Diagnosis in Fast-TAD (overlaid on BISTer-1) Ses Ses S1 S1 PLB PLB A A B B C DC TPG ORA TPG ORA CUT TPG b1,b2 CUT TPG b1,b2 CUT CUT c1,c2 c1,c2 b1,b2 D A S3 S3 S4 S4 CUT CUT CUT CUT d1,d2 d1,d2 a1,a2 a1,a2 a1,a2 CUT b1,b2 ORA S1 Theorem: Fast-TAD using BISTer-1 is 1-diagnosable • A f-faulty PLB Q config. as a TPG will have a GS of √ while Q configured as a CUT & performing its oper. functions will have GS of X. In all other cases GS is either a √ or a X a1,a2 CUT • In some cases, faults in A and C ( or B and D) ORA a1,a2 TPG ORA b1,b2 CUT CUT CUT CUT ORA TPG TPG ORA b1,b2 c1,c2 c1,c2 d1,d2 c1,c2 f-faulty PLB S2 S2 • Each PLB is tested in its two operational fn. d1,d2 CUT S3CUTS4 S2 may not be distinguishable – a 2nd test reqd. • Require 10.t1 time versus 16.t1 if both CUTs in a session are config. both their oper fns. Ses. PLB S1 S2 (C/A) (B/D) CUT b1,b2 ORA c1,c2 d1,d2 TPG √√ Xd1,d2 /√ X/√ a1,a2 X X/√ X/√ X A TPG B X √ X/√ X/√ B C X/√ X/√ X X √ √ X/√ X/√ CUT CUT c1,c2 b1,b2 C ORA D X/√ X/√ X √ CUT c1,c2 D ORA TPG Faulty PLB S1 (C/A) A √ B C D S2 (B/D) X X √
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Our BISTer-1 Architecture TPG A ORA B CUT TPG C CUT Sess  PLB  S1 ORA CUT D S2 S3 S4 S1 S2 S3 S4 Inference √ √ √ √ No faulty PLB X √ √ √ Fault not in PLB √ X √ √ Fault not in PLB √ √ X √ Fault not in PLB √ √ √ X Fault not in PLB X X √ √ Faulty C (CUT) √ X X √ Faulty D (CUT) √ √ X X Faulty A (CUT) X √ √ X Faulty B (CUT) X √ X √ Fault not in PLB √ X √ X Fault not in PLB A TPG ORA CUT CUT B CUT TPG ORA CUT X X X √ Faulty D √ X X X Faulty A C CUT CUT TPG ORA X X √ X Faulty C D ORA CUT CUT TPG X √ X X Faulty B X X X X Fault not in PLB
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Very Simple Weighted SP1 and SP2 K-plex Search on G6 Weighting: 0,1path nbrs of x times 3; 2path nbrs of x times 2; Until all degrees are weighted, then back to actual subgraph degrees H={123456789abc deg999923634438 H={123456789abc deg 999923634438 H={123456789abc deg 99962333886c H={123456789abc deg 996946334434 UNWEIGHTED Degrees H={123456789abc deg 333323334434 SP1 1 2 3 4 5 6 7 8 9 a b c 1 0 1 1 1 2 1 0 1 1 3 1 1 0 0 4 1 1 0 0 5 0 0 0 0 6 0 0 0 0 7 0 0 0 1 8 0 0 0 0 9 0 0 0 0 a 0 0 0 0 b 0 0 0 0 c 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 1 0 1 0 1 1 1 1 0 0 0 1 0 0 0 0 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 1 1 1 1 0 1 1 1 1 0 1 1 1 1 0 3 3 3 3 2 3 3 3 4 4 3 4 H=15 H=7 kplex k8 x=1 after cutting x=2 H={123456789abc deg999923634438 2,3,4 H={123456789abc deg999923634438 2,3,4 x=3 H={123456789abc deg 99962333886c H=6 H=4 2plex x=3, after cut 2368 x=1 x=4 H={123456789abc deg 996946334434 H=15 H=7 kplex k8 x=2 after cutting H=3 x=4 H={123456789abc k1 deg999923634438 H={123456789abc k1 deg999923634438 H={123456789abc deg 222623338861 H=6 H=5 kplex x=1, after cut 23468 H=6 H=5 kplex x=2, after cut 23468 H=3 H=3 0plex x=3 after cut 1 (actual subgraph degrees) H=3 0plex after cut 2346 H={123456789abc deg 333669964434 H=10 H=5 5plex x=5 after cut 34 H={123456789abc deg 333669964434 x=5 H={123456789abc deg 333669998834 x=6 H={123456789abc deg 333669998834 x=6 after cut 34 H={123456789abc deg 33312333223 H=3 H=2 1plex x=6 after cut 12 SG degs 211 H={123456789abc deg 333969934434 x=7 H={123456789abc deg 333969998834x=7 after cut 34 H={123456789abc deg 333122232234 H=3 H=3 0plex x=7 after cut 1 SG degs H={123456789abc deg 33334969cc68 x=8 H={123456789abc deg 33334969cc68 x=8 after cut 34 H={123456789abc H=3 H=3 0plex deg 333123314434x=5 after cut 1 from SG degs H={123456789abc deg 333342134433 SP2 1 2 3 4 1 0 0 0 0 2 0 0 0 0 3 0 0 0 1 4 0 0 1 0 5 0 0 0 1 6 0 0 0 1 7 1 1 0 0 8 0 0 0 0 9 0 0 1 0 a 0 0 1 0 b 0 0 1 0 c 1 1 0 0 H={123456789abc deg 33632639cc9c x=9 5 6 7 8 9 a b c 0 0 1 0 0 0 1 0 0 0 0 0 1 1 0 0 0 0 0 1 0 0 0 0 0 0 0 1 1 0 1 0 0 1 0 0 0 1 0 0 0 0 0 1 0 0 0 1 H={123456789abc deg 33632639cc9c x=a H={123456789abc deg 33632639cc9c H=10 H=8 H a kplex k 2 x=a after cut 2,3,6 0 0 0 1 0 0 0 1 1 1 1 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 H={123456789abc deg 33632336cc9c x=b H={123456789abc deg 33632639cc9c H=6 H=6 H a kplex k 0 x=b after cut 2,3,6 SP3 1 2 3 4 5 6 7 8 1 0 0 0 0 2 0 0 0 0 3 0 0 0 0 4 0 0 0 0 5 1 1 0 0 6 1 1 0 0 7 0 0 1 0 8 0 0 1 1 9 1 1 0 0 a 1 1 0 0 b 1 1 0 0 c 0 0 0 1 H={123456789abc deg 66932336ccpc x=c 1 1 0 0 1 1 0 0 0 0 1 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 1 0 1 0 0 1 0 0 0 1 0 0 9 a b c 1 1 1 0 1 1 1 0 0 0 0 0 0 0 0 1 1 1 0 0 0 0 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 SP4 1 2 3 4 1 0 0 0 0 2 0 0 0 0 3 0 0 0 0 4 0 0 0 0 5 0 0 1 0 6 0 0 1 0 7 0 0 0 0 8 1 1 0 0 9 0 0 0 1 a 0 0 0 1 b 0 0 0 1 c 0 0 0 0 5 6 7 8 0 0 0 1 0 0 0 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 1 0 1 0 9 a b c 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 0 0 0 1 1 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 H={123456789abc deg 33632639cc9c 2,3,6 H={123456789abc deg 66932336cc9c 2plex x=8 after cut12 SG degs H=10 H=8 H a kplex k 2 x=9 after Cutting H=6 H=6 H a kplex k 0 x=c after cut 2,3,6 By weighting the initial round we have gotten nearly perfect information for this example (G6). The weightings, 3 and 2, were arbitrarily chosen but worked here. In general, one should devise a formula to determine them. Also we could weight SP3 and etc. as well? If we have paid the price of constructing SPk k>1, this is a much simpler way to do it, as compared to the Clique Percolation method of Palla (next slide). G6 1 5 4 2 6 7 3 c 9 b 8 a
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Our BISTer-1 Architecture Each PLB is a CUT in 2 unique sessn’s and a TPG in another unique session – this serves to uniquelyis identify the Theorem: BISTer-1 1-diagnosable faulty PLB which will have a X X √ in these sessions. Sess  PLB  S1 S2 S3 S4 S1 S2 S3 S4 Inference √ √ √ √ No faulty PLB X √ √ √ Fault not in PLB √ X √ √ Fault not in PLB √ √ X √ Fault not in PLB √ √ √ X Fault not in PLB X X √ √ Faulty C (CUT) √ X X √ Faulty D (CUT) √ √ X X Faulty A (CUT) X √ √ X Faulty B (CUT) X √ X √ Fault not in PLB √ X √ X Fault not in PLB A TPG ORA CUT CUT B CUT TPG ORA CUT X X X √ Faulty D √ X X X Faulty A C CUT CUT TPG ORA X X √ X Faulty C D ORA CUT CUT TPG X √ X X Faulty B X X X X Fault not in PLB
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BISTer-2 architecture B CUT A TPG C ORA F ORA 1 2 Y1 Y1 – output of the ORA comparing CUTs Y2 – output of the ORA comparing TPGs Theorem: BISTer-2 is 1-diagnosable Proof: Gross syndrome corresponding to Y1 for each faulty PLB is unique. E.g. Y1 is pass in section 2 only for faulty PLB A and no other PLB. Y2 E D CUT TPG OR1 => ORA 1 (Y1) OR2 => ORA 2 (Y2) S1 S2 S3 S4 S5 S6 A TPG OR2 TPG CUT OR1 CUT B CUT TPG OR2 TPG CUT OR1 C OR1 CUT TPG OR2 TPG CUT D CUT OR1 CUT TPG OR2 TPG E TPG CUT OR1 CUT TPG OR2 F OR2 TPG CUT OR1 CUT TPG Gross syndrome corresponding to Y1 Faulty PLB S1 S2 S3 S4 S5 S6 A X √ X X X X B X X √ X X X C X X X √ X X D X X X X √ X E X X X X X √ F √ X X X X X
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Isolate 4 CONCLUSIONS BACKGROUND Acinetobacter spp. Has been documented as the cause of numerous nosocomial outbreaks and has been associated with increased lengths of stay in the ICU as well as increased mortality in infected ICU patients. In our institution the number of isolates cultured nearly doubled from 1998-2000 compared to 2001 with over one-third being multi-drug resistant. Susceptibility to commonly used antibiotics including cefepime piperacillin/tazobactam, and ampicillin/ sulbactam decreased while imipenem/cilistatin and tobramycin susceptibility remained stable. Antimicrobial resistance makes drug selection difficult. Inappropriate antimicrobial selection can lead to increased mortality, while exposure to broad spectrum antimicrobials is associated with development of resistance. Initial selection of antimicrobials at optimal dosing may have a significant effects on patient outcome antimicrobial resistance. Carbapenems alone or in combination with other antimicrobials are considered to be a therapy-ofchoice for Acinetobacter infections. The purpose of this study was to compare the bactericidal effects of imipenem/cilistatin (IC) and meropenem (M) against AC clinical isolates using an in vitro PK bacteremia model. Meropenem 3/4 runs Meropenem 1/4 runs Imipenem 8 7 6 5 4 Table 2. MIC/MBC for Meropenem and Imipenem Against Isolate 4 After Exposure to Meropenem 3 2 1 0 2 4 6 8 10 1224 30 36 42 48 MIC/MBC (mcg/ml) 48 hr. 24 hr. 48 hr. antibiotic 48 hr. Isolate Model Drug Baseline drug-free model plate drug-free plate sample (4x plate MIC) Meropenem 1/1 1/>16 >16/ND 128/ND 128/ND A Imipenem 0.5/0.5 1/1 >16/ND >128/ND >128/ND 4 Meropenem 1/1 NG NG NG NG B Imipenem 0.5/0.5 NG NG NG NG Time (hrs) Isolate 7 METHODS Organisms/Susceptibilities. Four AC clinical isolates were tested. Baseline data collected for M an IC against isolate included: MIC/MBC by microtiter methodologies following NCCLS protocol. Ppresence of resistant subpopulations on antibiotic containing plates representing 2x and 4x the MIC. Frequency of resistance = the number of organisms growing on the antibiotic-containing medium divided by number of antibiotic-free agar plates. Meropenem 5/6 runs Meropenem 1/6 runs Imipenem 8 7 6 5 4 3 2 1 0 In vitro pharmacokinetic/pharmacodynamic model. Isolates were tested over 48 hours against M and IC in a glass one compartment in vitro PK model emulating a bloodstream infection. Drug regimens and human PK parameters to be simulated include: 1) Imipenem/cilistatin 500 mg every six hours simulating a peak concentration of 40 mcg/ml and a half-life of 1 hour. 2) Meropenem 1 gram every 8 hours simulating a peak concentration of 60 mcg/ml and a half-life of 1 hour. 2 4 6 8 10 1224 30 36 42 48 Table 3. MIC/MBC for Meropenem and Imipenem Against Isolate 7 After Exposure to Meropenem MIC/MBC (mcg/ml) 48 hr. 24 hr. 48 hr. antibiotic 48 hr. Isolate Model Drug Baseline drug-free model plate drug-free plate sample (4x plate MIC) Meropenem 1/1 2/2 >16/ND 4/64 128/ND C Imipenem 0.5/0.5 1/1 >16/ND 1/32 >128/ND 7 Meropenem 1/1 2/2 >16/ND 4/64 4/32 D Imipenem 0.5/0.5 1/1 >16/ND 0.5/32 1/16 Time (hrs) Resistant subpopulations were seen in all isolates for IC and M (Table 1). Both agents provided bactericidal killing against 3/4 isolates. Regrowth occurred earlier for M in 3/4 isolates with IC maintaining killing at or below 2 log for ≥ 30 hours in 2/4 isolates. Despite regrowth occurring, no changes in MIC/MBC or growth on antibiotic-containing media were noted for isolates 9 and 10 for either M or IC. In contrast, MIC/MBC changes did occur with isolates 4 and 7. Tables 2 and 3 describe examples of these changes. For isolate 4, selection of a resistant clone likely occurred leading to regrowth in 3/4 model runs. High level resistance was seen when sampling directly from the model as well as off the antibioticcontaining medium. One of 4 runs did not regrow and may be attributed to lack of selection of a resistant clone. MIC/MBC changes occurring in isolate 7 are more difficult to explain. Selection of a resistant clone explains the regrowth occuring in 5/6 runs. No change in MIC/MBC occurred when evauating growth from the 24 hr drug-free plates. Induction of resistance with the addition of the antimicrobial likely occurred followed by reversion back to the susceptible form with the removal of drug pressure. Highly resistant MICs at 48 hours from samples from the model are expected. Tolerance, low MICs and elevated MBCs, is seen when evaluating growth from the 48 hr antibiotic-containing medium as well as with one run of the 48 drug-free plates. A second example (model C) at 48 hrs. maintained high level resistance despite removal of drug pressure. M and IC had similar rates of killing with both agents being bactericidal in 3/4 isolates. IC had superior duration of bacterial killing compared to M against AC. Despite initial bactericidal activity, significant regrowth occurred for all isolates against both drugs by 48 hours. This suggests carbapenem monotherapy may select for resistant populations or induce resistance and coul lead to potential drug failure. The presence of resistant subpopulations may support the use of combination therapy in AC infections.
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Lesson 12. Personal Safety and Hygiene  Footwear and Ear Protection  Footwear:     Personnel who work on wet floors should wear rubber boots or shoes. Non-slip bottoms and steel-toed shoes offer protection against slipping, as well as protecting against injuries from dropped equipment. Disposable shoe covers must be worn over shoes to prevent cross-contamination in germfree, quarantine and isolation areas. Work shoes must be worn only in the facility; they should never be taken or worn home.  Ear Protection:  Ear protectors or ear plugs are recommended in all noisy areas (such as cagewash areas) in which the average noise level is 85 decibels or greater.
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Autonomous saw  Inputs: Pressure sensors, touch sensors, position sensors, position sensor, safety sensors, Variable Frequency Drive (VFD) speed feedback (4-20 mA) for saw blade  Outputs: Open/Close clamps command, Raise/Lower saw, Move pipe Forward/Backward, coolant pump On/Off, saw blade speed command (4-20 mA)  Controller: Allen Bradley Programmable Logic Controller (PLC)  Application: Cut long pipes into specified length. Tolerance is +/- 0.005 in.  Sequence: 1. Select length and press Start 2. Close rear clamps 3. Close front clamps 4. Lower saw and cut 5. Retract pipe 6. Raise saw and open front clamps 7. Index pipe 8. Close from clamps 9. Repeat the sequence until end of pipe http://www.google.com/imgres? q=pipe+cutting+saw+machine&um=1&hl=en&biw=1024&bih=562&tbm=isch&t bnid=WliuZzoKoLVvgM:&imgrefurl=http://www.ecvv.com/product/1872085.ht ml&docid=OFdWWiTxazEgzM&imgurl=http://upload.ecvv.com/upload/Product/ 20093/China_Highly_efficient_Pipe_Cutting_Band_Saw_Machine20093111546 170.jpg&w=1024&h=768&ei=-NTgT4KvK8ry0gHP0oG3Dg&zoom=1 8
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W.W.G.C.S.A. Pesticide Seminar – 2009 Understanding and Reading Pesticide Labels and MSDS MSDS Ingestion Prevent eating, drinking, tobacco usage and cosmetic application in areas where there is a potential for exposure to the material. Wash thoroughly with soap and water after handling. Where eye contact is likely, use chemical splash goggles. Facilities storing or utilizing Eye Contact this material should be equipped with an eyewash facility and a safety shower. Where contact is likely, wear chemical-resistant (such as nitrile or butyl) gloves, Skin Contact coveralls, socks and chemical-resistant footwear. For overhead exposure, wear chemical-resistant headgear. Inhalation Use process enclosures, local exhaust ventilation, or other engineering controls to keep airborne levels below exposure limits. A NIOSH-certified combination airpurifying respirator with an N, P or R 95 or HE class filter and an organic vapor cartridge may be permissible under certain circumstances where airborne concentrations are expected to exceed exposure limits. Protection provided by airpurifying respirators is limited. Use a pressure demand atmosphere-supplying respirator if there is any potential for uncontrolled release, exposure levels are not known, or under any other circumstances where air-purifying respirators
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BISTer-0 [M. Abramovici et. al., ITC ’99] S1 S2 S3 S4 Theorem: BISTer-0 is zero-diagnosable. A B C D TPG CUT ORA CUT Proof: The same pair of PLBs are configured as CUT TPG CUT ORA CUTs in two different sessions: PLBs A and C in S2 and S4 ORA CUT TPG CUT PLBs B and D in S1 and S3. CUT ORA CUT TPG When either PLB fails, the gross syndrome will be identical in these sessions. Faulty S1 S2 S3 S4 PLB E.g. if A fails as a CUT only, then its gross syndrome is identical to the gross syn. of √/ A √ X X C failing as a CUT only. Hence we cannot X distinguish between faulty PLBs A and C. C √/ X X √ X Thus has a complex adaptive diagnosis phase
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