Miracle-dz/UniFAR-FTUs huggingface dataset:
Physiologically Based Pharmacokinetic Modeling and Allometric Scaling in Pediatric Drug Development: Where Do We Draw the Line?

Developing medicines for children is now established in legislation in both the United States and Europe; new drugs require pediatric study or investigation plans as part of their development. Particularly in early age groups, many developmental processes are not reflected by simple scalars such as body weight or body surface area, and even projecting doses based on simple allometric scaling can lead to significant overdoses in certain age groups. Modeling and simulation methodology, including physiologically based modeling, has evolved as part of the drug development toolkit and is being increasingly applied to various aspects of pediatric drug development. Pediatric physiologically based pharmacokinetic (PBPK) models account for the development of organs and the ontogeny of specific enzymes and transporters that determine the age‐related pharmacokinetic profiles. However, when should this approach be used, and when will simpler methods such as allometric scaling suffice in answering specific problems? The aim of this review article is to illustrate the application of allometric scaling and PBPK in pediatric drug development and explore the optimal application of the latter approach with reference to case examples. In reality, allometric scaling included as part of population pharmacokinetic and PBPK approaches are all part of a model‐informed drug development toolkit helping with decision making during the process of drug discovery and development; to that end, they should be viewed as complementary.
AutoClips: An Automatic Approach to Video Generation from Data Facts

Data videos, a storytelling genre that visualizes data facts with motion graphics, are gaining increasing popularity among data journalists, non‐profits, and marketers to communicate data to broad audiences. However, crafting a data video is often time‐consuming and asks for various domain knowledge such as data visualization, animation design, and screenwriting. Existing authoring tools usually enable users to edit and compose a set of templates manually, which still cost a lot of human effort. To further lower the barrier of creating data videos, this work introduces a new approach, AutoClips, which can automatically generate data videos given the input of a sequence of data facts. We built AutoClips through two stages. First, we constructed a fact‐driven clip library where we mapped ten data facts to potential animated visualizations respectively by analyzing 230 online data videos and conducting interviews. Next, we constructed an algorithm that generates data videos from data facts through three steps: selecting and identifying the optimal clip for each of the data facts, arranging the clips into a coherent video, and optimizing the duration of the video. The results from two user studies indicated that the data videos generated by AutoClips are comprehensible, engaging, and have comparable quality with human‐made videos.
Animated Presentation of Static Infographics with InfoMotion

By displaying visual elements logically in temporal order, animated infographics can help readers better understand layers of information expressed in an infographic. While many techniques and tools target the quick generation of static infographics, few support animation designs. We propose InfoMotion that automatically generates animated presentations of static infographics. We first conduct a survey to explore the design space of animated infographics. Based on this survey, InfoMotion extracts graphical properties of an infographic to analyze the underlying information structures; then, animation effects are applied to the visual elements in the infographic in temporal order to present the infographic. The generated animations can be used in data videos or presentations. We demonstrate the utility of InfoMotion with two example applications, including mixed‐initiative animation authoring and animation recommendation. To further understand the quality of the generated animations, we conduct a user study to gather subjective feedback on the animations generated by InfoMotion.
Healthcare worker training to improve quality of care for sexual and gender minority people in sub‐Saharan Africa: learning from efforts in Uganda

Training in care for sexual and gender minority (SGM) populations is critical for ending the HIV epidemic. SGM people, particularly men who have sex with men (MSM) and transgender women, experience disproportionate HIV infection across the globe. The objective of this commentary was to synthesize facilitators of and barriers to SGM health training efforts for healthcare workers in Uganda, in order to help inform potential priorities, strategies and next steps to advance culturally responsive HIV‐related care for SGM communities across Uganda and sub‐Saharan Africa.
A Visual Designer of Layer‐wise Relevance Propagation Models

Layer‐wise Relevance Propagation (LRP) is an emerging and widely‐used method for interpreting the prediction results of convolutional neural networks (CNN). LRP developers often select and employ different relevance backpropagation rules and parameters, to compute relevance scores on input images. However, there exists no obvious solution to define a “best” LRP model. A satisfied model is highly reliant on pertinent images and designers' goals. We develop a visual model designer, named as VisLRPDesigner, to overcome the challenges in the design and use of LRP models. Various LRP rules are unified into an integrated framework with an intuitive workflow of parameter setup. VisLRPDesigner thus allows users to interactively configure and compare LRP models. It also facilitates relevance‐based visual analysis with two important functions: relevance‐based pixel flipping and neuron ablation. Several use cases illustrate the benefits of VisLRPDesigner. The usability and limitation of the visual designer is evaluated by LRP users.
Effects of strain on band structure and effective masses in MoS$_2$

Submitted for the MAR13 Meeting of The American Physical Society Effects of strain on band structure and effective masses in MoS2 1 HARTWIN PEELAERS, CHRIS G. VAN DE WALLE, Materials Department, University of California, Santa Barbara, CA 93106-5050 — Molybdenum disulfide (MoS2) is a layered semiconductor that shows great promise for devices such as fieldeffect transistors. It has an important advantage compared to graphene, namely that it has a band gap. However, a lot of crucial information about the band structure and electronic properties of this material is still lacking, hampering interpretation of experiments and preventing accurate device modeling. Here we use hybrid density functional theory to calculate key materials parameters such as band gaps and effective masses, as well as to investigate effects of strain. We show how strain allows engineering the nature (direct vs. indirect) and size of the band gap and the magnitude of effective masses. In addition, insight into the fundamental physics is provided by considering the transition between the bulk and the monolayer as a function of tensile uniaxial stress. 1This work was supported by a GRO from SAIT. Hartwin Peelaers Materials Dept, University of California, Santa Barbara, CA 93106-5050 Date submitted: 28 Nov 2012 Electronic form version 1.4
Student Visual Thinking in Solving Realistic Problems: The Case of Arithmetic Sequence

Visual spatial, a representation of mental in depicting visual information, has a positive relation with student ability in processing mathematics information. In this research, we aimed to know student visualization in solving realistic problem. A total of participant involved in this research was 27 junior high school students at grade eight. There were three steps in this research. First, we gave two problems to all of students. We chose the problems from the Programme for International Student Assessment (PISA) 2009. Next, we interviewed five of the students. Finally, we analyzed student visualization from the test and the interview. We found three types of student visualization in this research that were concrete imagery, pattern imagery, and memory image of formulae. Furthermore, we can design the tasks from their visualization. For next research, we suggest to use the assessment test that can assess five types of visualization in solving realistic problem.
Building Extraction from RGB Satellite Images using Deep Learning: A U-Net Approach

Automatic building extraction from satellite RGB images, is a low-cost alternative to perform important urban planning tasks. Yet, it is a challenging one, especially when natural and non-city block objects interfere in the semantic segmentation of algorithms that extract their key features. In this work we approach the automatic building extraction using a Convolution Neural Network based on the U-Net architecture. In contrast to existing approaches, it successfully encodes important features and decodes the buildings’ localization by requiring both reduced computational time and dataset size. We evaluate the U-Net’s performance using RGB images selected from the SpaceNet 1 dataset and the experimental results show an accuracy in building localization of 92.3%. Finally, favorable comparison with existing CNN approaches to hyperspectral images targeting the SpaceNet 1 dataset, demonstrated its effectiveness.
The Relationship of the Test for Respiratory and Asthma Control in Kids Initial Score on the Prognosis of Pre-school Children With Asthma: A Prospective Cohort Study

Objective: The test for respiratory and asthma control in kids (TRACK) is currently the only standard follow-up tool for children under 5 years of age with asthma. The purpose of this study was to investigate the relationship between the TRACK initial score (Ti) and their prognosis after 6 months of follow-up in pre-schoolers with asthma. Design: A prospective cohort study. Methods: The study included pre-schoolers diagnosed with asthma at the Shanghai Children's Medical Center between January 2019 and June 2020, and follow-up for 6 months. TRACK scores, frequency of wheezing and respiratory infections, number of Emergency Department (ED) visits and treatment regimen were collected. According to the TRACK initial score, the children were divided into “Ti < 60 group” and “Ti ≥ 60 group,” and the two groups were compared in terms of TRACK score related indicators, clinical manifestations and treatment. Results: There are 102 pre-schoolers included in the analysis [78 boys (76.5%) and 24 girls (23.5%); mean (SD) age, 28.05 (11.63) months]. After 6 months of follow-up, the TRACK score was improved in both groups, and the “Ti ≥ 60 group” had a higher score, lower rate of uncontrolled asthma and fewer reassessments were required. There was no difference in the number of wheezing attacks between the two groups in terms of clinical presentation, but the “Ti < 60 group” had more respiratory infections and ED visits. Regarding the use of ICSs, in the “Ti < 60 groups,” the dose of ICSs was higher and reduced slowly, and the dose difference between the two groups began to appear after 5 months of follow-up. Conclusion: TRACK is essential for pre-schoolers with asthma at the time they are diagnosed. In addition, if the TRACK initial score is < 60, the probability of poor prognosis is higher.
Ground-State Structures of Hydrated Calcium Ion Clusters From Comprehensive Genetic Algorithm Search

We searched the lowest-energy structures of hydrated calcium ion clusters Ca2+(H2O)n (n = 10–18) in the whole potential energy surface by the comprehensive genetic algorithm (CGA). The lowest-energy structures of Ca2+(H2O)10–12 clusters show that Ca2+ is always surrounded by six H2O molecules in the first shell. The number of first-shell water molecules changes from six to eight at n = 12. In the range of n = 12–18, the number of first-shell water molecules fluctuates between seven and eight, meaning that the cluster could pack the water molecules in the outer shell even though the inner shell is not full. Meanwhile, the number of water molecules in the second shell and the total hydrogen bonds increase with an increase in the cluster size. The distance between Ca2+ and the adjacent water molecules increases, while the average adjacent O-O distance decreases as the cluster size increases, indicating that the interaction between Ca2+ and the adjacent water molecules becomes weaker and the interaction between water molecules becomes stronger. The interaction energy and natural bond orbital results show that the interaction between Ca2+ and the water molecules is mainly derived from the interaction between Ca2+ and the adjacent water molecules. The charge transfer from the lone pair electron orbital of adjacent oxygen atoms to the empty orbital of Ca2+ plays a leading role in the interaction between Ca2+ and water molecules.
Temporal Ordering of Inflammatory Analytes sTNFR2 and sTREM2 in Relation to Alzheimer's Disease Biomarkers and Clinical Outcomes

Inflammatory changes are among the key markers of Alzheimer's disease (AD) related pathological changes. Pro-inflammatory analytes have been related to cognitive decline while others have been related to attenuating neuronal death. Among them, changes in cerebrospinal fluid (CSF) levels of soluble triggering receptor expressed on myeloid cells 2 (sTREM2) and soluble tumor necrosis factor receptor 2 (sTNFR2) have been described as impacting favorable clinical outcomes in AD. We therefore evaluate the effect of CSF sTREM2 and sTNFR2 when taken together on AD biomarkers and longitudinal clinical decline to understand their relative role on impacting AD clinical biomarkers and subsequent clinical outcomes. This longitudinal observational cohort study included 168 amyloid-positive (A+) and p-tau-positive (T+) participants with mild cognitive impairment (MCI) or AD dementia from the Alzheimer's Disease Neuroimaging Initiative (ADNI) with 109 of them having concomitant CSF sTREM2 and sTNFR2 data and 48 A+ T+ participants with MCI from a tertiary memory clinic cohort. An exploratory analysis was performed using data from 86 cognitively normal (CN) participants from ADNI with 72 of them having concomitant CSF AD biomarkers and CSF sTREM2 and sTNFR2 data. General linear models were used to evaluate the effect of sTREM2 and sTNFR2 levels on baseline CSF Aβ42, t-tau, and p-tau, and a linear mixed-effects model was used to assess longitudinal cognitive change after controlling for well-known covariates. Among ADNI A+ T+ MCI and AD dementia participants, CSF sTNFR2 had a stronger association, than CSF sTREM2, with CSF t-tau and p-tau. This was replicated among A+ T+ MCI participants from the memory clinic cohort. On the contrary, among A+ T+ CN participants, CSF sTREM2 explained significant variance in CSF t-tau and p-tau, while CSF sTNFR2 did not. When the effects of CSF sTNFR2 and t-tau on longitudinal cognitive change were taken into account, higher CSF sTREM2 predicted slower cognitive decline in A+ T+ AD dementia participants and faster decline in A+ T+ CN participants. Our results show that given the dynamic changes in sTREM2 and sTNFR2, the clinical impact of these distinct inflammation related biomarkers in tracking AD temporal progression across disease stages are likely to differ.
Widely Different Correlation Patterns Between Pairs of Adjacent Thalamic Neurons In vivo

We have previously reported different spike firing correlation patterns among pairs of adjacent pyramidal neurons within the same layer of S1 cortex in vivo, which was argued to suggest that acquired synaptic weight modifications would tend to differentiate adjacent cortical neurons despite them having access to near-identical afferent inputs. Here we made simultaneous single-electrode loose patch-clamp recordings from 14 pairs of adjacent neurons in the lateral thalamus of the ketamine-xylazine anesthetized rat in vivo to study the correlation patterns in their spike firing. As the synapses on thalamic neurons are dominated by a high number of low weight cortical inputs, which would be expected to be shared for two adjacent neurons, and as far as thalamic neurons have homogenous membrane physiology and spike generation, they would be expected to have overall similar spike firing and therefore also correlation patterns. However, we find that across a variety of thalamic nuclei the correlation patterns between pairs of adjacent thalamic neurons vary widely. The findings suggest that the connectivity and cellular physiology of the thalamocortical circuitry, in contrast to what would be expected from a straightforward interpretation of corticothalamic maps and uniform intrinsic cellular neurophysiology, has been shaped by learning to the extent that each pair of thalamic neuron has a unique relationship in their spike firing activity.
Metabolomics Analysis in Different Development Stages on SP0 Generation of Rice Seeds After Spaceflight

Spaceflight is a special abiotic stress condition. In recent years, it has been confirmed that the spaceflight caused the stress response of rice seeds, and the protein level, transcription level, and methylation level will change during the planting process after returning to the ground. However, the changes at the metabolome level are not very clear. In this study, two kinds of rice seeds, Dongnong423 (DN3) and Dongnong416 (DN6), were carried on the ShiJian-10 retractable satellite (SJ-10) for 12.5 days in orbit, returned to the ground and planted in the field until the three-leaf (TLP) and tillering stage (TS). The results of antioxidant enzyme activity, soluble sugar, and electron leakage rate revealed that the spaceflight caused the stress response of rice. The TLP and TS of DN3 identified 110 and 57 different metabolites, respectively, while the TLP and TS of DN6 identified 104 and 74 different metabolites, respectively. These metabolites included amino acids, sugars, fatty acids, organic acids and secondary metabolites. We used qRT-PCR technology to explore the changes of enzyme genes in the tricarboxylic acid cycle (TCA) and amino acid metabolism pathway. Combined with the results of metabolomics, we determined that during the TLP, the TCA cycle rate of DN3 was inhibited and amino acid metabolism was activated, while the TCA cycle rate of DN6 was activated and amino acid metabolism was inhibited. In TS, the TCA cycle rate of DN3 was inhibited, and amino acid metabolism was not significantly changed, while the TCA cycle rate of DN6 was activated and amino acid metabolism was inhibited. These results suggested that the response mechanisms of the two different rice strains to spaceflight stress are different, and these differences may be reflected in energy consumption and compound biosynthesis of rice in different growth and development stages. This study provided new insights for further exploring the effects of spaceflight.
Virtual Reality in Fibromyalgia: Does Altering Visual Feedback Impact on Pain and Movement During Reaching?

People with fibromyalgia (FM) have movement-related fear impacting on daily activities. While virtual reality has been used as a distractor to promote exercise, it can be used to manipulate visual feedback (VF) about movement, potentially influencing pain and movement. Objectives: A. To determine whether altered VF modulates pain during movement; B. To compare adaptation to an altered VF between FM participants and healthy controls (HC); C. To explore relationships between adaptation, limb position sense, kinesiophobia and pain. 20 FM participants and 20 HC performed a reaching task during two sessions in a KINARM exoskeleton including a virtual reality interface allowing to replace their arm with a virtual arm. In one session, VF was altered to show GREATER movements while in the other it showed SMALLER movements (randomized order). Pain was assessed periodically using a numerical rating scale. Movement amplitude was assessed during exposure to altered VF (adaptation) and pre-/post-exposure (without VF; after-effects). Limb position sense was assessed with a KINARM task, and kinesiophobia was assessed with the Tampa Scale for Kinesiophobia (TSK-11). Pain intensity increased slightly with movement repetitions (p < 0.001), but did not differ between the VF conditions (GREATER vs. SMALLER). Both groups exhibited visuomotor adaptation, as shown by VF-dependent changes in movement amplitude and speed during exposure to altered VF, and by the presence of VF-dependent after-effects (p < 0.001 for all variables). However, no differences were observed across groups for any of these variables, despite the fact that FM had significantly more difficulty to correctly detect VF conditions than HC (p = 0.046). No clear limb position sense deficits were observed in FM participants, and no significant relationships were found between TSK-11 scores and changes in pain intensity during exposure to altered VF. Altering VF did not influence pain during a reaching task in the FM group. Surprisingly, both groups adapted similarly to altered VF. Visuomotor adaptation is therefore preserved in FM, despite impairments in sensory perception and the poor ability to detect VF alterations in the present study. Further research is warranted to clarify the relationship between sensory perceptions and motor control in FM.
Functional Limitations and Perceived Neighborhood Walkability Among Urban Dwelling Older Adults

Older adults with functional limitations (FLs) often experience obstacles to walking. Although health promotion programs targeting physical activity are available in lower-income areas, few studies have compared the walking experiences of older adults who have FLs with those who do not in the community. The purpose of this cross-sectional survey was to compare perceptions of neighborhood walkability among older adults living in lower-income communities with and without FLs. Participants (N = 132) were recruited in 2018 at regional health clinics in Flint, Michigan. To be eligible, participants had to be 65 years of age or older, report no cognitive decline, and be Flint residents. Of the 132 participants, the mean age was 69.74 (SD = 4.97). The majority were female (66%); African American (77%); single, divorced, or widowed (72%); educated below the General Education Development level (57%), and had a FL (67%). Older adults with FLs were significantly (p < 0.05) less likely than those without to visit many places within walking distance, to have well-lit neighborhoods at night, and to reside in neighborhoods where sidewalks were separated from the road and traffic. Multiple regression analyses revealed that having a FL was associated with poorer neighborhood perceptions of mixed-land-use (b = −0.19, p < 0.05) and more walking hazards (b = −0.26, p < 0.05). Findings suggest that a FL is associated with perceptions of walkability. It is essential to develop disability-friendly support systems and accommodations to encourage walking in lower-income communities.