Target Platform Research Articles

A novel multi-shot target platform for laser-driven laboratory astrophysics experiments

Abstract A new approach to target development for laboratory astrophysics experiments at high-power laser facilities is presented. With the dawn of high-power lasers, laboratory astrophysics has emerged as a field, bringing insight into physical processes in astrophysical objects, such as the formation of stars. An important factor for success in these experiments is targetry. To date, targets have mainly relied on expensive and challenging microfabrication methods. The design presented incorporates replaceable machined parts that assemble into a structure that defines the experimental geometry. This can make targets cheaper and faster to manufacture, while maintaining robustness and reproducibility. The platform is intended for experiments on plasma flows, but it is flexible and may be adapted to the constraints of other experimental setups. Examples of targets used in experimental campaigns are shown, including a design for insertion in a high magnetic field coil. Experimental results are included, demonstrating the performance of the targets.

Towards high-repetition rate petawatt laser experiments with cryogenic jets using a mechanical chopper system

Laser-plasma based ion accelerators require suitable high-repetition rate target systems that enable systematic studies at controlled plasma conditions and application-relevant particle flux. Self-refreshing, micrometer-sized cryogenic jets have proven to be an ideal target platform. Yet, operation of such systems in the harsh environmental conditions of high power laser induced plasma experiments have turned out to be challenging. Here we report on recent experiments deploying a cryogenic hydrogen jet as a source of pure proton beams generated with the PW-class ultrashort pulse laser DRACO. Damage to the jet target system during application of full energy laser shots was prevented by implementation of a mechanical chopper system interrupting the direct line of sight between the laser plasma interaction zone and the jet source.

AI 스마트 하우징 서비스 및 플랫폼 활성화를 위한 사업화 모델 수립에 관한 연구

In Korea, the demand for new housing services is increasing due to changes in the demographic structure, but in terms of activation, affordable and universal housing services are lacking. Therefore, in this study, the necessity of revitalizing the AI smart housing market was confirmed in terms of housing service activation, and through AI smart market analysis, various market participants tried to analyze the market access patterns in two factors: price and function. In addition, it was intended to present a commercialization model including price, target market, and service provided for the activation of AI smart housing.
 As a result of the study, although there is a difference in the level of functions, various industries in the front and rear are forming the market in terms of the implementation of AI smart housing. As a result of quantifying the functions of 16 similar/competitive markets and alternative markets based on a total of 11 functional levels, it was found that the lowest two functional levels had a maximum functional level of 7.5. In the case of AI smart housing service and platform, it was analyzed that a functional level of about 6.5-8 would be implemented. In the case of the price range, it was found that the distribution method of subscription was determined in the range of 0.11 to 6.49 million won/month. In the case of distribution by purchase, simple products start at about 20 million won, but when implemented with smart home appliances, the price is formed up to about 20 million won.
 Finally, seven types of commercialization models were established by comprehensively summarizing the target market and characteristics of the target market, price level, platform function, and core customer value (service). It was classified into entry-level, entry-level youth, entry-level elderly, high-end type, 1-2-person household type, high-end type, 3-4-person household type or more, high-end senior type, and high-end type. In the case of the entry-level type, it can be considered for application in terms of housing welfare, which has recently been attracting attention.

Effect of electroacupuncture on hippocampal synaptic plasticity and complement dependent memory impairment in Parkinson's disease dementia mice

To observe the effect of electroacupuncture (EA) of "Xiusanzhen" ［bilateral "Yingxiang"(LI20)+"Yintang"(GV24+)］ on synaptophysin (SYN), postsynaptic density protein-95 (PSD-95), Iba-1+ CD68+ microglia and complement C related protein expression of hippocampus in Parkinson's disease dementia (PDD) mice, so as to explore its mechanism in improving memory impairment of PDD. Male C57BL/6 mice were randomly divided into control, sham operation, model and EA groups, with 10 mice in each group. The PDD model was established by injecting 6-OHDA into the medial forebrain tract. EA (2 Hz, 1 mA) was applied to unilateral LI20 and GV29 for 20 min once daily for consecutive 14 days. Morris water maze and new object recognition test were used to evaluate the learning and memory ability. Western blot was used to detect the expression of SYN and PSD-95 proteins in hippocampus. Immunofluorescence was used to label Iba-1+ CD68+ microglia and C1q positive cells in hippocampal CA1 region. The content of C3 protein in hippocampus was detected by ELISA. Compared with the control group, there was no statistical significance in all the observed indexes in the sham operation group. Compared with the sham operation group, the average escape latency (AEL) prolonged significantly (P<0.01), the target platform crossing times (TPCT) and new object recognition index (NORI) decreased remarkably (P<0.01); the expressions of SYN and PSD-95 proteins in hippocampal CA1 region were significantly decreased (P<0.01); the rate of Iba-1+CD68+ microglia, the rate of C1q positive cells and the content of C3 protein were significantly increased (P<0.01) in the model group. In comparison with the model group, the AEL was shortened (P<0.01), the TPCT and NORI were increased (P<0.05) remarkably; the expressions of SYN and PSD-95 proteins in hippocampal CA1 region were increased (P<0.01, P<0.05); the rate of Iba-1+ CD68+ microglia, the rate of C1q positive cells and the content of C3 protein were significantly decreased (P<0.01) in the EA group. "Xiusanzhen" can alleviate the learning and memory impairment of PDD model mice, and improve the synaptic plasticity of hippocampal CA1 area. The mechanism may be related to the reduction of C1q and C3 deposition in hippocampal CA1 region and the reduction of microglia phagocytosis.

The role of regulation in facilitating new business models driven by digital platforms: creating regulatory ecosystems

ABSTRACT Digital platforms are facing a wave of regulatory activity in the UK and EU, primarily targeting their dominance, anti-competitive nature, and misconduct facilitated by their networks. Implementation of the new regulatory regimes is heavily reliant on the cooperation of the platforms themselves and use of their digital architecture, highlighting a potential weakness in the efficacy of the regulatory approach adopted. Though reference is made to the desire to deliver growth, innovation, and competition while minimising burdens on business, the prevalent regulatory tone is one of command and control with a punitive regulatory pitch targeting platforms’ financial interests. This paper presents the hypothesis that pitching towards the more practical motivations of regulatory targets, with a cooperative tone, will yield more successful and economically beneficial outcomes. A context-specific mix of regulatory modes combined with an understanding of the specific characteristics of digital platforms should be the foundation for regulation.

Systematic search for peptide and protein ligands of human serum albumin capable of affecting its interaction with amyloid β peptide

Background. Human serum albumin (HSA) is a natural buffer of amyloid-β peptide (Aβ), a key factor in the development of Alzheimer’s disease (AD). A promising approach to the AD prevention is to reduce the concentration of free Aβ by targeted stimulation of the interaction between HSA and Aβ. This approach can be implemented by increasing the affinity of HSA to Aβ through the action of HSA ligands, which was previously demonstrated for some low molecular weight ligands. The aim of the study was to search for peptide and protein ligands of human serum albumin capable of affecting its interaction with Aβ. Materials and methods. To perform a systematic search for peptides/proteins, HSA ligands that are capable of affecting Aβ-HSA interaction, we analyzed the DrugBank, BioGRID, and IntAct databases. As criteria for selecting candidates, along with physicochemical characteristics (molecular weight, solubility, blood-brain barrier passage, molar concentration), we used the requirements of extracellular proteins localization and strict association with AD, according to the DisGeNET and Open Targets Platform databases as well as Alzforum online resource. The algorithms for searching and analyzing the obtained data were implemented using the high-level programming language Python. Results. A candidate panel of 11 peptides and 34 proteins was formed. The most promising candidates include 4 peptides (liraglutide, exenatide, semaglutide, insulin detemir) and 4 proteins (S100A8, transferrin, C1 esterase inhibitor, cystatin C). Conclusions. Selected peptide and protein candidates are subject to experimental verification regarding their effect on the HSA-Aβ interaction and can become the basis for the development of first-in-class drugs for the prevention of Alzheimer’s disease.

Cross-platform sequential recommendation with sharing item-level relevance data

Cross-platform sequential recommendations are a typical solution to the problem of sparse data and cold starts in the field of recommendation systems. Specifically, we utilize data from the auxiliary platform to improve the recommendation performance of the target platform. One typical scenario is the fusion of data from two interaction platforms to perform cross-platform recommendation tasks. Existing approaches assume that interaction data from the auxiliary platform can fully share cross-platforms. However, such a hypothesis is unreasonable as, in the real world, different companies may operate these platforms. Records of user interactions with items are sensitive, and the complete sharing of original data could violate business privacy policies and increase the risk of privacy leaks. This paper considers a more realistic scenario for performing cross-platform sequential recommendations. To avoid compromising users’ privacy during data sharing, we contemplate sharing only item-level relevance data and not user-level relevance data. Concretely, we transfer item embedding cross-platform to make it easier for both companies to agree on data sharing (e.g., legal policies), as the data to share is irrelevant to the user and has no explicit semantics. For extracting a valuable signal from the transfer items embedding, we propose a new model, Neural Attention Transfer Sequential Recommendation (abbreviated as NATSR), by exploiting the powerful representation capabilities of neural networks. We perform thorough experiments with two real datasets to verify their performance. The NATSR model achieves the best recommendation performance compared to the traditional cross-platform approach of directly sharing user-level relevance data. We demonstrate further that the NATSR model dramatically mitigates the problem of data sparsity with significant user privacy-preserving.

The next-generation Open Targets Platform: reimagined, redesigned, rebuilt.

The Open Targets Platform (https://platform.opentargets.org/) is an open source resource to systematically assist drug target identification and prioritisation using publicly available data. Since our last update, we have reimagined, redesigned, and rebuilt the Platform in order to streamline data integration and harmonisation, expand the ways in which users can explore the data, and improve the user experience. The gene-disease causal evidence has been enhanced and expanded to better capture disease causality across rare, common, and somatic diseases. For target and drug annotations, we have incorporated new features that help assess target safety and tractability, including genetic constraint, PROTACtability assessments, and AlphaFold structure predictions. We have also introduced new machine learning applications for knowledge extraction from the published literature, clinical trial information, and drug labels. The new technologies and frameworks introduced since the last update will ease the introduction of new features and the creation of separate instances of the Platform adapted to user requirements. Our new Community forum, expanded training materials, and outreach programme support our users in a range of use cases.

Synthetic Platforms for Characterizing and Targeting of SARS-CoV-2 Genome Capping Enzymes.

Essential viral enzymes have been successfully targeted to combat the diseases caused by emerging pathogenic RNA viruses (e.g., viral RNA-dependent RNA polymerase). Because of the conserved nature of such viral enzymes, therapeutics targeting these enzymes have the potential to be repurposed to combat emerging diseases, e.g., remdesivir, which was initially developed as a potential Ebola treatment, then was repurposed for COVID-19. Our efforts described in this study target another essential and highly conserved, but relatively less explored, step in RNA virus translation and replication, i.e., capping of the viral RNA genome. The viral genome cap structure disguises the genome of most RNA viruses to resemble the mRNA cap structure of their host and is essential for viral translation, propagation, and immune evasion. Here, we developed a synthetic, phenotypic yeast-based complementation platform (YeRC0M) for molecular characterization and targeting of SARS-CoV-2 genome-encoded RNA cap-0 (guanine-N7)-methyltransferase (N7-MTase) enzyme (nsp14). In YeRC0M, the lack of yeast mRNA capping N7-MTase in yeast, which is an essential gene in yeast, is complemented by the expression of functional viral N7-MTase or its variants. Using YeRC0M, we first identified important protein domains and amino acid residues that are essential for SARS-CoV-2 nsp14 N7-MTase activity. We also expanded YeRC0M to include key nsp14 variants observed in emerging variants of SARS-CoV-2 (e.g., delta variant of SARS-CoV-2 encodes nsp14 A394V and nsp14 P46L). We also combined YeRC0M with directed evolution to identify attenuation mutations in SARS-CoV-2 nsp14. Because of the high sequence similarity of nsp14 in emerging coronaviruses, these observations could have implications on live attenuated vaccine development strategies. These data taken together reveal key domains in SARS-CoV-2 nsp14 that can be targeted for therapeutic strategies. We also anticipate that these readily tractable phenotypic platforms can also be used for the identification of inhibitors of viral RNA capping enzymes as antivirals.

Sleeve gastrectomy attenuated diabetes-related cognitive decline in diabetic rats.

To investigate the effects of sleeve gastrectomy (SG) on diabetes-related cognitive decline (DCD) in rats with diabetic mellitus (DM). Forty Wistar rats were randomly divided into control (CON) group (n=10), diabetes mellitus (DM) group (n=10), sham operation (SHAM) group (n=10) and SG group (n=10). DM model was established by high-fat diet (HFD) combined with intraperitoneal injection of streptozocin (STZ). Behavioral evaluation was given using Morris water maze test and Y-maze. In addition, PET-CT, TUNEL assay, histological analysis, transmission electron microscopy (TEM), immunohistochemistry (IHC) and Western blot analysis were used to evaluate the alleviating effects and potential mechanisms of SG on DCD in DM rats. Compared with the sham group, SG induced significant improvement in the metabolic indices such as blood glucose and body weight. Besides, it could attenuate the insulin resistance compared with SHAM group. In addition, SG could improve the cognitive function of DM rats, which were featured by significant decrease in the escape latency (P<0.05), and significant increase in the time in target quadrant and platform crossings (P<0.05) compared with the SHAM group. SG induced significant elevation in the spontaneous alternation compared with SHAM group (P<0.05). Moreover, SG could improve the arrangement and biosynthesis of hippocampus neuron. Moreover, SG triggered the inhibition of apoptosis of hippocampus neurons, and Western blot analysis showed SG induced significant increase in the ratios of Bcl-2/Bax and Caspase3/cleaved Caspase 3. TEM demonstrated SG could significantly improve the microstructure of hippocampus neurons compared with the SHAM group. Western blot and IHC confirmed the significant decrease in the phosphorylation of tau at Ser404 and Ser396 sites in the SG group. Furthermore, SG activated the PI3K signaling pathway by elevating the phosphorylation of PI3K and Akt and GSK3β compared with the SHAM group. SG attenuated the DCD in DM rats, which may be related to the activation of PI3K signaling pathway.

Prioritization of microRNA biomarkers for a prospective evaluation in a cohort of myocardial infarction patients based on their mechanistic role using public datasets.

MicroRNAs (miR) have proven to be promising biomarkers for several diseases due to their diverse functions, stability and tissue/organ-specific nature. Identification of new markers with high sensitivity and specificity will help in risk reduction in acute myocardial infarction (AMI) patients with chest pain and also prevent future adverse outcomes. Hence the aim of this study was to perform a detailed in silico analysis for identifying the mechanistic role of miRs involved in the pathogenesis/prognosis of AMI for prospective evaluation in AMI patients. miR profiling data was extracted from GSE148153 and GSE24591 datasets using the GEO2R gene expression omnibus repository and analyzed using limma algorithm. Differentially expressed miRs were obtained by comparing MI patients with corresponding controls after multiple testing corrections. Data mining for identifying candidate miRs from published literature was also performed. Target prediction and gene enrichment was done using standard bioinformatics tools. Disease specific analysis was performed to identify target genes specific for AMI using open targets platform. Protein-protein interaction and pathway analysis was done using STRING database and Cytoscape platform. The analysis revealed significant miRs like let-7b-5p, let-7c-5p, miR-4505, and miR-342-3p in important functions/pathways including phosphatidylinositol-3-kinase/AKT and the mammalian target of rapamycin, advanced glycation end products and its receptor and renin-angiotensin-aldosterone system by directly targeting angiotensin II receptor type 1, forkhead box protein O1, etc. With this approach we were able to prioritize the miR candidates for a prospective clinical association study in AMI patients of south Indian origin.

Ganglioside-Functionalized Nanoparticles for Chimeric Antigen Receptor T-Cell Activation at the Immunological Synapse.

Chimeric Antigen Receptor (CAR) T cell therapy has proven to be an effective strategy against hematological malignancies but persistence and activity against solid tumors must be further improved. One emerging strategy for enhancing efficacy is based on directing CAR T cells to antigen presenting cells (APCs). Activation of CAR T cells at the immunological synapse (IS) formed between APC and T cell is thought to promote strong, persistent antigen-specific T cell-mediated immune responses but requires integration of CAR ligands into the APC/T-cell interface. Here, we demonstrate that CAR ligand functionalized, lipid-coated, biodegradable polymer nanoparticles (NPs) that contain the ganglioside GM3 (GM3-NPs) bind to CD169 (Siglec-1)-expressing APCs and localize to the cell contact site between APCs and CAR T cells upon initiation of cell conjugates. The CD169+ APC/CAR T-cell interface is characterized by a strong optical colocalization of GM3-NPs and CARs, enrichment of F-actin, and recruitment of ZAP-70, indicative of integration of GM3-NPs into a functional IS. Ligands associated with GM3-NPs localized to the APC/T-cell contact site remain accessible to CARs and result in robust T-cell activation. Overall, this work identifies GM3-NPs as a potential antigen delivery platform for active targeting of CD169 expressing APCs and enhancement of CAR T-cell activation at the NP-containing IS.

Hyaluronic Acid-Protein Conjugate Modified Iron-Based MOFs (MIL-101 (Fe)) for Efficient Therapy of Neuroblastoma: Molecular Simulation, Stability and Toxicity Studies

Iron-based metal-organic frameworks (MIL (101)) have recently gained attention in materials science for biomedical applications. In the present work, Iron-based MOF (MIL-101(Fe)) were coated with lactoferrin (Lf) conjugated with hyaluronic acid (HA) and investigated its potential for delivering 5-fluorouracil (5-FU), along with assessing the toxicity profile. The synthesised nanoparticles were extensively characterised using spectroscopic, X-Ray, thermal and electron microscopic techniques. 5-FU was loaded into MOFs, and the drug-loading efficiency and drug release pattern were studied, along with stability testing in pH and serum protein. The toxicity of MIL-101(Fe) was assessed using both in vitro and in vivo techniques such as the haemolysis assay, cell viability assay and acute and subacute toxicity studies in animals. In silico molecular simulation was done to assess the Lf and Tf interaction. The molecular interaction of Lf with Transferrin (Tf) showed strong molecular interaction and negligible fluctuation in the RMSD (root mean square deviation) values. The MOFs were stable and demonstrated sustained drug release patterns. The in vitro cell studies demonstrated biocompatibility and enhanced cellular internalisation of MOFs. The in vivo toxicity studies supported the in vitro results. The synthesised MOFs demonstrated potential as a targeted delivery platform for cancer targeting.

Optimize Image Processing Algorithm on ARM Cortex-A72 and A53

This work presents a technique to optimize processing image algorithms. The increasing demand for video applications like context-aware computing on mobile embedded systems requires the use of computationally intensive image processing algorithms. The system engineer has the mandate to optimize them so as to meet real-time deadlines. A methodology to take advantage of the asymmetric dual-core processor, which includes an ARM supported by shared memory, is presented with implementation details. The target platform chosen is the NanoPi M4V2. It has a dual-core and quad-core architecture with an ARM Cortex-A72 and Cortex-A53. The basic image correlation algorithm is chosen for benchmarking as it finds widespread application for various template-matching tasks such as face recognition. The basic algorithm prototypes conform to OpenCV, a popular computer vision library. OpenCV algorithms can be easily ported to the ARM core, which runs a popular operating system such as Linux. The algorithms are tested on a variety of images, and performance results are presented, measuring the speedup obtained due to dual-core and quad-core implementation. A major advantage of this approach is that it allows the ARM processor to perform important real-time tasks.

Insights Gained from RNA Editing Targeted by the CRISPR-Cas13 Family.

Clustered regularly interspaced short palindromic repeat (CRISPR)/CRISPR-associated protein (Cas) systems, especially type II (Cas9) systems, have been widely developed for DNA targeting and formed a set of mature precision gene-editing systems. However, the basic research and application of the CRISPR-Cas system in RNA is still in its early stages. Recently, the discovery of the CRISPR-Cas13 type VI system has provided the possibility for the expansion of RNA targeting technology, which has broad application prospects. Most type VI Cas13 effectors have dinuclease activity that catalyzes pre-crRNA into mature crRNA and produces strong RNA cleavage activity. Cas13 can specifically recognize targeted RNA fragments to activate the Cas13/crRNA complex for collateral cleavage activity. To date, the Cas13X protein is the smallest effector of the Cas13 family, with 775 amino acids, which is a promising platform for RNA targeting due to its lack of protospacer flanking sequence (PFS) restrictions, ease of packaging, and absence of permanent damage. This study highlighted the latest progress in RNA editing targeted by the CRISPR-Cas13 family, and discussed the application of Cas13 in basic research, nucleic acid diagnosis, nucleic acid tracking, and genetic disease treatment. Furthermore, we clarified the structure of the Cas13 protein family and their molecular mechanism, and proposed a future vision of RNA editing targeted by the CRISPR-Cas13 family.

An empirical evaluation of a novel domain-specific language – modelling vehicle routing problems with Athos

Domain-specific languages (DSLs) are a popular approach among software engineers who demand for a tailored development interface. A DSL-based approach allows to encapsulate the intricacies of the target platform in transformations that turn DSL models into executable software code. Often, DSLs are even claimed to reduce development complexity to a level that allows them to be successfully applied by domain-experts with limited programming knowledge. Recent research has produced some scientifically backed insights on the benefits and limitations of DSLs. Further empirical studies are required to build a sufficient body of knowledge from which support for different claims related to DSLs can be derived. In this research study, we adopt current DSL evaluation approaches to investigate potential gains in terms of effectiveness and efficiency, through the application of our DSL Athos, a language developed for the domain of traffic and transportation simulation and optimisation. We compare Athos to the alternative of using an application library defined within a general-purpose language (GPL). We specified two sets of structurally identical tasks from the domain of vehicle routing problems and asked study groups with differing levels of programming knowledge to solve the tasks with the two approaches. The results show that inexperienced participants achieved considerable gains in effectiveness and efficiency with the usage of Athos DSL. Though hinting at Athos being the more efficient approach, the results were less distinct for more experienced programmers. The vast majority of participants stated to prefer working with Athos over the usage of the presented GPL’s API.

Metallated phthalocyanines and their hydrophilic derivatives for multi-targeted oncological photodynamic therapy.

A photosensitizer (PS) delivery and comprehensive tumor targeting platform was developed that is centered on the photosensitization of key pharmacological targets in solid tumors (cancer cells, tumor vascular endothelium, and cellular and non-cellular components of the tumor microenvironment) before photodynamic therapy (PDT). Interstitially targeted liposomes (ITLs) encapsulating zinc phthalocyanine (ZnPC) and aluminum phthalocyanine (AlPC) were formulated for passive targeting of the tumor microenvironment. In previous work it was established that the PEGylated ITLs were taken up by cultured cholangiocarcinoma cells. The aim of this study was to verify previous results in cancer cells and to determine whether the ITLs can also be used to photosensitize cells in the tumor microenvironment and vasculature. Following positive results, rudimentary in vitro and in vivo experiments were performed with ZnPC-ITLs and AlPC-ITLs as well as their water-soluble tetrasulfonated derivatives (ZnPCS4 and AlPCS4) to assemble a research dossier and bring this platform closer to clinical transition. Flow cytometry and confocal microscopy were employed to determine ITL uptake and PS distribution in cholangiocarcinoma (SK-ChA-1) cells, endothelial cells (HUVECs), fibroblasts (NIH-3T3), and macrophages (RAW 264.7). Uptake of ITLs by endothelial cells was verified under flow conditions in a flow chamber. Dark toxicity and PDT efficacy were determined by cell viability assays, while the mode of cell death and cell cycle arrest were assayed by flow cytometry. In vivo systemic toxicity was assessed in zebrafish and chicken embryos, whereas skin phototoxicity was determined in BALB/c nude mice. A PDT efficacy pilot was conducted in BALB/c nude mice bearing human triple-negative breast cancer (MDA-MB-231) xenografts. The key findings were that (1) photodynamically active PSs (i.e., all except ZnPCS4) were able to effectively photosensitize cancer cells and non-cancerous cells; (2) following PDT, photodynamically active PSs were highly toxic-to-potent as per anti-cancer compound classification; (3) the photodynamically active PSs did not elicit notable systemic toxicity in zebrafish and chicken embryos; (4) ITL-delivered ZnPC and ZnPCS4 were associated with skin phototoxicity, while the aluminum-containing PSs did not exert detectable skin phototoxicity; and (5) ITL-delivered ZnPC and AlPC were equally effective in their tumor-killing capacity in human tumor breast cancer xenografts and superior to other non-phthalocyanine PSs when appraised on a per mole administered dose basis. AlPC(S4) are the safest and most effective PSs to integrate into the comprehensive tumor targeting and PS delivery platform. Pending further in vivo validation, these third-generation PSs may be used for multi-compartmental tumor photosensitization.

Implementation of EPLL-Based Control Algorithms using Low-Cost Target Platforms for Synchronization in Electrified Transportation Systems

Implementation of EPLL-Based Control Algorithms using Low-Cost Target Platforms for Synchronization in Electrified Transportation Systems

Landing a quadrotor UAV on a moving platform with sway motion using robust control

Autonomous landing of quadrotor unmanned aerial vehicles (UAVs) is a critical and challenging issue, especially on a moving target under complex terrain. This paper proposes a practicable solution that consists of a reference trajectory and a robust control strategy. More specifically, a continuous reference trajectory is planned to ensure the safety, where a feasible landing constraint is provided by introducing the sway motion of the target platform. Then, a robust hierarchical control strategy that exploits a saturated force controller and an attitude constraint torque controller is developed, where a dynamics estimator is employed to counteract the uncertain dynamics. Stability analysis indicates that the overall closed-loop system is uniformly ultimately bounded. Since the global positioning system (GPS) fails to provide an acceptable measurement for the precise landing, an ultra-wide band (UWB) positioning system is designed which possesses a 20-centimeter level of accuracy. To simulate a realistic scenario over the rough ground or sea condition, a motion platform with sway motion is utilized in the experiment facility. Flight experiments are performed to validate and assess the proposed strategy.

Ion channel molecular complexes in vascular smooth muscle.

Ion channels that influence membrane potential and intracellular calcium concentration control vascular smooth muscle excitability. Voltage-gated calcium channels (VGCC), transient receptor potential (TRP) channels, voltage (KV), and Ca2+-activated K+ (BK) channels are key regulators of vascular smooth muscle excitability and contractility. These channels are regulated by various signaling cues, including protein kinases and phosphatases. The effects of these ubiquitous signaling molecules often depend on the formation of macromolecular complexes that provide a platform for targeting and compartmentalizing signaling events to specific substrates. This manuscript summarizes our current understanding of specific molecular complexes involving VGCC, TRP, and KV and BK channels and their contribution to regulating vascular physiology.