Revised Guidance on PPE for Health Care Workers Updated guidance on PPE to be used and processes for donning and doffing PPE for health care workers entering a patient room hospitalized with Ebola. Emphasizes the importance of training, practice, competence, and observation of health care workers in correct donning and doffing of PPE selected by the facility. Key principles: •Prior to patient contact, all workers must have repeated training and demonstrated competency in Ebola-related infection control, and specifically donning/ doffing proper PPE. •While working in PPE no skin should be exposed. •Overall safe care must be overseen by onsite manager at all times, and each step of every PPE donning/doffing procedure supervised by a trained observer •Ebola is spread through direct contact with blood or body fluids or with contaminated objects. For all workers, full body coverage PPE is recommended to reduce the risk of self-contamination •To protect workers, facilities must provide onsite management and oversight on safe use of PPE and implement administrative and environmental controls Source: Centers for Disease Control and Prevention. This guidance is current as of October 20, 2014 from http://www.cdc.gov/vhf/ebola/hcp/procedures-for-ppe.html. Please see website for complete details. 10/21/14
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Recommended PPE • • • • • • Key to all PPE is consistent implementation through repeated training and practice. Facility should select and standardize PPE for all essential workers directly interacting with Ebola patients Provide written protocol outlining procedures for donning and doffing of PPE, and review and monitor by trained observer CDC recommends facilities use a powered air-purifying respirator (PAPR) or an N95 or higher respirator in the event of an unexpected aerosol-generating procedure. For healthcare workers who spend extended periods in PPE, safety and comfort are critical. Standardizing attire under PPE (e.g., surgical scrubs or disposable garments and dedicated washable footwear) facilitates donning and doffing process and eliminates concerns of contamination of personal clothing. If facilities elect to use different PPE from what is outlined by CDC (e.g., coveralls with either an integrated hood or a surgical hood with integrated full face shield), they must train workers and ensure that donning and doffing procedures are adjusted and practiced accordingly. Source: Centers for Disease Control and Prevention. This guidance is current as of October 20, 2014 from http://www.cdc.gov/vhf/ebola/hcp/procedures-for-ppe.html. Please see website for complete details. 10/21/14
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Lesson 12. Personal Safety and Hygiene Protective Clothing Personal Protective Equipment (PPE) is the term used to describe the various types of clothing and equipment which help to prevent contact with infectious, toxic or corrosive agents. Also included is equipment which protects workers against temperature extremes and other physical hazards.  The type of clothing and equipment needed depends on the procedures being performed.  For example:  People who handle nonhuman primates need to wear a lab coat or gown, mask, eye or face shield, gloves, cap and protective footwear.  Personnel using acid to descale cages need to wear protective goggles, aprons and gloves.  On the other hand, those handling rodents in a conventional facility may not need much protective clothing.  Certain types of protective clothing provide greater comfort than others. Comfort, however, is not the deciding factor in the selection of protective clothing.  
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Training • • • • • Why PPE is necessary How PPE will protect the employee What PPE can and cannot do When and how to wear PPE How to identify signs of wear and tear • How to clean and disinfect PPE • When PPE is worn out and how to properly dispose of PPE PPT 10-hr. Construction – PPE v.05.18.15 30 Created by OTIEC Outreach Resources Workgroup
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Personal Protective Equipment  AGENCY MUST: – Provide PPE for all employees  at no cost to the employee – train employees how to use PPE properly – train employees on the limitation(s) of PPE – train employees in proper care, storage, and useful life, and disposal of PPE
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Syntatic Sugar - a bunch of static’s public static Tree leaf () { return new Tree(); } public static Tree node (Object val, Tree lt, Tree rt) { return new Tree(val, lt, rt); } public static boolean isLeaf (Tree t) { return t.isLeaf; } public static Object getValue(Tree t) { return t.getValue(); } public static Tree getLeft(Tree t) { return t.getLeft(); } public static Tree getRight(Tree t){ return t.getRight(); } public static void setValue (Tree t, Object newValue) { t.setValue(newValue); } public static void setLeft (Tree t, Tree newLeft) { t.setLeft(newLeft); } public static void setRight (Tree t, Tree newRight) { t.setRight(newRight); } // using the new notation: Tree T = leaf(); T = node("A", leaf(), leaf()); Tree tl = node("B", leaf(), leaf()); Tree tr = node("C", leaf(), leaf()); setLeft(T, tl); setRight(T, tr); setValue(getLeft(T),new Integer(5)); setRight(T, getRight(getRight(T)) ); 17 - 18
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Syntatic Sugar public static Tree leaf () { return new Tree(); } public static Tree node (Object val, Tree lt, Tree rt) { return new Tree(val, lt, rt); } public static boolean isLeaf (Tree t) { return t.isLeaf; } public static Object getValue(Tree t) { return t.getValue(); } public static Tree getLeft(Tree t) { return t.getLeft(); } public static Tree getRight(Tree t){ return t.getRight(); } public static void setValue (Tree t, Object newValue) { t.setValue(newValue); } public static void setLeft (Tree t, Tree newLeft) { t.setLeft(newLeft); } public static void setRight (Tree t, Tree newRight) { t.setRight(newRight); } Tree T = leaf(); T = node("A", leaf(), leaf()); Tree tl = node("B", leaf(), leaf()); Tree tr = node("C", leaf(), leaf()); setLeft(T, tl); setRight(T, tr); setValue(getLeft(T),new Integer(5)); setRight(T, getRight(getRight(T)) );17 - 22
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Schreiber, Schwöbbermeyer [12] proposed flexible pattern finder (FPF) in a system Mavisto.[23] It exploits downward closure , applicable for frequency concepts F2 and F3. The downward closure property asserts that the frequency for sub-graphs decrease monotonically by increasing the size of sub-graphs; but it does not hold necessarily for frequency concept F1. FPF is based on a pattern tree (see figure) consisting of nodes that represents different graphs (or patterns), where the parent is a sub-graph of its children nodes; i.e., corresp. graph of each pattern tree’s node is expanded by adding a new edge of its parent node. At first, FPF enumerates and maintains info of all matches of a sub-graph at the root of the pattern tree. Then builds child nodes of previous node by adding 1 edge supported by a matching edge in target graph, tries to expand all of previous info about matches to the new sub-graph (child node).[In next step, it decides whether the frequency of the current pattern is lower than a predefined threshold or not. If it is lower and if downward closure holds, FPF can abandon that path and not traverse further in this part of the tree; as a result, unnecessary computation is avoided. This procedure is continued until there is no remaining path to traverse. It does not consider infrequent sub-graphs and tries to finish the enumeration process as soon as possible; therefore, it only spends time for promising nodes in the pattern tree and discards all other nodes. As an added bonus, the pattern tree notion permits FPF to be implemented and executed in a parallel manner since it is possible to traverse each path of the pattern tree independently. But, FPF is most useful for frequency concepts F2 and F3, because downward closure is not applicable to F1. Still the pattern tree is still practical for F1 if the algorithm runs in parallel. It has no limitation on motif size, which makes it more amenable to improvements. ESU (FANMOD) Sampling bias of Kashtan et al. [9] provided great impetus for designing better algs for NM discovery, Even after weighting scheme, this method imposed an undesired overhead on the running time as well a more complicated impl. It supports visual options and is time efficient. But it doesn’t allow searching for motifs of size 9. Wernicke [10] RAND-ESU is better than jfinder, based on the exact enumeration algorithm ESU, has been implemented as an app called FANMOD.[10] Rand-esu is a discovery alg applicable for both directed and undirected networks. It effectively exploits an unbiased node sampling, and prevents overcounting sub-graphs. RAND-ESU uses DIRECT for determining sub-graph significance instead of an ensemble of random networks as a Null-model. DIRECT estimates sub-graph # w/oexplicitly generating random networks.[10] Empirically, DIRECT is more efficient than random network ensemble for sub-graphs with a very low concentration. But classical Null-model is faster than DIRECT for highly concentrated sub-graphs.[3][10] ESU alg: We show how this exact algorithm can be modified efficiently to RAND-ESU that estimates sub-graphs concentrations. The algorithms ESU and RAND-ESU are fairly simple, and hence easy to implement. ESU first finds the set of all induced sub-graphs of size k, let Sk be this set. ESU can be implemented as a recursive function; the running of this function can be displayed as a tree-like structure of depth k, called the ESU-Tree (see figure). Each of the ESU-Tree nodes indicate the status of the recursive function that entails two consecutive sets SUB and EXT. SUB refers to nodes in the target network that are adjacent and establish a partial sub-graph of size |SUB|≤k. If |SUB|=k, alg has found induced complete sub-graph, Sk=SUB ∪Sk. If |SUB|v} graphs of size 3 in the target graph. call ExtendSubgraph({v}, VExtension, v) endfor Leaves: set S3 or all of size-3 induced sub-graphs of the target graph (a). ESUtree nodes incl 2 adjoining sets: adjacent ExtendSubgraph(VSubgraph, VExtension, v) nodes called SUB and EXT=all adjacent if |VSubG|=k output G[VSubG] return 1 SUB node and where their numerical While VExt≠∅ do Remove arbitrary vertex w from VExt labels > SUB nodes labels. EXT set is VExtension′←VExtension∪{u∈Nexcl(w,VSubgraph)|u>v} utilized by the alg to expand a SUB set call ExtendSubgraph(VSubgraph ∪ {w}, VExtension′, v) until it reaches a desired size placed at return lowest level of ESU-Tree (or its leaves).
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Writing Intensive Course Rubric 2=Acceptable 1=Unacceptable Writing assignments are incorporated as an integral, ongoing part of the course, and the writing assignments are effectively integrated, structured, and sequenced in a way that clearly articulates how it helps students improve their writing Writing assignments are not incorporated as an integral component of the course, writing assignments are not structured and sequenced in a way that can help students improve their writing in any clear way From the course syllabus and course assignments, it is clear that students have many opportunities to receive constructive criticism on drafts, and the opportunity to revise their work, particularly drafts of longer projects. From the course syllabus and course assignments, it is unclear whether students have many opportunities to receive constructive criticism on drafts, or the opportunity to revise their work, particularly drafts of longer projects. From the course syllabus and course assignments, it is clear that assignments and course planning devote ample time for students to reflect on their writing and their intellectual growth. From the course syllabus and course assignments, it is clear that assignments and course planning do not devote any time for students to reflect on their writing and their intellectual growth. As stated in the course syllabus, written assignments are a major component of the course grade. The course syllabus clearly and amply explains the writing-intensive nature of the course and contains a detailed schedule for writing assignments and revisions. Written assignments are not a component of the course grade. The course syllabus does not explain the writing-intensive nature of the course and does not contain a schedule for writing assignments and revisions. The Writing Intensive Course has at least one rubric created for grading writing assignments and the rubric is distributed to the students before the writing assignments are due. The Writing Intensive Course has no rubric, and thus no rubric is distributed to the students before the writing assignments are due.
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Object features as model annotations agent Patron Name Email attributes features entity Train Speed Acceleration DoorsState On annotation association Name Patron; Type Agent Def Any person currently registered to a system’s library for some valid period. Synonyms Borrower Name Train; Type Entity Def Any train currently in operation in the system. Has Speed %…%; Acceleration %…%; DoorsState %…%; DomInvar MovingIffNonZeroSpeed: ( tr: Train) (Moving (tr)  tr.Speed 0) NonZeroSpeedIfNonZeroAcceler: ( tr: Train) (tr.Acceleration 0  tr.Speed 0) ClosedIfNotOpen: ( tr: Train) (tr.DoorsState ‘open’  tr.DoorsState = ‘closed’) Init For any train tr: tr.Speed = 0 tr.Acceleration = 0 tr.DoorsState = ‘closed’ Issue How about trains under maintenance? Block … Name On Def The current localization of a train on system blocks. DomInvar OnTwoBlocksAtMost: A train is on one or two successive blocks at any time. Init Any train entering the system is on the main station block
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Explicit PCA Regression on training/test set • We have for training set: ˆ train train train  yn Tnh wh  yn ˆ train train trainT train  1 trainT train yn Tnh Thn Tnh  Thn yn • And for the test set: ˆ test test test train yk Tkh wh  yk ˆ test yk Tkhtest ThntrainT Tnhtrain  X test km T mh B train T yn trainT train  1 trainT train Thn Tnh Thn yn   1 trainT hn 
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Protective Work Clothing & Equipment (PPE) • PPE is to be provided at no cost to the employee. • Examples: GLOVES, goggles, apron, “booties” • Assure appropriate PPE is readily accessible and fits properly • Supervisor will monitor and ensure employee uses PPE. • Provide for cleaning, laundering, or disposal of PPE.
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