Analysis Of Questions Research Articles

Assessing Large Language Models Used for Extracting Table Information from Annual Financial Reports

The extraction of data from tables in PDF documents has been a longstanding challenge in the field of data processing and analysis. While traditional methods have been explored in depth, the rise of Large Language Models (LLMs) offers new possibilities. This article addresses the knowledge gaps regarding LLMs, specifically ChatGPT-4 and BARD, for extracting and interpreting data from financial tables in PDF format. This research is motivated by the real-world need to efficiently gather and analyze corporate financial information. The hypothesis is that LLMs—in this case, ChatGPT-4 and BARD—can accurately extract key financial data, such as balance sheets and income statements. The methodology involves selecting representative pages from 46 annual reports of large Swiss corporations listed in the SMI Expanded Index from 2022 and copy–pasting text from these into LLMs. Eight analytical questions were posed to the LLMs, and their responses were assessed for accuracy and for identifying potential error sources in data extraction. The findings revealed significant variance in the performance of ChatGPT-4 and another LLM, BARD, with ChatGPT-4 generally exhibiting superior accuracy. This research contributes to understanding the capabilities and limitations of LLMs in processing and interpreting complex financial data from corporate documents.

“Visualization matters” – stereoscopic visualization of 3D graphic neuroanatomic models through AnaVu enhances basic recall and radiologic anatomy learning when compared with monoscopy

BackgroundThe authors had previously developed AnaVu, a low-resource 3D visualization tool for stereoscopic/monoscopic projection of 3D models generated from pre-segmented MRI neuroimaging data. However, its utility in neuroanatomical education compared to conventional methods (specifically whether the stereoscopic or monoscopic mode is more effective) is still unclear.MethodsA three-limb randomized controlled trial was designed. A sample (n = 152) from the 2022 cohort of MBBS students at Government Medical College, Thiruvananthapuram (GMCT), was randomly selected from those who gave informed consent. After a one-hour introductory lecture on brainstem anatomy and a dissection session, students were randomized to three groups (S – Stereo; M – Mono and C – Control). S was given a 20-min demonstration on the brainstem lesson module in AnaVu in stereoscopic mode. M was given the same demonstration, but in monoscopic mode. The C group was taught using white-board drawn diagrams. Pre-intervention and post-intervention tests for four domains (basic recall, analytical, radiological anatomy and diagram-based questions) were conducted before and after the intervention. Cognitive loads were measured using a pre-validated tool. The groups were then swapped -S→ M, M →S and C→S, and they were asked to compare the modes.ResultsFor basic recall questions, there was a statistically significant increase in the pre/post-intervention score difference of the S group when compared to the M group [p = 0.03; post hoc analysis, Bonferroni corrections applied] and the C group [p = 0.001; ANOVA test; post hoc analysis, Bonferroni corrections applied]. For radiological anatomy questions, the difference was significantly higher for S compared to C [p < 0.001; ANOVA test; post hoc analysis, Bonferroni corrections applied]. Cognitive load scores showed increased mean germane load for S (33.28 ± 5.35) and M (32.80 ± 7.91) compared with C (28.18 ± 8.17). Subjective feedbacks showed general advantage for S and M compared to C. Out of the S and M swap cohorts, 79/102 preferred S, 13/102 preferred M, and 6/102 preferred both.ConclusionsAnaVu tool seems to be effective for learning neuroanatomy. The specific advantage seen when taught with stereoscopy in basic recall and radiological anatomy learning shows the importance of how visualization mode influences neuroanatomy learning. Since both S and M are preferred in subjective feedbacks, these results have implications in choosing methods (stereoscopic – needs 3D projectors; monoscopic – needs web based or hand-held devices) to scale AnaVu for anatomy teaching in medical colleges in India. Since stereoscopic projection is technically novel and cost considerations are slightly higher compared to monoscopic projection, the specific advantages and disadvantages of each are relevant in the Indian medical education scenario.

Toward a Sociology of Plasma Products.

Over the past 20 years, plasma has become a medical treatment characterized as "liquid gold" to signal its lifesaving potential. Through a manufacturing process termed fractionation, plasma, collected through blood donation, is turned into Plasma Derived Medical Products (PDMPs). The World Health Organization (WHO) has underlined the importance of PDMPs for global health care, including a number of PDMPs on the WHO Model List of Essential Medicines. The process of collecting plasma from a donor, manufacturing plasma derived treatments, and distributing those treatments globally requires the coordination of multiple social actors operating in different social, political and economic contexts, but has received little attention in scholarly literature on public policy or the social sciences. This paper will introduce a set of analytic questions and concepts that can direct a sociology of plasma products. We build on the behavioral turn in the policy sciences to identify relevant policy questions emerging from this field and offer the analytic tools necessary to investigate how different social actors in this space make meaning of plasma. To do this, we will draw on key concepts in the sociology of health and illness.

The Influence of the Problem-Based Learning Model Assisted by Google Sites Interactive Multimedia on Critical Thinking Skills in the Science Subject of Grade V Elementary School

Critical thinking skills are part of 21st century learning that are important to be applied in the learning process. However, these skills have not been fully mastered by students. Based on the results of observations conducted in one elementary school, students have difficulty working on analytical questions. This study aims to determine the effect of the Problem-Based Learning model assisted by interactive multimedia Google sites significantly on critical thinking skills in the subject of science for grade V of elementary school. This type of research is a quasi-experiment with a nonequivalent control group design. The population in this study were grade V students of SDN 3 Bangunsari Ponorogo totaling 82 students. The research sample was grade V students consisting of a control class and an experimental class, each totaling 30 students. Data analysis used an independent sample t-test. The results showed that there was a difference in the average results of the pretest and posttest of critical thinking skills in the experimental class and the control class. In the experimental class there was an increase of 19.56%. While in the control class it increased by 6.27%. The results of the hypothesis test using the independent sample t-test showed a significance value (2-tailed) of 0.034, which means &lt;0.05, thus Ho is rejected and Ha is accepted. So there is a significant influence of the Problem-Based Learning model assisted by interactive multimedia Google sites on critical thinking skills in the subject of science for grade V of Elementary School. Learning with the Problem-Based Learning model assisted by interactive multimedia Google sites has been proven to be able to improve students' critical thinking skills.

NLP-based smart decision making for business and academics

Natural Language Processing (NLP) systems enable machines to understand, interpret, and generate human-like language, bridging the gap between human communication and computer understanding. Natural Language Interface to Databases (NLIDB) and Natural Language Interface to Visualization (NLIV) systems are designed to enable non-technical users to retrieve and visualize data through natural language queries. However, these systems often face challenges in handling complex correlation and analytical questions, limiting their effectiveness for comprehensive data analysis. Additionally, current Business Intelligence (BI) tools also struggle with understanding the context and semantics of complex questions, further hindering their usability for strategic decision-making. Also, when building these models for generating the queries from natural language, the system handles only the semantic parsing issues as each column header is being changed manually to their normal names by all existing models which is time-consuming, tedious, and subjective.Recent studies reflect the need for attention to context, semantics, and especially ambiguities in dealing with natural language questions. To address this problem, the proposed architecture focuses on understanding the context, correlation-based semantic analysis, and removal of ambiguities using a novel approach. An Enhanced Longest Common Subsequence (ELCS) is suggested where existing LCS is modified with a memorization component for mapping the natural language question tokens with ambiguous table column headers. This can speed up the overall process as human intervention is not required to manually change the column headers. The same is evidenced by carrying out thorough experimentation and comparative study in terms of precision, recall, and F1 score. By synthesizing the latest advancements and addressing challenges, this paper has proved how NLP can significantly enhance the accuracy and efficiency of information retrieval and visualization, broadening the inclusivity and usability of NLIDB, NLIV, and BI systems.

Automating incidence and prevalence analysis in open cohorts

MotivationData is increasingly used for improvement and research in public health, especially administrative data such as that collected in electronic health records. Patients enter and exit these typically open-cohort datasets non-uniformly; this can render simple questions about incidence and prevalence time-consuming and with unnecessary variation between analyses. We therefore developed methods to automate analysis of incidence and prevalence in open cohort datasets, to improve transparency, productivity and reproducibility of analyses.ImplementationWe provide both a code-free set of rules for incidence and prevalence that can be applied to any open cohort, and a python Command Line Interface implementation of these rules requiring python 3.9 or later.General featuresThe Command Line Interface is used to calculate incidence and point prevalence time series from open cohort data. The ruleset can be used in developing other implementations or can be rearranged to form other analytical questions such as period prevalence.AvailabilityThe command line interface is freely available from https://github.com/THINKINGGroup/analogy_publication.

Quantitation of oxidized and reduced albumin in mammals. An intriguing analytical question

Oxidized albumin is considered a short-term biomarker of oxidative stress and its measurement in blood contributes to evaluate the impact of diseases, drugs, dialytic treatments, physical activity, environmental contaminants etc. on the red-ox balance of humans as well as of other mammalians. Nevertheless, the most common methods for quantifying the oxidized and reduced albumins are costly and time-consuming. Furthermore, there is a dearth of information regarding the proper ways to store human serum or plasma samples in order to prevent inaccurate quantification of these various albumin forms. This paper explores these aspects and proposes a few spectrophotometric assay procedures which make the quantitation of oxidized and reduced albumin very fast, precise and un-expensive in various mammals.

Analyzing Social Interaction in Organizations: A Roadmap for Reflexive Choice

This article proposes a framework for reflexive choice in qualitative research, centering on social interaction. Interaction, fundamental to social and organizational life, has been studied extensively. Yet, researchers can get lost in the plethora of methodological tools, hampering reflexive choice. Our proposed framework consists of four dimensions of interaction (content, communication patterns, emotions, and roles), intersecting with five levels of analysis (individual, dyadic, group, organizational, and sociocultural), as well as three overarching analytic principles (following the dynamic, consequential, and contextual nature of interaction). For each intersection between dimension and level, we specify analytical questions, empirical markers, and references to exemplary works. The framework functions both as a compass, indicating potential directions for research design and data collection methods, and as a roadmap, illuminating pathways at the analysis stage. Our contributions are twofold: First, our framework fleshes out the broad spectrum of available methods for analyzing interaction, providing pragmatic tools for the researcher to reflexively choose from. Second, we highlight the broader relevance of maps, such as our own, for enhancing reflexive methodological choices.

Talk2Data: A Natural Language Interface for Exploratory Visual Analysis via Question Decomposition

Through a natural language interface (NLI) for exploratory visual analysis, users can directly “ask” analytical questions about the given tabular data. This process greatly improves user experience and lowers the technical barriers of data analysis. Existing techniques focus on generating a visualization from a concrete question. However, complex questions, requiring multiple data queries and visualizations to answer, are frequently asked in data exploration and analysis, which cannot be easily solved with the existing techniques. To address this issue, in this article, we introduce Talk2Data, a natural language interface for exploratory visual analysis that supports answering complex questions. It leverages an advanced deep-learning model to resolve complex questions into a series of simple questions that could gradually elaborate on the users’ requirements. To present answers, we design a set of annotated and captioned visualizations to represent the answers in a form that supports interpretation and narration. We conducted an ablation study and a controlled user study to evaluate the Talk2Data’s effectiveness and usefulness.

KEMAMPUAN BERPIKIR ANALISIS DALAM MENYELESAIKAN SOAL FISIKA PESERTA DIDIK SMAN SE-KOTA MAKASSAR

This research is quantitative descriptive research which aims to find out a picture. ability. think. analysis of high school students throughout the city Makassar. This research aims to determine analytical thinking skills in four schools, namely SMAN 4 Makassar, SMAN 6 Makassar, SMAN 9 Makassar, SMAN 23 Makassar using test instruments in the form of essay questions using a descriptive quantitative approach with a total research sample of 183 students, namely 62 participants. educated from SMAN 4 Makassar. 53 students from SMAN 6 Makassar, 22 students from SMAN 9 Makassar, and 46 students from SMAN 23 Makassar. The research instrument used is a test with 12 valid questions out of 22 questions that have been validated by experts, where the first indicator consists of 5 items, the second indicator consists of 4 questions and the third indicator consists of 3 questions. Test questions. This is used for collecting quantitative research data because it is a test instrument. to measure a person's abilities in a particular field. Instruments that. used to collect data in the form of essay tests that are developed accordingly. with indicators of analytical thinking skills which include analytical indicators. elements or elements, relationship analysis, and system analysis. And data mining through interviews was carried out using semi-structured interviews. Based on the research data, it was found that the physics analysis thinking ability of students at SMAN throughout Makassar City was in the medium category with an average amounting to 21.84. This is due to a lack of practice in analytical questions given.

Biology Textbook Grade X (2020): Analysis for the Development of Higher Order Thinking Skills among Secondary School Science Students

This study explores the development of higher-order thinking skills (HOTs) in secondary school students through a qualitative content analysis of a Biology textbook grade X (2020). The analysis was done using software called NVivo 12, and the book was chosen through purposeful sampling. The results showed that the textbook uses various strategies to develop critical thinking, such as practical activities, experiments, analytical questions, real-world applications, and open-ended problem-solving questions. Practical activities and experiments help students apply their theoretical understanding to actual problems. Analytical questions make students think critically by making them analyze data and explain complicated relationships between biological concepts. Real-world applications show students how scientific knowledge is used every day so they can evaluate scientific advancement more critically. Open-ended questions challenge students to use what they have learned to solve new problems and come up with unique answers.

‘J’accuse!’: whistleblowing, critical citizenship and the EU directive on whistleblowers’ protection

ABSTRACT Despite the enactment of legislation on public interest disclosures, whistleblowers still face significant retaliation. Perceptions and expectations of loyalty to a firm, organisation or a government continue to be seen as antithetical to ‘voice’, that is, the disclosure of wrongdoing, thereby triggering strategies of organisational exit and punishment. Real change can occur if whistleblowing is elevated to a civic duty of equal importance to other civic duties, such as to protect and defend the rule of law, human rights and democracy and to report suspected criminality to authorities. In this article, I justify whistleblowing on a good citizenship concept which transcends particular national institutional characteristics and critically examine the content and contribution of the European Union’s Directive on Whistleblower protection. By deploying a tripartite lens blending analytical questions and a discoursive theoretical perspective with a comparative assessment of instruments in the Member States and the EU, the discussion makes the case for the urgent change in the culture of punitive treatment of whistleblowers in the European Union and for further institutional reform when the Directive is reviewed in the future.

From existential uncertainty to a new mindset promoting recovery: Exploring the development of uncertainty experience in women with vulvar neoplasia – A qualitative longitudinal study

BackgroundWomen with vulvar neoplasia continue to experience uncertainty up to six months post-surgery. Uncertainty in illness is considered a significant psychosocial stressor, that negatively influences symptom distress, self-management strategies and quality of life. According to the Reconceptualized Uncertainty in Illness Theory, the appraisal of uncertainty changes positively over time in chronic illness. We aimed at exploring whether and how the experience of uncertainty develops in women with vulvar neoplasia.MethodsWe selected a purposive sample of seven women diagnosed with vulvar neoplasia in four Swiss and one Austrian women’s clinic. By means of a qualitative longitudinal study, we conducted 30 individual interviews at five points of time during one year after diagnosis. We applied Saldaña’s analytical questions for longitudinal qualitative research.ResultsFirst, participants experienced uncertainty as an existential threat, then an inherent part of their illness, and finally a certainty. Women initially associated the existential threat with a high risk for suffering from severe health deteriorations. Participants that could reduce their individually assessed risk by adopting health promoting behaviors, accepted the remaining uncertainty. From now on they reframed uncertainty into a certainty. This new mindset was based on a belief of promoting recovery and reducing the risk of recurrence.ConclusionsThe long-lasting and oscillating nature of uncertainty should receive attention in supportive oncology care. Uncertainty concerning existential issues is of special importance since it can inhibit a positive development of uncertainty experience.

Development of Critical Thinking Skills: An Analysis of English Curriculum Grades I-XII (2019)

Introduction: This quantitative study analysed the English Language Curriculum for Grades I-XII (2019) to assess how well it promotes critical thinking among secondary school students. The study aimed to determine the extent to which the curriculum facilitates the development of critical thinking skills. Methodology: The curriculum document was selected through purposeful sampling and analyzed using qualitative content analysis with NVivo 12 software. This method enabled a detailed examination of the curriculum content to identify elements related to critical thinking. Results/Findings: The analysis confirmed that critical thinking is deeply embedded in the curriculum through the integration of critical thinking skills with language skills, particularly reading and writing. Using Bloom's Taxonomy, the curriculum emphasizes activities designed to develop higher-level thinking skills. Additionally, well-structured assessments require students to answer analytical and evaluative questions, aligning with the objectives of fostering critical thinking. Future Direction: For the curriculum's potential to be fully realized, teachers must thoroughly understand its objectives and effectively implement the prescribed strategies. Continuous professional development and support for teachers are crucial to ensure the successful integration of critical thinking skills in teaching practices.

Modeling and Classification of the Behavioral Patterns of Students Participating in Online Examination

Online education has become an essential part of the modern education system, but keeping the integrity of the online examination remains a challenge. A significant increase in cheating in online examinations (from 29.9% before COVID-19 to 54.7% during COVID-19, as per a recent survey) points out the necessity of online exam proctoring systems. Traditionally, educational institutes utilize different questions in onsite exams: multiple-choice questions (MCQs), analytical questions, descriptive questions, etc. For online exams, form-based exams using MCQs are popular though in disciplines like math, engineering, architecture, art, or other courses, paper and pen tests are typical for proper assessment. In form-based exams, students’ attention is toward display devices, and cheating behavior is identified as the deviation of head and eye gaze direction from the display device. In paper- and pen-based exams, students’ main attention is on the answer script not on the device. Identifying cheating behavior in such exams is not a trivial task since complex body movements need to be observed to identify cheating. Previous research works focused on the deviation of the head and eyes from the screen which is more suited for form-based exams. Most of them are very resource-intensive; along with a webcam, they require additional hardware such as sensors, microphones, and security cameras. In this work, we propose an automated proctoring solution for paper- and pen-based online exams considering specific requirements of pen-and-paper exams. Our approach tracks head and eye orientations and lip movements in each frame and defines the movement as the change of orientation. We relate cheating with frequent coordinated movements of the head, eyes, and lips. We calculate a cheating score indicative of the frequency of movements. A case is marked as a cheating case if the cheating score is higher than the proctor-defined threshold (which may vary depending on the specific requirement of the discipline). The proposed system has five major parts: (1) identification and coordinate extraction of selected facial landmarks using MediaPipe; (2) orientation classification of the head, eye, and lips with K-NN classifier, based on the landmarks; (3) identification of abnormal movements; (4) calculation of a cheating score based on abnormal movement patterns; and (5) a visual representation of students’ behavior to support the proctor for early intervention. Our system is robust since it observes the pattern of movement over a sequence of frames and considers the coordinated movement pattern of the head, eye, and lips rather than considering a single deviation as a cheating behavior which will minimize the false positive cases. Visualization of the student behavior is another strength of our system that enables the human proctor to take preventive measures rather than punishing the student for the final cheating score. We collected video data with the help of 16 student volunteers from the authors’ university who participated in the two well-instructed mock exams: one with cheating and another without cheating. We achieved 100% accuracy in detecting noncheating cases and 87.5% accuracy for cheating cases when the threshold was set to 40.

Circumstantial evidence and explanatory models for synapses in large-scale spike recordings

Whether, when, and how causal interactions between neurons can be meaningfully studied from observations of neural activity alone are vital questions in neural data analysis. Here we aim to better outline the concept of functional connectivity for the specific situation where systems neuroscientists aim to study synapses using spike train recordings. In some cases, cross-correlations between the spikes of two neurons are such that, although we may not be able to say that a relationship is causal without experimental manipulations, models based on synaptic connections provide precise explanations of the data. Additionally, there is often strong circumstantial evidence that pairs of neurons are monosynaptically connected. Here we illustrate how circumstantial evidence for or against synapses can be systematically assessed and show how models of synaptic effects can provide testable predictions for pair-wise spike statistics. We use case studies from large-scale multi-electrode spike recordings to illustrate key points and to demonstrate how modeling synaptic effects using large-scale spike recordings opens a wide range of data analytic questions.

Abolition and the Welfare State: Implications for Social Welfare

Prison abolition has emerged as a new framework for critical analysis, policies, and practices with implications for social welfare. Mobilized through a series of social movement events and formations from the late 1990s, prison abolition has taken on public prominence since the summer of 2020 and unprecedented U.S. and global protests of racialized police violence. While proponents of abolition have called for the dismantling of the carceral state or that sphere of the state represented by policing, jails, and prisons, the implications for the welfare state have been less clear. This conceptual article provides an overview of the welfare state and its development since the New Deal, outlining critical debates regarding its contributions to well-being as well as its punitive functions. Building upon David Garland's categories of welfare state sectors, the article offers an initial framing and set of analytical questions for further inquiry into abolitionist informed frameworks and strategies with regard to the welfare state.

Из опыта использования сказок малочисленных народов Севера в обучении русскому языку как иностранному в китайской аудитории

The relevance of the research topic is due to the need to develop practical material on the Russian language as a foreign language with the use of national and regional artistic material. The article presents the work on fairy tales of the low-numbered peoples of the North (Even, Yukagir, Dolgan, Evenki), including cultural commen-tary, reproductive and analytical questions, creative tasks aimed at improving the linguistic, socio-cultural, cul-tural and communicative competence of foreign students. A list of folk tales reflecting the national picture of the world of the northern peoples of Yakutia is proposed. The author comes to the conclusion about the expediency and effectiveness of using this national-regional art material in teaching Russian as a foreign language, con-tributing to the expansion of students’ vocabulary with regional vocabulary, the development of oral coherent speech, as well as effective sociocultural and linguocultural adaptation of foreign students.

Motives and Political Representation: The Case of Women Members of Parliament in Uganda

Women’s political representation in Uganda is a contentious issue. On the one hand, there are doubting public narratives of Women Members of Parliaments’ (WMP) performance. The doubts about WMPs’ performance inspired growing interest in their parliamentary performance. On the other hand, there are concerns about the gender gap in parliamentary representation. The underrepresentation of women in the political scene raises a puzzle about those who dare to compete. However, at the same time, there has been neglect of what drives women in the first place to parliamentary representation and their relationship to performance. This intriguing question calls for an objective analysis to unravel what influences women’s interest in parliamentary office. This paper answers two analytical questions: How do women Members of Parliament construe their interests in joining parliamentary politics? And whether WMPs’ motives influence their performance. These questions were answered by analysing conversations and interviews of five purposively selected WMPs representing five districts of Northern Uganda in the tenth Parliament between 2020 and 2021. Field data was triangulated with performance data from the same Parliament’s Hansard. Findings reveal that personal and social-cultural factors drive WMPs to Parliament. Motives are consequential to performance, although personal motives were more potent than social-cultural motives to performance. Personal, compared to social-cultural motives, are more susceptible to social-political factors in constituencies, institutions of Parliament, and the broad government, affecting motives’ fulfilment

When Is a Belief Formed in an Epistemically Circular Way?

Abstract While there has been a great deal of discussion of whether and when beliefs formed in an epistemically circular manner can be justified, there has been almost no discussion of exactly which beliefs are formed in a circular manner. These discussions have tended to focus on an extremely limited number of intuitively-identified paradigm examples concerning attempts to establish the reliability of a method of belief formation. Here, I seek to answer a prior analytical question about the nature of epistemic circularity by developing a criterion which sorts epistemically circular beliefs from non-epistemically circular beliefs.