Higgs boson production and decay at e+e−e^{+}e^{-} colliders as a probe of the Left-Right twin Higgs model

In the framework of the Left-Right twin Higgs (LRTH) model, we consider the constrains from the latest search for high-mass dilepton resonances at the LHC and find that the heavy neutral boson $Z_H$ is excluded with mass below 2.76 TeV. Under these constrains, we study the Higgs-Gauge coupling production processes $e^{+}e^{-}\rightarrow ZH$, $e^{+}e^{-}\rightarrow \nu_{e}\bar{\nu_{e}}H$ and $e^{+}e^{-}\rightarrow e^{+}e^{-}H$, top quark Yukawa coupling production process $e^{+}e^{-}\rightarrow t\bar{t}H$, Higgs self-couplings production processes $e^{+}e^{-}\rightarrow ZHH$ and $e^{+}e^{-}\rightarrow \nu_{e}\bar{\nu_{e}}HH$ at $e^{+}e^{-}$ colliders. Besides, we study the major decay modes of the Higgs boson, namely $h\rightarrow f\bar{f}$($f=b,c,\tau$), $VV^{*}(V=W, Z)$, $gg$, $\gamma\gamma$. We find that the LRTH effects are sizable so that the Higgs boson processes at $e^{+}e^{-}$ collider can be a sensitive probe for the LRTH model.Comment: Final version to appear in Nucl.Phys.

Controlled release of nitric oxide chemotherapy using a nanosized biodegradable multi-arm polymer

Nitric oxide is a cell signaling molecule that can be a potent inducer of cell death in cancers at elevated concentrations. Nitric oxide molecules are short-lived in vivo; therefore, NO-donating prodrugs have been developed that can deliver NO to tissues at micromolar concentrations. However, NO is also toxic to normal tissues and chronic exposure at low levels can induce tumor growth. We have designed a polymeric carrier system to deliver nitric oxide locoregionally to tumorigenic tissues. A highly water solubility and biodegradable 4-arm polymer nanocarrier, sugar poly-(6-O-methacryloyl-D-galactose), was synthesized using MADIX/RAFT polymerization, and utilized to deliver high concentrations of nitric oxide to xenografts of human head and neck squamous cell carcinoma (HNSCC). The in vitro release of the newly synthesized nitric oxide donor, O2-(2,4-dinitrophenyl) 1-[4-(2-hydroxy)ethyl]-3-methylpiperazin-1-yl]diazen-1-ium-1,2-diolate and its corresponding multi-arm polymer-based nanoconjugate demonstrated a 1- and 2.3-fold increase in half-life, respectively, compared to the release half-life of the nitric oxide -donor prodrug JS-K. When administered to tumor-bearing nude mice, the subcutaneously injected multi-arm polymer nitric oxide nanoparticles resulted in 50% tumor inhibition and a 7-week extension of the average survival time, compared to intravenous JS-K therapy (nitric oxide nanoparticles: CR=25%, PR=37.5%, PD=37.5%; JS-K: PD=100%). In summary, we have developed an effective nitric oxide anti-cancer chemotherapy that could be administered regionally to provide the local disease control, improving prognosis for head and neck cancers

Streaming Facility Location in High Dimension via New Geometric Hashing

In Euclidean Uniform Facility Location, the input is a set of clients in $\mathbb{R}^d$ and the goal is to place facilities to serve them, so as to minimize the total cost of opening facilities plus connecting the clients. We study the classical setting of dynamic geometric streams, where the clients are presented as a sequence of insertions and deletions of points in the grid $\{1,\ldots,\Delta\}^d$, and we focus on the high-dimensional regime, where the algorithm's space complexity must be polynomial (and certainly not exponential) in $d\cdot\log\Delta$. We present a new algorithmic framework, based on importance sampling from the stream, for $O(1)$-approximation of the optimal cost using only $\mathrm{poly}(d\cdot\log\Delta)$ space. This framework is easy to implement in two passes, one for sampling points and the other for estimating their contribution. Over random-order streams, we can extend this to a one-pass algorithm by using the two halves of the stream separately. Our main result, for arbitrary-order streams, computes $O(d^{1.5})$-approximation in one pass by using the new framework but combining the two passes differently. This improves upon previous algorithms that either need space exponential in $d$ or only guarantee $O(d\cdot\log^2\Delta)$-approximation, and therefore our algorithms for high-dimensional streams are the first to avoid the $O(\log\Delta)$-factor in approximation that is inherent to the widely-used quadtree decomposition. Our improvement is achieved by introducing a novel geometric hashing scheme that maps points in $\mathbb{R}^d$ into buckets of bounded diameter, with the key property that every point set of small-enough diameter is hashed into at most $\mathrm{poly}(d)$ distinct buckets. Finally, we complement our results by showing $1.085$-approximation requires space exponential in $\mathrm{poly}(d\cdot\log\Delta)$, even for insertion-only streams.Comment: The abstract is shortened to meet the length constraint of arXi

A sample-position-autocorrection system with precision better than 1 \um~in angle-resolved photoemission experiments

We present the development of a high-precision sample-position-autocorrection system for photoemission experiments. A binocular vision method based on image pattern matching calculations was realized to track the sample position with an accuracy better than 1 \um, which was much smaller than the spot size of the incident laser. We illustrate the performance of the sample-position-autocorrection system with representative photoemission data on the topological insulator Bi$_2$Se$_3$ and an optimally-doped cuprate superconductor \Bi. Our method provides new possibilities for studying the temperature-dependent electronic structures in quantum materials by laser-based or spatially resolved photoemission systems with high precision and efficiency.Comment: 6 pages, 4 figure