ECM and SAGE based joint estimation of timing and frequency offset for DMIMO–OFDM system

Distributed multiple-input multiple-output (DMIMO) technology is a key enabler of coverage extension and enhancement of link reliability in wireless networks through distributed spatial diversity. DMIMO employs classic relay channels in between the source and the destination to opportunistically form a virtual antenna array (VAA) for emulating cooperative diversity. Use of multiple antennas at the relays further increases capacity and reliability of the relay–destination channel through multiplexing and diversity of MIMO antennas respectively. In such network, the signal received at the destination is characterized by multiple timing offsets (MTO) due to different propagation delay and multiple carrier frequency offsets (MCFO) due to independent oscillators of the relays. Hence, synchronization becomes a crucial issue in DMIMO in order to realize the distributed coherence. In this paper, we address joint estimation of MCFO and MTO in DMIMO orthogonal frequency division multiplexing (OFDM) with MIMO configuration at the relays for estimate-and-forward (EF) relaying protocol. Two iterative algorithms, based on expectation conditional maximization (ECM) and space alternating generalized expectation–maximization (SAGE) are proposed for joint estimation in presence of inter carrier interference (ICI). The robustness of both the estimators to ICI is evaluated by mathematical analysis and supported by extensive simulations. The performance of the proposed estimators is assessed in terms of mean square error (MSE) and bit error rate (BER). The theoretical Cramer–Rao lower bound (CRLB) of estimator error variance is also derived.     

Enzyme‐Induced Matrix Softening Regulates Hepatocarcinoma Cancer Cell Phenotypes

The progression of cancer is often accompanied by changes in the mechanical properties of an extracellular matrix. However, limited efforts have been made to reproduce these biological events in vitro. To this end, this study demonstrates that matrix remodeling caused by matrix metalloproteinase (MMP)‐1 regulates phenotypic activities and modulates radiosensitivity of cancer cells exclusively in a 3D matrix. In this study, hepatocarcinoma cells are cultured in a collagen‐based gel tailored to present an elastic modulus of ≈4.0 kPa. The subsequent exposure of the gel to MMP‐1 decreases the elastic modulus from 4.0 to 0.5 kPa. In response to MMP‐1, liver cancer cells undergo active proliferation, downregulation of E‐cadherin, and the loss of detoxification capacity. The resulting spheroids are more sensitive to radiation than the spheroids cultured in the stiffer gel not exposed to MMP‐1. Overall, this study serves to better understand and control the effects of MMP‐induced matrix remodeling.     

Open tubular capillary electrochromatography: A useful microreactor for collagen I glycation and interaction studies with low-density lipoprotein particles

Diabetes, a multifunctional disease and a major cause of morbidity and mortality in the industrialized countries, strongly associates with the development and progression of atherosclerosis. One of the consequences of high level of glucose in the blood circulation is glycation of long-lived proteins, such as collagen I, the most abundant component of the extracellular matrix (ECM) in the arterial wall. Glycation is a long-lasting process that involves the reaction between a carbonyl group of the sugar and an amino group of the protein, usually a lysine residue. This reaction generates an Amadori product that may evolve in advanced glycation end products (AGEs). AGEs, as reactive molecules, can provoke cross-linking of collagen I fibrils. Since binding of low-density lipoproteins (LDLs) to the ECM of the inner layer of the arterial wall, the intima, has been implicated to be involved in the onset of the development of an atherosclerotic plaque, collagen modifications, which can affect the affinity of native and oxidized LDL for collagen I, can promote the entrapment of LDLs in the intima and accelerate the progression of atherosclerosis.In this study, open tubular capillary electrochromatography is proposed as a new microreactor to study in situ glycation of collagen I. The kinetics of glycation was first investigated in a fused silica collagen I-coated capillary. Dimethyl sulphoxide, injected as an electroosmotic flow marker, gave information about the charge of coating. Native and oxidized LDL, and selected peptide fragments from apolipoprotein B-100, the protein covering LDL particles, were injected as marker compounds to clarify the interactions between LDLs and the glycated collagen I coating. The method proposed is simple and inexpensive, since only small amounts of collagen and LDL are required. Atomic force microscopy images complemented our studies, highlighting the difference between unmodified and glycated collagen I surfaces.     

时间序列模型的动态计量分析方法在科研投入效果评价中的应用

运用时间序列模型的动态计量方法对科研投入的效果进行分析.以GDP作为检验科研投入效果的经济指标,对1980-2001年我国科研投入对经济增长的贡献作用进行实证分析,构建了科研投入与GDP的自回归分布滞后(ADL)模型,以此为起点并结合平稳性检验和协整检验建立了动态计量经济学模型的一般形式即误差修正模型(ECM),该模型刻画了科研投入与经济增长二者之间长期稳定的均衡关系.     

The nonlinear theory of slow-wave electron cyclotron masers with inclusion of the beam velocity spread

The nonlinear theory of slow-wave electron cyclotron masers (ECM) with an initially straight electron beam is developed. The evolution equation of the nonlinear beam electron energy is derived. The numerical studies of the slow-wave ECM efficiency with inclusion of Gaussian beam velocity spread are presented. It is shown that the velocity spread reduces the interaction efficiency.     

Analysis of a new multispecies tumor growth model coupling 3D phase-fields with a 1D vascular network

In this work, we present and analyze a mathematical model for tumor growth incorporating ECM erosion, interstitial flow, and the effect of vascular flow and nutrient transport. The model is of phase-field or diffused-interface type in which multiple phases of cell species and other constituents are separated by smooth evolving interfaces. The model involves a mesoscale version of Darcy’s law to capture the flow mechanism in the tissue matrix. Modeling flow and transport processes in the vasculature supplying the healthy and cancerous tissue, one-dimensional (1D) equations are considered. Since the models governing the transport and flow processes are defined together with cell species models on a three-dimensional (3D) domain, we obtain a 3D–1D coupled model.     

Development of an enzyme-linked immunosorbent assay (ELISA)-like fluorescence assay to investigate the interactions of glycosaminoglycans to cells

Sulfated glycosaminoglycans were labeled with biotin to study their interaction with cells in culture. Thus, heparin, heparan sulfate, chondroitin 4-sulfate, chondroitin 6-sulfate and dermatan sulfate were labeled using biotin-hydrazide, under different conditions. The structural characteristics of the biotinylated products were determined by chemical (molar ratios of hexosamine, uronic acid, sulfate and biotin) and enzymatic methods (susceptibility to degradation by chondroitinases and heparitinases). The binding of biotinylated glycosaminoglycans was investigated both in endothelial and smooth muscle cells in culture, using a novel time resolved fluorometric method based on interaction of europium-labeled streptavidin with the biotin covalently linked to the compounds. The interactions of glycosaminoglycans were saturable and number of binding sites could be obtained for each individual compound. The apparent dissociation constant varied among the different glycosaminoglycans and between the two cell lines. The interactions of the biotinylated glycosaminoglycans with the cells were also evaluated using confocal microscopy. We propose a convenient and reliable method for the preparation of biotinylated glycosaminoglycans, as well as a sensitive non-competitive fluorescence-based assay for studies of the interactions and binding of these compounds to cells in culture.     

Engineering Biomimetic Microenvironment for Organoid

Organoid is an emerging frontier technology in the field of life science, in which pluripotent stem cells or tissue-derived differentiated/progenitor cells form 3D structures according to their multi-directional differentiation potential and self-assembly ability. Nowadays, although various types of organoids are widely investigated, their construction is still complicated in operation, uncertain in yield, and poor in reproducibility for the structure and function of native organs. Constructing a biomimetic microenvironment for stem cell proliferation and differentiation in vitro is recognized as a key to driving this field. This review reviews the recent development of engineered biomimetic microenvironments for organoids. First, the composition of the matrix for organoid culture is summarized. Then, strategies for engineering the microenvironment from biophysical, biochemical, and cellular perspectives are discussed in detail. Subsequently, the newly developed monitoring technologies are also reviewed. Finally, a brief conclusion and outlook are presented for the inspiration of future research.     

Clustering Multivariate Longitudinal Observations: The Contaminated Gaussian Hidden Markov Model

The Gaussian hidden Markov model (HMM) is widely considered for the analysis of heterogenous continuous multivariate longitudinal data. To robustify this approach with respect to possible elliptical heavy-tailed departures from normality, due to the presence of outliers, spurious points, or noise (collectively referred to as bad points herein), the contaminated Gaussian HMM is here introduced. The contaminated Gaussian distribution represents an elliptical generalization of the Gaussian distribution and allows for automatic detection of bad points in the same natural way as observations are typically assigned to the latent states in the HMM context. Once the model is fitted, each observation has a posterior probability of belonging to a particular state and, inside each state, of being a bad point or not. In addition to the parameters of the classical Gaussian HMM, for each state we have two more parameters, both with a specific and useful interpretation: one controls the proportion of bad points and one specifies their degree of atypicality. A sufficient condition for the identifiability of the model is given, an expectation-conditional maximization algorithm is outlined for parameter estimation and various operational issues are discussed. Using a large-scale simulation study, but also an illustrative artificial dataset, we demonstrate the effectiveness of the proposed model in comparison with HMMs of different elliptical distributions, and we also evaluate the performance of some well-known information criteria in selecting the true number of latent states. The model is finally used to fit data on criminal activities in Italian provinces. Supplementary materials for this article are available online     

Protein‐Affinitive Polydopamine Nanoparticles as an Efficient Surface Modification Strategy for Versatile Porous Scaffolds Enhancing Tissue Regeneration

Porous scaffolds for tissue regeneration are often functionalized with extracellular matrix proteins to enhance surface/cell interactions and tissue regeneration. However, continuous coatings produced by commonly used surface modification strategies may preclude cells from contacting and sensing the chemical and physical cues of the scaffold. Here, it is shown that polydopamine nanoparticles (PDA‐NPs) tightly adhere on various scaffolds to form nanostructures, and the coverage can be finely tuned. Furthermore, the PDA‐NPs have good affinity to a variety of proteins and peptides. Thus, the PDA‐NPs act as an anchor to immobilize signal biomolecules on scaffolds, and consequently promote cell activity and tissue regeneration. β‐Tricalcium phosphate (TCP) scaffolds decorated with PDA‐NPs demonstrate excellent osteoinductivity and bone‐regeneration performance due to the protein affinity of PDA‐NPs and the intrinsic bioactive characteristics of TCP scaffolds. In summary, PDA‐NPs with excellent affinity for protein adhesion represent a versatile platform to modify porous scaffolds while not compromising the biological functions of the scaffolds, and might have potential applications in tissue regeneration.