Standard Taxonomy Research Articles

Enhance fashion classification of mosquito vector species via self-supervised vision transformer

Vector-borne diseases pose a major worldwide health concern, impacting more than 1 billion people globally. Among various blood-feeding arthropods, mosquitoes stand out as the primary carriers of diseases significant in both medical and veterinary fields. Hence, comprehending their distinct role fulfilled by different mosquito types is crucial for efficiently addressing and enhancing control measures against mosquito-transmitted diseases. The conventional method for identifying mosquito species is laborious and requires significant effort to learn. Classification is subsequently carried out by skilled laboratory personnel, rendering the process inherently time-intensive and restricting the task to entomology specialists. Therefore, integrating artificial intelligence with standard taxonomy, such as molecular techniques, is essential for accurate mosquito species identification. Advancement in novel tools with artificial intelligence has challenged the task of developing an automated system for sample collection and identification. This study aims to introduce a self-supervised Vision Transformer supporting an automatic model for classifying mosquitoes found across various regions of Thailand. The objective is to utilize self-distillation with unlabeled data (DINOv2) to develop models on a mobile phone-captured dataset containing 16 species of female mosquitoes, including those known for transmitting malaria and dengue. The DINOv2 model surpassed the ViT baseline model in precision and recall for all mosquito species. When compared on a species-specific level, utilizing the DINOv2 model resulted in reductions in false negatives and false positives, along with enhancements in precision and recall values, in contrast to the baseline model, across all mosquito species. Notably, at least 10 classes exhibited outstanding performance, achieving above precision and recall rates exceeding 90%. Remarkably, when applying cropping techniques to the dataset instead of utilizing the original photographs, there was a significant improvement in performance across all DINOv2 models studied. This is demonstrated by an increase in recall to 87.86%, precision to 91.71%, F1 score to 88.71%, and accuracy to 98.45%, respectively. Malaria mosquito species can be easily distinguished from another genus like Aedes, Mansonia, Armigeres, and Culex, respectively. While classifying malaria vector species presented challenges for the DINOv2 model, utilizing the cropped images enhanced precision by up to 96% for identifying one of the top three malaria vectors in Thailand, Anopheles minimus. A proficiently trained DINOv2 model, coupled with effective data management, can contribute to the development of a mobile phone application. Furthermore, this method shows promise in supporting field professionals who are not entomology experts in effectively addressing pathogens responsible for diseases transmitted by female mosquitoes.

Stratification economics: historical origins and theoretical foundations

Abstract Stratification economics (SE) investigates how economies are organized around group inequalities, especially by race and gender but also by ethnicity, national origin, religion, sexual orientation, etc. Its historical origins and theoretical foundations have both a structural strand that addresses how and a social behavioural strand. SE’s structural strand goes back to Ricardo and Marx regarding the relationship between growth and distribution, and then draws on recent economic theory of noncompeting groups and dual economy models of labour market segmentation. SE’s structural strand produces an inequality-based understanding of economics’ standard goods taxonomy. The social behavioural strand builds on Du Bois’s psychological wage concept, Veblen’s social ladders theory of emulation, Blumer’s theory of prejudice and stereotyping, and current social identity theory. SE’s social behavioural strand makes it possible to explain how discrimination selectively stigmatizes people’s social identities in order to reinforce existing intergroup inequalities.

A threat analysis for the world’s most threatened turtle (Rafetus swinhoei)

We conducted a comprehensive threat analysis of the Swinhoe’s softshell turtle (Rafetus swinhoei), the most endangered freshwater turtle in the world, historically occurring along river systems in Vietnam and China, but currently almost extinct. Here, our goal was to identify the pressures along two main rivers in Vietnam (Black and Red rivers, both extending into Yunnan, People’s Republic of China), building a conceptual framework to understand the causal relationships among driving forces, threats, and the target species. We involved a panel of experts who identified two priority direct threats in Vietnam, classified following the IUCN standard taxonomy, and showing the highest Magnitude (as a proxy of threat pressure): (i) Habitat loss at nesting sites (LOS; code 1.2 - Commercial & industrial areas) and, (ii) Land conversion due to settlements (LAN; code 1.1 - Housing & urban areas). Threats showed a comparable (i.e., not significantly different) Magnitude in the two rivers (Mann-Whitney U test). Experts also identified the underlying driving forces behind these threats: (i) demographic drivers (due to a rapid population growth in the last decades) causing LAN and LOS, as the priority threats, but also sand mining, and water pollution; (ii) economic drivers induced by high poverty in local populations and causing harvesting (fishing activities and related markets), the needs of power supply for economic activities (e.g., dams), and recreational activities; (iii) ethical drivers linked to conservation project teams (limited funds and divergent points about strategies to carry out). Preliminary data for China suggest HAR (Harvesting by native fishers; code 5.4) and POL (water pollution; code 9.2) as priority threats. Threat analysis is an useful tool in the early stages of a conservation project during the context analysis, helping to define priorities for conservation and management.

Development of machine learning models for classification of tenders based on UNSPSC standard procurement taxonomy

Development of machine learning models for classification of tenders based on UNSPSC standard procurement taxonomy

Smart Classroom: A Review and Research Agenda

The presented systematic review aims to adopt a methodological approach of providing quantitative and qualitative knowledge on the emerging notion of the smart classroom. The analysis is based on an assessment of 572 publications published in peer-reviewed journals between 2000 and 2021. Citation networks, cocitation analysis, and publishing patterns have been used to identify important research works, characterize the intellectual structure of the domains, and highlight research gaps. Bibliometric analysis is used to identify the most notable journals, authors, nations, articles, and themes, which was followed by a comprehensive analysis of various disciplines using standard terminology and taxonomy of the papers. Emerging topics including smart interaction and positive engagement, intelligent evaluation, and inter-connected physical surroundings have been explored. Following the exploration of a conceptual framework, potential topics of research have been identified. This research will assist practitioners, educators, administrators, and academic researchers in understanding the fundamentals of smart classrooms and identifying pertinent topics for future research exploration.

Does XBRL Tagging Indicate Disclosure Quality? The Relationship Between XBRL Standard and Extension Tags and Stock Return Synchronicity

ABSTRACT We propose new measures of financial disclosure quality based on XBRL standard and extension tag counts. XBRL is designed to allow users to analyze more financial statement detail, thereby increasing reporting transparency. Thus, firms that use more XBRL standard tags should produce more detailed and comparable financial reports. To test this assertion, we examine the association between XBRL tag counts and stock return synchronicity, which measures the market’s reaction to the quality of firms’ disclosures. We find that firms that use more standard taxonomy tags in their 10-K reports have higher stock return synchronicity after the 10-K filing. However, we find that stock return synchronicity decreases as XBRL extension tag counts increase, suggesting that the use of extension tags reduces disclosure quality. Our findings contribute to the growing body of research on XBRL disclosure. Data Availability: Data are available from the public sources cited in the text.

A new epilithic bromeliad (Stigmatodon, Tillandsioideae) from Pedra dos Três Pontões, Espírito Santo, Brazil, with an emended combination for the genus

Background and aims – Stigmatodon (Bromeliaceae) is a monophyletic genus currently comprising 33 species, all endemic to rocky outcrops, mainly inselbergs, from the Atlantic Forest and campos rupestres of the Espinhaço range, Brazil. Material and methods – Our fieldwork in the inselbergs of the Atlantic Forest of the state of Espírito Santo led to the discovery of a new Stigmatodon species with a tubo-laciniate stigma type. Standard herbarium taxonomy practices were adopted to study the novelty. Morphological data were obtained from herbarium specimens and fresh material collected in the field. Key results – Stigmatodon lemeanus is here described and illustrated. Diagnostic characters and affinities of the new species are discussed, accompanied by notes on its ecology, geographic distribution, and conservation status. A key to the species of Stigmatodon from Espírito Santo state is provided. The novelty is similar to S. goniorachis from coastal inselbergs of Rio de Janeiro and S. attenuatoides, another inselberg endemic from southern Espírito Santo. Stigmatodon lemeanus is preliminarily assessed as Vulnerable (VU) according to the IUCN Red List criteria. Additionally, we present a new combination of Tillandsia oligantha in Stigmatodon, correcting a nomenclatural error.

Development of Machine Learning Models for Classification of Tenders based on UNSPSC Standard Procurement Taxonomy

Development of Machine Learning Models for Classification of Tenders based on UNSPSC Standard Procurement Taxonomy

Mechanism-based groups of children with ADHD are associated with distinct domains of impairment

Person-oriented analyses are commonly used to identify subgroups of children with mental health conditions in the hopes that they will meaningfully inform the taxonomy, assessment, and treatment of psychological disorder. However, whether these data-driven groups are demonstrably better at predicting important aspects of adaptive functioning than standard DSM taxonomy has not been established. Using Attention-Deficit-Hyperactivity-Disorder (ADHD) as a model condition, we utilized dimensions of personality and cognitive ability to identify person-centered profiles of school-aged children (N=246) and evaluated the association of these profiles with critical areas of adaptive functioning. A single profile (“Conscientious”) represented non-ADHD controls and was characterized by faster drift rate and higher executive functioning scores. Three profiles (“Disagreeable,” “Negative Emotionality,” and “Extraverted”) were identified for children with ADHD. Drift rate, but not executive functioning, distinguished among ADHD profiles, which were also distinctly associated with comorbid externalizing and internalizing psychopathology, social skills, and academic achievement. In contrast, the Diagnostic and Statistical Manual (DSM) presentations were not informative and showed similar patterns of impairment across domains. Person-centered profiles of children with ADHD are associated with distinct adaptive functioning deficits and may be useful in informing clinical practice.

Truth and Transparency, Compromise and Climate Change

Truth and Transparency, Compromise and Climate Change

Outcomes and outcome measurement instruments reported in randomised controlled trials of anxiety disorder treatments in children and adolescents: a scoping review protocol

IntroductionPaediatric anxiety disorders (AD) are prevalent and persistent mental health conditions worldwide affecting between 10% and 20% of children and adolescents. Despite the high prevalence of paediatric AD, there is...

Using extended reality (XR) for medical training and real-time clinical support during deep space missions

Medical events can affect space crew health and compromise the success of deep space missions. To successfully manage such events, crew members must be sufficiently prepared to manage certain medical conditions for which they are not technically trained. Extended Reality (XR) can provide an immersive, realistic user experience that, when integrated with augmented clinical tools (ACT), can improve training outcomes and provide real-time guidance during non-routine tasks, diagnostic, and therapeutic procedures. The goal of this study was to develop a framework to guide XR platform development using astronaut medical training and guidance as the domain for illustration. We conducted a mixed-methods study—using video conference meetings (45 subject-matter experts), Delphi panel surveys, and a web-based card sorting application—to develop a standard taxonomy of essential XR capabilities. We augmented this by identifying additional models and taxonomies from related fields. Together, this “taxonomy of taxonomies,” and the essential XR capabilities identified, serve as an initial framework to structure the development of XR-based medical training and guidance for use during deep space exploration missions. We provide a schematic approach, illustrated with a use case, for how this framework and materials generated through this study might be employed.

Increasing knowledge on the diversity of canelas-de-ema in the campo rupestre: two new species of Vellozia (Velloziaceae) from the southern Espinhaço Range, Brazil

Background and aims – Two new species of Vellozia (Velloziaceae) are here described and illustrated, Vellozia albohexandra and V. mellosilvae. These new species are morphologically similar to Vellozia armata, V. luteola, and V. inselbergae, probably belonging to the same informal group. Material and methods – Morphological and anatomical descriptions were based on herbarium specimens and in situ observations. Standard taxonomy and plant anatomy practices and methods were applied. Key results – Vellozia albohexandra can be easily distinguished from the other species of the group of V. luteola by its sessile flowers with white and smaller petals and sepals, six stamens, and smaller style and stigma. The species is endemic to the Cristália municipality, Minas Gerais state, and has been classified as Data Deficient according to IUCN criteria. Vellozia mellosilvae shares morphological affinities with V. armata, but it is distinguished by the leaves with serrate margin and abaxial furrows, longer and evident pedicel, and larger petals and sepals. This species is endemic to the Itacambira municipality, and should be considered Critically Endangered.

The Australian National Species List steps up for biodiversity conservation

The Australian National Species List (AuNSL) will bring together authoritative national taxonomies and supporting nomenclatural data for flora, fauna, fungi and algae. These data enable biodiversity infrastructures, such as the Atlas of Living Australia, to store information about taxa against a standard, permanently resolvable taxonomy, and to create linkages between them. The Biodiversity Data Repository (BDR) is a new Australian government infrastructure supporting environmental assessments under Australia's Environment Protection and Biodiversity Conservation Act. The BDR will bring together biodiversity data assets from a range of sources and enable decision making to be based on a more holistic view of taxa in Australia. To achieve its objectives, the BDR requires the ability to align disparate taxonomies to a national standard. To support the BDR we have restructured and consolidated the constituent datasets of the AuNSL and added a GraphQL interface from which we can provide machine access to the full suite of taxonomic and nomenclatural entities in the data and the linkages between them. Currently we provide a simple name check service for aligning supplied names with the standard AuNSL taxonomy and a full taxonomic backbone extract as a SKOS concept scheme expressed in JSON-LD. We are working towards an expanded set of taxonomic and nomenclatural services and a more generalised and complete graph of the AuNSL taxonomy, which can serve an increasing number of initiatives including the Australian Traits database (AusTraits), the Australian National DNA Library, and sensitive species data exchange mechanisms.

XII National Congress of the Research Group in Psychosomatics (RGP) October 21 and 22, 2022 - The clinimetric method.

This Supplement of La Clinica Terapeutica includes abstracts of lectures, symposia, workshops, clinical case presen-tations and posters of the XII National Congress of the Research Group in Psychosomatics (RGP). The Congress is characterized by "The clinimetric method". It is a tribute to Alvan Feinstein who 40 years ago introduced clinimetrics as a discipline aimed at creating indices, rating scales and other expressions to describe or measure symptoms, physical signs and other clinical phenomena. The standard taxonomy, in fact, did not include, and still does not include, the patterns of symptoms, the severity of the disease, the effects of comorbid manifestations, the timing of the phenomena, the rate of disease progression, functional capacity and other clinical characteristics which demarcate the main prognostic and therapeutic differences between patients who otherwise would appear deceptively similar because they share the same diagnosis and laboratory results. Feinstein also added the psychosocial impact of the disease and treatment on individual, family and interpersonal relationships, including physical activity, the joys and pains of everyday life. Psychosomatics represents an extraordinary opportunity to improve clinical practice in medicine, psychiatry and clinical psychology by integrating biological, psychological and social factors. The bio-psycho-social model is still the theoretical and practical core of psychosomatics. It allows clinicians to see disease as the result of mechanisms of interaction at the cellular, interpersonal and environmental levels that include personality and familiarity. The congress organized by the GRP for 2022 highlights clinimetrics as a science at the service of psychosomatics capable of providing the clinical tools that allow a complete and accurate assessment according to the principles of the bio-psycho-social model. The abstracts describe innovative studies and reflections on the most current and hot topics of psychosomatics. The crucial role of clini-metrics, and of the specific type of assessment it makes possible in psychosomatics, are underlined in research and by the importance of proposing integrated treatments. An increasing number of studies suggest that the clinical process leading to diagnosis should be based on a comprehensive and accurate assessment based on clinically useful indices. Such indices are expected to be, among the others, sensitive in recording changes over time, capable of providing additional information according to the principle of incremental validity, able to investigate the person in the complexity linked to suffering and resources. This approach can be an antidote to the reductionist models that clash with clinical reality and that make the patient's visit a kind of distracted listening and subsequent random prescription. Clinimetrics and psychosomatic assessment thus become essential in clinical practice and research. The abstracts document how psychosomatics in clinical practice is more timing than ever and adequate for give a home to researchers and clinicians who want to venture off the beaten and clinically unsatisfactory paths of standard nosography.

XII National Congress of the Research Group in Psychosomatics (RGP) October 21 and 22, 2022 - The clinimetric method.

This Supplement of La Clinica Terapeutica includes abstracts of lectures, symposia, workshops, clinical case presen-tations and posters of the XII National Congress of the Research Group in Psychosomatics (RGP). The Congress is characterized by "The clinimetric method". It is a tribute to Alvan Feinstein who 40 years ago introduced clinimetrics as a discipline aimed at creating indices, rating scales and other expressions to describe or measure symptoms, physical signs and other clinical phenomena. The standard taxonomy, in fact, did not include, and still does not include, the patterns of symptoms, the severity of the disease, the effects of comorbid manifestations, the timing of the phenomena, the rate of disease progression, functional capacity and other clinical characteristics which demarcate the main prognostic and therapeutic differences between patients who otherwise would appear deceptively similar because they share the same diagnosis and laboratory results. Feinstein also added the psychosocial impact of the disease and treatment on individual, family and interpersonal relationships, including physical activity, the joys and pains of everyday life. Psychosomatics represents an extraordinary opportunity to improve clinical practice in medicine, psychiatry and clinical psychology by integrating biological, psychological and social factors. The bio-psycho-social model is still the theoretical and practical core of psychosomatics. It allows clinicians to see disease as the result of mechanisms of interaction at the cellular, interpersonal and environmental levels that include personality and familiarity. The congress organized by the GRP for 2022 highlights clinimetrics as a science at the service of psychosomatics capable of providing the clinical tools that allow a complete and accurate assessment according to the principles of the bio-psycho-social model. The abstracts describe innovative studies and reflections on the most current and hot topics of psychosomatics. The crucial role of clini-metrics, and of the specific type of assessment it makes possible in psychosomatics, are underlined in research and by the importance of proposing integrated treatments. An increasing number of studies suggest that the clinical process leading to diagnosis should be based on a comprehensive and accurate assessment based on clinically useful indices. Such indices are expected to be, among the others, sensitive in recording changes over time, capable of providing additional information according to the principle of incremental validity, able to investigate the person in the complexity linked to suffering and resources. This approach can be an antidote to the reductionist models that clash with clinical reality and that make the patient's visit a kind of distracted listening and subsequent random prescription. Clinimetrics and psychosomatic assessment thus become essential in clinical practice and research. The abstracts document how psychosomatics in clinical practice is more timing than ever and adequate for give a home to researchers and clinicians who want to venture off the beaten and clinically unsatisfactory paths of standard nosography.

A Survey of Smart Classroom Literature

Recently, there has been a substantial amount of research on smart classrooms, encompassing a number of areas, including Information and Communication Technology, Machine Learning, Sensor Networks, Cloud Computing, and Hardware. Smart classroom research has been quickly implemented to enhance education systems, resulting in higher engagement and empowerment of students, educators, and administrators. Despite decades of using emerging technology to improve teaching practices, critics often point out that methods miss adequate theoretical and technical foundations. As a result, there have been a number of conflicting reviews on different perspectives of smart classrooms. For a realistic smart classroom approach, a piecemeal implementation is insufficient. This survey contributes to the current literature by presenting a comprehensive analysis of various disciplines using a standard terminology and taxonomy. This multi-field study reveals new research possibilities and problems that must be tackled in order to integrate interdisciplinary works in a synergic manner. Our analysis shows that smart classroom is a rapidly developing research area that complements a number of emerging technologies. Moreover, this paper also describes the co-occurrence network of technological keywords using VOSviewer for an in-depth analysis.

Big picture: analysis of DDoS attacks map - systems and network, cloud computing, SCADA systems, and IoT

Distributed denial-of-service (DDoS) attacks are among the toughest security issues nowadays. These attacks are launched at any time and can impact any part of a network's operations or IT resources. Because of the seriousness of these attacks, many countermeasures have been developed by both the private sector and the research community. Despite the availability of many research efforts that suggested DDoS attacks classifications, the multitude, diversity, and variety of both the attacks and their countermeasures have the consequence that no standard taxonomy exists. In this paper, we introduce an updated and structured taxonomy of both DDoS attacks and their countermeasures. The novelty of this work stems from the fact that it covers different dimensions of tackling DDoS attacks in the four main technology areas: systems and network, cloud computing, SCADA, and IoT, with the main aim of providing an all-in-one comprehensive reference for ongoing and future security research.

Recommendation Systems: An Insight Into Current Development and Future Research Challenges

Research on recommendation systems is swiftly producing an abundance of novel methods, constantly challenging the current state-of-the-art. Inspired by advancements in many related fields, like Natural Language Processing and Computer Vision, many hybrid approaches based on deep learning are being proposed, making solid improvements over traditional methods. On the downside, this flurry of research activity, often focused on improving over a small number of baselines, makes it hard to identify reference methods and standardized evaluation protocols. Furthermore, the traditional categorization of recommendation systems into content-based, collaborative filtering and hybrid systems lacks the informativeness it once had. With this work, we provide a gentle introduction to recommendation systems, describing the task they are designed to solve and the challenges faced in research. Building on previous work, an extension to the standard taxonomy is presented, to better reflect the latest research trends, including the diverse use of content and temporal information. To ease the approach toward the technical methodologies recently proposed in this field, we review several representative methods selected primarily from top conferences and systematically describe their goals and novelty. We formalize the main evaluation metrics adopted by researchers and identify the most commonly used benchmarks. Lastly, we discuss issues in current research practices by analyzing experimental results reported on three popular datasets.

Developing Pulmonary Rehabilitation for COVID-19: Are We Linked with the Present Literature? A Lexical and Geographical Evaluation Study Based on the Graph Theory.

The Coronavirus Disease 2019 (COVID-19) pandemic is a severe ongoing global emergency. Despite high rates of asymptomatic patients, in many cases, the infection causes a rapid decline in pulmonary function due to an acute respiratory distress-like syndrome, leading to multi-organ failure and death. To date, recommendations about rehabilitation on COVID-19 are based on clinical data derived from other similar lung diseases. Rehabilitation literature lacks a standard taxonomy, limiting a proper evaluation of the most effective treatments for patients after COVID-19 infection. In this study, we assessed the clinical and rehabilitative associations and the geographical area involved in interstitial lung diseases (ILD) and in COVID-19, by a mathematical analysis based on graph theory. We performed a quantitative analysis of the literature in terms of lexical analysis and on how words are connected to each other. Despite a large difference in timeframe (throughout the last 23 years for ILD and in the last 1.5 years for COVID-19), the numbers of papers included in this study were similar. Our results show a clear discrepancy between rehabilitation proposed for COVID-19 and ILD. In ILD, the term “rehabilitation” and other related words such as “exercise” and “program” resulted in lower values of centrality and higher values of eccentricity, meaning relatively less importance of the training during the process of care in rehabilitation of patients with ILD. Conversely, “rehabilitation” was one of the most cited terms in COVID-19 literature, strongly associated with terms such as “exercise”, “physical”, and “program”, entailing a multidimensional approach of the rehabilitation for these patients. This could also be due to the widespread studies conducted on rehabilitation on COVID-19, with Chinese and Italian researchers more involved. The assessment of the terms used for the description of the rehabilitation may help to program shared rehabilitation knowledge and avoid literature misunderstandings.