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In this paper, the effects of the rapid advancement of generative artificial intelligence (Gen AI) in higher education (HE) are discussed. A mixed exploratory research approach was employed to understand these impacts, combining analysis of current research trends and students’ perceptions of the effects of Gen AI tools in academia. Through bibliometric analysis and systematic literature review, 64 publications (indexed in the SCOPUS and Web of Science databases) were examined, highlighting Gen AI’s disruptive effect on the pedagogical aspects of HE. The impacts identified by the literature were compared with the perceptions held by computer science students of two different HE institutions (HEIs) on the topic. An exploratory study was developed based on the application of a questionnaire to a group of 112 students. The results suggest that while Gen AI can enhance academic work and learning feedback, it requires appropriate pedagogical support to foster critical, ethical, and digital literacy competencies. Students demonstrate awareness of both the risks and benefits associated with Gen AI in academic settings. The research concludes that failing to recognize and effectively use Gen AI in HE impedes educational progress and the adequate preparation of citizens and workers to think and act in an AI-mediated world.

During the transition to menopause, women experience a variety of physical and psychological symptoms that are directly or indirectly linked to changes in hormone secretion. Establishing animal models with intact ovaries is essential for understanding these interactions and finding new therapeutic targets. In this study, we assessed the endocrine profile, as well as the estrous cycle, in the 4-vinylcyclohexene diepoxide (VCD)-induced follicular depletion rat model in 10-day intervals over 1 month to accurately establish the best period for studies of the transition period. Twenty-eight-day-old female rats were injected daily with VCD or oil s.c. for 15 days and euthanized in the diestrus phase approximately 70, 80, 90 and 100 days after the onset of treatment. The percentage of rats showing irregular cycles and the plasma level of FSH increased only in the 100-day VCD group. Plasma anti-Müllerian hormone (AMH) and progesterone were lower in all VCD groups compared to control groups, while estradiol remained unchanged or higher. As in control groups, dihydrotestosterone (DHT) progressively decreased in the 70-90-day VCD groups; however, it was followed by a sharp increase only in the 100-day VCD group. No changes were found in plasma corticosterone, prolactin, thyroid hormones or luteinizing hormone. Based on the estrous cycle and endocrine profile, we conclude that 1) the time window from 70 to 100 days is suitable to study a perimenopause-like state in this model, and 2) regular cycles with low progesterone and AMH and normal FSH can be used as markers of the early/mid-transition period, whereas irregular cycles associated with higher FSH and DHT can be used as markers of the late transition period to estropause.

Currently, Brazil does not have a registry of abdominal wall hernia surgeries. In this paper we describe the creation of HERNIACLINIC-QoL, that aims to fill this gap, and its preliminary results. A RedCap form was developed to collect data on patients and surgeries for abdominal hernia repair in a private practice hospital. Data input errors were checked every 30 days, and a preliminary analysis of the database as a whole was carried out in 2024. We registered 554 patients (201 ventral, 227 inguinal and 103 for both hernias). The form needed corrections in the fields: preoperative data, hernia sizes and classifications, rectum diastasis and anesthesia type, ensuring completeness of data and simplifying the creation of statistical reports. HERNIACLINIC-QoL may become a valuable tool for hernia care and research, as its use is expanded to include more surgeons and more patients. Protocol Register at Brazilian Registry of Clinical Trials (ReBEC), ID: RBR-5vmhdfs https://ensaiosclinicos.gov.br/rg/RBR-5vmhdfs. •HERNIACLINIC-QoL is Brazil's first abdominal hernia surgery registry.•It tracks patient data, surgery details, and outcomes over two years.•Significant quality-of-life improvements observed post-surgery.•Pain and activity restriction decreased at 12 and 24 months.•Data informs quality improvement for hernia care in Brazil.

The integration of artificial intelligence (AI) into health sciences students' education holds significant importance. The rapid advancement of AI has opened new horizons in scientific writing and has the potential to reshape human-technology interactions. AI in education may impact critical thinking, leading to unintended consequences that need to be addressed. Understanding the implications of AI adoption in education is essential for ensuring its responsible and effective use, empowering health sciences students to navigate AI-driven technologies' evolving field with essential knowledge and skills. This study aims to provide details on the study protocol and the methods used to investigate the usability and efficacy of ChatGPT, a large language model. The primary focus is on assessing its role as a supplementary learning tool for improving learning processes and outcomes among undergraduate health sciences students, with a specific emphasis on chronic diseases. This single-blinded, crossover, randomized, controlled trial is part of a broader mixed methods study, and the primary emphasis of this paper is on the quantitative component of the overall research. A total of 50 students will be recruited for this study. The alternative hypothesis posits that there will be a significant difference in learning outcomes and technology usability between students using ChatGPT (group A) and those using standard web-based tools (group B) to access resources and complete assignments. Participants will be allocated to sequence AB or BA in a 1:1 ratio using computer-generated randomization. Both arms include students' participation in a writing assignment intervention, with a washout period of 21 days between interventions. The primary outcome is the measure of the technology usability and effectiveness of ChatGPT, whereas the secondary outcome is the measure of students' perceptions and experiences with ChatGPT as a learning tool. Outcome data will be collected up to 24 hours after the interventions. This study aims to understand the potential benefits and challenges of incorporating AI as an educational tool, particularly in the context of student learning. The findings are expected to identify critical areas that need attention and help educators develop a deeper understanding of AI's impact on the educational field. By exploring the differences in the usability and efficacy between ChatGPT and conventional web-based tools, this study seeks to inform educators and students on the responsible integration of AI into academic settings, with a specific focus on health sciences education. By exploring the usability and efficacy of ChatGPT compared with conventional web-based tools, this study seeks to inform educators and students about the responsible integration of AI into academic settings. ClinicalTrails.gov NCT05963802; https://clinicaltrials.gov/study/NCT05963802. PRR1-10.2196/51873.

Industry 5.0 changes the paradigm of the current production model, with repercussions throughout the value chain, and opens up opportunities for new approaches that include reducing waste to optimize the use of the planet’s resources. This paper proposes a functional and executable model that implements a Holonic Manufacturing System (HMS) architecture inspired by the I5.0 guidelines. This architecture presents the factory floor as a service provider for the product to be built, intending to make the manufacturing process adaptable to changes. The model uses Reference nets as the modeling language, a high-level class of Petri nets, Java programming language as the annotation language, and free tool support. The model can be used to perform software-level simulations and can also be interconnected to existing physical devices using Internet of things technologies, enabling interactions between Cyber–Physical Systems (CPSs). It thus allows for the control of the shop floor and the reuse of the current machine park to make its adoption more sustainable. The model was used to generate several simulation results, which are presented and analyzed, thus demonstrating the model’s usefulness.

Controllers for discrete-event systems are commonly designed using state-based formalisms, like state diagrams and Petri nets. These formalisms are strongly supported by the concept of events, which, from an automation system perspective, can be associated with a simple change in the value of a signal or more complex behavioral evolutions of the signals. In this paper, the characterization of several types of events is proposed, associated with different types of signals, such as Boolean and multivalued signals. The major goal of this characterization is to improve the compactness of the model, benefiting the editing and visual interpretation of the graphical model but keeping precise execution semantics, which in turn allows for the use of computational tools covering the different stages of system development. The behavioral model of the controller is produced using a non-autonomous class of Petri nets, the IOPT nets, and the associated IOPT-Tools, which supports the specification, simulation, property verification, and automatic code generation ready to be deployed into implementation platforms. All the types of proposed events have a behavioral sub-model executed concurrently with the main model of the controller. An application example is provided to illustrate some of the advantages of the adoption of the proposed approach, encapsulating the behavioral dependencies on the evolution of input signals into events.

Pristine multiwalled carbon nanotubes (P-MWCNTs) were functionalized with carboxylic groups (MWCNT-COOH) through oxidation reactions and then reduced to produce hydroxyl groups (MWCNT-OH). Pristine and functionalized MWCNTs were used to produce poly(hydroxybutyrate-co-hydroxyvalerate) (PHBV) nanocomposites with 0.5 wt% of MWCNTs. MWCNT functionalization was verified by visual stability in water, infrared and Raman spectroscopy, and zeta potential measurements. Pristine and functionalized MWCNTs acted as the nucleating agent in a PHBV matrix, as verified by differential scanning calorimetry (DSC). However, the dispersion of filler into the matrix, thermal stability, and direct current (DC) conductivity were affected by MWCNT functionalization. Scanning electron microscopy (SEM) showed that filler dispersion into the PHBV matrix was improved with MWCNT functionalization. The surface roughness was reduced with the addition and functionalization of MWCNT. The thermal stability of PHBV/MWCNT-COOH, PHBV/P-MWCNT, and PHBV/MWCNT-OH nanocomposites were 20, 30, and 30 °C higher than neat PHBV, respectively, as verified by thermogravimetry analysis (TGA). Addition of pristine and functionalized MWCNTs provided electrical conductivity in nanocomposite, which was higher for PHBV/P-MWCNTs (1.2 × 10−5 S cm−1).

The scarcity of drinking water affects various regions of the planet. Although climate change is responsible for the water availability, humanity plays an important role in preserving this precious natural resource. In case of negligence, the likely trend is to increase the demand and the depletion of water resources due to the increasing world population. This paper addresses the development, design and construction of a low cost system for measuring soil volumetric water content (θ), electrical conductivity (σ) and temperature (T), in order to optimize the use of water, energy and fertilizer in food production. Different from the existing measurement instruments commonly deployed in these applications, the proposed system uses an auto-balancing bridge circuit as measurement method. The proposed models to estimate θ and σ and correct them in function of T are compared to the ones reported in literature. The final prototype corresponds to a simple circuit connected to a pair of electrode probes, and presents high accuracy, high signal to noise ratio, fast response, and immunity to stray capacitance. The instrument calibration is based on salt solutions with known dielectric constant and electrical conductivity as reference. Experiments measuring clay and sandy soils demonstrate the satisfactory performance of the instrument.

Purpose This study retrospectively analyzed the risk factors for transchemotherapy dysgeusia. Methods Before each chemotherapy cycle, patients were routinely evaluated for the presence/severity of dysgeusia based on the Common Terminology Criteria for Adverse Events (CTCAE) v5.0 scale for adverse effects and graded as follows: 0, no change in taste; 1, altered taste with no impact on eating habits; or 2, altered taste with an impact on eating habits. Information from 2 years of evaluations was collected and patient medical records were reviewed to obtain data on chemotherapy cycle, sex, age, body mass index, body surface area, primary tumor, chemotherapy protocol, and history of head and neck radiotherapy. The X 2 test and multinomial logistic regression were used for statistical analysis (SPSS 20.0, p < 0.05). Results Among 7425 total patients, 3047, 2447, and 1931 were evaluated after the first, second, and third chemotherapy cycles, respectively. One-fifth of the patients (19.0%) presented a significant loss of taste, with 1118 (15.0%) showing grade 1 dysgeusia and 442 (6.0%) showing grade 2 dysgeusia. The chemotherapy duration ( p < 0.001), female sex ( p < 0.001), location of the primary tumor in the uterus ( p = 0.008), head and neck ( p = 0.012), and testicles ( p = 0.011), and use of ifosfamide ( p = 0.009), docetaxel ( p = 0.001), paclitaxel ( p < 0.001), pertuzumab ( p = 0.005), bevacizumab ( p < 0.001), and dacarbazine ( p = 0.002) independently increased the risk of dysgeusia. In head and neck tumors, a previous history of radiotherapy significantly increased the prevalence of dysgeusia ( p = 0.017), and the use of cisplatin ( p = 0.001) increased this prevalence. Conclusion Cycles of chemotherapy, sex, uterine cancer, head and neck tumors, testicular cancer, ifosfamide, docetaxel, paclitaxel, pertuzumab, bevacizumab, and dacarbazine increase the risk of dysgeusia.

Background Generative artificial intelligence (AI) integrated programs such as Chat Generative Pre-trained Transformers (ChatGPT) are becoming more widespread in educational settings, with mounting ethical and reliability concerns regarding its usage. This paper explores the experiences, perceptions, and usability of ChatGPT in undergraduate health sciences students. Methods Twenty-seven students at Carleton University (Canada) were enrolled in a crossover randomized controlled trial study from a Health Sciences course during the Fall 2023 academic term. The intervention condition involved the use of ChatGPT-3.5, whereas the control condition involved using conventional web-based tools. Technology usability was compared between ChatGPT-3.5 and the traditional tools using questionnaires. Focus group discussions were conducted with seven students to further elaborate on student perceptions and experiences. Reflexive thematic analysis was employed to identify themes from the focus group data. Results Easiness of learnability for personal use and a perception of quick learnability towards ChatGPT-3.5 were significantly higher, compared to conventional online tools from the Systems Usability Scale. Qualitative results highlighted strong benefits of ChatGPT-3.5, such as being a tool for increased overall productivity and brainstorming. However, students identified challenges associated with reliability and accuracy, and concerns about academic integrity. Conclusions Despite the benefits and positive usability of ChatGPT-3.5 identified by students, an explicit need for the development of policies, procedures and regulations remains. An established framework of best practices for the usage of AI within health science education is necessary. This will ensure accountability of users and lead to a more effective integration of AI technologies into academic settings.