Visualization 1: Heart structural remodeling in a mouse model of Duchenne cardiomyopathy revealed using optical polarization tractography [Invited]

3D intensity view of a BL6 heart Originally published in Biomedical Optics Express on 01 March 2017 (boe-8-3-1271

Economic Indicators July 2002

This publication presents basic statistics data about economic condition in Indonesia. It contains statistics on economics and finance such as consumer price index, whose sale price index, foreign currency, and banking, investment, agriculture products, mining and quarrying products balance of payments, exports and imports, consumption, hotel and tourism, and national income. Specially in each January edition, it present data of Indonesian population. Previously, this monthly publication is called Statistics Conjuncture (January 1950-July/August 1963)

AUXIN RESPONSE FACTOR3 plays distinct role during early flower development

<p>AUXIN RESPONSE FACTOR3 (ARF3), one of the auxin response factors family of transcription factors, is well characterized by its functions in polarity identification and organ patterning. We recently demonstrated that ARF3 plays important roles in floral meristem (FM) maintenance and termination by regulating cytokinin biosynthesis and signaling. However, the relationship of its multiple roles in differently developmental stage is still unclear. Here, we present data that ARF3 plays distinct roles during early flower development that are different from its roles in organ polarity determination and pattering. Thus, our findings shed light on the functional diversity of one specific transcription factor in plant development.</p

Characterizing Spatial Patterns of Airborne Coarse Particulate (PM10–2.5) Mass and Chemical Components in Three Cities: The Multi-Ethnic Study of Atherosclerosis

Background: The long-term health effects of coarse particular matter (PM10–2.5) are challenging to assess because of a limited understanding of the spatial variation in PM10–2.5 mass and its chemical components. Objectives: We conducted a spatially intensive field study and developed spatial prediction models for PM10–2.5 mass and four selected species (copper, zinc, phosphorus, and silicon) in three American cities. Methods: PM10–2.5 snapshot campaigns were conducted in Chicago, Illinois; St. Paul, Minnesota; and Winston-Salem, North Carolina, in 2009 for the Multi-Ethnic Study of Atherosclerosis and Coarse Airborne Particulate Matter (MESA Coarse). In each city, samples were collected simultaneously outside the homes of approximately 40 participants over 2 weeks in the winter and/or summer. City-specific and combined prediction models were developed using land use regression (LUR) and universal kriging (UK). Model performance was evaluated by cross-validation (CV). Results: PM10–2.5 mass and species varied within and between cities in a manner that was predictable by geographic covariates. City-specific LUR models generally performed well for total mass (CV R2, 0.41–0.68), copper (CV R2, 0.51–0.86), phosphorus (CV R2, 0.50–0.76), silicon (CV R2, 0.48–0.93), and zinc (CV R2, 0.36–0.73). Models pooled across all cities inconsistently captured within-city variability. Little difference was observed between the performance of LUR and UK models in predicting concentrations. Conclusions: Characterization of fine-scale spatial variability of these often heterogeneous pollutants using geographic covariates should reduce exposure misclassification and increase the power of epidemiological studies investigating the long-term health impacts of PM10–2.5. Citation: Zhang K, Larson TV, Gassett A, Szpiro AA, Daviglus M, Burke GL, Kaufman JD, Adar SD. 2014. Characterizing spatial patterns of airborne coarse particulate (PM10–2.5) mass and chemical components in three cities: the Multi-Ethnic Study of Atherosclerosis. Environ Health Perspect 122:823–830; http://dx.doi.org/10.1289/ehp.130728

Biological soil crusts: An eco-adaptive biological conservative mechanism and implications for ecological restoration

<div><p>Biological soil crusts (BSCs) are highly complex associations of soil particles with mosses, cyanobacteria, lichens, bacteria, and fungi. BSCs affect many ecological processes, including infiltration and evaporation, soil erosion, vegetation succession, and nutrient cycling, and perform important ecological functions of ecosystems in arid areas. In the past 30 years, many studies on BSCs were conducted by researchers all over the world. This paper reviews the recent research progresses and frontier problems, and discusses the current controversial conclusions. The main ideas are as follows: (1) influenced by many macroclimate and micro-environment factors, BSCs are characterized by developmental complexity, composition diversity, and spatial heterogeneity. In any typical areas where exist all types of BSCs at different succession stages, it is of great significance to conduct comparable studies on BSCs and to explore if there exists a probable zonality for them. (2) BSCs not only exert positive impacts on soil fertility and soil erosion, but they also show controversial influences on the hydrological processes, especially on infiltration, evaporation, soil moisture, and vegetation succession such as survival, germination, emergence, and establishment. To understand the function-performing mechanisms of BSCs is helpful for the revealing of their action patterns and the comprehension of the implications of the patterns on ecological processes and restoration as well as clarification of existing controversial points. It will eventually contribute to the effective management and utilization of BSCs resources in a given region for large-scale ecological engineering.</p></div

Incorporating conditional random fields and active learning to improve sentiment identification.

Many machine learning, statistical, and computational linguistic methods have been developed to identify sentiment of sentences in documents, yielding promising results. However, most of state-of-the-art methods focus on individual sentences and ignore the impact of context on the meaning of a sentence. In this paper, we propose a method based on conditional random fields to incorporate sentence structure and context information in addition to syntactic information for improving sentiment identification. We also investigate how human interaction affects the accuracy of sentiment labeling using limited training data. We propose and evaluate two different active learning strategies for labeling sentiment data. Our experiments with the proposed approach demonstrate a 5%-15% improvement in accuracy on Amazon customer reviews compared to existing supervised learning and rule-based methods

Hydrogen Adsorption in Metal-Organic Framework MIL-101(Cr) - Adsorbate Densities and Enthalpies from Sorption, Neutron Scattering, in Situ X-ray Diffraction, Calorimetry, and Molecular Simulations

In this paper, hydrogen adsorption in metal-organic framework MIL-101(Cr) is investigated through a combination of sorption experiments, modeling of experimental isotherms, differential scanning calorimetry (DSC), neutron scattering, in situ synchrotron powder X-ray diffraction, and molecular simulations. The molecular simulations at 77 K for H2 adsorption in the material show excellent correspondence with excess uptakes determined from experimental isotherms. The simulations also indicate that H2 adsorption at a low pressure is mainly located in the 0.7 nm supertetrahedron and that, with increasing pressure, H2 starts to accumulate in the small (2.9 nm) and large (3.4 nm) cages. The inelastic neutron scattering results show that, in contrast to reports for hydrogen adsorption under the same conditions for microporous carbons, there is no solid-like H2 or any higher density H2 phases adsorbed in the pores of MIL-101(Cr). This indicates that, with increasing pressures, the adsorbed density of the MIL-101(Cr) remains constant but the volume of adsorbate increases and that higher densities for adsorbed hydrogen require pore sizes smaller than 0.7 nm, which is the size of the smallest pore in MIL-101(Cr). The enthalpies of adsorption are also investigated for this material using simulations, the Clapeyron equation applied to the isosteres and DSC, with the direct calorimetric method showing good agreement at zero coverage with the other two methods. The simulations and the Clapeyron equation are also in good agreement up to 6 wt % coverage. © 2021 American Chemical Society. All rights reserved.</p

How Do Metal/Graphene Self-Assemble into Core−Shelled Composite Nanostructures?

Molecular dynamics (MD) simulations were carried out to study the self-assembly of graphene and metallic particle. The metallic particle can help the graphene overcome the energy barrier, which leads to rapid self-scrolling of flat graphene and the formation of stable core−shelled composite nanostructure. The van der Waals interaction plays an important role in the self-assembly. The chirality of the graphene does not affect the self-scrolling process, which thus provides a simple way of controlling the chiralities and the physical properties of the resulting conformations. This work opens new and exciting possibilities for the fabrication of metal/carbon core−shelled composite nanostructures through the self-scrolling of graphene

Genome-wide association study for reproduction-related traits in Chinese domestic goose

1. This study measured six reproduction traits in a Sichuan white goose population (209 individuals), including fertility, qualified egg rate, plasma concentrations of progesterone (P), follicle-stimulating hormone (FSH), prolactin (PRL) and oestrogen (E2). 2. Whole-genome resequencing data from the same goose population (209 individuals) were used in a genome-wide association study (GWAS) utilising a mixed linear model to investigate the genes and genetic markers associated with reproduction traits. The frequency of the selected SNPs and haplotypes were determined using the Matrix-Assisted Laser Desorption Ionisation Time-Of-Flight Mass Spectrometry (MALDI-TOF MS) method. 3. In total, 42 SNPs significantly associated with these traits were identified. A haplotype block was constructed based on five SNPs that were significantly associated with qualified egg rate, with individuals having the haplotype CCTTAAGGAA having the lowest qualified egg rate. 4. In conclusion, these results provided potential markers for marker-assisted selection to improve goose reproductive performance and a basis for elucidating the genetics of goose reproduction.</p

Smart Nanofibers from Combined Living Radical Polymerization, “Click Chemistry”, and Electrospinning

A simple method for preparing solvent-resistant nanofibers with a thermal-sensitive surface has been developed by the combined technology of reversible addition-fragmentation chain-transfer (RAFT) polymerization, atom transfer radical polymerization (ATRP), electrospinning, and “click chemistry”. Initially, well-defined block copolymers of 4-vinylbenzyl chloride (VBC) and glycidyl methacrylate (GMA) (PVBC-b-PGMA) were prepared via RAFT polymerization. Electrospinning of PVBC-b-PGMA from a solution in tetrahydrofuran gave rise to fibers with diameters in the range of 0.4−1.5 μm. Exposure to a solution of sodium azide (NaN3) not only affords nanofibers with azido groups on the surface but also leads to a cross-linking structure in the nanofibers. One more step of “click chemistry” between the PVBC-b-PGMA nanofibers with azido groups on the surface (PVBC-b-PGMA−N3) and alkyne-terminated polymers of N-isopropylacrylamide (NIPAM) (PNIPAMAT), which were prepared by ATRP, allows the preparation of a PVBC-b-PGMA nanofiber with thermal-sensitive PNIPAM brushes on the surface (PVBC-b-PGMA-g-PNIPAM). PVBC-b-PGMA-g-PNIPAM nanofibers exhibit a good resistance to solvents and thermal-responsive character to the environment, having a hydrophobic surface at 45 °C (water contact angle ∼140°) and having a hydrophilic surface at 20 °C (water contact angle ∼30°)