To date more than 2,1 million gene products from more than 100000 different species have been described specifying their function, the processes they are involved in and their cellular localization using a very well defined and structured vocabulary, the gene ontology (GO). Such vast, well defined knowledge opens the possibility of compare gene products at the level of functionality, finding gene products which have a similar function or are involved in similar biological processes without relying on the conventional sequence similarity approach. Comparisons within such a large space of knowledge are highly data and computing intensive. For this reason this project was based upon the use of the computational GRID, a technology offering large computing and storage resources.
We have developed a tool, GEN e AnaloG ue FIN dE r (ENGINE) that parallelizes the search process and distributes the calculation and data over the computational GRID, splitting the process into many sub-processes and joining the calculation and the data on the same machine and therefore completing the whole search in about 3 days instead of occupying one single machine for more than 5 CPU years. The results of the functional comparison contain potential functional analogues for more than 79000 gene products from the most important species. 46% of the analyzed gene products are well enough described for such an analysis to individuate functional analogues, such as well-known members of the same gene family, or gene products with similar functions which would never have been associated by standard methods.
ENGINE has produced a list of potential functionally analogous relations between gene products within and between species using, in place of the sequence, the gene description of the GO, thus demonstrating the potential of the GO. However, the current limiting factor is the quality of the associations of many gene products from non-model organisms that often have electronic associations, since experimental information is missing. With future improvements of the GO, this limit will be reduced. ENGINE will manifest its power when it is applied to the whole GODB of more than 2,1 million gene products from more than 100000 organisms. The data produced by this search is planed to be available as a supplement to the GO database as soon as we are able to provide regular updates.
Gene ontology (GO) [1–4], with the corresponding associations with the gene products, is becoming a very valuable and important form of knowledge in bioinformatics. GO is already frequently used to analyse and cluster results of many bioinformatics applications and especially high-throughput applications . Such tools are mainly used to elaborate an overrepresentation of a few functions and processes in a large list of gene products in order to provide clues as to what the gene products in the list might have in common and to better understand the biological background of the biological experiments under investigation.
The GO model is a directed acyclic graph (DAG) in which the terms and the term-to-term relationships provide the conceptualisation of the biological domain of knowledge . The knowledge is split into three topics (term types), namely 'biological process', 'molecular function' and 'cellular component' and therefore into three independent DAGs, used to describe gene products for all organisms. A repository of the current GO terms and gene products with GO associations is frequently compiled in a MySQL database, the GO database (GODB) .
Collaborating institutions maintaining the major biological databases provide sets of data consisting of links between the database entries and GO terms, the so-called associations. These associations are well documented and characterized by the type of evidence supporting the association. High-quality associations are available, structured into 13 classes, normally based on a curatorial review of the literature, experimental evidence or computational analysis methods. Many associations were made using a number of different automatic comparative methods covering both model and less experimentally traceable organisms. More information about evidence classes can be found on the Gene Ontology web site .
GO is a recent effort to provide a unique description of gene products from a wide range of different organisms and it is therefore still heterogenic in terms of precision and reliability. Since experimental information is often missing, gene products from less well-studied organisms often inherit low level GO terms from orthologous gene products of well-studied organisms such as human or mouse. Therefore the precision and reliability of such descriptions are much lower and this influences the quality of knowledge of the GO.
However, with the increasing number of gene products described using GO terminology and the daily increase in the precision of their description, GO will play an ever more important role in comparing as well as establishing links between gene products, of the same or across different organisms, on the level of functionality. Finding gene products from different species with similar functionality, or those involved within biological processes similar to the gene product in which they are interested, will benefit researchers in many fields.
GRID computing is a quickly evolving technology driven by several initiatives all over the world. In Europe the EGEE (Enabling Grids for E-sciencE) project  is the major driving force, beside smaller but no less important national projects, to build on recent advances in GRID technology and build a service GRID infrastructure which is available to scientists 24 hours a day. In recent years the GRID service has become a technique for users such as physicists, chemists and biologists. In brief, the computational GRID connects under unique middleware a certain number of computers representing the resources for computation and storage. The connection is loose, as all the computers involved are still independent. Jobs are submitted to the GRID by means of the User Interface (UI). After submission, computers dedicated to job submission management, known as resource brokers (RB), distribute the jobs to free computers, the worker nodes (WN), for execution. In this way a large number of computational resources can be formed, such as the EGEE infrastructure connecting more than 25000 CPUs ; it is theoretically possible to use all these computational resources for a single problem with a large number of jobs. However, the EGEE infrastructure is divided into virtual organizations (VO), and for biological and biomedical applications a VO 'biomed' has been created, recently reaching a total of more than 5000 CPUs.
In our study we presented Gen e Analog ue Fin de r (ENGINE), an application of the GO to compare gene products at the level of their description and to suggest gene products that are functionally analogous to each other. Conventional methods of comparing different gene products are principally based on a comparison at the level of the corresponding sequences. According to the sequence similarity, the gene products are considered similar also in respect to their function. However, the "sequence – function" correlation is only partially applicable. With ENGINE, using the GO, we are able to compile comparisons between gene products on the level of their descriptions, profiting from the large and continuously increasing knowledge about all the annotated gene products.
Such a comparison [SGC1] within such a large amount of gene products already associated to GO terms, and the resulting high number of associations, the search has become a data- and process-demanding task and would occupy our cluster for months or even years. The approach we were followed to solve this resource problem was to distribute the MySQL database GODB over the available computational GRID resources, paralleling the search process and reducing the load on the single computers involved to several hours, processing the total search in about 3 days.
Hence, we have demonstrated the potential of the GO to find functionally analogous gene products and the power of the computational GRID to solve such large data comparisons.
To calculate similarity between gene products based on gene ontology (GO), we cannot consider only the associated gene ontology terms (GO terms). Apparently different associated terms might share parental terms with similar global functionality. To profit from this information we need to search for all the parental terms of the associated terms; in other words, we need to build the paths from the associated terms to the root of the tree, and then compare the whole paths of associated GO terms between two gene products. All the path's GO terms different from the directly associated ones are called indirectly associated terms. The advantage of this approach over a previously proposed one in which only the first common parent was used for the comparison  lies in the observation that a longer path characterizing an associated GO term corresponds to better knowledge of the specific gene product as well as the corresponding functions and processes the gene product is involved in. Using all members in the path for a comparison of two gene products, the similarity value increases when more terms are shared between the two gene products, but it also decreases when many terms not in common are present. With this approach of using the path for the comparison we take into account all the known knowledge. However, just comparing the number of common and non-common terms is not an accurate approach, since the information content of different GO terms is different and should be weighted accordingly.
Moving along the path of a specific GO term away from the root, the detail of the information of a given term increases from node to node. The specificity of information is directly dependent upon the level of the node within the path, but it is not comparable between two different paths. A GO term at level 6 in one path can be much less descriptive than a term at the same level in another path. Therefore, using the level within a path as a measurement of similarity is a poor technique. One method of determining the semantic similarity of two terms is to examine how frequently those terms are used to describe different gene products [9, 10] considering the notion of 'information content'. The less a term of a vocabulary is used the higher the information content and the more descriptive it is.
We therefore calculated the probability p(term) for every term by counting the number of gene products associated with a term or any of its children, divided by the number of total associations between the GO terms and gene products. Information content (detail level of the description) is inversely proportional to p(term) (Table 1). The highest p(term) values are found for GO terms 'molecular function', 'biological process' and 'cellular component', which are the roots of the three DAGs, however, their p(term) value is not 1 (Table 1), since not every gene product has an association with all three term types. Table 1 demonstrates that terms of the same level in different paths can have clearly different information content and therefore different p(term) values. The p(term) value was then used as a weight within the statistical analysis and entered as 1-p(term) to obtain an additive weight system for high 'information content' GO terms.
Examples of GO terms and their level in the tree are listed including their frequency of use (count) to describe gene products and the corresponding p(term) value.
The non-parametric χ2 – test is a typical statistical test used to compare two different samples, in our case two gene products A and B, according to some characteristics or aspects, in our case the GO terms directly or indirectly associated with the gene products. Since every gene product can be described using a different number of GO terms, the table of values was designed as a 2 × 2 array containing the sum of 1-p(term) of present or absent GO terms according to the two compared gene products. (Table 2) . In this way we have the same degree of freedom for all gene-product-to-gene-product comparisons; therefore the χ2 – values are comparable. All three term-types were taken into account for the main search in order to increase the total description and to enable separation of, for example, two gene products with the same function acting in different cellular components. However, we also calculated the statistics for each separate term-type to have a 'molecular function', 'biological process' and 'cellular component' specific comparison to find functional analogues based only on one term-type. This is an example of how our method can be used to find gene products exhibiting a particular functionality which is independent of their cellular localization.
The 2 × 2 array used for the χ2 – calculation to compare gene product A with gene product B.
To reduce the vast amount of output data, we stored only the best 100 hits in the output file, including, according to a pre-evaluation of the algorithm (data not shown), the most significant candidates for a functional analogy. The best 100 hits were chosen by sorting the components of the total output list by their χ2 – squared values and selecting the 100 highest values.
The version of the GO database (GODB) used for the present study (version 2005-11-1) contained 20088 terms within the three trees. Those terms described more than 1760000 gene products with more than 7200000 associations.
To ensure that for all gene products we found the best functional analogues within the whole GODB, the GO terms of one gene product should have been compared with all other gene products in the GODB. However, many gene products are associated with only a few and/or low 'information content' GO terms. A previous test run comparing more than 100000 gene products showed that those with fewer than 15 directly or indirectly (parents) associated GO terms should not be considered by the search for the first 100 best hits (unpublished data). For this reason, all gene products with 15 or fewer directly or indirectly associated GO terms were eliminated from both the input list and the total list of gene products with GO terms associated. With this restriction, the total gene product list of 1763776 entries was drastically reduced to 1076279 gene products (61% of total). Our input list included all gene products related to 13 fully sequenced organisms annotated within Ensembl , namely Caenorhabditis elegans, Caenorhabditis briggsae, Anopheles gambiae (African malaria mosquito), Drosophila melanogaster (fruit fly), Apis mellifera (honey bee), Danio rerio (zebrafish), Gallus gallus (chicken), Pan troglodytes (chimpanzee), Homo sapiens (human), Mus musculus (house mouse), Rattus norvegicus (Norway rat), Takifugu rubripes, and Tetraodon biocellatus. A total of 125791 gene products in the GODB belong to these organisms. Applying the '15 directly or indirectly associated GO terms' rule results in a final input list of 79125 gene products (63% of candidates). Therefore the search compares 79125 with 1076279 gene products, resulting in more than 85 billion comparisons.
The algorithm for the statistical comparison of two gene products according to their description was implemented in Perl. The necessary information was retrieved by accessing the GODB by means of the Perl 'DBI' modules, while the 'Statistics_chisquare' module was used for the χ2 – calculation . The analysis of one gene product against all other selected gene products occupies one CPU (1.0 GHz Pentium III) for between 30 and 45 min., depending on the number of associated GO terms. The analysis of all 79125 gene products would require approximately 5 CPU-years.
Due to the enormous quantity of computer resources available, the GRID enables splitting a large, complex application into many smaller jobs running in parallel, greatly reducing execution time. For this specific case, however, splitting the full search into several smaller jobs does not increase the speed of the search, because the limiting factor is the limited bandwidth of the single database which contains all the required information. Improving the performance of the search application will require increasing the number of data sources; the best possible performance will be obtained by providing a database server for each job running on the GRID.
An important new capacity of ENGINE is its ability to distribute and temporally install a relational database such as MySQL on the same WN on the GRID where ENGINE is running. In most applications simple files are distributed and used for calculation. ENGINE can distribute and install on each WN the GODB downloaded from the godatabase site without further modification, thus reducing maintenance time for the application. A locally installed database not only drastically reduces processing time, since there is no competition between several parallel queries, but also there is and no network transition time, which is very important for data-access intensive processes.
The INFN production GRID  was used for the search. Its primary scope is to provide computational resources to INFN high-energy physics experiments, but it is also open to other sciences. It is part of the EGEE infrastructure, comprising more than 20 sites all over Italy and, at the time of the search, integrating more than 1500 CPUs, mostly Pentium IIIs and IVs or equivalents, all running the Linux Red Hat 7.3 operating system. Most of the farms were using Open-PBS  as their local batch system, while some used LSF . The GRID middleware was LCG2.6 .
That functionally equivalent computers, all running the same operation system, were used throughout the GRID infrastructure helped simplify the database installation procedure; a static linked binary MySQL server was used. To guarantee faster data installation, the database content was transferred from the central repository to the worker nodes using the MySQL binary format. Before the actual search job was started, a bash script, launched on the WN, performed the entire installation procedure by executing all needed operations in a well-defined order and by making all necessary checks to verify whether the created environment was adequate to run the job.
After installing the database, ENGINE installs and sets up the Perl libraries for use by the ENGINE Perl script. Since the use of Perl and its modules is very common in bioinformatics, this type of distributed installation may also be of interest for other applications.
The installation procedure described above was executed without incident on all sites of the INFN production GRID infrastructure which support virtual organization (VO) "bio".
To perform the analogous genes search, the entire list of reference gene products (79125) was split into sub-lists of 20 gene products each. The number of gene products per job was chosen to produce jobs with execution times short enough to avoid problems due to accidental hardware or software crashes, but long enough to keep environment set-up time negligible compared to the total job execution time. With the chosen number of genes, the jobs lasted ten hours on average, while environment set up time was on the order of only 6% of job execution time.
The jobs were submitted by means of a Perl script, running on the User Interface (UI), which first created the job input file with the sub-list of gene products assigned to that particular job by splitting the full list of reference gene products. Then the job description file (jdl file) was created with appropriate input and output file names, which varied from job to job for bookkeeping reasons. Finally, the script consecutively submitted each job, with its corresponding input file, bash script, and jdl file, for parallel execution. It also initialized the monitoring of the job by activating JAM, a Job and Application Monitoring tool . JAM made it possible to follow the steps performed by the bash script during the WN environment installation phase and to keep track in real time of all gene products already examined by all jobs running on the GRID. JAM registered all failed comparisons, which were then re-submitted to successfully complete the full search.
At fixed time intervals, output files produced by completed jobs were retrieved and checked for missing information caused by job failures. A different Perl script was used to identify the missing genes, to generate new lists with those gene products and to re-submit jobs to complete the whole search.
In Figure 1 a schematic view of the different processes is shown, including job submission, creation of the local running environment (MySQL server installation and database population), job monitoring (by JAM) and data retrieval.
Job submission schema and data flow. A job is initiated at the user interface (UI) and forwarded by the resource broker (RB) to the worker nodes or farms. In parallel a job monitoring procedure (JAM) is started to test the success of the executed job. The execution on the farms firstly initiates a download of the required data from a storage element (SE) followed by the effective computing. Then the results can be recovered from the farm via the UI.
The search for the analogous candidates for the list of reference gene products (79125) required the submission of a total of 5200 jobs to the GRID, each with 20 gene products as search input. The jobs were distributed to as many as 950 WN assigned by the Resource Broker. Failed jobs (about 16%) were restarted. Total computing time was more than 52000 CPU hours (~ 6 CPU years), including the time needed to set up the running environment, data base and library installations (6% of overall job length). The search was completed in about three days. The acceleration of the process was about 580 times, taking into account the re-running of failed processes, the time for necessary installations per job, and that not all those 950 WN were available at any time.
To demonstrate the value of the search results, we performed a variety of different analyses on the data. One measure of how well a gene product is described, among others, is the number of other gene products having exactly the same description; the description of a gene product is the non-redundant list of all directly and indirectly associated GO terms. We divided the results into three groups according to the number of identically annotated gene products. Group 1 (26587; 33.6%) comprised those analyzed gene products which had a unique description. In group 2 (10251; 13.0%), the analyzed gene products shared exactly the same description with fewer than 100 other gene products, and in group 3 (42286; 53.4%), more than 100 other gene products. About half of the gene products (groups 1 and 2) have quite detailed descriptions, which makes it possible to distinguish them from the majority of the analysed gene products. This proportion should increase for each new GODB release, since the list of GO terms is increasing and, more importantly, the quality and the number of associations are improving.
Another measure of the quality of the description is the total number of directly and indirectly associated terms (parents). As mentioned before, as the total number of directly and indirectly associated terms increases, the gene product's description becomes more detailed; therefore, the more common terms two gene products share, the higher the quality of the comparison. The average number of common terms in group 1 is higher than within the other groups but decreases with increasing ranking number of the hits (Figure 2). However, the first 25 ranks still have a higher average number of common terms than groups 2 and 3, demonstrating that the quality of comparison is higher in group 1 than in groups 2 and 3.
Common term distribution. The average number of common terms between the input gene product and the analogous gene product found is plotted against the ranking of hits. Group 1 members are plotted in yellow, group 2 in purple, and group 3 in blue. x-axis: Ranking of the search hits according the χ2 – value; y-axis: Average of total common terms between the input gene product associations and the hit gene product associations.
The same analysis, carried out individually for term types 'molecular function' and 'biological process', clearly showed that the combination of the three term types produces a much better description than any term type alone. For example, by using only term type 'biological process', the search found that 95% (75442) of the input gene products were described by GO terms of type 'biological process'. Of this number, only 17.2% (12943) belonged to group 1, 14.0% (10571) to group 2 and the majority, 68.8% (51928) to group 3. By using only term type 'molecular function', the corresponding values were as follows: 94% (74088) had association terms of type 'molecular function', 12.3% (9092) of which belonged to group 1, 20.1% (14882) to group 2, and 67.6% (50114) to group 3. Limiting the comparison to only a single term type, the number of significantly described gene products (groups 1 and 2) dropped drastically. However, we expect that the improvement of the GO and its associations will increase the percentage of well described gene products, i.e., those falling in groups 1 and 2.
These latter results also confirmed the success of the '15 directly or indirectly associated GO terms' rule to eliminate the low level described gene products before the search; most of the gene products have associations with GO terms of all term types. Of the total number of gene products covering the chosen species, only 89% had an association to term type 'molecular function' terms and only 76% to term type 'biological process' terms. Those values were increased to 94% and 95%, respectively, when the '15 directly or indirectly associated GO terms' rule was applied.
Another measure of the quality of the search results is an analysis of the frequency of use of the involved types of evidence. There are 13 different codes for the type of evidence validating the GO association, of which 8 are based on experimental information and 3 on computational methods (Table 3). The more types of evidence based on experimental information are involved in our comparative analysis, the more the search results differ from computational methods based on sequence comparison, and the more biological information influences our functional analogy search.
Description of the evidence code and assignment to experimental or computational methods.
A graphic was compiled with an average frequency of use of every type of evidence code at every position of the ranking of the best 100 hits (Figure 3). This graph demonstrates that the evidence 'Inferred from Electronic Annotation' (code IEA) is the most used type of evidence and that it is equally applied throughout all three groups we defined above. The IEA evidence is critical, since it can add valuable additional information to the gene product description, but it can also add incorrect information due to incorrect assumptions. However, it is more important that the frequency of use of all experimental evidence codes such as 'Traceable or Non-traceable Author Statements' (TAS or NAS) are significantly higher in the first two groups to validate our results in those groups. Furthermore, the frequency of use drops towards the end of the ranking, indicating a decrease not only in the similarity but also in the specificity and number of descriptions. In group 3, evidence codes such as IEA and ISS are more prominent, pointing out that the electronically associated GO terms are overrepresented in gene products with poorer descriptions. In group 2, most of the frequencies of use of the experimental evidence behave similarly to the group 1 members and therefore can be evaluated as significantly described gene products. This evidence code usage speaks in favour of our analysis of analogous gene products, showing that the significant hits (groups 1 and 2) are dominated by experimental evidence and that they clearly distinguish their information content from sequence comparison.
Frequency of evidence codes. The average frequencies of use of the 13 evidence codes are plotted against the ranking of the hits. For every evidence code the frequencies were split according to the three groups 1 (blue), 2 (purple) and 3 (yellow). x-axis: evidence code and the corresponding first 100 ranks for each evidence code (see Table 2), y-axis: frequency of usage of the evidence codes.
Both analyses of the nature of the GO show that the state of knowledge is mature for running comparative analysis but that it is not yet sufficient to efficiently include data from the whole set of gene products. However, and more importantly, we demonstrate that the GO has the potential to harbour knowledge for such an analysis.
For quality control on a biological level, we analyzed two gene products: BCL2_HUMAN [UniProt: P10415], a well studied apoptosis gene; and Q88869_MIDDV [UniProt: Q88869] a non-structural polyprotein gene of a mosquito alphavirus, the Middelburg virus. The latter represents a well described gene product of a non well known organism, which adds valuable information to a functional analogue search. We limited this analysis to the 30 best hits. Table 4 lists a collection of information describing the biology of the 30 best suggested analogous gene products of BCL2_HUMAN. Firstly, BCL2_HUMAN was found as the only best hit and therefore is a well-described gene product. Within the 30 best hits we found 12 other gene products which, according to the protein family database (Pfam) [19, 20], belong to the same family, the Bcl-2 family. 4 gene products belong to another apoptosis protein family, the apoptosis inhibitory protein 5 (API5) family. This demonstrates how ENGINE can find members of the same or of a similar protein family, which is an important confirmation of our algorithm. It is important to mention that members of gene families within Pfam are assigned by sequence similarity and therefore can be found by sequence based approaches. Focusing on the Bcl-2 family, ENGINE found 5 out of 6 BCL2 orthologous gene products present in the SwissProt database [21–23] with high sequence similarity (Figure 4a, line). Only the mouse orthologue was missing. It seems that there were problems in the mouse association data set of the GODB we used; therefore, it was hard to find any mouse analogues in any search. This problem will be resolved by a future update of our search results, which will use a new version of the GODB.
The table contains the following information: The ranking of the potential functional analogues of BCL2_HUMAN according the χ2 – value, the gene name and the UniProt accession number, the χ2 – value, the number of common terms between a hit and BCL2_HUMAN, the Pfam name with short domain description the gene product belongs to, the organism the gene products is from, and the local alignment characteristics, such as hit length and the % identity of the hit, of the alignment between BCL2_HUMAN and the hit sequence.
Sequence identity versus number of common and non-common GO terms. A comparison of the sequence similarity is plotted together with the percentage of common terms (purple columns) and the non-common terms (blue columns) of potential functional analogues of a) BCL2_HUMAN and b) Q88869_MIDDV. The percentages of the common terms are in relation to the number of terms associated to a) BCL2_HUMAN and b) Q88869_MIDDV, whereas the percentage of the non-common term is calculated in relation to the total associated terms of the same gene product. x-axis: gene products with decreasing ranking; y-axis: percentage of common or non-common terms and percentage of sequence identity.
Most Bcl2 orthologues, however, have a significantly lower-than-maximum χ2 – value. Figure 4a shows the number of common (purple columns) and non-common (blue columns) terms and indicates that those orthologues do not have nearly as many associated terms as do the BCL2_HUMAN and the rat orthologues. An examination of the evidence code for these associations shows that the orthologous ones inherited the GO terms from well described orthologues, often via common functional domains, and are not yet as well described by experimental evidence as are the human and rat Bcl2. Figure 4a also shows that most of the gene products within the first 30 ranks have 50% or more terms in common with BCL2_HUMAN but the χ2 – value is reduced because of the high number of non-common terms pointing out other functions than those shared with BCL2_HUMAN.
Among the 13 non-Bcl-2 and non-API5 gene products, 8 are, according to their gene descriptions, related to apoptosis, 1 oncogene homolog, 3 inflammation related and one unknown gene product. Evaluating the common GO terms we find in all, except in the inflammation related gene products, terms related to apoptosis and more specific anti-apoptosis. The inflammation related gene products have terms linked to regulation of cell proliferation in common with BCL2_HUMAN.
Comparing the results by means of sequence similarity (Figure 4a, line), it becomes clear that apart from the orthologous gene products, all sequences have a similarity value below 0.5; for genes products not belonging to the Bcl-2 family the value is below 0.2. Therefore it is very difficult to define them as 'similar to BCL2_HUMAN' according to the sequence comparison; they were selected by ENGINE because of their similar description.
The second example, Q88869_MIDDV, is illustrated in Table 5, a collection of information about analogous gene products. Q88869_MIDDV also has a unique description and appears to be the best hit. This example was chosen because it is an example of a well described gene product from a non-model organism having non-electronic evidence for all its associated terms. Since Q88869_MIDDV is a short gene product (37 amino acids), there are no known protein domains reported (Table 5); a tblastn search found only fragments of other virus which have mostly GO associations to RNA polymerase activity and RNA processing (data not shown). However, with the help of ENGINE, and because the researcher had communicated some experimental information to GOA, we could find functionally analogous gene products with a similar GO term profile in organisms such as human, rat, mouse, Arabidopsis, fruitfly (as a representative of insects), and the protozoan cause of the sleeping disease, Trypanosoma brucei; a total of 10 different organisms. Q88869_MIDDV has general functional annotations such as 'transporter activity' and 'protein binding', is involved in more specific processes such as 'protein targeting' and 'endosome transport', and has the specific locus descriptions 'endosome' and 'trans-Golgi network transport vesicle membrane'. Functional analogues ranked 2 and 3 (a human and a rat endosomic gene product with a RasGTP effectors domain) have almost identical term profiles, as confirmed by their χ2 – values. However, sequence similarity is very low (Figure 4b) and it would be improbable to find them using a sequence based approach. All other hits are involved in a kind of vesicle transport activity, which can be deduced from the kinds of domains those gene products contain, with some common directly associated terms and mostly common parental terms. This example demonstrates that ENGINE can assist a scientist with a gene product with experimental annotations to find functionally similar gene products, which could provide further information for future experiment planning.
The table contains the following information: The ranking of the potential functional analogues of Q88869_MIDDV according the χ2 - value, the gene name and the UniProt accession number, the χ2 - value, the number of common terms between a hit and Q88869_MIDDV, the Pfam name with short domain description the gene product belongs to, the organism the gene products is from, and the local alignment characteristics, such as hit length and the % identity of the hit, of the alignment between Q88869_MIDDV and the hit sequence.
In both test gene products we found hits in more than 10 different organisms, proving that ENGINE finds functionally similar gene products across several organisms, not only human or model organisms.
ENGINE was compared with the GO-family tool, a member of the long list of tools using GO, which calculates a functional similarity measurement using the GO. The GO-family tool is part of the package called GOToolBox , that uses a statistical method to compare two gene products according to their descriptions via the GO and calculates a list of functionally similar gene products for a gene product of interest.
GO-family is limited to 7 organisms, all of them model organisms (Arabidopsis thaliana, Caenorhabditis elegans, Drosophila melanogaster, Homo sapiens, Mus musculus, Rattus norvegicus, Saccharomyces cerevisiae), whereas ENGINE compares the gene products from 13 model organisms with gene products of all available organisms within the GODB.
GO-family uses the method of DICE distance (alias Sorensen, Czekanowski), giving double-weighting to the common terms, whereas ENGINE uses a χ2 – approach, including a semantic measurement to weight the information content of each term used for the comparison.
A common search was performed with both tools for the BCL2_HUMAN gene product. Comparing only the 30 best hits shows that only 7 gene products are in common, and they all belong to the Pfam BCL2 protein family. Further, ENGINE finds 14 BCL2 family members, whereas GO-family finds 7; ENGINE's 30 best hits contain gene products from 8 different protein families, whereas the output from GO-family is distributed over 14 protein families; and ENGINE's output contains gene products from 8 different species, whereas the output of GO-family is from 4 different species.
With ENGINE we demonstrate that GO has the potential to be used not only for analysis of biological data but also directly for comparative researches like the search for functional analogues we implemented in ENGINE. When compared with other similar tools, in particular with the GO-family tool, we find that ENGINE provides different and complementary information.
However, it is important to mention that although there is a large space of knowledge provided by the GO, there are still limitations for an optimal comparative analysis. Too many gene products and mainly from non-model organisms have low level and/or prevalently electronically evaluated associations. For this reasons too many gene products have an identical description: only additional experimental knowledge will differentiate those gene products from each other. There is also a certain redundancy for the same biological abstraction leading to a separation of the same biological function and therefore also to the separation of the corresponding gene products. This limitation of the GO has to be taken in account, also from the side of all other tools using this knowledge. Due to the fact that GO is daily updated, it is conceivable that most of these problems will progressively be reduced. It is worth to state again that additional effort is required to improve the GO by adding more experimental information for non-model organisms and really push the GO over the crucial limit for being used for optimal comparative analysis.
The run of ENGINE over the GRID showed to be highly effective: the functional analogy search was divided in a large number of jobs and distributed over the INFN production GRID to reduce the processing time from about 5 years on a single machine to about 3 days occupying up to 950 worker nodes. The acceleration of the process was measured to be 580 times. The prototype framework used by ENGINE for the remote installation of the MySQL DB and of the Perl Library, the application monitor performed by JAM and the job submitting mechanism showed to be highly reliable and quite general to be applied in other bioinformatics applications as well as in other research fields.
Recently we have been working on a new version of ENGINE applicable to the steadily increasing whole set of more than 2 millions gene products in the GODB using the GRID infrastructure of EGEE, and, importantly, an efficient updating procedure to profit from the new monthly GODB versions and increasing knowledge to be able to provide with the same frequency the new search data.
Angelica Tulipano, Giacinto Donvito contributed equally to this work.
We are grateful to Prof. C. Saccone and Prof. G. Pesole for careful reading, corrections, and making constructive comments on the manuscript. We also thank Richard Lusardi and Stan Clark for the English corrections. We would also like to thank the INFN production GRID Resource Centres administrators and the INFN-GRID/GRID.IT management.
This work was partially supported by grants for ITB from MIUR: FIRB 2003 art. 8 D.D. 2187 del 12-12-2003 LIBI, and by the BIOINFOGRID project (INFSO-RI-026808) and for INFN by the INFN-GRID project and by the EGEE project (INFSO-RI-508833).
AT was responsible for the feasibility study, the development of the Perl script to calculate the statistical comparison of the gene products and writing part of the manuscript. GD was responsible for the development of the GRID technology part and writing part of the manuscript. FL was responsible for adjustment and update of the gene ontology database. GM was involved in the development of the GRID technology part and writing the manuscript. AG guided the project, was involved in the development of the Perl script to calculate the statistical comparison of the gene products and writing the manuscript. All authors read and approved the final manuscript.


A new project I've been working on since the start of 2017, has just launched and is available for listening today on iTunes!
Beyond the Studio is a podcast about the business of being an artist, co-hosted by myself and fellow artist Amanda Adams of Close Call Studio.
"Beyond the Studio focuses on the behind the scenes work of visual artists—how they're supporting and sustaining themselves and their creative work. It features candid conversations about their business practices, time management, financial planning, and how they're navigating the unique challenges of making a living, creatively.
I'd love it if you gave it a listen, and let us know what you think! We have been interviewing artists we know and admire, and can't wait to share more honest conversations with artists, makers, and business experts on the work that goes on beyond the studio.
You can listen to our first three episodes today by subscribing to the podcast on iTunes, Soundcloud, or streaming here on our website beyondthe.studio.
Sign up for Beyond the Studio's mailing list to stay in the loop about the show, and follow us on Facebook or Instagram to stay plugged in to the conversation!
Thanks for supporting this new venture!


I am building a Robot that can find, pick, and sort coca-cola plastic and glass bottles and aluminum cans. Any sugestions on how to do the sorting? I have some ideas such as using a scale, camera for color etc. But I read something about possibly using feedback from my arm servo.
Like if youre a beginner, sorry to say dude but forget about it.
Well checkout airman00's butler robot...its really cool It might give you some ideas.
The robot arm could be simple or highly specialized, depending how much work you want to do. Try reading Admin's robot arm tutorial first (he talks about visual servoing and other important concepts). Because you'll be working with bottles and cans the arm doesn't have to be super heavy duty. Go to http://www.lynxmotion.com/, they sell robot arms (ironically, they show pictures of them picking up coke cans).
This should help you get started.
Every thing you listed has bar codes perhaps you could use that to identify them. You would still need to figure out how to locate them to pick them up and get them oriented so you could read the bar code. Course figuring out how to implement a bar code reader might be a hassle too! I just thought I would throw the idea out there since it popped in my head at work last night.
If all the bottles are right side up, you can use a simple Sharp IR and measure height of each (they all have different heights that are easy to measure).
I am actually a instructor. I am ssisting some students in this project. I have some experience with BS2 microcontrollers (Boebots, SumoBots etc).
There are discrete color sensors you can purchase. I believe they do have a specific range, so possibly adding them to an arm would be a good way of getting them in the specified range.
google color sensors, also here is a link to Society of Robots color sensor tutorial.


text:
The WGVU Morning Show
Tours Around Michigan
WGVU News | By Shelley Irwin
Published September 17, 2020 at 9:15 AM EDT
Tours Around Michigan, Tour enthusiast Candice Smith Fleszar discussing the latest when it comes to getting to know your own backyard, including the cemetary.
The WGVU Morning Show Tours Around Michigan
Shelley Irwin
Shelley Irwin is the host and producer for The WGVU Morning Show, a newsmagazine talk-show format on the local NPR affiliate Monday through Friday. The show, broadcast from 9 a.m. to 11 a.m. features a wide variety of local and national newsmakers, plus special features.
See stories by Shelley Irwin

redpajama_set_name: RedPajamaCommonCrawl


Lizenz: CC BY-SA 2.0 DE.
The dimension of affine Deligne-Lusztig varieties in the affine Grassmannian of unramified groups, International Mathematical Research Notices, IMRN 2015, no. 23, pp. 12804–12839 (preprint).
The p-rank stratification on the Siegel moduli space with Iwahori level structure, Manuscripta Mathematica 143 (2014) , pp. 51-80 (preprint).
Kleine AG "Algebraische Geometrie und Zahlentheorie"


text:
No Secrets
Coven of the Wolf, Book 4
Rae Morgan
October, Bear Hollow, Tennessee
Cindy Long hurried down the dimly lit forest path. The full moon glowed eerily red overhead and barely provided enough light for her to distinguish the shadows from the trees.
According to her best friend, Tad Benton, the October full moon was named the Blood Moon because the Ancients made offerings to it as they hunted wild animals and slaughtered domestic ones in preparation for the long winter ahead. Tad knew all sorts of neat stuff. Listening to his stories of the Ancients was one of the reasons why she was out past her curfew. That, and because Tad was tall, lean, and extremely good-looking—not that she'd ever assume he'd want to date her, but a girl could always hope.
Glancing at the lighted dial on her watch, Cindy groaned. Her dad would ground her for a week—unless she could sneak in through her bedroom window. Heck, being grounded would be the least of her worries. More than likely, he'd tan her bottom if he ever found out that she'd been out with Tad and his friends. Her dad didn't like the new "element" that had moved into town late last summer, after the rescue of Selena Jones by Sheriff Teague and the hunky Gor Petrov. Her dad thought all the members of the Drake, Ltd. organic farming commune were loonies and unfit companions for his seventeen-year-old daughter.
Cindy just thought they were cool. Especially Tad.
She reached the fork in the trail that would break away from the woods. As she stepped onto the path that led home, she caught the scent of something chemical—something hot—on the night breeze. It smelled smoky. Was someone cooking out? Didn't the idiots realize there was a "no open burning" rule in effect? The forests were so dry that the slightest spark could start a forest fire. And why did the smoke smell so strange, more like a chemistry lab than a wienie roast? Was someone deliberately setting a fire?
No matter what was burning, it was dangerous. Cindy decided to investigate. If someone was breaking the law, she could tell her forest ranger dad, and maybe he would cut her some slack on her curfew violation.
Cindy left the well-trodden public pathway. Following her nose, she carefully picked her way through brittle undergrowth and fallen leaves. Ahead she could make out the warm yellow glow of a fire. Inhaling sharply, she could now identify some of the chemical odors—one was definitely ammonia. Another smell overlay it, but was less easily named. Was it something she'd smelled in the school lab? Another strong sniff and she had it! It smelled like the nail polish remover at Nancy's Nails and Tips.
What would someone be doing in the forest in the middle of the night cooking chemicals? Not only was it dangerous—it was weird. Her curiosity totally engaged, she slid through the spindly new tree growth and rhododendron bushes, careful not to make any unnecessary sounds. Some primordial instinct told her not to be observed by whoever was out there.
Using a large oak as cover, she peered around the trunk.
The scene looked like something out of a Friday the 13th movie—or Hell itself. Four dark male shapes hovered around a large brick fire pit. Suspended over the orange-yellow flames was a large shiny pot. A pile of red and white boxes lay strewn around the men's feet. The boxes were easily recognizable—Sudafed. Large glass bottles containing some sort of clear liquid sat off to the side, barely illuminated by the fire. She couldn't make out the labels, but the smell of ammonia was almost overpowering now, so it was a safe bet that some of the containers held the powerful cleaning compound.
A nagging memory tickled the back of her brain. Ammonia. Sudafed. And that chemical that was in nail polish remover, acid, no, acetone. The men were making crystal meth! She'd read about the process in the newspapers back in August when a kid from school had died from an overdose of the street drug. The "poor man's heroin," the reporter had called it.
Fear and excitement combined to settle in the pit of her stomach like a lump of indigestible meat. She had to get to Sheriff Teague. This was way more trouble than her dad was capable of handling. These men were criminals, not careless campers.
Cindy turned to leave the way she'd come.
"What have we here?" a shadowy shape in front of her intoned.
Cindy's scream was cut off when the cowl-robed speaker encircled her neck with his hands in a cruel grip, then pulled her to him. His cowl fell from his head, revealing his sharply cut features under the October full moon's glow. His dark eyes gleamed with wicked excitement. His teeth shone brightly in the moonlight. His thin lips twisted into a cruel smile. He was evil personified.
God, she was so in trouble.
Every night since Debby had left him in Southern Illinois, Boris visited and, like an incubus, made mad, passionate love to her. Never mind the fact her sensual tormentor was physically hundreds of miles away in Chicago and she was in the Smoky Mountains of Tennessee. Never mind that she'd told him repeatedly she didn't want him. Never mind that she'd reluctantly resorted to every defensive dark magick trick in the book, and some she'd made up, to forestall his nightly assault on her mind and body. He still visited and with only slight variations in technique, made carnal love to her on the highest levels of the astral plane.
Tonight he was late. Stupid fool that she was, she called him on it, as if she really cared. And she didn't! Of course she didn't.
"You're late. Hot date?" Debby said.
"You missed me, bébé?"
"No. In fact, I was relieved."
Boris snorted. "Liar. I'm growing on you, admit it, little hell cat."
Boris's astral body reached for her. Debby slapped his hand away and stepped back. Putting what she hoped was a look of disdain on her face, she drawled, "Growing on me? Yeah, like an icky, smelly fungus."
"Debby, my beloved one, you love me, but are just too stubborn to admit it."
"I don't love you, Bo. Get away from me…" She backpedaled and came up against a stone wall that hadn't been there two seconds earlier. That was the thing about dreams and the astral plane—real world physics went all to hell.
Trapped, she growled, "Get over yourself and leave me the hell alone. I'm sure there are lots of women in Chicago you can torment on a nightly basis. Some of us need our sleep, because we have a job to do."
"Actions speak louder than words, bébé. So let's see just how much you hate my love-making, eh?"
Within the space of a millisecond, Boris's astral body swept Debby's dream self into a garden on the astral plane, high above the psychic-vamps and unaware dreamers trolling the lower levels. Her clothes whisked away by his thoughts, Debby was open to his sensual assault, once again helpless to fight him off.
Each night it was the same. It was as if her astral body wouldn't listen to her higher brain, the part of herself that knew Boris and all that he represented was bad for her. Instead some primitive part of her psyche drove her dreams, allowing her to become a helpless victim to Boris's lovemaking.
Lately, in the pale gray of early morning after a night of indescribable, passionate sex, there were times she second-guessed herself. Maybe she was fighting Boris and herself far too hard. Maybe she could live with him, make a family, and perform magick. Then the bright dawn of reason arrived with the morning sun and she convinced herself yet again that turning her back on him and his magical world was the best thing she could do for herself—and for the world. Never again could she allow herself to lose control of the cursed powers she possessed. Yes, she'd helped rescue Selena, Gor, and Boris from the dark magician Darius, but the use of her powers, grown greater with age, both attracted and repelled her. Call her a coward, but she couldn't face the horrifying darkness within her.
So she'd run home to her safe little world.
The Coven followed her—and Boris wooed her nightly.
"Little one, you are not paying attention. I am nibbling your neck and stroking your pussy lips, but you are miles away. I am distraught."
Boris inserted a finger, then two, into her vaginal opening, stroking and spreading her wetness over her puffy labia. Every few seconds, he'd flick her needy clit as if to announce he was there and wasn't leaving until he got the reaction he desired. Horny, sensual bastard.
"Distraught? That'll be the day. If you must know, I was thinking of England."
Boris laughed. His lips moved from her hyper-sensitive neck to her turgid nipples. He licked, then bit first one and then the other until they were rosy and wet. All the while he increased the stroking of her sex. Already her body tightened as her arousal heightened. The tension was so great she had to remind herself to breathe, just as she fought not to react, not to allow him to control her body.
It was a useless battle. He'd proven in the past he could arouse her no matter how hard she tried not to respond. Each night she vowed to lie still like a stone statue, and each night she ended up moaning, groaning and shouting his name to the alternate reality sky. The only thing she'd been successful at was denying him the words he wished to hear—and even those had come pretty damn close to the surface. But somehow she'd managed not to give him the words of love he wanted so badly. She couldn't love him. She wouldn't allow it. It was too dangerous.
A long talented finger stroked her G-spot. Debby moaned. The man knew how to push her buttons. If the sex was this good out-of-body, she figured she'd never survive the real thing.
"Oh, you will not only survive, but beg for more, bébé. Let me fly to you this night. Let's take our love into the light of the real world."
"It's this or nothing, Bo."
"You can't stop me from visiting your dreams…"
"I'm working on it—don't count me out. My blocking is becoming stronger. You can't reach me any longer during the day. Admit it."
"As you say, I'm working on it, little cat. Don't count me out. I am a persistent man when there is something I want."
"You're a horny, overbearing, ruthless, obstinate Scorpio shifter is what you are."
"And you are my temperamental, slightly out of touch with reality Pisces match. It's that Taurus rising that makes you so damn stubborn, but we Scorpions are a tenacious bunch."
"My mother told you my birth sign!"
"Your mother knows excellent son-in-law material when she sees it."
"Forget that, she just wants grandchildren."
"And for you to use your Goddess-given abilities."
Debby groaned. Boris was correct. Her mother had been acting strangely ever since she'd met Boris. Lately, she'd taken up knitting baby things—in blue. No pink. No yellow. Just blue. And she made duplicates of everything.
She was scared. Her mother had foreseen something and wasn't telling her only daughter. Debby's precognitive abilities were useless when it came to her own future, and Boris's future was shrouded in a mysterious dark mist she couldn't penetrate—or was afraid to.
Debby was also afraid Boris knew exactly what it was that her mother hid. It was a damn conspiracy.
"Your mother is an uncommonly intelligent woman—you should listen to her for a change."
And he did—on her inner thigh, then worked his way with nibbling little kisses to her labia, now supersensitive from his finger's ministrations.
"Come for me, Debby. Give me your moans, your sweet cries of passion. Tell me you're mine."
Boris took her clit between his lips and sucked—hard.
Debby fell into a deep pool of whirling sensation as wave after wave of orgiastic pleasure surged across her body. As waves turned to ripples, Boris placed his engorged cock at her opening and surged inside, beginning the rhythm that would take her to the top once more. Groaning, she lay back and allowed him to sweep her to the stars again. She couldn't fight him. It felt too good. And, after all, it was just out-of-body sex—not the real thing. She could always get her REM sleep later.
As Boris came into her, he shouted, "Je t'aime, bébé."
Debby gritted her teeth against the love words ready to come out of her mouth and instead groaned in the back of her throat as she reached her peak soon after his.
"Give me the words, little cat." Boris's etheric self breathed his plea against the damp hair above her ear. "You know we are meant to be life partners. It is preordained. We can work together on your magical control. Work on containing your shadow-self. I would never let you hurt anyone or yourself. Trust me. Love me."
Debby heard the truth in Boris's words. The pleading. The proud Scorpio male allowing himself to beg called to the Piscean need to please a lover. She wanted to give him the words, wanted to please him, to be what he wanted. But the Taurean aspect of her nature, the cautious stubborn side that had allowed her to deny her magick, deny her strong shadow-self, forced the words to stick in her throat.
Instead, she said, "Bo, I'm tired—please…"
Whatever she would've said next was cut off by the sound of her beeper. She was very much afraid that the sound of the beep had saved her from weeping and begging Boris to leave her alone.
Fully awake now, she sat up in bed. She sensed the dampness between her legs, felt the lingering soreness of strenuous sex. Reaching for the beeper, she wondered how OBE sex could feel so real. She'd have to research that. Maybe Selena would know. Now that the shaman had helped her mother become stronger and forced her mother's cancer into remission, Debby didn't fear the woman so much.
The beeper readout had the Sheriff's Office dispatch phone number. Duty called—and tired as she was, she was grateful for the interruption. She'd been too damn close to giving Boris what he wanted tonight. One or two more orgasms and she'd have been vowing love, devotion, and the willingness to have his pups. She was so not ready for any of that.
As she dialed the night-shift dispatcher, a shiver of atavistic fear crawled down her spine. Something told her she wasn't ready for whatever called her out of her bed, either.
"You can't ignore this any longer, Debby."
Debby tuned out Gor Petrov's statement and concentrated instead on the brutally tortured body of a young girl who wouldn't see her graduation day next June. Cindy Long had been a classmate of Deputy Bud Traskus's deceased nephew Donnie. Three Bear Hollow teenagers had died in the last two months because of crystal meth and its growing influence in the area. Cindy brought the number to four dead teens, cut down in their prime by the scourge.
Debby kicked at an empty box of Sudafed left next to the body and cast angry eyes at the remains of a fire. The stink of ammonia and acetone lingered in the air. The girl had obviously stumbled across a meth lab and was killed to ensure her silence. Debby and her deputies had worked many eighteen-hour-days since the first death in late August, but had made no headway in tracking down the culprits. The townspeople blamed progress and eyed newcomers and passers-through with more and more suspicion.
But the three who stood over Cindy's torn body knew the real cause—Darius, a practitioner of dark chaos magick, who'd assisted Laird Benjamin in the kidnapping of Selena Jones. Darius was a member of a splinter group of dark witches who'd followed the late Warrick Bettencourt. This same band of badass witches had taken over Benjamin's Chicago underworld empire and now targeted all Coven holdings, in particular the newest one in Bear Hollow.
So far, the dark ones had attacked through their mere-mortal allies—the meth cookers and dealers. It was their warped invitation for the Coven to come out and defend the people under its protection. Unfortunately, the dark ones had covered their tracks all too well. No one had a clue as to where their local headquarters was. The area surrounding Bear Hollow was rife with caves and hollows in which to hide.
"Call Drake, Gor. Tell him to send more security personnel to the farming commune," she requested, but not without a boatload of regrets.
Debby heard Bud's sharp intake of breath and his lowly muttered "about time." Her deputy had urged her to solicit the Coven's aid immediately after his nephew's death, but she'd put him off, not wanting to admit she needed a bunch of witches and their magick to help her do her job.
Three more teens had died because of her pride. Because of her fear of magick. More guilt for her to bear.
Lately, she'd suspected crystal meth was merely the tip of the iceberg. The note pinned to Cindy's skin verified it: "Coven cowards, come out and face us if you dare. More innocents will die until you do." It was more than past time to take the help the Coven could provide. Darius and his followers were without morals and had the ability to cause a lot more harm—and death—in the future. The Coven security personnel would be needed. Plus, it was really their battle. After all, if they hadn't come to Bear Hollow, the evil wouldn't have followed.
Of course, more of a Coven presence meant Boris would come to Bear Hollow. She would just have to pray he'd be too busy chasing Darius and his dark followers to chase her too.
Together Boris and Gor were super-investigators and might have what it took to track Darius to his lair. Truth was she and her deputies couldn't handle Darius and his minions on their own—not without using her magical ability. And she had no intention of ever using that again.
"Make sure the note the bastards left on her body is marked 'For Sheriff's Eyes Only,'" she instructed Bud. "I sure as hell don't want the general public to know the assholes are killing kids with crystal meth to draw a group of witches out to fight. We don't need a modern-day Salem on top of this mess. There are already enough rumors circulating about the nature of the commune as it is."
The rumors had worried her. She suspected Darius had started those, too. He wanted chaos. Locals versus commune witches. Witches versus his dark army.
Debby turned and stomped away. She had to call Cindy's parents and inform them their only child had been found, dead and mutilated. There were days she really hated this job. And there had been far too many of them in the recent months.
Bud turned to look at Gor.
"She's taking this too personally," Bud said. "We warned the kids, but they think they're immortal at this age."
Gor observed the strain on Bud's face, heard it in the man's voice. For the first two weeks after Donnie's death, Bud had shut down, and then he'd pulled on some inner reserves and taken on the mantle of an avenger.
Gor knew that the deputy had his heart and mind in the right place, but would be of little real help in the battle ahead. Dark witches like Darius were not an easy enemy to overcome. Even with reinforcements from the Coven and his own twin, Gor wasn't sure they could defeat the dark brand of chaos magick Darius wielded. They didn't know enough about it, and because of its very nature, the magick morphed continuously. Only a few witches like Rhea, the wife of Coven leader Drake Morgan, and Debby, seemed to be able to defend against it.
Rhea was pregnant with a second child and Drake wouldn't allow her to leave Chicago. Their only hope to get ahead of Darius and his ilk was Debby—and she refused to use her great power because of an incident in her past. Gor only hoped his brother could break through Debby's strong aversions to magick in time to save them all.


text:
Sedition law in Bangladesh
Compiled by Law Desk
Tue Mar 1, 2016 12:00 AM Last update on: Tue Mar 1, 2016 12:00 AM
The Penal Code, 1860 in its section 124A defines the offence of sedition. According to this section, anyone who by spoken or written words, or by signs, or by visible representation, or otherwise, brings or attempts to bring into hatred or contempt, or excites or attempts to excite disaffection towards the lawful Government can be accused of committing sedition.
The punishment prescribed varies from imprisonment up to three years to life imprisonment, with fine or without it.
It is to mention that the expression "disaffection" under this section includes disloyalty and all feelings of enmity.
However, any comment expressing disapprobation of the measures of the Government with a view to obtain their alteration by lawful means, without exciting or attempting to excite hatred, contempt or disaffection, does not constitute an offence under this section.
Even comments expressing disapprobation of the administrative or other action of the Government without exciting or attempting to excite hatred, contempt or disaffection, do not constitute an offence under this section.
Section 108 of the Code of Criminal Procedure, 1898 provides an option to have
security for good behaviour from persons disseminating seditious matter. According to this section, the District Magistrate, or any other Executive Magistrate specially empowered by the Government, may require any person – accused of disseminating of any seditious matter the publication of which is punishable under section 123A or section 124A of the Penal Code – to show cause why he should not be ordered to execute a bond, with or without sureties, for his good behaviour for such period, not exceeding one year, as the Magistrate thinks fit to fix.
However, no proceedings can be taken under this section against the editor, proprietor, printer of publisher of any publication registered under, and edited, printed and published in conformity with, the provisions of the Printing Presses and Publications (Declaration and Registration) Act, 1973, with reference to any matters contained in such publication except by the order or under the authority of the Government or some officer empowered by the Government in this behalf.
Source: bdlaws.minlaw.gov.bd


Resiliency. I have seen the light and I'm crowing, to quote the great Muhammad Ali.
In the great movie "The Lion in Winter", Richard and his brothers Geoffrey and John are waiting to be executed by their father, King Henry II of England.
Previous Previous post: Things written in unawareness that matriculated from immersive awareness intent upon impeccability.


Home care franchises are doing just fine, thank you, and the facts speak for themselves. Franchise market research firm, Franchise Grade reports that since 2010 home care franchises have grown by 62% and average franchisee turnover has gone from 9.6% to 7.31%.
In addition, in 2016, 60% of franchises did a Financial Performance Representation under Item 19 and for 2017 the number increased to 74%. These results reflect arguably the most healthy and dynamic franchise category in all of franchising with little possibility of abating.
There are over 6.500 franchise locations and 91 home care and senior care franchise brands in the U.S.
Most of these franchise brands provide non-skilled or companion type private pay home care services. Some predict that more home care franchise brands will migrate to providing skilled nursing services.
Over the past twenty years home care has been one of the fastest growing industries in the United States. This growth has been replicated in the franchise industry by home care franchises.
In 2011 one-third of the home care agencies were franchises, but in 2016 about half were, according to market research firm Home Care Pulse LLC. As the United States population continues to age, it's predicted that health-care employment will continue to surpass other sectors of the U.S. economy.
In fact, health care has recently surpassed manufacturing and retail sector employment, becoming the largest source of jobs in the U.S. The cost saving benefits of home care is a major driver of growth and the more franchises that provide skilled nursing government reimbursed services the greater opportunity for growth.
Federal and state funding for health-care means that health-care employment is insulated from swings in the economy. As an example, health care employment increased during the Great Recession.
The Bureau of Labor Statistics, predicts that personal care and home-health aides will represent one in every 10 new jobs during the next 10 years.
As the population continues to age, the demand for home care services will continue to grow. For individuals seeking to own and operate a franchise for a reasonable investment, a home care franchise can be a good choice.
In the case of Senior Care, a franchisee can tap into a market that continues to grow and operate a business that is uncomplicated and straightforward. In addition, the demand for home care services has encouraged more entrepreneurs to launch home care franchise programs.
Home health care Services provided in the home by nurses, home health aides and companions. Payment for these services includes Medicare, Medicaid, Insurance and Private Pay. A limited number of franchises provide these services.
Senior care: Often referred to as private duty, companion care or unskilled home care involves basic services such as meal preparation, compliance with medication, assistance with housekeeping and companionship.
Most home care franchises provide senior care services which are usually paid for by private pay or in some cases special insurance.
Medical staffing Is the temporary staffing of health care personnel to hospitals, nursing homes and other healthcare providers.
Franchises may include medical staffing as part of other home care services or as a separate franchise operation. The number of medical staffing franchises is quite low.
Medical equipment Include both durable medical equipment such as patient ramps, specialized vans and wheel chairs and home medical equipment which are companies that provide supplies, oxygen breathing devices and other supplies for home care patients.
* Has a lower average royalty rate than other personal services franchise categories and the overall franchise industry.
In the mid-90's, I completed master franchise agreements in several countries including the first home care master franchise in Japan. Since that time, many home care franchises including Right at Home, Home Instead, Interim and Bright Star, have been successful in exporting their home care franchise overseas.
Several U.S. home care franchises begin their international franchise program by franchising directly into a small country or a country close to their U.S. Operation, such as Canada or Cost Rica.
The prognosis for the home care franchise sector is excellent based upon aging populations throughout the industrialized countries and the cost saving benefits of home care services.
Ed Teixeira, is COO of Franchise Grade, LLC and a contributor to Forbes.com. Ed has spent over 35 years in the franchise industry, including 15 years in the franchised home healthcare sector. He served as a senior executive for a publicly traded home care franchisor as well as franchisee of a multi-million-dollar home care operation with six locations. He was also Chief Operating Officer of a franchised medical staffing company. During his tenure, Teixeira was directly responsible for executing international licensing agreements to include the first home healthcare franchise license in Japan and agreements in Spain, Indonesia and Brazil. He is the author of The Franchise Buyers Manual and Franchising From The Inside Out.


text:
Q: Determine the Vectors Which Span R^4 I understand how to determine WHETHER a set of vectors span a space, but I've been given two vectors (1,2,3,4) and (17,17,17,17) and asked to find two more vectors such that the set of all these vectors span $ \mathbb{R}^4 $.
At the moment I'm just going about with kind of a trial and error approach...is there some better way to work this out?
Hints, or suggestions would be greatly appreciated as I want to figure this out without a full solution.

A: Try to complete your basis using the vectors of the standard basis: $(1,0,0,0), (0,1,0,0),$ etc. Pick one of them and check if the three vectors you have now are independent. If yes, great, keep the vector you chose and repeat the procedure with the three remaining vectors of the standard basis. If not, discard the vector you chose and try again with another one. Repeat until done.

A: Put your two given vectors into a $4 \times 2$ row matrix $M$, and apply row operations to covert $M$ into a matrix $M'$ in which the leading nonzero entry of row $2$ is to the right of the leading nonzero entry of row $1$. The row spaces of $M$ and $M'$ are identical. It should now be obvious how to add two row vectors to $M'$ to make a basis. Your original two vectors, together with the two added row vectors, form the basis you want.

A: HINT
What basis do you already know that spans $\mathbb{R}^4$?
How can you use this in combination with the vectors that you are already given to get a basis?

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Зетабајт се користи као јединица мере података у рачунарству и износи било 1000 или 1024 ексабајта, што зависно од интерпретације може да буде:

 1.000.000.000.000.000.000.000 бајта (1021, хиљаду трилиона) - по СИ систему
 1.180.591.620.717.411.303.424 бајта (270) - по "бинарним" умношцима (зебибајт)

Јединице количине података

de:Byte#Bedeutungen von Dezimal- und Binärpräfixen für große Anzahlen von Bytes

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Automatic water softeners—the kind that use rock salt or potassium chloride pellets—are banned in the Santa Clarita Valley. Automatic water softeners discharge a salty waste into the sewer system that is treated by a process that does not remove salt; therefore, the salty waste is released into the Santa Clara River. Too much salt in the river may harm downstream agricultural crops.
The Sanitation District's goal is to reduce salt in an environmentally friendly, cost-effective, and timely manner, in order to comply with the state's legal limit for chloride discharged to the river. Measure S, approved by voters on November 4, 2008, enacted the Santa Clara River Chloride Reduction Ordinance of 2008. The Santa Clara River Chloride Reduction Ordinance of 2008 required the removal of all residential automatic water softeners by June 30, 2009. These efforts have resulted in the removal of over 8,000 salt discharging automatic water softeners and significant reductions in chloride levels.
The Sanitation District is conducting home inspections to remove the remaining automatic water softeners in the community. Residents that still have automatic water softeners should click the link below and apply for a rebate or remove their unit immediately.


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Vintage Men's 14K Solid Yellow Gold Oval Green Jade Ring. 10mm x 14mm natural oval cabochon jade. This stone has a nice polished finish with no major cracks or chips evident. The item "Vintage Men's 14K Yellow Gold Oval Green Jade Jadeite Ring Estate Nugget Sz 9.75" is in sale since Tuesday, September 05, 2017.
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Police are appealing for the public's help to trace a dangerous man after a couple in their late seventies were subjected to a horrifying kidnap ordeal.
Between 3am and 4am on Thursday, March 16, Andrew Evans, 26, of Heath Street, Golborne, near Wigan, forced himself through the front door of a couple's house in Lowton armed with a gun in one hand and a knife in the other.
He demanded money from the man and his wife and then bundled them into their own black Landrover Freelander before driving them to a cash machine on High Street in Golborne Town Centre.
He forced them to withdraw hundreds of pounds, telling them he needed the money for his dying daughter so he could buy her a present.
He then took them back home, kissed the man's wife on the hand and fled in the Landrover towards the East Lancashire Road after telling them he would leave the car in a supermarket car park for the couple to collect later.
Minutes later, the car was seen travelling at around 70mph before it collided with a roundabout and flipped over.
Evans is now wanted in connection with the incident and officers are appealing for the public's help to trace him.
Detective Inspector Paul Rollinson of GMP's Wigan Borough, said: "This prolonged and harrowing ordeal has left this innocent couple shaken and petrified after being violently confronted in their own home.
"It is extremely important that anyone who knows where Evans tells us at the earliest opportunity.
Anyone with information about Evans' whereabouts should contact police on 0161 856 7225 or the independent charity Crimestoppers, anonymously, on 0800 555 111.


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Dairy Finds Innovative Use for Wheel Unbalance
Innovations often come from the most unexpected of places, and are sometimes found by complete accident. Such a case came to light recently when one of the world's largest dairy companies started having problems with one of their bulk tankers. "We had a tanker delivery from the farms, where the whole tanker had turned to cottage cheese before delivery!", said Peter Påhittat, Fleet Maintenance Manager at the plant where it happened, "It was a complete mystery why."
After a detailed investigation, it transpired that the tanker in question had been fitted with a new set of wheels that the fitter had neglected to balance. The extreme vibration from this had damaged the tankers cooling system, and by coincidence the load had also been contaminated with a strain of bacteria. The bacteria and the shaking from the unbalanced wheels conspired to turn the cargo to cottage cheese.
"We have always balanced our wheels with EASYBALANCE, as we know that it saves us about 20% on the tyre wear, as well as wheel bearings, shock absorbers and so on", said Peter, "but this has made us rethink that a little, when we realised we could manufacture finished product on the road from the farm, it saves us both money and time!"
"We don't like to lose the sales for EASYBALANCE", said Mark McCullough, Sales Development for EASYBALANCE, "we have proven that it gives significant savings in any other circumstances, but they have come across a very unusual exception here."
Update: You can't taking everything seriously on 1st April of course, except that EASYBALANCE saves MONEY on the tyre wear!
Published: Friday 01 April 2016


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Vancouver Whitecaps 2, LAFC 1 | 2020 MLS Match Recap
October 15, 202012:02AM EDT
Pardeep CattryContributor
The Vancouver Whitecaps kept their playoff hopes alive with a second win in a row, riding two goals by star striker Lucas Cavallini to a 2-1 victory over LAFC on Wednesday in Portland.
The Whitecaps now occupy the eighth and final playoff spot in the Western Conference with five matches to go and they sit just three points behind LAFC in 4th place in the conference standings.
Vancouver started strong with two shots in the opening minutes of the match, maintaining that momentum until they scored the game's opening goal in the 30th minute. From midfield, Fredy Montero sent the ball towards Cristian Dajome in the box. Then, Dajome sent a square pass towards Cavallini, who hit the back of the net from close range. It was the highlight of a strong first half for the Whitecaps, who had nine shots and four on target.
LAFC started the second half with the urgency of a team looking for an equalizer, and their first shot on target. But that mission was disrupted when Cavallini scored a second in the 59th minute. The trio that combined for the first goal did the same for the second, with Dajome sending the ball to Montero on the right side of the penalty area. Montero then crossed to Cavallini in front of goal, and he punched it home to make it 2-0.
LAFC continued pushing for a goal, though they struggled to record a shot on target despite dominating possession. The chance to get on the board came through an 83rd minute penalty kick that was awarded after a handball infraction by Vancouver's Jake Nerwinski. Although 'Caps goalkeeper Evan Bush made a save on Eduard Atuesta's first attempt, the kick was retaken due to goalkeeper encroachment and he scored on his second try.
Despite their best efforts, however, there was no equalizer to come from LAFC, who have lost their seventh match of the season after only dropping four in a record-setting 2019.
30' - VAN - Lucas Cavallini | WATCH
83' - LAFC - Eduard Atuesta - PK | WATCH
THE BIG PICTURE: Just when everyone's ready to write off the Whitecaps after four straight losses, they show the heart of a team that is far from ready to concede no matter the adversity they continue to face in 2020. They gutted out their second straight victory against a weakened, but still very capable LAFC side, making it clear they will be scrapping until the very end. LAFC look forward to welcoming their South American stars back from national team duty and subsequent quarantine for the final stretch run.
MOMENT OF THE MATCH: Lucas Cavallini, Fredy Montero, and Cristian Dajome were crucial to the Whitecaps' success, and on the second goal provided stellar passing and in Cavallini's case, a standout finish.
MAN OF THE MATCH: Lucas Cavallini was the Whitecaps' key to success, scoring both of the team's goals and recording four shots overall.
VAN: Sunday, October 18 at LA Galaxy (10:30 pm ET | MLS LIVE on ESPN+; TSN 1/4 in Canada)
LAFC: Sunday, October 18 at Portland Timbers (10 pm ET | MLS LIVE on ESPN+; MLS LIVE on DAZN in Canada)
As Cavallini starts to heat up, so do the Whitecaps
HIGHLIGHTS: Vancouver Whitecaps FC vs. LAFC | October 14, 2020
October 15, 2020 (4 min)
Vancouver Whitecaps FC 2-1 LAFC | 2-Minute Highlights
YELLOW CARD: Janio Bikel, Vancouver Whitecaps - 89th minute
YELLOW CARD: Erik Dueñas, LAFC - 93rd minute
YELLOW CARD: Evan Bush, Vancouver Whitecaps - 83rd minute


After the Malevolence arc, Anakin is still feverishly trying to locate Grievous, who (unbeknownst to the Republic) has hatched a new plan to destroy Kamino at the outer rim where Clones are produced. The outpost guarding that area is mainly manned by rookie Clones who are not fully trained, yet placed because the Republic is short on troops. The outpost is attacked as Commander Cody and Captain Rex are on their way for an inspection. When they get there, only three Clones have survived the surprise attack by drones.
This episode focused mainly on humanizing the Clones, giving them personalities and making us - the audience - feel sympathetic towards them. Many perished, and there were a few heroics to drive that point home. Commander Cody dropped a heavy line when he told his team that they weren't just defending a base for the Republic, but they were defending their brothers-in-arms, and the closest thing that they, as Clones, could call a home (their production/training facility). Later, Rex inducted the surviving Clones into the 501st Legion.
Upon further thought, I guess if Grievous had succeeded in destroying the facility at Kamino, many more Jedi might have survived Order 66. But then again, I wonder whether they would have even made it to that point without the Clone army? It's a weird cycle of catch-22s that's making my head hurt.
Anyway, I'm glad to see that writers weren't afraid to make episodes that didn't focus on the Jedi. We're back to Anakin and Ahsoka next time though, and some R2D2 action, so I'm looking forward to that.


Registration for this course is now open!
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Known as the yoga of action, it is the foundation of the existence of our centre. Karma Yoga is how everything happens at Gendun Drubpa Buddhist Centre . We work together in the kitchen, garden and grounds; we repair our buildings; we clean and care for our spaces.
All members and guests are encouraged to participate in Karma Yoga and engage with work as a part of our spiritual practice.
Discovering Buddhism is a 14 module correspondence course. Students can choose to participate on a casual basis or to pursue a certificate of completion for each module by participating in retreats, meditations, reading translations and texts, and listening to lectures. This program is not designed as an academic study of Buddhism but is intended to change a person's life.


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Q: Can neural network fail to learn a function? and How to choose better feature descriptors for pattern recognition? I was working on webots which is an environment used to model, program and simulate mobile robots. Basically i have a small robot with a VGA camera, and it looks for simple blue coloured patterns on white walls of a small lego maze and moves accordingly
The method I used here was

*

*Obtain images of the patterns from webots and save it in a location
in PC.

*Detect the blue pattern, form a square enclosing the pattern
with atleast 2 edges of the pattern being part of the boundary of the
square.

*Resize it to 7x7 matrix(using nearest neighbour
interpolation algorithm)

*The input to the network is nothing but the red pixel intensities of each of the 7x7 image(when i look at the blue pixel through a red filter it appears black so). The intensities of each pixel is extracted and the 7x7 matrix is then converted it to a 1D vector i.e 1x49 which is my input to the neural network. (I chose this characteristic as my input because it is 'relatively' less difficult to access this information using C and webots.)
I used MATLAB for this offline training method and I used a slower learning rate(0.06) to ensure parameter convergence and tested it on large and small datasets(1189 and 346 respectively). On all the numerous times I have tried, the network fails to classify the pattern.(it says the pattern belongs to all the 4 classes !!!! ) . There is nothing wrong with the program as I tested it out on the simpleclass_dataset in matlab and it works almost perfectly
Is it possible that the neural network fails to learn the function because of really poor data? (by poor data i mean that the datapoints corresponding to one sample of one class are very close to another sample belonging to a different class or something of that sort). Or can the neural network fail because of very poor feature descriptors?
Can anyone suggest a simpler method to extract features from the image(I am now shifting to MATLAB as I am now only concerned with simulations in webots and not the real robot). What sort of features can I choose? The patterns are very simple (L,an inverted L and its reflected versions are the 4 patterns)

A: Neural networks CAN fail to learn a function; this is most often caused by employing a network topology which is too simple to model the necessary function. A classic example of this case is attempting to learn an XOR function using a perceptron classifier, although it can even happen in multilayer neural nets sometimes; especially for complex tasks like image recognition. See my previous answer for a rough guide on how to select neural network parameters (ignore the convolution stuff if you want, although I would highly recommened looking into convolutional neural networks if you are still having problems).
It is a possiblity that there is too little seperability between classes, although I doubt that this is the case given your current features. Is there a reason that your network needs to allow an image to be four classifications simultaneously? If not, then perhaps you could classify the input as the output with the highest activation instead of all those with high activations.