Miracle-dz/UniFAR-FTUs huggingface dataset:
A Mixed-methods Approach to Understanding the Perspectives, Experiences and Attitudes of Cognitive Behavioral Therapy for African American Patients with Type-2 Diabetes: A Randomized Parallel Design Pilot Study

BackgroundAfrican American (AA) adults are 60% more likely to be diagnosed with diabetes mellitus (DM) and experience more complications than non-Hispanic White adults. Cognitive behavioral therapy (CBT) is a technique that combines traditional care with cognitive and psychosocial techniques. We aimed to assess the effects of CBT integrated with motivational interviewing (MI) on glycemic control in AA participants and understand their perspectives, attitudes, and experiences toward CBT. MethodsUsing a randomized, parallel design pilot study (web-based group vs in-person group), 20 participants aged >18 years, identifying as AA, and having a glycosylated hemoglobin (HbA1c) > 8%, were recruited. CBT was administered in six sessions over three months. Participants completed baseline and follow-up assessments on measures for diabetes control (HbA1c), self-efficacy, generalized anxiety, depression, perceived stress, health-related quality of life and cognitive ability. Post-CBT focus groups were conducted to determine patient perspectives regarding the intervention. ResultsFourteen participants completed the study, their mean HbA1c improved from 8.5% to 7.7%. The Diabetes Distress Scale demonstrated decreased distress overall (t(26)=2.6; p- value=0.02). The Generalized Anxiety Disorder Scale demonstrated decreased generalized anxiety for all participants (t(26)=2.2; p =0.04). Themes identified in focus groups included: (1) intervention group social support through information sharing; (2) mental health and personal identities in diabetes understanding and management; (3) receptivity to CBT/MI Intervention positively impacts self-efficacy through improved health literacy. ConclusionGroup-based CBT intervention for type 2 DM care was positively received by AA participants and helped improve diabetes control, as demonstrated by the change in HbA1c. There were additional benefits of social support through group interactions and a stronger sense of self-efficacy due to health education. A comprehensive treatment plan like CBT, may be useful in promoting healthy diabetes self-management.Trial registrationThis trial is registered at ClinicalTrials.gov with the identifier NCT03562767. 70 Registered 19 June 2018, https://clinicaltrials.gov/ct2/show/NCT03562767? term=NCT03562767&draw=2&rank=1
European Vintage tomatoes galore: a result of farmers combinatorial assorting/swapping of a few diversity rich loci

A comprehensive collection of 1,254 tomato accessions corresponding to European heirlooms and landraces, together with modern varieties, early domesticates and wild relatives, were analyzed by genotyping by sequencing. A continuous genetic gradient between the vintage and modern varieties was observed. European vintage tomatoes displayed very low genetic diversity, with only 298 loci out of 64,943 variants being polymorphic at the 95% threshold. European vintage tomatoes could be classified in several genetic groups. Two main clusters consisting of Spanish and Italian accessions showed a higher genetic diversity than the rest varieties, suggesting that these regions might be independent secondary centers of diversity and with a different history. Other varieties seem to be the result of a more recent complex pattern of migrations and hybridizations among the European regions. Several polymorphic loci were associated in a GWAS with fruit morphological traits in the European vintage collection, and the corresponding alleles were found to contribute to the distinctive phenotypic characteristic of the genetic varietal groups. The few highly polymorphic loci associated with morphological traits in an otherwise diversity-poor genome suggests a history of balancing selection, in which tomato farmers maintained the morphological variation by applying a high selective pressure within different varietal types. Highlight The high phenotypic diversity observed among European vintage varieties was created by traditional farmers by combining very few polymorphic loci subjected to balancing selection.
A Mixed Methods Case Study of Food Shopping in a Community with High Infant Mortality

In the U.S., preterm birth disproportionately impacts certain racial/ethnic groups, with Black women experiencing preterm birth at a rate 50% higher than other groups. Among the numerous factors that likely contribute to these increased rates are neighborhood characteristics, such as food environment. In this mixed-methods case study, we evaluated how pregnant women living in a predominately minority, lower income community with high preterm birth rates navigate and perceive their food environment. Qualitative interviews were performed to assess perceptions of food environment (n = 7) along with geographic and observational assessments of their food environment. Participants traveled an average of 2.10 miles (SD = 1.16) and shopped at an average of 3 stores. They emphasized the importance of pricing and convenience when considering where to shop and asserted that they sought out healthier foods they thought would enhance their pregnancy health. Observational assessments of stores’ nutrition environment showed that stores with lower nutritional scores were in neighborhoods with greater poverty and a higher percent Black population. Future policies and programmatic efforts should focus on improving nutrition during pregnancy for women living in communities with high rates of poor birth outcomes. Availability, affordability, and accessibility are key aspects of the food environment to consider when attempting to achieve birth equity.
Closed-Form Pseudolinear Estimators for DRSS-AOA Localization

This paper investigates the hybrid source localization problem using differential received signal strength (DRSS) and angle of arrival (AOA) measurements. The main advantage of hybrid measurements is to improve the localization accuracy with respect to a single sensor modality. For sufficiently short wavelengths, AOA sensors can be constructed with size, weight, power and cost (SWAP-C) requirements in mind, making the proposed hybrid DRSS-AOA sensing feasible at a low cost. Firstly the maximum likelihood estimation solution is derived, which is computationally expensive and likely to become unstable for large noise levels. Then a novel closed-form pseudolinear estimation method is developed by incorporating the AOA measurements into a linearized form of DRSS equations. This method eliminates the nuisance parameter associated with linearized DRSS equations, hence improving the estimation performance. The estimation bias arising from the injection of measurement noise into the pseudolinear data matrix is examined. The method of instrumental variables is employed to reduce this bias. As the performance of the resulting weighted instrumental variable (WIV) estimator depends on the correlation between the IV matrix and data matrix, a selected-hybrid-measurement WIV (SHM-WIV) estimator is proposed to maintain a strong correlation. The superior bias and mean-squared error performance of the new SHM-WIV estimator is illustrated with simulation examples.
Coronary Artery Dimensions in Endurance Athletes by Computed Tomography Angiography: A Quantitative Analysis

(1) Background: The athlete’s heart may develop permanent vessel enlargement. The purpose of our study was to define normal values for coronary artery dimensions of endurance athletes by coronary computed tomography angiography (CTA). (2) Methods: Ninety-eight individuals (56.2 ± 11 years) were included into this retrospective matched case-controlled-study. Endurance athletes had regular training volumes of ≥1 h per unit, ≥3–7 times per week (either cycling, running or mountain-endurance). Athletes were matched for age and gender with sedentary controls using propensity score. Quantitative CTA analysis included coronary vessel dimensions (two diameters and area) of the LM, LAD, CX and RCA for all AHA-16-segments. (3) Results: Proximal LAD area and diameter (p = 0.019); proximal/mid CX (diameter and area; p = 0.026 and p = 0.018/p = 0.008 and p = 0.009); mid RCA diameter and area; and proximal RCA diameter were significantly larger in endurance athletes (p < 0.05). The left main area (p = 0.708) and diameter (p = 0.809) as well as the mid LAD and distal segments were not different. We present the histograms and data for normal values ±1 and ± 2 SD. (4) Conclusions: Endurance athletes have larger proximal LAD, proximal/mid CX and RCA vessel dimensions, while LM and distal segments are similar. Hence, dilated coronary arteries in endurance athletes (“Athlete’s arteries”) have to be distinguished from diffuse ectatic segments developing during Kawasaki disease or multisystemic inflammation syndrome after COVID-19.
RCX—an R package adapting the Cytoscape Exchange format for biological networks

Motivation The Cytoscape Exchange (CX) format is a JSON-based data structure designed for the transmission of biological networks using standard web technologies. It was developed by the network data exchange (NDEx), which itself serves as online commons to share and collaborate on biological networks. Furthermore, the Cytoscape software for the analysis and visualization of biological networks contributes structure elements to capture the visual layout within the CX format. However, there is a fundamental difference between data handling in web standards and R. A manual conversion requires detailed knowledge of the CX format to reproduce and work with the networks. Results Here we present a software package to create, handle, validate, visualize and convert networks in CX format to standard data types and objects within R. Networks in this format can serve as a source for biological knowledge, and also capture the results of the analysis of those while preserving the visual layout across all platforms. The RCX package connects the R environment for statistical computing with outside platforms for storage and collaboration, as well as further analysis and visualization of biological networks. Availability RCX is a free and open-source R package, available on Bioconductor from release 3.15 (https://bioconductor.org/packages/RCX) and via GitHub (https://github.com/frankkramer-lab/RCX). Contact florian.auer@informatik.uni-augsburg.de Supplementary information Supplementary data are available at Bioinformatics Advances online.
Novelty of Lithium Salt Solution in Sulfone and Dimethyl Carbonate-Based Electrolytes for Lithium-Ion Batteries: A Classical Molecular Dynamics Simulation Study of Optimal Ion Diffusion

The reduction in the usage of fossil fuel can be achieved by focusing on development of high-energy storage battery. Recently, tetramethylene sulfone (TMS) based electrolytes have become the center of attraction for Li-ion battery due to its high electrochemical and thermal stability. Our work uncovers the novel effect of adding dimethyl carbonate (DMC) to the mixture of TMS with LiPF6 solvent having different molar ratios of individual constituent by the classical Molecular Dynamics simulations. We calculated composite electrolyte properties such as solvation structures, diffusion coefficients, ionic conductivities and found that the coordination between Li+ and PF6- is least for DMC/TMS ratio of (1:2); because Li ions are found to be more coordinated with TMS molecules, which provides better structural stability to the system. Moreover, the transport properties of this system illustrate that the diffusion of ions is not so encouraging. But, while taking differ-ent concentrations of LiPF6 with the same molecular ratio of DMC/TMS, it was found that Li+ and PF6- have more diffusion coeffi-cient and ionic conductivities with the salt/solvent molar ratio of 1:20. However, due to strong interactions of Li-F, we propose a salt-solvent ratio of 1:12 as an appropriate choice based on optimal ion diffusion for better battery performance.
Notes on the genus Dendrocerus Ratzeburg (Hymenoptera, Megaspilidae) from China, with description of two new species

Species of the genus Dendrocerus Ratzeburg, 1852 (Hymenoptera: Megaspilidae) from China were studied. Six species are recorded, of which two known species, D. carpenteri (Curtis, 1829) and D. laticeps (Hedicke, 1929) are re-described; and two species are described as new to science, D. anisodontus Wang, Chen and Mikó sp. nov. and D. bellus Wang, Chen and Mikó sp. nov. Sequences of the 28S rDNA were generated to associate both sexes of the same species.
Veterinarians and Wildlife Biologists Should Join Forces to End Inhumane Mammal Trapping Technology

Current mammal trapping standards uphold the use of inhumane trapping technology. For example, killing neck snares for the capture of canids, and rotating-jaw traps, and steel-jawed leghold traps for procyonids and mustelids, are being used by trappers despite decades of research showing that they are inhumane, and cause serious injuries and distress in captured animals. Many wildlife biologists unsuccessfully raised concerns about inhumane mammal trappings. This short communication stresses the need for veterinarians and wildlife biologists to work together to improve the fate of mammals captured in killing or restraining traps, and modify mammal trapping standards on the basis of animal welfare science.
Antenatal care in Mozambique: Number of visits and gestational age at the beginning of antenatal care

Objective: 1)to assess the gestational age at the beginning of antenatal care and its covariates; 2)to assess the number of antenatal visits and its covariates; and 3)to identify the reasons for the late initiation of antenatal care and for attending less than four visits among postpartum women living in Nampula, Mozambique. Method: cross-sectional study conducted with 393 mothers who answered a structured instrument in face-to-face interviews. Logistic regression was used to analyze the covariates of having initiated antenatal care up to the 16thgestational week, having attended four or more antenatal visits, and reporting both situations simultaneously. Results: all postpartum women underwent antenatal care, but only 39.9% started it until the 16thgestational week, 49.1% attended four or more visits, and 34.1% reported both events. Having concluded high school (ORadj=1.99; 95%CI=1.19-3.31) or college (ORadj=3.87; 95%CI=1.47-10.18) were aspects associated with reporting both situations. The reasons for the late initiation of antenatal care and attending less than four visits were as follows: not finding it important to attend several visits, not having easy access to the health facility, not being aware about pregnancy, and not having a companion for the visits. Conclusion: the gestational age at the beginning of antenatal care and the number of antenatal visits are lower than the current recommendations in the country.
3-D blade resolved CFD performance analysis of a Ducted Wind Turbine

Ducted wind turbines are very promising wind energy concentrator-systems for smallscale applications exhibiting an appreciable power density increase compared with their open rotor competitors. The aim of this work is to build up a robust and automated methodology for the 3D blade-resolved performance analysis of these devices in view of their CFD-aided optimal design. The reliability of this procedure, based on an in-house Python module for the generation of the structured multi-block 3D mesh, is verified by comparing the obtained numerical results with available experimental data. The developed methodology is employed to spotlight the differences in terms of extracted power between open and ducted rotors and to investigate some typically-disregarded aspects playing a key role in the design and analysis of ducted wind turbines. Specifically, it is shown that the shrouding of an existing open rotor leads to a sub-optimal turbine operating condition as well as to a significantly change in the local features of the tip vortex and associated losses.
Multi-pixels Classification for nuclei segmentation in digital pathology based on deep machine learning

The problem this paper solves is identifying the accurate boundary for nuclei in breast cancer digital pathology images. By doing the nuclei segmentation, the output image can be a reference for the doctors to make better diagnosis for breast cancer patients. Using convolutional neural network to solve this problem which is a popular deep learning method for image classification. By generating labelled patches from the original dataset for training and using a sliding window to cut out patches from testing image for classifying pixels in the testing image, the image level classification can be transferred to pixel level classification. A 2x2 receptive field can be classified to 16 classes, and each pixel can be calculated 4 time, which increase the pixel level TPR (true positive rate) from 0.868 to 0.909. And the boundaries are smother than traditional method that the receptive field is 1x1.
Improving Image Filters with Cartesian Genetic Programming

The automatic construction of an image filter is a difficult task for which many recent machine learning methods have been proposed. However, these approaches, such as deep learning, do not allow for the filter to be understood, and they often replace existing filters designed by human engineers without building on this expertise. Genetic improvement offers an alternative approach to construct understandable image filter programs and to build them by improving existing systems. In this paper, we propose a method for genetic improvement of image filters using Cartesian Genetic Programming. We introduce two operators for genetic improvement which allow insertion and deletion of a node in the graph in order to quickly improve a given filter. These new operators are tested in three different datasets starting from published or engineered filters. We show that insertion and deletion operators improve the performance of CGP to produce newly adapted filters.
Multifunctional Nanopolymers for Blood–Brain Barrier Delivery and Inhibition of Glioblastoma Growth through EGFR/EGFRvIII, c-Myc, and PD-1

Glioblastoma (GBM) is the most prevalent primary brain cancer in the pediatric and adult population. It is known as an untreatable tumor in urgent need of new therapeutic approaches. The objective of this work was to develop multifunctional nanomedicines to treat GBM in clinical practice using combination therapy for several targets. We developed multifunctional nanopolymers (MNPs) based on a naturally derived biopolymer, poly(β-L-malic) acid, which are suitable for central nervous system (CNS) treatment. These MNPs contain several anticancer functional moieties with the capacity of crossing the blood–brain barrier (BBB), targeting GBM cells and suppressing two important molecular markers, tyrosine kinase transmembrane receptors EGFR/EGFRvIII and c-Myc nuclear transcription factor. The reproducible syntheses of MNPs where monoclonal antibodies are replaced with AP-2 peptide for effective BBB delivery were presented. The active anticancer inhibitors of mRNA/protein syntheses were Morpholino antisense oligonucleotides (AONs). Two ways of covalent AON-polymer attachments with and without disulfide bonds were explored. These MNPs bearing AONs to EGFR/EGFRvIII and c-Myc, as well as in a combination with the polymer-attached checkpoint inhibitor anti-PD-1 antibody, orchestrated a multi-pronged attack on intracranial mouse GBM to successfully block tumor growth and significantly increase survival of brain tumor-bearing animals.
Nanostructure and phase formation in annealed a-Si 1-x C x :H thin films for advanced silicon solar cells

Motivation Crystalline Silicon (Si) based solar cells are dominating the photovoltaic market and the situation is likely to continue for the next decades. Microelectronic concepts and processes were transferred to high efficiency Si solar cells and as a consequence high efficiencies were achieved. However, the development of high efficiency Si solar cells stagnated in the last years. In microelectronics Si nanocrystals (NCs) have been a subject of research for more than 15 years. Periodically aligned Si NCs in a dielectric matrix are a promising material for the application as an upper cell of a Si based tandem solar cell to realize very high efficiency solar cells. Recent modelling showed that a high density of Si nanocrystals within a SiC matrix has the highest potential, compared to SiO2 or Si3N4, as a Si quantum dot absorber material [1]. To fabricate a Si quantum dot material by Plasma enhanced Chemical Vapour Deposition (PECVD) two different methods can be used: On the one hand a single layer approach, where the size of Si NCs is only controlled by the annealing conditions or a multilayer approach as proposed by Zacharias aiming at the control of the Si NCs by a stoichiometric diffusion barrier [2]. The emphasis in this paper is placed on the single layer approach.
Bridging the information and dynamics attributes of neural activities

The brain works as a dynamic system to process information. Various challenges remain in understanding the connection between information and dynamics attributes in the brain. The present research pursues exploring how the characteristics of neural information functions are linked to neural dynamics. We attempt to bridge dynamics (e.g., Kolmogorov-Sinai entropy) and information (e.g., mutual information and Fisher information) metrics on the stimulus-triggered stochastic dynamics in neural populations. On the one hand, our uniﬁed analysis identiﬁes various essential features of the information-processing-related neural dynamics. We discover spatiotemporal diﬀerences in the dynamic randomness and chaotic degrees of neural dynamics during neural information processing. On the other hand, our framework reveals the fundamental role of neural dynamics in shaping neural information processing. The neural dynamics creates an oppositely directed variation of encoding and decoding properties under speciﬁc conditions, and it determines the neural representation of stimulus distribution. Overall, our ﬁndings demonstrate a potential direction to explain the emergence of neural information processing from neural dynamics and help understand the intrinsic connections between the informational and the physical brain.
Differential regulation of cranial and cardiac neural crest by Serum Response Factor

Serum response factor (SRF) is an essential transcription factor that influences many cellular processes including cell proliferation, migration, and differentiation. SRF directly regulates and is required for immediate early gene (IEG) and actin cytoskeleton-related gene expression. SRF coordinates these competing transcription programs through discrete sets of cofactors, the Ternary Complex Factors (TCFs) and Myocardin Related Transcription Factors (MRTFs). The relative contribution of these two programs to in vivo SRF activity and mutant phenotypes is not fully understood. To study how SRF utilizes its cofactors during development, we generated a knock-in SrfαI allele in mice harboring point mutations that disrupt SRF-MRTF-DNA complex formation but leave SRF-TCF activity unaffected. Homozygous SrfαI/αI mutants die at E10.5 with notable cardiovascular phenotypes, and neural crest conditional mutants succumb at birth to defects of the cardiac outflow tract but display none of the craniofacial phenotypes associated with complete loss of SRF in that lineage. Our studies further support an important role for MRTF mediating SRF function in cardiac neural crest and suggest new mechanisms by which SRF regulates transcription during development.