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The publication landscape for case reports has undergone a significant shift, with many high-impact journals deprioritizing or ceasing their publication altogether. This trend has led to the emergence of case-based reviews as an alternative to traditional case reports. Several factors drive this shift. Case-based reviews offer a more comprehensive synthesis of the literature compared to single case reports. They employ systematic search methodologies, reducing the risk of excluding relevant data, and providing robust evidence. From a publisher's perspective, case-based reviews have a greater potential for citation. While recommendations exist for writing traditional case reports, such as the CAse REports (CARE) guidelines, there is a lack of published recommendations for composing case-based reviews. This review aims to address this gap by providing guidance on drafting high-quality case-based reviews.
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Editoração , Humanos , Editoração/normas , Publicações Periódicas como Assunto/normas , Literatura de Revisão como Assunto , Políticas EditoriaisRESUMO
Perovskites have gained widespread attention across various fields such as photovoltaics, displays, and imaging. Despite their promising applications, achieving precise and high-quality patterning of perovskite films remains a challenge. In this study, femtosecond laser direct writing technology is utilized to achieve rapid and highly precise micro/nanofabrication on perovskites. The study successfully fabricates multiple structured and emission-tunable perovskite patterns composed of A2(FA)n-1PbnX3n+1 (A represents a series of long-chain amine cations, and X = Cl, Br, I), encompassing 2D, quasi-2D, and 3D structures. The study delves into the intricate interplay between fabrication technology and the growth of multi-dimensional perovskites: higher repetition rates, coupled with appropriate laser power, prove more conducive to perovskite growth. By employing precise halogen element design, the simultaneous generation of two distinct color quick-response (QR) code patterns is achieved through one-step laser processing. These mirrored QR codes offer a novel approach to anti-counterfeiting. To further enhance anti-counterfeiting capabilities, artificial intelligence (AI)-based methods are introduced for recognizing patterned perovskite anti-counterfeiting labels. The combination of deep learning algorithms and a non-deterministic manufacturing process provides a convenient means of identification and creates unclonable features. This integration of materials science, laser fabrication, and AI offers innovative solutions for the future of security features.
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Introduction: People with language difficulties cannot face challenges related to social skills. Those language disorders affect academic, work environments, and social interaction, leading to maladaptive and aggressive behaviors. Young inmates are at high risk of experiencing unrecognized language deficiencies. It is, therefore, necessary to analyze linguistic pathologies that can influence criminal behavior (drugs possession/consumption and gender violence crimes). There are many standardized tests to evaluate and detect language difficulties in adults in English. However, there are relatively few options in Spanish; there are no tests that evaluate language qualitatively and in depth. Most of the research is conducted with children and adolescents. Objectives: To propose a reliable coding system for the correction and interpretation of narratives (essays and narratives) from the Battery for the Evaluation of Writing Processes (PROESC) in the prisoners charged of drugs possession or consumption and gender violence crimes. Design: The sample was composed of 287 men. Main outcome measures: They completed the Demographic, Offense, and Behavioral Interview in Institutions, the International Personality Disorders Examination (IPDE), and PROESC. Results: We found that the proposed coding system presented high concordance, that is, high inter-rater reliability. Conclusion: The classification system for the correction and interpretation of narratives was shown to be reliable.
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Objectives: Proficiency in medical writing and publishing is essential for medical researchers. Workshops can play a valuable role in addressing these issues. However, there is a lack of systematic summaries of evidence on the evaluation of their impacts. So, in this systematic review, we aimed to evaluate all articles published on the impact of such workshops worldwide. Methods: We searched Ovid EMBASE, Ovid Medline, ISI Web of Science, ERIC database, and grey literature with no language, time period, or geographical location limitations. Randomized controlled trials, cohort studies, before-after studies, surveys, and program evaluation and development studies were included. We performed a meta-analysis on data related to knowledge increase after the workshops and descriptively reported the evaluation of other articles that did not have sufficient data for a meta-analysis. All analyses were performed using Stata software, version 15.0. Results: Of 23â 040 reports, 222 articles underwent full-text review, leading to 45 articles reporting the impacts of workshops. Overall, the reports on the impact of such workshops were incomplete or lacked the necessary precision to draw acceptable conclusions. The workshops were sporadic, and researchers used their own method of assessment. Meta-analyses of the impact on the knowledge showed that workshops could nonsignificantly increase the mean or percentage of participants' knowledge. Conclusion: In the absence of systematic academic courses on medical writing/publishing, workshops are conducted worldwide; however, reports on educational activities during such workshops, the methods of presentations, and their curricula are incomplete and vary. Their impact is not evaluated using standardized methods, and no valid and reliable measurement tools have been employed for these assessments.
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Reflective writing develops meta-cognition among students. Therefore, it is of interest to compare effectiveness of post lecture reflective writing to didactic lecture between individual and group reflective writing. Hence, we included 124 first-year students from AIIMS Bhopal, India and divided them in two groups of 62 students. Both groups took a pre-test using a reflection questionnaire. Students were taught reflective writing. Both groups attended physiology lectures on two different topics. First lecture on body fluids where Group A wrote reflections individually and Group B did so in sub-groups (B1 to B6). After another lecture on Pathophysiology of oedema, Group A wrote reflections in groups and Group B wrote individually (A1 to A6). Both groups took a test in the form of MCQ about reflective writing on lectures. After intervention both groups took a post-test using a reflection questionnaire. Mean and standard deviation of Pre-test is 3.86 ± 0.86 and Post-test is 7.58 ± 1.01, respectively. The Mean and standard deviation of reflection who wrote individually is 38.05 ± 4.41 and in group is 27.45 ± 3.93, respectively with p-value < 0.05. Evaluation of students who wrote reflection in groups after second lecture the mean and standard deviation of reflection who wrote individually is 38.22 ± 4.64 and in group is 27.03 ± 2.87 respectively with p-value < 0.05. The performance of students who wrote reflection in groups is not satisfactory as compared to students who wrote their reflection individually.
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Recent advancements in natural language processing, computational linguistics, and Artificial Intelligence (AI) have propelled the use of Large Language Models (LLMs) in Automated Essay Scoring (AES), offering efficient and unbiased writing assessment. This study assesses the reliability of LLMs in AES tasks, focusing on scoring consistency and alignment with human raters. We explore the impact of prompt engineering, temperature settings, and multi-level rating dimensions on the scoring performance of LLMs. Results indicate that prompt engineering significantly affects the reliability of LLMs, with GPT-4 showing marked improvement over GPT-3.5 and Claude 2, achieving 112% and 114% increase in scoring accuracy under the criteria and sample-referenced justification prompt. Temperature settings also influence the output consistency of LLMs, with lower temperatures producing scores more in line with human evaluations, which is essential for maintaining fairness in large-scale assessment. Regarding multi-dimensional writing assessment, results indicate that GPT-4 performs well in dimensions regarding Ideas (QWK=0.551) and Organization (QWK=0.584) under well-crafted prompt engineering. These findings pave the way for a comprehensive exploration of LLMs' broader educational implications, offering insights into their capability to refine and potentially transform writing instruction, assessment, and the delivery of diagnostic and personalized feedback in the AI-powered educational age. While this study attached importance to the reliability and alignment of LLM-powered multi-dimensional AES, future research should broaden its scope to encompass diverse writing genres and a more extensive sample from varied backgrounds.
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Original articles in the medical literature should have informative titles, also referred to as declarative titles. A nondeclarative title expresses the study's theme (topic) or, at most, the materials and methods used, whereas an informative title highlights the significance of the study findings (study's significance) and, at the very least, its results. A manuscript is typically organized to cover (i) the theme, (ii) materials and methods, (iii) results, and (iv) conclusion (study's significance). Consequently, a nondeclarative title typically encompasses only the (ii) stage, whereas an informative title extends to the (iii) or (iv) stages. This study underscores the importance of informative titles in medical papers and offers guidance for crafting titles that align with established paper writing fundamentals.
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INTRODUCTION: The TUSOM ONR STEM-IMPRESS Program sees a future where everyone is given opportunities and resources to become a physician regardless of race, gender, sexual orientation, social economic status, or any other differences in the shared learning environment. We strive to achieve this vision by EMPOWERING all college freshmen and sophomores to make the decision to enter the medical field; ENRICHING them with a well-rounded program that includes clinical rotations, research projects, MCAT preparations, interview tips, and panel sessions; and ENGAGING with them by establishing career-long mentorship. Program values: Equity-IMPRESS offers services to those who would otherwise not have access to opportunities and exposure to healthcare careers. Diversity-IMPRESS recognizes the importance of diversity in medicine including race, gender, sexual orientation, social economic status, ideology, or any other differences. Inclusion-IMPRESS values the uniqueness of each individual viewpoint, experience, and their combined contribution to a more inclusive environment in medicine. Culture-IMPRESS promotes a culture in medicine that reflects the richness and vitality in the culture of New Orleans and the surrounding area. The objective is to assess the precision of references generated by Chatbot Generative Pretrained Transformer version 4 (ChatGPT-4) in scientific literature pertaining to colon and rectal surgery. METHODS: Ten frequently studied keywords pertaining to colon and rectal surgery were chosen: colon cancer, rectal cancer, anal cancer, total neoadjuvant therapy, diverticulitis, low anterior resection, transanal minimally invasive surgery, ileal pouch anal anastomosis, abdominoperineal resection, and hemorrhoidectomy. ChatGPT-4 was prompted to search for the most representative citations for all keywords. After this, two separate evaluators meticulously examined the outcomes each key element, awarding full accuracy to generated citations in which there was no discrepancies in any of the fields when cross-referenced with the Scopus, Google, and PubMed databases. References from ChatGPT-4 underwent a thorough review process, which involved careful examination of key elements such as the article title, authors, journal name, publication year, and Digital Object Identifier (DOI). RESULTS: Forty-one of the 100 references generated by were fully accurate; however, but none included a DOI. Partial accuracy was observed in 67 of the references, which were identifiable by title and journal. Performance varied across specific keywords; for example, references for colon and rectal cancer were 100% identifiable by title and journal, but no term had 100% accuracy across all categories. Notably, none of the generated references correctly listed all authors. Conducted within a short timeframe during which ChatGPT4 is rapidly evolving and updating its knowledge base. CONCLUSIONS: While ChatGPT-4 offers improvements over its predecessors and shows potential for use in academic literature, its inconsistent performance across categories, lack of DOIs, and irregularities in authorship listings raise concerns about its readiness for application in the field of colon and rectal surgery research.
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This study investigates persuasive strategies used in the writings of Iranian university students in the field of teaching English as foreign language (TEFL). The study utilized the 7 principles of persuasive strategies presented by Cialdini (The psychology of persuasion, Quill William Morrow, New York 1984; Pre-suasion: A revolutionary way to influence and persuade, Simon & Schuster, New York 2016), which include 'reciprocity', 'commitment and consistency', 'social proof', 'liking', 'authority', 'scarcity', and 'unity'. The results indicate that strategies such as 'liking', 'unity', and 'authority' were used more frequently than other persuasive strategies. On the other hand, 'scarcity' was the least used strategy by the participants. Significant gender differences were also observed in the data. These findings have important pedagogical implications and suggest the need to incorporate persuasive strategies into instructional materials and teaching practices to enhance the persuasive writing skills of university students. Furthermore, gender differences highlight the importance of considering individual differences when teaching persuasive writing. Finally, the study discusses the pedagogical implications of these findings in the context of learning and teaching.
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Comunicação Persuasiva , Estudantes , Redação , Humanos , Estudantes/psicologia , Irã (Geográfico) , Masculino , Universidades , Feminino , Adulto Jovem , AdultoRESUMO
Writing is usually integrated in the curriculum of science studies. However, students often lack the skills to write for various audiences or, to produce a well written manuscript. We developed a concise project of 15 European Credits to improve the writing skills in an early phase of the bachelor study. Students worked on texts from various journals and looked at the writing styles. They rewrote texts in a popular and more scientific way and practiced with clear, vivid language, avoiding clutter and hedge words, considering a proper use of grammar and interpunction. Medical writing was also introduced during the project. Grading was based on rewriting for a non-expert and expert audience. A rewritten text was presented to the public in the form of a student-initiated survey. This project shows an inverted approach creating student ownership and enthusiasm for writing. In addition, we created and tested successfully a concise two-day workshop based on this project. Based on the results we herewith present the work as an idea to explore.
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OBJECTIVES: To evaluate the dimensional accuracy of occlusal veneers printed using a novel direct ink writing (DIW) system and a clinically approved dental composite. METHODS: A novel three-dimensional printer was developed based on the extrusion-based DIW principle. The printer, constructed primarily with open-source hardware, was calibrated to print with a flowable resin composite (Beautifil Flow Plus). The feasibility of this technology was assessed through an evaluation of the dimensional accuracy of 20 printed occlusal veneers using a laboratory confocal scanner. The precision was determined by pairwise superimposition of the 20 prints, resulting in a set of 190 deviation maps used to evaluate between-sample variations. RESULTS: Without material waste or residuals, the DIW system can print a solid occlusal veneer of a maxillary molar within a 20-minute timeframe. Across all the sampled surface points, the overall unsigned dimensional deviation was 30.1 ± 20.2 µm (mean ± standard deviation), with a median of 24.4 µm (interquartile range of 22.5 µm) and a root mean square value of 36.3 µm. The pairwise superimposition procedure revealed a mean between-sample dimensional deviation of 26.7 ± 4.5 µm (mean ± standard deviation; n = 190 pairs), indicating adequate precision. Visualization of the deviation together with the nonextrusion movements highlights the correlation between high-deviation regions and material stringing. SIGNIFICANCE: This study underscores the potential of using the proposed DIW system to create indirect restorations utilizing clinically approved flowable resin composites. Future optimization holds promise for enhancing the printing accuracy and increasing the printing speed.
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Polymer materials with multiple stimuli-responsive properties have demonstrated many potential and practical applications. By covalently introducing spiropyran (SP1) and spirothiopyran (STP) into the polyurethane backbone, photochromic, mechanochromic, and thermally discolored polymer materials have been prepared. In this work, we report for the first time that white light (violet, blue, and green light) above a certain intensity can activate STP to green color. Based on the above discovery, the polyurethane with SP1 and STP can exhibit reversible three-color changes (brown, green, and purple) in response to four stimuli: ultraviolet irradiation, white light irradiation, mechanical stress, and heat. The color-changing polymer materials have high color contrast and excellent reversibility, and can be used for reversible writing, anticounterfeiting and information encryption, etc.
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Direct ink writing (DIW) of high-temperature thin-film sensors holds significant potential for monitoring extreme environments. However, existing high-temperature inks face a trade-off between cost and performance. This study proposes a SiCN/RuO2/TiB2 composite ceramic ink. The added TiB2, after annealing in a high-temperature atmospheric environment, forms B2O3 glass, which synergizes with the SiO2 glass phase formed from the SiCN precursor to effectively encapsulate RuO2 particles. This enhances the film's density and adhesion to the substrate, preventing RuO2 volatilization at high temperatures. Additionally, the high conductivity of TiB2 improves the film's overall conductivity. Test results indicate that the SiCN/RuO2/TiB2 film exhibits high linearity from room temperature to 900 °C, high stability (resistance drift rate of 0.1%/h at 800 °C), and high conductivity (4410 S/m). As a proof of concept, temperature sensors and a heat flux sensor were successfully fabricated on a metallic hemispherical surface. Performance tests in extreme environments using high-power lasers and flame guns verified that the conformal thin-film sensor can accurately measure spherical temperature and heat flux, with a heat flux sensor response time of 53 ms. In conclusion, the SiCN/RuO2/TiB2 composite ceramic ink developed in this study offers a high-performance and cost-effective solution for high-temperature conformal thin-film sensors in extreme environments.
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Background: Anhedonia is a risk factor for a severe course of depression but is often not adequately addressed in psychotherapy. This study presents the Training to Enhance Reward Experience (T-REx), a novel self-help approach that uses savoring and mental imagery to target impairments in reward experience associated with anhedonia. We aimed to examine feasibility and acceptability of T-REx and exploratively investigated its effects on anhedonia and other clinical variables. Method: In an online, randomized controlled trial, 79 subjects participated for five days in T-REx or the active control condition Gratitude Writing (GW). We assessed changes in anhedonia, depression, and active behavior at inclusion, after the waiting period, post-intervention and at follow-up. The intervention effects were examined for the full sample and an anhedonic sub-sample. Results: T-REx and GW were equally feasible and clearly accepted by the sample. Both interventions significantly reduced depressive symptoms and increased behavioral activation. Although there was no significant main effect of the interventions, between-group differences were observed for depressive symptoms and active behavior at post-intervention and follow-up, favoring T-REx. Further, within-group changes for T-REx were larger than for GW. The observed effects had a greater magnitude in the anhedonic sub-sample, suggesting that individuals with more pronounced anhedonic symptoms derived greater benefit from the interventions. Discussion: This first study of T-REx provides promising results that should prompt further investigations of T-REx in clinical samples. The results suggest that T-REx has a positive effect on depression symptoms and active behavior. Further, its potential as a valuable adjunct to behavioral activation interventions is discussed.
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Chat generative pretrained transformer (ChatGPT) is a conversational language model powered by artificial intelligence (AI). It is a sophisticated language model that employs deep learning methods to generate human-like text outputs to inputs in the natural language. This narrative review aims to shed light on ethical concerns about using AI models like ChatGPT in writing assistance in the health care and medical domains. Currently, all the AI models like ChatGPT are in the infancy stage; there is a risk of inaccuracy of the generated content, lack of contextual understanding, dynamic knowledge gaps, limited discernment, lack of responsibility and accountability, issues of privacy, data security, transparency, and bias, lack of nuance, and originality. Other issues such as authorship, unintentional plagiarism, falsified and fabricated content, and the threat of being red-flagged as AI-generated content highlight the need for regulatory compliance, transparency, and disclosure. If the legitimate issues are proactively considered and addressed, the potential applications of AI models as writing assistance could be rewarding.
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INTRODUCTION: The pencil grasp and drawing patterns are specific to different age levels. So, if one knows a certain pattern for that particular age, it will guide the intervention plan for children with cerebral palsy (CP). The chances of improvement in diplegic CP are possible with the help of early intervention; therefore, early intervention is only possible if one knows the areas of delay and the age at which the intervention should be started. MATERIAL AND METHODS: It was a cross-sectional, case-control study. A total of 60 children were selected for the study, of which 30 (50%) were normal and 30 (50%) had diplegic cerebral palsy. A convenient sampling method is used for evaluation. RESULTS: The t-value for pencil grasp between the two groups, i.e., normal and CP diplegic, was 3.515 (P=0.001), revealing a significant difference in the grasp pattern of the two groups. Similarly, the t-value for drawing patterns between the two groups, i.e., normal and CP diplegic, was 5.796 (P = 0.001). A significant difference was found in the drawing patterns of both groups. CONCLUSION: Our study found that diplegic CP children performed lower on the Erhardt Developmental Prehension Assessment (EDPA) and showed larger variation in the pencil grasp and drawing than the normal children.
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Automated writing evaluation (AWE) has shown promise in enhancing students' writing outcomes. However, further research is needed to understand how AWE is perceived by middle school students in the United States, as they have received less attention in this field. This study investigated U.S. middle school students' perceptions of the MI Write AWE system. Students reported their perceptions of MI Write's usefulness using Likert-scale items and an open-ended survey question. We used Latent Dirichlet Allocation (LDA) to identify latent topics in students' comments, followed by qualitative analysis to interpret the themes related to those topics. We then examined whether these themes differed among students who agreed or disagreed that MI Write was a useful learning tool. The LDA analysis revealed four latent topics: (1) students desire more in-depth feedback, (2) students desire an enhanced user experience, (3) students value MI Write as a learning tool but desire greater personalization, and (4) students desire increased fairness in automated scoring. The distribution of these topics varied based on students' ratings of MI Write's usefulness, with Topic 1 more prevalent among students who generally did not find MI Write useful and Topic 3 more prominent among those who found MI Write useful. Our findings contribute to the enhancement and implementation of AWE systems, guide future AWE technology development, and highlight the efficacy of LDA in uncovering latent topics and patterns within textual data to explore students' perspectives of AWE.
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Extensive use of AI-generated texts culminated recently after the advent of large language models. Although the use of AI text generators, such as ChatGPT, is beneficial, it also threatens the academic level as students may resort to it. In this work, we propose a technique leveraging the intrinsic stylometric features of documents to detect ChatGPT-based plagiarism. The stylometric features were normalized and fed to classical classifiers, such as k-Nearest Neighbors, Decision Tree, and Naïve Bayes, as well as ensemble classifiers, such as XGBoost and Stacking. A thorough examination of the classifier was conducted by using Cross-Fold validation, hyperparameters tuning, and multiple training iterations. The results show the efficacy of both classical and ensemble learning classifiers in distinguishing between human and ChatGPT writing styles with a noteworthy performance of XGBoost where 100 % was achieved for accuracy, recall, and precision metrics. Moreover, the proposed XGBoost classifier outperformed the state-of-the-art result on the same dataset and same classifier highlighting the superiority of the proposed feature style extraction method over TF-IDF techniques. The ensemble learning classifiers were also applied to the generated dataset with mixed texts, where paragraphs are written by ChatGPT and humans. The results show that 98 % of the documents were classified correctly as either mixed or human. The last contribution consists in the authorship attribution of the paragraphs of a single document where the accuracy reached 92.3 %.