16 research outputs found
Tuning a Josephson junction through a quantum critical point
We tune the barrier of a Josephson junction through a zero-temperature
metal-insulator transition and study the thermodynamic behavior of the junction
in the proximity of the quantum-critical point. We examine a
short-coherence-length superconductor and a barrier (that is described by a
Falicov-Kimball model) using the local approximation and dynamical mean-field
theory. The inhomogeneous system is self-consistently solved by performing a
Fourier transformation in the planar momentum and exactly inverting the
remaining one-dimensional matrix with the renormalized perturbation expansion.
Our results show a delicate interplay between oscillations on the scale of the
Fermi wavelength and pair-field correlations on the scale of the coherence
length, variations in the current-phase relationship, and dramatic changes in
the characteristic voltage as a function of the barrier thickness or
correlation strength (which can lead to an ``intrinsic'' pinhole effect).Comment: 16 pages, 15 figures, ReVTe
A time predefined variable depth search for nurse rostering
This paper presents a variable depth search for the nurse rostering problem. The algorithm works by chaining together single neighbourhood swaps into more effective compound moves. It achieves this by using heuristics to decide whether to continue extending a chain and which candidates to examine as the next potential link in the chain. Because end users vary in how long they are willing to wait for solutions, a particular goal of this research was to create an algorithm that accepts a user specified computational time limit and uses it effectively. When compared against previously published approaches the results show that the algorithm is very competitive
A scatter search methodology for the nurse rostering problem
The benefits of automating the nurse scheduling process in hospitals include reducing the planning workload and associated costs and being able to create higher quality and more flexible schedules. This has become more important recently in order to retain nurses and to attract more people into the profession. Better quality rosters also reduce fatigue and stress due to overwork and poor scheduling and help to maximise the use of leisure time by satisfying more requests. A more contented workforce will lead to higher productivity, increased quality of patient service and a better level of healthcare. This paper presents a scatter search approach for the problem of automatically creating nurse rosters. Scatter search is an evolutionary algorithm, which has been successfully applied across a number of problem domains. To adapt and apply scatter search to nurse rostering, it was necessary to develop novel implementations of some of scatter search's subroutines. The algorithm was then tested on publicly available real-world benchmark instances and compared against previously published approaches. The results show the proposed algorithm is a robust and effective method on a wide variety of real-world instances
An assessment of a days off decomposition approach to personnel shift scheduling
This paper studies a two-phase decomposition approach to solving the personnel scheduling problem. The first phase creates a days-off-schedule, indicating working days and days off for each employee. The second phase assigns shifts to the working days in the days-off-schedule. This decomposition is motivated by the fact that personnel scheduling constraints are often divided into two categories: one specifies constraints on working days and days off, while the other specifies constraints on shift assignments. To assess the consequences of the decomposition approach, we apply it to public benchmark instances, and compare this to solving the personnel scheduling problem directly. In all steps we use mathematical programming. We also study the extension that includes night shifts in the first phase of the decomposition. We present a detailed results analysis, and analyze the effect of various instance parameters on the decompositions’ results. In general, we observe that the decompositions significantly reduce the computation time, but the quality, though often good, depends strongly on the instance at hand. Our analysis identifies which aspects in the instance can jeopardize the quality
A shift sequence based approach for nurse scheduling and a new benchmark dataset
This paper investigates an adaptive constructive method for solving nurse rostering problems. The constraints considered in the problems are categorised into three classes: those that are sequence related, those that are nurse schedule related and those that are roster related. We propose a decomposition approach (to construct solutions) that consists of two stages: (1) to construct high quality sequences for nurses by only considering the sequence constraints, and (2) to iteratively construct schedules for nurses and the overall rosters, based on the sequences built and considering the schedule and roster constraints. In the second stage of the schedule construction, nurses are ordered and selected adaptively according to the quality of the schedules they were assigned to in the last iteration. Greedy local search is carried out during and after the roster construction, in order to improve the (partial) rosters built. We show that the local search heuristic during the roster construction can further improve the constructed solutions for the benchmark problems tested. In addition, we introduce new benchmark nurse rostering datasets which are based upon real world data. The data sets represent a variety of real world constraints. The publication of this problem data to the research community is aimed at closing the gap between theory and practice in nurse scheduling research. One of the main objectives is to encourage more research on these data sets
Blockchain Governance and the Role of Trust Service Providers: The TrustedChainn Network
JC Virus Multiplication in Human Hematopoietic Progenitor Cells Requires the NF-1 Class D Transcription Factor
JCV, a small DNA virus of the polyomavirus family, has been shown to infect glial cells of the central nervous system, hematopoietic progenitor cells, and immune system lymphocytes. A family of DNA binding proteins called nuclear factor-1 (NF-1) has been linked with site-coding specific transcription of cellular and viral genes and replication of some viruses, including JC virus (JCV). It is unclear which NF-1 gene product must be expressed by cells to promote JCV multiplication. Previously, it was shown that elevated levels of NF-1 class D mRNA were expressed by human brain cells that are highly susceptible to JCV infection but not by JCV nonpermissive HeLa cells. Recently, we reported that CD34(+) precursor cells of the KG-1 line, when treated with the phorbol ester phorbol 12-myristate 13-acetate (PMA), differentiated to cells with macrophage-like characteristics and lost susceptibility to JCV infection. These studies have now been extended by asking whether loss of JCV susceptibility by PMA-treated KG-1 cells is linked with alterations in levels of NF-1 class D expression. Using reverse transcription-PCR, we have found that PMA-treated KG-1 cells express mRNA that codes for all four classes of NF-1 proteins, although different levels of RNA expression were observed in the hematopoietic cells differentiated into macrophages. Northern hybridization confirms that the expression of NF-1 class D gene is lower in JCV nonpermissive PMA-treated KG-1 cells compared with non-PMA-treated cells. Further, using gel mobility shift assays, we were able to show the induction of specific NF-1–DNA complexes in KG-1 cells undergoing PMA treatment. The binding increases in direct relation to the duration of PMA treatment. These results suggest that the binding pattern of NF-1 class members may change in hematopoietic precursor cells, such as KG-1, as they undergo differentiation to macrophage-like cells. Transfection of PMA-treated KG-1 cells with an NF-1 class D expression vector restored the susceptibility of these cells to JCV infection, while the transfection of PMA-treated KG-1 cells with NF-1 class A, B, and C vectors was not able to restore JCV susceptibility. These data collectively suggest that selective expression of NF-1 class D has a regulatory role in JCV multiplication