Miracle-dz/UniFAR-FTUs huggingface dataset:
Using mobile health to encourage physical activity in individuals with intellectual disability: a pilot mixed methods feasibility study

Background Many individuals with intellectual disability (ID) have a sedentary lifestyle. Few interventions aimed at increasing their level of physical activity (PA) have shown lasting effects. Aim To assess the feasibility and acceptability of a pilot intervention study using innovative mobile health (mHealth) support systems to encourage PA in individuals with ID. Methods Nine individuals with ID and a low level of PA, aged 16–36 years, were included in the present convergent triangulation mixed method design. Two mHealth support systems (apps) were developed and tested. PA was measured with a Fitbit smartwatch, accelerometer, the International Physical Activity Questionnaire—Short Form (IPAQ-S), and Goal attainment scaling. Data were collected through online pre-, mid- (4 weeks), and post-intervention (12 weeks) questionnaires and activity trackers. Semi-structured qualitative interviews with participants and/or a family or staff member were held after the 12-week follow-up. Data were analyzed using conventional nonparametric statistics and thematic analyses. Results The response rate and retention to the trial were 16% and 100%, respectively. Data quality was high, except for missing data from Fitbit activity trackers of approximately 30% from the 4- and 12-week follow-up stages. The feasibility challenges with activity trackers include rashes, size, non-acceptance, and loss of motivation. Participants and family members/staff reported interest in the study theme and were pleased with the data collection method. All but one participant achieved their PA goals. Most participants reported being satisfied with the apps as they were enjoyable or provided a reminder for performing physical and other activities. Social support for PA among family members also increased. However, app support from staff and family members was needed, and apps were not used regularly. Two of nine participants (22%) had increased their PA measured as steps per day with Fitbit at the 12-week follow-up. Conclusions The acceptability and feasibility of using tailored mobile applications in natural settings to increase PA among adults with ID are promising. This study aligns with previous studies in showing the challenges to increasing PA, which requires the inclusion of family members, staff, and stakeholders. The intervention requires modifications before a randomized controlled trial can be conducted.
Inclusion and adaptation beyond disability: Using virtual reality to foster empathy.

BACKGROUND Virtual reality (VR) has the potential to be a powerful tool in promoting empathy towards inclusion, particularly for individuals with impairments such as mobility difficulties, vision deficits, or autism but also about pregnancy, which can create temporary difficulties. By immersing users in simulated environments that replicate the experiences of those with different abilities, VR can create a sense of understanding and empathy for those who face challenges in their daily lives. For example, VR experiences can simulate the experience of navigating space as someone with a mobility impairment, providing a new perspective and appreciation for the difficulties that others face. Similarly, VR experiences can simulate the experience of vision impairment, pregnancy, or autism, providing a window into the challenges faced by those with these conditions and fostering empathy and understanding. MATERIAL AND METHODS During the development of this study, field experts were consulted to ensure the robustness of the methods employed. Then, questionnaires were specifically developed to explore disabilities and challenges related to inclusion and were administered to a large population. Additionally, guided interviews were conducted with individuals who possess specific impairments to gather first-hand insights. RESULTS The results obtained from the questionnaires and interviews provide a comprehensive overview of the inclusion challenges that necessitate attention and resolution. By drawing on the expertise of both experts and individuals with lived experiences, a holistic landscape of inclusion challenges has been established. CONCLUSIONS The VR emerges as a powerful tool for promoting inclusion and fostering understanding among individuals. Its capacity to create immersive experiences that facilitate empathy has the potential to reshape society into a more compassionate and empathetic one. By leveraging the unique capabilities of VR, we can bridge the gap between different perspectives, fostering greater understanding, acceptance, and inclusivity. Med Pr. 2023;74(3):171-85.
A Self-Oscillated Feedback Network for Push–Pull Resonant Power Converters

This article proposes a self-oscillated feedback network for push–pull resonant topologies. Resonant topologies such as Class E power amplifiers are suitable for very high frequency (VHF) switching applications as they ideally have no switching losses. However, since VHF gate driving still requires complex and expensive auxiliary circuits, a self-oscillated driving method can be considered. Conventional self-oscillated feedback networks are only applicable to single-ended topologies, which are limited to low-power applications. On the other hand, the proposed self-oscillated feedback network is expandable to push–pull topologies and can significantly increase power handling capability. The proposed circuit maintains complementary symmetry by utilizing the coupled inductor and virtual ground characteristics and satisfies the oscillation criteria for all operating conditions. The proposed circuit is experimentally verified through a 3.3 MHz, 30 W push–pull power oscillator prototype.
DEVELOPING YOUNG CHILDREN’S TEXT PROCESSING SKILLS BY USING DETECTIVE BOARD GAMES AND RWCT TECHNIQUES

Using board games in the classroom is an opportunity for experiential learning. A previous examination proves that the systematic use of Rory's Story Cubes in the methodology of native language teaching can be included as a playful method because they are useful in the development of oral and written communication. I have reflected on this with a new project focusing on reading skills. My goal is to examine how the card games, Black Stories Junior (Red Stories, Rainbow Stories) combined with RWCT techniques (Reading and Writing for Critical Thinking) can develop the interpretation of texts in 9 to 10-year-old students. The games contain riddles with exciting criminal cases for children. The players try to reconstruct the stories by asking, guessing, and fiddling. RWCT methods are the sum of cooperative, interactive and reflective techniques that make the learning process more successful and creative. In the first period, the experimental and the control group were formed. After that, the experimental group played the card game 30 times and got to know graphic organizers, drama pedagogical methods, and creative writing tasks related to the short stories. The activities were carried out under the supervision of the methodical leader of the experiment and recorded with a video camera. In the end, the students could use the learned methods independently and achieved more points on reading comprehension tests than the control group members. Thanks to the drama techniques the students were able to write in a more meaningful way from another person's perspective. The results show that the consistent use of the given board game is beneficial for reading and writing skills. The project's achievements may contribute to the widespread educational use of board games and RWCT techniques, thereby expanding the methodology of native language teaching.
Multiplexed Genetic Perturbations of the Regulatory Network of E. coli.

Despite advances in DNA sequencing, we have yet to understand how an organism’s phenotype relates to the contents of their genome. However it has become clear that the impact of genes are context dependant. The mere presence of a gene within a genome does not inform us of when it is expressed, and which other genes are expressed along with it. Understanding how gene expression is regulated is a necessary piece of understanding how phenotypes emerge from a given genotype. Transcription factors, which can activate or repress the expression of a gene, form a complex network of interactions between themselves and their targeted genes. This network consists of a hierarchy of groups of strongly connected transcription factors, each relating to distinct cellular processes. Is the structure of this transcriptional regulatory network significant to the transcriptional response of a cell? Here we use a programmable DNA binding protein called CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats) to perturb gene expression of global regulators within the transcriptional regulatory network. These global regulators are regulating many distinct cellular processes and have many genetic targets. The CRISPR system allows us to perturb these regulators in all possible combinations, including higher order perturbations with potentially all targeted global regulators perturbed at the same time. We then record both the expression pattern of the transciptome using RNA sequencing, and the fitness of each strain. We find that the structure of the regulatory network increases the dimensionality of the transcriptional response rather than reducing it. This results in significant high order epistasis beyond pair-wise interactions. This has implications for how these networks evolve. The pair-wise epistasis we find between global transcription factors rely on the presence or absence of other perturbations. This implies that other perturbations could act as potentiating mutations. The number of potential evolutionary paths increases with high order epistasis, although this alone tells us nothing about the quality of those paths. Importantly, the replicates for this thesis are still on-going and the data presented here has not yet excluded experimental artefacts.
Global, regional, and national burden of digestive diseases: findings from the global burden of disease study 2019

Background The global burden of digestive diseases has been rising in the last 30 years. The rates and trends of incidence, deaths, and disability-adjusted life-years (DALYs) for digestive diseases need to be investigated. Methods We extracted the data on overall digestive diseases and by cause between 1990–2019 from the Global Burden of Diseases 2019 website, including the absolute number and the corresponding age-standardized rates of incidence (ASIR), deaths (ASDR), and DALYs (ASDALYs). Results Globally, the incident cases, deaths, and DALYs of digestive diseases in 2019 increased by 74.44, 37.85, and 23.46%, respectively, compared with that in 1990, with an increasing ASIR of 0.09%, as well as decreasing ASDR and ASDALYs of 1.38 and 1.32% annually. The sociodemographic index (SDI) of overall digestive diseases showed a slight increase in ASIR from low to middle-low regions. The downtrend in ASDR and ASDALYs was found in all SDI regions. The burden of incidence was higher in females, while the burden of deaths and DALYs was higher in males for the overall digestive diseases and most causes. The estimated annual percentage changes were significantly associated with the baseline ASIR, ASDR, and ASDALYs for the overall digestive diseases, and the negative correlations between ASDR, ASDALYs, and human development index both in 1990 (R = −0.68, R = −0.69) and 2019 (R = −0.71, R = −0.73) were noticed. Conclusion The findings indicate that digestive diseases remain a significant public health burden, with substantial variation across countries, sexes, and age groups. Therefore, implementing age, gender, and country-specific policies for early screening and targeted interventions could significantly reduce the global burden of digestive diseases.
A Novel Learning Dictionary for Sparse Coding-Based Key Point Detection

Recently, a sparse coding-based key point detector (SCK) was proposed. An SCK shows very impressive performance compared with state-of-the-art key point detection methods on different challenging conditions, such as variations in scale, rotation, context, and nonuniform lighting. The rotational-invariant dictionary in the SCK is, however, manually generated using a time-consuming process of selecting a good seed dictionary and combining multiple versions of its rotated atoms. In this work, the process is automated using a novel duplet autoencoder structure, in which the weights between the input and the hidden layers are designed to embed a rotational-invariant dictionary. A set of loss functions is also proposed to enforce the learning process. A novel retinal image registration pipeline that best uses the new detector is also designed with thorough analysis for selection of different technologies. Extensive experiments on four challenging datasets have confirmed that SCK with the learned dictionary achieves state-of-the-art key point detection performance.
Identification of dynamic systems assisted by an autoregressive recurrent model

The identification of parameters in dynamic systems usually first requires modeling the system as nonlinear differential equations based on physical principles, which then can be evaluated to search for a set of optimal parameters that enable the mathematical model to reproduce some desired behavior of the real system. To overcome the necessity of complex modeling and to possibly reduce the number of extensive experimental evaluations of the real system or numerical evaluations of the differential equations, strategies from machine learning may be applied. The proposed method uses recurrent architectures such as Long Short‐Term Memory (LSTM) networks as core to predict the system development from initial conditions and parameter values. The trainable weights of the model are optimized based on a set of training data containing parameter values and corresponding solution trajectories generated by evaluation of the system to be investigated. The trained model may then be used to identify unknown system parameter values related to a specific solution trajectory by solving an optimization problem for the inputs of the machine learning model.
Factores quirúrgicos pronósticos del neuroblastoma en el Centro Regional Oriental de Oncología Pediátrica de Holguín, Cuba

Introducción: El neuroblastoma es la neoplasia sólida fuera de la cavidad craneal más frecuente en la edad pediátrica. Su particularidad se refleja en varias características clínicas y biológicas que se toman en cuenta para predecir los resultados terapéuticos. Objetivo: Identificar los factores quirúrgicos pronósticos en los pacientes diagnosticados con neuroblastoma en el Centro Regional Oriental de Oncología Pediátrica de Holguín, Cuba, durante la etapa comprendida de enero de 2010 a diciembre del 2022. Métodos: Se realizó un estudio descriptivo retrospectivo en 18 pacientes en los que se realizó la descripción de las variables: clínicas epidemiológicas, métodos de imágenes, diagnóstico patológico, tipo de cirugía y evolución. Resultados: El 50 % se diagnosticó antes del año de vida, con predominio en las niñas (66,65 %), en la localización abdominal y con afectación de la suprarrenal izquierda (87 %). La ultrasonografía, en asociación con la tomografía axial computarizada, permitió el diagnóstico inicial en un 94,50 %, y resultó de gran utilidad en la identificación de factores de riesgos quirúrgicos (78 %). El diagnóstico patológico evidenció predominio de los grados indiferenciados en el 66,70 % y en estadios más avanzados III y IV (55,60 %). Se realizó cirugía primaria (28 %) y secundaria (44 %), con un 28,0 % de fallecidos. Conclusiones: Esta enfermedad continúa siendo un desafío quirúrgico y, en ausencia de determinantes moleculares y citogenéticos, los factores clínicos e histopatológicos constituyen los de especial relevancia y correlación pronóstica. La transición estandarizada hacia la utilización de la clasificación pretratamiento de riesgo quirúrgico por imagenología es fundamental para la definición de la modalidad terapéutica a emplear.
A risk identification model for detection of patients at risk of antidepressant discontinuation

Purpose Between 30 and 68% of patients prematurely discontinue their antidepressant treatment, posing significant risks to patient safety and healthcare outcomes. Online healthcare forums have the potential to offer a rich and unique source of data, revealing dimensions of antidepressant discontinuation that may not be captured by conventional data sources. Methods We analyzed 891 patient narratives from the online healthcare forum, “askapatient.com,” utilizing content analysis to create PsyRisk—a corpus highlighting the risk factors associated with antidepressant discontinuation. Leveraging PsyRisk, alongside PsyTAR [a publicly available corpus of adverse drug reactions (ADRs) related to antidepressants], we developed a machine learning-driven algorithm for proactive identification of patients at risk of abrupt antidepressant discontinuation. Results From the analyzed 891 patients, 232 reported antidepressant discontinuation. Among these patients, 92% experienced ADRs, and 72% found these reactions distressful, negatively affecting their daily activities. Approximately 26% of patients perceived the antidepressants as ineffective. Most reported ADRs were physiological (61%, 411/673), followed by cognitive (30%, 197/673), and psychological (28%, 188/673) ADRs. In our study, we employed a nested cross-validation strategy with an outer 5-fold cross-validation for model selection, and an inner 5-fold cross-validation for hyperparameter tuning. The performance of our risk identification algorithm, as assessed through this robust validation technique, yielded an AUC-ROC of 90.77 and an F1-score of 83.33. The most significant contributors to abrupt discontinuation were high perceived distress from ADRs and perceived ineffectiveness of the antidepressants. Conclusion The risk factors identified and the risk identification algorithm developed in this study have substantial potential for clinical application. They could assist healthcare professionals in identifying and managing patients with depression who are at risk of prematurely discontinuing their antidepressant treatment.
Potential Correlation between Microbial Diversity and Volatile Flavor Substances in a Novel Chinese-Style Sausage during Storage

A novel Chinese-style sausage with Chinese traditional fermented condiments used as additional ingredients is produced in this study. The aim of this study was to investigate the microbial community’s structure, the volatile flavor substances and their potential correlation in the novel Chinese sausage. High-throughput sequencing (HTS) and solid-phase microextraction-gas chromatography-mass spectrometry (GC-MS) were, respectively, used to analyze the microbial diversity and volatile flavor substances of the novel Chinese-style sausage during storage. The results showed that Firmicutes, Proteobacteria and Actinobacteria were the predominant bacterial genera, and Hyphopichia and Candida were the predominant fungal genera. A total of 88 volatile flavor substances were identified through GC-MS, among which 18 differential flavor compounds were screened (VIP > 1), which could be used as potential biomarkers to distinguish the novel sausages stored for different periods. Lactobacillus exhibited a significant negative correlation with 2,3-epoxy-4,4-dimethylpentane and acetoin and a significant positive correlation with 2-phenyl-2-butenal. Hyphopichia significantly positively correlated with ester. Leuconostoc significantly positively correlated with ethyl caprate, ethyl palmate, ethyl tetradecanoate and ethyl oleate while it negatively correlated with hexanal. This study provides a theoretical basis for revealing the flavor formation mechanisms and the screening of functional strains for improving the flavor quality of the novel Chinese-style sausage.
An Evaluation of a Pesticide Training Program to Reduce Pesticide Exposure and Enhance Safety among Female Farmworkers in Nan, Thailand

Background: Although exposure to chemical pesticides is known to cause negative effects on human health, farmers in Ban Luang, Nan, Thailand, continue to use them regularly to protect crops. This study focused on mothers who were engaged in farm tasks and had children between the ages of 0 to 72 months, with the objective of reducing pesticide exposure. Methods: This study was conducted from May 2020 to October 2020 in the Ban Fa and Ban Phi sub-districts in Ban Luang due to the high use of pesticides in these areas. A systematic random sampling technique was used to recruit 78 mothers exposed to pesticides. Thirty-nine mothers from Ban Fa district were randomly assigned to the intervention group and 39 from Ban Phi to the control group over a 3-month period. This study applied a pesticide behavioral change training program for the intervention group. To assess the effectiveness of the program, the study compared the results of a questionnaire regarding knowledge, attitude, and practice (KAP) and health beliefs related to pesticide exposure as well as the levels of acetylcholinesterase (AChE) and butyryl cholinesterase (BChE) enzymes, biomarkers of exposure to pesticides, before and after the intervention using ANCOVA statistical test. Furthermore, to evaluate the effectiveness of the intervention program, a paired t-test was used to investigate the in-home pesticide safety assessment. Results: After the intervention, we observed no significant change in AChE; however, a significant improvement in BChE (p < 0.05), a marker of short-term recovery, was observed. Pesticides can cause a reduction in AChE and BChE, however, after eliminating pesticides, BChE takes a shorter time (about 30–50 days) to recover than AChE (around 90–120 days). Therefore, increases in the measured concentrations of AChE and/or BChE suggest the presence of less chemicals from pesticides in the human body. The study also found a significant improvement in KAP and beliefs about chemical pesticide exposure after the intervention (p < 0.05). Furthermore, using a paired t-test, we found a significant increase in pesticide safety practices (p < 0.05) in the intervention group and a borderline significant increase regarding in-home safety (p = 0.051) in the control group. Conclusions: Based on the results, the constructs of the intervention program were effective and could be applied in other agricultural areas in less developed countries. However, due to time limitations during the COVID-19 pandemic, further studies should be conducted to enable data collection over a longer time, with a larger number of subjects providing the ChE levels for the non-agricultural season.
Using Adaptive Behaviour Patterns of Open Plan Office Occupants in Energy Consumption Predictions

One of the factors that affects energy consumption in buildings is the level of control that occupants have over their environment, as well as their adaptive behaviour. The aim of this study was to focus on the adaptive clothing behaviour pattern, and to analyse its impact on energy consumption when integrated into a dynamic energy prediction tool. A questionnaire survey was conducted in an office building to collect the occupant behaviour data. The occupant clothing levels and the window opening behaviour were integrated into the dynamic energy performance prediction software, IDA ICE. The results of the simulations showed that the impact of adaptive clothing behaviour on energy consumption is relatively small, but it can meaningfully improve thermal comfort. Including adaptive behaviour in energy simulations can help in improving the accuracy of the energy performance and comfort predictions.