Topological and Algebraic Properties of Chernoff Information between Gaussian Graphs

In this paper, we want to find out the determining factors of Chernoff information in distinguishing a set of Gaussian graphs. We find that Chernoff information of two Gaussian graphs can be determined by the generalized eigenvalues of their covariance matrices. We find that the unit generalized eigenvalue doesn't affect Chernoff information and its corresponding dimension doesn't provide information for classification purpose. In addition, we can provide a partial ordering using Chernoff information between a series of Gaussian trees connected by independent grafting operations. With the relationship between generalized eigenvalues and Chernoff information, we can do optimal linear dimension reduction with least loss of information for classification.Comment: Submitted to Allerton2018, and this version contains proofs of the propositions in the pape

Enhancement of Secrecy of Block Ciphered Systems by Deliberate Noise

This paper considers the problem of end-end security enhancement by resorting to deliberate noise injected in ciphertexts. The main goal is to generate a degraded wiretap channel in application layer over which Wyner-type secrecy encoding is invoked to deliver additional secure information. More specifically, we study secrecy enhancement of DES block cipher working in cipher feedback model (CFB) when adjustable and intentional noise is introduced into encrypted data in application layer. A verification strategy in exhaustive search step of linear attack is designed to allow Eve to mount a successful attack in the noisy environment. Thus, a controllable wiretap channel is created over multiple frames by taking advantage of errors in Eve's cryptanalysis, whose secrecy capacity is found for the case of known channel states at receivers. As a result, additional secure information can be delivered by performing Wyner type secrecy encoding over super-frames ahead of encryption, namely, our proposed secrecy encoding-then-encryption scheme. These secrecy bits could be taken as symmetric keys for upcoming frames. Numerical results indicate that a sufficiently large secrecy rate can be achieved by selective noise addition.Comment: 11 pages, 8 figures, journa

Asymptotic Error Free Partitioning over Noisy Boolean Multiaccess Channels

In this paper, we consider the problem of partitioning active users in a manner that facilitates multi-access without collision. The setting is of a noisy, synchronous, Boolean, multi-access channel where $K$ active users (out of a total of $N$ users) seek to access. A solution to the partition problem places each of the $N$ users in one of $K$ groups (or blocks) such that no two active nodes are in the same block. We consider a simple, but non-trivial and illustrative case of $K=2$ active users and study the number of steps $T$ used to solve the partition problem. By random coding and a suboptimal decoding scheme, we show that for any $T\geq (C_1 +\xi_1)\log N$, where $C_1$ and $\xi_1$ are positive constants (independent of $N$), and $\xi_1$ can be arbitrary small, the partition problem can be solved with error probability $P_e^{(N)} \to 0$, for large $N$. Under the same scheme, we also bound $T$ from the other direction, establishing that, for any $T \leq (C_2 - \xi_2) \log N$, the error probability $P_e^{(N)} \to 1$ for large $N$; again $C_2$ and $\xi_2$ are constants and $\xi_2$ can be arbitrarily small. These bounds on the number of steps are lower than the tight achievable lower-bound in terms of $T \geq (C_g +\xi)\log N$ for group testing (in which all active users are identified, rather than just partitioned). Thus, partitioning may prove to be a more efficient approach for multi-access than group testing.Comment: This paper was submitted in June 2014 to IEEE Transactions on Information Theory, and is under review no

Partition Information and its Transmission over Boolean Multi-Access Channels

In this paper, we propose a novel partition reservation system to study the partition information and its transmission over a noise-free Boolean multi-access channel. The objective of transmission is not message restoration, but to partition active users into distinct groups so that they can, subsequently, transmit their messages without collision. We first calculate (by mutual information) the amount of information needed for the partitioning without channel effects, and then propose two different coding schemes to obtain achievable transmission rates over the channel. The first one is the brute force method, where the codebook design is based on centralized source coding; the second method uses random coding where the codebook is generated randomly and optimal Bayesian decoding is employed to reconstruct the partition. Both methods shed light on the internal structure of the partition problem. A novel hypergraph formulation is proposed for the random coding scheme, which intuitively describes the information in terms of a strong coloring of a hypergraph induced by a sequence of channel operations and interactions between active users. An extended Fibonacci structure is found for a simple, but non-trivial, case with two active users. A comparison between these methods and group testing is conducted to demonstrate the uniqueness of our problem.Comment: Submitted to IEEE Transactions on Information Theory, major revisio

Ultrafast Photoisomerization Dynamics of Photochromic Molecular Switches Affected by Their Environment and Ultrafast Energy Transfer

The main goal of this Thesis is the investigation of the excited-state dynamics of photochromic molecular switches following photoexcitation in different molecular environments by static and femtosecond time-resolved transient absorption spectroscopy in combination with quantum-chemical calculations. The time-resolved transient absorption spectroscopy on thin polymethylmethacrylate (PMMA) films doped with azobenzene (AB) derivatives called for an improved experimental setup and data collection strategy combined with a background subtraction scheme. The vibrational cooling in the electronic ground state of the ABs is slowed down moderately by a factor of 2 in the polymer film. We observed formation of the isomerisation photoproduct of the dianionic cis-ferulic acid. The ultrafast electronic energy transfer (EET) of a donor–acceptor dyad with a time constant of 3 ps was investigated

Privet: A Privacy-Preserving Vertical Federated Learning Service for Gradient Boosted Decision Tables

Vertical federated learning (VFL) has recently emerged as an appealing distributed paradigm empowering multi-party collaboration for training high-quality models over vertically partitioned datasets. Gradient boosting has been popularly adopted in VFL, which builds an ensemble of weak learners (typically decision trees) to achieve promising prediction performance. Recently there have been growing interests in using decision table as an intriguing alternative weak learner in gradient boosting, due to its simpler structure, good interpretability, and promising performance. In the literature, there have been works on privacy-preserving VFL for gradient boosted decision trees, but no prior work has been devoted to the emerging case of decision tables. Training and inference on decision tables are different from that the case of generic decision trees, not to mention gradient boosting with decision tables in VFL. In light of this, we design, implement, and evaluate Privet, the first system framework enabling privacy-preserving VFL service for gradient boosted decision tables. Privet delicately builds on lightweight cryptography and allows an arbitrary number of participants holding vertically partitioned datasets to securely train gradient boosted decision tables. Extensive experiments over several real-world datasets and synthetic datasets demonstrate that Privet achieves promising performance, with utility comparable to plaintext centralized learning.Comment: Accepted in IEEE Transactions on Services Computing (TSC

Risk Evaluation and Software Development of Urban Natural Gas Pipelines Based on Bayesian Networks

Based on the urban natural gas pipeline accident statistics and semi-quantitative risk evaluation index system, this paper applies Bayesian network to establish a network model between various types of risk factors and the risk of natural gas pipeline failure. The EM algorithm was used to learn from the statistical accident data to obtain the parameters of the model. Based on the principle of evidential reasoning in reverse, the probability of occurrence of all risk indicators can be obtained when the probability of occurrence of urban natural gas pipeline accidents is 100%, the index weight is obtained by normalizing the occurrence probability. On this basis, this paper develops an efficient urban natural gas pipeline integrity risk identification and management software. The software can realize the basic data management of urban natural gas pipeline system, pipeline relative risk value calculation, pipeline risk level calculation and other functions, and the results are visualized. Finally, the practicability and effectiveness of the model and software are verified by a case of natural gas pipeline evaluation in a block

MR Elastography-Based Assessment of Matrix Remodeling at Lesion Sites Associated With Clinical Severity in a Model of Multiple Sclerosis

Magnetic resonance imaging (MRI) with gadolinium based contrast agents (GBCA) is routinely used in the clinic to visualize lesions in multiple sclerosis (MS). Although GBCA reveal endothelial permeability, they fail to expose other aspects of lesion formation such as the magnitude of inflammation or tissue changes occurring at sites of blood-brain barrier (BBB) disruption. Moreover, evidence pointing to potential side effects of GBCA has been increasing. Thus, there is an urgent need to develop GBCA-independent imaging tools to monitor pathology in MS. Using MR-elastography (MRE), we previously demonstrated in both MS and the animal model experimental autoimmune encephalomyelitis (EAE) that inflammation was associated with a reduction of brain stiffness. Now, using the relapsing-remitting EAE model, we show that the cerebellum-a region with predominant inflammation in this model-is especially prone to loss of stiffness. We also demonstrate that, contrary to GBCA-MRI, reduction of brain stiffness correlates with clinical disability and is associated with enhanced expression of the extracellular matrix protein fibronectin (FN). Further, we show that FN is largely expressed by activated astrocytes at acute lesions, and reflects the magnitude of tissue remodeling at sites of BBB breakdown. Therefore, MRE could emerge as a safe tool suitable to monitor disease activity in MS

Hypoxia-inducible transcription factor-1α promotes hypoxia-induced A549 apoptosis via a mechanism that involves the glycolysis pathway

BACKGROUND: Hypoxia-inducible transcription factor-1α (HIF-1α), which plays an important role in controlling the hypoxia-induced glycolysis pathway, is a "master" gene in the tissue hypoxia response during tumor development. However, its role in the apoptosis of non-small cell lung cancer remains unknown. Here, we have studied the effects of HIF-1α on apoptosis by modulating HIF-1α gene expression in A549 cells through both siRNA knock-down and over-expression. METHODS: A549 cells were transfected with a HIF-1α siRNA plasmid or a HIF-1α expression vector. Transfected cells were exposed to a normoxic or hypoxic environment in the presence or absence of 25 mM HEPES and 2-deoxyglucose (2-DG) (5 mM). The expression of three key genes of the glycolysis pathway, glucose transporter type 1(GLUT1), phosphoglycerate kinase 1(PGK1), and hexokinase 1(HK1), were measured using real-time RT-PCR. Glycolysis was monitored by measuring changes of pH and lactate concentration in the culture medium. Apoptosis was detected by TUNEL assay and flow cytometry. RESULTS: Knocking down expression of HIF-1α inhibited the glycolysis pathway, increased the pH of the culture medium, and protected the cells from hypoxia-induced apoptosis. In contrast, over-expression of HIF-1α accelerated glycolysis in A549 cells, decreased the pH of the culture medium, and enhanced hypoxia-induced apoptosis. These effects of HIF-1α on glycolysis, pH of the medium, and apoptosis were reversed by treatment with the glycolytic inhibitor, 2-DG. Apoptosis induced by HIF-1α over-expression was partially inhibited by increasing the buffering capacity of the culture medium by adding HEPES. CONCLUSION: During hypoxia in A549 cells, HIF-1α promotes activity of the glycolysis pathway and decreases the pH of the culture medium, resulting in increased cellular apoptosis