Description Coding Research Articles

Towards prompt tuning-based software vulnerability assessment with continual learning

Software vulnerability assessment (SVA) has become increasingly important due to the growing reliance on various software systems and the rising complexity of cyber threats. SVA aims to quickly identify and remediate high-risk vulnerabilities in software systems, which helps protect sensitive information and maintain the integrity of digital infrastructure. In our study, we focus on prompt tuning-based SVA. Prompt tuning reduces computational costs by tuning the input prompts instead of the entire model. We further incorporate the continual learning paradigm to enable the SVA model to adapt to new vulnerabilities as they emerge dynamically. This paradigm ensures the SVA model remains up-to-date, reduces the risk of catastrophic forgetting, and provides resource-efficient updates. To achieve this goal, we propose a novel method SVACL. SVACL combines confidence-based replay and regularization methods for continual learning. Additionally, SVACL uses both source code and vulnerability descriptions to create hybrid prompts for prompt tuning with the pre-trained model CodeT5. Experimental results demonstrate that SVACL outperforms state-of-the-art SVA baselines by 20% to 380% in terms of MCC performance measure. Finally, our ablation study results confirm the effectiveness of the component settings (such as confidence-based replay, regularization method, vulnerability information fusion, CodeT5, and hybrid prompts) for SVACL. Therefore, our study provides the first promising step toward prompt tuning-based SVA with continual learning.

Classifying sources of low- and no-calorie sweeteners within the Canadian food composition database

Low- and no-calorie sweeteners are sugar substitutes that impart sweetness. Examining exposure to low- and no-calorie sweeteners is challenging because the amounts of sweeteners in food and beverage products are not standard elements of food composition databases. We identified food codes representing sources of low- and no-calorie sweeteners in the food composition database used for Canadian surveillance data using multiple approaches. First, food code descriptions were searched for keywords (e.g. low calorie) potentially representing low and no-calorie sweeteners. Next, the U.S. Food and Nutrient Database for Dietary Surveys food code descriptions, matched to food codes within the Canadian database, were examined for keywords representing confirmed sweetener sources. Finally, using websites for three Canadian grocers, ingredient lists for brand-specific products were examined for sources of low- and no-calorie sweeteners. Recipe codes often required an examination of ingredient-level food codes. Of 5180 food codes, 76 were classified as sources of low- and no-calorie sweeteners and an additional 46 recipe codes were identified as containing a source of sweetener. The classification system can be applied to national survey data to describe exposure to low- and no-calorie sweeteners and identify key sources of sweeteners. Standardized identification of food codes as sources of low- and no-calorie sweeteners will contribute to an evidence base that can be synthesized to inform nutrition policy.

Assessing Appropriation of Space in Urban Green Spaces: Three Case Studies in Downtown Shanghai

This study investigated patterns of activities in urban green spaces (UGSs) in downtown Shanghai. UGSs are essential public infrastructure, contributing to urban sustainability, quality of life, and social cohesion. Although widely studied, there is a gap in the literature regarding Chinese UGSs when the object of study is the nature the activities. In this sense, we aimed to investigate the activities from the perspective of appropriation of the space, considered here as different from the use of space. This study addressed this by analyzing user demographics, frequency, and spatial activity patterns to assess how these activities could be classified and scored according to a varying levels of appropriation. Through a mixed-methods design based on non-participant observation and behavior mapping, the study was conducted across three comprehensive parks in Shanghai, divided into nine observation zones. The data were analyzed through descriptive statistics, IBM SPSS, and qualitative coding, revealing, as the main findings, sixty distinct activity types, a soft to moderate level of appropriation, and notable variations in demographic presence and temporal trends. This research underscores the effectiveness of observational methods, validates appropriation as an analytical category, and emphasizes the importance of structured classification systems for improving the understanding of UGSs’ socio-spatial performance and their societal role.

Revealing Religious Tolerance and Moderation in Upin & Ipin Series

Children’s animated films play an important role in shaping children’s perceptions of social and cultural values, including tolerance and religious moderation. This study aimed to understand how messages about religious tolerance and moderation are communicated through symbols, scenes, and character interactions in the Upin & Ipin series. This study used a qualitative approach with a visual discourse analysis method to examine the visual representation in the series. The data analysis technique involved observing scenes that show interreligious interactions, religious celebrations, and respectful behavior between characters with different cultural and religious backgrounds. Each scene was analyzed based on the visual and narrative context to identify messages of religious moderation. Data were analyzed using descriptive coding and thematic analysis to find patterns of visual depictions of religious moderation. The results showed that Upin & Ipin series consistently displays the values ​​of religious moderation through harmonious characters in participating in religious celebrations. This visual message emphasizes the importance of mutual respect in a multicultural society. This study implies that children’s media, especially cartoon film, can be used to teach the values ​​of religious moderation and tolerance from an early age.

User Views on Online Sexual Health Symptom Checker Tool: Qualitative Research.

Delayed diagnosis and treatment of sexually transmitted infections (STIs) contributes to poorer health outcomes and onward transmission to sexual partners. Access to best-practice sexual health care may be limited by barriers such as cost, distance to care providers, sexual stigma, and trust in health care providers. Online assessments of risk offer a novel means of supporting access to evidence-based sexual health information, testing, and treatment by providing more individualized sexual health information based on user inputs. This developmental evaluation aims to find potential users' views and experiences in relation to an online assessment of risk, called iSpySTI (Melbourne Sexual Health Center), including the likely impacts of use. Individuals presenting with urogenital symptoms to a specialist sexual health clinic were given the opportunity to trial a web-based, Bayesian-powered tool that provides a list of 2 to 4 potential causes of their symptoms based on inputs of known STI risk factors and symptoms. Those who tried the tool were invited to participate in a once-off, semistructured research interview. Descriptive, action, and emotion coding informed the comparative analysis of individual cases. Findings from interviews with 14 people who had used the iSpySTI tool support the superiority of the online assessment of STI risk compared to existing sources of sexual health information (eg, internet search engines) in providing trusted and probabilistic information to users. Additionally, potential users reported benefits to their emotional well-being in the intervening period between noticing symptoms and being able to access care. Differences in current and imagined urgency of health care seeking and emotional impacts were found based on clinical diagnosis (eg, non-STI, curable and incurable but treatable STIs) and whether participants were born in Australia or elsewhere. Online assessments of risk provide users experiencing urogenital symptoms with more individualized and evidence-based health information that can improve their health care-seeking and provide reassurance in the period before they can access care.

Implementation of an adult life-course vaccine review service, VaxCheck, in community pharmacy: A qualitative analysis

BackgroundCommunity pharmacists are well placed to identify and vaccinate unimmunized or under-immunized individuals who can put themselves and communities at risk of preventable disease. We designed and tested VaxCheck, a novel life-course vaccine review service that can be used to raise awareness and guide personal vaccination action plans, in community pharmacies in Ontario, Canada. ObjectiveTo understand the experiences of community pharmacists and staff directly involved with providing the VaxCheck service as part of initial testing. MethodsSemi-structured interviews were performed with pharmacy staff from nine pharmacies who participated in the study. Interviews were conducted at baseline and following each of three plan-do-study-act quality improvement cycles. Activities undertaken to perform VaxCheck were assessed. An inductive thematic analysis was performed to identify dominant themes and subthemes. Activities and descriptive codes were then correlated to the Consolidated Framework for Implementation Research (CFIR). Results26 interviews were conducted. Pharmacy staff described VaxCheck activities as spanning three stages: (1) Promotion/offering of VaxCheck, (2) Completing the VaxCheck, and (3) Enacting recommendations and follow-up. VaxCheck activities were compatible with workflow related to delivery of other vaccines and medication reviews. Thematic analysis found three considerations guided VaxCheck adoption: (1) Aligning VaxCheck with workflow through flexible integration, (2) Enabling patient-oriented vaccination services, and (3) Contributing to community healthcare provision. Data aligned with all CFIR domains with strengths noted in constructs from the “Innovation characteristics” and “Individuals” domains. Barriers to implementation were identified in “Inner setting”, “Outer setting” and “Process” domains, such as pharmacy workflow capacity, patient knowledge about vaccination, availability of vaccine records, and interactions with other healthcare providers. ConclusionCommunity pharmacists found VaxCheck to be a valuable, accessible service that was well-received by patients and supported adult vaccination reviews and individualized recommendations. VaxCheck was compatible with pharmacy workflow but needed additional resources for sustainability and promotion with stakeholders.

Qudit stabilizer codes, CFTs, and topological surfaces

We study general maps from the space of rational conformal field theories (CFTs) with a fixed chiral algebra and associated Chern-Simons (CS) theories to the space of qudit stabilizer codes with a fixed generalized Pauli group. We consider certain natural constraints on such a map and show that the map can be described as a graph homomorphism from an orbifold graph, which captures the orbifold structure of CFTs, to a code graph, which captures the structure of self-dual stabilizer codes. By studying explicit examples, we show that this graph homomorphism cannot always be a graph embedding. However, we construct a physically motivated map from universal orbifold subgraphs of CFTs to operators in a generalized Pauli group. We show that this map results in a self-dual stabilizer code if and only if the surface operators in the bulk CS theories corresponding to the CFTs in question are self-dual. For CFTs admitting a stabilizer code description, we show that the full Abelianized generalized Pauli group can be obtained from twisted sectors of certain 0-form symmetries of the CFT. Finally, we connect our construction with SymTFTs, and we argue that many equivalences between codes that arise in our setup correspond to equivalence classes of bulk topological surfaces under fusion with invertible surfaces. Published by the American Physical Society 2024

Multiple description image coding using Schur transform

A novel obvious and robust image Multiple Description Coding (MDC) using Schur transform (ST)is presented in this work. To overcome the inherent drawbacks in the discrete wavelet transform (DWT)which are the hardware implementation and computational complexityIn the MDC approach, two or more correlated descriptions of the same data aregenerated, which can be independently decoded, and yield mutually refinable information. Therefore, the quality of the recovered signal is dependent only on the number of received descriptions, and not on the specific loss pattern. The new techniquewas analyzed and compared to the conventional approach in the case of four descriptions by using multiple grayscale test images having different spectral characteristics.Theexperimental results of Schur transform (ST) compared to discrete wavelet transform (DWT)show that our method achievesbetter performance in terms of delivered peaksignal to noise ratio (PSNR) and visual image quality reconstruction.The proposed MDC has a low redundancy and outperforms the conventionalscheme for image transmission over error-prone networks.Therefore, the proposed approach provides an easier practical implementation and a better redundancy performancethan the classical approach.

Educational Leaders’ Insights on PBPD, Implementation, and Sustainability Practices of SRSD, a Writing EBP

The purpose of this qualitative study was to gain insights from educational leaders who had participated in a larger study and received extensive practice-based professional development on an evidence-based practice, self-regulated strategy development for informative writing. The participants also previously implemented the self-regulated strategy development strategies with elementary students with high incidence disabilities during a summer tutoring program. The current study included one-on-one video conferencing interviews with six educational leaders: a principal, a complex area specialist, three complex area coaches, and a student services coordinator about their reported impact of the practice-based professional development on implementation of self-regulated strategy development during a regular school year given their current job descriptions. Open coding of the transcripts resulted in five descriptive codes detailing the participants’ intention for enrolling, application of self-regulated strategy development, additional supports, barriers, and the impact of the evidence-based practice. Implications discussed include post-intervention supports needed to help educational leaders guide the sustained implementation of an evidence-based practice for writing instruction.

Service language and small talk: differentiating genuine from mundane in B2B contexts

PurposeThis study examines the role of genuine small talk in business-to-business (B2B) communication through the lens of service language. By exploring and distinguishing genuine and mundane small talk, the research elucidates the impact of sincere, empathetic interactions on value co-creation and relational dynamics within the B2B contexts.Design/methodology/approachEmploying an abductive qualitative research strategy, we conducted semi-structured interviews with 25 B2B professionals from Australian and Indonesian multinational corporations. Data analysis involved descriptive coding and thematic analysis, supplemented by network view strategies to visualize interrelations within the dataset.FindingsThe study finds that genuine small talk, characterized by sincere and contextually relevant exchanges, enhances relational enrichment, customer satisfaction and long-term loyalty in B2B interactions. Participants highlighted the importance of empathetic communication and personalized conversations in building trust and rapport. Conversely, mundane small talk, marked by superficiality, was found to erode trust and diminish the quality of client relationships. These insights underscore the critical importance of integrating genuine small talk into communication strategies to foster enduring business relationships and enhance overall service effectiveness.Originality/valueThis study contributes to the service literature by exploring the notion of genuine and mundane small talk in B2B communication, grounding them in service language perspective. It provides novel insights into the verbal and non-verbal elements of genuine small talk, offering practical implications for enhancing B2B negotiation strategies.

Possible Health Benefits and Risks of DeepFake Videos: A Qualitative Study in Nursing Students.

"DeepFakes" are synthetic performances created by AI, using neural networks to exchange faces in images and modify voices. Due to the novelty and limited literature on its risks/benefits, this paper aims to determine how young nursing students perceive DeepFake technology, its ethical implications, and its potential benefits in nursing. This qualitative study used thematic content analysis (the Braun and Clarke method) with videos recorded by 50 third-year nursing students, who answered three questions about DeepFake technology. The data were analyzed using ATLAS.ti (version 22), and the project was approved by the Ethics Committee (code UCV/2021-2022/116). Data analysis identified 21 descriptive codes, classified into four main themes: advantages, disadvantages, health applications, and ethical dilemmas. Benefits noted by students include use in diagnosis, patient accompaniment, training, and learning. Perceived risks include cyberbullying, loss of identity, and negative psychological impacts from unreal memories. Nursing students see both pros and cons in DeepFake technology and are aware of the ethical dilemmas it poses. They also identified promising healthcare applications that could enhance nurses' leadership in digital health, stressing the importance of regulation and education to fully leverage its potential.

Data-Driven Control for Nonlinear Networked Systems on Basis of Two Description Coding Scheme

Data-Driven Control for Nonlinear Networked Systems on Basis of Two Description Coding Scheme

Can GPT-3.5 generate and code discharge summaries?

The aim of this study was to investigate GPT-3.5 in generating and coding medical documents with International Classification of Diseases (ICD)-10 codes for data augmentation on low-resource labels. Employing GPT-3.5 we generated and coded 9606 discharge summaries based on lists of ICD-10 code descriptions of patients with infrequent (or generation) codes within the MIMIC-IV dataset. Combined with the baseline training set, this formed an augmented training set. Neural coding models were trained on baseline and augmented data and evaluated on an MIMIC-IV test set. We report micro- and macro-F1 scores on the full codeset, generation codes, and their families. Weak Hierarchical Confusion Matrices determined within-family and outside-of-family coding errors in the latter codesets. The coding performance of GPT-3.5 was evaluated on prompt-guided self-generated data and real MIMIC-IV data. Clinicians evaluated the clinical acceptability of the generated documents. Data augmentation results in slightly lower overall model performance but improves performance for the generation candidate codes and their families, including 1 absent from the baseline training data. Augmented models display lower out-of-family error rates. GPT-3.5 identifies ICD-10 codes by their prompted descriptions but underperforms on real data. Evaluators highlight the correctness of generated concepts while suffering in variety, supporting information, and narrative. While GPT-3.5 alone given our prompt setting is unsuitable for ICD-10 coding, it supports data augmentation for training neural models. Augmentation positively affects generation code families but mainly benefits codes with existing examples. Augmentation reduces out-of-family errors. Documents generated by GPT-3.5 state prompted concepts correctly but lack variety, and authenticity in narratives.

Sources of moral distress among obstetrician-gynecologists after Dobbs: A qualitative, multi-state study

Since the US Supreme Court's 2022 decision in Dobbs v Jackson Women's Health Organization, 18 states have enacted functional bans on abortion, yet little is known about how these laws contribute to workplace stress and its sequelae among clinicians. The purpose of this study was to characterize sources of moral distress—which occurs when a clinician knows the right course of clinical action but is barred from taking that action by external constraints—among obstetrician-gynecologists (OB-GYNs) in states with abortion bans. We conducted qualitative, semi-structured interviews with 54 OB-GYNs practicing in 13 of 14 states where abortion was illegal as of March 2023. Using a qualitative descriptive coding approach, we identified four types of clinical situations leading to moral distress: delaying treatment for patients with obstetric complications, conflict with other clinicians, denying care they would have provided locally prior to Dobbs, and restrictions on clinical counseling. These situations provoked feelings of anger, frustration, helplessness, and emotional exhaustion. Participants attributed moral distress to the cumulative toll of routinely being unable to provide evidence-based healthcare, in addition to the acute burden of managing obstetric emergencies in legal gray areas, which was relatively rarer. The findings demonstrate a previously unreported source of moral distress: the everyday chipping away of professional integrity that occurs when OB-GYNs cannot care for patients in the way that patients need. Next steps include developing institutional-level policies and programs to support clinicians and enable them to practice ethical medicine in abortion-restrictive policy environments.

The Investigation of a Nelsonian Approach to Socratic Dialogue with Student-Teachers at a Midwestern Private University

Student-teachers must be afforded opportunities to seek guidance on challenges that arise during teaching experiences, such as addressing student behavior, creating meaningful lessons, and fostering open and welcoming learning environments. Student-teachers can undergo negative experiences, which can lead to frustration, anger, and lack of interest in the profession. One way to address these challenges is through dialogue (Kumar & Downey, 2018). In this qualitative study, the researcher investigated whether a nuanced version of the Socratic method, developed by Leonard Nelson (1882-1927), can be an efficacious instructional strategy for finding solutions to student-teachers’ classroom challenges. The research study consisted of five undergraduate students enrolled in a student teaching seminar at a private midwestern university. The course prepared students for roles as new teachers by reading, discussing, and sharing challenges about teaching. Both the researcher and research participants worked together to faithfully follow the essential steps of a Nelsonian Socratic method approach. Once the preparation was settled, the researcher, as the external analyst, facilitated a Nelsonian Socratic dialogue with the student-teachers on a specific challenge a student teacher within the group was facing. After the dialogue, participants were assembled in a focus group and asked several questions about their experiences participating in a Nelsonian Socratic dialogue. Descriptive, categorical, and analytical coding of data indicated that participants reached consensus on a solution for the student-teacher’s challenge and perceived the Nelsonian Socratic method approach as an effective dialogic strategy that generated feelings of belongingness and empowerment as a group, a shared understanding about the challenge, and a healthy respect for dialogue.

Interests, Plans, and Hopes for Life After High School From Autistic Young Adults’ Perspectives

Obtaining the perspectives of autistic young adults is critical for planning educational and service delivery systems focused on the preparation for a high life quality after high school. The perspective and voice of autistic young adults who participated in the Center on Secondary Education for Students with Autism (CSESA) multi-site follow-up study conducted across three states (North Carolina, Wisconsin, and California) are described. Participants who exited high school or were enrolled in a district transition program responded to short-answer items on a Young Adult Questionnaire and Interview ( n = 148) and completed the Adolescent and Young Adult Activity Card Sort (Berg, 2015; n = 150) to address research questions about their current interests, future plans, and perceived barriers to fulfilling future plans using descriptive statistics and coding of interview responses. The young adults report current engagement in leisure activities, and 79% seek a job change and the opportunity to date and engage in a long-term relationship.

The experiences of medical and pharmacy students participating in a collaborative online international learning on social accountability and global health: a qualitative study

BackgroundSocial accountability aims to promote a collective ethic that upholds the fundamental values of equity, efficiency, solidarity, and social justice in healthcare and is now considered as a critical mission of academic health centers. Collaborative Online International Learning (COIL) is a pedagogical approach that uses digital technology to provide experiential international learning, specifically for increasingly diverse and multicultural healthcare work environments. The SOLID’AIRS program is an innovative French-language COIL that aims to set up international exchanges and workshops on social accountability between health sciences students. The aim of our study was to assess the impact of participation in the SOLID’AIRS program on medical and pharmacy students.MethodFive universities in four different countries were involved in SOLID’AIRS. We conducted a qualitative study by performing individual, semi-directed interviews with students who participated in the program from 2021 to 2022. A thematic analysis was conducted in five chronological phases: (1) reading, (2) descriptive coding, (3) conceptual coding, (4) identification of themes and (5) production of a coherent thematic structure.ResultsAfter including sixteen student participants, 13 medical and 3 pharmacy students, we identified four main themes related to the impact of participation: (1) previous experiences in social accountability and international learning, (2) perception of the program, (3) perceived impacts of the program, and (4) difficulties encountered and avenues to improve the program. Overall, the program was well received by all participants who reported the advantages and limitations of the online learning format. The primary advantage of this format was its feasibility. The participants noted both professional and personal benefits of the program for their current and future practice, including greater reflexivity towards health sciences practice. Based on the challenges faced during the program, particularly in coordinating group work and communication, participants suggested increased supervision of group projects by collaborators, and organizing at least one in-person meeting for future editions. The participants reported encountering difficulties during the COIL and suggested ways of improvement.ConclusionParticipating in a COIL on social accountability appears to be an effective way to adopt a reflective approach to medical practice and should be implemented and evaluated in other educational contexts.

Students' Learning Interest In Following The Process Pjok Learning At Mi Miftahul Ulum Plinggisan

This research uses quantitative descriptive methods to measure and analyxe The level of student interest in learning following the PJOK learning process at MI Miftahul Ulum Plinggisan. This method aims to get a clear picture of the factors that influence students' learning interest and the effectiveness of the strategies that have been implemented. The population of this study was all students at MI Miftahul Ulum Plinggisan, with samples selected randomly to ensure representation from each class. The research instrument is a questionnaire consisting of four main parts: Learning Motivation, Enjoyment, Involvement, and Perceptions of PJOK Lessons. Each section consists of several statements which are measured using a Likert scale with a range of 1 (Strongly Disagree) to 5 (Strongly Agree). Data collection was carried out by distributing questionnaires to students who were research samples, with filling in under the supervision of researchers to ensure completeness and accuracy of the data. The collected data was analyzed using descriptive statistical techniques, including editing and coding, tabulation, calculating descriptive statistics (mean, median, mode, and standard deviation), as well as Pearson correlation analysis to see the relationship between the variables motivation, enjoyment, involvement, and perception with interest. student learning. The research results showed that as many as 70% of students felt motivated to take part in PJOK lessons, as many as 80% of students enjoyed the activities in learning PJOK, as many as 80% of students were active in PJOK activities. As many as 75% of students have a positive view of the importance of PJOK lessons.

Ensemble neural models for ICD code prediction using unstructured and structured healthcare data

Disease coding is the process of assigning one or more standardized diagnostic codes to clinical notes that are maintained by health practitioners (e.g. clinicians) to track patient condition. Such a coding process is often expensive and error-prone, as human medical coders primarily perform it. Automating diagnostic coding using Artificial Intelligence is seen as an essential solution in Hospital Information Management Systems and approaches built on Convolutional Neural Networks currently perform best. In this work, a neural model built on unstructured clinical text for enabling automatic diagnostic coding for given patient discharge summaries is proposed. We incorporate a structured self-attention mechanism designed to boost learning of label-specific vectors and the significant clinical text snippets associated with a certain label for this purpose. These vectors are then combined with a novel code description pipeline leveraging the descriptions provided for each standardized diagnostic code. The proposed model achieved best performance in terms of standard metrics over the MIMIC-III dataset, outperforming models based on Longformers and Knowledge graphs. Furthermore, to leverage structured clinical data to enhance the proposed model, and to enable improved diagnostic code prediction, model ensembling is considered. A neural model built on structured data by leveraging supervised machine learning algorithms such as random forest and boosting, is designed for multi-class code classification. Experimental results revealed that the proposed ensemble models show promising performance compared to traditional models that rely solely on unstructured or structured clinical data, emphasizing their suitability for real-world deployment.

Interactions with new-to-teacher language resources: Supporting translingual composing in a multilingual elementary classroom

Educators should support multilingual students’ translingual writing. However, it can be challenging for teachers to support students’ composing in languages that teachers do not speak. Drawing on a community translanguaging lens, this paper explores this issue by asking: How did teachers talk about and interact with language resources that were new to them while supporting translingual writing in an English-medium classroom? Data were collected using ethnographic and practitioner research methods across 1 year in one second-grade writing workshop in the U.S. Students spoke Spanish, Korean, French, Tagalog, or English, and classroom teachers spoke English and Spanish. Data analysis first involved descriptive coding of videorecorded composing interactions to identify every teacher interaction involving a new-to-them named language. These events were then re-examined using constant comparative coding to identify interactional patterns. This yielded three main findings; teachers: (1) positioned students as language experts and themselves as language learners, (2) drew on shared language resources to support student writing in new-to-teacher languages, and (3) expanded audiences to support student writing in new-to-teacher languages. Implications include pedagogical steps teachers can take to support students’ use of new-to-teacher languages while writing, and ideological and social implications of teacher talk about those languages.