Ancilla-assisted sequential approximation of nonlocal unitary operations

We consider the recently proposed "no-go" theorem of Lamata et al [Phys. Rev. Lett. 101, 180506 (2008)] on the impossibility of sequential implementation of global unitary operations with the aid of an itinerant ancillary system and view the claim within the language of Kraus representation. By virtue of an extremely useful tool for analyzing entanglement properties of quantum operations, namely, operator-Schmidt decomposition, we provide alternative proof to the "no-go" theorem and also study the role of initial correlations between the qubits and ancilla in sequential preparation of unitary entanglers. Despite the negative response from the "no-go" theorem, we demonstrate explicitly how the matrix-product operator(MPO) formalism provides a flexible structure to develop protocols for sequential implementation of such entanglers with an optimal fidelity. The proposed numerical technique, that we call variational matrix-product operator (VMPO), offers a computationally efficient tool for characterizing the "globalness" and entangling capabilities of nonlocal unitary operations.Comment: Slightly improved version as published in Phys. Rev.

A Study of the Effect of Zone Design Parameters on Frequency Domain Transfer Functions for Radiant and Convective Systems

This paper presents a parametric study on the effect of a number of room design parameters for radiant and convective heating sources as well as solar gains. This study is performed using frequency domain modeling approach by means of which important room transfer functions are obtained and studied. Frequency domain modeling is a useful tool for analyzing building thermal dynamics as well as different design options. The phenomena affecting energy consumption inside a building such as solar gains, exterior temperature and heating/cooling sources are usually cyclic phenomena and can be modeled by means of frequency domain techniques assuming periodic conditions in the calculations. Using frequency domain techniques, the transient heat conduction inside the walls can be accurately modeled with no discretization for the thermal mass. However, there is difficulty modeling time-varying variables in the frequency domain. This is especially important in the case of convective and radiative heat transfer coefficients which are inherently non-linear elements. The coefficients are usually linearized in order to have a linear system of equation that can be presented by means of a linear thermal network[1]. In frequency domain modeling approach usually a constant value for the convective and radiative heat transfer coefficients is assumed. However, this assumption can produce significant errors when there are large differences between surfaces temperatures for example in the case of floor heating or direct gain rooms with large windows[2]. In this case, a sensitivity analysis on the magnitude of the important room transfer functions considering different values for convective and radiative heat transfer coefficients needs to be done. A room is considered with different types of heating (convective and radiative heating sources) and different levels of thermal mass on the floor. The effect of thermal mass and floor covering on the room thermal response considering different types of heating is investigated. Magnitude of the transfer functions between room air temperature and the convective heating source is a determining element in the room air temperature fluctuations considering thermal comfort aspects. Also, in the case of radiant heating, the transfer function between room air temperature and radiant heat source can be used to determine the room air temperature swings due to the floor radiant heating source. The sensitivity of the magnitude of the transfer functions versus different values of convective and radiative heat transfer coefficients is studied and compared. This study will guide future model predictive control (MPC) research by means of frequency domain techniques to make choices such as optimal thermal mass thickness for floor heating versus convective systems. It will contribute to linking design with MPC. [1] Athienitis, A.K. and O\u27Brien, W., Eds. (2015). Modelling, design and optimization of net-zero energy buildings, Solar heating and cooling, Berlin: Ernst, Wilhelm & Sohn 2015. [2] Saberi Derakhtenjani, Ali, Candanedo, Jos A., Chen, Yuxiang, Dehkordi, Vahid R., Athienitis, Andreas K. (2015), Modeling approaches for the characterization of building thermal dynamics and model-based control: a case study. ASHRAE STBE (Science and Technology for the Built Environment) Journal (21): 824-836

Inferring gene regulatory networks from gene expression data by a dynamic Bayesian network-based model

Enabled by recent advances in bioinformatics, the inference of gene regulatory networks (GRNs) from gene expression data has garnered much interest from researchers. This is due to the need of researchers to understand the dynamic behavior and uncover the vast information lay hidden within the networks. In this regard, dynamic Bayesian network (DBN) is extensively used to infer GRNs due to its ability to handle time-series microarray data and modeling feedback loops. However, the efficiency of DBN in inferring GRNs is often hampered by missing values in expression data, and excessive computation time due to the large search space whereby DBN treats all genes as potential regulators for a target gene. In this paper, we proposed a DBN-based model with missing values imputation to improve inference efficiency, and potential regulators detection which aims to lessen computation time by limiting potential regulators based on expression changes. The performance of the proposed model is assessed by using time-series expression data of yeast cell cycle. The experimental results showed reduced computation time and improved efficiency in detecting gene-gene relationships

Inferring gene regulatory networks from gene expression data by a dynamic Bayesian network-based model

Enabled by recent advances in bioinformatics, the inference of gene regulatory networks (GRNs) from gene expression data has garnered much interest from researchers. This is due to the need of researchers to understand the dynamic behavior and uncover the vast information lay hidden within the networks. In this regard, dynamic Bayesian network (DBN) is extensively used to infer GRNs due to its ability to handle time-series microarray data and modeling feedback loops. However, the efficiency of DBN in inferring GRNs is often hampered by missing values in expression data, and excessive computation time due to the large search space whereby DBN treats all genes as potential regulators for a target gene. In this paper, we proposed a DBN-based model with missing values imputation to improve inference efficiency, and potential regulators detection which aims to lessen computation time by limiting potential regulators based on expression changes. The performance of the proposed model is assessed by using time-series expression data of yeast cell cycle. The experimental results showed reduced computation time and improved efficiency in detecting gene-gene relationships

Improving Rheological And Thermal Performance Of Gilsonite-Modified Binder With Phase Change Materials

Gilsonite, as a type of natural asphalt binder, has been used to improve the high-temperature performance of regular asphalt binders. However, the addition of Gilsonite may compromise binders\u27 low-temperature thermal cracking resistance. In this research, polyethylene glycol (PEG), as one type of the phase change materials (PCMs), was used as an innovative material to balance the impacts of Gilsonite on high and low performance of asphalt binders. The dosages of Gilsonite and PEG were first determined based on the materials\u27 rheological behaviors at low temperatures. The performance of the PEG-Gilsonite-modified binder was then fully evaluated in terms of the resistance to cracking and rutting at various temperatures. Thermal tests were also conducted to assess the thermal behaviors of the modified binders. The testing results indicate that with the proper dosage of Gilsonite and PEG, the rutting resistance of the binder can be improved without sacrificing its low-temperature performance. With the addition of the PCM, the binder was tested to have high volumetric heat capacity, which indicates PCM can reduce the rate and the magnitude of the temperature changes in pavements

Urban Network Gridlock: Theory, Characteristics, and Dynamics

AbstractThis study explores the limiting properties of network-wide traffic flow relations under heavily congested conditions in a large-scale complex urban street network; these limiting conditions are emulated in the context of dynamic traffic assignment (DTA) experiments on an actual large network. The primary objectives are to characterize gridlock and understand its dynamics. This study addresses a gap in the literature with regard to the existence of exit flow and recovery period. The one- dimensional theoretical Network Fundamental Diagram (NFD) only represents steady-state behavior and holds only when the inputs change slowly in time and traffic is distributed homogenously in space. Also, it does not describe the hysteretic behavior of the network traffic when a gridlock forms or when network recovers. Thus, a model is proposed to reproduce hysteresis and gridlock when homogeneity and steady-state conditions do not hold. It is conjectured that the network average flow can be approximated as a non-linear function of network average density and variation in link densities. The proposed model is calibrated for the Chicago Central Business District (CBD) network. We also show that complex urban networks with multiple route choices, similar to the idealized network tested previously in the literature, tend to jam at a range of densities that are smaller than the theoretical average network jam density. Also it is demonstrated that networks tend to gridlock in many different ways with different configurations. This study examines how mobility of urban street networks could be improved by managing vehicle accumulation and re-distributing network traffic via strategies such as demand management and disseminating real-time traveler information (adaptive driving). This study thus defines and explores some key characteristics and dynamics of urban street network gridlocks including gridlock formation, propagation, recovery, size, etc

Deep Metric Learning with Soft Orthogonal Proxies

Deep Metric Learning (DML) models rely on strong representations and similarity-based measures with specific loss functions. Proxy-based losses have shown great performance compared to pair-based losses in terms of convergence speed. However, proxies that are assigned to different classes may end up being closely located in the embedding space and hence having a hard time to distinguish between positive and negative items. Alternatively, they may become highly correlated and hence provide redundant information with the model. To address these issues, we propose a novel approach that introduces Soft Orthogonality (SO) constraint on proxies. The constraint ensures the proxies to be as orthogonal as possible and hence control their positions in the embedding space. Our approach leverages Data-Efficient Image Transformer (DeiT) as an encoder to extract contextual features from images along with a DML objective. The objective is made of the Proxy Anchor loss along with the SO regularization. We evaluate our method on four public benchmarks for category-level image retrieval and demonstrate its effectiveness with comprehensive experimental results and ablation studies. Our evaluations demonstrate the superiority of our proposed approach over state-of-the-art methods by a significant margin

On designing observers for time-delay systems with nonlinear disturbances

This is the post print version of the article. The official published version can be obtained from the link below - Copyright 2002 Taylor & Francis LtdIn this paper, the observer design problem is studied for a class of time-delay nonlinear systems. The system under consideration is subject to delayed state and non-linear disturbances. The time-delay is allowed to be time-varying, and the non-linearities are assumed to satisfy global Lipschitz conditions. The problem addressed is the design of state observers such that, for the admissible time-delay as well as non-linear disturbances, the dynamics of the observation error is globally exponentially stable. An effective algebraic matrix inequality approach is developed to solve the non-linear observer design problem. Specifically, some conditions for the existence of the desired observers are derived, and an explicit expression of desired observers is given in terms of some free parameters. A simulation example is included to illustrate the practical applicability of the proposed theory.The work of Z. Wang was supported in part by the University of Kaiserslautern of Germany and the Alexander von Humboldt Foundation of Germany

Antiretroviral therapy experience, satisfaction, and preferences among a diverse sample of young adults living with HIV

Youth and young adults living with HIV (YLWH) have a high HIV infection rate and suboptimal oral medication adherence. Biomedical researchers hope that long-acting antiretroviral therapy (LAART) modalities can help those who struggle with daily oral adherence. While adults living with HIV have expressed interest in LAART, little research has explored perspectives of YLWH. This study explores ART experiences and perspectives on LAART through qualitative interviews with twenty diverse YLWH (18–29) in the United States. Data were analyzed using framework analysis. Most participants were satisfied with their current ART yet had experienced side effects or had struggled with daily adherence. Preferences for improving daily oral ART included making pills smaller and reformulating ART into flavored chewable gummies. Most expressed enthusiasm for LAART, although needle aversion and previous injection drug use were potential barriers for some. Approximately half were interested in an ART patch, though its visibility and fear of stigmatization was concerning. Few expressed interest in implantable ART, calling it unappealing. Although younger people are most likely to benefit from these advancements in HIV treatment, additional research is needed to identify gaps in uptake and to further explore perspectives of YLWH to improve the success of new treatment modalities