Morphological Dependence of Star Formation Properties for the Galaxies in the Merging Galaxy Cluster A2255

The merging cluster of galaxies A2255 is covered by the Sloan Digital Sky Survey (SDSS) survey. In this paper we perform a morphological classification on the basis of the SDSS imaging and spectral data, and investigate the morphological dependence of the star formation rates (SFRs) for these member galaxies. As we expect, a tight correlation between the normalized SFR by stellar mass (SFR/M$_*$) and the H$\alpha$ equivalent width is found for the late-type galaxies in A2255. The correlation of SFR/M$_*$ with the continuum break strength at 4000 \AA is also confirmed. The SFR/M$_*$ - M$_*$ correlation is found for both the early- and late-type galaxies, indicating that the star formation activity tends to be suppressed when the assembled stellar mass M$_*$) increases, and this correlation is tighter and steeper for the late-type cluster galaxies. Compared with the mass range of field spiral galaxies, only two massive late-type galaxies with M$_*>10^{11}$ M$_{\odot}$ are survived in A2255, suggesting that the gas disks of massive spiral galaxies could have been tidally stripped during cluster formation. Additionally, the SFR variation with the projected radial distance are found to be heavily dependent upon galaxy morphology: the early-type galaxies have a very weak inner decrease in SFR/M$_*$, while the inner late-type galaxies tend to have higher SFR/M$_*$ values than the outer late-types. This may suggest that the galaxy-scale turbulence stimulated by the merging of subclusters might have played different roles on early- and late-type galaxies, which leads to a suppression of the star formation activity for E/S0 galaxies and a SFR enhancement for spiral and irregular galaxies.Comment: 21 pages, including 7 EPS figures and 1 tables, uses aastex.cls, Accepted by the A

Sliding Mode Control (SMC) of Image‐Based Visual Servoing for a 6DOF Manipulator

The accuracy and stability are two fundamental concerns of the visual servoing control system. This chapter presents a sliding mode controller for image‐based visual servoing (IBVS) which can increase the accuracy of 6DOF robotic system with guaranteed stability. The proposed controller combines proportional derivative (PD) control with sliding mode control (SMC) for a 6DOF manipulator. Compared with conventional proportional or SMC controller, this approach owns faster convergence and better disturbance rejection ability. Both simulation and experimental results show that the proposed controller can increase the accuracy and robustness of a 6DOF robotic system

Dislocation behaviors in nanotwinned diamond

Experimental results (Huang et al.) indicated that nanotwinned diamond (nt-diamond) has unprecedented hardness, whose physical mechanism has remained elusive. In this report, we categorize interaction modes between dislocations and twin planes in nt-diamond and calculate the associated reaction heat, activation energies, and barrier strength using molecular dynamics. On the basis of the Sachs model, twin thickness dependence of nt-diamond hardness is evaluated, which is in good agreement with the experimental data. We show that two factors contribute to the unusually high hardness of nt-diamond: high lattice frictional stress by the nature of carbon bonding in diamond and high athermal stress due to the Hall-Petch effect. Both factors stem from the low activation volumes and high activation energy for dislocation nucleation and propagation in diamond twin planes. This work provides new insights into hardening mechanisms in nt-diamond and will be helpful for developing new superhard materials in the future

GolgiP: prediction of Golgi-resident proteins in plants

Summary: We present a novel Golgi-prediction server, GolgiP, for computational prediction of both membrane- and non-membrane-associated Golgi-resident proteins in plants. We have employed a support vector machine-based classification method for the prediction of such Golgi proteins, based on three types of information, dipeptide composition, transmembrane domain(s) (TMDs) and functional domain(s) of a protein, where the functional domain information is generated through searching against the Conserved Domains Database, and the TMD information includes the number of TMDs, the length of TMD and the number of TMDs at the N-terminus of a protein. Using GolgiP, we have made genome-scale predictions of Golgi-resident proteins in 18 plant genomes, and have made the preliminary analysis of the predicted data

Construction of Shanghai Diabetes Clinical Database and real-world study

Objective·To construct a clinical database of diabetes in Shanghai, mine the value of clinical data, and carry out real-world study.Methods·The data were extracted from Shanghai Link Healthcare Database. All original clinical data have undergone standard processes such as desensitization, encryption, cleaning, standardization, information extraction and structuring, and clinical data were analyzed by the method of medical statistics or machine learning according to different research contents.Results·The database has imported the clinical data of 150 million visits and treatment records of 2.12 million diabetic patients in 37 municipal hospitals over a ten-year period from 2013 to 2022. The overall analysis showed the basic characteristics and development trends of all aspects of diabetes disease in real-world settings, the potential risks of diabetes are discovered by constructing retrospective cohort, and the inherent patterns of the disease are revealed by using machine learning methods such as cluster analysis and network analysis.Conclusion·The establishment of Shanghai Diabetes Clinical Database can not only summarize and show the clinical status of diabetes, but also obtain more scientific achievements with realistic clinical value by real-world clinical data study

Photocatalytic abstraction of hydrogen atoms from water using hydroxylated graphitic carbon nitride for hydrogenative coupling reactions

Employing pure water, the ultimate green source of hydrogen donor to initiate chemical reactions that involve a hydrogen atom transfer (HAT) step is fascinating but challenging due to its large H−O bond dissociation energy (BDEH-O=5.1 eV). Many approaches have been explored to stimulate water for hydrogenative reactions, but the efficiency and productivity still require significant enhancement. Here, we show that the surface hydroxylated graphitic carbon nitride (gCN−OH) only requires 2.25 eV to activate H−O bonds in water, enabling abstraction of hydrogen atoms via dehydrogenation of pure water into hydrogen peroxide under visible light irradiation. The gCN−OH presents a stable catalytic performance for hydrogenative N−N coupling, pinacol-type coupling and dehalogenative C−C coupling, all with high yield and efficiency, even under solar radiation, featuring extensive impacts in using renewable energy for a cleaner process in dye, electronic, and pharmaceutical industries

An FDA bioinformatics tool for microbial genomics research on molecular characterization of bacterial foodborne pathogens using microarrays

<p>Abstract</p> <p>Background</p> <p>Advances in microbial genomics and bioinformatics are offering greater insights into the emergence and spread of foodborne pathogens in outbreak scenarios. The Food and Drug Administration (FDA) has developed a genomics tool, ArrayTrack^TM, which provides extensive functionalities to manage, analyze, and interpret genomic data for mammalian species. ArrayTrack^TM has been widely adopted by the research community and used for pharmacogenomics data review in the FDA’s Voluntary Genomics Data Submission program. </p> <p>Results</p> <p>ArrayTrack^TM has been extended to manage and analyze genomics data from bacterial pathogens of human, animal, and food origin. It was populated with bioinformatics data from public databases such as NCBI, Swiss-Prot, KEGG Pathway, and Gene Ontology to facilitate pathogen detection and characterization. ArrayTrack^TM’s data processing and visualization tools were enhanced with analysis capabilities designed specifically for microbial genomics including flag-based hierarchical clustering analysis (HCA), flag concordance heat maps, and mixed scatter plots. These specific functionalities were evaluated on data generated from a custom Affymetrix array (FDA-ECSG) previously developed within the FDA. The FDA-ECSG array represents 32 complete genomes of <it>Escherichia coli</it> and<it> Shigella.</it> The new functions were also used to analyze microarray data focusing on antimicrobial resistance genes from <it>Salmonella</it> isolates in a poultry production environment using a universal antimicrobial resistance microarray developed by the United States Department of Agriculture (USDA).</p> <p>Conclusion</p> <p>The application of ArrayTrack^TM to different microarray platforms demonstrates its utility in microbial genomics research, and thus will improve the capabilities of the FDA to rapidly identify foodborne bacteria and their genetic traits (e.g., antimicrobial resistance, virulence, etc.) during outbreak investigations. ArrayTrack^TM is free to use and available to public, private, and academic researchers at <url>http://www.fda.gov/ArrayTrack</url>. </p

Association of genetic variation with systolic and diastolic blood pressure among African Americans: the Candidate Gene Association Resource study

The prevalence of hypertension in African Americans (AAs) is higher than in other US groups; yet, few have performed genome-wide association studies (GWASs) in AA. Among people of European descent, GWASs have identified genetic variants at 13 loci that are associated with blood pressure. It is unknown if these variants confer susceptibility in people of African ancestry. Here, we examined genome-wide and candidate gene associations with systolic blood pressure (SBP) and diastolic blood pressure (DBP) using the Candidate Gene Association Resource (CARe) consortium consisting of 8591 AAs. Genotypes included genome-wide single-nucleotide polymorphism (SNP) data utilizing the Affymetrix 6.0 array with imputation to 2.5 million HapMap SNPs and candidate gene SNP data utilizing a 50K cardiovascular gene-centric array (ITMAT-Broad-CARe [IBC] array). For Affymetrix data, the strongest signal for DBP was rs10474346 (P= 3.6 × 10−8) located near GPR98 and ARRDC3. For SBP, the strongest signal was rs2258119 in C21orf91 (P= 4.7 × 10−8). The top IBC association for SBP was rs2012318 (P= 6.4 × 10−6) near SLC25A42 and for DBP was rs2523586 (P= 1.3 × 10−6) near HLA-B. None of the top variants replicated in additional AA (n = 11 882) or European-American (n = 69 899) cohorts. We replicated previously reported European-American blood pressure SNPs in our AA samples (SH2B3, P= 0.009; TBX3-TBX5, P= 0.03; and CSK-ULK3, P= 0.0004). These genetic loci represent the best evidence of genetic influences on SBP and DBP in AAs to date. More broadly, this work supports that notion that blood pressure among AAs is a trait with genetic underpinnings but also with significant complexit