A simulation based learning meachanism for scheduling systems with continuous control and update structure

A simulation based learning mechanism is proposed in this study. The system learns in the manufacturing environment by constructing a learning tree and selects a dispatching rule from the tree for each scheduling period. The system utilizes the process control charts to monitor the performance of the learning tree which is automatically updated whenever necessary. Therefore, the system adapts itself for the changes in the manufacturing environment and works well over time. Extensive simulation experiments are conducted for the system parameters such as monitoring (MPL) and scheduling period lengths (SPL) on a job shop problem with objective of minimizing average tardiness. Simulation results show that the performance of the proposed system is considerably better than the simulation-based single-pass and multi-pass scheduling algorithms available in the literature

Real time selection of scheduling rules and knowledge extraction via dynamically controlled data mining

A new scheduling system for selecting dispatching rules in real time is developed by combining the techniques of simulation, data mining, and statistical process control charts. The proposed scheduling system extracts knowledge from data coming from the manufacturing environment by constructing a decision tree, and selects a dispatching rule from the tree for each scheduling period. In addition, the system utilises the process control charts to monitor the performance of the decision tree and dynamically updates this decision tree whenever the manufacturing conditions change. This gives the proposed system the ability to adapt itself to changes in the manufacturing environment and improve the quality of its decisions. We implement the proposed system on a job shop problem, with the objective of minimising average tardiness, to evaluate its performance. Simulation results indicate that the performance of the proposed system is considerably better than other simulation-based single-pass and multi-pass scheduling algorithms available in the literature. We also illustrate knowledge extraction by presenting a sample decision tree from our experiments. © 2010 Taylor & Francis

Salmonella enteritidis meningitis in a first time diagnosed AIDS patient: Case report

We describe a patient with salmonella enteritidis meningitis and unknown HIV infection

Impact of HLA polymorphism on the immune response to bacillus anthracis protective antigen in vaccination versus natural infection

The causative agent of anthrax, Bacillus anthracis, evades the host immune response and establishes infection through the production of binary exotoxins composed of Protective Antigen (PA) and one of two subunits, lethal factor (LF) or edema factor (EF). The majority of vaccination strategies have focused upon the antibody response to the PA subunit. We have used a panel of humanised HLA class II transgenic mouse strains to define HLA-DR-restricted and HLA-DQ-restricted CD4+ T cell responses to the immunodominant epitopes of PA. This was correlated with the binding affinities of epitopes to HLA class II molecules, as well as the responses of two human cohorts: individuals vaccinated with the Anthrax Vaccine Precipitated (AVP) vaccine (which contains PA and trace amounts of LF), and patients recovering from cutaneous anthrax infections. The infected and vaccinated cohorts expressing different HLA types were found to make CD4+ T cell responses to multiple and diverse epitopes of PA. The effects of HLA polymorphism were explored using transgenic mouse lines, which demonstrated differential susceptibility, indicating that HLA-DR1 and HLA-DQ8 alleles conferred protective immunity relative to HLA-DR15, HLA-DR4 and HLA-DQ6. The HLA transgenics enabled a reductionist approach, allowing us to better define CD4+ T cell epitopes. Appreciating the effects of HLA polymorphism on the variability of responses to natural infection and vaccination is vital in planning protective strategies against anthrax

Predictors of hospital mortality among septic ICU patients with Acinetobacter spp. bacteremia: A cohort study

BACKGROUND: We hypothesized that among septic ICU patients with Acinetobacter spp. bacteremia (Ac-BSI), carbapenem-resistant Acinetobacter spp. (CRAc) increase risk for inappropriate initial antibiotic therapy (non-IAAT), and non-IAAT is a predictor of hospital death. METHODS: We conducted a retrospective cohort study of adult septic ICU patients with Ac-BSI. Non-IAAT was defined as exposure to initially prescribed antibiotics not active against the pathogen based on in vitro susceptibility testing, and having no exposure to appropriate antimicrobial treatment within 24 hours of drawing positive culture. We compared patients who died to those who survived, and derived regression models to identify predictors of hospital mortality and of non-IAAT. RESULTS: Out of 131 patients with Ac-BSI, 65 (49.6%) died (non-survivors, NS). NS were older (63 [51, 76] vs. 56 [45, 66] years, p = 0.014), and sicker than survivors (S): APACHE II (24 [19, 31] vs. 18 [13, 22], p < 0.001) and Charlson (5 [2, 8] vs. 3 [1, 6], p = 0.009) scores. NS were also more likely than S to require pressors (75.4% vs. 42.4%, p < 0.001) and mechanical ventilation (75.4% vs. 53.0%, p = 0.008). Both CRAc (69.2% vs. 47.0%, p = 0.010) and non-IAAT (83.1% vs. 59.1%, p = 0.002) were more frequent among NS than S. In multivariate analyses, non-IAAT emerged as an independent predictor of hospital death (risk ratio [RR] 1.42, 95% confidence interval [CI] 1.10-1.58), while CRAc was the single strongest predictor of non-IAAT (RR 2.66, 95% CI 2.43-2.72). CONCLUSIONS: Among septic ICU patients with Ac-BSI, non-IAAT predicts mortality. Carbapenem resistance appears to mediate the relationship between non-IAAT and mortality

Multidrug resistance, inappropriate empiric treatment and hospital mortality in Acinetobacter baumannii pneumonia and sepsis

Background: The relationship between multidrug resistance (MDR), inappropriate empiric therapy (IET), and mortality among patients with Acinetobacter baumannii (AB) remains unclear. We examined it using a large U.S. database. Methods: We conducted a retrospective cohort study using the Premier Research database (2009–2013) of 175 U.S. hospitals. We included all adult patients admitted with pneumonia or sepsis as their principal diagnosis, or as a secondary diagnosis in the setting of respiratory failure, along with antibiotic administration within 2 days of admission. Only culture-confirmed infections were included. Resistance to at least three classes of antibiotics defined multidrug-resistant AB (MDR-AB). We used logistic regression to compute the adjusted relative risk ratio (RRR) of patients with MDR-AB receiving IET and IET’s impact on mortality. Results: Among 1423 patients with AB infection, 1171 (82.3 %) had MDR-AB. Those with MDR-AB were older (63.7 ± 15.4 vs. 61.0 ± 16.9 years, p = 0.014). Although chronic disease burden did not differ between groups, the MDR-AB group had higher illness severity than those in the non-MDR-AB group (intensive care unit 68.0 % vs. 59. 5 %, p < 0.001; mechanical ventilation 56.2 % vs. 42.1 %, p < 0.001). Patients with MDR-AB were more likely to receive IET than those in the non-MDR-AB group (76.2 % MDR-AB vs. 13.8 % non-MDR-AB, p < 0.001). In a regression model, MDR-AB strongly predicted receipt of IET (adjusted RRR 5.5, 95 % CI 4.0–7.7, p < 0.001). IET exposure was associated with higher hospital mortality (adjusted RRR 1.8, 95 % CI 1.4–2.3, p < 0.001). Conclusions: In this large U.S. database, the prevalence of MDR-AB among patients with AB infection was > 80 %. Harboring MDR-AB increased the risk of receiving IET more than fivefold, and IET nearly doubled hospital mortality

Active and Passive Immunization Protects against Lethal, Extreme Drug Resistant-Acinetobacter baumannii Infection

Extreme-drug-resistant (XDR) Acinetobacter baumannii is a rapidly emerging pathogen causing infections with unacceptably high mortality rates due to inadequate available treatment. New methods to prevent and treat such infections are a critical unmet medical need. To conduct a rational vaccine discovery program, OmpA was identified as the primary target of humoral immune response after intravenous infection by A. baumannii in mice. OmpA was >99% conserved at the amino acid level across clinical isolates harvested between 1951 and 2009 from cerebrospinal fluid, blood, lung, and wound infections, including carbapenem-resistant isolates, and was ≥89% conserved among other sequenced strains, but had minimal homology to the human proteome. Vaccination of diabetic mice with recombinant OmpA (rOmpA) with aluminum hydroxide adjuvant markedly improved survival and reduced tissue bacterial burden in mice infected intravenously. Vaccination induced high titers of anti-OmpA antibodies, the levels of which correlated with survival in mice. Passive transfer with immune sera recapitulated protection. Immune sera did not enhance complement-mediated killing but did enhance opsonophagocytic killing of A. baumannii. These results define active and passive immunization strategies to prevent and treat highly lethal, XDR A. baumannii infections