A multi-objective programming model for scheduling emergency medicine residents

Scheduling emergency medicine residents (EMRs) is a complex task, which considers a large number of rules (often conflicting) related to various aspects such as limits on the number of consecutive work hours, number of day and night shifts that should be worked by each resident, resident staffing requirements according to seniority levels for the day and night shifts, restrictions on the number of consecutive day and night shifts assigned, vacation periods, weekend off requests, and fair distribution of responsibilities among the residents. Emergency rooms (ERs) are stressful workplaces, and in addition shift work is well-known to be more demanding than regular daytime work. For this reason, preparing schedules that suit the working rules for EMRs is especially important for reducing the negative impact on shift workers physiologically, psychologically, and socially. In this paper, we present a goal programming (GP) model that accommodates both hard and soft constraints for a monthly planning horizon. The hard constraints should be adhered to strictly, whereas the soft constraints can be violated when necessary. The relative importance values of the soft constraints have been computed by the analytical hierarchy process (AHP), which are used as coefficients of the deviations from the soft constraints in the objective function. The model has been tested in the ER of a major local university hospital. The main conclusions of the study are that problems of realistic size can be solved quickly and the generated schedules have very high qualities compared to the manually prepared schedules, which require a lot of effort and time from the chief resident who is responsible for this duty.     

A constraint programming-based solution approach for medical resident scheduling problems

Persistent calls come from within the graduate medical education community and from external sources for regulating the resident duty hours in order to meet the obligations about the quality of resident education, the well-being of residents themselves, and the quality of patient care services. The report of the Accreditation Council for Graduate Medical Education (ACGME) proposes common program requirements for resident hours. In this paper, we first develop a mixed-integer programming model for scheduling residents’ duty hours considering the on-call night, day-off, rest period, and total work-hour ACGME regulations as well as the demand coverage requirements of the residency program. Subsequently, we propose a column generation model that consists of a master problem and an auxiliary problem. The master problem finds a configuration of individual schedules that minimizes the sum of deviations from the desired service levels for the day and night periods. The formulation of this problem is possible by representing the feasible schedules using column variables, whereas the auxiliary problem finds the whole set of feasible schedules using constraint programming. The proposed approach has been tested on a series of problems using real data obtained from a hospital. The results indicate that high-quality schedules can be obtained within a few seconds.     

Tailoring Cu/Al2O3 catalysts for the catalytic pyrolysis of tomato waste

In this study, pyrolysis of tomato waste has been performed in fixed bed tubular reactor at 500 °C, both in absence and presence of Cu/Al₂O₃ catalyst. The influences of heating rate, catalyst preparation method and catalyst loading on bio-oil yields and properties were examined. According to pyrolysis experiments, the highest bio-oil yield was obtained as 30.31% with a heating rate of 100 °C/min, 5% Cu/Al₂O₃ catalyst loading ratio and co-precipitation method. Results showed that the catalysts have strong positive effect on bio-oil yields. Bio-oil quality obtained from fast catalytic pyrolysis was more favorable than that obtained from non-catalytic and slow catalytic pyrolysis.     

A review of supply chain complexity drivers

Studies on supply chain complexity mainly use the static and dynamic complexity distinction. While static complexity describes the structure of the supply chain, the number and the variety of its components and strengths of interactions between these; the dynamic complexity represents the uncertainty in the supply chain and involves the aspects of time and randomness. This distinction is also valid when classifying the drivers of supply chain complexity according to the way they are generated. Supply chain complexity drivers (e.g., number/variety of suppliers, number/variety of customers, number/variety of interactions, conflicting policies, demand amplification, differing/conflicting/non-synchronized decisions and actions, incompatible IT systems) play a significant and varying role in dealing with complexity of the different types of supply chains (e.g., food, chemical, electronics, automotive).     

Weibull renewal equation solution

The existing solution methods for the Weibull Renewal Equation suffer from a lack of sufficient accuracy due to the singularity at the origin for some parameter values of the weibull density. The proposed method of solution provides accuracy to any desired degree of precision for all parameter values particularly in the singular range. The method utilizes a cubic spline approximation of the unknown renewal function and applies the Galerkin technique of integral equation solution. Gaussian quadratures are used to evaluate integrals. The singular nature of the integrand is handled by the Gauss-Jacobi quadrature. Results are compared with those obtained by simulation.     

Poly(glycidyl methacrylate‐co‐3‐thienyl‐methylmethacrylate) based working electrodes for hydrogen peroxide biosensing

BACKGROUND: Hydrogen peroxide biosensors based on Poly(glycidyl methacrylate‐co‐3‐thienylmethylmethacrylate)/ Polypyrrole [Poly(GMA‐co‐MTM)/PPy] composite film were reported. Poly(GMA‐co‐MTM) including various amounts of GMA and MTM monomers was synthesized via the radical polymerization. Enzyme horseradish peroxidase (HRP) was trapped in Poly(GMA‐co‐MTM)/PPy composites during the electropolymerization reaction between pyrrole and thiophene groups of MTM monomer, and chemically bonded via the epoxy groups of GMA. Analytical parameters of the fabricated electrodes were calculated and are discussed in terms of film electroactivity and mass transfer conditions of the composite films. RESULTS: The amount of electroactive HRP was found to be 1.25, 0.34 and 0.213 µg for the working electrodes of Poly(GMA_30%‐ co‐MTM_70%)/PPy/HRP, Poly(GMA_85%‐co‐MTM_15%)/PPy/HRP and Poly(GMA_90%‐co‐MTM_10%)/PPy/HRP, respectively. Optimal response of the fabricated electrodes was obtained at pH 7 and an operational potential of ? 0.35 V. It was observed that effective enzyme immobilization and electroactivity of the composite films could be changed by changing the ratios of GMA and MTM fractions of Poly(GMA‐co‐MTM) based working electrodes. CONCLUSION: The amount of electroactive enzyme increases with increasing MTM content of the final copolymer. High operational stabilities of the biosensors can be attributed to the strong covalent enzyme linkage via the epoxy groups of GMA due to preventing enzyme deterioration and loss. A more convenient microenvironment for mass transfer was provided for the electrodes by higher GMA ratios. It is observed that mass transfer is dominated by the mechanism of electron transfer to obtain effective sensitivity values. This work contributes to discussions clarifying the problems regarding the design parameters of biosensors. Copyright © 2011 Society of Chemical Industry     

New current–mode special function continuous-time active filters employing only OTAs and OPAMPs

This paper reports three current mode second order filters, each of which realizes a specific function without any external passive elements. These filters realize low-pass notch (LPN), high-pass notch (HPN) and all-pass (AP) functions. Two OPAMPs, a double output OTA and a single output OTA are employed for each circuit. The filter structures can be easily cascaded since they have high output impedances. This property is especially useful for achieving high-order filters using these LPN and HPN filters as building blocks. The presented theory is verified with macro models in SPICE simulations and, using the SPICE parameters of the layout technology, post layout simulations are carried out, with parasitics extracted from the layouts of the filter chips.     

Process Variation-Aware Multiple-Fault Diagnosis of Thermometer-Coded Current-Steering DACs

In this brief, we first introduce a process-variation-aware test-point generation method. With this method, faults are not obscured by process variations and we are able to generate new test points by measuring a very limited number of current values on-chip and estimating values of the remaining currents. We furthermore introduce a multiple-fault diagnosis procedure where we use the process-variation aware test-point generation method. The proposed methods can also be used for structural test. For the application, we have used a thermometer coded current steering digital to analog converter, as they are widely used due to their suitability for high speed applications and the symmetric design is suitable for the application of our method. We introduce a design-for-test hardware for the diagnosis cost reduction, while implementing our methods. Experimental results show that parametric errors as small as 20% can be diagnosed with up to 97.8% accuracy