Identification Of Class Research Articles

Enhancing ECG Heartbeat classification with feature fusion neural networks and dynamic minority-biased batch weighting loss function

Objective. This study aims to address the challenges of imbalanced heartbeat classification using electrocardiogram (ECG). In this proposed novel deep-learning method, the focus is on accurately identifying minority classes in conditions characterized by significant imbalances in ECG data. Approach. We propose a feature fusion neural network enhanced by a dynamic minority-biased batch weighting loss function. This network comprises three specialized branches: the complete ECG data branch for a comprehensive view of ECG signals, the local QRS wave branch for detailed features of the QRS complex, and the R wave information branch to analyze R wave characteristics. This structure is designed to extract diverse aspects of ECG data. The dynamic loss function prioritizes minority classes while maintaining the recognition of majority classes, adjusting the network’s learning focus without altering the original data distribution. Together, this fusion structure and adaptive loss function significantly improve the network’s ability to distinguish between various heartbeat classes, enhancing the accuracy of minority class identification. Main results. The proposed method demonstrated balanced performance within the MIT-BIH dataset, especially for minority classes. Under the intra-patient paradigm, the accuracy, sensitivity, specificity, and positive predictive value for Supraventricular ectopic beat were 99.63 % , 93.62 % , 99.81 % , and 92.98 % , respectively, and for Fusion beat were 99.76 % , 85.56 % , 99.87 % , and 84.16 % , respectively. Under the inter-patient paradigm, these metrics were 96.56 % , 89.16 % , 96.84 % , and 51.99 % for Supraventricular ectopic beat, and 96.10 % , 77.06 % , 96.25 % , and 13.92 % for Fusion beat, respectively. Significance. This method effectively addresses the class imbalance in ECG datasets. By leveraging diverse ECG signal information and a novel loss function, this approach offers a promising tool for aiding in the diagnosis and treatment of cardiac conditions.

Wind resource assessment for turbine class identification in Bayanzhaganxiang, China

Abstract The wind resource assessment has been used effectively to identify the classification of wind turbines at a particular wind farm site. The current study used WAsP software and various statistical methods such as graphical, energy pattern factor, standard deviation, and Rayleigh distribution methods to find the Weibull parameters by evaluating the raw data collected from August 2005 until July 2006 at four (4) different heights of the meteorological mast station in Bayanzhaganxiang, China. The Weibull parameters were utilized to find the annual mean wind speed, probability density, and cumulative distribution functions of wind conditions at the reference heights of 70 m, 50 m, 30 m, and 10 m. The wind shear coefficient was 0.130 with an overall roughness factor of 0.0385 m, suggesting the site vicinity is an open country with no significant structures and vegetation. The results also showed that the post-processed output from WAsP and standard deviation method at the sensor’s height of 70 m have a correlation coefficient and confidence level of 0.99977 and above 95%, respectively. Based on the turbine classification from GL Wind 2003 and IEC 61400-1 Ed.2, it was found that the turbine class ideal for the site is class III wind turbines with an annual mean wind speed of 7.439 m/s at a hub height of 99 m. The measured wind power density at hub height was calculated according to IEC 61400-12-1, which yields 464.36 W/m2. The characteristic wind turbulence at 70 m high is IEC subclass B. Among the selected wind turbines, the net annual energy production with efficiency is 8,059.57 MWh/year using Avantis AV1010, with the highest capacity factor of 40.05%. It has been found that the lowest energy generation cost is US$ 0.0292/kWh for a period of 20 years.

Classification of Cardiovascular Arrhythmia Using Deep Learning Techniques: A Review

Deep Learning (DL), an offshoot of Machine Learning (ML) has emerged as a powerful and feasible solution for medical image analysis due to advancements in robust computer software and hardware technologies. It plays a key role in Cardiovascular disease (CVD) diagnosis by detecting anomalies in Electrocardiogram (ECG) signals. Cardiac arrhythmia, which refers to irregular heartbeat, may signal an early symptom of CVD and can lead to fatal outcomes if ignored. Accurate detection of arrhythmia is very challenging even for experts to distinguish between acute and chronic conditions in ECG readings. This triggered the focus of researchers to explore the application of Artificial Intelligence for ECG classification. Traditional machine learning methods use handcrafted features that require domain knowledge. The new era in DL makes the automatic detection of Cardiovascular Disease (CVD) possible. In this paper, an exhaustive review of DL-based techniques for ECG classification has been presented. Research findings in this survey indicate the challenges and issues with arrhythmia detection, such as single lead and multiple lead ECG signals, choice of the size of the training data set, and the number of arrhythmia classes, etc. The study also signifies that there is great scope for improving the performance of arrhythmia prediction models by employing hybrid ensemble learning, time series analysis using Recurrent Neural Network architectures and identification of unexplored classes of arrhythmia.

The first national survey on cultural participation in Portugal: exploring social and professional backgrounds

ABSTRACT Portugal undertook the first national survey of cultural practices (2020) with support from the Calouste Gulbenkian Foundation. The present paper describes the contemporary cultural eclecticism in keeping with the analysis of key indicators for the cultural consumption of cinema, live performances, theatre, dance, circus, festivals, and local events. In line with previous European Survey conclusions, the first Portuguese National Survey results demonstrate how the younger and better educated, alongside those raised by educated parents, display “cultural omnivorism”. The main findings converge around how the influence of social backgrounds, positions in the professional structure and class identities, are shaping cultural consumption as pointed out by Reeves in his cross-national European study.

Identification of a Novel Structural Class of HV1 Inhibitors by Structure-Based Virtual Screening.

The human voltage-gated proton channel, hHV1, is highly expressed in various cell types including macrophages, B lymphocytes, microglia, sperm cells and also in various cancer cells. Overexpression of HV1 has been shown to promote tumor formation by highly metastatic cancer cells, and has been associated with neuroinflammatory diseases, immune response disorders and infertility, suggesting a potential use of hHV1 inhibitors in numerous therapeutic areas. To identify compounds targeting this channel, we performed a structure-based virtual screening on an open structure of the human HV1 channel. Twenty selected virtual screening hits were tested on Chinese hamster ovary (CHO) cells transiently expressing hHV1, with compound 13 showing strong block of the proton current with an IC50 value of 8.5 μM. Biological evaluation of twenty-three additional analogs of 13 led to the discovery of six other compounds that blocked the proton current by more than 50% at 50 μM concentration. This allowed for an investigation of structure-activity relationships. The antiproliferative activity of the selected promising hHV1 inhibitors was investigated in the cell lines MDA-MB-231 and THP-1, where compound 13 inhibited growth with an IC50 value of 9.0 and 8.1 μM, respectively. The identification of a new structural class of HV1 inhibitors contributes to our understanding of the structural requirements for inhibition of this ion channel and opens up the possibility of investigating the role of HV1 inhibitors in various pathological conditions and in cancer therapy.

Parenting practices and trajectories of proactive coping assets among emerging adult Black men.

Positive youth development (PYD)frameworks suggest that a critical response to investigating the challenges young Black men living in resource poor communities experience involves identifying contextual resources in young men's lives and personal assets that promote success. The following study examines heterogeneity in proactive coping assets trajectories, parental practices as predictors of developmental trajectories, and associated outcomes of each trajectory. The study sample consisted of Black emerging adult men living in rural Georgia (N = 504). At baseline, men were between the ages of 19 and 22 (Mage = 20.29; SD = 1.10). At wave four, the participants' mean age was 27.67 (SD = 1.39). Results of growth mixture modeling from waves 1 to 3 discerned three developmental trajectory classes of emerging adults' proactive coping assets: a high and increasing class (n = 247, 49%), a low and stable class (n = 212, 42%), and a moderate and decreasing class (n = 45, 9%). Trajectory classes were linked to baseline levels of parental support, coaching, and expectations. Analysis revealed that parental support and parental coaching predicted proactive coping asset trajectory class identification. Links were then investigated between emerging adults' proactive coping asset trajectory classes and wave four physical health, depression, and alcohol use. Results revealed significant associations between class identification, alcohol use, and physical health. Study findings provide evidence supporting the impact of parenting on emerging adult Black men, underscoring the need to expand resources that support parenting and emerging adult relationships.

“Alive in Every Fibre”: Chopin and Wharton on Pain, Pleasure, and Private Feeling

In this essay, novels by Kate Chopin and Edith Wharton serve to elucidate more widely resonant value-laden distinctions between publicly embodied and quietly internalized responses to pain and pleasure. This fictional archive denigrates the demonstrativeness it associates with people marginalized by ascriptive identities of race and class while endorsing the uncommonly vibrant inner lives of particular elite white subjects. Pain and pleasure are valued for arousing hidden depths of feeling that distinguish a singular subject’s affective life from purportedly commonplace and conformist incarnations. Conceptions of selfhood and otherness hinge on distinctions between a subject afforded a purportedly uncommon, deeply vibrant affect molded by an equally uncommon responsiveness to hedonic stimuli and a person or set of persons whose discernable, often simulated or conventional hedonic feelings are represented as typifying a comparatively depreciated racialized, classed, or gendered norm, or some combination of the three. This high-cultural literary investment in a nonnormative, nonreproducible affective interiority strengthened amid debates about privacy rights, an increasing cultural preference for performative self-presentations, and efforts to standardize the US population into types. Drawing on this context along with both affect theory and affective science, the essay demonstrates these novels’ importance to understanding how an unexpressed inner vitality emerged as distinction’s volitionally unattainable vital sign.

Ecophobia and Social Class Identity: An Ecocritical Approach to the Nature/Culture Divide in Oscar Wilde’s Fairy Tales “The Young King” and “The Star Child”

This article applies an ecocritical approach to the analysis of the nature/culture divide in Oscar Wilde’s “The Young King” and “The Star-Child”. These two tales contrast the realm of nature, embodied in the forest, and the realm of civilisation, represented by the city. Both stories focus on the protagonists’ journey from wilderness to the city, where not only do they need to become civilised subjects, but they are expected to govern as kings. This physical journey is matched by an internal one since both characters simultaneously undergo a transition from an animal-like state to a human one. I argue that these tales’ use of the nature/culture and animal/human dichotomies is closely connected to Wilde’s reflections about the Victorian social class system included in The Soul of Man under Socialism. Class struggle is indeed a major preoccupation in traditional folktales, where protagonists tend to magically escape from an initial disadvantaged position. Applying an ecocritical perspective to “The Young King” and “The Star-Child” helps to illustrate how these two tales manage to question the legitimacy of the hierarchical social structure by blurring the lines that separate the civilised subject from the animal one.

Identification of Key Classes in Software Systems Based on Static Analysis and Voting Mechanism

Identifying key classes of a software system can help developers understand the system quickly, reduce the time for system maintenance, and prevent security risks caused by defects in key classes. So far, many approaches have been proposed to identify key classes from software systems. However, some approaches select too many key class candidates, making it inconvenient and difficult for developers to start understanding the system from these classes. For the other approaches, although the number of key class candidates is not large, their effectiveness needs to be further improved. To this end, in this paper, we propose a new model, named SAVM, to detect key classes by combining static analysis and a voting mechanism. First, we extract structural information from the source codes of a software system and construct a class coupling network (CCN) using this information. Then, we present the VRWD method that iteratively identifies important nodes in CCN based on a voting mechanism. Specifically, in each iteration, a node votes for its outgoing neighbors and in the meantime receives votes from its incoming neighbors. Afterward, the node that attains the highest voting score is elected as the important node in this turn. Finally, the corresponding classes of the selected important nodes are the key class candidates. The effectiveness of the proposed model and eight other baselines is evaluated in eight open-source Java projects. The experimental results show that although no method performs the best in all projects, according to the average ranking of the Friedman test, our method overall performs better compared to the baselines. In addition, this paper also proves through experiments that our approach can be applied to large-scale software projects. These indicate that our approach is a valuable technique for developers.

Participatory mapping of tree equity, preferences, and environmental justice in Portland, Oregon

In this study, we examine community lived experiences, preferences, and narratives about tree equity in Portland, Oregon. Using an environmental justice framework combined with participatory mapping, focus group discussions, and semi-structured interviews, we examine values, perceptions of canopy cover, and everyday relationships with trees across different racial and socio-economic backgrounds. Results show that participants from neighborhoods with histories of investment and privilege had different lived experiences compared to those with histories of disinvestment and marginalization. While participants overall valued trees, concerns about tree-related risk and safety varied in ways that reflected racial and class identities. Furthermore, memories and historic knowledge shaped perceived tree equity but contemporary problems such as tree removal, maintenance policies, and gentrification were viewed as barriers to achieving more equitable outcomes. Our study underscores the importance of centering community experiences, values, and needs along with tree programs that can alleviate barriers to tree care and maintenance.

Identifying type II quasars at intermediate redshift with few-shot learning photometric classification

A sub-population of AGNs where the central engine is obscured are known as type II quasars (QSO2s). These luminous AGNs have a thick and dusty torus that obscures the accretion disc from our line of sight. Thus, their special orientation allows for detailed studies of the AGN-host co-evolution. Increasing the sample size of QSO2 sources in critical redshift ranges is crucial for understanding the interplay of AGN feedback, the AGN-host relationship, and the evolution of active galaxies. We aim to identify QSO2 candidates in the `redshift desert' using optical and infrared photometry. At this intermediate redshift range (i.e. $1 z 2$), most of the prominent optical emission lines in QSO2 sources (e.g. CIV$ OIII 4959, 5008$) fall either outside the wavelength range of the SDSS optical spectra or in particularly noisy wavelength ranges, making QSO2 identification challenging. Therefore, we adopted a semi-supervised machine learning approach to select candidates in the SDSS galaxy sample. Recent applications of machine learning in astronomy focus on problems involving large data sets, with small data sets often being overlooked. We developed a `few-shot' learning approach for the identification and classification of rare-object classes using limited training data (200 sources). The new AMELIA pipeline uses a transfer-learning based approach with decision trees, distance-based, and deep learning methods to build a classifier capable of identifying rare objects on the basis of an observational training data set. We validated the performance of AMELIA by addressing the problem of identifying QSO2s at $1 z 2$ using SDSS and WISE photometry, obtaining an F1-score above 0.8 in a supervised approach. We then used AMELIA to select new QSO2 candidates in the `redshift desert' and examined the nature of the candidates using SDSS spectra, when available. In particular, we identified a sub-population of NeV emitters at $z which are highly likely to contain obscured AGNs. We used X-ray and radio cross-matching to validate our classification and investigated the performance of photometric criteria from the literature showing that our candidates have an inherent dusty nature. Finally, we derived physical properties for our QSO2 sample using photoionisation models and verified the AGN classification using an SED fitting. Our results demonstrate the potential of few-shot learning applied to small data sets of rare objects, in particular QSO2s, and confirms that optical-IR information can be further explored to search for obscured AGNs. We present a new sample of candidates to be further studied and validated using multi-wavelength observations.

Two-Dimensional Thin-Layer Chromatography as an Accessible, Low-Cost Tool for Lipid-Class Profile Screening

The interest in lipid composition profiling is significantly increasing as research reveals the immense importance of lipids in medicine, plant science, food and agriculture. However, lipidomic analysis requires high-end specialty equipment. We used two-dimensional thin-layer chromatography (2D-TLC) as a readily available, low-cost tool for basic lipidomic profiling of lipid classes in algal samples in the models Chlamydomonas reinhardtii, Auxenochlorella protothecoides, and Euglena gracilis, validating lipid class identification using an LC-MS/MS analysis. Algal lipid extracts were separated on a 2D-TLC plate, and TLC analysis was followed by scraping individual TLC spots off the plate, and a subsequent liquid chromatography separation and tandem mass spectrometry (LC-MS/MS) analysis. For comparison, crude lipid extracts were also injected directly to the LC-MS/MS system. Lipid class annotation was achieved by a combination of accurate mass, retention time information, neutral loss and fragment ion analysis by MS2Analyzer, and by matching spectra to LipidBlast MS/MS library. Overall, we were able to identify 15 lipid classes, and to adequately profile the lipid classes in all three organisms. This TLC method is thus suggested as an accessible tool for lipid class profiling of algal, plant, and food lipids, alike, when a rapid and simple analysis is required, e.g., for screening purposes.

Promoting Awareness and Self-Efficacy for Culturally Responsive Teaching of Pre-Service Teachers Through the Identity Project – a Mixed Methods Study

ABSTRACT Culturally Responsive Teaching (CRT) provides a framework for teachers to include students’ ethnic-cultural identities in class, aiming to tackle issues of educational and societal inequity. This quasi-experimental mixed methods intervention study tested whether pre-service teachers attending a seminar based on an ethnic-cultural identity school intervention, the Identity Project, would show greater CRT self-efficacy and more positive beliefs about teaching in ethnic-culturally diverse classes, compared to a control group. Repeated measures ANCOVAs of survey data from 606 pre-service teachers in Germany indicated a stronger T1-T2 increase in confidence for interacting with ethnic-culturally diverse students and engaging in culture- and ethnic-related conversations in the intervention group. No significant time-by-group interactions emerged for other CRT facets. A content analysis of brief texts of pre-service teachers in the intervention group revealed they became more self-reflective about their own beliefs, learned about CRT practices for their own teaching, and gained confidence for including issues of ethnicity and culture in class. Yet, the complexity of ethnic-cultural diversity-related topics left some pre-service teachers feeling overwhelmed about how to adequately address ethnic-cultural diversity in the classroom. Overall, the Identity Project seminar raised pre-service teachers’ awareness and self-efficacy for engaging in CRT in the future.

The Art of Speech: Elocution, Speech Training, Speech Therapy, and the Performative Limits of Class in Mid-twentieth-century Britain.

This article argues that elocution, speech training, and speech therapy-three professions concerned with the voice-were intimately bound up with a shifting politics of class in early- and mid-twentieth-century Britain. The last two, in particular, attempted to stake new claims in the changed landscape of the post-1945 welfare state. Proponents of speech training distinguished themselves from elocutionists and saw their role to improve children's speech, but they performatively disavowed class as an organizing category within it. This was paralleled by speech therapy, which emerged as a formal profession in Britain in 1945 through the unification of two separate (and often rival) halves of the profession under a single regulatory college, and which found itself having to justify where its pathologizing of vocal production ended and elocution's focus on the aesthetics of accent began. I argue that these disavowals provide a useful framework through which to read class dynamics and consider the performative dimensions of class identities at this time. Mobilising select writers and speech experts-who straddled the boundaries of elocution, speech training, and speech therapy-this article shows how a variety of different categories, from gender to geography, were employed as proxies to allow for the problematization of dialect but not accent and to efface 'class'.

“I come from a poor family”: deciphering how working-class young men aspire to and experience their journeys in STEM higher education

AbstractWorking-class young men are often pathologised for their perceived lack of white-collar career aspirations. Historically, and in our present context, only a select minority of working-class males pursue higher education. Of those who attend, few choose to study STEM, which is often associated with academic rigour, competition and prestige. As a result, we know little about the motivations and experiences of working-class men pursuing STEM degrees. The aim of this paper is to decipher some of the complex interweaving of masculinities, social class and learner identities in STEM through focusing on three key themes from a longitudinal study focused on first-in-family males: (1) desire for financial stability and fulfilment; (2) internalising pressure; (3) struggles with social acclimatisation to university. The research provides some insight into how we can better support males from non-traditional backgrounds who aspire to pathways that contrast greatly with their socio-economic background.

Trade Unions in Contemporary India: Revitalisation Strategies and Migrant Workers

This article explores diverse strategies adopted by Indian trade unions (TUs) to counteract their decline, with a specific focus on migrant labour in contemporary India. While studies in the past have analysed unionism and strategies at the nation-state level, this article draws from interviews with senior leaders of the three central Indian TUs to underscore the diversity of approaches among the TUs. It first draws on Frege and Kelly’s work on union revitalisation to make sense of the organisational strategies adopted by unions to adapt to globalisation and neoliberal policies in the context of India’s transition from a command to a market economy, characterised by intricate institutional arrangements and a prevalence of informal labour. It then uses Alberti’s framework that distinguishes between universalistic and particularistic approaches, with a focus on intersectionality, to explore whether Indian TUs adopt the former approach rooted in class identity, or the latter approach based on the intersecting and complex dimensions of inequality experienced by migrant workers. The article finds that individual union strategies vary on account of their historical origins, ideological underpinnings and relationship with the state and the market. It argues that the disconnect between TUs and the vast migrant workforce in India holds critical significance due to the substantial number of migrant workers in the country, their vulnerability to exploitation, and the role their exclusion has played in the TUs’ decline. The article suggests a combination of universalistic and particularistic approaches to bridge this disconnect, and in doing so it offers a novel disaggregated perspective of TU strategies at the subnational level, scrutinising the approaches of three central Indian TUs through an intersectionality lens and advocating for necessary course correction.

Food metaphors and humour in Nigerian online interaction

AbstractThis article explores the complementary role of Cultural Linguistics in making up for the inadequacies of linguistics‐oriented theories of humour in unpacking culturally embedded meanings in humorous discourse. On the basis of purposively sampled internet memes, it analyses different types of cultural presuppositions in some food metaphors that netizens in Nigerian online interaction appropriate to negotiate gender and class identities, which reflect inherent beliefs, shared values and communicative practices in the Nigerian world. It applies Sharifian’s categorisation of the analytical tools of Cultural Linguistics―cultural schemas, cultural categories and cultural metaphors. The article concludes that mental spaces and conceptual blending are instrumental in forging a holistic conceptual approach, which can account for not only the linguistic but also cultural and discursive meanings of humour as an essentially social and interactional phenomenon.

Water Supply and the Hygiene of the Poorest in G. B. Shaw’s Pygmalion

ABSTRACT In Pygmalion, Shaw describes Eliza as extremely dirty. This article examines Shaw’s views on hygiene for the poorest in Pygmalion, those who were increasingly marginalized in modernizing London in the early 1910s. First, the article examines improvements in London in the first decades of the 1900s. Then, it explores the water schemes of two organizations: the London County Council in the 1890s and the Metropolitan Water Board in the 1900s up to the 1910s. The LCC’s schemes were deeply entangled with the Fabian Society, of which Shaw was a lifelong member. Examining the LCC’s proposals for water municipalization, this article argues that Shaw imbued Pygmalion with social criticism. With his descriptions of the short supply of water in Eliza’s lodgings, which resulted in her unhygienic body and clothing, Shaw ironically dramatized the problematic boundaries of class and gender identity in a social order commonly regarded as natural and even genuine.

Volunteering for a Job: Creativity and Tanzanian Youth

This paper explores motivations behind voluntary activities of youth in Dar es Salaam, Tanzania, during an increasingly common period of ‘waithood,’ characterized by prolonged status as youth and delay in adulthood due to challenges with unemployment. Drawing on ethnographic anthropological fieldwork conducted in 2019, this paper uses stories of two youths from two youth-led organizations located in Dar es Salaam to explore differing motivations for engaging in volunteering. These examples illustrate how volunteering either acts as a stepping-stone to future employment or as a replacement for formal employment, dependent on class identity. It is argued that for Tanzanian youths, volunteering is a creative response to the challenges of waithood. This paper suggests that policymakers and civil society organizations addressing youth issues in Tanzania should recognize the diverse motivations and creative and strategic dimensions of volunteering to better support young people in navigating waithood and their futures.

Synthesis, in silico, and in vitro evaluation of 7-chloro-quinolines designed as myeloperoxidase inhibitors

Given the central role of the myeloperoxidase (MPO) enzyme in inflammation, MPO inhibition is recognized as a promising pharmacological strategy for managing inflammatory-related diseases. This study describes the synthesis, as well as the in silico and in vitro evaluation, of a series of 7‑chloro-quinolines designed as novel MPO inhibitors. Among the synthetic analogs, compounds 13k, 13l, and 14 emerged as the most potent enzyme inhibitors. The in silico pharmacokinetic and toxicological assessments of these compounds pointed to their drug-likeness and favorable pharmacokinetic profiles but raised some concerns about their potential for toxicity. Additionally, in silico analysis elucidated their binding profiles, which were found to be consistent with prior results for several inhibitors previously described, suggesting that the ability of compounds 13k, 13l, and 14 to inhibit MPO mainly arises from interactions with catalytic triad residues. Furthermore, molecular dynamics indicated that compound 14, the most potent MPO inhibitor, consistently maintained close interactions within the active site during the simulations, thereby reaffirming complex stability. This study led to the identification of a novel chemical class of 7‑chloro-quinoline MPO inhibitors, highlighting the potential of derivatives 13k, 13l, and 14 as promising candidates for future in vitro and in vivo studies investigating their safety and anti-inflammatory activities.