The infrared spectra of ABC-stacking tri- and tetra-layer graphenes studied by first-principles calculations

The infrared absorption spectra of ABC-stacking tri- and tetra-layer graphenes are studied using the density functional theory. It is found that they exhibit very different characteristic peaks compared with those of AB-stacking ones, caused by the different stacking sequence and interlayer coupling. The anisotropy of the spectra with respect to the direction of the light electric field is significant. The spectra are more sensitive to the stacking number when the electric field is perpendicular to the graphene plane due to the interlayer polarization. The high sensitivities make it possible to identify the stacking sequence and stacking number of samples by comparing theory and experiment.Comment: 7 pages, 5 figure

Highly tunable spin-dependent electron transport through carbon atomic chains connecting two zigzag graphene nanoribbons

Motivated by recent experiments of successfully carving out stable carbon atomic chains from graphene, we investigate a device structure of a carbon chain connecting two zigzag graphene nanoribbons with highly tunable spin-dependent transport properties. Our calculation based on the non-equilibrium Green's function approach combined with the density functional theory shows that the transport behavior is sensitive to the spin configuration of the leads and the bridge position in the gap. A bridge in the middle gives an overall good coupling except for around the Fermi energy where the leads with anti-parallel spins create a small transport gap while the leads with parallel spins give a finite density of states and induce an even-odd oscillation in conductance in terms of the number of atoms in the carbon chain. On the other hand, a bridge at the edge shows a transport behavior associated with the spin-polarized edge states, presenting sharp pure $\alpha$-spin and $\beta$-spin peaks beside the Fermi energy in the transmission function. This makes it possible to realize on-chip interconnects or spintronic devices by tuning the spin state of the leads and the bridge position.Comment: 7 pages, 9 figure

Learning ranking functions for efficient search

This dissertation explores algorithms for learning ranking functions to efficiently solve search problems, with application to automated planning. Specifically, we consider the frameworks of beam search, greedy search, and randomized search, which all aim to maintain tractability at the cost of not guaranteeing completeness nor optimality. Our learning objective for each of these frameworks is to induce a linear ranking function for guiding the search that performs nearly as well as unconstrained search, hence gaining computational efficiency without seriously sacrificing optimality. We first investigate the problem of learning ranking functions to guide beam search, with a focus on learning feature weights given a set of features. We present a theoretical analysis of the problem's computational complexity that identifies the core efficient and hard subclasses. In addition we study online learning algorithms for the problem and analyze their convergence properties. The algorithms are applied to automated planning, showing that our approach is often able to outperform an existing state-of-the-art planning heuristic as well as a recent approach to learning such heuristics. Next, we study the problem of automatically learning both features and weights to guide greedy search. We present a new iterative learning algorithm based on RankBoost, an efficient boosting algorithm for ranking and demonstrate strong empirical results in the domain of automated planning. Finally, we consider the problem of learning randomized policies for guiding randomized greedy search with restarts. We pose this problem in the framework of reinforcement learning and investigate policy-gradient algorithms for learning both features and weights. The results show that in a number of domains this approach is significantly better than those obtained for deterministic greedy search

Hypoacetylation, Hypomethylation, and Dephosphorylation of H2B Histones and Excessive Histone Deacetylase Activity in DU-145 Prostate Cancer Cells

BACKGROUND: Hypoacetylation on histone H3 of human prostate cancer cells has been described. Little is known about the modifications of other histones from prostate cancer cells. METHODS: Histones were isolated from the prostate cancer cell line DU-145 and the non-malignant prostatic cell line RC170N/h. Post-translational modifications of histone H2B were determined by liquid chromatography-mass spectrometry (LC-MS)/MS. RESULTS: The histone H2B of the prostate cancer cell line DU-145 was found to have hypoacetylation, hypomethylation, and dephosphorylation as compared to the non-malignant prostatic cell line RC170N/h. H2B regained acetylation on multiple lysine residues, phosphorylation on Thr19, and methylation on Lys23 and Lys43 in the DU-145 cells after sodium butyrate treatment. CONCLUSIONS: The histone H2B of DU-145 prostate cancer cells are hypoacetylated, hypomethylated, and dephosphorylated. Histone deacetylase inhibitor reversed this phenotype. Epigenetic agent may therefore be useful for prostate cancer therapy and worth further investigation

Occupational skin diseases and prevention among sanitation workers in China

Background: Little research has been focused on the health status or the occupational protection awareness of sanitation workers. The policy recommendations on the occupational safety and health of sanitation workers based on the scientific research are also insufficient in developing countries like China. Objective: To study the incidence of dermatoses and the relevance with occupational exposure, protection awareness and protective measures among sanitation workers for better management and protection of the sanitation workers. Methods: 273 sanitation workers and 113 administrative staff from 11 streets of Wuhan were recruited. Dermatological problems were evaluated and recorded by physical examination. Occupational exposure, protection awareness, the use of protective equipments and personal history of skin disease were assessed by questionnaires. Results: Compared with administrative staff, sanitation workers had much more occupational dermatological problems and had a much higher rate of harmful ultraviolet ray exposure. Young sanitation workers were more aware of occupational self-protection and a relatively higher rate of them using protective equipments compared with old ones. Conclusion: Exposure to multiple health hazards and the poor use of protective equipments are related to skin diseases in sanitation workers. Prejob training of self-protection and the use of protective equipments are recommended

Significance of alpha-fetoprotein combined with apolipoprotein A1 and alkaline phosphatase in the diagnosis of hepatitis B virus-related liver cancer

Objective To investigate the changes of apolipoprotein A1 （ApoA1） and alkaline phosphatase in hepatitis B virus （HBV）-related liver cancer， and evaluate the diagnostic performance of alpha-fetoprotein （AFP） combined with other indexes for HBV-related liver cancer. Methods 1 089 patients with chronic hepatitis B， compensated cirrhosis， non-compensated cirrhosis post-hepatitis B and chronic B-related liver cancer were enrolled. Among them， 745 cases were included in non-liver cancer group， and 344 cases in the HBV-related liver cancer group （liver cancer group）. The influencing factors of HBV-related liver cancer were identified by univariate and multivariate Logistic regression analyses. The area under the receiver operating characteristic （ROC） curve （AUC） was adopted to evaluate the diagnostic efficacy of AFP combined with other serological indexes in HBV-related liver cancer. Results Significant differences were observed in serum levels of ApoA1， alkaline phosphatase and AFP between the non-liver cancer and liver cancer groups （all P<0.05）. Multivariate Logistic regression analysis showed that sex， age， AFP， ApoA1 and alkaline phosphatase were the influencing factors of HBV-related liver cancer （all P < 0.05）. The AUC of the model consisting of these indexes combined for HBV-related liver cancer was 0.859， and 0.750 for AFP alone， indicating the model of these indexes combined yielded significantly higher diagnostic efficacy compared with AFP alone （P < 0.05）. Conclusions The model consisting of serum AFP， ApoA1 and alkaline phosphatase yields higher diagnostic efficacy than AFP alone. It possesses certain value for auxiliary diagnosis of HBV-related liver cancer

Hybrid GRU-CNN Bilinear Parameters Initialization for Quantum Approximate Optimization Algorithm

The Quantum Approximate Optimization Algorithm (QAOA), a pivotal paradigm in the realm of variational quantum algorithms (VQAs), offers promising computational advantages for tackling combinatorial optimization problems. Well-defined initial circuit parameters, responsible for preparing a parameterized quantum state encoding the solution, play a key role in optimizing QAOA. However, classical optimization techniques encounter challenges in discerning optimal parameters that align with the optimal solution. In this work, we propose a hybrid optimization approach that integrates Gated Recurrent Units (GRU), Convolutional Neural Networks (CNN), and a bilinear strategy as an innovative alternative to conventional optimizers for predicting optimal parameters of QAOA circuits. GRU serves to stochastically initialize favorable parameters for depth-1 circuits, while CNN predicts initial parameters for depth-2 circuits based on the optimized parameters of depth-1 circuits. To assess the efficacy of our approach, we conducted a comparative analysis with traditional initialization methods using QAOA on Erd\H{o}s-R\'enyi graph instances, revealing superior optimal approximation ratios. We employ the bilinear strategy to initialize QAOA circuit parameters at greater depths, with reference parameters obtained from GRU-CNN optimization. This approach allows us to forecast parameters for a depth-12 QAOA circuit, yielding a remarkable approximation ratio of 0.998 across 10 qubits, which surpasses that of the random initialization strategy and the PPN2 method at a depth of 10. The proposed hybrid GRU-CNN bilinear optimization method significantly improves the effectiveness and accuracy of parameters initialization, offering a promising iterative framework for QAOA that elevates its performance

TIR/BB-Loop Mimetic AS-1 Attenuates Cardiac Ischemia/Reperfusion Injury via a Caveolae and Caveolin-3-Dependent Mechanism

AS-1, the TIR/BB loop mimetic, plays a protective role in cardiac ischemia/reperfusion (I/R) but the molecular mechanism remains unclear. The muscle specific caveolin3 (Cav-3) and the caveolae have been found to be critical for cardioprotection. This study aimed to evaluate our hypothesis that caveolae and Cav-3 are essential for AS-1-induced cardioprotection against myocardial I/R injury. To address these issues, we analyzed the involvement of Cav-3 in AS-1 mediated cardioprotection both in vivo and in vitro. We demonstrate that AS-1 administration significantly decreased infarct size, improved cardiac function after myocardial I/R and modulated membrane caveolae and Cav-3 expression in the myocardium. For in vitro studies, AS-1 treatment prevented Cav-3 re-distribution induced by H/R injury. In contrast, disruption of caveolae by MCD treatment or Cav-3 knockdown abolished the protection against H/R-induced myocytes injury by AS-1. Our findings reveal that AS-1 attenuates myocardial I/R injury through caveolae and Cav-3 dependent mechanism