An Improved Process Based Ammonia Emission Model for Agricultural Sources—Emission Estimates

Ammonia is an important atmospheric pollutant that combines with sulfuric acid and nitric acid to form aerosol sulfates and nitrate, respectively. These aerosol species are major components of fine particulate matter (PM) and contribute significantly to visibility impairment. Estimates of ammonia emission factors are both highly variable and uncertain. Emissions factors vary depending on meteorological conditions and seasonal and regional differences in farming practices. Previous ammonia emissions inventories have not adequately characterized seasonal and geographical variations in emissions factors. Recent chemical transport modeling suggests that daily and hourly variability in ammonia emissions is required to model accurately the formation of ammonium nitrate and ammonium sulfates. In a companion paper, the development of a process-based model for predicting or estimating ammonia emission rates and factors from individual or a group of animal feeding operations at local, regional and national levels was presented. This paper discusses the data requirements and implementation of the process-based ammonia emission model. Preliminary emission estimates developed from the process-based ammonia emission model are also presented. Detailed description of databases used as input values for the process-developed model and recommendations for future improvement on the farm-based data regarding the animal feeding and manure management practices are documented. Where available, comparisons of the new ammonia emission estimates with existing ammonia emission inventories for livestock farms at a local, regional and national level are presented. The work presented here is sponsored and funded by the Lake Michigan Air Directors Consortium (LADCO)

Homozygous p.Ser267Phe in SLC10A1 is associated with a new type of hypercholanemia and implications for personalized medicine.

SLC10A1 codes for the sodium-taurocholate cotransporting polypeptide (NTCP), which is a hepatocellular transporter for bile acids (BAs) and the receptor for hepatitis B and D viruses. NTCP is also a target of multiple drugs. We aimed to evaluate the medical consequences of the loss of function mutation p.Ser267Phe in SLC10A1. We identified eight individuals with homozygous p.Ser267Phe mutation in SLC10A1 and followed up for 8-90 months. We compared their total serum BAs and 6 species of BAs with 170 wild-type and 107 heterozygous healthy individuals. We performed in-depth medical examinations and exome sequencing in the homozygous individuals. All homozygous individuals had persistent hypercholanemia (P = 5.8 × 10-29). Exome sequencing excluded the involvement of other BA metabolism-associated genes in the hypercholanemia. Although asymptomatic, all individuals had low vitamin D levels. Of six adults that were subjected to bone mineral density analysis, three presented with osteoporosis/osteopenia. Sex hormones and blood lipids were deviated in all subjects. Homozygosity of p.Ser267Phe in SLC10A1 is associated with asymptomatic hypercholanemia. Individuals with homozygous p.Ser267Phe in SLC10A1 are prone to vitamin D deficiency, deviated sex hormones and blood lipids. Surveillance of these parameters may also be needed in patients treated with drugs targeting NTCP.This project is supported by the National Natural Science Foundation of China (31471193, 81570539, 81370535, 91331204 and 31525014). S.X. acknowledges financial support from the Strategic Priority Research Program (XDB13040100) and Key Research Program of Frontier Sciences (QYZDJ-SSW-SYS009) of the Chinese Academy of Sciences (CAS)

Career-Specific Parenting Practices and Career Decision-Making Self-Efficacy Among Chinese Adolescents: The Interactive Effects of Parenting Practices and the Mediating Role of Autonomy

This study examined the unique and interactive effects of various career-specific parenting practices (i.e., parental career support, interference, and lack of engagement) on Chinese high school students’ career decision-making self-efficacy (CDSE) as well as the mediating role of autonomy in such associations. Based on data from 641 Chinese high school students (47.6% male; mean age = 15.28 years old, SD = 0.49) in 2016, two moderated mediating effects were identified. Higher level of parental career engagement strengthened the positive association between parental career support and adolescents’ autonomy, which in turn, was associated positively with adolescents’ CDSE. Parental career interference related negatively with adolescents’ CDSE via autonomy when lack of parental career engagement was low, but related positively with adolescents’ CDSE via autonomy when lack of parental career engagement was high. These findings advance our understanding of the underlying processes between career-specific parenting practices and adolescents’ CDSE. Implications for practices were discussed

FooMinder Refrigerator Detector

Households tend to buy a lot of vegetables, fruits and meat at once and use the refrigerator as a place to store food for a long time. Fruits and vegetables stored in the refrigerator for a long time are likely to lose their nutritive value while at the same time, fruits and vegetables stored in the refrigerator are easily forgotten and start to deteriorate. If we can reduce such food waste, we are able to save money on buying groceries and moreover help accomplish the world’s sustainable goal. FooMinder is designed to consist of a mobile application and a fridge detector. In this modern world, people rely on technology products, such as smartphones, for their daily needs. Apps installed on smartphones are a simple way to keep users engaged. We propose to use image processing to convert images to texts after users scan their receipts. This technique will allow us to generate the grocery lists and set up a reminder to alert users when certain items are going to soon go rotten. To properly store food and analyze data accurately, we have added a dedicated environmental detector to the home refrigerator. We believe this system will be an accurate and effective solution to the problem

Grain size effect on piezoelectric properties of Sr2Nb2O7 ceramics

Grain size effect on piezoelectric properties and thermal stability of perovskite layer structured (PLS) Sr2Nb2O7 ceramics are investigated. The Sr2Nb2O7 ceramics with different average grain sizes from 1.2μm to 3.6μm were prepared in different sintering temperatures by solid state reaction method. The average grain size increases, accompanied by a higher relative density of up to 96%. Pure Sr2Nb2O7 ceramics with larger grain size show a remarkable d33 of (1.7±0.1)pC/N while still with a very high Tc of (1340±4)∘C. The thermal depolarization temperature of samples with large grain sizes reach over 1200∘C and the thermal stability increased with increasing of grain size. The ferroelectric domains structure was observed by PFM and larger grain is easy to form ferroelectric domain then enhance piezoelectric properties. This study demonstrates enhanced piezoelectric properties can be achieved in pure Sr2Nb2O7 by solid state reaction method and bring great revitalization to the Sr2Nb2O7-based ceramics as a promising high-temperature piezoelectric material

Identification of shared pathogenetic mechanisms between COVID-19 and IC through bioinformatics and system biology

Abstract COVID-19 increased global mortality in 2019. Cystitis became a contributing factor in SARS-CoV-2 and COVID-19 complications. The complex molecular links between cystitis and COVID-19 are unclear. This study investigates COVID-19-associated cystitis (CAC) molecular mechanisms and drug candidates using bioinformatics and systems biology. Obtain the gene expression profiles of IC (GSE11783) and COVID-19 (GSE147507) from the Gene Expression Omnibus (GEO) database. Identified the common differentially expressed genes (DEGs) in both IC and COVID-19, and extracted a number of key genes from this group. Subsequently, conduct Gene Ontology (GO) functional enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis on the DEGs. Additionally, design a protein–protein interaction (PPI) network, a transcription factor gene regulatory network, a TF miRNA regulatory network, and a gene disease association network using the DEGs. Identify and extract hub genes from the PPI network. Then construct Nomogram diagnostic prediction models based on the hub genes. The DSigDB database was used to forecast many potential molecular medicines that are associated with common DEGs. Assess the precision of hub genes and Nomogram models in diagnosing IC and COVID-19 by employing Receiver Operating Characteristic (ROC) curves. The IC dataset (GSE57560) and the COVID-19 dataset (GSE171110) were selected to validate the models' diagnostic accuracy. A grand total of 198 DEGs that overlapped were found and chosen for further research. FCER1G, ITGAM, LCP2, LILRB2, MNDA, SPI1, and TYROBP were screened as the hub genes. The Nomogram model, built using the seven hub genes, demonstrates significant utility as a diagnostic prediction model for both IC and COVID-19. Multiple potential molecular medicines associated with common DEGs have been discovered. These pathways, hub genes, and models may provide new perspectives for future research into mechanisms and guide personalised and effective therapeutics for IC patients infected with COVID-19