Fractional-in-time and multifracational-in-space stochastic partial differential equations

This paper derives the weak-sense Gaussian solution to a family of fractional-in-time and multifractional-in-space stochastic partial differential equations, driven by fractional-integrated-in-time spatiotemporal white noise. Some fundamental results on the theory of pseudodifferential operators of variable order, and on the Mittag-Leffler function are applied to obtain the temporal, spatial and spatiotemporal H¨older continuity, in the mean-square sense, of the derived solution

Synthesis of Single Phase Hg-1223 High Tc Superconducting Films With Multistep Electrolytic Process

We report the multistep electrolytic process for the synthesis of high Tc single phase HgBa2Ca2Cu3O8+ (Hg-1223) superconducting films. The process includes : i) deposition of BaCaCu precursor alloy, ii) oxidation of BaCaCu films, iii) electrolytic intercalation of Hg in precursor BaCaCuO films and iv) electrochemical oxidation and annealing of Hg-intercalated BaCaCuO films to convert into Hg1Ba2Ca2Cu3O8+ (Hg-1223). Films were characterized by thermo-gravimetric analysis (TGA) and differential thermal analysis (DTA), X-ray diffraction (XRD) and scanning electron microscopy (SEM). The electrolytic intercalation of Hg in BaCaCuO precursor is proved to be a novel alternative to high temperature-high pressure mercuration process. The films are single phase Hg-1223 with Tc = 121.5 K and Jc = 4.3 x 104 A/cm2.Comment: 17 Pages, 10 Figures. Submitted to Superconductor Science and Technolog

Plasmon oscillations in ellipsoid nanoparticles: beyond dipole approximation

The plasmon oscillations of a metallic triaxial ellipsoid nanoparticle have been studied within the framework of the quasistatic approximation. A general method has been proposed for finding the analytical expressions describing the potential and frequencies of the plasmon oscillations of an arbitrary multipolarity order. The analytical expressions have been derived for an electric potential and plasmon oscillation frequencies of the first 24 modes. Other higher orders plasmon modes are investigated numerically.Comment: 33 pages, 12 figure

A 6-DIMENSIONAL HILBERT APPROACH TO INDEX FULL WAVEFORM LiDAR DATA IN A DISTRIBUTED COMPUTING ENVIRONMENT

Laser scanning data are increasingly available across the globe. To maximize the data's usability requires proper storage and indexing. While significant research has been invested in developing storage and indexing solutions for laser scanning point clouds (i.e. using the discrete form of the data), little attention has been paid to developing equivalent solutions for full waveform (FWF) laser scanning data, especially in a distributed computing environment. Given the growing availability of FWF sensors and datasets, FWF data management solutions are increasingly needed. This paper presents an attempt towards establishing a scalable solution for handling large FWF datasets by introducing the distributed computing solution for FWF data. The work involves a FWF database built atop HBase – the distributed database system running on Hadoop commodity clusters. By combining a 6-dimensional (6D) Hilbert spatial code and a temporal index into a compound indexing key, the database system is capable of supporting multiple spatial, temporal, and spatio-temporal queries. Such queries are important for FWF data exploration and dissemination. The proposed spatial decomposition at a fine resolution of 0.05 m allows the storage of each LiDAR FWF measurement (i.e. pulse, waves, and points) on a single row of the database, thereby providing the full capabilities to add, modify, and remove each measurement record anatomically. While the feasibility and capabilities of the 6D Hilbert solution are evident, the Hilbert decomposition is not due to the complications from the combination of the data’s high dimensionality, fine resolution, and large spatial extent. These factors lead to a complex set of both attractive attributes and limitation in the proposed solution, which are described in this paper based on experimental tests using a 1.1 billion pulse LiDAR scan of a portion of Dublin, Ireland

Immunotherapeutic approaches for hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a cancer with a high mortality rate due to the fact that the diagnosis usually occurs at anadvanced stage. Even in case of curative surgical treatment, recurrence is common. Sorafenib and regorafenib are the only therapeutic agents that have been demonstrated to be effective in advanced HCC, thus novel curative approaches are urgently needed. Recent studies focus on the role of immune system in HCC. In fact, the unique immune response in the liver favors tolerance, which can represent a real challenge for conventional immunotherapy in these patients. Spontaneous immune responses against tumor antigens have been detected, and new immune therapies are under investigation: dendritic cell vaccination, immune-modulator strategy, and immune checkpoint inhibition. In recent years different clinical trials examining the use of immunotherapy to treat HCC have been conducted with initial promising results. This review article will summarize the literature data concerning the potential immunotherapeutic approaches in HCC patient

Deep Memory Networks for Attitude Identification

We consider the task of identifying attitudes towards a given set of entities from text. Conventionally, this task is decomposed into two separate subtasks: target detection that identifies whether each entity is mentioned in the text, either explicitly or implicitly, and polarity classification that classifies the exact sentiment towards an identified entity (the target) into positive, negative, or neutral. Instead, we show that attitude identification can be solved with an end-to-end machine learning architecture, in which the two subtasks are interleaved by a deep memory network. In this way, signals produced in target detection provide clues for polarity classification, and reversely, the predicted polarity provides feedback to the identification of targets. Moreover, the treatments for the set of targets also influence each other -- the learned representations may share the same semantics for some targets but vary for others. The proposed deep memory network, the AttNet, outperforms methods that do not consider the interactions between the subtasks or those among the targets, including conventional machine learning methods and the state-of-the-art deep learning models.Comment: Accepted to WSDM'1

Mobile power generation system based on biomass gasification

Disaster-hit and/or un-electrified remote areas usually have electricity accessibility issues and an abundance of plant-derived debris and wood from destroyed wooden structures; this can be potentially addressed by employing a decentralized ultra-small biomass-fed gasification power generating system. This paper presents an assessment of the technical viability of an ultra-small gasification system that utilizes densified carbonized wood pellets/briquettes. The setup was run continuously for 100 h. A variety of biomass was densified and carbonized by harnessing fugitive heat sources before charging into the reactor. Carbonized briquettes and furnished blends exhibited inferior gasification performance compared to the carbonized pellets. In the absence of tar blockage problems, steady-state conditions were achieved when pre-treated feedstock was used. Under steady-state conditions for carbonized pellets gasification operated at an equivalence ratio of 0.32, cold gas efficiency and carbon conversion achieved 49.2% and 70.5%, respectively. Overall efficiency and maximum power output of 20.3% and 21 kW were realised, respectively. It was found that the system could keep stable while the low heating valve of syngas was over 4 MJ/m3 on condition that avoiding tar blocking issues. The results indicate that the proposed compact ultra-small power generation system is a technically feasible approach to remedy power shortage challenge. In addition, process simulation considering carbonized wood gasification combined power generation was formulated to produce syngas and electricity. Woody pellets with the flow rate of 20 kg/h could generate a 15.18 kW power at the air flow rate of 40 Nm3/h, which is in a good agreement with 15 kW in the 100 h operation. It is indicated that the gasification combined power generation cycle simulated by Aspen simulator could achieve reliable data to assist the complicated experiment operation. © 2022, The Author(s).Science and Technology Commission of Shanghai Municipality, STCSM: 20PJ1402800; Ministry of Defence, MOD; National Key Research and Development Program of China, NKRDPC: 2021YFE0108900The authors thank for the project of the National Key Research and development (R&D) Program and International Science and Technology Innovation Project between Governments (2021YFE0108900) and Pujiang Talent Program Supported by Fund of Shanghai Science and Technology Committee (project code: 20PJ1402800). This work has been supported by Innovative Science and Technology Initiative for Security (Ministry of Defence, Japan)

Modelling chemistry and biology after implantation of a drug-eluting stent. Part I: Drug transport

Drug-eluting stents have been used widely to prevent restenosis of arteries following percutaneous balloon angioplasty. Mathematical modelling plays an important role in optimising the design of these stents to maximise their efficiency. When designing a drug-eluting stent system, we expect to have a sufficient amount of drug being released into the artery wall for a sufficient period to prevent restenosis. In this paper, a simple model is considered to provide an elementary description of drug release into artery tissue from an implanted stent. From the model, we identified a parameter regime to optimise the system when preparing the polymer coating. The model provides some useful order of magnitude estimates for the key quantities of interest. From the model, we can identify the time scales over which the drug traverses the artery wall and empties from the polymer coating, as well as obtain approximate formulae for the total amount of drug in the artery tissue and the fraction of drug that has released from the polymer. The model was evaluated by comparing to in-vivo experimental data and good agreement was found

Late transient acceleration of the universe in string theory on S1/Z2S^{1}/Z_{2}

Recently, in Gong {\em et al} \cite{GWW07} and Wang and Santos \cite{WS07} it was shown that the effective cosmological constant on each of the two orbifold branes can be easily lowered to its current observational value, by using the large extra dimensions in the framework of both M-Theory and string theory on $S^{1}/Z_{2}$. In this paper, we study the current acceleration of the universe, using the formulas developed in \cite{WS07}. We first construct explicitly time-dependent solution to the 10-dimensional bulk of the Neveu-Schwarz/Neveu-Schwarz sector, compactified on a 5-dimensional torus. Then, we write down the generalized Friedmann equations on each of the two dynamical branes, and fit the models to the 182 gold supernova Ia data and the BAO parameter from SDSS, using both of our MINUIT and Monte-Carlo Markov Chain (MCMC) codes. With the best fitting values of the parameters involved as initial conditions, we integrate the generalized Friedmann equations numerically and find the future evolution of the universe. We find that it depends on the choice of the radion potentials $V_{4}^{(I)} (I = 1, 2)$ of the branes. In particular, when choosing them to be the Goldberger-Wise potentials, $V_{4}^{(I)} = \lambda_{4}^{(I)} (\psi^{2} - {v_{I}}^{2})^{2}$, we find that the current acceleration of the universe driven by the effective cosmological constant is only temporary. Due to the effects of the potentials, the universe will be finally in its decelerating expansion phase again. We also study the proper distance between the two branes, and find that it remains almost constant during the whole future evolution of the universe in all the models considered.Comment: revtex4, 18 figures. Typos corrected and new References added. Version to be published in JCA