Miracle-dz/UniFAR-FTUs huggingface dataset:
Visual post-occupancy evaluation of a restorative garden using virtual reality photography: Restoration, emotions, and behavior in older and younger people

Natural environments have a restorative effect from mental/attentional fatigue, prevent stress, and help to revitalize psychological and physical resources. These benefits are crucial for promoting active aging, which is particularly relevant given the phenomenon of population aging in recent decades. To be considered restorative, green spaces have to meet specific requirements in ecological and psychological terms that can be assessed through Post-Occupancy Evaluation (POE), a multimethod approach commonly used by environmental psychologists and landscape architects after construction to evaluate the design outcomes from the users’ perspective. Generally, POEs consist of surveys and/or interviews accompanied by more or less structured observations of onsite users’ behavior. Despite this, various practical constraints can prevent physical access to the renovated area (e.g., weather conditions, time/resources limits, health issues, bureaucratic constraints). Exploiting digital tools for such an assessment can be a crucial support in such circumstances. The current study presents the visual POE of a restorative garden for older adults in Milan, Italy. We developed a web application, that includes the exp-EIA© patented method, which allows participants to virtually explore a visual simulation of the environment and provide their feedback. We identified 3 representative viewpoints in the redeveloped garden differing from each other for the functions and the design principles that inspired the transformation. For each point of view, we created 360° Virtual Reality photographs, that can be navigated by looking around, i.e., panning, from the standing point of each view. In connection to each virtual scene, a survey was conducted (N = 321). The focus was the psychological experience related to each viewpoint, assessed with two psychometric scales investigating the constructs of emotions (pleasure and arousal) and restoration (fascination, being away, coherence, scope, and environmental preference); such information is integrated with behavioral aspects, including the main activities prefigured by participants and their visual exploration of the VR photography. The results of the virtual exploration show that the garden is perceived as restorative, with a more intense effect in a spot purposely designed. The emotions experienced in the garden are positive and a mild level of arousal is observed. The behavioral dimension is characterized by predominantly contemplative activities and contact with nature. A cartographic representation of the psychological and behavioral data is developed, to support the maintenance of the garden.
Epigenetic manipulation to improve mouse SCNT embryonic development

Cloned mammals can be achieved through somatic cell nuclear transfer (SCNT), which involves reprogramming of differentiated somatic cells into a totipotent state. However, low cloning efficiency hampers its application severely. Cloned embryos have the same DNA as donor somatic cells. Therefore, incomplete epigenetic reprogramming accounts for low development of cloned embryos. In this review, we describe recent epigenetic barriers in SCNT embryos and strategies to correct these epigenetic defects and avoid the occurrence of abnormalities in cloned animals.
Statistical investigation on equatorial pitch angle distribution of energetic electrons in Earth’s outer radiation belt during CME- and CIR-driven storms

We present a statistical investigation (September 2012 - September 2017) of pitch angle distribution (PAD) of energetic electrons (∼30 keV - 1 MeV) in the outer radiation belt (L ≥ 3) during CME- and CIR-driven geomagnetic storms using Van Allen Probe measurements. We selected geomagnetic storms based on minimum of SYM-H being less than -50 nT and classified the storms according to their drivers. Thus, we obtained 23 CME- and 24 CIR-driven storms. During the storm intervals, pitch angle resolved electron flux measurements are obtained from the MagEIS instrument on-board Van Allen Probe-A spacecraft. We assume symmetric pitch angle distributions around 90° pitch angle and fit the observed PADs with Legendre polynomials after propagating them to the magnetic equator. Legendre coefficients c 2 and c 4, and the ratio R = |c 2/c 4| are used to categorize the different PAD types. To resolve the spatio-temporal distribution of PADs, these coefficients are binned in 5 L-shell bins, 12 MLT bins for seven energy channels and four storm phases. We found that several hundreds of keV electrons exhibit clear dependence on local time, storm phases and storm drivers, with increased anisotropy for CME-driven storms during main and early recovery phases. On the contrary, we found that tens of keV electrons do not exhibit significant dependence on these parameters. We have discussed the different physical mechanisms responsible for the observed MLT dependent PADs and found drift-shell splitting to be the major contributor.
Mindful practice for teachers: Relieving stress and enhancing positive mindsets

Objectives The present study aimed to determine the degree of stress relief and increase in mindfulness attributes experienced by 18 participants in an 8-week Mindful Practice for Teachers (MPT) program. Methods The mixed-methods study design included participant reflections collected throughout the study and self-report measures: Perceived Stress Scale (PSS), Positive Mindset Index (PMI), and Five Facets of Mindfulness Questionnaire (FFMQ). Data analysis Pre- and post-program paired-samples t-tests were completed for the self-report measures. Inductive coding was completed for the participant reflections. Results The participants (N = 18) reported a significant decrease in perceived stress pre-program and post-program. The significant changes in the sub-scales of the FFMQ were reported for observing, non-reaction, and non-judgment pre-program and post-program. A statistically significant change was reported for the PMI sub-scale stability which increased post-program. According to participant reflections, there was an increased awareness of the physiological response during positive and challenging events/incidents. The participants reported positive satisfaction pertaining to program materials, exercises, and activities. Conclusion Findings indicated that the participants experienced a decrease in their perceived level of stress and an increase in their mindfulness attributes consequently highlighting the benefits of mindfulness-based programs for teacher stress management. The MPT program may prove to be a positive intervention for managing work-related stress and providing teachers with simple, stress management resources.
Stemness analysis in hepatocellular carcinoma identifies an extracellular matrix gene–related signature associated with prognosis and therapy response

Background: Tumor stemness is the stem-like phenotype of cancer cells, as a hallmark for multiple processes in the development of hepatocellular carcinoma (HCC). However, comprehensive functions of the regulators of tumor cell’s stemness in HCC remain unclear. Methods: Gene expression data and clinical information of HCC samples were downloaded from The Cancer Genome Atlas (TCGA) dataset as the training set, and three validation datasets were derived from Gene Expression Omnibus (GEO) and International Cancer Genome Consortium (ICGC). Patients were dichotomized according to median mRNA expression–based stemness index (mRNAsi) scores, and differentially expressed genes were further screened out. Functional enrichment analysis of these DEGs was performed to identify candidate extracellular matrix (ECM)–related genes in key pathways. A prognostic signature was constructed by applying least absolute shrinkage and selection operator (LASSO) to the candidate ECM genes. The Kaplan–Meier curve and receiver operating characteristic (ROC) curve were used to evaluate the prognostic value of the signature. Correlations between signatures and genomic profiles, tumor immune microenvironment, and treatment response were also explored using multiple bioinformatic methods. Results: A prognostic prediction signature was established based on 10 ECM genes, including TRAPPC4, RSU1, ILK, LAMA1, LAMB1, FLNC, ITGAV, AGRN, ARHGEF6, and LIMS2, which could effectively distinguish patients with different outcomes in the training and validation sets, showing a good prognostic prediction ability. Across different clinicopathological parameter stratifications, the ECMs signature still retains its robust efficacy in discriminating patient with different outcomes. Based on the risk score, vascular invasion, α-fetoprotein (AFP), T stage, and N stage, we further constructed a nomogram (C-index = 0.70; AUCs at 1-, 3-, and 5-year survival = 0.71, 0.75, and 0.78), which is more practical for clinical prognostic risk stratification. The infiltration abundance of macrophages M0, mast cells, and Treg cells was significantly higher in the high-risk group, which also had upregulated levels of immune checkpoints PD-1 and CTLA-4. More importantly, the ECMs signature was able to distinguish patients with superior responses to immunotherapy, transarterial chemoembolization, and sorafenib. Conclusion: In this study, we constructed an ECM signature, which is an independent prognostic biomarker for HCC patients and has a potential guiding role in treatment selection.
Extending repair in peer interaction: A conversation analytic study

Peer interaction constitutes a focal site for understanding learning orientations and autonomous learning behaviors. Based on 10 h of video-recorded data collected from small-size conversation-for-learning classes, this study, through the lens of Conversation Analysis, analyzes instances in which L2 learners spontaneously exploit learning opportunities from the on-task public talk and make them relevant for private learning in sequential private peer interaction. The analysis of extended negation-for-meaning practices in peer interaction displays how L2 learners orient to public repair for their learning opportunities in an immediate manner and in so doing, how different participation framework is being utilized to maximize their learning outcomes. As these extended repair practices are entirely managed by learners themselves, they yield both efficient and inefficient learning outcomes. Findings reveal that learners frequently resort to their peers to recycle the focal trouble words for learning opportunities, shifting their participating role from the on looking audience to active learners. By reporting the rather under-researched post-repair negotiation-for-meaning sequence in peer interactions, the study highlights the relevance between on-task classroom activities and private learning, contributing to understanding private learning behaviors in the language classroom and learning as a co-constructed activity locally situated in peer interaction.
Chaos of flexible rotor system with critical speed in magnetic bearing based on the improved precise Runge–Kutta hybrid integration

Magnetic rotor-bearing system has drawn great attention because of its several advantages compared to existent rotor-bearing system, and explicit Runge–Kutta method has achieved good results in solving dynamic equation. However, research on flexible rotor of magnetic bearing is relatively less. Moreover, explicit Runge–Kutta needs a smaller integral step to ensure the stability of the calculation. In this article, we propose a nonlinear dynamic analysis of flexible rotor of active magnetic bearing established by using the finite element method. The precise Runge–Kutta hybrid integration method and the largest Lyapunov exponent are used to analyze the chaos of the rotor system at the first- and second-order critical speed of the rotor. Experiment on chaos analysis has shown that compared with the explicit Runge–Kutta method, the precise Runge–Kutta hybrid integration method can improve the convergence step of calculation significantly while avoiding iterative solution and maintain high accuracy which is four times the increase of the integral step.
The clinical impact of serum 1,5-anhydro-D-glucitol levels on coronary artery calcification and adverse outcomes assessed by coronary optical coherence tomography in diabetic patients

Background Serum 1,5-anhydro-D-glucitol (1,5-AG) is a novel biomarker for short-term glycemic status and postprandial hyperglycemia. The association between serum 1,5-AG levels and coronary artery calcification (CAC) through a quantitative assessment using optical coherence tomography (OCT) is unclear. We aimed to evaluate this association using OCT in patients with diabetes mellitus (DM). Methods From June 2016 to December 2019, we prospectively enrolled 256 patients who underwent OCT-guided percutaneous coronary intervention (PCI). Half of the patients had diabetes. Patients were followed up for a mean period of 1.8 ± 0.8 years (median: 2.2 years). The relative calcium index and relative lipid core index measured by quantitative OCT analysis were used to evaluate the intra-plaque calcium and lipid levels of culprit plaques. We also analyzed the correlation between serum 1,5-AG levels and long-term major adverse cardiovascular events. Results Serum 1,5-AG levels were significantly lower in diabetic patients than in non-diabetic patients (DM vs. non-DM: 55.6 ± 27.9 μg/mL vs. 63.7 ± 26.1 μg/mL, p = 0.016), and lower in fibrocalcified lesions than in fibrotic or fibrolipidic lesions (fibrocalcified vs. fibrotic or fibrolipidic: 42.8 ± 19.1 vs. 72.9 ± 25.2 or 66.4 ± 27.5 μg/mL, p < 0.001, respectively). In addition, we found a significant inverse correlation between serum 1,5-AG levels and relative calcium index (r = −0.729, p < 0.001). In multivariate Cox regression analysis, low serum 1,5-AG level was identified as an independent predictor for major adverse cardiovascular events in diabetic patients (p = 0.043), but not in non-diabetic patients (p = 0.748) after adjusting for age and sex. Conclusion This study revealed that low serum 1,5-AG levels were associated with an increased risk of CAC as assessed by OCT, especially in diabetic patients. Low serum 1,5-AG levels may predict future major adverse cardiovascular events in diabetic patients undergoing OCT-guided PCI.
A personalized DVH prediction model for HDR brachytherapy in cervical cancer treatment

Purpose Although the knowledge-based dose-volume histogram (DVH) prediction has been largely researched and applied in External Beam Radiation Therapy, it is still less investigated in the domain of brachytherapy. The purpose of this study is to develop a reliable DVH prediction method for high-dose-rate brachytherapy plans. Method A DVH prediction workflow combining kernel density estimation (KDE), k-nearest neighbor (kNN), and principal component analysis (PCA) was proposed. PCA and kNN were first employed together to select similar patients based on principal component directions. 79 cervical cancer patients with different applicators inserted was included in this study. The KDE model was built based on the relationship between distance-to-target (DTH) and the dose in selected cases, which can be subsequently used to estimate the dose probability distribution in the validation set. Model performance of bladder and rectum was quantified by |ΔD2cc|, |ΔD1cc|, |ΔD0. 1cc|, |ΔDmax|, and |ΔDmean| in the form of mean and standard deviation. The model performance between KDE only and the combination of kNN, PCA, and KDE was compared. Result 20, 30 patients were selected for rectum and bladder based on KNN and PCA, respectively. The absolute residual between the actual plans and the predicted plans were 0.38 ± 0.29, 0.4 ± 0.32, 0.43 ± 0.36, 0.97 ± 0.66, and 0.13 ± 0.99 for |ΔD2cc|, |ΔD1cc|, |ΔD0. 1cc|, |ΔDmax|, and |ΔDmean| in the bladder, respectively. For rectum, the corresponding results were 0.34 ± 0.27, 0.38 ± 0.33, 0.63 ± 0.57, 1.41 ± 0.99 and 0.23 ± 0.17, respectively. The combination of kNN, PCA, and KDE showed a significantly better prediction performance than KDE only, with an improvement of 30.3% for the bladder and 33.3% for the rectum. Conclusion In this study, a knowledge-based machine learning model was proposed and verified to accurately predict the DVH for new patients. This model is proved to be effective in our testing group in the workflow of HDR brachytherapy.
Investigating the effects of sleep and sleep loss on the different stages of episodic emotional memory: A narrative review and guide to the future

For two decades, sleep has been touted as one of the primary drivers for the encoding, consolidation, retention, and retrieval of episodic emotional memory. Recently, however, sleep’s role in emotional memory processing has received renewed scrutiny as meta-analyses and reviews have indicated that sleep may only contribute a small effect that hinges on the content or context of the learning and retrieval episodes. On the one hand, the strong perception of sleep’s importance in maintaining memory for emotional events may have been exacerbated by publication bias phenomena, such as the “winner’s curse” and “file drawer problem. ” On the other hand, it is plausible that there are sets of circumstances that lead to consistent and reliable effects of sleep on emotional memory; these circumstances may depend on factors such as the placement and quality of sleep relative to the emotional experience, the content and context of the emotional experience, and the probes and strategies used to assess memory at retrieval. Here, we review the literature on how sleep (and sleep loss) influences each stage of emotional episodic memory. Specifically, we have separated previous work based on the placement of sleep and sleep loss in relation to the different stages of emotional memory processing: (1) prior to encoding, (2) immediately following encoding during early consolidation, (3) during extended consolidation, separated from initial learning, (4) just prior to retrieval, and (5) post-retrieval as memories may be restructured and reconsolidated. The goals of this review are three-fold: (1) examine phases of emotional memory that sleep may influence to a greater or lesser degree, (2) explicitly identify problematic overlaps in traditional sleep–wake study designs that are preventing the ability to better disentangle the potential role of sleep in the different stages of emotional memory processing, and (3) highlight areas for future research by identifying the stages of emotional memory processing in which the effect of sleep and sleep loss remains under-investigated. Here, we begin the task of better understanding the contexts and factors that influence the relationship between sleep and emotional memory processing and aim to be a valuable resource to facilitate hypothesis generation and promote important future research.
Brain disorder prediction with dynamic multivariate spatio-temporal features: Application to Alzheimer’s disease and autism spectrum disorder

The dynamic functional connectivity (dFC) in functional magnetic resonance imaging (fMRI) is beneficial for the analysis and diagnosis of neurological brain diseases. The dFCs between regions of interest (ROIs) are generally delineated by a specific template and clustered into multiple different states. However, these models inevitably fell into the model-driven self-contained system which ignored the diversity at spatial level and the dynamics at time level of the data. In this study, we proposed a spatial and time domain feature extraction approach for Alzheimer’s disease (AD) and autism spectrum disorder (ASD)-assisted diagnosis which exploited the dynamic connectivity among independent functional sub networks in brain. Briefly, independent sub networks were obtained by applying spatial independent component analysis (SICA) to the preprocessed fMRI data. Then, a sliding window approach was used to segment the time series of the spatial components. After that, the functional connections within the window were obtained sequentially. Finally, a temporal signal-sensitive long short-term memory (LSTM) network was used for classification. The experimental results on Alzheimer’s Disease Neuroimaging Initiative (ADNI) and Autism Brain Imaging Data Exchange (ABIDE) datasets showed that the proposed method effectively predicted the disease at the early stage and outperformed the existing algorithms. The dFCs between the different components of the brain could be used as biomarkers for the diagnosis of diseases such as AD and ASD, providing a reliable basis for the study of brain connectomics.
Lifestyle habits, macronutrient intake, and obesity prevalence among adolescents in rural-periurban community senior high schools in the Ho municipality of Ghana

Background Adolescence is a critical stage in the life cycle that presents a window of opportunity for the formation of lifetime habits or an aversion to childhood malnutrition effects. This study assessed the lifestyle habits, macronutrient intakes, and obesity prevalence among adolescents in some selected Senior High Schools in rural communities in Ho Municipality. Materials and methods A cross-sectional survey was conducted among 272 adolescents aged 13–19 years and attending senior high schools in the Ho Municipality of Ghana. Data on sociodemographic, physical activity levels, dietary habits, and anthropometrics were obtained. A body mass index (BMI) and waist circumference (WC) were determined, while a repeated 24-h dietary recall was used to collect the dietary intakes of the participants. Results The majority of the adolescents did not meet the Recommended Dietary Allowances (RDA) for calories (94.5%), dietary protein (68.8%), and fibre (91.5%). Adolescent boys consumed more calories (1,969.7 ± 579.9 Kcal) on average than adolescent girls (1,658.0 ± 458.7 Kcal) (p = 0.001). Overweight and obesity prevalence were 15.8 and 8.5%, respectively. About 90.4% of the adolescents did not meet the WHO recommended 150 min per week of physical exercise. On sedentary, 97.6% of adolescents spent half an hour to 5 h per day watching television when at home. Breakfast was the most frequently skipped meal (47.9%), and 59.6% of adolescents consumed fast foods such as pizza, burgers, and ice cream one to three times per week. Adolescent girls also had higher odds of being overweight or obese compared with adolescent boys (AOR = 2.4, p = 0.094, 95% CI = 0.9–6.4). Adolescents who did not meet the RDA for calories had lower odds of being overweight or obese compared with those who did (UOR = 0.3, p = 0.045, 95% CI = 0.1–0.9). Conclusion Poor dietary habits and intake, sedentary lifestyle, and obesity prevalence were observed among the adolescents. Being an adolescent girl was associated with obesity risk, while not meeting caloric intake showed a protective effect. Efficient and effective nutrition and lifestyle education programme should be promoted in communities to improve the dietary intake and lifestyle habits of adolescents.