Dominant role of many-body effects on the carrier distribution function of quantum dot lasers

The effects of free-carrier-induced shift and broadening on the carrier distribution function are studied considering different extreme cases for carrier statistics (Fermi–Dirac and random carrier distributions) as well as quantum dot (QD) ensemble inhomogeneity and state separation using a Monte Carlo model. Using this model, we show that the dominant factor determining the carrier distribution function is the free carrier effects and not the choice of carrier statistics. By using empirical values of the free-carrier-induced shift and broadening, good agreement is obtained with experimental data of QD materials obtained under electrical injection for both extreme cases of carrier statistics

Development of Advanced GaAs Based Quantum Dot Devices

This thesis details research on the development of ~1.3μm quantum dot (QD) devices. QD devices which are theoretically ideal for the realisation of temperature insensitive lasers. A method to measure the recombination coefficients in a semiconductor laser is developed, and the role of Auger recombination in the realisation of temperature insensitive lasers is discussed. Moreover, due to a broad spectral linewidth and strong state-filling effects, QD structures are promising for application as broadband light sources. It is reported that the Auger recombination coefficient decreases with increasing device temperature, as measured by several complicated experimental techniques. In chapter 2, a simple analysis method (small signal modulation) to measure all of the recombination coefficients is introduced and discussed. In chapter 3, experimental data based on the small signal modulation technique is analysed. Which shows that all of the recombination coefficients, including the Auger coefficient, are a function of temperature and modulation doping in QD lasers. Following on from chapter 3, in chapter 4 the dynamic characteristic (differential carrier lifetime) of a 3μm-ridge QD laser device fabricated from commercial QD material is investigated. The modelled GS peak gain as a function of current density is determined based on the recombination coefficients, the random population model and the measured gain (via the iv Hakki-Paoli method). Then, by comparing the modelled GS gain to the experimental results, the carrier thermal escape parameter is determined. Finally in chapter 4, the variation of the Auger coefficient is explored to investigate the possibility of a temperature independent current density. The selective intermixing technique can be used in order to achieve broadband light source devices. In chapter 5, the intermixing method is introduced based on both quantum well and quantum dot structures. Then, a number of different capping materials on samples with different active region structures are discussed based on photoluminescence measurements from intermixed structures. The potential for selective area intermixing of an integrated device with a TiO2 and SiO2 cap annealed on a p-doped sample is demonstrated at the end of the chapter. Finally, in chapter 6, two integrated devices are fabricated based on this TiO2 and SiO2 cap. These devices demonstrate a broad emission bandwidth, and by applying a fast Fourier transform to the spectra in order to determine the point spread function of the instrument, and application of the Rayleigh criterion for resolution, an estimation of the resolution in an OCT system is made

Learning from Symmetry: Meta-Reinforcement Learning with Symmetric Data and Language Instructions

Meta-reinforcement learning (meta-RL) is a promising approach that enables the agent to learn new tasks quickly. However, most meta-RL algorithms show poor generalization in multiple-task scenarios due to the insufficient task information provided only by rewards. Language-conditioned meta-RL improves the generalization by matching language instructions and the agent's behaviors. Learning from symmetry is an important form of human learning, therefore, combining symmetry and language instructions into meta-RL can help improve the algorithm's generalization and learning efficiency. We thus propose a dual-MDP meta-reinforcement learning method that enables learning new tasks efficiently with symmetric data and language instructions. We evaluate our method in multiple challenging manipulation tasks, and experimental results show our method can greatly improve the generalization and efficiency of meta-reinforcement learning

Dynamic capability matters: Uncovering its fundamental role in decision making of environmental innovation

The final publication is available at Elsevier via http:/dx.doi.org/10.1016/j.jclepro.2017.12.208 © 2018. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/This study aims to explore organizations’ intrinsic drivers of voluntarily adopting environmental innovations that are in early stage of diffusion. In particular, it investigates the vital role of dynamic capabilities in the decision-making process of adoption. Adopting a process-oriented model, this study focuses on the initiation (instead of implementation) process of innovation adoption and examines how dynamic capabilities can result in intention of adopting environmental innovation voluntarily. The findings show that dynamic capabilities have positive effects on organizational intention of adoption not only directly, but also indirectly through facilitating managers to interpret environmental innovations as an opportunity, rather than a threat. Furthermore, this partial mediating role of managerial interpretation between dynamic capabilities and environmental innovation adoption varies depending on organizational social position. Compared to central firms, peripheral firms tend to be more responsive to managerial interpretation. The chain from dynamic capabilities, to interpretation of environmental innovation as an opportunity, and finally to the intention of adoption is stronger for peripheral firms than for central ones.National Natural Science Foundation of China [grant numbers 71171183, 71172213

A giant glitch from the magnetar SGR J1935+2154 before FRB 200428

Fast radio bursts (FRBs) are short pulses observed in radio frequencies usually originating from cosmological distances. The discovery of FRB 200428 and its X-ray counterpart from the Galactic magnetar SGR J1935+2154 suggests that at least some FRBs can be generated by magnetars. However, the majority of X-ray bursts from magnetars are not associated with radio emission. The fact that only in rare cases can an FRB be generated raises the question regarding the special triggering mechanism of FRBs. Here we report a giant glitch from SGR J1935+2154, which occurred approximately $3.1\pm2.5$\,day before FRB 200428, with $\Delta\nu=19.8\pm1.4$ {\rm $\mu$Hz} and $\Delta\dot{\nu}=6.3\pm1.1$\,pHz s$^{-1}$. The corresponding spin-down power change rate $\Delta\dot\nu/\dot\nu$ is among the largest in all the detected pulsar glitches. The glitch contains a delayed spin-up process that is only detected in the Crab pulsar and the magnetar 1E 2259+586, a large persistent offset of the spin-down rate, and a recovery component which is about one order of magnitude smaller than the persistent one. The temporal coincidence between the glitch and FRB 200428 suggests a physical connection between the two. The internally triggered giant glitch of the magnetar likely altered the magnetosphere structure dramatically in favour of FRB generation, which subsequently triggered many X-ray bursts and eventually FRB 200428 through additional crustal cracking and Alfv\'en wave excitation and propagation

Identifying the Antiproliferative Effect of Astragalus Polysaccharides on Breast Cancer: Coupling Network Pharmacology With Targetable Screening From the Cancer Genome Atlas

Background:Astragalus polysaccharides (APS), natural plant compounds, have recently emerged as a promising strategy for cancer treatment, but little is known concerning their effects on breast cancer (BC) tumorigenesis.Methods: We obtained breast cancer genetic data from The Cancer Genome Atlas (TCGA) database, network pharmacology to further clarify its biological properties. Survival analysis and molecular docking techniques were implemented for the final screening to obtain key target information. Our experiments focused on the detection of intervention effects of APS on BC cells (MCF-7 and MDA-MB-231), and quantitative RT-PCR (qRT-PCR) was used to assess the expression of key targets.Results: A total of 1,439 differentially expressed genes (DEGs) were identified by TCGA and used to build disease networks. Module analysis, gene ontology and pathway analysis revealed characteristic of the DEGs network. Topological properties were used to identify key targets, survival analysis and molecular docking finally found that the targets of APS regulation of BC cells may be CCNB1, CDC6, and p53. Through cell viability, migration and invasion assays, we found that APS interferes with the development of breast cancer in MCF7 and MDA-MB-231 cells in a dose-dependent manner. Furthermore, qRT-PCR verification suggested that the expression of CCNB1 and CDC6 in breast cancer cells was significantly downregulated in response to APS, while expression of the tumor suppressor gene P53 was significantly increased.Conclusion: Results of this study suggest therapeutic potential for APS in BC treatment, possibly through interventions with CCNB1, CDC6, and P53. Furthermore, these findings illustrate the feasibility of using network pharmacology to connect large-scale target data as a way to discover the mechanism of natural products interfering with disease

The Modulatory Properties of Astragalus membranaceus Treatment on Triple-Negative Breast Cancer: An Integrated Pharmacological Method.

Background: Studies have shown that the natural products of Astragalus membranaceus (AM) can effectively interfere with a variety of cancers, but their mechanism of action on breast cancer remains unclear. Triple-negative breast cancer (TNBC) is associated with a severely poor prognosis due to its invasive phenotype and lack of biomarker-driven-targeted therapies. In this study, the potential mechanism of the target composition acting on TNBC was explored by integrated pharmacological models and in vitro experiments. Materials and Methods: Based on the Gene Expression Omnibus (GEO) database and the relational database of Traditional Chinese Medicines (TCMs), the drug and target components were initially screened to construct a common network module, and multiattribute analysis was then used to characterize the network and obtain key drug-target information. Furthermore, network topology analysis was used to characterize the betweenness and closeness of key hubs in the network. Molecular docking was used to evaluate the affinity between compounds and targets and obtain accurate combination models. Finally, in vitro experiments verified the key component targets. The cell counting kit-8 (CCK-8) assay, invasion assay, and flow cytometric analysis were used to assess cell viability, invasiveness, and apoptosis, respectively, after Astragalus polysaccharides (APS) intervention. We also performed western blot analysis of key proteins to probe the mechanisms of correlated signaling pathways. Results: We constructed "compound-target" (339 nodes and 695 edges) and "compound-disease" (414 nodes and 6458 edges) networks using interaction data. Topology analysis and molecular docking were used as secondary screens to identify key hubs of the network. Finally, the key component APS and biomarkers PIK3CG, AKT, and BCL2 were identified. The in vitro experimental results confirmed that APS can effectively inhibit TNBC cell activity, reduce invasion, promote apoptosis, and then counteract TNBC symptoms in a dose-dependent manner, most likely by inhibiting the PIK3CG/AKT/BCL2 pathway. Conclusion: This study provides a rational approach to discovering compounds with a polypharmacology-based therapeutic value. Our data established that APS intervenes with TNBC cell invasion, proliferation, and apoptosis via the PIK3CG/AKT/BCL2 pathway and could thus offer a promising therapeutic strategy for TNBC

GaAs-Based Superluminescent Light-Emitting Diodes with 290-nm Emission Bandwidth by Using Hybrid Quantum Well/Quantum Dot Structures

A high-performance superluminescent light-emitting diode (SLD) based upon a hybrid quantum well (QW)/quantum dot (QD) active element is reported and is assessed with regard to the resolution obtainable in an optical coherence tomography system. We report on the appearance of strong emission from higher order optical transition from the QW in a hybrid QW/QD structure. This additional emission broadening method contributes significantly to obtaining a 3-dB linewidth of 290 nm centered at 1200 nm, with 2.4 mW at room temperature

Review and consensus recommendations on clinical APT-weighted imaging approaches at 3T: Application to brain tumors

Amide proton transfer-weighted (APTw) MR imaging shows promise as a biomarker of brain tumor status. Currently used APTw MRI pulse sequences and protocols vary substantially among different institutes, and there are no agreed-on standards in the imaging community. Therefore, the results acquired from different research centers are difficult to compare, which hampers uniform clinical application and interpretation. This paper reviews current clinical APTw imaging approaches and provides a rationale for optimized APTw brain tumor imaging at 3T, including specific recommendations for pulse sequences, acquisition protocols, and data processing methods. We expect that these consensus recommendations will become the first broadly accepted guidelines for APTw imaging of brain tumors on 3 T MRI systems from different vendors. This will allow more medical centers to use the same or comparable APTw MRI techniques for the detection, characterization, and monitoring of brain tumors, enabling multi-center trials in larger patient cohorts and, ultimately, routine clinical use