Miracle-dz/UniFAR-FTUs huggingface dataset:
Balancing the benefits of patient-clinician relationships with professional boundaries in Home-based Primary Care

ABSTRACT In the home care setting, boundaries may be difficult to identify when behavioral changes are made to accommodate the nature of care being delivered. In this secondary qualitative study, we examined how Home-based Primary Care (HBPC) clinicians understand role and relationship boundaries with patients and how these dynamics support patient care. The data set consisted of 14 semi-structured interviews with HBPC clinicians representing multiple disciplines and field observations of 6 HBPC team meetings. Using a directed approach to content analysis, we identified and described how HBPC clinicians worked to build relationships with patients, experienced challenges with emotional attachment, and negotiated boundaries in the patient-clinician relationship. Our findings illustrate how the home care setting is a site for which strong, therapeutic patient-clinician relationships can be developed while also highlighting the work that clinicians must do to balance addressing patient needs stemming from social isolation and adherence to their own professional boundaries.
Maize starch derived boron doped carbon spheres via facile solvothermal route as the photoluminescence sensor for determination of pH and Cr(VI)

In this work, a kind of boron doped carbon spheres (B-CSs) was successfully synthesized utilizing maize starch as carbon source and boric acid as dopant via facile solvothermal method. The chemical structure of the prepared B-CSs was systemically investigated by TEM, FT-IR, XRD, XPS and EDS. The synthesized B-CSs feature spherical structure with average size of ∼254 nm and exhibit strong photoluminescence (PL) with maximum emission at a wavelength of ∼453 nm under irradiation at 350 nm, leading to a quantum yield of 6.2%. Furthermore, the aqueous pH and Cr(VI) has a significantly various impact on the PL intensity of B-CSs, which can be flexibly utilized as the PL sensor for detection aqueous pH and Cr(VI) in aqueous. Particularly, the B-CSs have a desirable sensitivity and selectivity for detection of Cr(VI) with a low detection limit of ∼0.34 μmol l−1. Conclusively, our work provides a novel and dual-functional fluorescent sensor for detection of the pH and toxic metal ions in water environment.
hCoronavirusesDB: an integrated bioinformatics resource for human coronaviruses

Abstract In the twenty-first century, three new human coronaviruses have been identified with known zoonotic origins: severe acute respiratory syndrome coronavirus (SARS-CoV), SARS-CoV-2, and Middle East respiratory syndrome coronavirus (MERS-CoV). SARS-CoV-2 was identified in November 2019 and is associated with an ongoing pandemic. Molecular surveillance and monitoring studies are essential for containing viral outbreaks, epidemics, and pandemics. In addition, the development and deployment of bioinformatics resources for highly pathogenic human coronaviruses are crucial for understanding the genetic and immunogenic landscape associated with these viruses. Here, we introduce an open-access, integrated resource for SARS-CoV, SARS-CoV-2, and MERS-CoV: the Human Coronaviruses Database and Analysis Resource (hCoronavirusesDB; http://hcoronaviruses.net/), which include nucleotide and protein sequence data obtained for these viruses. The database also offers a user-friendly search interface coupled with bioinformatics analytics and visualization tools. In addition, hCoronavirusesDB contains curated, experimentally validated B cell and T cell epitope data for these viruses. This resource can assist with the molecular surveillance necessary to trace virus circulation and contribute to microevolutionary studies. This application can also serve as a valuable resource for the development of rationally designed pan-coronavirus diagnostic tools, vaccines, and therapeutic agents. Database URL:http://hcoronaviruses.net/
The prevalence and associated factors of fear of childbirth among Turkish pregnant women

ABSTRACT Objective This study was conducted to determine the prevalence of fear of childbirth and affecting factors in pregnant women in Turkey. Materials and methods This was a cross-sectional study and included a total of 2025. Pregnant Women Assessment, some variables related to previous and current perinatal processes and Wijma Delivery Expectancy/Experience Questionnaire (version A) were used for data collection. Findings In this sample, 42.4% of the women reported fear of childbirth. What the women were afraid of most was the development of unwanted conditions at childbirth, obscurity/uncertainty, and negative attitudes of health professionals. The factors causing fear of childbirth were the low education level, unemployment status, low financial status, stillbirth, unplanned pregnancy, indecisiveness about the type of delivery, not attending prenatal education programs, negative effects of other people, insufficient social support, confiding in the healthcare centre and health professional, negative, and indecisive birth perceptions, prior negative birth experiences and not feeling ready for childbirth (p < 0.001). Conclusions The prevalence of fear of childbirth in this Turkish sample, especially in the multipara is higher than in Western countries. Causes of fear of childbirth can vary with countries and even with each region of a country.
Learning Continuous-Time Dynamics With Attention

Learning the hidden dynamics from sequence data is crucial. Attention mechanism can be introduced to spotlight on the region of interest for sequential learning. Traditional attention was measured between a query and a sequence based on a discrete-time state trajectory. Such a mechanism could not characterize the irregularly-sampled sequence data. This paper presents an attentive differential network (ADN) where the attention over continuous-time dynamics is developed. The continuous-time attention is performed over the dynamics at all time. The missing information in irregular or sparse samples can be seamlessly compensated and attended. Self attention is computed to find the attended state trajectory. However, the memory cost for attention score between a query and a sequence is demanding since self attention treats all time instants as query points in an ordinary differential equation solver. This issue is tackled by imposing the causality constraint in causal ADN (CADN) where the query is merged up to current time. To enhance the model robustness, this study further explores a latent CADN where the attended dynamics are calculated in an encoder-decoder structure via Bayesian learning. Experiments on the irregularly-sampled actions, dialogues and bio-signals illustrate the merits of the proposed methods in action recognition, emotion recognition and mortality prediction, respectively.
β-Cyanoalanine synthase protects mites against Arabidopsis defenses

Abstract Glucosinolates are antiherbivory chemical defense compounds in Arabidopsis (Arabidopsis thaliana). Specialist herbivores that feed on brassicaceous plants have evolved various mechanisms aimed at preventing the formation of toxic isothiocyanates. In contrast, generalist herbivores typically detoxify isothiocyanates through glutathione conjugation upon exposure. Here, we examined the response of an extreme generalist herbivore, the two-spotted spider mite Tetranychus urticae (Koch), to indole glucosinolates. Tetranychus urticae is a composite generalist whose individual populations have a restricted host range but have an ability to rapidly adapt to initially unfavorable plant hosts. Through comparative transcriptomic analysis of mite populations that have differential susceptibilities to Arabidopsis defenses, we identified β-cyanoalanine synthase of T. urticae (TuCAS), which encodes an enzyme with dual cysteine and β-cyanoalanine synthase activities. We combined Arabidopsis genetics, chemical complementation and mite reverse genetics to show that TuCAS is required for mite adaptation to Arabidopsis through its β-cyanoalanine synthase activity. Consistent with the β-cyanoalanine synthase role in detoxification of hydrogen cyanide (HCN), we discovered that upon mite herbivory, Arabidopsis plants release HCN. We further demonstrated that indole glucosinolates are sufficient for cyanide formation. Overall, our study uncovered Arabidopsis defenses that rely on indole glucosinolate-dependent cyanide for protection against mite herbivory. In response, Arabidopsis-adapted mites utilize the β-cyanoalanine synthase activity of TuCAS to counter cyanide toxicity, highlighting the mite’s ability to activate resistant traits that enable this extreme polyphagous herbivore to exploit cyanogenic host plants.
Advanced risk management in offshore terminals and marine ports

This research aims to propose a Risk Management (RM) framework and develop a generic risk-based model for dealing with potential hazards and risk factors associated with offshore terminals' and marine ports' operations and management. Hazard identification was conducted through an appropriate literature review of major risk factors of these logistic infrastructures. As a result in the first phase of this research a Fuzzy Analytical Hierarchal Process (FAHP) method was used for determining the relative weights of the risk factors identified via the literature review. This has led to the development of a generic risk -based model which can help related industrial professionals and risk managers assess the risk factors and develop appropriate strategies to take preventive/corrective actions for mitigation purposes, with a view of maintaining efficient offshore terminals' and marine ports' operations and management. In the second phase of the research the developed risk-based model incorporating Fuzzy Set Theory (FST), an Evidential Reasoning (ER) approach and the IDS software were used to evaluate the risk levels of different ports in real situations using a case study. The IDS software based on an ER approach was used to aggregate the previously determined relative weights of the risk factors with the new evaluation results of risk levels for the real ports. The third phase of the research made use of the Cause and Consequence Analysis (CCA) including the Fault Tree Analysis (FTA) and Event Tree Analysis (ETA) under a fuzzy environment, to analyse in detail the most significant risk factors determined from the first phase of the research, using appropriate case-studies. In the fourth phase of the research an individual RM strategy was tailored and implemented on the most significant risk factor identified previously. In the last phase of the research and in order to complete the RM cycle, the best mitigation strategies were introduced and evaluated in the form of ideal solutions for mitigating the identified risk factors. All methods used in this research have quantitative and qualitative nature. Expert judgements carried out for gathering the required information accounted for the majority of data collected. The proposed RM framework can be a useful method for managers and auditors when conducting their RM programmes in the offshore and marine industries. The novelty of this research can help the Quality, Health, Safety, Environment and Security (QHSES) managers, insurers and risk managers in the offshore and marine industries investigate the potential hazards more appropriately if there is uncertainty of data sources. In this research with considering strategic management approaches to RM development the proposed RM framework and risk based model contribute to knowledge by developing and evaluating an effective methodology for future use of the RM professionals.
Punishment sensitivity and the persistence of anorexia nervosa: High punishment sensitivity is related to a less favorable course of anorexia nervosa

Abstract Objective Cross‐sectional research provides robust evidence that individuals with anorexia nervosa (AN) report higher punishment sensitivity (PS) than individuals without an eating disorder (ED). High PS might interfere with treatment motivation and the ability to learn from experience. The current study took a longitudinal approach to test predictions that follow from the proposed relevance of PS as a factor in the persistence of AN symptoms. More specifically we tested (1) if higher PS at the start of treatment was related to less improvement in ED symptoms after one year, and (2) if a decrease in ED symptoms was associated with a concurrent decrease in PS. Method Participants were 69 adolescents with a diagnosis of AN at the start of treatment of whom 62 participated again one year later. ED symptom severity and PS were assessed at both time points. Results Findings showed that (1) higher PS at the start of treatment was related to less improvement in ED symptoms, and (2) an improvement in ED symptoms was related to a decrease in PS. Discussion These findings are consistent with the proposed relevance of PS in the persistence of AN and suggest that it might be beneficial to address high PS in treatment. Public Significance Consistent with the view that punishment sensitivity (PS) is related to the persistence of anorexia nervosa, high PS at the start of treatment was related to less improvement in eating disorder symptoms in patients with anorexia nervosa. Furthermore, an improvement in eating disorder symptoms was associated with a concurrent decrease in PS, suggesting that PS can be subject to change and may be a relevant target for treatment.
Detection of spoilage‐causing yeasts and bacteria in tchapalo, the Ivorian traditional sorghum beer

In this study, we aimed to analyse the spoilage potential of the isolated yeast, LAB and AAB species. Thus, 11 strains were inoculated at 0·3% (v/v) into a sterile filtered tchapalo and stored for 3 days at ambient temperature (27–30°C). All the tested strains grew well or remained stable except for Limosilactobacillus fermentum and Pediococcus acidilactici, which decreased throughout the storage time. A significant decrease of total soluble solids was observed only for Saccharomyces cerevisiae (from 7·8 to 5·8 °Brix) and Meyerozyma guilliermondii (from 7·8 to 5·5 °Brix). The tchapalo samples inoculated with the LAB strains Weissella paramesenteroides, P. acidilactici, L. fermentum and the yeast strain Candida tropicalis were judged similar to the control by the panellists. However, the strains of Lacticaseibacillus paracasei and Latilactobacillus curvatus (LAB), S. cerevisiae, M. guilliermondii and Kluyveromyces marxianus (yeasts) and Acetobacter pasteurianus and A. cerevisiae (AAB) induced the spoilage of the tchapalo appearance, smell and/or taste. In the spoiled tchapalo quantitative and qualitative modification of some volatile compounds (VOCs), such as lilac aldehyde, ethyl acetate, ethyl hexanoate, ethyl octanoate and phenethyl acetate, were observed. These results provide information about the microorganisms that need to be removed to extend the shelf life of tchapalo.
Association of triglyceride-glucose with cardiac hemodynamics in type 2 diabetes

Purpose Triglyceride-glucose (TyG) index is a reliable and inexpensive alternative indicator of insulin resistance. Previous studies have shown that elevated TyG index increases the risk of diabetes, coronary heart disease, and other diseases, but the relationship between TyG index and cardiac hemodynamics in patients with type 2 diabetes mellitus (T2DM) is not clear. This study was conducted in patients with T2DM to assess the relationship between TyG and cardiac hemodynamics and its predictive ability for T2DM. Methods A total of 647 individuals (348 males and 299 females) were enrolled in this study, including 446 T2DM patients and 201 healthy controls. The clinical data and related laboratory variables were assessed and recorded, and TyG index was calculated. Cardiac hemodynamics was measured by echocardiography. Pearson or Spearman correlation analysis and linear regression analysis were conducted to explore the association between TyG and cardiac hemodynamics. The receiver operating characteristics (ROC) curve was used to evaluate the efficacy of TyG index in the diagnosis of T2DM. Results Compared with healthy controls, the systolic blood pressure (SBP), body weight, body mass index (BMI), waist circumference (WC), hip circumference (HC), HOMA-IR, and TyG levels were higher in patients with T2DM. With the increase of TyG, the levels of left ventricular mass index (LVMI), left ventricular mass (LVM), left ventricular end diastolic diameter (LVDd), posterior wall thickness (PWT), and interventricular septum thickness (IVST) were also increased in T2DM individuals. Multivariate linear regression analysis showed that TyG was an independent determinant of LVEF, PWT, IVST, and ejection time (ET) after adjusting for confounding factors. In addition, individuals with visceral obesity had higher TyG and TyG can be used as a predictor of T2DM with an AUC of 0.903 (95% CI:0.879–0.927). Conclusions The increase of TyG index is closely related to cardiac hemodynamics of T2DM patients, which is expected to be a simple and practical biological index to predict the changes of cardiac function in patients with T2DM.
A digital twin for simulating the vertebroplasty procedure and its impact on mechanical stability of vertebra in cancer patients

We present the application of ReconGAN, introduced in a previous study, for simulating the vertebroplasty (VP) operation and its impact on the fracture response of a vertebral body. ReconGAN consists of a Deep Convolutional Generative Adversarial Network (DCGAN) and a finite element based shape optimization algorithm to virtually reconstruct the trabecular bone microstructure. The VP procedure involves injecting shear‐thinning liquid bone cement through a needle in the trabecular region to reinforce a diseased or fractured vertebra. To simulate this treatment modality, computational fluid dynamics (CFD) is employed to predict the morphology of the injected cement within the bone microstructure. A power‐law equation is utilized to characterize the non‐Newtonian shear‐thinning behavior of the polymethyl methacrylate (PMMA) bone cement during injection simulations. The CFD model is coupled with the level‐set method to simulate the motion of the interface separating bone cement and bone marrow. After predicting the cement morphology, a data co‐registration algorithm is employed to transform the CFD model to a high‐fidelity continuum damage mechanics (CDM) finite element model of the augmented vertebra for predicting the fracture response. A feasibility study is presented to demonstrate the ability of this CFD‐CDM framework to investigate the effect of VP on the mechanical integrity of the vertebral body in a cancer patient with a lytic metastatic tumor.
Physics-Guided Reflection Separation from a Pair of Unpolarized and Polarized Images

Undesirable reflections contained in photos taken in front of glass windows or doors often degrade visual quality of the image. Separating two layers apart benefits both human and machine perception. Polarization status of the light changes after refraction or reflection, providing more observations of the scene, which can benefit reflection separation. Different from previous works that take three or more polarization images as input, we propose to exploit physical constraints from a pair of unpolarized and polarized images to separate reflection and transmission layers in this paper. Due to the simplified capturing setup, the system is more under-determined compared to the existing polarization-based works. In order to solve this problem, we propose to estimate the semi-reflector orientation first to make the physical image formation well-posed, and then learn to reliably separate two layers using additional networks based on both physical and numerical analysis. In addition, a motion estimation network is introduced to handle the misalignment of paired input. Quantitative and qualitative experimental results show our approach performs favorably over existing polarization and single image based solutions.
Multiple Mechanisms of Photoreceptor Spectral Tuning in Heliconius Butterflies

Abstract The evolution of color vision is often studied through the lens of receptor gain relative to an ancestor with fewer spectral classes of photoreceptor. For instance, in Heliconius butterflies, a genus-specific UVRh opsin duplication led to the evolution of UV color discrimination in Heliconius erato females, a rare trait among butterflies. However, color vision evolution is not well understood in the context of loss. In Heliconius melpomene and Heliconius ismenius lineages, the UV2 receptor subtype has been lost, which limits female color vision in shorter wavelengths. Here, we compare the visual systems of butterflies that have either retained or lost the UV2 photoreceptor using intracellular recordings, ATAC-seq, and antibody staining. We identify several ways these butterflies modulate their color vision. In H. melpomene, chromatin reorganization has downregulated an otherwise intact UVRh2 gene, whereas in H. ismenius, pseudogenization has led to the truncation of UVRh2. In species that lack the UV2 receptor, the peak sensitivity of the remaining UV1 photoreceptor cell is shifted to longer wavelengths. Across Heliconius, we identify the widespread use of filtering pigments and co-expression of two opsins in the same photoreceptor cells. Multiple mechanisms of spectral tuning, including the molecular evolution of blue opsins, have led to the divergence of receptor sensitivities between species. The diversity of photoreceptor and ommatidial subtypes between species suggests that Heliconius visual systems are under varying selection pressures for color discrimination. Modulating the wavelengths of peak sensitivities of both the blue- and remaining UV-sensitive photoreceptor cells suggests that Heliconius species may have compensated for UV receptor loss.
Resilience of Critical Infrastructure to Extreme Fires - Gaps and Challenges

Abstract : This report provides the results of the study conducted by NRC on the protection and resilience of critical infrastructures against extreme fires, e.g. fuel storage or tanker fires. The 9/11 World Trade Centre building collapse and the MacArthur Maze Bridge collapse on April 27, 2007, a critical bridge in the San Francisco area, are two examples of such extreme fire threats to critical infrastructures. The main goal of this study was to develop a better understanding of the threats from extreme fires to critical physical infrastructures. Furthermore, the studies attempted to identify and prioritize the gaps and challenges of the prevention, response and recovery from such incidents. The study included a literature review of the gaps and research needs for the assessment and protection of critical infrastructures to enhance their resilience against extreme fire. Critical border crossing bridges/tunnels, embassies and government buildings are examples of critical infrastructures. An advisory board with 25 members from different government departments, industries and regulatory bodies discussed these research needs and provided inputs on their priorities. This project also included two demonstration fire tests conducted using a new testing facility at the National Research Council Canada (NRC). As an example of a bridge/building structural element, two reinforced concrete columns were successfully tested based on two standards; an extreme fire, ASTM E1529, and a typical building fire, ASTM E119. The results demonstrated that 1) extreme fire conditions could be produced using the NRC furnace facility and 2) fire endurance/resilience of critical infrastructures can be tested and evaluated using this facility. This report presents the outcomes of the review study on the gaps and priorities as well as the results of the two fire tests.