Dynamic routing on stochastic time-dependent networks using real-time information

In just-in-time (JIT) manufacturing environments, on-time delivery is one of the key performance measures for dispatching and routing of freight vehicles. Both the travel time delay and its variability impact the efficiency of JIT logistics operations, that are becoming more and more common in many industries, and in particular, the automotive industry. In this dissertation, we first propose a framework for dynamic routing of a single vehicle on a stochastic time dependent transportation network using real-time information from Intelligent Transportation Systems (ITS). Then, we consider milk-run deliveries with several pickup and delivery destinations subject to time windows under same network settings. Finally, we extend our dynamic routing models to account for arc traffic condition dependencies on the network. Recurrent and non-recurrent congestion are the two primary reasons for travel time delay and variability, and their impact on urban transportation networks is growing in recent decades. Hence, our routing methods explicitly account for both recurrent and non-recurrent congestion in the network. In our modeling framework, we develop alternative delay models for both congestion types based on historical data (e.g., velocity, volume, and parameters for incident events) and then integrate these models with the forward-looking routing models. The dynamic nature of our routing decisions exploits the real-time information available from various ITS sources, such as loop sensors. The forward-looking traffic dynamic models for individual arcs are based on congestion states and state transitions driven by time-dependent Markov chains. We propose effective methods for estimation of the parameters of these Markov chains. Based on vehicle location, time of day, and current and projected network congestion states, we generate dynamic routing policies using stochastic dynamic programming formulations. All algorithms are tested in simulated networks of Southeast-Michigan and Los Angeles, CA freeways and highways using historical traffic data from the Michigan ITS Center, Traffic.com, and Caltrans PEMS

MASH Suite Pro: A Comprehensive Software Tool for Top-Down Proteomics

Top-down mass spectrometry (MS)-based proteomics is arguably a disruptive technology for the comprehensive analysis of all proteoforms arising from genetic variation, alternative splicing, and posttranslational modifications (PTMs). However, the complexity of top-down high-resolution mass spectra presents a significant challenge for data analysis. In contrast to the well-developed software packages available for data analysis in bottom-up proteomics, the data analysis tools in top-down proteomics remain underdeveloped. Moreover, despite recent efforts to develop algorithms and tools for the deconvolution of top-down high-resolution mass spectra and the identification of proteins from complex mixtures, a multifunctional software platform, which allows for the identification, quantitation, and characterization of proteoforms with visual validation, is still lacking. Herein, we have developed MASH Suite Pro, a comprehensive software tool for top-down proteomics with multifaceted functionality. MASH Suite Pro is capable of processing high-resolution MS and tandem MS (MS/MS) data using two deconvolution algorithms to optimize protein identification results. In addition, MASH Suite Pro allows for the characterization of PTMs and sequence variations, as well as the relative quantitation of multiple proteoforms in different experimental conditions. The program also provides visualization components for validation and correction of the computational outputs. Furthermore, MASH Suite Pro facilitates data reporting and presentation via direct output of the graphics. Thus, MASH Suite Pro significantly simplifies and speeds up the interpretation of high-resolution top-down proteomics data by integrating tools for protein identification, quantitation, characterization, and visual validation into a customizable and user-friendly interface. We envision that MASH Suite Pro will play an integral role in advancing the burgeoning field of top-down proteomics

Heart field origin of great vessel precursors relies on nkx2.5-mediated vasculogenesis

The pharyngeal arch arteries (PAAs) are transient embryonic blood vessels that make indispensable contributions to the carotid arteries and great vessels of the heart, including the aorta and pulmonary artery1, 2. During embryogenesis, the PAAs appear in a craniocaudal sequence to connect pre-existing segments of the primitive circulation after de novo vasculogenic assembly from angioblast precursors3, 4. Despite the unique spatiotemporal characteristics of PAA development, the embryonic origins of PAA angioblasts and the genetic factors regulating their emergence remain unknown. Here, we identify the embryonic source of PAA endothelium as nkx2.5+ progenitors in lateral plate mesoderm long considered to adopt cell fates within the heart exclusively5, 6. Further, we report that PAA endothelial differentiation relies on Nkx2.5, a canonical cardiac transcription factor not previously implicated in blood vessel formation. Together, these studies reveal the heart field origin of PAA endothelium and attribute a novel vasculogenic function to the cardiac transcription factor nkx2.5 during great vessel precursor development

One-Dimensional “Ghost Imaging” in Electron Microscopy of Inelastically Scattered Electrons

Entanglement and correlation are at the basis of quantum mechanics and have been used in optics to create a framework for “ghost imaging”. We propose that a similar scheme can be used in an electron microscope to exploit the correlation of electrons with the coincident detection of collective mode excitations in a sample. In this way, an image of the sample can be formed on an electron camera even if electrons never illuminated the region of interest directly. This concept, which can be regarded as the inverse of photon-induced near-field electron microscopy, can be used to probe delicate molecules with a resolution that is beyond the wavelength of the collective mode

Performance of a plastic scintillator developed using styrene monomer polymerization

This paper presents a newly developed plastic scintillator produced in collaboration with Turkiye Energy, Nuclear and Mineral Research Agency (TENMAK). The scintillator is manufactured using thermal polymerization of commercially available styrene monomer. The absorption spectrum of the scintillator exhibited two absorption bands at 225 nm and 340 nm, with an absorption edge observed at 410 nm. The wavelength of the emitted light was measured in the range of 400-800 nm, with a maximum intensity at 427 nm. Monoenergetic electrons from the 137Cs source were used to evaluate the characteristics of the new scintillator, particularly its light yield. As the light readout the MAPD-3NM type silicon photomultiplier array (4 x 4) with an active area of 15 x 15 mm2, assembled using single MAPDs with an active area of 3.7 x 3.7 mm2, was used. The light yield of the scintillator was determined to be 6134 photons/MeV. In addition, the efficiency of the scintillator for gamma rays with an energy of 662 keV was found to be approximately 1.8 %. A CmBe neutron source was employed to evaluate its fast neutron detection performance. However, neutron/gamma discrimination using pulse shape discrimination (charge integration) method was not observed. The results demonstrate the potential of a newly produced plastic scintillator for various applications, particularly in radiation monitoring and detection systems.Comment: 7 pages, 7 figure

T-Cell Infiltration and Adaptive Treg Resistance in Response to Androgen Deprivation With or Without Vaccination in Localized Prostate Cancer

Purpose: Previous studies suggest that androgen deprivation therapy (ADT) promotes antitumor immunity in prostate cancer. Whether a vaccine-based approach can augment this effect remains unknown. Experimental Design: Therefore, we conducted a neoadjuvant, randomized study to quantify the immunologic effects of a granulocyte-macrophage colony-stimulating factor (GM-CSF)-secreting allogeneic cellular vaccine in combination with low-dose cyclophosphamide (Cy/GVAX) followed by degarelix versus degarelix alone in patients with high-risk localized prostate adenocarcinoma who were planned for radical prostatectomy. Results: Both Cy/GVAX plus degarelix and degarelix alone led to significant increases in intratumoral CD8+ T cell infiltration and PD-L1 expression as compared to a cohort of untreated, matched controls. However, the CD8+ T cell infiltrate was accompanied by a proportional increase in regulatory T cells (Treg), suggesting that adaptive Treg resistance may dampen the immunogenicity of ADT. Although Cy/GVAX followed by degarelix was associated with a modest improvement in time-to-PSA progression and time-to-next treatment as well as an increase in PD-L1, there was no difference in the CD8 T-cell infiltrate as compared to degarelix alone. Gene expression profiling demonstrated that CHIT1, a macrophage marker, was differentially upregulated with Cy/GVAX plus degarelix compared to degarelix alone. Conclusions: Our results highlight that ADT with or without Cy/GVAX induces a complex immune response within the prostate tumor microenvironment. These data have important implications for combining ADT with immunotherapy. In particular, our finding that ADT increases both CD8+ T cells and Tregs, supports the development of regimens combining ADT with Treg-depleting agents in the treatment of prostate cancer

Prediction of Optimal Folding Routes of Proteins That Satisfy the Principle of Lowest Entropy Loss: Dynamic Contact Maps and Optimal Control

An optimization model is introduced in which proteins try to evade high energy regions of the folding landscape, and prefer low entropy loss routes during folding. We make use of the framework of optimal control whose convenient solution provides practical and useful insight into the sequence of events during folding. We assume that the native state is available. As the protein folds, it makes different set of contacts at different folding steps. The dynamic contact map is constructed from these contacts. The topology of the dynamic contact map changes during the course of folding and this information is utilized in the dynamic optimization model. The solution is obtained using the optimal control theory. We show that the optimal solution can be cast into the form of a Gaussian Network that governs the optimal folding dynamics. Simulation results on three examples (CI2, Sso7d and Villin) show that folding starts by the formation of local clusters. Non-local clusters generally require the formation of several local clusters. Non-local clusters form cooperatively and not sequentially. We also observe that the optimal controller prefers “zipping” or small loop closure steps during folding. The folding routes predicted by the proposed method bear strong resemblance to the results in the literature

Comprehensive glycosylation profiling of IgG and IgG-fusion proteins by top-down MS with multiple fragmentation techniques

We employed top- and middle-down analyses with multiple fragmentation techniques including electron transfer dissociation (ETD), electron capture dissociation (ECD), and matrix-assisted laser desorption ionization in-source decay (MALDI-ISD) for characterization of a reference monoclonal antibody (mAb) IgG1 and a fusion IgG protein. Fourier transform ion cyclotron resonance (FT-ICR) or high performance liquid chromatography electrospray ionization (HPLC-ESI) on an Orbitrap was employed. These experiments provided a comprehensive view on the protein species; especially for different glycosylation level in these two proteins, which showed good agreement with oligosaccharide profiling. Top- and middle-down MS provided additional information regarding glycosylation sites and different combinational protein species that were not available from oligosaccharide mapping or conventional bottom-up analysis. Finally, incorporating a limited enzymatic digestion by immunoglobulin G-degrading enzyme of Streptococcus pyogene (IdeS) with MALDI-ISD analysis enabled extended sequence coverage of the internal region of protein without pre-fractionation. Biological significance: Oligosaccharide profiling together with top- and middle-down methods enabled: 1) detection of heterogeneous glycosylated protein species and sites in intact IgG1 and fusion proteins with high mass accuracy, 2) estimation of relative abundance levels of protein species in the sample, 3) confirmation of the protein termini structural information, and 4) improved sequence coverage by MALDI-ISD analysis for the internal regions of the proteins without sample pre-fractionation