Miracle-dz/UniFAR-FTUs huggingface dataset:
Near-peer teaching in problem-based learning: Perspectives from tutors and tutees

Introduction This study explores how tutors and tutees perceived their teaching and learning experience in a near-peer teaching programme within a formal undergraduate medical-education curriculum. Methods This mixed-methods study was conducted in an Asian medical school. First, a survey was administered to two groups of students, one that had been tutored by near-peers, and another with faculty tutors. Then, the near-peer tutors were interviewed and wrote reflection essays that the researchers collected. Quantitative analysis was used to analyse the survey responses, and qualitative analysis to analyse the interview and reflection data. Results Our study found no difference between near-peer tutees’ and faculty tutees’ perceptions of either tutor facilitation or tutor behaviours. Also, when near-peer tutors explained how their experience of delivering tutoring had influenced their professional-identity formation, they highlighted that they had gained skills important to their future careers as medical educators. Conclusion Integrating near-peer teaching into undergraduate medical curricula could be beneficial to both tutors and tutees because of the social, cognitive, and professional congruence between these two groups, and due to its likely positive influence on their professional-identity formation.
Perceived water-related risk factors of Buruli ulcer in two villages of south-central Côte d’Ivoire

Background Buruli ulcer, caused by Mycobacterium ulcerans, is a neglected tropical skin disease that is primarily endemic in West and Central Africa, including Côte d’Ivoire. Studies indicate that M. ulcerans infections are caused by contact with an environmental reservoir of the bacteria, governed by specific human biological conditions. Yet, the nature of this reservoir and the exact mode of transmission remain unknown. Methodology To identify ecologic risk factors of Buruli ulcer in south-central Côte d’Ivoire, we pursued a qualitative study matched with geo-referencing inquiry. Embedded in a broader integrated wound management research project, we (i) mapped households and water sources of laboratory confirmed Buruli ulcer cases and (ii) interviewed 12 patients and four health care workers to assess exposure to surface water and to deepen the understanding of perceived transmission pathways. Principal findings Water availability, accessibility, and affordability were reported as key determinants for choosing water resources. Furthermore, perceived risks were related to environmental, structural, and individual factors. Despite the presence of improved water sources (e.g., drilled wells), communities heavily relied on unprotected surface water for a multitude of activities. The nearby Bandama River and seasonal waterbodies were frequently used for washing, bathing, and collection of water for drinking and cooking. Many residents also reported to cross the river on a daily basis for agricultural chores, and hence, are exposed to stagnant water during farming activities. Conclusions/significance Our study in two Buruli ulcer endemic villages in south-central Côte d’Ivoire revealed a wide range of water-related domestic activities that might expose people to an increased risk of contracting the disease. Environmental, biological, social, and cultural risk factors are closely interlinked and should be considered in future investigations of Buruli ulcer transmission. Active participation of the communities is key to better understand their circumstances to advance research and fight against Buruli ulcer and other neglected tropical diseases.
Cost-effectiveness analysis of the multi-strategy WHO emergency care toolkit in regional referral hospitals in Uganda

Background Low- and middle-income countries bear a disproportionate amount of the global burden of disease from emergency conditions. To improve the provision of emergency care in low-resource settings, a multifaceted World Health Organization (WHO) intervention introduced a toolkit including Basic Emergency Care training, resuscitation area guidelines, a trauma registry, a trauma checklist, and triage tool in two public hospital sites in Uganda. While introduction of the toolkit revealed a large reduction in the case fatality rate of patients, little is known about the cost-effectiveness and affordability. We analysed the cost-effectiveness of the toolkit and conducted a budget analysis to estimate the impact of scale up to all regional referral hospitals for the national level. Methods A decision tree model was constructed to assess pre- and post-intervention groups from a societal perspective. Data regarding mortality were drawn from WHO quality improvement reports captured at two public hospitals in Uganda from 2016–2017. Cost data were drawn from project budgets and included direct costs of the implementation of the intervention, and direct costs of clinical care for patients with disability. Development costs were not included. Parameter uncertainty was assessed using both deterministic and probabilistic sensitivity analyses. Our model estimated the incremental cost-effectiveness of implementing the WHO emergency care toolkit measuring all costs and outcomes as disability-adjusted life-years (DALYs) over a lifetime, discounting both costs and outcomes at 3.5%. Results Implementation of the WHO Toolkit averted 1,498 DALYs when compared to standard care over a one-year time horizon. The initial investment of $5,873 saved 34 lives (637 life years) and avoided $1,670,689 in downstream societal costs, resulted in a negative incremental cost-effectiveness ratio, dominating the comparator scenario of no intervention. This would increase to saving 884 lives and 25,236 DALYs annually with national scale up. If scaled to a national level the total intervention cost over period of five years would be $4,562,588 or a 0.09% increase of the total health budget for Uganda. The economic gains are estimated to be $29,880,949 USD, the equivalent of a 655% return on investment. The model was most sensitive to average annual cash income, discount rate and frequency survivor is a road-traffic incident survivor, but was robust for all other parameters. Conclusion Improving emergency care using the WHO Toolkit produces a cost-savings in a low-resource setting such as Uganda. In alignment with the growing body of literature highlighting the value of systematizing emergency care, our findings suggest the toolkit could be an efficient approach to strengthening emergency care systems.
Development of a 3D simulator for training the mouse in utero electroporation

In utero electroporation (IUE) requires high-level training in microinjection through the mouse uterine wall into the lateral ventricle of the mouse brain. Training for IUE is currently being performed in live mice as no artificial models allow simulations yet. This study aimed to develop an anatomically realistic 3D printed simulator to train IUE in mice. To this end, we created embryo models containing lateral ventricles. We coupled them to uterus models in six steps: (1) computed tomography imaging, (2) 3D model segmentation, (3) 3D model refinement, (4) mold creation to cast the actual model, (5) 3D mold printing, and (6) mold casting the molds with a mix of soft silicones to ensure the hardness and consistency of the uterus and embryo. The results showed that the simulator assembly successfully recreated the IUE. The compression test did not differ in the mechanical properties of the real embryo or in the required load for uterus displacement. Furthermore, more than 90% of the users approved the simulator as an introduction to IUE and considered that the simulator could help reduce the number of animals for training. Despite current limitations, our 3D simulator enabled a realistic experience for initial approximations to the IUE and is a real alternative for implementing the 3Rs. We are currently working on refining the model.
Impacts of climate change on species distribution patterns of Polyspora sweet in China

Abstract Climate change is an important driver of species distribution and biodiversity. Understanding the response of plants to climate change is helpful to understand species differentiation and formulate conservation strategies. The genus Polyspora (Theaceae) has an ancient origin and is widely distributed in subtropical evergreen broad‐leaved forests. Studies on the impacts of climate change on species geographical distribution of Chinese Polyspora can provide an important reference for exploring the responses of plant groups in subtropical evergreen broad‐leaved forests with geological events and climate change in China. Based on the environmental variables, distribution records, and chloroplast genomes, we modeled the potential distribution of Chinese Polyspora in the Last Glacial Maximum, middle Holocene, current, and future by using MaxEnt‐ArcGIS model and molecular phylogenetic method. The changes in the species distribution area, centroid shift, and ecological niche in each periods were analyzed to speculate the response modes of Chinese Polyspora to climate change in different periods. The most important environmental factor affecting the distribution of Polyspora was the precipitation of the driest month, ranging from 13 to 25 mm for the highly suitable habitats. At present, highly suitable distribution areas of Polyspora were mainly located in the south of 25°N, and had species‐specificity. The main glacial refugia of the Chinese Polyspora might be located in the Ailao, Gaoligong, and Dawei Mountains of Yunnan Province. Jinping County, Pingbian County, and the Maguan County at the border of China and Vietnam might be the species differentiation center of the Chinese Polyspora. Moderate climate warming in the future would be beneficial to the survival of P. axillaris, P. chrysandra, and P. speciosa. However, climate warming under different shared socio‐economic pathways would reduce the suitable habitats of P. hainanensis and P. longicarpa.
Ultraviolet mini-Raman lidar for stand-off, in situ identification of chemical surface contaminants

The Mini-Raman Lidar System (MRLS) is a portable chemical sensor that combines the spectral fingerprinting of Raman spectroscopy with the principles of solar-blind ultraviolet lidar for short-range, noncontact detection and identification of unknown substances on surfaces. The MRLS has the potential to detect contaminant films several microns thick at distances of meters and bulk quantities of substances at distances of tens of meters. The signal acquisition time is less than 1 min. The device has application to those involved in emergency response, environmental remediation, and military reconnaissance who respond initially at the site of a chemical spill or attack.
Quantum mechanical Hamiltonian models of discrete processes

Here the results of other work on quantum mechanical Hamiltonian models of Turing machines are extended to include any discrete process T on a countably infinite set A. The models are constructed here by use of scattering phase shifts from successive scatterers to turn on successive step interactions. Also a locality requirement is imposed. The construction is done by first associating with each process T a model quantum system M with associated Hilbert space HM and step operator UT. Since UT is not unitary in general, M, HM, and UT are extended into a (continuous time) Hamiltonian model on a larger space which satisfies the locality requirement. The construction is compared with the minimal unitary dilation of UT. It is seen that the model constructed here is larger than the minimal one. However, the minimal one does not satisfy the locality requirement.
Microcavities in polymeric photonic crystals

We report the fabrication and characteristics of planar microcavities in a log-pile photonic crystal structure formed using light-induced photopolymerization of resin. A planar defect was introduced into the middle of the log-pile structure as a single layer with every second rod missing. The existence of confined cavity states was confirmed experimentally and by numeric simulations. The cavity resonance found at the midgap wavelength λM∼4.0 μm had a quality factor of about 130.
Estimation of Chromaticity Differences and Nearest Color Temperature on the Standard 1931 ICI Colorimetric Coordinate System

Estimation of chromaticity differences has been facilitated by the preparation of a standard mixture diagram showing by a group of ellipses the scales of perceptibility at the various parts of the diagram. The distances from the boundaries of the ellipses to their respective “centers” all correspond approximately to the same number (100) of “least perceptible differences. ” The estimation of nearest color temperature has been facilitated by the preparation of a mixture diagram on which is shown a family of straight lines intersecting the Planckian locus; each straight line corresponds approximately to the locus of points representing stimuli of chromaticity more closely resembling that of the Planckian radiator at the intersection than that of any other Planckian radiator.
A Structural Equation Model for implementation of Smart Card A Structural Equation Model for implementation of Smart Card Technology in public healthcare Technology in public healthcare

The improvement of health care, efficiency, safety, and quality of delivery and access for patients is highly portrays a rather significant increase in public healthcare.The emergence of this proliferation of healthcare technology is then expected to grow. The researcher seeks to investigate the factors that influence the implementation of sct in sa public healthcare institutions. A quantitative research method approach was used. respondents were selected using the purposive sampling method. using a self-administered questionnaire completed by 406 healthcare professionals from Steve
Remote estimation of geologic composition using interferometric synthetic-aperture radar in California's Central Valley

California's Central Valley is the national agricultural center, producing 1/4 of the nation's food. However, land in the Central Valley is sinking at a rapid rate (as much as 20 cm per year) due to continued groundwater pumping. Land subsidence has a significant impact on infrastructure resilience and groundwater sustainability. In this study, we aim to identify specific regions with different temporal dynamics of land displacement and find relationships with underlying geological composition. Then, we aim to remotely estimate geologic composition using interferometric synthetic aperture radar (InSAR)-based land deformation temporal changes using machine learning techniques. We identified regions with different temporal characteristics of land displacement in that some areas (e.g., Helm) with coarser grain geologic compositions exhibited potentially reversible land deformation (elastic land compaction). We found a significant correlation between InSAR-based land deformation and geologic composition using random forest and deep neural network regression models. We also achieved significant accuracy with 1/4 sparse sampling to reduce any spatial correlations among data, suggesting that the model has the potential to be generalized to other regions for indirect estimation of geologic composition. Our results indicate that geologic composition can be estimated using InSAR-based land deformation data. In-situ measurements of geologic composition can be expensive and time consuming and may be impractical in some areas. The generalizability of the model sheds light on high spatial resolution geologic composition estimation utilizing existing measurements.
Appropriateness of video call consultations in a Dutch primary care setting

The pressure on healthcare is increasing worldwide. The trend toward digitalization in recent decades and the emergence of modern technologies have enabled remote treatment and offered patients new ways to interact with physicians. Despite numerous studies showing promising results in the use of video calls for primary care consultations, some survey studies report lingering doubts about the effectiveness of this method among general practitioners (GPs) and patients. Because the organization of health care varies widely across countries, we set out to investigate the appropriateness of video calling in a Dutch health care setting. Unlike many survey studies, we collected real-life data where GPs evaluated the video call directly after the consultation, allowing a more realistic assessment of perceived quality. We find that video calls are appropriate 84.2% (95% CI 80.3%-87.8%) of the time for consultations with patients of moderate to low urgency. Importantly, the appropriateness of video calls decreased with increasing urgency. These results build on previous studies and confirm the positive use cases of video calls focused on primary care in the Netherlands.
Low temperature solid phase crystallization of amorphous silicon at 380 °C

Amorphous silicon (a-Si) was crystallized by metal induced crystallization (MIC) in an electric field. A 2 nm Ni layer on a-Si was used for the crystallization. The MIC temperature can be reduced to 380 °C in an electric field of 360 V/cm. The Ni-MIC poly-Si has a crystalline volume fraction of 92% with an average grain size of ∼150 nm. The fact that the crystallization temperature can be reduced appears to be due to the enhancement of NiSi2 migration through a-Si in an electric field.
Solar modulation of galactic cosmic rays: 3. Implications of the Compton‐Getting Coefficient

It is useful to express spectra of modulated galactic cosmic rays in terms of the Compton-Getting coefficient C. This parameter can reveal the energy range over which the force field approximation is valid and the range where convection effects dominate over those of diffusion. A value of C near zero over an extended low-energy range (according to recent observations this is the situation for protons) implies that the radial gradient at low energies cannot be large. This small gradient may imply, in turn, that the diffusion coefficient increases beyond 1 AU less rapidly than if it were proportional to heliocentric radial distance and/or that there is essentially no scattering for a sizeable distance from the sun to earth. The behavior of C with rigidity (or energy) is discussed in terms of the omnidirectional distribution function ƒ0. Contours of constant ƒ0 in the heliocentric distance versus rigidity plane are useful for illustrating the mean rigidity loss experienced by cosmic rays in the interplanetary medium.
Continuum–discontinuum modelling of shear bands

A methodology to model shear bands as strong discontinuities within a continuum mechanics context is presented. The loss of hyperbolicity of the IBVP is used as the criterion for switching from a classical continuum description of the constitutive behaviour to a traction–separation model acting at the discontinuity surface. The extended finite element method (XFEM) is employed for the spatial discretization of the governing equations. This enables the shear bands to be arbitrarily positioned within the mesh. Examples that study the shear band progression within a rate‐independent material are presented. Copyright © 2005 John Wiley & Sons, Ltd.
Feature extraction using supervised constrained maximum variance mapping

Constrained maximum variance mapping (CMVM) based on the multi-manifold learning is an efficiency method for feature extraction. CMVM preserves the local manifold structure by keep the sum of the distances of samples unchanged, but ignores the local label information of the samples, which is very important to the recognition. To tackle the shortage, we propose a new method called supervised constrained maximum variance mapping (SCMVM), which projects the local structure into feature space by a linear map. SCMVM combines the Euclidean distance with the label information in local structure and maximizing the distance of samples with different classes. Because consider the local label information, the efficiency of recognition enhances clearly. In this paper, we take experiments on Yale face database and USPS handwriting database using CMVM and SCMVM, and compare the efficiency.
BAHADUR REPRESENTATION OF SAMPLE CONDITIONAL QUANTILES BASED ON SMOOTHED CONDITIONAL EMPIRICAL DISTRIBUTION FUNCTION

Let {(X1, Y1) : i = 1, 2, . ; be a sequence of stationary independent random vectors in :71(2) with a continuous distribution, and let G. ,(•) denote the conditional distribution function of Y1 given X, = x. In this paper, Bahadur's almost sure representation for the sample conditional quantile G,,„V), 0 < i. < 1, is established, where G,,. , is a smoothed (rank nearest neighbor or the NadarayaWatson type) estimator of G,-. Such representations arc useful in the study of asymptotics of functionals of conditional quantiles.
Detecting bone lesions in X-ray under diverse acquisition conditions.

Purpose The diagnosis of primary bone tumors is challenging as the initial complaints are often non-specific. The early detection of bone cancer is crucial for a favorable prognosis. Incidentally, lesions may be found on radiographs obtained for other reasons. However, these early indications are often missed. We propose an automatic algorithm to detect bone lesions in conventional radiographs to facilitate early diagnosis. Detecting lesions in such radiographs is challenging. First, the prevalence of bone cancer is very low; any method must show high precision to avoid a prohibitive number of false alarms. Second, radiographs taken in health maintenance organizations (HMOs) or emergency departments (EDs) suffer from inherent diversity due to different X-ray machines, technicians, and imaging protocols. This diversity poses a major challenge to any automatic analysis method. Approach We propose training an off-the-shelf object detection algorithm to detect lesions in radiographs. The novelty of our approach stems from a dedicated preprocessing stage that directly addresses the diversity of the data. The preprocessing consists of self-supervised region-of-interest detection using vision transformer (ViT), and a foreground-based histogram equalization for contrast enhancement to relevant regions only. Results We evaluate our method via a retrospective study that analyzes bone tumors on radiographs acquired from January 2003 to December 2018 under diverse acquisition protocols. Our method obtains 82.43% sensitivity at a 1.5% false-positive rate and surpasses existing preprocessing methods. For lesion detection, our method achieves 82.5% accuracy and an IoU of 0.69. Conclusions The proposed preprocessing method enables effectively coping with the inherent diversity of radiographs acquired in HMOs and EDs.