Release Of Version Research Articles

HUBUNGAN ROTASI JABATAN DAN MOTIVASI KERJA PADA ANGGOTA KEPOLISIAN FUNGSI TURJAWALI POLRES SLEMAN

ABSTRACTThis research aimed to determine the relation of job rotation with work motivation in POLRES Sleman. This research is conducted in quantitative approach, using two and Subjects in this study were staff of Turjawali POLRES Sleman. Data was collected with tour of duty scale and job motivation scale. Data was analyzed using SPSS (Statistical Packages for Social Science) for windows release version 17.0.The result showed a positive significant relationship between tour of duty with job motivation in the case of staff Turjawali POLRES Sleman. The coefficient of determination () is 0,889 or 88,9%, this means job rotation can predict job motivation variable (Y) of 88,9% and the rest remaining 11,1% can be explained or predicted by other factors. So, the higher job rotation it would be impact to the higher work motivation to the worker, otherwise the lower of job rotation then the lower of work motivation staff.Keyword: Job rotation, work motivation

PERAN EFIKASI DIRI TERHADAP REGULASI DIRI PADA PELAJARAN MATEMATIKA DITINJAU DARI JENIS KELAMIN

ABSTRACT The purpose of this study are to find out the role self-efficacy and self regulated learning of mathematics in term gender. The subjects of this study are 166 students at SMA Muhammadiyah 3 Yogyakarta. The methods in this research are interview between teacher and students, observation and test. The instruments used in this research were regulation and self-efficacy scale. Analyzing data were done by Correlation Product Moment and independent sample t-test with SPSS for windows release version 17.0. The result shows coeficient correlation r = 0,802, p = 0,000 (p<0,05) and r² = 64,4%, 35,6% of self regulated learning was defined by the other factors such as gender, knowledge, motivation, self willingness. Research shows there is a significant positive correlation between self efficacy for self regulated learning at students and there are differences in self regulated learning by gender.Keyword: self efficacy, self regulated learning.

Design and Implementation of Information Management Tools for the EDISON Open Platform

We have developed an information management tool for the EDISON (EDucation-research Integration through Simulation On the Net) open platform. EDISON is, at present, a web-based simulation service for education and research in five computational areas, namely, nanophysics, fluid dynamics, chemistry, structural dynamics, and computer aided optimal design. The EDISON open platform consists of three tiers: EDISON application framework, EDISON middleware, and EDISON infra-resources. The platform provides web portals for education and research in areas such as computational fluid dynamics, computational chemistry, computational nanophysics, computational structural dynamics, and computer aided optimal design along with user service. The main purpose of this research is to test the behavior of the release version of the EDISON Open-Platform under normal operating conditions. This management tool has been implemented using the RESTful API designed in EDISON middleware. The intention is to check co-operation between the middleware and the infrastructure. Suggested tools include User management, Simulation and Job management, and Simulation software (i.e., solver) testing. Finally, it is considered meaningful to develop a management tool that is not supported in other web-based online simulation services.

Forging the Basis for Developing Protein-Ligand Interaction Scoring Functions.

In structure-based drug design, scoring functions are widely used for fast evaluation of protein-ligand interactions. They are often applied in combination with molecular docking and de novo design methods. Since the early 1990s, a whole spectrum of protein-ligand interaction scoring functions have been developed. Regardless of their technical difference, scoring functions all need data sets combining protein-ligand complex structures and binding affinity data for parametrization and validation. However, data sets of this kind used to be rather limited in terms of size and quality. On the other hand, standard metrics for evaluating scoring function used to be ambiguous. Scoring functions are often tested in molecular docking or even virtual screening trials, which do not directly reflect the genuine quality of scoring functions. Collectively, these underlying obstacles have impeded the invention of more advanced scoring functions. In this Account, we describe our long-lasting efforts to overcome these obstacles, which involve two related projects. On the first project, we have created the PDBbind database. It is the first database that systematically annotates the protein-ligand complexes in the Protein Data Bank (PDB) with experimental binding data. This database has been updated annually since its first public release in 2004. The latest release (version 2016) provides binding data for 16 179 biomolecular complexes in PDB. Data sets provided by PDBbind have been applied to many computational and statistical studies on protein-ligand interaction and various subjects. In particular, it has become a major data resource for scoring function development. On the second project, we have established the Comparative Assessment of Scoring Functions (CASF) benchmark for scoring function evaluation. Our key idea is to decouple the "scoring" process from the "sampling" process, so scoring functions can be tested in a relatively pure context to reflect their quality. In our latest work on this track, i.e. CASF-2013, the performance of a scoring function was quantified in four aspects, including "scoring power", "ranking power", "docking power", and "screening power". All four performance tests were conducted on a test set containing 195 high-quality protein-ligand complexes selected from PDBbind. A panel of 20 standard scoring functions were tested as demonstration. Importantly, CASF is designed to be an open-access benchmark, with which scoring functions developed by different researchers can be compared on the same grounds. Indeed, it has become a popular choice for scoring function validation in recent years. Despite the considerable progress that has been made so far, the performance of today's scoring functions still does not meet people's expectations in many aspects. There is a constant demand for more advanced scoring functions. Our efforts have helped to overcome some obstacles underlying scoring function development so that the researchers in this field can move forward faster. We will continue to improve the PDBbind database and the CASF benchmark in the future to keep them as useful community resources.

Application of Triple Collocation in Ground-Based Validation of Soil Moisture Active/Passive (SMAP) Level 2 Data Products

The validation of the soil moisture retrievals from the recently launched National Aeronautics and Space Administration (NASA) Soil Moisture Active/Passive (SMAP) satellite is important prior to their full public release. Uncertainty in attempts to characterize footprint-scale surface-layer soil moisture using point-scale ground observations has generally limited past validation of remotely sensed soil moisture products to densely instrumented sites covering an area approximating the satellite ground footprint. However, by leveraging independent soil moisture information obtained from land surface modeling and/or alternative remote sensing products, triple collocation (TC) techniques offer a strategy for characterizing upscaling errors in sparser ground measurements and removing the impact of such error on the evaluation of remotely sensed soil moisture products. Here, we propose and validate a TC-based strategy designed to utilize existing sparse soil moisture networks (typically with a single sampling point per satellite footprint) to obtain an unbiased correlation validation metric for satellite surface soil moisture retrieval products. Application of this TC strategy at five SMAP core validation sites suggests that unbiased estimates of correlation between the satellite product and the true footprint average can be obtained - even in cases where ground observations provide only one single reference point within the footprint. An example of preliminary validation results from the application of this TC strategy to the SMAP Level 2 Soil Moisture Passive (beta release version) product is presented.

Description and evaluation of the Community Multiscale Air Quality (CMAQ) modeling system version 5.1.

The Community Multiscale Air Quality (CMAQ) model is a comprehensive multipollutant air quality modeling system developed and maintained by the US Environmental Protection Agency’s (EPA) Office of Research and Development (ORD). Recently, version 5.1 of the CMAQ model (v5.1) was released to the public, incorporating a large number of science updates and extended capabilities over the previous release version of the model (v5.0.2). These updates include the following: improvements in the meteorological calculations in both CMAQ and the Weather Research and Forecast (WRF) model used to provide meteorological fields to CMAQ, updates to the gas and aerosol chemistry, revisions to the calculations of clouds and photolysis, and improvements to the dry and wet deposition in the model. Sensitivity simulations isolating several of the major updates to the modeling system show that changes to the meteorological calculations result in enhanced afternoon and early evening mixing in the model, periods when the model historically underestimates mixing. This enhanced mixing results in higher ozone (O3) mixing ratios on average due to reduced NO titration, and lower fine particulate matter (PM2.5) concentrations due to greater dilution of primary pollutants (e.g., elemental and organic carbon). Updates to the clouds and photolysis calculations greatly improve consistency between the WRF and CMAQ models and result in generally higher O3 mixing ratios, primarily due to reduced cloudiness and attenuation of photolysis in the model. Updates to the aerosol chemistry result in higher secondary organic aerosol (SOA) concentrations in the summer, thereby reducing summertime PM2.5 bias (PM2.5 is typically underestimated by CMAQ in the summer), while updates to the gas chemistry result in slightly higher O3 and PM2.5 on average in January and July. Overall, the seasonal variation in simulated PM2.5 generally improves in CMAQv5.1 (when considering all model updates), as simulated PM2.5 concentrations decrease in the winter (when PM2.5 is generally overestimated by CMAQ) and increase in the summer (when PM2.5 is generally underestimated by CMAQ). Ozone mixing ratios are higher on average with v5.1 vs. v5.0.2, resulting in higher O3 mean bias, as O3 tends to be overestimated by CMAQ throughout most of the year (especially at locations where the observed O3 is low); however, O3 correlation is largely improved with v5.1. Sensitivity simulations for several hypothetical emission reduction scenarios show that v5.1 tends to be slightly more responsive to reductions in NOx (NO + NO2), VOC and SOx (SO2 + SO4) emissions than v5.0.2, representing an improvement as previous studies have shown CMAQ to underestimate the observed reduction in O3 due to large, widespread reductions in observed emissions.

Genomic Variability in Multiple Myeloma (MM) Patients By Race: An Analysis of the Publically Available Mmrf Commpass Study Database

Genomic Variability in Multiple Myeloma (MM) Patients By Race: An Analysis of the Publically Available Mmrf Commpass Study Database

Quantum computing simulation through reduction and decomposition optimizations with a case study of Shor's algorithm

SummaryBecause of the expansion of transformations and read/write memory states by tensor products in multidimensional quantum applications, the exponential increase in temporal and spatial complexities constitutes one of the main challenges for quantum computing simulations. Simulation of these systems is very relevant to develop and test new quantum algorithms. In order to overcome the increase in simulation complexity, this work presents reduction and decomposition optimizations for the Distributed Geometric Machine environment. By exploring properties as the sparsity of the Identity operator and partiality of dense unitary transformations, better storage and distribution of quantum information are achieved. The main improvements are reached by decreasing replication and void elements inherited from quantum operators. In the evaluation of this proposal, Hadamard transformations from 21 to 28 qubits and Quantum Fourier Transforms from 26 to 28 qubits were simulated over CPU, sequentially and in parallel, and in graphics processing unit, showing reduced temporal complexity and, consequently, shorter simulation time. Moreover, evaluations of the Shor's algorithm considering 2n + 3 qubits in the order‐finding quantum algorithm were simulated up to 25 qubits. When comparing our implementations running on the same hardware with language‐integrated quantum operation, academic release version, our new simulator was faster and allowed for the simulation of more qubits. Copyright © 2016 John Wiley & Sons, Ltd.

NUV Star Catalog from the Lunar-based Ultraviolet Telescope Survey: First Release

We present a star catalog extracted from the Lunar-based Ultraviolet Telescope (LUT) survey program. LUT's observable sky area is a circular belt around the Moon's north pole, and the survey program covers a preferred area of about 2400 deg2 which includes a region of the Galactic plane. The data are processed with an automatic pipeline which copes with stray light contamination, artificial sources, cosmic rays, flat field calibration, photometry and so on. In the first release version, the catalog provides high confidence sources which have been cross-identified with the Tycho-2 catalog. All the sources have signal-to-noise ratio larger than 5, and the corresponding magnitude limit is typically 14.4 mag, but can be as deep as ∼16 mag if stray light contamination is at the lowest level. A total of 86 467 stars are recorded in the catalog. The full catalog in electronic form is available online.

The environment ontology in 2016: bridging domains with increased scope, semantic density, and interoperation.

BackgroundThe Environment Ontology (ENVO; http://www.environmentontology.org/), first described in 2013, is a resource and research target for the semantically controlled description of environmental entities. The ontology's initial aim was the representation of the biomes, environmental features, and environmental materials pertinent to genomic and microbiome-related investigations. However, the need for environmental semantics is common to a multitude of fields, and ENVO's use has steadily grown since its initial description. We have thus expanded, enhanced, and generalised the ontology to support its increasingly diverse applications.MethodsWe have updated our development suite to promote expressivity, consistency, and speed: we now develop ENVO in the Web Ontology Language (OWL) and employ templating methods to accelerate class creation. We have also taken steps to better align ENVO with the Open Biological and Biomedical Ontologies (OBO) Foundry principles and interoperate with existing OBO ontologies. Further, we applied text-mining approaches to extract habitat information from the Encyclopedia of Life and automatically create experimental habitat classes within ENVO.ResultsRelative to its state in 2013, ENVO's content, scope, and implementation have been enhanced and much of its existing content revised for improved semantic representation. ENVO now offers representations of habitats, environmental processes, anthropogenic environments, and entities relevant to environmental health initiatives and the global Sustainable Development Agenda for 2030. Several branches of ENVO have been used to incubate and seed new ontologies in previously unrepresented domains such as food and agronomy. The current release version of the ontology, in OWL format, is available at http://purl.obolibrary.org/obo/envo.owl.ConclusionsENVO has been shaped into an ontology which bridges multiple domains including biomedicine, natural and anthropogenic ecology, ‘omics, and socioeconomic development. Through continued interactions with our users and partners, particularly those performing data archiving and sythesis, we anticipate that ENVO’s growth will accelerate in 2017. As always, we invite further contributions and collaboration to advance the semantic representation of the environment, ranging from geographic features and environmental materials, across habitats and ecosystems, to everyday objects in household settings.

CellShape: A user-friendly image analysis tool for quantitative visualization of bacterial cell factories inside.

Visualization of the intracellular constituents of individual bacteria while performing as live biocatalysts is in principle doable through more or less sophisticated fluorescence microscopy. Unfortunately, rigorous quantitation of the wealth of data embodied in the resulting images requires bioinformatic tools that are not widely extended within the community-let alone that they are often subject to licensing that impedes software reuse. In this context we have developed CellShape, a user-friendly platform for image analysis with subpixel precision and double-threshold segmentation system for quantification of fluorescent signals stemming from single-cells. CellShape is entirely coded in Python, a free, open-source programming language with widespread community support. For a developer, CellShape enhances extensibility (ease of software improvements) by acting as an interface to access and use existing Python modules; for an end-user, CellShape presents standalone executable files ready to open without installation. We have adopted this platform to analyse with an unprecedented detail the tridimensional distribution of the constituents of the gene expression flow (DNA, RNA polymerase, mRNA and ribosomal proteins) in individual cells of the industrial platform strain Pseudomonas putida KT2440. While the CellShape first release version (v0.8) is readily operational, users and/or developers are enabled to expand the platform further.

Abstract 130: International Cancer Genome Consortium (ICGC)

Abstract The International Cancer Genome Consortium (ICGC) was established to bring together researchers from around the globe to comprehensively analyze the genomic, transcriptomic, and epigenomic changes in 50 different tumour types or subtypes that are of clinical and societal importance across the globe (International network of cancer genome projects. Nature 464, 993-998 (15 April 2010)). As of November 2015, the ICGC has received commitments from researchers and funding organizations in Asia, Australia, Europe, North America and South America for 89 project teams in 17 jurisdictions to study more than 25,000 tumour genomes. Processed data is available via the Data Coordination Centre (http://dcc.icgc.org) based at the Ontario Institute for Cancer Research and is updated semi-annually. The November 2015 release (Version 20) includes datasets from 66 ICGC projects. In total, ICGC data release 20 comprises data from 14,767 cancer genomes. The Pan-Cancer Analysis of Whole Genomes (PCAWG) project of the ICGC and The Cancer Genome Atlas (TCGA) is coordinating analysis of more than 2,800 cancer genomes, with the extensive use of cloud computing. Because of the very large size of the pan-cancer dataset, with 5,000 whole genome sequences, PCAWG is using a distributed compute cloud environment (generated by computing centres in the USA, Europe and Asia) that meets the project's technical requirements and the bioethical framework of ICGC and its member projects. Each genome is being characterized through a suite of standardized algorithms, including alignment to the reference genome, uniform quality assessment, and the calling of multiple classes of somatic mutations. Scientists participating in the research projects of PCAWG are addressing a series of fundamental questions about cancer biology and evolution based on these data. The first phase of ICGC, which is slated for completion in 2018, has focused on developing extensive catalogs of tumour genomic information. The proposed second phase, ICGCmed, will link genomics to clinical information and health, including lifestyle, patient history, response to therapies, and underlying causes of disease, for a broad spectrum of cancers, including preneoplastic lesions, early cancers and metastases. The goal will be to accelerate the movement of genomic information into the clinic to guide prevention, early detection, diagnosis, and prognosis, and provide the information needed to match a patient's disease to the most effective combinations of therapy. The ICGC develops policies and quality control criteria to help harmonize the work of member projects located in different jurisdictions. Data produced by ICGC projects are made rapidly and freely available to qualified researchers around the world via the data cloud and through the ICGC Data Coordination Center at (http://dcc.icgc.org). More information can be found on www.icgc.org. Citation Format: Jennifer L. Jennings, Thomas J. Hudson. International Cancer Genome Consortium (ICGC). [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 130.

From frames to OWL2: Converting the Foundational Model of Anatomy.

The Foundational Model of Anatomy (FMA) [Rosse C, Mejino JLV. A reference ontology for bioinformatics: the Foundational Model of Anatomy. J. Biomed. Inform. 2003;36:478-500] is an ontology that represents canonical anatomy at levels ranging from the entire body to biological macromolecules, and has rapidly become the primary reference ontology for human anatomy, and a template for model organisms. Prior to this work, the FMA was developed in a knowledge modeling language known as Protégé Frames. Frames is an intuitive representational language, but is no longer the industry standard. Recognizing the need for an official version of the FMA in the more modern semantic web language OWL2 (hereafter referred to as OWL), the objective of this work was to create a generalizable Frames-to-OWL conversion tool, to use the tool to convert the FMA to OWL, to "clean up" the converted FMA so that it classifies under an EL reasoner, and then to do all further development in OWL. The conversion tool is a Java application that uses the Protégé knowledge representation API for interacting with the initial Frames ontology, and uses the OWL-API for producing new statements (axioms, etc.) in OWL. The converter is relation centric. The conversion is configurable, on a property-by-property basis, via user-specifiable XML configuration files. The best conversion, for each property, was determined in conjunction with the FMA knowledge author. The convertor is potentially generalizable, which we partially demonstrate by using it to convert our Ontology of Craniofacial Development and Malformation as well as the FMA. Post-conversion cleanup involved using the Explain feature of Protégé to trace classification errors under the ELK reasoner in Protégé, fixing the errors, then re-running the reasoner. We are currently doing all our development in the converted and cleaned-up version of the FMA. The FMA (updated every 3 months) is available via our FMA web page http://si.washington.edu/projects/fma, which also provides access to mailing lists, an issue tracker, a SPARQL endpoint (updated every week), and an online browser. The converted OCDM is available at http://www.si.washington.edu/projects/ocdm. The conversion code is open source, and available at http://purl.org/sig/software/frames2owl. Prior to the post-conversion cleanup 73% of the more than 100,000 classes were unsatisfiable. After correction of six types of errors no classes remained unsatisfiable. Because our FMA conversion captures all or most of the information in the Frames version, is the only complete OWL version that classifies under an EL reasoner, and is maintained by the FMA authors themselves, we propose that this version should be the only official release version of the FMA in OWL, supplanting all other versions. Although several issues remain to be resolved post-conversion, release of a single, standardized version of the FMA in OWL will greatly facilitate its use in informatics research and in the development of a global knowledge base within the semantic web. Because of the fundamental nature of anatomy in both understanding and organizing biomedical information, and because of the importance of the FMA in particular in representing human anatomy, the FMA in OWL should greatly accelerate the development of an anatomically based structural information framework for organizing and linking a large amount of biomedical information.

Recent developments in CrystFEL.

CrystFEL is a suite of programs for processing data from 'serial crystallography' experiments, which are usually performed using X-ray free-electron lasers (FELs) but also increasingly with other X-ray sources. The CrystFEL software suite has been under development since 2009, just before the first hard FEL experiments were performed, and has been significantly updated and improved since then. This article describes the most important improvements which have been made to CrystFEL since the first release version. These changes include the addition of new programs to the suite, the ability to resolve 'indexing ambiguities' and several ways to improve the quality of the integrated data by more accurately modelling the underlying diffraction physics.

Simulation of Auger electron emission from nanometer-size gold targets using the Geant4 Monte Carlo simulation toolkit

A revised atomic deexcitation framework for the Geant4 general purpose Monte Carlo toolkit capable of simulating full Auger deexcitation cascades was implemented in June 2015 release (version 10.2 Beta). An overview of this refined framework and testing of its capabilities is presented for the irradiation of gold nanoparticles (NP) with keV photon and MeV proton beams. The resultant energy spectra of secondary particles created within and that escape the NP are analyzed and discussed. It is anticipated that this new functionality will improve and increase the use of Geant4 in the medical physics, radiobiology, nanomedicine research and other low energy physics fields.

Genetic differences among ethnic groups.

BackgroundMany differences between different ethnic groups have been observed, such as skin color, eye color, height, susceptibility to some diseases, and response to certain drugs. However, the genetic bases of such differences have been under-investigated. Since the HapMap project, large-scale genotype data from Caucasian, African and Asian population samples have been available. The project found that these populations were located in different areas of the PCA (Principal Component Analysis) plot. However, as an unsupervised method, PCA does not measure the differences in each single nucleotide polymorphism (SNP) among populations.ResultsWe applied an advanced mutual information-based feature selection method to detect associations between SNP status and ethnic groups using the latest HapMap Phase 3 release version 3, which included more sub-populations. A total of 299 SNPs were identified, and they can accurately predicted the ethnicity of all HapMap populations. The 10-fold cross validation accuracy of the SMO (sequential minimal optimization) model on training dataset was 0.901, and the accuracy on independent test dataset was 0.895.ConclusionsIn-depth functional analysis of these SNPs and their nearby genes revealed the genetic bases of skin and eye color differences among populations.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-015-2328-0) contains supplementary material, which is available to authorized users.

MEDXVIEWER: PROVIDING A WEB-ENABLED WORKSTATION ENVIRONMENT FOR COLLABORATIVE AND REMOTE MEDICAL IMAGING VIEWING, PERCEPTION STUDIES AND READER TRAINING

MedXViewer (Medical eXtensible Viewer) has been developed to address the need for workstation-independent, picture archiving and communication system (PACS)-less viewing and interaction with anonymised medical images. The aim of this paper is to describe the design and features of MedXViewer as well as to introduce the new features available in the latest release (version 1.2). MedXViewer currently supports digital mammography and tomosynthesis. The flexible software design used to develop MedXViewer allows it to be easily extended to support other imaging modalities. Regions of interest can be drawn by a user, and any associated information about a mark, an image or a study can be added. The questions and settings can be easily configured depending on the need of the research allowing both ROC and FROC studies to be performed. Complex tree-like questions can be asked where a given answer presents the user to new questions. The hanging protocol can be specified for each study. Panning, windowing, zooming and moving through slices are all available while modality-specific features can be easily enabled, e.g. quadrant zooming in digital mammography and tomosynthesis studies. MedXViewer can integrate with a web-based image database OPTIMAM Medical Image Database allowing results and images to be stored centrally. The software can, alternatively, run without a network connection where the images and results can be encrypted and stored locally on a machine or external drive. MedXViewer has been used for running remote paper-less observer studies and is capable of providing a training infrastructure and coordinating remote collaborative viewing sessions.

Updating sea spray aerosol emissions in the Community Multiscale Air Quality (CMAQ) model version 5.0.2

Abstract. Sea spray aerosols (SSAs) impact the particle mass concentration and gas-particle partitioning in coastal environments, with implications for human and ecosystem health. Model evaluations of SSA emissions have mainly focused on the global scale, but regional-scale evaluations are also important due to the localized impact of SSAs on atmospheric chemistry near the coast. In this study, SSA emissions in the Community Multiscale Air Quality (CMAQ) model were updated to enhance the fine-mode size distribution, include sea surface temperature (SST) dependency, and reduce surf-enhanced emissions. Predictions from the updated CMAQ model and those of the previous release version, CMAQv5.0.2, were evaluated using several coastal and national observational data sets in the continental US. The updated emissions generally reduced model underestimates of sodium, chloride, and nitrate surface concentrations for coastal sites in the Bay Regional Atmospheric Chemistry Experiment (BRACE) near Tampa, Florida. Including SST dependency to the SSA emission parameterization led to increased sodium concentrations in the southeastern US and decreased concentrations along parts of the Pacific coast and northeastern US. The influence of sodium on the gas-particle partitioning of nitrate resulted in higher nitrate particle concentrations in many coastal urban areas due to increased condensation of nitric acid in the updated simulations, potentially affecting the predicted nitrogen deposition in sensitive ecosystems. Application of the updated SSA emissions to the California Research at the Nexus of Air Quality and Climate Change (CalNex) study period resulted in a modest improvement in the predicted surface concentration of sodium and nitrate at several central and southern California coastal sites. This update of SSA emissions enabled a more realistic simulation of the atmospheric chemistry in coastal environments where marine air mixes with urban pollution.

Molcas 8: New capabilities for multiconfigurational quantum chemical calculations across the periodic table.

In this report, we summarize and describe the recent unique updates and additions to the Molcas quantum chemistry program suite as contained in release version 8. These updates include natural and spin orbitals for studies of magnetic properties, local and linear scaling methods for the Douglas-Kroll-Hess transformation, the generalized active space concept in MCSCF methods, a combination of multiconfigurational wave functions with density functional theory in the MC-PDFT method, additional methods for computation of magnetic properties, methods for diabatization, analytical gradients of state average complete active space SCF in association with density fitting, methods for constrained fragment optimization, large-scale parallel multireference configuration interaction including analytic gradients via the interface to the Columbus package, and approximations of the CASPT2 method to be used for computations of large systems. In addition, the report includes the description of a computational machinery for nonlinear optical spectroscopy through an interface to the QM/MM package Cobramm. Further, a module to run molecular dynamics simulations is added, two surface hopping algorithms are included to enable nonadiabatic calculations, and the DQ method for diabatization is added. Finally, we report on the subject of improvements with respects to alternative file options and parallelization.

PlantPAN 2.0: an update of plant promoter analysis navigator for reconstructing transcriptional regulatory networks in plants.

Transcription factors (TFs) are sequence-specific DNA-binding proteins acting as critical regulators of gene expression. The Plant Promoter Analysis Navigator (PlantPAN; http://PlantPAN2.itps.ncku.edu.tw) provides an informative resource for detecting transcription factor binding sites (TFBSs), corresponding TFs, and other important regulatory elements (CpG islands and tandem repeats) in a promoter or a set of plant promoters. Additionally, TFBSs, CpG islands, and tandem repeats in the conserve regions between similar gene promoters are also identified. The current PlantPAN release (version 2.0) contains 16 960 TFs and 1143 TF binding site matrices among 76 plant species. In addition to updating of the annotation information, adding experimentally verified TF matrices, and making improvements in the visualization of transcriptional regulatory networks, several new features and functions are incorporated. These features include: (i) comprehensive curation of TF information (response conditions, target genes, and sequence logos of binding motifs, etc.), (ii) co-expression profiles of TFs and their target genes under various conditions, (iii) protein-protein interactions among TFs and their co-factors, (iv) TF-target networks, and (v) downstream promoter elements. Furthermore, a dynamic transcriptional regulatory network under various conditions is provided in PlantPAN 2.0. The PlantPAN 2.0 is a systematic platform for plant promoter analysis and reconstructing transcriptional regulatory networks.