Sequential Steps in Reading: Reading Workpad, Volume 15, , Harcourt, Brace & Jovanovich, 1973, , . .

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Sequential steps in reading , Theodore Glim, 1973, Education, . .

Filipino value system a cultural definition, F. Landa Jocano, 1997, History, 123 pages. .

Sulod Society A Study in the Kinship System and Social Organization of a Mountain of Central Panay, F. Landa Jocano, Jul 1, 2009, Social Science, 254 pages. This work offers a comprehensive description and analysis of the kinship system and social organization of the Sulod..

Windows NT startup process starts when the computer finds a Windows boot loader, a portion of Windows responsible for finding and starting it up. On IA-32 or x64 systems, the boot loader is called Windows Boot Manager (BOOTMGR). Prior to Windows Vista however, the boot loader was NTLDR. Microsoft has also released operating systems for Intel Itanium processors which use IA-64 architecture. The boot loader of these editions of Windows is IA64ldr.efi (later referred as simply IA64ldr). It is an Extensible Firmware Interface (EFI) program.[1]

The boot loader, once executed, searches for a Windows operating system. Windows Boot Manager does so by reading Boot Configuration Data (BCD), a complex firmware-independent database for boot-time configuration data. Its predecessor, NTLDR, does so by reading the simpler boot.ini. If the boot.ini file is missing, the boot loader will attempt to locate information from the standard installation directory. For Windows NT and 2000 machines, it will attempt to boot from C:\WINNT. For Windows XP and 2003 machines, it will boot from C:\WINDOWS.

Both databases may contain a list of installed Microsoft operating systems that may be loaded from the local hard disk drive or a remote computer on the local network. NTLDR supports operating systems installed on disks whose is NTFS or FAT file systems, CDFS (ISO 9660) or UDFS.[2] Windows Boot Manager also supports operating systems installed inside a VHD file, stored on an NTFS disk drive.[3]

In the Windows 2000 or in later versions of Windows which hibernation is supported, the Windows boot loader starts the search for operating systems by searching for hiberfil.sys. NTLDR looks into the root folder of the default volume specified in boot.ini. Windows Boot Manager looks up the location of hiberfil.sys in BCD. If this file is found and an active memory set is found in it, the boot loader loads the contents of the file (which will match the amount of physical memory in the machine) into memory and restores the computer to the state that it was prior to hibernation.

Next, the boot loader looks for a list of installed operating system entries. If more than one operating system is installed, the boot loader shows a boot menu and allow the user to select an operating system. If a non NT-based operating system such as Windows 98 is selected (specified by an MS-DOS style of path, e.g. C:\), then the boot loader loads the associated "boot sector" file listed in boot.ini or BCD (by default, this is bootsect.dos if no file name is specified) and passes execution control to it. Otherwise, the boot process continues.

The operating system starts when certain basic drivers flagged as "Boot" are loaded into memory. The appropriate file system driver for the partition type (NTFS, FAT, or FAT32) which the Windows installation resides are amongst them. At this point in the boot process, the boot loader clears the screen and displays a textual progress bar, (which is often not seen due to the initialization speed); Windows 2000 also displays the text "Starting Windows..." underneath. If the user presses F8 during this phase, the advanced boot menu is displayed, containing various special boot modes including Safe mode, with the Last Known Good Configuration, with debugging enabled, and (in the case of editions) Directory Services Restore Mode. Once a boot mode has been selected (or if F8 was never pressed) booting continues.

With the kernel in memory, boot-time device drivers are loaded (but not yet initialized). The required information (along with information on all detected hardware and Windows Services) is stored in the HKEY_LOCAL_MACHINE\System portion of the registry, in a set of registry keys collectively called a Control Set. Multiple control sets (typically two) are kept, in the event that the settings contained in the currently-used one prohibit the system from booting. HKEY_LOCAL_MACHINE\System contains control sets labeled ControlSet001, ControlSet002, etc., as well as CurrentControlSet. During regular operation, Windows uses CurrentControlSet to read and write information. CurrentControlSet is a reference to one of the control sets stored in the registry. Windows picks the "real" control set being used based on the values set in the HKLM\SYSTEM\Select registry key:

A "Boot" driver that is loaded by the boot loader prior to starting the kernel. "Boot" drivers are almost exclusively drivers for hard-disk controllers and file systems (ATA, SCSI, file system filter manager, etc.); in other words, they are the absolute minimum that the kernel will need to get started with loading other drivers, and the rest of the operating system.

During the first phase, basic internal memory structures are created, and each CPU's interrupt controller is initialized. The memory manager is initialized, creating areas for the file system cache, paged and non-paged pools of memory. The ,[4] initial security token for assignment to the first process on the system, and the Process Manager itself. The System process as well as the System process are created at this point.

Through the process of loading device drivers, a "progress bar" is visible at the bottom of the display on Windows 2000 systems; in Windows XP and Windows Server 2003, this was replaced by an animated bar which does not represent actual progress. Prior to Windows XP, this part of the boot process took significantly longer; this is because the drivers would be initialized one at a time. On Windows XP and Server 2003, the drivers are all initialized asynchronously.

Before any files are opened, Autochk [1] is started by smss.exe. Autochk mounts all drives and checks them one at a time to see whether or not they were cleanly unmounted. If autochk determines one or more volumes are dirty, it will automatically run chkdsk and provides the user with a short window to abort the repair process by pressing a key within 10 seconds (introduced in Windows NT 4.0 Service Pack 4; earlier versions would not allow the user to abort chkdsk). Since Windows 2000, XP and 2003 show no text screen at that point (unlike NT, which displayed a blue text screen), the user will see a different background picture holding a mini-text-screen in the center of the screen and show the progress of chkdsk there.

Starts the Windows Logon Manager (.exe). Winlogon is responsible for handling interactive logons to a Windows system (local or remote). The Graphical Identification aNd Authentication (GINA) library is loaded inside the Winlogon process, and provides support for logging in as a local or user.

Winlogon starts the Local Security Authority Subsystem Service (LSASS) and (SCM), which in turn will start all the Windows services that are set to Auto-Start.[5] It is also responsible for responding to the secure attention sequence (SAS), loading the user profile on logon, and optionally locking the computer when a screensaver is running.

A combination of ESPRIT, SLP and mothur computes taxonomic independent clusters (Operational Taxonomic Units - OTUs) using the total collection of available V6 sequences in VAMPS. The sequences were binned into separate datasets for the Archaeal or Eukaryal domains, and into Bacterial phylum- or Proteobacterial class-level datasets. For each bin, the unique.seqs function in mothur, eliminated duplicate sequences but retained information about observed frequencies for each unique read. The kmerdist module of ESPRIT (with default values) identified all sequence pairs within each bin that are predicted to be at least 90% similar. The needledist module in ESPRIT generated a sparse matrix of pairwise distances by performing a Needleman-Wunsch alignment on the sequence pairs and calculating pairwise distances using quickdist. The algorithm SLP uses the pairwise distances to perform a modified single-linkage preclustering at 2% to reduce noise in the sequence data. Initially SLP orders sequences according to their rank abundance and then steps through the ordered sequences assigning them to clusters. The most abundant sequence defines the first cluster. Each subsequent sequence is tested against the growing list of clusters using the single-linkage algorithm. If the sequence has a pairwise distance less than 0.02 (equivalent to a single difference in the V6 region) to any of the sequences already in the cluster, the new sequence will be added to the cluster and not tested against subsequent clusters. If the sequence is not within a distance of 0.02 from any read in any of the existing clusters, it will establish a new cluster. Once all sequences have been assigned to clusters, sequences in the low abundance clusters (< 10 tags) are tested against the larger clusters and added to those clusters if possible. For each precluster, SLP uses the sequence with the highest frequency and the count of all tags in the precluster for average linkage clustering by mothur. Taxonomy for each cluster relies upon on a two-thirds majority of the taxonomy for each cluster member; CATCHALL estimates the estimate richness.

The .tax file shows the taxonomy corresponding to the reads in the .list file for the 0.03, 0.06, and 0.10 widths. Clusters are tab-delimited and contain a list of comma-separated taxa and their counts. The lists are in order of decreasing abundance, so the most common taxon is first. The format will be

The header line is REQUIRED. The required header line consists of the word: 'Cluster_ID', then the dataset names. Taxonomy is optional and if it is present it is the last tab field in each row and there must be the word 'Taxonomy' as the last word in the header. If the word taxonomy is found in the header then all taxonomy needs to be filled in. If the taxonomy is unknown then 'unknown' should be in the row. All of the fields in the file are separated by tabs including the header line. The dataset names should be alpanumeric only (underscore allowed also) and contain no spaces.

The 5-nt run key is used to look up the amplification primers on the researcher submission form. The start of the tag sequence is compared with the list of amplification start primers (i.e., 5' end of a forward read). If an exact match to an expected proximal primer is not found, the tag is deleted for low-quality, otherwise the run key and primer are removed from the tag sequence.

If an exact match to the distal primer is not located, BLASTN (with non-default parameters -q -1, -W 7, -S 1, -E 2, -F 'F', and -G 1), and the EMBOSS program fuzznuc (with non-default parameter -mismatch=3) are used for a fuzzy comparison of expected primers with the end of the sequence. If a match is found (either exact or fuzzy) the distal primer is removed from the sequence.

Because the top BLAST hit may not have the highest overall similarity to the tag sequence, particularly because edge-effects in the short region being compared can be pronounced, we align the tag sequence to the reference tags corresponding to the top 100 BLAST hits. We use MUSCLE (with non-default parameters - diags diags1 and -maxiters 2 to reduce processing time).

We calculate the global distance from the tag to each of the aligned reference sequences as the number of insertions, deletions and mismatches divided by the length of the tag. We considered the reference sequence or sequences with the minimum global distance to be the top GAST match(es). The top BLAST hit was generally the best global match; however, for 5% to 25% of tags the best global match is to a reference sequence with a lower BLAST score.

If two-thirds or more of the full-length sequences share the same assigned genus, the tag is assigned to that genus. If there is no such agreement, we proceed up the tree one level to family. If there is a two-thirds or better consensus at the family level, we assign this taxonomy to the tag, and if not, we continue up the tree, until we achieve a two-thirds majority. Tags that do not match any reference tag by BLAST were not given a taxonomic assignment. Comparison of taxonomic assignments of hypervariable tags via GAST with the taxonomic assignments of known source full-length sequences through RDP show a 98+% correlation.

Trimmed sequences can be uploaded to the VAMPS database directly using the tools on this page. If you use this method you will be asked for a project and dataset name as well as domain and which region of the S16 molecule the sequences come from. This metadata will be used to select the reference database when you want the taxonomy assigned using the GAST system. You will also be asked to supply an environmental source for your data which will be used to filter your dataset(s) later. It is also possible to add a new dataset to one of your projects that is already in the VAMPS database, but you are not allowed to add to an already existing dataset. The sequence file must be fasta format (plain text, zipped or gzipped).

The second type of data that can be uploaded is raw sequences that you want to have trimmed using specific primers and keys (short barcode sequences which separate datasets) which you supply (see this page to start uploading raw sequences). A quality file can also be included to help elucidate which sequences are to be discarded because of low quality. See below for file formats for uploading raw sequences. The sequences and quality files must be fasta format (plain text, zipped or gzipped) and the primers and runkeys file are tab delimited text files.

Trimmed sequences can be imported using the NCBI FASTA format. Each read starts with a ‘>’ and the Read_ID is between the ‘>’ and the first ‘|’ (a ‘pipe’ symbol) or the first white space ('tab' or 'space') and cannot contain any special characters other than underscore ‘_’. Each Read_ID must be a unique value. If there is any other information on the definition line, it must be after the first ‘|’ (or space). The whole definition line is separated from the sequence data by a return or linefeed.

The metadata file is a csv (comma separated values) file. It is required and provides a way to include runkeys (barcodes) so that the trimmed sequences can be de-multiplexed into separate datasets. The metadata file contains other required data such as project and dataset names. In the table below is an explanation of the different columns. The double quotes around each item are okay but not required.

The third part is determined by the type of analysis requested. It is in the form of Bv6 or Av4v5. where the 'B' and 'A' stand for Bacteria and Archaea respectively. Eukarya may also occur if you choose the ITS1 region. Currently for HiSEQ and MiSeq the dna_regions are v6 and v4v5 (or ITS1). The three parts are joined by an underscore to create the VAMPS project name. The submission form will report if the project name is already chosen and we reserve the right to change a submitted name.

We classify all bacterial and archaeal sequences directly with the Ribosomal Database Project Classifier (RDP). We used only RDP classifications with a bootstrap value of >=80%. If the bootstrap value was <80%, the taxonomic assignment was moved to a higher classification level until an 80% or better bootstrap value was achieved. For example, if the genus assignment had a bootstrap value of 70%, but the family had a value of 85%, that sequence would be assigned only as far as family and not to genus. RDP Classifier does not classify sequences below the genus level.

We incorporate other taxonomy sources, such as Entrez Genome accession numbers or researcher knowledge of specific entries, as they become available. These "other sources" are used preferentially over the RDP for bacteria and archaea. RDP does not classify eukaryotes. For eukaryota taxonomies, we use the EMBL taxonomy from the SILVA database where we do not have other sources.

Two reference IDs are assigned to each reference hypervariable region. A ref16s_id (previously alt_local_gi) links the hypervariable sequence with its source full-length sequence, and a second, e.g., refv6_id (previously known as local_gi) is used to identify all entries having the exact same sequence of the hypervariable region. The taxonomy is carried directly from the full-length source.

Conserved sequences that flank the hypervariable V6 region of rRNAs serve as primer sites to generate PCR amplicons. Each PCR reaction produces products that can be informatically identified using a unique "key" incorporated between the 454 Life Sciences primer A and the 5' flanking rRNA primer. The use of a 5-bp key allows for the synthesis of as many as 81 oligonucleotides that differ by at least two sites. Our multiplexing strategy allows the concurrent collection of 10,000-50,000 tags from each of 8-40 samples in a single four- hour sequencing run without use of partitioning gaskets that reduce the number of sequencing wells on the PicoTiterPlateTM. Amplicons can be pooled before the emPCR step and each pool is run on a large region of the plate. http://edufb.net/2195.pdf http://edufb.net/2630.pdf http://edufb.net/3853.pdf http://edufb.net/2152.pdf http://edufb.net/3040.pdf http://edufb.net/1214.pdf http://edufb.net/3967.pdf http://edufb.net/3987.pdf http://edufb.net/2336.pdf http://edufb.net/1647.pdf http://edufb.net/1886.pdf http://edufb.net/1636.pdf http://edufb.net/1885.pdf