Web Services for forward integration in international tourism supply chains: A case study of tourism in Thailand

International tourism is a highly competitive and information-intensive industry. Customers need volumes of information for decision aids. Moreover, the decision-making processes are quite sensitive to the variables of personal preferences, the tourist industrial ecosystem, the legal regulations and political environments of destinations, the regional or global economic situations, the natural matters, and so on. Hence, the owners of tourism are motivated to upgrade the competitiveness of their businesses with information technologies. This paper intends to design the architecture of Web Services in international tourism, which can contribute to the forward integration in international tourism supply chains. First, the authors conduct an in-depth case study of a regional tour operator in Thailand. In the case study, we examine the strength, weakness, challenges visions, and strategic approaches of international tourism, and their relationships with the information systems in the tourist business. Then, this paper designs the architecture of Web Services in international tourism. The architecture is expected to improve the information transparency through the global tourism supply chain, construct business-to-business collaboration mechanism, provide efficient and effective information to tourists, and consequently contribute to forward integration in international tourism supply chains

Coordinated Multicasting with Opportunistic User Selection in Multicell Wireless Systems

Physical layer multicasting with opportunistic user selection (OUS) is examined for multicell multi-antenna wireless systems. By adopting a two-layer encoding scheme, a rate-adaptive channel code is applied in each fading block to enable successful decoding by a chosen subset of users (which varies over different blocks) and an application layer erasure code is employed across multiple blocks to ensure that every user is able to recover the message after decoding successfully in a sufficient number of blocks. The transmit signal and code-rate in each block determine opportunistically the subset of users that are able to successfully decode and can be chosen to maximize the long-term multicast efficiency. The employment of OUS not only helps avoid rate-limitations caused by the user with the worst channel, but also helps coordinate interference among different cells and multicast groups. In this work, efficient algorithms are proposed for the design of the transmit covariance matrices, the physical layer code-rates, and the target user subsets in each block. In the single group scenario, the system parameters are determined by maximizing the group-rate, defined as the physical layer code-rate times the fraction of users that can successfully decode in each block. In the multi-group scenario, the system parameters are determined by considering a group-rate balancing optimization problem, which is solved by a successive convex approximation (SCA) approach. To further reduce the feedback overhead, we also consider the case where only part of the users feed back their channel vectors in each block and propose a design based on the balancing of the expected group-rates. In addition to SCA, a sample average approximation technique is also introduced to handle the probabilistic terms arising in this problem. The effectiveness of the proposed schemes is demonstrated by computer simulations.Comment: Accepted by IEEE Transactions on Signal Processin

Profit Maximization by Forming Federations of Geo-Distributed MEC Platforms

This paper has been presented at: Seventh International Workshop on Cloud Technologies and Energy Efficiency in Mobile Communication Networks (CLEEN 2019). How cloudy and green will mobile network and services be? 15 April 2019 - Marrakech, MoroccoIn press / En prensaMulti-access edge computing (MEC) as an emerging technology which provides cloud service in the edge of multi-radio access networks aims to reduce the service latency experienced by end devices. When individual MEC systems do not have adequate resource capacity to fulfill service requests, forming MEC federations for resource sharing could provide economic incentive to MEC operators. To this end, we need to maximize social welfare in each federation, which involves efficient federation structure generations, federation profit maximization by resource provisioning configuration, and fair profit distribution among participants. We model the problem as a coalition game with difference from prior work in the assumption of latency and locality constraints and also in the consideration of various service policies/demand preferences. Simulation results show that the proposed approach always increases profits. If local requests are served with local resource with priority, federation improves profits without sacrificing request acceptance rates.This work was partially supported by the Ministry of Science and Technology, Taiwan, under grant numbers 106-2221-E-009-004 and by the H2020 collaborative Europe/Taiwan research project 5G-CORAL (grant number 761586)

Determining the physical conditions of extremely young Class 0 circumbinary disk around VLA1623A

We present detailed analysis of high-resolution C18O (2-1), SO (88-77), CO (3-2) and DCO+ (3-2) data obtained by the Atacama Large Millimeter/sub-millimeter Array (ALMA) towards a Class 0 Keplerian circumbinary disk around VLA1623A, which represents one of the most complete analysis towards a Class 0 source. From the dendrogram analysis, we identified several accretion flows feeding the circumbinary disk in a highly anisotropic manner. Stream-like SO emission around the circumbinary disk reveals the complicated shocks caused by the interactions between the disk, accretion flows and outflows. A wall-like structure is discovered south of VLA1623B. The discovery of two outflow cavity walls at the same position traveling at different velocities suggests the two outflows from both VLA1623A and VLA1623B overlays on top of each other in the plane of sky. Our detailed flat and flared disk modeling shows that Cycle 2 C18O J = 2-1 data is inconsistent with the combined binary mass of 0.2 Msun as suggested by early Cycle 0 studies. The combined binary mass for VLA1623A should be modified to 0.3 ~ 0.5 Msun.Comment: 26 pages, 20 figures, accepted by ApJ 2020.2.2

Quantum-Inspired Sublinear Algorithm for Solving Low-Rank Semidefinite Programming

Semidefinite programming (SDP) is a central topic in mathematical optimization with extensive studies on its efficient solvers. In this paper, we present a proof-of-principle sublinear-time algorithm for solving SDPs with low-rank constraints; specifically, given an SDP with $m$ constraint matrices, each of dimension $n$ and rank $r$, our algorithm can compute any entry and efficient descriptions of the spectral decomposition of the solution matrix. The algorithm runs in time $O(m\cdot\mathrm{poly}(\log n,r,1/\varepsilon))$ given access to a sampling-based low-overhead data structure for the constraint matrices, where $\varepsilon$ is the precision of the solution. In addition, we apply our algorithm to a quantum state learning task as an application. Technically, our approach aligns with 1) SDP solvers based on the matrix multiplicative weight (MMW) framework by Arora and Kale [TOC '12]; 2) sampling-based dequantizing framework pioneered by Tang [STOC '19]. In order to compute the matrix exponential required in the MMW framework, we introduce two new techniques that may be of independent interest: $\bullet$ Weighted sampling: assuming sampling access to each individual constraint matrix $A_{1},\ldots,A_{\tau}$, we propose a procedure that gives a good approximation of $A=A_{1}+\cdots+A_{\tau}$. $\bullet$ Symmetric approximation: we propose a sampling procedure that gives the \emph{spectral decomposition} of a low-rank Hermitian matrix $A$. To the best of our knowledge, this is the first sampling-based algorithm for spectral decomposition, as previous works only give singular values and vectors.Comment: 37 pages, 1 figure. To appear in the Proceedings of the 45th International Symposium on Mathematical Foundations of Computer Science (MFCS 2020

Sampling-based sublinear low-rank matrix arithmetic framework for dequantizing quantum machine learning

We present an algorithmic framework for quantum-inspired classical algorithms on close-to-low-rank matrices, generalizing the series of results started by Tang’s breakthrough quantum-inspired algorithm for recommendation systems [STOC’19]. Motivated by quantum linear algebra algorithms and the quantum singular value transformation (SVT) framework of Gilyén et al. [STOC’19], we develop classical algorithms for SVT that run in time independent of input dimension, under suitable quantum-inspired sampling assumptions. Our results give compelling evidence that in the corresponding QRAM data structure input model, quantum SVT does not yield exponential quantum speedups. Since the quantum SVT framework generalizes essentially all known techniques for quantum linear algebra, our results, combined with sampling lemmas from previous work, suffices to generalize all recent results about dequantizing quantum machine learning algorithms. In particular, our classical SVT framework recovers and often improves the dequantization results on recommendation systems, principal component analysis, supervised clustering, support vector machines, low-rank regression, and semidefinite program solving. We also give additional dequantization results on low-rank Hamiltonian simulation and discriminant analysis. Our improvements come from identifying the key feature of the quantum-inspired input model that is at the core of all prior quantum-inspired results: ℓ²-norm sampling can approximate matrix products in time independent of their dimension. We reduce all our main results to this fact, making our exposition concise, self-contained, and intuitive

Deranged Bioenergetics and Defective Redox Capacity in T Lymphocytes and Neutrophils Are Related to Cellular Dysfunction and Increased Oxidative Stress in Patients with Active Systemic Lupus Erythematosus

Urinary excretion of N-benzoyl-glycyl-Nε-(hexanonyl)lysine, a biomarker of oxidative stress, was higher in 26 patients with active systemic lupus erythematosus (SLE) than in 11 non-SLE patients with connective tissue diseases and in 14 healthy volunteers. We hypothesized that increased oxidative stress in active SLE might be attributable to deranged bioenergetics, defective reduction-oxidation (redox) capacity, or other factors. We demonstrated that, compared to normal cells, T lymphocytes (T) and polymorphonuclear neutrophils (PMN) of active SLE showed defective expression of facilitative glucose transporters GLUT-3 and GLUT-6, which led to increased intracellular basal lactate and decreased ATP production. In addition, the redox capacity, including intracellular GSH levels and the enzyme activity of glutathione peroxidase (GSH-Px) and γ-glutamyl-transpeptidase (GGT), was decreased in SLE-T. Compared to normal cells, SLE-PMN showed decreased intracellular GSH levels, and GGT enzyme activity was found in SLE-PMN and enhanced expression of CD53, a coprecipitating molecule for GGT. We conclude that deranged cellular bioenergetics and defective redox capacity in T and PMN are responsible for cellular immune dysfunction and are related to increased oxidative stress in active SLE patients

Mass-accretion, spectral, and photometric properties of T Tauri stars in Taurus based on TESS and LAMOST

We present the analysis of 16 classical T Taur stars using LAMOST and TESS data, investigating spectral properties, photometric variations, and mass-accretion rates. All 16 stars exhibit emissions in H$\alpha$ lines, from which the average mass-accretion rate of $1.76\times10^{-9}~M_{\odot}yr^{-1}$ is derived. Two of the stars, DL Tau and Haro 6-13, show mass-accretion bursts simultaneously in TESS, ASAS-SN, and/or ZTF survey. Based on these observations, we find that the mass-accretion rates of DL Tau and Haro 6-13 reach their maximums of $2.5 \times 10^{-8}~M_{\odot}yr^{-1}$ and $2 \times 10^{-10}~M_{\odot}yr^{-1}$ during the TESS observation, respectively. We detect thirteen flares among these stars. The flare frequency distribution shows that the CTTSs' flare activity is not only dominated by strong flares with high energy but much more active than those of solar-type and young low-mass stars. By comparing the variability classes reported in the literature, we find that the transition timescale between different classes of variability in CTTSs, such as from Stochastic (S) to Bursting (B) or from quasi-periodic symmetric (QPS) to quasi-periodic dipping (QPD), may range from 1.6 to 4 years. We observe no significant correlation between inclination and mass-accretion rates derived from the emission indicators. This suggests that inner disk properties may be more important than that of outer disk. Finally, we find a relatively significant positive correlation between the asymmetric metric "M" and the cold disk inclination compared to the literature. A weak negative correlation between the periodicity metric "Q" value and inclination has been also found.Comment: 39 pages, 22 figures, 8 table

Urinary Neutrophil Gelatinase-Associated Lipocalin Is a Potential Biomarker for Renal Damage in Patients with Systemic Lupus Erythematosus

Neutrophil gelatinase-associated lipocalin (NGAL) has been demonstrated to be a novel biomarker in acute and chronic kidney disease. We hypothesized that 24-hour urinary NGAL excretion may be a predictor for renal damage in patients with systemic lupus erythematosus (SLE). Thirty-four SLE patients with renal involvement (SLE-renal group), 8 SLE patients without renal involvement (SLE-nonrenal group), 14 patients with non-SLE autoimmune diseases (disease control or DC group), and 12 healthy volunteers (normal control or NC group) were compared for 24-hour urinary excretion of NGAL and different cytokines. We found that the 24-hour urinary NGAL excretion in the SLE-renal group was higher than that in the SLE-non-renal, DC, and NC groups. However, the excretion of interleukin-10, transforming growth factor-β1, and tumor necrosis factor-α was not different between the SLE-renal and SLE-non-renal groups. Furthermore, NGAL excretion in the SLE-renal group was correlated with serum creatinine levels and creatinine clearance, but not with the SLE Disease Activity Index score. Multivariate logistic regression analysis and receiver operating characteristic curve analysis revealed that 24-hour urinary NGAL excretion is a potential biomarker for renal damage in SLE patients, with higher sensitivity and specificity than anti-dsDNA antibody titers