Substructure and Boundary Modeling for Continuous Action Recognition

This paper introduces a probabilistic graphical model for continuous action recognition with two novel components: substructure transition model and discriminative boundary model. The first component encodes the sparse and global temporal transition prior between action primitives in state-space model to handle the large spatial-temporal variations within an action class. The second component enforces the action duration constraint in a discriminative way to locate the transition boundaries between actions more accurately. The two components are integrated into a unified graphical structure to enable effective training and inference. Our comprehensive experimental results on both public and in-house datasets show that, with the capability to incorporate additional information that had not been explicitly or efficiently modeled by previous methods, our proposed algorithm achieved significantly improved performance for continuous action recognition.Comment: Detailed version of the CVPR 2012 paper. 15 pages, 6 figure

Estimation Diversity and Energy Efficiency in Distributed Sensing

Distributed estimation based on measurements from multiple wireless sensors is investigated. It is assumed that a group of sensors observe the same quantity in independent additive observation noises with possibly different variances. The observations are transmitted using amplify-and-forward (analog) transmissions over non-ideal fading wireless channels from the sensors to a fusion center, where they are combined to generate an estimate of the observed quantity. Assuming that the Best Linear Unbiased Estimator (BLUE) is used by the fusion center, the equal-power transmission strategy is first discussed, where the system performance is analyzed by introducing the concept of estimation outage and estimation diversity, and it is shown that there is an achievable diversity gain on the order of the number of sensors. The optimal power allocation strategies are then considered for two cases: minimum distortion under power constraints; and minimum power under distortion constraints. In the first case, it is shown that by turning off bad sensors, i.e., sensors with bad channels and bad observation quality, adaptive power gain can be achieved without sacrificing diversity gain. Here, the adaptive power gain is similar to the array gain achieved in Multiple-Input Single-Output (MISO) multi-antenna systems when channel conditions are known to the transmitter. In the second case, the sum power is minimized under zero-outage estimation distortion constraint, and some related energy efficiency issues in sensor networks are discussed.Comment: To appear at IEEE Transactions on Signal Processin

Energy-Efficient Joint Estimation in Sensor Networks: Analog vs. Digital

Sensor networks in which energy is a limited resource so that energy consumption must be minimized for the intended application are considered. In this context, an energy-efficient method for the joint estimation of an unknown analog source under a given distortion constraint is proposed. The approach is purely analog, in which each sensor simply amplifies and forwards the noise-corrupted analog bservation to the fusion center for joint estimation. The total transmission power across all the sensor nodes is minimized while satisfying a distortion requirement on the joint estimate. The energy efficiency of this analog approach is compared with previously proposed digital approaches with and without coding. It is shown in our simulation that the analog approach is more energy-efficient than the digital system without coding, and in some cases outperforms the digital system with optimal coding.Comment: To appear in Proceedings of the 2005 IEEE International Conference on Acoustics, Speech and Signal Processing, Philadelphia, PA, March 19 - 23, 200

DNA Self-Assembly of Targeted Near-Infrared-Responsive Gold Nanoparticles for Cancer Thermo-Chemotherapy

Targeted Cancer Therapy: Inspired by the ability of DNA hybridization, a targeted near-infrared (NIR) light-responsive delivery system has been developed through simple DNA self-assembly (PEG=polyethylene glycol). This DNA-based platform shows the ability of releasing therapeutics upon near-infrared irradiation, and remarkable targeted thermo- and chemotherapeutic efficacy in vitro and in vivo

Overcoming DoF Limitation in Robust Beamforming: A Penalized Inequality-Constrained Approach

A well-known challenge in beamforming is how to optimally utilize the degrees of freedom (DoF) of the array to design a robust beamformer, especially when the array DoF is smaller than the number of sources in the environment. In this paper, we leverage the tool of constrained convex optimization and propose a penalized inequality-constrained minimum variance (P-ICMV) beamformer to address this challenge. Specifically, we propose a beamformer with a well-targeted objective function and inequality constraints to achieve the design goals. The constraints on interferences penalize the maximum gain of the beamformer at any interfering directions. This can efficiently mitigate the total interference power regardless of whether the number of interfering sources is less than the array DoF or not. Multiple robust constraints on the target protection and interference suppression can be introduced to increase the robustness of the beamformer against steering vector mismatch. By integrating the noise reduction, interference suppression, and target protection, the proposed formulation can efficiently obtain a robust beamformer design while optimally trade off various design goals. When the array DoF is fewer than the number of interferences, the proposed formulation can effectively align the limited DoF to all of the sources to obtain the best overall interference suppression. $\$To numerically solve this problem, we formulate the P-ICMV beamformer design as a convex second-order cone program (SOCP) and propose a low complexity iterative algorithm based on the alternating direction method of multipliers (ADMM). Three applications are simulated to demonstrate the effectiveness of the proposed beamformer.Comment: submitted to IEEE Transactions on Signal Processin

Bypass transition in a boundary layer flow induced by plasma actuators

Bypass transition in ow over a at plate triggered by a pair of Dielectric-barrier-discharge (DBD) plasma actuators mounted on the plate surface and aligned in the streamwise direction is investigated. A 4-species plasma-uid model is used to model the electrohydrodynamic (EHD) force generated by the plasma actuation. A pair of counter-rotating streamwise vortices is created downstream of the actuators, leading to the formation of a high-speed streak in the centre and two low-speed streaks on each side. As the length of actuators increases, more momentum is added to the boundary layer and eventually a turbulent wedge is generated at an almost fixed location. With large spanwise distance between the actuators (wide layout), direct numerical simulations (DNS) indicate that the low-speed streaks on both sides lose secondary stability via an inclined varicose-like mode simultaneously, leaving a symmetric perturbation pattern with respect to the centre of the actuators. Further downstream, the perturbations are tilted by the mean shear of the high- and low-speed streaks and consequently a `W' shape pattern is observed. When the pair of plasma actuators is placed closer (narrow layout) in the spanwise direction, the mean shear in the centre becomes stronger and secondary instability first occurs on the high-speed streak with an asymmetric pattern. Inclined varicose-like and sinuous-like instabilities coexist in the following breakdown of the negative streaks on the side and the perturbations remain asymmetric with respect to the centre. Here the tilting of disturbances is dominated by the mean shear in the centre and the perturbations display a `V' shape. Linear analysis techniques including biglobal stability and transient growth are performed to further examine the uid physics and the aforementioned phenomena at narrow and wide layouts, such as the secondary instabilities, `V' and `W' shapes, the symmetric and asymmetric breakdown, are all observed

Nanodelivery of nucleic acids

Funding: This work was supported by the European Research Council (ERC) Starting Grant (ERC-StG-2019-848325 to J. Conde) and the Fundação para a Ciência e a Tecnologia FCT Grant (PTDC/BTM-MAT/4738/2020 to J. Conde). J.S. acknowledges US National Institute of Health (NIH) grants (R01CA200900, R01HL156362 and R01HL159012), the US DoD PRCRP Idea Award with Special Focus (W81XWH1910482), the Lung Cancer Discovery Award from the American Lung Association and the Innovation Discovery Grants award from the Mass General Brigham. H.L., D.Y. and X.Z. were supported by the National Key R&D Program of China (no. 2020YFA0710700), the National Natural Science Foundation of China (nos 21991132, 52003264, 52021002 and 52033010) and the Fundamental Research Funds for the Central Universities (no. WK2060000027).There is growing need for a safe, efficient, specific and non-pathogenic means for delivery of gene therapy materials. Nanomaterials for nucleic acid delivery offer an unprecedented opportunity to overcome these drawbacks; owing to their tunability with diverse physico-chemical properties, they can readily be functionalized with any type of biomolecules/moieties for selective targeting. Nucleic acid therapeutics such as antisense DNA, mRNA, small interfering RNA (siRNA) or microRNA (miRNA) have been widely explored to modulate DNA or RNA expression Strikingly, gene therapies combined with nanoscale delivery systems have broadened the therapeutic and biomedical applications of these molecules, such as bioanalysis, gene silencing, protein replacement and vaccines. Here, we overview how to design smart nucleic acid delivery methods, which provide functionality and efficacy in the layout of molecular diagnostics and therapeutic systems. It is crucial to outline some of the general design considerations of nucleic acid delivery nanoparticles, their extraordinary properties and the structure–function relationships of these nanomaterials with biological systems and diseased cells and tissues.publishersversionpublishe

KARR-seq reveals cellular higher-order RNA structures and RNA–RNA interactions

RNA fate and function are affected by their structures and interactomes. However, how RNA and RNA-binding proteins (RBPs) assemble into higher-order structures and how RNA molecules may interact with each other to facilitate functions remain largely unknown. Here we present KARR-seq, which uses N3-kethoxal labeling and multifunctional chemical crosslinkers to covalently trap and determine RNA–RNA interactions and higher-order RNA structures inside cells, independent of local protein binding to RNA. KARR-seq depicts higher-order RNA structure and detects widespread intermolecular RNA–RNA interactions with high sensitivity and accuracy. Using KARR-seq, we show that translation represses mRNA compaction under native and stress conditions. We determined the higher-order RNA structures of respiratory syncytial virus (RSV) and vesicular stomatitis virus (VSV) and identified RNA–RNA interactions between the viruses and the host RNAs that potentially regulate viral replication

Prognostic and therapeutic significance of microbial cell-free DNA in plasma of people with acutely decompensated cirrhosis

BACKGROUND AND AIMS: Although the effect of bacterial infection on cirrhosis has been well-described, the effect of non-hepatotropic virus (NHV) infection is unknown. This study evaluated the genome fragments of circulating microorganisms using metagenomic next-generation sequencing (mNGS) in cirrhosis patients with acute decompensation (AD), focusing on NHVs and related the findings to clinical outcomes. METHODS: Plasma mNGS was performed in 129 cirrhosis patients with AD in study cohort. Ten healthy volunteers and 20, 39, and 81 patients with stable cirrhosis, severe sepsis and hematological malignancies, respectively, were enrolled as controls. Validation assays for human cytomegalovirus (CMV) reactivation in a validation cohort (n = 58) were performed and exploratory treatment instituted. RESULTS: In study cohort, 188 microorganisms were detected in 74.4% (96/129) patients, including viruses (58.0%), bacteria (34.1%), fungi (7.4%) and chlamydia (0.5%). Patients with AD had an NHV signature, and CMV was the most frequent NHV, which correlated with the clinical effect of empirical antibiotic treatment, progression to acute-on-chronic liver failure (ACLF), and 90-day mortality. The NHV signature in ACLF patients was similar to patients with sepsis and hematological malignancies. The treatable NHV, CMV was detected in 24.1% (14/58) patients in the validation cohort. Of the 14 cases with detectable CMV by mNGS, 9 were further validated by DNA RT-PCR or pp65 antigenemia testing. Three patients with CMV reactivation received ganciclovir therapy in exploratory manner with clinical resolutions. CONCLUSIONS: The results of this study suggests that NHVs may have a pathogenic role in complicating the course of AD. Further validation is needed to define whether this should be incorporated in the routine management of AD patients. IMPACT AND IMPLICATIONS: ●Cirrhosis patients with acute decompensation have a non-hepatotropic virus (NHV) signature, which is similar to that in sepsis and hematological malignancies patients. ●The detected viral signature had clinical correlates, including clinical efficacy of empirical antibiotic treatment, progression to acute-on-chronic liver failure and short-term mortality. ●The treatable NHV, CMV reactivation may be involved in the clinical outcomes of decompensated cirrhosis. ●Routine screening for NHVs, especially CMV, may be useful for the management of patients with acutely decompensated cirrhosis

Development of Multinuclear Polymeric Nanoparticles as Robust Protein Nanocarriers

One limitation of current biodegradable polymeric nanoparticles is their inability to effectively encapsulate and sustainably release proteins while maintaining protein bioactivity. Here we report the engineering of a PLGA-polycation nanoparticle platform with core-shell structure as a robust vector for the encapsulation and delivery of proteins and peptides. We demonstrate that the optimized nanoparticles can load high amounts of proteins (>20% of nanoparticles by weight) in aqueous solution by simple mixing via electrostatic interactions without organic solvents, forming nanospheres in seconds with diameter <200 nm. We also investigate the relationship between nanosphere size, surface charge, PLGA-polycation composition, and protein loading. The stable nanosphere complexes contain multiple PLGA-polycation nanoparticles, surrounded by large amounts of protein. This study highlights a novel nanoparticle platform and nanotechnology strategy for the delivery of proteins and other relevant molecules