Parasympathetic tone activity, heart rate, and grimace scale in conscious horses of 3 breeds before, during, and after nociceptive mechanical stimulation.

BACKGROUND: Parasympathetic tone activity (PTA) in response to nociceptive stimulus in conscious non-sedated horses is unknown. OBJECTIVES: Study PTA, heart rate (HR), and horse grimace scale (HGS) at rest and during mechanical nociceptive stimulation. ANIMALS: Ninety healthy young adult horses (females, males): 30 each of Friesians, Quarter Horses, and Warmbloods. METHODS: Prospective control study. The study consisted of habituation to equipment (Day 1), baseline recordings (Days 2 and 3), and nociceptive testing applying mild pressure to the metacarpus (Day 4). Parasympathetic tone, HR, and HGS were recorded simultaneously on Days 2 to 4. Each study lasted 30 minutes and was done in triplicate at 3 different time points per day. RESULTS: Baseline PTA was not different among breeds. It decreased in Warmbloods and Quarter Horses during placement of the stimulus device without stimulation (P < .01). A significant decrease in PTA (P < .001) occurred during nociceptive stimulus (marked in Quarter Horses, intermediate in Warmbloods, and mild in Friesians). Heart rate and HGS increased significantly (P < .001) during the stimulus in all breeds but returned to baseline poststimulation. Friesians required higher pressure (P < .05) to elicit an aversive response to the stimulus. CONCLUSIONS: Horses' PTA, HR, and HGS change in response to a mild mechanical nociceptive stimulus with Friesians showing less variation. Stress induced a decrease in PTA in Quarter Horses and Warmbloods but not in Friesians. Friesians appeared to be more tolerant to pain based on PTA, HR, and HGS findings compared with other breeds.

Dynamic survival analysis: Modelling the hazard function via ordinary differential equations.

The hazard function represents one of the main quantities of interest in the analysis of survival data. We propose a general approach for parametrically modelling the dynamics of the hazard function using systems of autonomous ordinary differential equations (ODEs). This modelling approach can be used to provide qualitative and quantitative analyses of the evolution of the hazard function over time. Our proposal capitalises on the extensive literature on ODEs which, in particular, allows for establishing basic rules or laws on the dynamics of the hazard function via the use of autonomous ODEs. We show how to implement the proposed modelling framework in cases where there is an analytic solution to the system of ODEs or where an ODE solver is required to obtain a numerical solution. We focus on the use of a Bayesian modelling approach, but the proposed methodology can also be coupled with maximum likelihood estimation. A simulation study is presented to illustrate the performance of these models and the interplay of sample size and censoring. Two case studies using real data are presented to illustrate the use of the proposed approach and to highlight the interpretability of the corresponding models. We conclude with a discussion on potential extensions of our work and strategies to include covariates into our framework. Although we focus on examples of Medical Statistics, the proposed framework is applicable in any context where the interest lies in estimating and interpreting the dynamics of the hazard function.

Real-time path planning for autonomous vehicle off-road driving.

Background: Autonomous driving is a growing research area that brings benefits in science, economy, and society. Although there are several studies in this area, currently there is no a fully autonomous vehicle, particularly, for off-road navigation. Autonomous vehicle (AV) navigation is a complex process based on application of multiple technologies and algorithms for data acquisition, management and understanding. Particularly, a self-driving assistance system supports key functionalities such as sensing and terrain perception, real time vehicle mapping and localization, path prediction and actuation, communication and safety measures, among others. Methods: In this work, an original approach for vehicle autonomous driving in off-road environments that combines semantic segmentation of video frames and subsequent real-time route planning is proposed. To check the relevance of the proposal, a modular framework for assistive driving in off-road scenarios oriented to resource-constrained devices has been designed. In the scene perception module, a deep neural network is used to segment Red-Green-Blue (RGB) images obtained from camera. The second traversability module fuses Light Detection And Ranging (LiDAR) point clouds with the results of segmentation to create a binary occupancy grid map to provide scene understanding during autonomous navigation. Finally, the last module, based on the Rapidly-exploring Random Tree (RRT) algorithm, predicts a path. The Freiburg Forest Dataset (FFD) and RELLIS-3D dataset were used to assess the performance of the proposed approach. The theoretical contributions of this article consist of the original approach for image semantic segmentation fitted to off-road driving scenarios, as well as adapting the shortest route searching A* and RRT algorithms to AV path planning. Results: The reported results are very promising and show several advantages compared to previously reported solutions. The segmentation precision achieves 85.9% for FFD and 79.5% for RELLIS-3D including the most frequent semantic classes. While compared to other approaches, the proposed approach is faster regarding computational time for path planning.

Dual-Slope Path Loss Model for Integrating Vehicular Sensing Applications in Urban and Suburban Environments.

The development of intelligent transportation systems (ITS), vehicular ad hoc networks (VANETs), and autonomous driving (AD) has progressed rapidly in recent years, driven by artificial intelligence (AI), the internet of things (IoT), and their integration with dedicated short-range communications (DSRC) systems and fifth-generation (5G) networks. This has led to improved mobility conditions in different road propagation environments: urban, suburban, rural, and highway. The use of these communication technologies has enabled drivers and pedestrians to be more aware of the need to improve their behavior and decision making in adverse traffic conditions by sharing information from cameras, radars, and sensors widely deployed in vehicles and road infrastructure. However, wireless data transmission in VANETs is affected by the specific conditions of the propagation environment, weather, terrain, traffic density, and frequency bands used. In this paper, we characterize the path loss based on the extensive measurement campaign carrier out in vehicular environments at 700 MHz and 5.9 GHz under realistic road traffic conditions. From a linear dual-slope path loss propagation model, the results of the path loss exponents and the standard deviations of the shadowing are reported. This study focused on three different environments, i.e., urban with high traffic density (U-HD), urban with moderate/low traffic density (U-LD), and suburban (SU). The results presented here can be easily incorporated into VANET simulators to develop, evaluate, and validate new protocols and system architecture configurations under more realistic propagation conditions.

Estrategias didácticas para el aprendizaje autónomo y su repercusión en la salud de estudiantes de una universidad de Lambayeque

Fundamento: las estrategias didácticas para fomentar el aprendizaje autónomo son las estrategias cognitivas y afectivas que facilitan: aprender a aprender, aprender a hacer y aprender de forma cooperativa, para establecer la relación con sus pares y lograr el bienestar de la salud. Objetivo: determinar el nivel de implementación de las estrategias didácticas para lograr el aprendizaje autónomo y su repercusión en la salud de estudiantes de una universidad privada de Lambayeque. Métodos: se realizó una investigación con un enfoque cuantitativo, de tipo descriptiva, transversal y diseño cuasi experimental (estudio de antes-después). La muestra se obtuvo mediante muestreo no probabilístico por conveniencia con 390 estudiantes según el criterio de inclusión. Se evaluaron dos variables en sus dimensiones correspondientes. Para el análisis estadístico se empleó el programa IBM SPSS Statistics V.25. Resultados: para la variable, Estrategias didácticas, tanto en el pre-test como en el post-test, la mayoría la calificó como: siempre repercute en la salud mental. Con respecto a la variable, Aprendizaje autónomo, hubo un incremento en la calificación para la opción siempre, de 2,4 %, mientras que en: a veces, hubo una disminución del 1,7 % y en: nunca, el 1,8 %, mostraron la repercusión en la salud de los estudiantes. Conclusiones: se utilizaron estrategias didácticas para fomentar el aprendizaje autónomo que permitieron a los estudiantes: seleccionar, organizar, procesar y elaborar la información; de igual forma, para desarrollar la motivación y autorregulación para la toma de conciencia y control de su aprendizaje y mejorar la salud mental, al disminuir los niveles de estrés.

Foundation: teaching strategies to promote autonomous learning are cognitive and affective strategies that facilitate: learning to learn, learning to do and learning cooperatively, to establish relationships with peers and achieve health well-being. Objective: determine the level of implementation of teaching strategies to achieve autonomous learning and its impact on the health of students at a private university in Lambayeque. Methods: a research was carried out with a quantitative approach, descriptive, cross-sectional and quasi-experimental design (before-after study). The sample was obtained through non-probabilistic convenience sampling with 390 students according to the inclusion criterion. Two variables were evaluated in their corresponding dimensions. For the statistical analysis, the IBM SPSS Statistics V.25 program was used. Results: for the variable, Teaching strategies, both in the pre-test and in the post-test, the majority rated it as: it always has an impact on mental health. Regarding the variable, Autonomous Learning, there was an increase in the rating for the option always, of 2.4 %, while in: sometimes, there was a decrease of 1.7 % and in: never, of 1.8 %, which showed the impact on the health of the students. Conclusions: teaching strategies were used to promote autonomous learning that allowed students to: select, organize, process and elaborate information; likewise, to develop motivation and self-regulation for awareness and control of their learning and improve mental health, by reducing stress levels.

Accessible Autonomous Transportation and Services: Design Considerations From the Perspective of Consumers and Providers.

OBJECTIVE: To understand the priorities and preferences of people with disabilities (PwDs) and older adults regarding accessible autonomous vehicles (AVs) to address existing transportation barriers. DESIGN: Two national surveys, Voice of the Consumer and Voice of the Provider, were conducted to gather feedback from accessible AV consumers and providers, respectively, in the United States. SETTING: This U.S.-based study focused on PwDs and older adults who may face transportation challenges and those who provide or design AV solutions. PARTICIPANTS: The 922 consumers and 45 providers in the surveys encompassed a diverse range of disability types, caregiver roles, and age groups (N = 967). INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: The main outcomes were consumer usage needs and provider preferences for features in accessible autonomous transportation. Patterns in usage needs and feature preferences through 2-step clustering algorithm were applied subsequent to the descriptive analysis of participant demographics and their responses. RESULTS: Participants strongly preferred AV features enhancing personal transportation, especially for rural medical appointments. Most sought comprehensive AV automated features. Wheelchair users emphasized accessible entrances, particularly for lower-income brackets ($25,000-$49,000). Provider priorities closely aligned with consumer preferences, reinforcing content validity. CONCLUSIONS: The study highlights the importance of prioritizing wheelchair accessibility in AVs and improving access to medical appointments, especially in rural and low-income communities. Implications include developing inclusive AV services for PwDs and underserved populations. The research establishes a foundation for a more equitable and accessible transportation landscape through AV technology integration.

Adult aberrant astrocytes submitted to late passage cultivation lost differentiation markers and decreased their pro-inflammatory profile.

In amyotrophic lateral sclerosis (ALS), astrocytes are considered key players in some non-cell non-neuronal autonomous mechanisms that underlie motor neuron death. However, it is unknown how much of these deleterious features were permanently acquired. To assess this point, we evaluated if the most remarkable features of neurotoxic aberrant glial phenotypes (AbAs) isolated from paralytic rats of the ALS model G93A Cu/Zn superoxide dismutase 1 (SOD1) could remain upon long lasting cultivation. Real time PCR, immunolabelling and zymography analysis showed that upon many passages, AbAs preserved the cell proliferation capacity, mitochondrial function and response to different compounds that inhibit some key astrocyte functions but decreased the expression of parameters associated to cell lineage, homeostasis and inflammation. As these results are contrary to the sustained inflammatory status observed along disease progression in SOD1G93A rats, we propose that the most AbAs remarkable features related to homeostasis and neurotoxicity were not permanently acquired and might depend on the signaling coming from the injuring microenvironment present in the degenerating spinal cord of terminal rats.

Integrating Modular Pipelines with End-to-End Learning: A Hybrid Approach for Robust and Reliable Autonomous Driving Systems.

Autonomous driving navigation relies on diverse approaches, each with advantages and limitations depending on various factors. For HD maps, modular systems excel, while end-to-end methods dominate mapless scenarios. However, few leverage the strengths of both. This paper innovates by proposing a hybrid architecture that seamlessly integrates modular perception and control modules with data-driven path planning. This innovative design leverages the strengths of both approaches, enabling a clear understanding and debugging of individual components while simultaneously harnessing the learning power of end-to-end approaches. Our proposed architecture achieved first and second place in the 2023 CARLA Autonomous Driving Challenge's SENSORS and MAP tracks, respectively. These results demonstrate the architecture's effectiveness in both map-based and mapless navigation. We achieved a driving score of 41.56 and the highest route completion of 86.03 in the MAP track of the CARLA Challenge leaderboard 1, and driving scores of 35.36 and 1.23 in the CARLA Challenge SENSOR track with route completions of 85.01 and 9.55, for, respectively, leaderboard 1 and 2. The results of leaderboard 2 raised the hybrid architecture to the first position, winning the edition of the 2023 CARLA Autonomous Driving Competition.

Evolutionary and Structural Analysis of PP16 in Viridiplantae.

Members of the phloem protein 16 (PP16) gene family are induced by elicitors in rice and the corresponding proteins from cucurbits, which display RNA binding and intercellular transport activities, are accumulated in phloem sap. These proteins facilitate the movement of protein complexes through the phloem translocation flow and may be involved in the response to water deficit, among other functions. However, there is scant information regarding their function in other plants, including the identification of paralog genes in non-vascular plants and chlorophytes. In the present work, an evolutionary and structural analysis of the PP16 family in green plants (Viridiplantae) was carried out. Data mining in different databases indicated that PP16 likely originated from a larger gene present in an ancestral lineage that gave rise to chlorophytes and multicellular plants. This gene encodes a protein related to synaptotagmin, which is involved in vesicular transport in animal systems, although other members of this family play a role in lipid turnover in endomembranes and organelles. These proteins contain a membrane-binding C2 domain shared with PP16 proteins in vascular plants. In silico analysis of the predicted structure of the PP16 protein family identified several ß-sheets, one α-helix, and intrinsically disordered regions. PP16 may have been originally involved in vesicular trafficking and/or membrane maintenance but specialized in long-distance signaling during the emergence of the plant vascular system.

SiaN-VO: Siamese Network for Visual Odometry.

Despite the significant advancements in drone sensory device reliability, data integrity from these devices remains critical in securing successful flight plans. A notable issue is the vulnerability of GNSS to jamming attacks or signal loss from satellites, potentially leading to incomplete drone flight plans. To address this, we introduce SiaN-VO, a Siamese neural network designed for visual odometry prediction in such challenging scenarios. Our preliminary studies have shown promising results, particularly for flights under static conditions (constant speed and altitude); while these findings are encouraging, they do not fully represent the complexities of real-world flight conditions. Therefore, in this paper, we have furthered our research to enhance SiaN-VO, improving data integration from multiple sensors and enabling more accurate displacement predictions in dynamic flight conditions, thereby marking a significant step forward in drone navigation technology.

Aprendizaje autónomo en la educación a distancia en estudiantes de Psicopedagogía durante la COVID-19: una revisión sistemática

Introducción: Durante la COVID-19, la educación a distancia fue una oportunidad para el ejercicio del autoaprendizaje en salud mediante el uso de recursos electrónicos, con el dinamismo e impulso del aprendizaje autodidacta mediante el uso de las TIC. Objetivo: Valorar a través de una revisión sistemática el comportamiento del aprendizaje autónomo en estudiantes de Psicopedagogía durante la pandemia por la COVID-19. Método: Se realizó una revisión sistemática en publicaciones entre los años 2020-2022, donde se identificaron 767 artículos en Scopus, 64 registros en SciELO y 759 en Google Scholar, luego de su procesamiento quedó una muestra de 52 artículos. Fueron recopilados: título, año, tipo de artículo, contexto, revista, indexación, tema, comentario, posible uso en el artículo, referencia bibliográfica y DOI. Las referencias bibliográficas se procesaron mediante el gestor bibliográfico Mendeley. Resultados: Se destacó el creciente acto investigativo acerca de las estrategias metodológicas de la autonomía en los aprendizajes en educación básica y con aspiraciones a efectuar estudios en salud, durante la pandemia por la COVID-19. El país con más producciones académicas sobre aprendizaje autónomo en educación básica fue Perú con cuatro, seguido de Ecuador con tres producciones científicas vinculadas a salud; también se encontraron investigaciones de otras latitudes. Conclusiones: El aprendizaje autónomo es una prioridad de vigencia actual, indispensable para responder a las demandas de una sociedad cambiante y compleja. En los países de Latinoamérica hubo creciente interés investigativo sobre aprendizaje autónomo en educación básica y que aspiraron a efectuar estudios en salud durante la pandemia por la COVID-19.

Introduction: During COVID-19, distance education was an opportunity to practice self-learning in health through the use of electronic resources, with the dynamism and promotion of self-taught learning through the use of ICT. Objective: To assess, through a systematic review, the behavior of autonomous learning in Psychopedagogy students during the COVID-19 pandemic. Method: A systematic review was carried out on publications between the years 2020-2022, where 767 articles were identified in Scopus, 64 records in SciELO and 759 in Google Scholar, after processing a sample of 52 articles remained. The following were collected: title, year, type of article, context, journal, indexing, topic, comment, possible use in the article, bibliographic reference and DOI. Bibliographic references were processed using the Mendeley bibliographic manager. Results: The growing research act was highlighted about the methodological strategies of autonomy in learning in basic education and with aspirations to carry out health studies, during the COVID-19 pandemic. The country with the most academic productions on autonomous learning in basic education was Peru with four, followed by Ecuador with three scientific productions linked to health; Research from other latitudes was also found. Conclusions: Autonomous learning is a current priority, essential to respond to the demands of a changing and complex society. In Latin American countries, there was growing research interest in autonomous learning in basic education and they aspired to carry out health studies during the COVID-19 pandemic.

Introdução: Durante a COVID-19, a educação a distância foi uma oportunidade para praticar a autoaprendizagem em saúde através do uso de recursos eletrônicos, com a dinamização e promoção da aprendizagem autodidata através do uso das TIC. Objetivo: Avaliar, por meio de uma revisão sistemática, o comportamento da aprendizagem autônoma em estudantes de Psicopedagogia durante a pandemia da COVID-19. Método: Foi realizada uma revisão sistemática sobre publicações entre os anos de 2020 a 2022, onde foram identificados 767 artigos na Scopus, 64 registros na SciELO e 759 no Google Acadêmico, após processamento permaneceu uma amostra de 52 artigos. Foram coletados: título, ano, tipo de artigo, contexto, periódico, indexação, tema, comentário, possível uso no artigo, referência bibliográfica e DOI. As referências bibliográficas foram processadas utilizando o gerenciador bibliográfico Mendeley. Resultados: Destacou-se a crescente atuação de pesquisa sobre as estratégias metodológicas de autonomia na aprendizagem na educação básica e com aspirações à realização de estudos em saúde, durante a pandemia de COVID-19. O país com mais produções acadêmicas sobre aprendizagem autônoma na educação básica foi o Peru com quatro, seguido pelo Equador com três produções científicas ligadas à saúde; Pesquisas de outras latitudes também foram encontradas. Conclusões: A aprendizagem autónoma é uma prioridade atual, essencial para responder às exigências de uma sociedade complexa e em mudança. Nos países latino-americanos, havia um crescente interesse de investigação na aprendizagem autónoma no ensino básico e aspiravam a realizar estudos de saúde durante a pandemia da COVID-19.

A Comparison Study between Traditional and Deep-Reinforcement-Learning-Based Algorithms for Indoor Autonomous Navigation in Dynamic Scenarios.

At the beginning of a project or research that involves the issue of autonomous navigation of mobile robots, a decision must be made about working with traditional control algorithms or algorithms based on artificial intelligence. This decision is not usually easy, as the computational capacity of the robot, the availability of information through its sensory systems and the characteristics of the environment must be taken into consideration. For this reason, this work focuses on a review of different autonomous-navigation algorithms applied to mobile robots, from which the most suitable ones have been identified for the cases in which the robot must navigate in dynamic environments. Based on the identified algorithms, a comparison of these traditional and DRL-based algorithms was made, using a robotic platform to evaluate their performance, identify their advantages and disadvantages and provide a recommendation for their use, according to the development requirements of the robot. The algorithms selected were DWA, TEB, CADRL and SAC, and the results show that-according to the application and the robot's characteristics-it is recommended to use each of them, based on different conditions.

Performance Comparison of Meta-Heuristics Applied to Optimal Signal Design for Parameter Identification.

This paper presents a comparative study that explores the performance of various meta-heuristics employed for Optimal Signal Design, specifically focusing on estimating parameters in nonlinear systems. The study introduces the Robust Sub-Optimal Excitation Signal Generation and Optimal Parameter Estimation (rSOESGOPE) methodology, which is originally derived from the well-known Particle Swarm Optimization (PSO) algorithm. Through a real-life case study involving an Autonomous Surface Vessel (ASV) equipped with three Degrees of Freedom (DoFs) and an aerial holonomic propulsion system, the effectiveness of different meta-heuristics is thoroughly evaluated. By conducting an in-depth analysis and comparison of the obtained results from the diverse meta-heuristics, this study offers valuable insights for selecting the most suitable optimization technique for parameter estimation in nonlinear systems. Researchers and experimental tests in the field can benefit from the comprehensive examination of these techniques, aiding them in making informed decisions about the optimal approach for optimizing parameter estimation in nonlinear systems.

Robust Localization for Underground Mining Vehicles: An Application in a Room and Pillar Mine.

Most autonomous navigation systems used in underground mining vehicles such as load-haul-dump (LHD) vehicles and trucks use 2D light detection and ranging (LIDAR) sensors and 2D representations/maps of the environment. In this article, we propose the use of 3D LIDARs and existing 3D simultaneous localization and mapping (SLAM) jointly with 2D mapping methods to produce or update 2D grid maps of underground tunnels that may have significant elevation changes. Existing mapping methods that only use 2D LIDARs are shown to fail to produce accurate 2D grid maps of the environment. These maps can be used for robust localization and navigation in different mine types (e.g., sublevel stoping, block/panel caving, room and pillar), using only 2D LIDAR sensors. The proposed methodology was tested in the Werra Potash Mine located at Philippsthal, Germany, under real operational conditions. The obtained results show that the enhanced 2D map-building method produces a superior mapping performance compared with a 2D map generated without the use of the 3D LIDAR-based mapping solution. The 2D map generated enables robust 2D localization, which was tested during the operation of an autonomous LHD, performing autonomous navigation and autonomous loading over extended periods of time.

Caresses, whispers and affective faces: A theoretical framework for a multimodal interoceptive mechanism underlying ASMR and affective touch: An evolutionary and developmental perspective for understanding ASMR and affective touch as complementary processes within affiliative interactions.

Autonomous sensory meridian response (ASMR) and affective touch (AT) are two phenomena that have been independently investigated from separate lines of research. In this article, I provide a unified theoretical framework for understanding and studying them as complementary processes. I highlight their shared biological basis and positive effects on emotional and psychophysiological regulation. Drawing from evolutionary and developmental theories, I propose that ASMR results from the development of biological mechanisms associated with early affiliative behaviour and self-regulation, similar to AT. I also propose a multimodal interoceptive mechanism underlying both phenomena, suggesting that different sensory systems could specifically respond to affective stimulation (caresses, whispers and affective faces), where the integration of those inputs occurs in the brain's interoceptive hubs, allowing physiological regulation. The implications of this proposal are discussed with a view to future research that jointly examines ASMR and AT, and their potential impact on improving emotional well-being and mental health.

Overnight 1-mg Dexamethasone Suppression Test for Screening Cushing Syndrome and Mild Autonomous Cortisol Secretion (MACS): What Happens when Serum Dexamethasone Is Below Cutoff? How Frequent Is it?

OBJECTIVE: To determine the frequency of "invalid" 1-mg overnight dexamethasone (Dex) suppression tests (DSTs) (1-mg DST) on a large series of patients investigated for hypercortisolism and examine the interference of substances and clinical conditions that may explain low serum Dex levels. METHODS: A retrospective analysis of 1300 Dex-controlled 1-mg DST applied to patients screened for Cushing syndrome or mild autonomous cortisol secretion in a single center for which there were identified invalid tests and distinctive characteristics that may have interfered with the outcome. RESULTS: Among all tests, 146 (11.2%) were considered invalid (serum Dex levels <140 ng/dL, 36 [24.7%] of which were undetectable [<19.5 ng/dL]). In the Dex-undetectable group, 17% failed to take Dex correctly, 25% were on glucocorticoids (GCs), and 20% were on anticonvulsants and moderate CYP3A4 inducers. In the remaining 110 tests (serum Dex 20-140 ng/dL), 6.5% did not take Dex or were using GC, 22% were on anticonvulsants or CYP3A4 inducers, and another 13% had previous gastrointestinal tract abnormalities impairing drug absorption. CONCLUSION: Inappropriately low serum Dex levels during the 1-mg DST may lead to false-positive results. This is associated with recurrent use of CYP3A4-inducing drugs and/or gastrointestinal abnormalities. When serum Dex is undetectable, the key reason is failure to take the medication or the use of GC (when cortisol is suppressed). Simultaneous measurement of serum cortisol and Dex allows for DST validation, improving its accuracy and avoiding unnecessary repetitions. Adherence to verbal/written recommendations and actual use of medication are critical for interpreting the test.

Análisis de las horas de trabajo autónomo al implementarse el sistema de créditos en odontología / Analysis of self-employed hours when implementing the credit system in dentistry

Introducción: El Sistema de Créditos Transferibles fue desarrollado para traducir la carga de trabajo de los estudiantes en créditos académicos que son reconocidos en todos los países, apuntando al logro del aprendizaje. El aprendizaje autónomo es un objetivo que la mayoría de los programas educativos promueven como una opción estratégica para conectar la profesión, el entorno de estudio y las expectativas profesionales. Objetivo: Analizar las horas de trabajo autónomo utilizadas por los estudiantes para lograr los resultados de aprendizaje determinados en los programas de asignaturas, su efectividad en cuanto al rendimiento académico y su correspondencia con lo establecido en el plan de estudio, ajustado al Sistema de Créditos Transferibles. Métodos: Se realizó un análisis descriptivo transversal retrospectivo a partir de datos de un registro manual de estudiantes (n = 54) y docentes (n = 6) respecto a seis asignaturas de primer nivel de la Carrera de Odontología de la Universidad Autónoma de Chile, sede Temuco. Resultados: Los análisis revelan una incoherencia entre las horas de trabajo autónomo utilizadas por los estudiantes con respecto a lo establecido en el plan de estudio y las horas de trabajo extra-aula estimadas por los profesores. Conclusión: Se concluye que la implementación del Sistema de Créditos Transferibles por sí sola no asegura una mejora en el desempeño de los estudiantes, requiriendo revisar el procedimiento institucional para definirlas; por parte de los docentes una mayor apropiación de los resultados de aprendizajes y la didáctica necesaria para orientar a los estudiantes a obtener un mayor rendimiento del trabajo autónomo, por otro lado, los estudiantes deben ser responsables del uso consciente de dichas horas(AU)

Introduction: The Transferable Credit System was developed to translate student workload into academic credits that are recognized in all countries, aiming at learning achievement. Autonomous learning is an objective that most educational programs promote as a strategic option to connect career, study environment and professional expectations. Objective: Analyzing the hours of autonomous work used by students to achieve the learning outcomes determined in the subject programs, their effectiveness in terms of academic performance and their correspondence with what is established in the study plan, adjusted to the Transferable Credit System. Methods: A retrospective cross-sectional descriptive analysis was carried out using data from a manual record of students (n= 54) and teachers (n= 6) regarding six first level subjects of the Dentistry course of the Universidad Autónoma de Chile, Temuco campus. Results: The analysis revealed an incoherence between the hours of autonomous work used by the students with respect to what is established in the study plan and the hours of extra-classroom work estimated by the professors. Conclusion: It is concluded that the implementation of the Transferable Credit System alone does not ensure an improvement in student performance, requiring a review of the institutional procedure to define them; on the part of teachers a greater appropriation of the learning outcomes and the didactics necessary to guide students to obtain a higher yield of autonomous work, on the other hand, students must be responsible for the conscious use of these hours(AU)

Mature iPSC-derived astrocytes of an ALS/FTD patient carrying the TDP43A90V mutation display a mild reactive state and release polyP toxic to motoneurons.

Astrocytes play a critical role in the maintenance of a healthy central nervous system and astrocyte dysfunction has been implicated in various neurodegenerative disorders, including amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). There is compelling evidence that mouse and human ALS and ALS/FTD astrocytes can reduce the number of healthy wild-type motoneurons (MNs) in co-cultures or after treatment with astrocyte conditioned media (ACM), independently of their genotype. A growing number of studies have shown that soluble toxic factor(s) in the ACM cause non-cell autonomous MN death, including our recent identification of inorganic polyphosphate (polyP) that is excessively released from mouse primary astrocytes (SOD1, TARDBP, and C9ORF72) and human induced pluripotent stem cells (iPSC)-derived astrocytes (TARDBP) to kill MNs. However, others have reported that astrocytes carrying mutant TDP43 do not produce detectable MN toxicity. This controversy is likely to arise from the findings that human iPSC-derived astrocytes exhibit a rather immature and/or reactive phenotype in a number of studies. Here, we have succeeded in generating a highly homogenous population of functional quiescent mature astrocytes from control subject iPSCs. Using identical conditions, we also generated mature astrocytes from an ALS/FTD patient carrying the TDP43A90V mutation. These mutant TDP43 patient-derived astrocytes exhibit key pathological hallmarks, including enhanced cytoplasmic TDP-43 and polyP levels. Additionally, mutant TDP43 astrocytes displayed a mild reactive signature and an aberrant function as they were unable to promote synaptogenesis of hippocampal neurons. The polyP-dependent neurotoxic nature of the TDP43A90V mutation was further confirmed as neutralization of polyP in ACM derived from mutant TDP43 astrocytes prevented MN death. Our results establish that human astrocytes carrying the TDP43A90V mutation exhibit a cell-autonomous pathological signature, hence providing an experimental model to decipher the molecular mechanisms underlying the generation of the neurotoxic phenotype.

Bio-Inspired Autonomous Navigation and Formation Controller for Differential Mobile Robots.

This article proposes a decentralized controller for differential mobile robots, providing autonomous navigation and obstacle avoidance by enforcing a formation toward trajectory tracking. The control system relies on dynamic modeling, which integrates evasion forces from obstacles, formation forces, and path-following forces. The resulting control loop can be seen as a dynamic extension of the kinematic model for the differential mobile robot, producing linear and angular velocities fed to the mobile robot's kinematic model and thus passed to the low-level wheel controller. Using the Lyapunov method, the closed-loop stability is proven for the non-collision case. Experimental and simulated results that support the stability analysis and the performance of the proposed controller are shown.

Autonomous sensory meridian response is associated with a larger heartbeat-evoked potential amplitude without differences in interoceptive awareness.

Autonomous sensory meridian response (ASMR) describes the experience of a pleasant body sensation accompanied by a feeling of well-being and relaxation in response to specific audiovisual stimuli, such as whispers and personal attention. Previous work suggests a relationship between this experience with the processing of affective and body states; however, no research has explored differences in interoception between people experiencing ASMR and those who do not. We hypothesized that the ASMR experience is based on interoception processing. To test this, we assessed group differences across different dimensions of interoception: Interoceptive sensibility (IS), measured using the multidimensional assessment of interoceptive awareness (MAIA); Interoceptive accuracy score (IAS), measured by calculating performance in a heartbeat counting task (HCT), and the electrophysiological index of interoception, the heartbeat evoked potential (HEP), which was calculated during the HCT and an ASMR tingle reporting task (ASMR-TRT). Our results showed that IS and IAS, dimensions requiring conscious awareness, showed no differences between groups. However, HEP amplitude was larger in the ASMR group in both tasks. We concluded that the ASMR experience is based on an unconscious interoceptive mechanism, reflected by HEP, where exteroceptive social-affective stimuli are integrated to represent a body state of positive affective feelings and relaxation, as has been described for affective touch. The relevance of this finding relies on that interoceptive function, body regulation, and emotional/affective experiences are fundamental for well-being, and the relationship between ASMR and interoception opens the way to future research exploring the causal relationship between them and their potential clinical applications.