Network-Wide Optimal Scheduling of Transit Systems Using Genetic Algorithms

The primary objective of any transit system is to provide a better level of service to its passengers. One of the good measures of level of service is the waiting time of passengers during their journey. The waiting time consists of an initial waiting time (the time a passenger waits to board a vehicle at his or her point of origin) and a transfer time (the time a passenger waits at a transfer station while transferring from one vehicle to another). An efficient schedule minimizes the overall transfer time (TT) of passengers transferring between different routes as well as the initial waiting time (IWT) of the passengers waiting to board the vehicle at their point of origin. This paper uses genetic algorithm (GA)—a search and optimization procedure—to find optimal/near-optimal schedules of vehicles in a transit network. The main advantage of using GA is that the transit network scheduling problem can be reformulated in a manner that is computationally more efficient than the original problem. Further, the coding aspect of GA inherently takes care of most of the constraints associated with the scheduling problem. Results from a number of test problems show that GAs are able to find optimal/near-optimal schedules with minimal computational resources.     

Genetic Algorithms for Optimal Urban Transit Network Design

This article attempts to highlight the effectiveness of genetic algorithm (GA)–based procedures in solving the urban transit network design problem (UTNDP). The article analyzes why traditional methods have problems in solving the UTNDP. The article also suggests procedures to alleviate these problems using GA–based optimization technique. The thrust of the article is three–fold: (1) to show the effectiveness of GAs in solving the UTNDP, (2) to identify features of the UTNDP that make it a difficult problem for traditional techniques, and (3) to suggest directions, through the presentation of GA–based methodologies for the UTNDP, for the development of GA–based procedures for solving other optimization problems having features similar to the UTNDP.     

Topologically controlled growth of magnetic-metal-functionalized semiconductor oxide nanorods

Colloidal semiconductor-magnetic hybrid nanocrystals with topologically controlled composition are fabricated by heterogeneous nucleation of spherical epsilon-Co domains onto anatase TiO2 nanorods. The latter can be selectively decorated at either their tips or at multiple locations along their longitudinal sidewalls, forming lattice-matched heterointerfaces regardless of the metal deposition sites. The possibility of switching between either heterostructure growth modes arises from the facet-dependent chemical reactivity of the oxide seeds, which is governed mainly by selective adhesion of the surfactants rather than by small differences in misfit-induced interfacial strain at the relevant junction points.     

Tumor-Derived Small Extracellular Vesicles Induce Pro-Inflammatory Cytokine Expression and PD-L1 Regulation in M0 Macrophages via IL-6/STAT3 and TLR4 Signaling Pathways

Tumor-associated macrophages play a key role in promoting tumor progression by exerting an immunosuppressive phenotype associated with the expression of programmed cell death ligand 1 (PD-L1). It is well known that tumor-derived small extracellular vesicles (SEVs) affect the tumor microenvironment, influencing TAM behavior. The present study aimed to examine the effect of SEVs derived from colon cancer and multiple myeloma cells on macrophage functions. Non-polarized macrophages (M0) differentiated from THP-1 cells were co-cultured with SEVs derived from a colorectal cancer (CRC) cell line, SW480, and a multiple myeloma (MM) cell line, MM1.S. The expression of PD-L1, interleukin-6 (IL-6), and other inflammatory cytokines as well as of the underlying molecular mechanisms were evaluated. Our results indicate that SEVs can significantly upregulate the expressions of PD-L1 and IL-6 at both the mRNA and protein levels and can activate the STAT3 signaling pathway. Furthermore, we identified the TLR4/NF-kB pathway as a convergent mechanism for SEV-mediated PD-L1 expression. Overall, these preliminary data suggest that SEVs contribute to the formation of an immunosuppressive microenvironment.     

Filter for biomedical imaging and image processing

Image filtering techniques have numerous potential applications in biomedical imaging and image processing. The design of filters largely depends on the a priori, knowledge about the type of noise corrupting the image. This makes the standard filters application specific. Widely used filters such as average, Gaussian, and Wiener reduce noisy artifacts by smoothing. However, this operation normally results in smoothing of the edges as well. On the other hand, sharpening filters enhance the high-frequency details, making the image nonsmooth. An integrated general approach to design a finite impulse response filter based on Hebbian learning is proposed for optimal image filtering. This algorithm exploits the interpixel correlation by updating the filter coefficients using Hebbian learning. The algorithm is made iterative for achieving efficient learning from the neighborhood pixels. This algorithm performs optimal smoothing of the noisy image by preserving high-frequency as well as low-frequency features. Evaluation results show that the proposed finite impulse response filter is robust under various noise distributions such as Gaussian noise, salt-and-pepper noise, and speckle noise. Furthermore, the proposed approach does not require any a priori knowledge about the type of noise. The number of unknown parameters is few, and most of these parameters are adaptively obtained from the processed image. The proposed filter is successfully applied for image reconstruction in a positron emission tomography imaging modality. The images reconstructed by the proposed algorithm are found to be superior in quality compared with those reconstructed by existing PET image reconstruction methodologies.     

Synthesis of CuCr and CuCrAg alloy with nano-ceramic dispersion by mechanical alloying and consolidation by laser assisted sintering

Cu-4.5Cr and Cu-4.5Cr-3Ag (in wt%) alloys without or with 10 wt% nanocrystalline Al₂O₃ and ZrO₂ dispersion have been synthesized by mechanical alloying or milling and consolidated by laser assisted sintering in Ar atmosphere. Microstructural characterization by scanning and transmission electron microscopy and phase analysis by X-ray diffraction suggest that the alloyed matrix undergoes significant grain growth after sintering while the dispersoids retain their ultrafine size and uniform distribution in the matrix. The dispersion of nano-Al₂O₃ is more effective than that of nano-ZrO₂ in enhancing the mechanical properties due to the smaller initial particle size of Al₂O₃ than that of ZrO₂. In general, laser sintering of mechanically alloyed Cu-4.5Cr and Cu-4.5Cr-3Ag alloys with 10 wt% nanocrystalline Al₂O₃ at 100 W laser power and 1-2 mm s⁻¹ scan speed yields the optimum combination of high density (7.1-7.5 mg m⁻³), hardness (165-225 VHN), wear resistance and electrical conductivity (13-20% IACS).     

Influence of surface scattering on the anomalous conductance plateaus in an asymmetrically biased InAs/In(0.52)Al(0.48)As quantum point contact

We study of the appearance and evolution of several anomalous (i.e., G < G(0) D 2e(2)/h) conductance plateaus in an In(0.52)Al(0.48)As/InAs quantum point contact (QPC). This work was performed at T = 4:2 K as a function of the offset bias ΔV(G) between the two in-plane gates of the QPC. The number and location of the anomalous conductance plateaus strongly depend on the polarity of the offset bias. The anomalous plateaus appear only over an intermediate range of offset bias of several volts. They are quite robust, being observed over a maximum range of nearly 1 V for the common sweep voltage applied to the two gates. These results are interpreted as evidence for the sensitivity of the QPC spin polarization to defects (surface roughness and impurity (dangling bond) scattering) generated during the etching process that forms the QPC side walls. This assertion is supported by non-equilibrium Green function simulations of the conductance of a single QPC in the presence of dangling bonds on its walls. Our simulations show that a spin conductance polarization as high as 98% can be achieved despite the presence of dangling bonds. The maximum in is not necessarily reached where the conductance of the channel is equal to 0:5G(0).     

Structural and photoluminescence studies of Eu3+ doped zinc oxide nanorods prepared by precipitation method

Trivalent europium doped zinc oxide (ZnO:Eu3+) nanocrystals were synthesized via room temperature chemical co-precipitation and they were systematically characterized by means of X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR) and photoluminescence (PL) spectroscopy. The as-synthesized samples were found to have hexagonal wurtzite coexisted with the intermediate Zn5(OH)8Cl2·H2O phase, while the single hexagonal phase was facilitated due to the calcinations. The as obtained samples were broadly composed of nanoflakes while the highly crystalline nanorods were formed due to low temperature annealing of the as-synthesized samples. The crystallite size of the nanoflakes and nanorods (40-90 nm) were extracted from the XRD pattern which was found to be consistent with scanning electron microscopy (SEM) measurements. The photolumi-nescence (PL) spectra of nanophosphors showed bright red and orange emissions at 618 and 594 nm respectively with efficient broad blue green emission spectrum due to ZnO lattice. Further, a good energy transfer process from ZnO host to Eu3+ was observed in PL emission and excitation spectra of Eu3+ doped ZnO ions. In all, the present nanophosphors were found to have great potentiality for bio-applications.