Super Class Research Articles

Patterns of digital health access and use among US adults: a latent class analysis

BackgroundDigital technologies allow users to engage in health-related behaviors associated with positive outcomes. We aimed to identify classes of US adults with distinct digital technologies access and health use patterns and characterize class composition. Data came from Health Information National Trends Survey Wave 5 Cycles 1–4, a nationally representative cross-sectional survey of US adults (N = 13,993). We used latent class analysis to identify digital technologies access and health use patterns based on 32 ternary variables of behaviors and access to requisite technologies and platforms, including the internet, internet-enabled devices, health monitors, and electronic health records (EHRs). We ran a multinomial logistic regression to identify sociodemographic and health correlates of class membership (n = 10,734).ResultsTen classes captured patterns of digital technology access and health use among US adults. This included a digitally isolated, a mobile-dependent, and a super user class, which made up 8.9%, 7.8%, and 13.6% of US adults, respectively, and captured access patterns from only basic cellphones and health monitors to near complete access to web-, mobile-, and EHR-based platforms. Half of US adults belonged to classes that lacked access to EHRs and relied on alternative web-based tools typical of patient portals. The proportion of class members who used digital technologies for health purposes varied from small to large. Older and less educated adults had lower odds of belonging to classes characterized by access or engagement in health behaviors. Hispanic and Asian adults had higher odds of belonging to the mobile-dependent class. Individuals without a regular healthcare provider and those who had not visited a provider in the past year were more likely to belong to classes with limited digital technologies access or health use.DiscussionOnly one third of US adults belonged to classes that had near complete access to digital technologies and whose members engaged in almost all health behaviors examined. Sex, age, and education were associated with membership in classes that lacked access to 1 + digital technologies or exhibited none to limited health uses of such technologies. Results can guide efforts to improve access and health use of digital technologies to maximize associated health benefits and minimize disparities.

Lipidome is a valuable tool for the severity prediction of coronavirus disease 2019.

To describe the lipid metabolic profile of different patients with coronavirus disease 2019 (COVID-19) and contribute new evidence on the progression and severity prediction of COVID-19. This case-control study was conducted in Peking University Third Hospital, China. The laboratory-confirmed COVID-19 patients aged ≥18 years old and diagnosed as pneumonia from December 2022 to January 2023 were included. Serum lipids were detected. The discrimination ability was calculated with the area under the curve (AUC). A random forest (RF) model was conducted to determine the significance of different lipids. Totally, 44 COVID-19 patients were enrolled with 16 mild and 28 severe patients. The top 5 super classes were triacylglycerols (TAG, 55.9%), phosphatidylethanolamines (PE, 10.9%), phosphatidylcholines (PC, 6.8%), diacylglycerols (DAG, 5.9%) and free fatty acids (FFA, 3.6%) among the 778 detected lipids from the serum of COVID-19 patients. Certain lipids, especially lysophosphatidylcholines (LPCs), turned to have significant correlations with certain immune/cytokine indexes. Reduced level of LPC 20:0 was observed in severe patients particularly in acute stage. The AUC of LPC 20:0 reached 0.940 in discriminating mild and severe patients and 0.807 in discriminating acute and recovery stages in the severe patients. The results of RF models also suggested the significance of LPCs in predicting the severity and progression of COVID-19. Lipids probably have the potential to differentiate and forecast the severity, progression, and clinical outcomes of COVID-19 patients, with implications for immune/inflammatory responses. LPC 20:0 might be a potential target in predicting the progression and outcome and the treatment of COVID-19.

Operations and Similarity Measures Between (m,n)-Fuzzy Sets

Recently Jun and Hur proposed (m, n)-fuzzy sets which can handle vagueness and uncertainty in information very efficiently in the process of solving complex problems. They defined basic operations over (m, n)-fuzzy sets. The present paper created some new operations over this super class of fuzzy sets and established many theorems related to the their properties. Further some distance and similarity measures of (m, n)-fuzzy sets are proposed and their properties are examined. Moreover, the proposed similarity measures are applied to the problem of pattern recognition.

A New Fixed Coefficient Diagonally Implicit Block Backward Differentiation Formula for Solving Stiff Initial Value Problems

Stiff initial value problems in ordinary differential equations occur when solution components evolve at varying rates, posing challenges for traditional computational methods. Specialized techniques are crucial for maintaining accuracy and stability during rapid transitions, emphasizing their significance in developing reliable numerical algorithms across scientific and engineering applications. This study aims to develop a new fixed coefficient 3-point diagonally implicit block backward differentiation formula for the numerical solution of first order stiff initial value problems. The method is constructed by integrating a triangular matrix into the coefficient matrix of an existing extended 3-point super class of block BDF for solving stiff initial value problems. The selection of a fixed coefficient within the interval accompanies this integration to ensure optimal stability. The method is found to order five. Stability analysis indicates that the method is consistent, zero-stable, and almost A-stable, validating its applicability to stiff initial value problems. Implementation of the method involves Newton’s iteration, and a code in the C programming language is devised to demonstrate its effectiveness. Comparative examination of numerical outcomes with the existing 3BBDF and 3ESBBDF methods highlights the proposed method's enhanced accuracy and reduced computation time.

The effects of race and probiotic supplementation on the intestinal microbiota of 10-km open-water swimmers

This study collected the stools of 10-km open-water swimmers after race and probiotic supplementation, and 16S rRNA sequencing and metabolomic analysis were performed to clarify their intestinal microbiota characteristics. The findings revealed a relatively high proportion of Firmicutes in all the athletes. Firmicutes in female athletes were significantly higher after probiotic supplementation. The intestinal microbiota of athletes was closely associated with the pathways of exercise against cancer, exercise against aging, exercise for improving cognition, sphingolipid metabolism and endocrine resistance. Future research should focus on the relationship between Firmicutes and Proteobacteria with super class metabolites in athletes. This report initially explored the changes in intestinal microbiota involved in metabolic pathways in athletes after race and after probiotic supplementation and provided a theoretical basis for the further improvement of the monitoring of their physical function after race and selection of nutritional strategies during exercise training.

RNN Based Deep Learning Approach for ECG Beat Classification

The electrical patterns of the heart, captured through an electrocardiogram (ECG/EKG), serve as a diagnostic tool to identify potential issues such as heart attacks, irregular heart rhythms, heart failure, and arrhythmia, which manifests as irregularities in the heartbeat's rhythm. Deep Learning (DL) architectures have been successfully employed for arrhythmia detection and classification and offered superior performance to traditional shallow Machine Learning (ML) approaches. This paper introduces a novel approach utilizing deep learning techniques, specifically a Bidirectional Gated Recurrent Unit (Bi-GRU) model a variant of RNN, to classify ECG arrhythmia beats into distinct categories. The Bi-GRU model is employed in this work due to its capability to capture temporal dependencies in ECG signals, enabling a nuanced understanding of beat sequences for precise classification. Leveraging the MIT-BIH arrhythmia database, a comprehensive dataset containing annotated ECG signals, this study explores the efficacy of deep learning in accurately categorizing beats in to five super classes as per the standard of Association for the Advancement of Medical Instrumentation (AAMI). Evaluation metrics encompassing accuracy (Acc), specificity (Spe), sensitivity (Sen), positive predictive value (Ppv), and F1-score are utilized to assess the model performance in distinguishing between diverse arrhythmia classes.

Prioritised identification of structural classes of natural products from higher plants in the expedition of antimalarial drug discovery

The emergence and spread of drug-recalcitrant Plasmodium falciparum parasites threaten to reverse the gains made in the fight against malaria. Urgent measures need to be taken to curb this impending challenge. The higher plant-derived sesquiterpene, quinoline alkaloids, and naphthoquinone natural product classes of compounds have previously served as phenomenal chemical scaffolds from which integral antimalarial drugs were developed. Historical successes serve as an inspiration for the continued investigation of plant-derived natural products compounds in search of novel molecular templates from which new antimalarial drugs could be developed. The aim of this study was to identify potential chemical scaffolds for malaria drug discovery following analysis of historical data on phytochemicals screened in vitro against P. falciparum. To identify these novel scaffolds, we queried an in-house manually curated database of plant-derived natural product compounds and their in vitro biological data. Natural products were assigned to different structural classes using NPClassifier. To identify the most promising chemical scaffolds, we then correlated natural compound class with bioactivity and other data, namely (i) potency, (ii) resistance index, (iii) selectivity index and (iv) physicochemical properties. We used an unbiased scoring system to rank the different natural product classes based on the assessment of their bioactivity data. From this analysis we identified the top-ranked natural product pathway as the alkaloids. The top three ranked super classes identified were (i) pseudoalkaloids, (ii) naphthalenes and (iii) tyrosine alkaloids and the top five ranked classes (i) quassinoids (of super class triterpenoids), (ii) steroidal alkaloids (of super class pseudoalkaloids) (iii) cycloeudesmane sesquiterpenoids (of super class triterpenoids) (iv) isoquinoline alkaloids (of super class tyrosine alkaloids) and (v) naphthoquinones (of super class naphthalenes). Launched chemical space of these identified classes of compounds was, by and large, distinct from that of ‘legacy’ antimalarial drugs. Our study was able to identify chemical scaffolds with acceptable biological properties that are structurally different from current and previously used antimalarial drugs. These molecules have the potential to be developed into new antimalarial drugs.

CONVERGENCE TEST FOR THE EXTENDED 3 - POINT SUPER CLASS OF BLOCK BACKWARD DIFFERENTIATION FORMULA FOR INTEGRATING STIFF IVP

In this work, a new scheme is generated from the extended 3–point super class of block backward differentiation formula for integrating stiff IVP and the proposed method is subjected to convergence test. The proposed scheme is found to be zero stable, consistent and of order 5. Thus, possess all the required criteria for convergence. The scheme can approximate the values of three points at a time per integration step. The scheme maintained the same technique of co-opting a stability control parameter () in the formula and by adjusting its value within the interval , more A-stabled schemes can be generated. However, this research considers and arrived at zero and A– Stabled method, capable of solving any stiff IVPs. Hence, the proposed convergent scheme can be used for integrating stiff IVPs and archives accuracy of scale error and less executional time.

Developing Energy Access Ontology using Protege Tool

In this internet-based world where a large amount of information exists on the World Wide Web (WWW), the information retrieval systems are mainly centred on topic-based classification. Numerous efforts and time have been consumed for relevant information extraction through major search engines if the data is not organised correctly. Ontologies proved to be an effective technique for representing and retrieving information, which is the key idea in semantic web applications. Ontologies not only help in efficient knowledge representation and information retrieval, but it also helps in mapping the hidden knowledge about a subject. This paper discusses the process and method of building ontology on the “Energy access” domain. The methodology is based on the tools used in developing the ontology. Several tools are used to create an ontology. Protégé is a most popular tool for ontology editing and for developing ontology.1 In this paper, various aspects like super class and subclass hierarchy, creating a subclass, instances for class illustration, query retrieval process, visualisation, and graph views have been demonstrated by using protégé software.

Sailing the tide of over consumption: applying a business history approach to explore the rising demand of luxury yachts and travel since 1979

PurposeThe purpose of this paper is to identify how the socio-economic trends caused by the economic deregulation of the last four decades have led to a high-net-worth strata of individuals and families that conspicuously consumes luxury items and are the main customers in the luxury yacht market.Design/methodology/approachA selected cross-section review and discussion of relevant publications and theories within the field of tourism, social sciences, business and economic history are synthesised with relevant data to outline the factors leading to socio-economic change and conspicuous consumption.FindingsThis paper advocates for the synthesis of scholarly techniques found within the discipline of Business History to illuminate the development of a luxury yachting industry over the past four decades. Using the varieties of capitalism approach this paper demonstrates that the local characteristics of the BRIC (Brazil, Russia, India and China) in combination with the international globalisation and trade deregulation since 1980 has led to a new super wealthy class that engages in conspicuous consumption. Using a schema based on critical juncture theory, light has been shed on the specific factors underpinning the demand for luxury yachts as part of this conspicuous consumption.Originality/valueThis paper adds a new set of methodologies and theoretical tools to the student of luxury tourism that embed the practice within the context of socio-economic changes brought forth by economic globalisation since 1979, opening up new avenues of research.

Subtypes of Relapsing-Remitting Multiple Sclerosis Identified by Network Analysis (P3-3.004)

<h3>Objective:</h3> To use network analysis to identify subtypes of relapsing-remitting multiple sclerosis patients based on their cumulative signs and symptoms. <h3>Background:</h3> Network analysis can elucidate the complex relationships between the phenotypes, genes, proteins, and metabolic pathways that underlie human diseases, without a priori knowledge of how these elements will interact. It is of interest to determine whether subtypes of multiple sclerosis based on predominant clinical presentation (sensory, cerebellar, motor, visual, cognitive, fatigue, etc.) can be identified. Clinical subtypes could differ regarding prognosis, course, and response to treatment. <h3>Design/Methods:</h3> We reviewed the electronic medical records of 120 patients with relapsing-remitting multiple sclerosis and recorded signs and symptoms. Signs and symptoms were mapped to a neuro-ontology and then collapsed into 16 super classes by subsumption. Bipartite (subject-feature) and unipartite (subject-subject) network graphs were created using Gephi for both a normalized and unnormalized feature set. Degree and weighted degree were calculated for each node. Graphs were partitioned into communities using the modularity score. Feature maps were used to visualize differences in features by community. <h3>Results:</h3> Network analysis of unipartite graphs yielded higher modularity scores (unnormalized 0.377, normalized 0.49) than the bipartite graphs (unnormalized 0.258, normalized 0.247). Across all graphs, we found large communities of subjects with predominantly sensory features and communities with predominantly motor features (weakness combined with hypertonia, hyperreflexia, or incoordination). When the feature dataset was normalized, network analysis showed motor and sensory communities and additional communities of subjects with a predominance of fatigue, pain, and cognitive features. <h3>Conclusions:</h3> Network analysis can partition multiple sclerosis subjects into communities based on signs and symptoms. Communities of subjects with predominant motor, sensory, pain, fatigue, cognitive, and behavior features were found. Larger datasets and additional partitioning algorithms are needed to confirm these results and elucidate their clinical significance. <b>Disclosure:</b> Mr. Howlett-Prieto has nothing to disclose. Ms. Oommen has nothing to disclose. The institution of Dr. Carrithers has received research support from Biogen. Dr. Hier has nothing to disclose.

On BV supermanifolds and the super Atiyah class

We study global and local geometry of forms on odd symplectic BV supermanifolds, constructed from the total space of the bundle of 1-forms on a base supermanifold. We show that globally 1-forms are an extension of vector bundles defined on the base supermanifold. In the holomorphic category, we prove that this extension is split if and only if the super Atiyah class of the base supermanifold vanishes. This is equivalent to the existence of a holomorphic superconnection: we show how this condition is related to the characteristic non-split geometry of complex supermanifolds. From a local point of view, we prove that the deformed de Rham double complex naturally arises as a de-quantization of the de Rham/Spencer double complex of the base supermanifold. Following Ševera, we show that the associated spectral sequence yields semidensities on the BV supermanifold, together with their differential in the form of a super BV Laplacian.

A Review of Techniques to Enhance an Amplifier’s Performance Using Resistive Local Common Mode Feedback

A review of some of the most common applications of the resistive local common mode feedback technique to enhance amplifier’s performance is presented. It is shown that this simple technique offers essential improvement in open loop gain, gain-bandwidth product, slew rate, common mode rejection ratio, power supply rejection ratio, etc. This is achieved without increasing power dissipation or supply voltage requirements and with small additional silicon area and circuit complexity. It is also shown that it is especially appropriate to improve amplifiers’ performance in current fine-line submicrometer CMOS technology. Some of the applications discussed are GB enhanced, class AB and super class AB operational amplifiers, gain boosted op-amps, bulk-driven circuits, sample and hold circuits and power management circuits, among others.

A height bound for abelian schemes with realtimes mathbb {Q}^{2} multiplication

In this paper, we prove a height bound for points on the base of a family of abelian varieties at which the fibre possesses additional endomorphisms. This complements a result of André in his book (G-Functions and Geometry Aspects of Mathematics, E13. Friedrich Vieweg and Sohn, Braunschweig, 1989) as well a result of Daw and Orr (Ann Scuol Norm Super Class Sci 39:1, 2021). The work in this paper will be used to prove a new case of the Zilber-Pink conjecture which will form part of the author’s PhD thesis.

Some Super Hyper Degrees and Co-Super Hyper Degrees on Neutrosophic Super Hyper Graphs and Super Hyper Graphs Alongside Applications in Cancer’s Treatments

In this research, new setting is introduced for new notions, namely, Super Hyper Degree and Co-Super Hyper Degree. Two different types of definitions are debut for them but the research goes further and the Super Hyper Notion, Super Hyper Uniform, and Super Hyper Class based on that are well-defined and well-reviewed. The literature review is implemented in the whole of this research. For shining the elegancy and the significancy of this research, the comparison between this Super Hyper Notion with other Super Hyper Notions and fundamental Super Hyper Numbers are featured. The definitions are followed by the examples and the instances thus the clarifications are driven with different tools. The applications are figured out to make sense about the theoretical aspect of this ongoing research. The cancer’s treatments are the under research to figure out the challenges make sense about ongoing and upcoming research. The special case is up. The cells are viewed in the deemed ways. There are different types of them. Some of them are individuals and some of them are well-modeled by the group of cells. These types are all officially called “Super Hyper Vertex” but the relations amid them all officially called “Super Hyper Edge”. The frameworks “Super Hyper Graph” and “neutrosophic Super Hyper Graph” are chosen and elected to research about “cancer’s treatments”. Thus, these complex and dense Super Hyper Models open up some avenues to research on theoretical segments and “cancer’s treatments”. Some avenues are posed to pursue this research. It’s also officially collected in the form of some questions and some problems. If there’s a Super Hyper Edge between two Super Hyper Vertices, then these two Super Hyper Vertices are called Super Hyper Neighbors. The number of Super Hyper Neighbors for a given Super Hyper Vertex is called Super Hyper Degree. The number of common Super Hyper Neighbors for some Super Hyper Vertices is called Co-Super Hyper Degree for them and used Super Hyper Vertices are called Co-Super Hyper Neighbors. A graph is Super Hyper Uniform if it’s Super Hyper Graph and the number of elements of Super Hyper Edges are the same. Assume a neutrosophic Super Hyper Graph. There are some Super Hyper Classes as follows. It’s SuperHyperPath if it’s only one SuperVertex as intersection amid two given Super Hyper Edges with two exceptions; it’s SuperHyperCycle if it’s only one SuperVertex as intersection amid two given Super Hyper Edges; it’s Super Hyper Star it’s only one SuperVertex as intersection amid all Super Hyper Edges; it’s SuperHyperBipartite it’s only one SuperVertex as intersection amid two given Super Hyper Edges and these SuperVertices, forming two separate sets, has no Super Hyper Edge in common; it’s SuperHyperMultiPartite it’s only one SuperVertex as intersection amid two given Super Hyper Edges and these SuperVertices, forming multi separate sets, has no Super Hyper Edge in common; it’s SuperHyperWheel if it’s only one SuperVertex as intersection amid two given Super Hyper Edges and one SuperVertex has one Super Hyper Edge with any common SuperVertex. The number of Super Hyper Edges for a given Super Hyper Vertex is called Super Hyper Degree.

(Neutrosophic) 1-Failed SuperHyperForcing As the Entrepreneurs on Cancer's Recognitions To Fail Forcing Style As the Super Classes With Hyper Effects In The Background of the Framework is So-Called (Neutrosophic) SuperHyperGraphs

(Neutrosophic) 1-Failed SuperHyperForcing As the Entrepreneurs on Cancer's Recognitions To Fail Forcing Style As the Super Classes With Hyper Effects In The Background of the Framework is So-Called (Neutrosophic) SuperHyperGraphs

A New Multi - Block Super Class of BDF for Integrating First Order Stiff IVP of ODEs

A new multi-block super class of backward differentiation formula for integrating first order stiff IVPs with a variable mesh size strategy is derived. The proposed scheme approximate two solution values at a time per integration step. The stability properties are achieved by varying the mesh size ratio in the formula to generate more zero stable and A-Stable schemes, capable of solving stiff IVPs of ODEs. Approximates result from the system of stiff ODE problems considered are found to favorably validate the new method in terms of accuracy of the scale error and less executional time in respect to the two methods compared in the study. Hence, the proposed scheme can be used for solving for stiff IVPs of ODEs.

Orthodontic Camouflage of Borderline Skeletal Class III MalocclusionA Report of Two Cases

Camouflage treatment in borderline Class III patients, especially those who refuse a surgical line of treatment, remains a challenge to the orthodontists. Such patients were usually treated using Class III elastics and lower premolar extractions. Mandibular arch distalisation is an alternative option for non extraction Class III camouflage. Temporary Anchorage Devices (TADs) help in achieving effective mandibular molar distalisation and are more accepted by adult patients. This case report discusses the diagnosis and management of two different presentations of borderline skeletal Class III malocclusion treated with miniscrew assisted mandibular arch distalisation. Two adult female patients between 18-20 years of age presented with a skeletal Class III malocclusion, average growth pattern, super Class I molar relationship and straight facial profile. The patients did not agree for a surgical line of treatment. Camouflage treatment by distalisation of mandibular arch using buccal miniscrew implants was done. Inter-radicular miniscrews were placed between mandibular second premolar and first molar to apply distalisation force of 250 gm/side. Lower arch distalisation of 2-3 mm was achieved in an average of 4.6 months. The outcomes were well retained 3 years post-treatment.

Two–Point Diagonally Implicit Extended Super Class of Block Backward Differentiation Formula for Stiff Initial Value Problems

In this paper, a diagonal form of the extended super class of block backward differentiation formula is derived. The method is fully implicit and approximates two solution values at a time. By varying a parameter 𝜌𝜖 (–1,1) in the formula, different sets of formulae can be generated. Analysis of the method indicated that the method is both zero and A–stable, hence, suitable for solving stiff initial value problems. Comparison of the method with some existing algorithms showed its advantage in terms of accuracy over some methods.

Super Hyper Dominating and Super Hyper Resolving on Neutrosophic Super Hyper Graphs and Their Directions in Game Theory and Neutrosophic Super Hyper Classes

In this research article, the notions of Super Hyper Dominating and Super Hyper Resolving are defined in the setting of neutrosophic Super Hyper Graphs. Some ideas are introduced on both notions of Super Hyper Dominating and Super Hyper Resolving, simultaneously and as the same with each other. Some neutrosophic Super Hyper Classes are defined based on the notion, Super Hyper Resolving. The terms of duality, totality, perfectness, connectedness, and stable, are added to basic framework and initial notions, Super Hyper Dominating and Super Hyper Resolving but the concentration is on the “perfectness” to figure out what’s going on when for all targeted Super Hyper Vertices, there’s only one Super Hyper Vertex in the intended set. There are some instances and some clarifications to make sense about what’s happened and what’s done in the starting definitions. The key point is about the minimum sets. There are some questions and some problems to be taken as some avenues to pursue this study and this research. A basic familiarity with Super Hyper Graph theory and neutrosophic Super Hyper Graph theory is proposed.