Miracle-dz/UniFAR-FTUs huggingface dataset:
Enhancing family nursing practice in schools: School nurses’ perspectives on illness beliefs and family nursing practice skills when caring for children with attention-deficit hyperactivity disorder or asthma – A cross-sectional study

An increasing number of children attend schools with chronic illnesses/disorders that require managing and comprehensive healthcare from school nurses during the day. Collaboration between school nurses, the school-aged child with attention-deficit hyperactivity disorder (ADHD) or asthma, and their families is needed when coordinating/managing chronic health problems in the school setting. However, involving families in the assessment and care planning processes can be challenging. The aim of this study was to survey the illness beliefs of school nurses and their perceptions of their family nursing practice skills when offering healthcare services to children with ADHD or asthma in schools. A cross-sectional study was used for a sample of 82 school nurses. The manuscript was prepared following STROBE guidelines. Results indicated that the school nurses perceived themselves to be more confident and to have better knowledge and skill in family nursing practice when offering healthcare services to families of children with ADHD in comparison to asthma.
New Mechanistic Procedure to Predict the Critical Cracking Temperature of Asphalt Concrete from Bending Beam Rheometer and Indirect Tension Test Data

This study presents a new mechanistic procedure for determining the critical cracking temperature of asphalt concrete (AC) using data from bending beam rheometer (BBR) test of asphalt binder and indirect tension (IDT) test of AC. This new procedure uses BBR creep data to generate the mixture relaxation modulus mastercurve by utilizing the Hirsch model, time-temperature superposition principle, and Prony series-based interconversion method. The Hirsch model parameters are calibrated by comparing creep data from BBR and IDT creep tests performed at the same temperature. Boltzmann hereditary integral and second-order heat equation are then used to calculate thermal stress from the developed relaxation modulus mastercurve. IDT strength data is transferred from test strain rate to thermal strain rate using the viscoelastic continuum damage model. Since a strain gauge is not attached for traditional laboratory IDT strength testing, this study derived an analytical equation based on the Hondros solution to compute the horizontal strain rate from the applied vertical displacement rate. Finally, the critical cracking temperature is determined by coupling the thermal stress and strength profiles. Using the procedure presented in this paper, the critical cracking temperatures of four AC mixtures were predicted from BBR and IDT data. Their actual critical cracking temperatures were measured using thermal stress restrained specimen test performed in the laboratory to validate the method. The predicted critical cracking temperatures are found to be very close to the laboratory measured values. The developed procedure has substantial practical and technical importance in predicting the critical cracking temperature of AC because it utilizes widely available BBR and IDT tests.
A practical guide to data analysis in general literature reviews

Academic theses at the bachelor’s and master’s levels in nursing, physiotherapy, occupational therapy, public health and related fields often take the form of general reviews of published research on a relevant clinical issue. While there are many guides to doing literature searches and evaluating article quality, there are to our knowledge no published detailed guides of how to do the actual data analysis in such general literature reviews, particularly that are applicable to students. This article seeks to describe a systematic method of data analysis appropriate for undergraduate research theses, where the data consists of the results from available published research. We present a step-by-step guide with authentic examples and practical tips.
School Bus Routing Problem with a Mixed Ride, Mixed Load, and Heterogeneous Fleet

Special education students are usually routed on different buses than non-disabled general education students. To make the routes more efficient, this study proposes serving general students and special education students on the same bus at the same time (mixed ride) while allowing heterogeneous fleets and mixed loads. ESRI Location-Allocation tools and Google OR-Tools are used for bus stop selection, route generation, and bus stop optimization. Parallel cheapest insertion heuristic and metaheuristic, simulated annealing, are adopted to generate school bus routes. The effectiveness of the mixed ride approach is tested for three schools with 178 synthetic students’ locations data (including 12 with wheelchair) in New York City using a fleet of 14 buses spread over four types. The results show the mixed ride approach achieved 14.32% reduction in total travel distance and 10.46% reduction in total travel time. The mixed ride approach tends to return solutions with fewer vehicles and fewer bus stops, less average travel distance, and shorter average travel time.
Music therapy in the hospital-at-home: A practice for children in palliative care

This pilot research study investigated music therapy in a hospital-at-home setting for children in palliative care, focusing on parental and nurses experiences of music therapy. Nine families included in the study were interviewed after receiving a maximum of five individual music therapy sessions at home with a Music Therapist. In addition, a focus group interview with allied health professionals involved in the patients’ care was conducted investigating the multidisciplinary team’s experiences with music therapy. Results revealed that the families drew attention to the feeling of being isolated–yet connected due to music therapy. All the families reported the importance of the relationship to the Music Therapist, while emphasizing flexibility and joint music-making. Music therapy within hospital-at-home treatment was reported as a meaningful and much appreciated form of therapy, while the multidisciplinary teamwork was highly valued by both the health personnel and the families. The results showed the need for a highly skilled Music Therapist to support the families’ complex and dynamic needs within a hospital-at-home setting. The results demonstrated the need for, and the possibilities of, a dynamic music therapy programme adapting not only to the patients’ individual needs but additionally providing family-centred care that considered shifting locations.
‘We actually get to go out and play’: looking through children’s views on Out of School Hours Care to children’s experience of school

ABSTRACT Out of School Hours Care (OSHC) is recognised as an important service for working parents. Enabling parents to work beyond school hours, this sector has seen increased demand. Research and policy have provided insight into the nature of OSHC in relation to parent use and staff processes, with little consideration to the perspective at the core of this service – children. This small, exploratory project focused on children's perceptions of OSHC, adding to our understanding of children's perceptions of play. They identified key themes in relation to the importance of friends and social interaction; play and choice; and provision of technology for relaxation. Amidst the children's comments is a reflection on the increasing contrast between the value of play at OSHC and the busyness of school. This suggests there is a need for further research to better understand children's experience of OSHC, alongside their experience of and perspectives about school.
Potential Utilization of Dagaa (Rastrineobola argentea) Protein Hydolysate in Formulation of Media to Support Microbial Growth and Production of Bacterial Secondary Metabolites

ABSTRACT Dagaa fish hydrolysate (DFH) and dagaa protein hydrolysate (DPH) were prepared from dagaa using Alcalase enzyme. Proximate, mineral analysis, and potential use of DFH and DPH in microbial media were evaluated. Dagaa media formulations were used to culture bacteria commonly used for amylase production (Bacillus subtilis and Rhodobacter capsulatus) and that used as a bio-pesticide (Metarhizium anisopliae). Whole dagaa had the highest protein (5.2 ± 0.1 mg/ml), ash (13.5 ± 0.4%) and fat (2.36 ± 0.2%) content, while DPH had the least protein (2.6 ± 0.0 mg/ml) content. Mineral content was significantly different (p < 0.05) between dagaa and its hydrolysates. Dagaa and LB had the highest Sodium (22.7 ± 1.1 mg/ml) and calcium (0.3 ± 0.0 mg/ml), content respectively. Sustenance of amylase production in DPH-starch and standard media by both microorganisms was significantly different (p < 0.05). Sporulation rate of M. anisopliae in experimental media was not significant (p ˃ 0.05).
An Empirical Study on Knowledge Aggregation in Academic Virtual Community Based on Deep Learning

Abstract Academic virtual community provides an environment for users to exchange knowledge, so it gathers a large amount of knowledge resources and presents a trend of rapid and disorderly growth. We learn how to organize the scattered and disordered knowledge of network community effectively and provide personalized service for users. We focus on analyzing the knowledge association among titles in an all-round way based on deep learning, so as to realize effective knowledge aggregation in academic virtual community. We take ResearchGate (RG) “online community” resources as an example and use Word2Vec model to realize deep knowledge aggregation. Then, principal component analysis (PCA) is used to verify its scientificity, and Wide & Deep learning model is used to verify its running effect. The empirical results show that the knowledge aggregation system of “online community” works well and has scientific rationality.
Comprehension of experienced English language teachers’ professional identity and related metacognitive thinking procedures

ABSTRACT In order to comprehend the attributes of expert teachers, the current study investigated professional identity (PI) and related metacognitive thinking procedures of experienced Korean teachers of English through a questionnaire survey and interviews. The teachers’ PIs contained pedagogic meanings that highly regarded teachers’ having language knowledge and skills, realising learner-centred practices, teaching communication skills for practicality, and developing professionalism. They relatively less valued practising teacher-led, test-preparation lessons but also using challenging tasks and creative materials and combining content, materials, and activities, which reflects their unestablished meanings of learner-centredness. Some of the interviewed teachers revealed their active performance of metacognitive monitoring and regulations of different meanings (cognitions), emotions, and actions over their pedagogical problem-solving processes for overcoming teacher-led, test-preparation lessons. Thus, experimenting with negotiated pedagogies and modifying their pedagogic meanings by learning from this, they tried to balance identity-congruent actions and verification, and reshaped their PI and related metacognitive thinking procedures; others’ pedagogic experimentations and related experiences were rejected by contextual rigidities. Comprehension of the PI and related metacognitive thinking procedures of experienced teachers provided several implications for teacher education.
Role of Surface-Capping Ligands in Photoexcited Electron Transfer between CdS Nanorods and [FeFe] Hydrogenase and the Subsequent H2 Generation

Complexes of CdS nanorods and [FeFe] hydrogenase I from Clostridium acetobutylicum have been shown to photochemically produce H2. This study examines the role of the ligands that passivate the nanocrystal surfaces in the electron transfer from photoexcited CdS to hydrogenase and the H2 generation that follows. We functionalized CdS nanorods with a series of mercaptocarboxylate surface-capping ligands of varying lengths and measured their photoexcited electron relaxation by transient absorption (TA) spectroscopy before and after hydrogenase adsorption. Rate constants for electron transfer from the nanocrystals to the enzyme, extracted by modeling of TA kinetics, decrease exponentially with ligand length, suggesting that the ligand layer acts as a barrier to charge transfer and controls the degree of electronic coupling. Relative light-driven H2 production efficiencies follow the relative quantum efficiencies of electron transfer, revealing the critical role of surface-capping ligands in determining the pho.
Hyperprogressive Disease After Combined Anti-PD-L1 and Anti-CTLA-4 Immunotherapy for MSI-H/dMMR Gastric Cancer: A Case Report

Immune checkpoint inhibitors (ICI) have been developed in gastric adenocarcinomas and approved in first-line metastatic setting (in combination with chemotherapy) as well as in pretreated patients. Microsatellite instability-high (MSI-H) tumors are predicted to derive high benefit from ICI but data in gastric locations are limited. Here, we describe the case of a 68-year old patient with stage IV MSI-H gastric adenocarcinoma, referred to our center to receive immunotherapy after failure of standard of care (surgery with perioperative platin-based chemotherapy and paclitaxel plus ramucirumab at disease progression). The patient received one injection of durvalumab and tremelimumab and was hospitalized eighteen days after because of occlusive syndrome. The CT scan showed hyperprogression of the lymph nodes and hepatic lesions, compressing the gastric stump. He died few days later. Molecular analyses did not explain this outcome. To our knowledge, this is one of the first reported cases of hyperprogressive disease after combined ICI for a patient with MSI-H tumor. We review the potential causes and discuss the emerging literature regarding predictive factors of hyperprogression in the particular subset of MSI-H patients. If some data were available in retrospective studies, validation of strong predictive factors is needed to avoid such dramatic evolutions.
Sensory-Evoked 40-Hz Gamma Oscillation Improves Sleep and Daily Living Activities in Alzheimer’s Disease Patients

Pathological proteins contributing to Alzheimer’s disease (AD) are known to disrupt normal neuronal functions in the brain, leading to unbalanced neuronal excitatory-inhibitory tone, distorted neuronal synchrony, and network oscillations. However, it has been proposed that abnormalities in neuronal activity directly contribute to the pathogenesis of the disease, and in fact it has been demonstrated that induction of synchronized 40 Hz gamma oscillation of neuronal networks by sensory stimulation reverses AD-related pathological markers in transgenic mice carrying AD-related human pathological genes. Based on these findings, the current study evaluated whether non-invasive sensory stimulation inducing cortical 40 Hz gamma oscillation is clinically beneficial for AD patients. Patients with mild to moderate AD (n = 22) were randomized to active treatment group (n = 14; gamma sensory stimulation therapy) or to sham group (n = 8). Participants in the active treatment group received precisely timed, 40 Hz visual and auditory stimulations during eye-closed condition to induce cortical 40 Hz steady-state oscillations in 1-h daily sessions over a 6-month period. Participants in the sham group were exposed to similar sensory stimulation designed to not evoke cortical 40 Hz steady-state oscillations that are observed in the active treatment patients. During the trial, nighttime activities of the patients were monitored with continuous actigraphy recordings, and their functional abilities were measured by Alzheimer’s Disease Cooperative Study – Activities of Daily Living (ADCS-ADL) scale. Results of this study demonstrated that 1-h daily therapy was well tolerated throughout the 6-month treatment period by all subjects. Patients receiving gamma sensory stimulation showed significantly reduced nighttime active periods, in contrast, to deterioration in sleep quality in sham group patients. Patients in the sham group also showed the expected, significant decline in ADCS-ADL scores, whereas patients in the gamma sensory stimulation group fully maintained their functional abilities over the 6-month period. These findings confirm the safe application of 40 Hz sensory stimulation in AD patients and demonstrate a high adherence to daily treatment. Furthermore, this is the first time that beneficial clinical effects of the therapy are reported, justifying expanded and longer trials to explore additional clinical benefits and disease-modifying properties of gamma sensory stimulation therapy. Clinical Trial Registration: clinicaltrials.gov, identifier: NCT03556280.
Diversity and Interrelations Among the Constitutive VOC Emission Blends of Four Broad-Leaved Tree Species at Seedling Stage

Volatile organic compounds (VOCs) emitted by plants consist of a broad range of gasses which serve purposes such as protecting against herbivores, communicating with insects and neighboring plants, or increasing the tolerance to environmental stresses. Evidence is accumulating that the composition of VOC blends plays an important role in fulfilling these purposes. Constitutional emissions give insight into species-specific stress tolerance potentials and are an important first step in linking metabolism and function of co-occurring VOCs. Here, we investigate the blend composition and interrelations among co-emitted VOCs in unstressed seedlings of four broad-leaved tree species, Quercus robur, Fagus sylvatica, Betula pendula, and Carpinus betulus. VOCs of Q. robur and F. sylvatica mainly emitted isoprene and monoterpenes, respectively. B. pendula had relatively high sesquiterpene emission; however, it made up only 1.7% of its total emissions while the VOC spectrum was dominated by methanol (∼72%). C. betulus was emitting methanol and monoterpenes in similar amounts compared to other species, casting doubt on its frequent classification as a close-to-zero VOC emitter. Beside these major VOCs, a total of 22 VOCs could be identified, with emission rates and blend compositions varying drastically between species. A principal component analysis among species revealed co-release of multiple compounds. In particular, new links between pathways and catabolites were indicated, e.g., correlated emission rates of methanol, sesquiterpenes (mevalonate pathway), and green leaf volatiles (hexanal, hexenyl acetate, and hexenal; lipoxygenase pathway). Furthermore, acetone emissions correlated with eugenol from the Shikimate pathway, a relationship that has not been described before. Our results thus indicate that certain VOC emissions are highly interrelated, pointing toward the importance to improve our understanding of VOC blends rather than targeting dominant VOCs only.
Integrating Behavior Change and Persuasive Design Theories into an Example Mobile Health Recommender System

Behavior change for health promotion is a complex process that requires a high level of personalization, which health recommender systems, as an emerging area, have been trying to address. Despite the advantages of behavior change theories in explaining individuals’ behavior and standardizing the behavior change program overall, these theoretical models are either overlooked or unreported for the most part in health promotion systems, a small share of them being related to mental well-being. For a health recommender system to personalize interventions, the interventions should be properly designed, and the behavior change aspects should be adequately integrated into the recommendation process. This paper demonstrates an implementation guideline derived from a practical approach in integrating behavior change theories and persuasive design principles into an example mobile-based health recommender system for mental health promotion. This implementation maps a set of relevant theories for designing the health recommender system into a set of requirements using a functional framework. By realizing these requirements, one can assure that the behavior change theories are at the very least considered. This effort serves as a guideline for future implementations and highlights elements that could perhaps be used for other health or recommendation domains and, particularly, user integration purposes.
Demo: Chewpin: a wearable acoustic device for chewing detection

Diet intervention has emerged as a promising strategy in obesity prevention and treatment. Existing research predominantly focused on macronutrient intake and food quantity restriction in diet manipulation. Eating habit is difficult to change due to its highly habitual nature; therefore, it is essential to automatically detect eating behavior and provide real-time intervention in unhealthy eating patterns. In this study, we explored the possibility of designing Chewpin, an easy-to-be-implemented and socially acceptable device for capturing eating behavior(i.e., chewing and swallowing) in a controlled environment. We implemented a convolutional neural network (CNN) for data classification. Overall, our system achieved a promising accuracy of eating recognition of 98.23% on the test set. In the future, we will evaluate its usability and feasibility in real-life eating practices and use this system as a technical tool for problematic eating intervention.
Attribute Reduction Method and Its Application using Bat Algorithm and Rough Sets

Attributes reduction is one of the important key in knowledge discovery. In order to find the effective methods of minimum attribute reduction and its application in data processing and analysis, an attribute reduction method by using bat algorithm and rough sets can be proposed by combining intelligent bat optimization algorithm with the rough sets. This method uses the attribute dependency to calculate the attribute core, combining the optimization of bat algorithm towards the attribute reduction to get the smallest attribute reduction. In the analyzation of criminal information, it will be applied to analyze the main influence factors of criminal behavior and carry out experimental verification. From the experimantal results, we found that this method is feasible and effective. By analysing the criminal behavior, the pattern of criminal characteristic will be discovered and this helps us to achieve the goal of criminal prevention and improve the police efficiency in handling cases.
Blind Calibration by Maximizing Correlation

In large-scale IoT systems, blind calibration problem becomes increasingly prominent for sensor calibration without ground truth reference. Most of the existing blind calibration methods adopt either a handcrafted spatio-temporal model or a specific drift mechanism assumption. However, these assumptions may be over-simplified or introduce inappropriate bias, and therefore lead to great performance degradation in the real-world deployment. In this paper, we present a novel generative framework for blind calibration problems without specific data correlation or drift model assumption. We extract the most informative feature that maximizes correlation between reference data and target data using soft-HGR maximal correlation regression. Therefore, our method can be used in different blind calibration tasks especially where data correlation or drift model is unknown or deviated. Besides, our method can be conveniently augmented with a reliable drift model to further improve performance on specific tasks. We conduct comprehensive evaluations over a three-month real-world air pollution sensing dataset collected in Foshan, China. Results show our method can obtain the best performance compared to previous blind calibration methods in the absence of accurate drift model knowledge.