proposed. Firstly, the LSTM network is modified by incorporating the auto-regressive structure with respect to sequence input, allowing it to deduce a locally linearized model without the need for Taylor expansion...

BACKGROUND: Care of older adults requires comprehensive management and control of systemic diseases, which can be effectively managed by family physicians. Complicated medical conditions in older patients admitted to orthopedic departments (orthopedic patients) necessitate interprofessional collaboration. Nutrition is one of the essential components of management involved in improving the systemic condition of older patients. Nutrition support teams play an important role in nutrition management and can be supported by family physicians...

BACKGROUND AND OBJECTIVE: The incidence of stroke is rising, and it is the second major cause of mortality and the third leading cause of disability around the globe. The goal of this study was to rapidly and accurately identify carotid plaques and automatically quantify plaque burden using our automated tracking and segmentation US-video system. METHODS: We collected 88 common carotid artery transection videos (11048 frames) with a history of atherosclerosis or risk factors for atherosclerosis, which were randomly divided into training, test, and validation sets using a 6:3:1 ratio...

SIGNIFICANCE: Three-dimensional quantitative phase imaging (QPI) has rapidly emerged as a complementary tool to fluorescence imaging, as it provides an objective measure of cell morphology and dynamics, free of variability due to contrast agents. It has opened up new directions of investigation by providing systematic and correlative analysis of various cellular parameters without limitations of photobleaching and phototoxicity. While current QPI systems allow the rapid acquisition of tomographic images, the pipeline to analyze these raw three-dimensional (3D) tomograms is not well-developed...

Many organismal traits are genetically determined and covary in evolving populations. The resulting trait correlations can either help or hinder evolvability - the ability to bring forth new and adaptive phenotypes. The evolution of evolvability requires that trait correlations themselves must be able to evolve, but we know little about this ability. To learn more about it, we here study two evolvable systems, a yellow fluorescent protein and the antibiotic resistance protein VIM-2 metallo beta-lactamase. We consider two traits in the fluorescent protein, namely the ability to emit yellow and green light, and three traits in our enzyme, namely the resistance against ampicillin, cefotaxime, and meropenem...

Patient advocates, referring to those individuals that have been diagnosed with the disease for which they advocate, are essential stake holders in healthcare. For those facing the stages of being diagnosed with Inflammatory Breast Cancer (IBC), the "call to advocate" is an immediate response to being diagnosed with a rare and aggressive disease that progresses rapidly, often in a matter of weeks or months. There is a great stigma and bias in the medical community that has inhibited the education and study of IBC...

The rapid growth of the Internet of Things and wearable sensors has led to advancements in monitoring technology in the field of health. One such advancement is the development of wearable respiratory sensors, which offer a new approach to real-time respiratory monitoring compared to traditional methods. However, the energy consumption of these sensors raises concerns about environmental pollution. To address the issue, this study proposes the use of a triboelectric nanogenerator (TENG) as a sustainable energy source...

STUDY DESIGN: Retrospective Cohort Study Objectives: Robot-assisted spine surgery (RASS) is a rapidly evolving technique with potential benefits for improving surgical outcomes. A number of studies on RASS learning curve have focused on early iterations of the Mazor robot. Limited research exists on the learning curve associated with using the Globus Medical ExcelsiusGPS® system. In this retrospective study, we aimed to evaluate the learning curve of RASS using the ExcelsiusGPS® system at a single institution...