Diversity receiver design and channel statistic estimation in fading channels

The main goal of this thesis is to provide an in-depth study of two important techniques that are effective in improving the performance, data rate, or bandwidth-efficiency in wireless communication systems. The two techniques are, first, diversity combining equipped with quadrature amplitude modulation (QAM), and second, the estimation of fading channel statistical properties;To effectively combat the adverse effect of fading and to improve the error rate performance in wireless communications, one of the major approaches is to employ diversity combining techniques. In the first part of this thesis, we focus on the equal gain combining (EGC) and hybrid-selection equal gain combining (HS/EGC) for bandwidth-efficient wireless systems (i.e. QAM systems). For EGC QAM systems, we propose the receiver structure and the corresponding decision variables, and then study the effects of imperfect channel estimation (ICE) and quantify the loss of the signal-to-noise ratio (SNR) gain caused by ICE. For HS/EGC QAM system, we develop a general approach to derive unified error rate and outage probability formulas over various types of fading channels based on the proposed HS/EGC receiver. The main contribution of this work lies in that it provides effective hybrid diversity schemes and new analytical approaches to enable thorough analysis and effective design of bandwidth efficient wireless communication systems which suffer from ICE and operate in realistic multipath channels;Channel statistic information is proven to be critical in determining the systems design, achievable data rate, and achievable performance. In the second part of this thesis, we study the estimation of the fading channel Statistics and Probability; We propose several iterative algorithms to estimate the first- and second-order statistics of general fading or composite fading-shadowing channels and derive the Cramer-Rao bounds (CRBs) for all the cases. We demonstrate that these iterative methods are efficient in the sense that they achieve their corresponding CRBs. The main contribution of this work is that it bridges the gap between the broad utilization of fading channel statistical properties and the lack of systematic study that makes such statistical properties available

Isotopic effects on the thermal conductivity of graphene nanoribbons: localization mechanism

Thermal conductivity of graphene nanoribbons (GNR) with length 106~{\AA} and width 4.92~{\AA} after isotopic doping is investigated by molecular dynamics with quantum correction. Two interesting phenomena are found: (1) isotopic doping reduces thermal conductivity effectively in low doping region, and the reduction slows down in high doping region; (2) thermal conductivity increases with increasing temperature in both pure and doped GNR; but the increasing behavior is much more slowly in the doped GNR than that in pure ones. Further studies reveal that the physics of these two phenomena is related to the localized phonon modes, whose number increases quickly (slowly) with increasing isotopic doping in low (high) isotopic doping region.Comment: 6 fig

Maximum likelihood estimation of statistical properties of composite gamma-lognormal fading channels

We propose maximum likelihood (ML) methods for estimating the parameters of composite gamma-lognormal fading channels. Newton-Raphson and expectation-maximization (EM) algorithms are developed to compute the ML estimates of the mean and variance of the shadowing component, and the Nakagami-m parameter of the fading component. We also derive Crame/spl acute/r-Rao bounds (CRBs) for the unknown parameters. Numerical simulations demonstrate the performance of the proposed method

Impact of Managerial Responses on Product Sales: Examining the Moderating Role of Competitive Intensity and Market Position

Online review platforms have become very popular in recent years, generating massive numbers of online reviews and thus enticing numerous enterprises to respond to reviews. Although the economic impact (e.g., sales impact) of managerial responses is well recognized, it is unclear whether such an impact is moderated by competitive intensity and market position. This study examines the moderating effects of competitive intensity and market position in the relationship between managerial responses and sales. Using a panel dataset from one of the largest restaurant review platforms in China, this research found that the influence of the volume of managerial responses to positive word-of-mouth (WOM) on sales declined with increasing competitive intensity and decreasing market position. Moreover, we found the volume and degree of personalization of managerial responses to negative WOM to be more important for enterprises with a low market position versus those with a high market position. Our results provide insights into the effectiveness of managerial responses in different environments. We also offer managerial implications to service providers on response strategies

High-mass Starless Clumps in the inner Galactic Plane: the Sample and Dust Properties

We report a sample of 463 high-mass starless clump (HMSC) candidates within $-60\deg<l<60\deg$ and $-1\deg<b<1\deg$. This sample has been singled out from 10861 ATLASGAL clumps. All of these sources are not associated with any known star-forming activities collected in SIMBAD and young stellar objects identified using color-based criteria. We also make sure that the HMSC candidates have neither point sources at 24 and 70 \micron~nor strong extended emission at 24 $\mu$m. Most of the identified HMSCs are infrared ($\le24$ $\mu$m) dark and some are even dark at 70 $\mu$m. Their distribution shows crowding in Galactic spiral arms and toward the Galactic center and some well-known star-forming complexes. Many HMSCs are associated with large-scale filaments. Some basic parameters were attained from column density and dust temperature maps constructed via fitting far-infrared and submillimeter continuum data to modified blackbodies. The HMSC candidates have sizes, masses, and densities similar to clumps associated with Class II methanol masers and HII regions, suggesting they will evolve into star-forming clumps. More than 90% of the HMSC candidates have densities above some proposed thresholds for forming high-mass stars. With dust temperatures and luminosity-to-mass ratios significantly lower than that for star-forming sources, the HMSC candidates are externally heated and genuinely at very early stages of high-mass star formation. Twenty sources with equivalent radius $r_\mathrm{eq}<0.15$ pc and mass surface density $\Sigma>0.08$ g cm$^{-2}$ could be possible high-mass starless cores. Further investigations toward these HMSCs would undoubtedly shed light on comprehensively understanding the birth of high-mass stars.Comment: 16 pages, 15 figures, and 5 tables. Accepted for publication in ApJS. FITS images for the far-IR to sub-mm data, H2 column density and dust temperature maps of all the HMSC candidates are available at https: //yuanjinghua.github.io/hmscs.html. Codes used for this work are publicly available from https://github.com/yuanjinghua/HMSCs_ca

Nonlinear statistical characteristics of the multi-directional waves with equivalent energy

Directional distribution is believed to have a significant impact on the statistical characteristics in multi-directional sea states. In real sea states, short-crested waves are discrete not only in frequency but also in direction. For the former one, they are well explained in unidirectional mode, but for the latter one, they are not. In this paper, the kurtosis of short-crested waves with equivalent energy is first discussed. Unimodal-spectrum-multi-direction sea states and bimodal-spectrum-multi-direction sea states are simulated for a long time in a numerical wave basin based on the high-order spectral method. In the equivalent sea-swell sea state, the spatial evolution of kurtosis becomes more inhomogeneous, along with the maximum value of kurtosis being larger and the area where the maximum value occurs wider in the configuration with a crossing angle β = 40° than that with β = 0°, while little variations in swell-dominated and wind-sea-dominated states. A positive linear correlation between wavelet group steepness and kurtosis is obtained in a unimodal sea state, but not applied to a crossing sea state characterized by a bimodal spectrum. The exceedance probability of wave height and wave crest distribution at maximum kurtosis is also given. These findings can help predict the probability of extreme waves occurring, guiding the selection of ocean engineering sites to avoid extreme configurations

S3: Social-network Simulation System with Large Language Model-Empowered Agents

Social network simulation plays a crucial role in addressing various challenges within social science. It offers extensive applications such as state prediction, phenomena explanation, and policy-making support, among others. In this work, we harness the formidable human-like capabilities exhibited by large language models (LLMs) in sensing, reasoning, and behaving, and utilize these qualities to construct the S$^3$ system (short for $\textbf{S}$ocial network $\textbf{S}$imulation $\textbf{S}$ystem). Adhering to the widely employed agent-based simulation paradigm, we employ prompt engineering and prompt tuning techniques to ensure that the agent's behavior closely emulates that of a genuine human within the social network. Specifically, we simulate three pivotal aspects: emotion, attitude, and interaction behaviors. By endowing the agent in the system with the ability to perceive the informational environment and emulate human actions, we observe the emergence of population-level phenomena, including the propagation of information, attitudes, and emotions. We conduct an evaluation encompassing two levels of simulation, employing real-world social network data. Encouragingly, the results demonstrate promising accuracy. This work represents an initial step in the realm of social network simulation empowered by LLM-based agents. We anticipate that our endeavors will serve as a source of inspiration for the development of simulation systems within, but not limited to, social science

Identification of novel proteins affected by rotenone in mitochondria of dopaminergic cells

Background: Many studies have shown that mitochondrial dysfunction, complex I inhibition in particular, is involved in the pathogenesis of Parkinson's disease (PD). Rotenone, a specific inhibitor of mitochondrial complex I, has been shown to produce neurodegeneration in rats as well as in many cellular models that closely resemble PD. However, the mechanisms through which complex I dysfunction might produce neurotoxicity are as yet unknown. A comprehensive analysis of the mitochondrial protein expression profile affected by rotenone can provide important insight into the role of mitochondrial dysfunction in PD. Results: Here, we present our findings using a recently developed proteomic technology called SILAC (stable isotope labeling by amino acids in cell culture) combined with polyacrylamide gel electrophoresis and liquid chromatography-tandem mass spectrometry to compare the mitochondrial protein profiles of MES cells (a dopaminergic cell line) exposed to rotenone versus control. We identified 1722 proteins, 950 of which are already designated as mitochondrial proteins based on database search. Among these 950 mitochondrial proteins, 110 displayed significant changes in relative abundance after rotenone treatment. Five of these selected proteins were further validated for their cellular location and/or treatment effect of rotenone. Among them, two were confirmed by confocal microscopy for mitochondrial localization and three were confirmed by Western blotting (WB) for their regulation by rotenone. Conclusion: Our findings represent the first report of these mitochondrial proteins affected by rotenone; further characterization of these proteins may shed more light on PD pathogenesis.The study is supported by NIH grants to JZ (R01AG025327 and R01ES012703)