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Classification Schemes

The University Library uses industry standard schemes to organise and describe the collections of our libraries. This includes employing three classification schemes, which are chosen to suit the materials being organised, and two subject heading schemes, which are chosen to best describe the materials in the collections.

Classification Schemes

A classification scheme is utilised in a library to decide the shelf order of the physical materials, regardless of format (e.g books, journals, DVDs, etc). The scheme provides a ‘address’ for each item (known as a call number). The Library catalogue will provide a call number for each physical item in the collection, as well as telling which collection and which library the item is housed in.

Electronic Resources do not have a ‘call number’ or ‘collection’ as they have no physical location and ‘belong’ to all libraries.

The University Library uses three Classification Schemes to organise materials in the Library Collections.

They are:

The DDC scheme, the most widely used library classification system in the world, divides the entire world of knowledge into ten main classes according to disciplines or fields of study. Each of these main classes is further divided into ten divisions, and each division into ten sections. Each of these levels of the system is given a unique three digit number.

These numbers are then used to place the library materials in numerical order on the shelves for easy retrieval. The structure of the system means that books on the same or similar subjects will be shelved near each other (that said, it is worth remembering that a book may cover more than one subject and may therefore be classified so that multiple copies appear in more than one discipline area).

Click here if you want to know more about the Dewey scheme.

The law collections are classified according to the Moys Classification Scheme, 5th edition. Unlike other disciplines, the study of law is usually approached in terms of its jurisdiction. The scheme splits law materials into primary materials (statute and case law) and secondary materials (treatises, reference materials and journals). Under Moys, countries whose legal systems are based almost entirely on the English Common Law, i.e. England and Wales, Ireland, Canada, Australia, New Zealand, United States and the former British West Indian colonies are treated as one unit Territorial jurisdictions with Civil Law systems or legal systems not wholly based on the Common Law e.g. those in Africa, Latin America, Asia and Europe, are treated as separate units. Moys numbers begin with the letter K. They are arranged by alphabetical and followed by numerical order.

Click here if you want to know more about theMoys scheme.

The NLM Classification covers the discipline of medicine and related sciences. The NLM Classification is a system which employs alphabetical letters to denote broad subject categories and then further subdivides these catagories by numbers. The headings for the individual schedules are given in brief form (e.g., WE - Musculoskeletal System; WG - Cardiovascular System) and these headings are interpreted broadly and include the physiological system, the specialty or specialties connected with them, the regions of the body chiefly concerned and subordinate related fields. The Classification is hierarchical, and within each schedule, division by organ usually has priority. Each main schedule, as well as some sections within a schedule, begins with a group of form numbers ranging generally from 1-49 which are used to classify materials by the type of publication (e.g., dictionaries, atlases, laboratory manuals, etc). The main schedules QS-QZ, W-WY, and WZ (excluding WZ 220-270) are used to classify works published after 1913; the 19th century schedule is used for works published 1801-1913; and WZ 220-270 is used to provide century groupings for works published before 1801 and Americana.

See an outline of the scheme or download a copy .

(Source Fact Sheet: National Library of Medicine, available at - http://www.nlm.nih.gov/pubs/factsheets/nlmclassif.html )

Subject Headings are applied to each item within a library’s collection, and help library user’s locate to items in the library catalogue that cover a specific subject as well as helping them to find other items that cover similar subject matter. They are searched anytime the Library catalogue is searched using a ‘subject heading’, ‘subject keyword’ and ‘general keyword’ search.

Figure 6. Manually constructed classification tree for the partitioning of analytes into compartments and intermediate units based on their estimated subcellular distribution as well as compartmental abundance and variability.

The classification tree was used to assign an analyte into a group defining its subcellular distribution type (type) and an associated mode (mode) which represents one of the resolved compartments or the overlap between them. Assignments are based on the mean and standard deviations of the subcellular distribution, estimated using the best fit algorithm (BFA), for each analyte based on the three independent gradient data. Analytes with insufficiently explained subcellular distributions according to the selected compartment-specific markers are accounted as unexplained and are not further considered in this tree. Analytes revealing sufficiently explained fits are accounted as ‘shared’ if the minimum of the percentage value (min  =  mean - SD) in the most abundant compartment is overlapping with the maximum percentage value (max  =  mean + SD) of any other considered compartment. The corresponding mode is defined by the overlapping compartments regarding the most abundant compartment. Analytes are considered ‘specific’ with the mode according to the estimated most abundant compartment, if the minimum of the most abundant compartment is ≥75% and the values of all other (low abundant) compartments are negligible, i.e. ≤10%. If the minimum in the most abundant compartment is larger than the sum of the maxima among the other compartment and ≥66.67% (2/3 compartments), analytes are accounted as ‘dominantly’ distributed in the respective compartment. Analytes are accounted as ‘enriched’ in a compartment, if the value of the most abundant fraction is ≥50% than the sum of the other compartment. If none of this decisions result in an assignment the analyte is considered as being shared but with enrichment in a particular compartment (‘shared*’).

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Using BFA the subcellular distributions of 3,198 (81.5%) out of all 3,922 analytes are considered as sufficiently explained by the averaged compartment-specific markers using a three-compartmental calculation strategy, considering the vacuolar, cytosolic, and plastidic compartments ( Van Heusen Driveaway Mocs JLt22Ay
; Data S4 and S5 ). Consequently, the subcellular distributions of 724 (18.5%) analytes are insufficiently explained. Classification based on the compartment-specificity of the three nearest neighboring markers using k-nearest neighbor algorithm (kNN, with k = 3) facilitated the assignment of 487 (67.3%), 174 (24.0%), and 63 (8.7%) of these insufficiently explained analytes into the cytosolic, plastidic, and vacuolar compartments, respectively ( Table 1 ). Interestingly, the mitochondrial marker citrate synthase was considered as insufficiently explained but, as mentioned before, it showed a more cytosol-like distribution and therefore was assigned to the cytosol (Data S4). Similarly, sucrose, a metabolite which is synthesized in the cytosol and transported into sink organs via the phloem, was assigned to the cytosol (Data S4). Earlier conducted NAF studies [10] , [11] have already indicated that the observed sucrose distribution could not clearly be ascribed to the cytosolic, plastidic, or vacuolar compartment, most likely due to the greatly higher amounts present in sieve tubes [11] .

Note that unlike manual injection, automatic injection occurs at the pod-level. You won’t see any change to the deployment itself. Instead you’ll want to check individual pods (via kubectl describe ) to see the injected proxy.

The sidecar injecting webhook is enabled by default. If you wish to disable the webhook, you can use 5 to generate an updated istio.yaml with the option sidecarInjectorWebhook.enabled set to false . E.g.

$ helm template --namespace = istio-system --set sidecarInjectorWebhook.enabled = false install/kubernetes/helm/istio > istio.yaml $ kubectl create ns istio-system $ kubectl apply -n istio-system -f istio.yaml

In addition, there are some other configuration parameters defined for the sidecar injector webhook service in values.yaml . You can override the default values to customize the installation.

Deploy sleep app. Verify both deployment and pod have a single container.

$ kubectl apply -f samples/sleep/sleep.yaml $ kubectl get deployment -o wide
$ kubectl get pod
NAME READY STATUS RESTARTS AGE sleep-776b7bcdcd-7hpnk 1/1 Running 0 4

Label the default namespace with istio-injection=enabled

$ kubectl label namespace default istio-injection = enabled $ kubectl get namespace -L istio-injection
NAME STATUS AGE ISTIO-INJECTION default Active 1h enabled istio-system Active 1h kube-public Active 1h kube-system Active 1h

Injection occurs at pod creation time. Kill the running pod and verify a new pod is created with the injected sidecar. The original pod has 1/1 READY containers and the pod with injected sidecar has 2/2 READY containers.

$ kubectl delete pod sleep-776b7bcdcd-7hpnk $ kubectl get pod
NAME READY STATUS RESTARTS AGE sleep-776b7bcdcd-7hpnk 1/1 Terminating 0 1m sleep-776b7bcdcd-bhn9m 2/2 Running 0 7s

View detailed state of the injected pod. You should see the injected istio-proxy container and corresponding volumes. Be sure to substitute the correct name for the Running pod below.

$ kubectl describe pod sleep-776b7bcdcd-bhn9m

Disable injection for the default namespace and verify new pods are created without the sidecar.

$ kubectl label namespace default istio-injection- $ kubectl delete pod sleep-776b7bcdcd-bhn9m $ kubectl get pod
NAME READY STATUS RESTARTS AGE sleep-776b7bcdcd-bhn9m 2/2 Terminating 0 2m sleep-776b7bcdcd-gmvnr 1/1 Running 0 2s

admissionregistration.k8s.io/v1beta1#MutatingWebhookConfiguration configures when the webhook is invoked by Kubernetes. The default supplied with Istio selects pods in namespaces with label istio-injection=enabled . This can be changed by modifying the MutatingWebhookConfiguration in install/kubernetes/istio-sidecar-injector-with-ca-bundle.yaml .

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