An enhanced version of SMMP—open-source software package for simulation of proteins

We describe a revised and updated version of the program package SMMP (Simple Molecular Mechanics for Proteins) [F. Eisenmenger, U.H.E. Hansmann, Sh. Hayryan, C.-K. Hu, Comput. Phys. Comm. 138 (2001) 192-212]. SMMP is an open-source FORTRAN package for molecular simulation of proteins within the standard geometry model. It is designed as a simple and inexpensive tool for researchers and students to become familiar with protein simulation techniques. This announcement describes the first major revision of this software package and its newly added features.

Program summary

Title of program:SMMPCatalogue identifier:ADOJ₋v2₋0Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADOJ_v2_0Program obtainable from: CPC Program Library, Queen's University of Belfast, N. IrelandOperating system under which the program has been tested:LINUX systemProgramming language used:FORTRANComputer:PC PentiumNumber of lines in distributed program, including test data, etc.:18 492Number of bytes in distributed program, including test data, etc.:278 995Distribution format:ASCIICard punching code:ASCIICatalogue Identifier of previous version:ADOJJournal Reference of previous version:F. Eisenmenger, U.H.E. Hansmann, Sh. Hayryan, C.-K. Hu, Comput. Phys. Comm. 138 (2001) 192-212Does the new version supersede the previous version?:YesNature of physical problem:Molecular mechanics computations and Monte Carlo simulation of proteinsReasons for the new version:Increased functionalitySummary of revisions:Changes in energy function and protein representation; differences in program structure and organization; new functionalities added; miscellaneous changes and additionsMethod of solution:Utilizes ECEPP2/3 and FLEX potentials. Includes Monte Carlo simulation algorithms for canonical, as well as for generalized ensemblesRestrictions on the complexity of the problem:The consumed CPU time increases with the size of protein moleculeTypical running time:Depends on the size of the molecule under simulationUnusual features of the program:No     

Exact enumeration of three-dimensional lattice proteins

We present an algorithm for the exhaustive enumeration of all monomer sequences and conformations of short lattice proteins as described by the hydrophobic-polar (HP) model. The algorithm is used for an exact identification of all designing sequences of HP proteins consisting of up to 19 monomers whose conformations are represented by interacting self-avoiding walks on the simple cubic lattice. Employing a parallelized implementation on a Linux cluster, we generate the complete set of contact maps of such walks.     

Detecting trends in forest disturbance and recovery using yearly Landsat time series: 1. LandTrendr — Temporal segmentation algorithms

We introduce and test LandTrendr (Landsat-based detection of Trends in Disturbance and Recovery), a new approach to extract spectral trajectories of land surface change from yearly Landsat time-series stacks (LTS). The method brings together two themes in time-series analysis of LTS: capture of short-duration events and smoothing of long-term trends. Our strategy is founded on the recognition that change is not simply a contrast between conditions at two points in time, but rather a continual process operating at both fast and slow rates on landscapes. This concept requires both new algorithms to extract change and new interpretation tools to validate those algorithms. The challenge is to resolve salient features of the time series while eliminating noise introduced by ephemeral changes in illumination, phenology, atmospheric condition, and geometric registration. In the LandTrendr approach, we use relative radiometric normalization and simple cloud screening rules to create on-the-fly mosaics of multiple images per year, and extract temporal trajectories of spectral data on a pixel-by-pixel basis. We then apply temporal segmentation strategies with both regression-based and point-to-point fitting of spectral indices as a function of time, allowing capture of both slowly-evolving processes, such as regrowth, and abrupt events, such as forest harvest. Because any temporal trajectory pattern is allowable, we use control parameters and threshold-based filtering to reduce the role of false positive detections. No suitable reference data are available to assess the role of these control parameters or to test overall algorithm performance. Therefore, we also developed a companion interpretation approach founded on the same conceptual framework of capturing both long and short-duration processes, and developed a software tool to apply this concept to expert interpretation and segmentation of spectral trajectories (TimeSync, described in a companion paper by Cohen et al., 2010). These data were used as a truth set against which to evaluate the behavior of the LandTrendr algorithms applied to three spectral indices. We applied the LandTrendr algorithms to several hundred points across western Oregon and Washington (U.S.A.). Because of the diversity of potential outputs from the LTS data, we evaluated algorithm performance against summary metrics for disturbance, recovery, and stability, both for capture of events and longer-duration processes. Despite the apparent complexity of parameters, our results suggest a simple grouping of parameters along a single axis that balances the detection of abrupt events with capture of long-duration trends. Overall algorithm performance was good, capturing a wide range of disturbance and recovery phenomena, even when evaluated against a truth set that contained new targets (recovery and stability) with much subtler thresholds of change than available from prior validation datasets. Temporal segmentation of the archive appears to be a feasible and robust means of increasing information extraction from the Landsat archive.     

Temporal and Spatial Distribution of Ulva.prolifera in the Yellow Sea and Influence of Typhoon “CHAN-HOM” in 2015

A recurrent floating green algae bloom was detected in the Yellow Sea since 2007.The Ulva.prolifera is non\|toxic,but the massive accumulations can result in significant environmental damage and cause economic loss to marine industries.In this study,the spatial and temporal patterns of Ulva.prolifera green tides were investigated in the Yellow Sea during 2015 using HJ\|1A/1B and MODIS satellite images by means of NDVI (normalized difference vegetation index)and artificial interpretation.The results showed：(1)A little Ulva.prolifera was discovered firstly in adjacent sea of Yancheng,Jiangsu province in early May with distribution area 0.831 km².Under the action of the southeast monsoon,Ulva.prolifera was gradually drifted to Shandong peninsula waters from south to north.The influential area and range reached a peak value with 1 752.756 km² in late June,and gradually subsided from July to August.And Ulva.prolifera about 38.791 km² was monitored in the South Bay of North Korea.In conclusion,Ulva.prolifera in the Yellow Sea in 2015 has experienced five major processes including “Occur\|Development\|Outbreak\|Recession\|Disappeared”.(2)Typhoon "CHAN\|HOM" certainly influenced the northward pathway of Ulva.prolifera and shifted towards the southwest,resulting in most of Ulva.prolifera moved to the east coast of Lianyungang,and speculated that minority Ulva.prolifera drifted to the South Bay of North Korea.(3)From the monitoring data,the spatial resolution between MODIS and ENVISAT (HJ\|1A / 1B)is difference significantly,250 m and 30 m respectively.A functional relation of the two data with monitoring area difference about 2.26 times was established to make up for the shortage of the environmental satellite (HJ\|1A/1B)images. 