Set Of Categories Research Articles

Generating Python Type Annotations from Type Inference: How Far Are We?

In recent years, dynamic languages such as Python have become popular due to their flexibility and productivity. The lack of static typing makes programs face the challenges of fixing type errors, early bug detection, and code understanding. To alleviate these issues, PEP 484 introduced optional type annotations for Python in 2014, but unfortunately, a large number of programs are still not annotated by developers. Annotation generation tools can utilize type inference techniques. However, several important aspects of type annotation generation are overlooked by existing works, such as in-depth effectiveness analysis, potential improvement exploration, and practicality evaluation. And it is unclear how far we have been and how far we can go. In this paper, we set out to comprehensively investigate the effectiveness of type inference tools for generating type annotations, applying three categories of state-of-the-art tools on a carefully-cleaned dataset. First, we use a comprehensive set of metrics and categories, finding that existing tools have different effectiveness and cannot achieve both high accuracy and high coverage. Then, we summarize six patterns to present the limitations in type annotation generation. Next, we implement a simple but effective tool to demonstrate that existing tools can be improved in practice. Finally, we conduct a controlled experiment showing that existing tools can reduce the time spent annotating types and determine more precise types, but cannot reduce subjective difficulty. Our findings point out the limitations and improvement directions in type annotation generation, which can inspire future work.

The Development and Content Validation of Brief ICF Category Sets for 6 - 12-Year-Old Children with Cerebral Palsy, from the Perspective of Iranian Occupational Therapists

Background: There is uncertainty in identifying which aspects of functioning should be prioritized in the clinical brief assessment of children with cerebral palsy (CP). Brief ICF category sets specify the essential aspects of functioning that should be addressed in such assessments. Objectives: This study aimed to develop five brief ICF category sets based on the functional limitations of children with CP, as viewed by Iranian occupational therapists (OTs). Methods: This cross-sectional, multi-method study was conducted from January to May 2022 in Iran. Nineteen OTs were recruited through purposive sampling for a Delphi process, and ten OTs through snowball sampling for an expert panel, all experienced in CP and ICF. The Delphi involved two rounds of electronic surveys, where participants identified categories that should be minimally addressed in brief assessments of children aged 6 - 12 with CP based on their functional limitations. The content validity of these sets was then quantitatively evaluated by the expert panel. Results: Most confirmed categories in the gross and fine motor brief sets pertained to body structure and function, while those in the eating-and-drinking and communication-function brief sets related to cognition and motor reflexes. Categories in the visual function brief set mostly pertained to activity, participation, and environmental factors. Content validity ratio (CVR) and item-content validity indexes (I-CVI) ranged from 0.80 to 1 across all categories/brief sets, with scale-content validity index/Average (S-CVI/Ave) ranging from 0.95 to 0.98. Conclusions: These functional-based ICF brief sets are the first developed for children with CP in this age group and provide occupational therapists with tools to address crucial aspects of functioning, tailored to specific functional limitations. However, cultural biases and the generalizability of these brief sets remain limitations.

Object search by a concept-conditioned object detector

Object detectors are used for searching all objects belonging to a pre-defined set of categories contained in a given picture. However, users are often not interested in finding all objects, but only those that pertain to a small set of categories or concepts. Nowadays, the standard approach to solve this task involves initially employing an object detector to identify all objects within the image, followed by refining the outcomes to retain only the ones of interest. Nevertheless, the object detector does not take advantage of the user’s prior intent that, when used, can potentially improve the detection performance of the model. This work presents a method to condition an existing object detector with the user’s intent, encoded as one or more concepts from the WordNet graph, to find just those objects of interest. The proposed approach takes advantage of existing datasets for object detection without the need for new annotations, and it allows to adapt the already existing object detector models with minor changes. The evaluation, performed on the COCO and the Visual Genome datasets considering several object detector architectures, shows that conditioning the search on concepts is actually beneficial. The code and the pre-trained model weights are released at: https://github.com/drigoni/Concept-Conditioned-Object-Detector.

Foundational features of indigenous pregnancy care: Lessons learned from indigenous pregnancy care providers

ProblemIndigenous populations experience higher odds of poor maternal and infant health outcomes than non-Hispanic White mothers yet have lower odds of receiving adequate prenatal care. BackgroundMany Indigenous communities rely on modern Western medical institutions to provide pregnancy related health care. These systems were not developed with or for Indigenous communities and often fail to meet the needs of Indigenous pregnant patients. Offering culturally congruent models of care may increase prenatal care utilization. Question, hypothesis or aimThis paper used qualitative inquiry to identify Indigenous approaches to caring for pregnancy. MethodsOur team conducted 16 semi-structured individual interviews and one group interview with a total of 19 respondents. To arrive at thematic categories, the research team engaged in a modified pile sorting technique. The final set of categories, along with sub-themes, descriptions and example quotes, were sent to interviewees for approval. FindingsTen Foundational Features of Indigenous Pregnancy Care were identified. These covered themes related to Indigenous cultural practices, relationships, Indigenous sovereignty, local Indigenous community, full spectrum care, wholistic care, birthing person's wisdom, power and autonomy, flexibility, historical trauma, and cultural awareness. DiscussionModern midwifery care delivered by Indigenous practitioners may partially bridge the cultural gap; however, intentional effort is needed to integrate Indigenous ways into medical doctor practice models and facilities. ConclusionThis paper identifies ten foundational features of Indigenous pregnancy care and demonstrates the importance of recognizing the effects of trauma and providing opportunities for healing, upholding sovereignty, and centering relationships when caring for Indigenous pregnancies.

N-spherical Functors and Tensor Categories

Abstract We apply the recently introduced notion, due to Dyckerhoff, Kapranov, and Schechtman, of $N$-spherical functors of stable infinity categories, which generalise spherical functors, to the setting of monoidal categories. We call an object $N$-bounded if the corresponding regular endofunctor on the derived category is $N$-spherical. Besides giving new examples of $N$-spherical functors, the notion of $N$-bounded objects gives surprising connections with Jones-Wenzl idempotents, Frobenius-Perron dimensions, and central conjectures in the field of symmetric tensor categories in positive characteristic.

ON THE ISSUE OF THE ESSENCE OF ADMINISTRATIVE AND LEGAL REGULATION OF CITIZENS' PARTICIPATION IN THE PROTECTION OF PUBLIC ORDER

The protection of public order is one of the most important functions of the state, with proper implementation of which the normal progressive development of society is possible. The participation of citizens in the protection of public order is often unreasonably overlooked by scientific research, since attention is paid only to the activities of law enforcement agencies in this area. We believe that the potential of citizens' participation in the protection of public order is underestimated and needs additional scientific analysis and improvement of regulatory regulation of such activities. The article examines the essence of the concept of administrative and legal regulation of citizens' participation in the protection of public order by studying its content as a set of legal categories "participation of citizens in the protection of public order" and "mechanism of administrative and legal regulation". The analysis made it possible to formulate the author's definitions of the concepts "participation of citizens in the protection of public order" and "administrative and legal regulation of citizens' participation in the protection of public order".

Exploration of an Open Vocabulary Model on Semantic Segmentation for Street Scene Imagery

This study investigates the efficacy of an open vocabulary, multi-modal, foundation model for the semantic segmentation of images from complex urban street scenes. Unlike traditional models reliant on predefined category sets, Grounded SAM uses arbitrary textual inputs for category definition, offering enhanced flexibility and adaptability. The model’s performance was evaluated across single and multiple category tasks using the benchmark datasets Cityscapes, BDD100K, GTA5, and KITTI. The study focused on the impact of textual input refinement and the challenges of classifying visually similar categories. Results indicate strong performance in single-category segmentation but highlighted difficulties in multi-category scenarios, particularly with categories bearing close textual or visual resemblances. Adjustments in textual prompts significantly improved detection accuracy, though challenges persisted in distinguishing between visually similar objects such as buses and trains. Comparative analysis with state-of-the-art models revealed Grounded SAM’s competitive performance, particularly notable given its direct inference capability without extensive dataset-specific training. This feature is advantageous for resource-limited applications. The study concludes that while open vocabulary models such as Grounded SAM mark a significant advancement in semantic segmentation, further improvements in integrating image and text processing are essential for better performance in complex scenarios.

Exploring Psychosocial Needs of Patients with Cancers through the Lens of the Physicians and Nurses: A Qualitative Study

Aims. To explore the experience of nurses and physicians regarding psychosocial needs of patients with cancer and to describe their perception according to professional category and clinical setting. Design. A qualitative descriptive study. Method. 14 nurses and 12 physicians were selected from three hospital clinical units and four primary care centers in northern Spain. Data were collected using semistructured interviews. Content analysis was performed using open coding. Reporting of findings followed the COREQ checklist. Results. Four themes were identified: the needs of patients with cancer, psychosocial care provided by health professionals, difficulties addressing psychosocial needs, and available resources. According to nurses and physicians, being diagnosed with cancer involves a radical life-changing process, with a profound impact at the psychosocial level. Within the field of psychosocial care, the role perceived by each profession was different. Thus, nurses highlighted the need for these patients to receive emotional support and care, although limited importance is given to psychosocial needs. The role of physicians was more focused on referring these patients to other health professionals. The lack of training or time was one of the main difficulties perceived by the professionals. The family is a fundamental resource and, overall, patients are provided with limited information about other psychosocial resources. At the hospital, the emphasis is placed on physical needs and health professionals experience greater burnout and fear of compassion fatigue. Primary care teams could, therefore, have a primary role in addressing psychosocial needs due to their understanding of each person’s context and personal circumstances. Conclusions. It is essential for nurses and physicians to consider the psychosocial needs of patients with cancer. However, these needs are not always adequately addressed. Further resources are required to reduce the workload, increase the training of health professionals, and introduce organizational changes to consider psychosocial needs during routine care.

Identifying the Severity of Criminal Activity in Society Using Picture Fuzzy Baire Space

In this paper, the idea of picture fuzzy Baire space is explored and its properties are examined. The features of picture fuzzy semi-closed and semi-open sets, picture fuzzy nowhere dense sets, picture fuzzy first and second category sets, picture fuzzy residual sets, picture fuzzy submaximal spaces, picture fuzzy strongly irresolvable spaces, picture fuzzy Gδ set, picture fuzzy Fσ set, and picture fuzzy regular closed sets are analyzed. To understand the concepts, some examples are provided. An algorithm using picture fuzzy Baire space is developed to address real-world scenarios. This method is more effective in assessing criminal activity as it identifies an individual who has committed a more serious offense. This algorithmic approach proves its effectiveness in navigating the complexities of practical examples, showcasing its potential for real-world applications.

BDNF plasma concentrations, cognitive test performances and lifetime suicide ideation in psychotic disorders: a secondary analysis

IntroductionPsychotic disorders present a significant lifetime risk for suicide. Past estimates suggest that up to 25-50% of individuals with schizophrenia (SCZ) may attempt suicide during their lifetime. A growing body of literature indicates that the level of cognitive performances may be associated with a differing level of lifetime suicide attempts, albeit inconsistently depending on the diagnostic category and study setting. However, the vast majority of the literature in the field is composed of cross-sectional studies, limiting the overall interpretation of the available evidence.ObjectivesIn the present study, we probed the possible association of BDNF plasma levels, cognitive functions assessed through the Brief Assessment of Cognition in Schizophrenia (BACS) and lifetime suicide ideation and/or attempts (LSI+LSA). More specifically, we tested whether such association would persist during the 2 years follow-up divided in 5 different timepoints at 6-month intervals, if present.MethodsThe present study represents a secondary analysis of a previously described cohort (Manchia et al. Brain Sci. 2022 Dec 4;12(12):1666). The sample comprised 105 subjects with SZC or schizoaffective disorder. We employed the 1) Wilcoxon test for non-parametric data 2) linear modelling to test the possible association of BACS-defined cognitive task performances with LSI+LSA. We also investigated if either BDNF plasma levels or four tested BDNF SNP genes would mediate this association.ResultsFrom a total of 105 subjects, data relevant to the analysis were available for 89 subjects. We observed a significant association between BACS-Letter fluency task (BACS-LF) with LSI+LSA, persisting even when adjusting for gender, duration of untreated psychosis, total Positive and Negative Syndrome Scale score, age, chlorpromazine equivalents of antipsychotic therapy and for the effect of time. The association remained significant even when adjusting with the Bonferroni-Holms method for multiple comparisons (p=0.002). No association was found either for BDNF plasma levels or the tested BDNF genes for the tested outcomes.ConclusionsIn our sample, higher BACS-LF performances appeared to be associated with a higher lifetime risk of LSI+LSA. This report adds to the previous literature suggesting that different cognitive performance levels may represent one of the many chronic risk factors associated with LSI+LSA, and that may ultimately complexly interact with more proximal ones.Disclosure of InterestNone Declared

Simple Image-Level Classification Improves Open-Vocabulary Object Detection

Open-Vocabulary Object Detection (OVOD) aims to detect novel objects beyond a given set of base categories on which the detection model is trained. Recent OVOD methods focus on adapting the image-level pre-trained vision-language models (VLMs), such as CLIP, to a region-level object detection task via, eg., region-level knowledge distillation, regional prompt learning, or region-text pre-training, to expand the detection vocabulary. These methods have demonstrated remarkable performance in recognizing regional visual concepts, but they are weak in exploiting the VLMs' powerful global scene understanding ability learned from the billion-scale image-level text descriptions. This limits their capability in detecting hard objects of small, blurred, or occluded appearance from novel/base categories, whose detection heavily relies on contextual information. To address this, we propose a novel approach, namely Simple Image-level Classification for Context-Aware Detection Scoring (SIC-CADS), to leverage the superior global knowledge yielded from CLIP for complementing the current OVOD models from a global perspective. The core of SIC-CADS is a multi-modal multi-label recognition (MLR) module that learns the object co-occurrence-based contextual information from CLIP to recognize all possible object categories in the scene. These image-level MLR scores can then be utilized to refine the instance-level detection scores of the current OVOD models in detecting those hard objects. This is verified by extensive empirical results on two popular benchmarks, OV-LVIS and OV-COCO, which show that SIC-CADS achieves significant and consistent improvement when combined with different types of OVOD models. Further, SIC-CADS also improves the cross-dataset generalization ability on Objects365 and OpenImages. Code is available at https://github.com/mala-lab/SIC-CADS.

A close analysis of eight flourishing measures

ABSTRACT Scholarly interest in flourishing has recently burgeoned, leading many scholars to develop measures of flourishing. We closely analyzed the content of eight systematically chosen, prominent inventories of flourishing, thriving, or rich well-being. Some instruments contain subscales, and some consist of lists of items. Therefore, we utilized a set of categories to compare the larger components of the eight inventories based primarily on the domains of the Psychological Well-Being Scales, one of the first modern measures of flourishing. Then we compare items across inventories in the most common components. Despite apparent structural similarity, we argue that flourishing instruments demonstrate significant variation at both the component and the item-levels. This indicates a lack of consensus among flourishing scholars as to what flourishing is, and this absence of consensus may lead to an unnecessarily fragmented research domain. We conclude by advocating for consensus building and addressing what a consensus on flourishing might require.

Social dimension of the circular economy: Impact categories through fuzzy Delphi method

AbstractThe scholarly literature highlights the relevance of the social dimension of the circular economy (CE); yet the empirical analysis of this issue has been overlooked. This work sheds light empirically on this gap with a fuzzy Delphi study carried out in a region with strong institutional support for this paradigm. Through the consensus of 25 experts, a set of social impact categories of the CE was scrutinized. The results contribute to widening the current quantitative vision on the employment generated by CE, through the exploration of its qualitative aspects. According to our findings, technological innovation in high‐skilled employment appears to be crucial. Likewise, the results anticipate impacts derived from collaboration among stakeholders in a circular context still at an incipient stage. The expert panel also highlights the relevance of socio‐cultural and behavioral changes. Implications for public policy makers and other stakeholders are also analyzed, namely the development of a monitoring framework of the social dimension of the CE.

A Study on the Punishment Day Calculation Method and Related Issues in the “Punishment Day” Section of the Mawangdui Manuscript Yinyang wuxing A

Abstract First, through an analysis of the binary categorization of the heavenly stems and the earthly branches in calculations and arts (shushu 數術) literature in transmitted and excavated texts, this paper argues that the two characters meng 䖟（孟） and zhong 中（仲） next to the branches in the Punishment Day diagram do not connote substantive meaning, but constitute a set of binary categories in the same vein as the binarisms yin/yang, hard/soft, man/woman, female/male, heaven/earth, punishment/virtue, and so on. Next, this paper points out a mistake made in the previous calculation of punishment days in the Changsha Mawangdui Han mu jianbo jicheng before putting forward a new calculation method. Based on the new method, we find that the two columns of stem-branch binomes inscribed on the manuscript should be construed such that the stem-branch binomes in one column represent the punishment days resulting from the movements of a stem and a branch starting from contiguous branch positions, and those in the other column represent the punishment days resulting from the movements of a stem and a branch starting from branch positions six branches apart. The reason for the emphasis on the punishment days resulting from these two cases lies in the fact that the branches of these punishment days are the grave branches (muchen 墓辰) in the Three Unions Scheme of the Five Agents. The meaning of the grave branches as vanishing and decaying resonates with the activities of military display, battling, attacking, killing, imprisonment, and demolishing constructions that may be undertaken on punishment days. Therefore, particular attention is paid to the punishment days identified by the four grave branches. In the end, this paper argues against the view that correlates Punishment Day with Meeting Day. This paper maintains that despite their similarity on the surface, they are in fact two different types of calendar spirits and should not be confused.

Classification aggregation without unanimity

A classification is a surjective mapping from a set of objects to a set of categories. A classification aggregation function aggregates every vector of classifications into a single one. We show that every citizen sovereign and independent classification aggregation function is essentially a dictatorship. This impossibility implies an earlier result of Maniquet and Mongin (2016), who show that every unanimous and independent classification aggregation function is a dictatorship. The relationship between the two impossibilities is reminiscent to the relationship between Wilson’s (1972) and Arrow’s (1951) impossibilities in preference aggregation. Moreover, while the Maniquet-Mongin impossibility rests on the existence of at least three categories, we propose an alternative proof technique that covers the case of two categories, except when the number of objects is also two. We also identify all independent and unanimous classification aggregation functions for the case of two categories and two objects.

Applications of reduced and coreduced modules I

This is the first in a series of papers highlighting the applications of reduced and coreduced modules. Let $R$ be a commutative unital ring and $I$ be an ideal of $R$. We show that $I$-reduced $R$-modules and $I$-coreduced $R$-modules provide a setting in which the Matlis-Greenless-May (MGM) Equivalence and the Greenless-May (GM) Duality hold. These two notions have been hitherto only known to exist in the derived category setting. We realise the $I$-torsion and the $I$-adic completion functors as representable functors and under suitable conditions compute natural transformations between them and other functors.

A Human-Scale Set of Categories for the Historical Thesaurus of English

ABSTRACT: The Historical Thesaurus of English ( HT ) categorizes the English vocabulary into meaning-based categories containing synonymous or near-synonymous lexical items. Its extensive hierarchical categorization scheme (c. 235,000 categories) is, however, unwieldy for new and more casual users. Additionally, it can be too fine-grained for implementation in natural language processing tools, leading them to produce over-specified results where humans recognize ambiguity. This article outlines the reasoning and methodology behind the creation of a truncated semantic hierarchy, known by the HT editors as the thematic category set. Development of the category set was guided by evaluation of which concepts are too technical or too general to be relevant to the average user, with cut-offs imposed on the hierarchy at an intermediate human-scale level. The result is a hybrid category set which combines organisation by synonymy at higher levels of abstraction, and organisation by something approaching a conceptual field at lower, less abstract levels.

Checklist das categorias da CIF relevantes para o desenvolvimento de fala e linguagem

ABSTRACT Purpose Create a checklist of the International Classification of Functioning, Disability and Health (ICF) based on relevant categories for the development of speech and language, according to the perception of parents and speech therapists. Methods Pilot application and research were carried out. 100 parents of preschool children with typical language/cognition development and 57 language specialist speech therapists participated in the survey. A questionnaire was created with 199 ICF categories of body function components, activities and participation, and environmental factors. Each category was scored as: indispensable (2); important (1) or unimportant (0). Statistical analysis was performed (descriptive, sum, cluster/K-means and Mann-Whitney method). Results With the sum of the points (essential, important and unimportant) and the number of responses essential, the most relevant categories were identified for each group of respondents, as well as the set of categories in common (72 considered to have the greatest influence). The common list to the groups included the three components: body functions (30 categories/40% of the total), activities and participation (35/49.29%) and environmental factors (seven/13.20%). From the selected categories, 58.33% presented statistically significant results between the groups, regarding the relevance given. Conclusions The categories were considered with different scores between the groups: those of body functions were more scored by speech therapists, while those of environmental factors by parents. Thus, it was possible to create a checklist from the identification of the most relevant categories for the development of speech and language, in preschool age, contemplating the components of body functions, activities and participation and environmental factors.

A categorization-modelling procedure to estimate urban goods transport demand with a minimum number of activity categories

This paper presents an integrated clustering-regression modelling framework to assess the number of trips that each establishment of a given urban zone, city or conurbation generates. The goal of the method is to construct establishment-based trip models using the categorial FTG methodology using a minimal set of categories of activities. The methodology combines a hierarchical cluster analysis that defines a limited number of coherent categories of activities, then a regression-based modelling method that links the FTG rates (production, attraction and generation) to employment, giving a specific functional form for each category (constant, linear, logarithmic or potential). The models are constructed and calibrated on the basis of the 2011-2012 Freight Trip Survey of the Paris Region. Using a hierarchical clustering technique, 5 categories of establishment are defined and resulting FTG models obtained. Most functional forms are linear or potential, with some particular cases where constant generation is preferred. Results are assessed using the R2 coefficient and discussed. The resulting models are robust and applicable to any French city.

Tracking sustainable Industry 4.0 for listed companies

The goal of this study is to develop replicable methodology to diagnose sustainable Industry 4.0 status in listed companies. Quantitative content analysis using MAXQDA software was applied. The content of documents was mapped according to the predefined set of keywords (dictionary) and categories with lemmatization of keywords. Both annual reports and Internet news were analysed. Finally, quantitative analysis of keywords occurrence was performed, and descriptive statistics with correlation analysis was presented comparing findings for annual reports and Internet news. The methodology was demonstrated based on companies listed on the Warsaw Stock Exchange, representing ca. two thirds of total market capitalization and many different sectors. Communication in annual reports and Internet news exhibited in-consistencies and dependent on or influenced by company’s characteristics. The re-search effectively addressed research questions regarding the inclusion of Industry 4.0 and sustainability issues in company’s report and Internet communication. A limitation of the presented study is the lack of a qualitative perspective to explain potential phenomena underlying the uncovered potential correlations. Nonetheless, the methodology can serve signals for policymakers, to position economies in different countries concerning Industry 4.0 and sustainability. Furthermore, the presented re-search demonstrates excellent potential for replicability and traceability. It can be applied to other indices for sample selection, comparative analyses of sectors and branches, explore markets, and enable year-to-year comparisons.