Current pharmaceutical research and development (R&D) is a high-risk investment which is usually faced with some unexpected even disastrous failures in different stages of drug discovery. One main ...reason for R&D failures is the efficacy and safety deficiencies which are related largely to absorption, distribution, metabolism and excretion (ADME) properties and various toxicities (T). Therefore, rapid ADMET evaluation is urgently needed to minimize failures in the drug discovery process. Here, we developed a web-based platform called ADMETlab for systematic ADMET evaluation of chemicals based on a comprehensively collected ADMET database consisting of 288,967 entries. Four function modules in the platform enable users to conveniently perform six types of drug-likeness analysis (five rules and one prediction model), 31 ADMET endpoints prediction (basic property: 3, absorption: 6, distribution: 3, metabolism: 10, elimination: 2, toxicity: 7), systematic evaluation and database/similarity searching. We believe that this web platform will hopefully facilitate the drug discovery process by enabling early drug-likeness evaluation, rapid ADMET virtual screening or filtering and prioritization of chemical structures. The ADMETlab web platform is designed based on the Django framework in Python, and is freely accessible at
http://admet.scbdd.com/
.
In this brief, a novel direct adaptive fuzzy tracking control (DAFTC) scheme for marine vehicles with fully unknown parametric dynamics and uncertainties is proposed. The significant contributions of ...the DAFTC approach are as follows. First, in the backstepping framework, fully unknown parametric dynamics and uncertainties are encapsulated into a lumped nonlinearity function encompassing system states and virtual control signals. Second, the integrated nonlinearity function is further identified online by an adaptive fuzzy approximator that synthesizes a model-free control scheme (termed DAFTC) without requiring any a priori knowledge of the model. Third, tracking errors are proven to be uniformly ultimately bounded (UUB) and can converge to an arbitrarily small neighborhood of zero in a finite time. Simulation studies and comprehensive comparisons demonstrate that the proposed DAFTC scheme has remarkable performance and is superior in both tracking accuracy and unknown parametric dynamics compensation.
Background Sarcopenia, a relatively new syndrome referring to the age-related decline of muscle strength and degenerative loss of skeletal muscle mass and function, often resulting in frailty, ...disability, and mortality. Osteoarthritis, as a prevalent joint degenerative disease, is affecting over 250 million patients worldwide, and it is the fifth leading cause of disability. Despite the high prevalence of osteoarthritis, there are still lack of efficient treatment potions in clinics, partially due to the heterogeneous and complexity of osteoarthritis pathology. Previous studies revealed the association between sarcopenia and osteoarthritis, but the conclusions remain controversial and the prevalence of sarcopenia within osteoarthritis patients still needs to be elucidated. To identify the current evidence on the prevalence of sarcopenia and its association with osteoarthritis across studies, we performed this systematic review and meta-analysis that would help us to further confirm the association between these two diseases. Methods and analysis Electronic sources including PubMed, Embase, and Web of Science will be searched systematically following appropriate strategies to identify relevant studies from inception up to 28 February 2022 with no language restriction. Two investigators will evaluate the preselected studies independently for inclusion, data extraction and quality assessment using a standardized protocol. Meta-analysis will be performed to pool the estimated effect using studies assessing an association between sarcopenia and osteoarthritis. Subgroup analyses will also be performed when data are sufficient. Heterogeneity and publication bias of included studies will be investigated. PROSPERO registration number CRD42020155694.
Hydrogen has emerged as an environmentally attractive fuel and a promising energy carrier for future applications to meet the ever‐increasing energy challenges. The safe and efficient storage and ...release of hydrogen remain a bottleneck for realizing the upcoming hydrogen economy. Hydrogen storage based on liquid‐phase chemical hydrogen storage materials is one of the most promising hydrogen storage techniques, which offers considerable potential for large‐scale practical applications for its excellent safety, great convenience, and high efficiency. Recently, nanopore‐supported metal nanocatalysts have stood out remarkably in boosting the field of liquid‐phase chemical hydrogen storage. Herein, the latest research progress in catalytic hydrogen production is summarized, from liquid‐phase chemical hydrogen storage materials, such as formic acid, ammonia borane, hydrous hydrazine, and sodium borohydride, by using metal nanocatalysts confined within diverse nanoporous materials, such as metal–organic frameworks, porous carbons, zeolites, mesoporous silica, and porous organic polymers. The state‐of‐the‐art synthetic strategies and advanced characterizations for these nanocatalysts, as well as their catalytic performances in hydrogen generation, are presented. The limitation of each hydrogen storage system and future challenges and opportunities on this subject are also discussed. References in related fields are provided, and more developments and applications to achieve hydrogen energy will be inspired.
Recent research progress on nanopore‐supported metal nanocatalysts for H2 generation from various liquid‐phase chemical hydrogen storage materials is reviewed, mainly focusing on the presentation of state‐of‐the‐art synthetic strategies and advanced characterizations of these nanocatalysts and their catalytic performances in hydrogen generation. Some drawbacks of each hydrogen storage system and challenges and opportunities in future research are also highlighted.
Urban tourism promotes the economic growth of a nation around the year through direct and indirect incomes. In recent years, the digital economy has impacted the growth of urban tourism through ...hassle-free money transactions and expenditures. This article, therefore, introduces a Multi-Criteria Fuzzy-based Decision-Making Method (MCFDMM) for validating the impact of the digital economy impact over tourism. The study introduces a new framework, DLFDSS-RRM, that uses deep learning and fuzzy decision support systems for residence right management, enhancing resource allocation, security, and resident satisfaction in urban residential communities. The criteria such as expenses, positive response, and repeated payments are validated by the tourists across their travel plan. These conditions satisfying the tourist’s expectations are estimated based on their reviews of economic conditions are validated. The validation is performed against the growth of the country from urban tourism. The fuzzy process validates the growth of the country between two successive financial quarters based on the above conditions. In the condition analysis, the fuzzy process identifies the least derivatives contributing to minimal economic growth. This is reversed using the hiking condition that occurs in any quarter and hinders economic growth. Therefore, the process is validated using the metrics growth rate, condition satisfaction, analysis rate, analysis time, and unrelated assessment. The comparative analysis across various models reveals growth rates ranging from 0.263 to 0.4055, condition satisfaction percentages from 53.747 to 74.351, and analysis rates from 0.275 to 0.4662.
Most photocrosslinkable hydrogels have inadequacy in either mechanical performance or biodegradability. This issue is addressed by adopting a novel hydrogel design by introducing two different ...chitosan chains (catechol‐modified methacryloyl chitosan, CMC; methacryloyl chitosan, MC) via the simultaneous crosslinking of carbon–carbon double bonds and catechol‐Fe3+ chelation. This leads to an interpenetrating network of two chitosan chains with high crosslinking‐network density, which enhances mechanical performance including high compressive modulus and high ductility. The chitosan polymers not only endow the hydrogels with good biodegradability and biocompatibility, they also offer intrinsic antibacterial capability. The quinone groups formed by Fe3+ oxidation and protonated amino groups of chitosan polymer further enhance antibacterial property of the hydrogels. Serving as one of the two types of crosslinking mechanisms, the catechol‐Fe3+ chelation can covalently link with amino, thiol, and imidazole groups, which substantially enhance the hydrogel's adhesion to biological tissues. The hydrogel's adhesion to porcine skin shows a lap shear strength of 18.1 kPa, which is 6‐time that of the clinically established Fibrin Glue's adhesion. The hydrogel also has a good hemostatic performance due to the superior tissue adhesion as demonstrated with a hemorrhaging liver model. Furthermore, the hydrogel can remarkably promote healing of bacteria‐infected wound.
A novel photocrosslinkable, injectable, and tough chitosan hydrogel demonstrating a remarkable improvement in tissue adhesion and antibacterial activity is fabricated via double crosslinking (blue light crosslinking and catechol‐Fe3+ chelation) and double network design, suggesting that it can be promising as wound dressing for cutaneous tissue repair, remodeling, and regeneration.
Crystalline nanoporous materials with uniform porous structures, such as zeolites and metal–organic frameworks (MOFs), have proven to be ideal supports to encapsulate ultrasmall metal nanoparticles ...(MNPs) inside their void nanospaces to generate high‐efficiency nanocatalysts. The nanopore‐encaged metal catalysts exhibit superior catalytic performance as well as high stability and catalytic shape selectivity endowed by the nanoporous matrix. In addition, the synergistic effect of confined MNPs and nanoporous frameworks with active sites can further promote the catalytic activities of the composite catalysts. Herein, recent progress in nanopore‐encaged metal nanocatalysts is reviewed, with a special focus on advances in synthetic strategies for ultrasmall MNPs (<5 nm), clusters, and even single atoms confined within zeolites and MOFs for various heterogeneous catalytic reactions. In addition, some advanced characterization methods to elucidate the atomic‐scale structures of the nanocatalysts are presented, and the current limitations of and future opportunities for these fantastic nanocatalysts are also highlighted and discussed. The aim is to provide some guidance for the rational synthesis of nanopore‐encaged metal catalysts and to inspire their further applications to meet the emerging demands in catalytic fields.
Recent advancements in nanopore‐encaged metal nanocatalysts are reviewed, mainly focusing on presenting the state‐of‐the‐art strategies for the fabrication of ultrasmall metal nanoparticles (<5 nm), clusters, and even single atoms confined within crystalline nanoporous materials including zeolites and metal–organic frameworks. Some related catalytic applications and advanced characterization methods are introduced, and the current limitations of and future opportunities for these fantastic nanocatalysts are also highlighted.
In this paper, under unforeseen circumstances, a dynamics-constrained global-local (DGL) hybrid path planning scheme incorporating global path planning and local hierarchical architecture is created ...for an autonomous surface vehicle (ASV) with constrained dynamics. By encapsulating ASV safety area into Theta*-like heuristics, global path planning algorithm is developed to optimally generate sparse waypoints which are sufficiently clear to constraints. To deal with dynamically unforeseen environments, a local hierarchy is established by fuzzy decision-making (FDM) and fine dynamic window (FDW) layers, which are responsible for large- and close-range collision avoidance, respectively, by governing surge and yaw velocity guidance signals. With the aid of the FDW, constrained dynamics pertaining to the ASV, i.e., actuatable surge/yaw velocities and accelerations, are elaboratively embedded into local path planning, which in turn governs trackable collision-avoidance local path. By inserting virtual waypoints onto the globally optimal path, a seamless interface between global and local path-planning mechanism is devised, and thereby contributing to the entire DGL hybrid path planning scheme. Simulations and comparisons in various real-world geographies demonstrate the effectiveness and superiority of the proposed DGL hybrid path planning scheme.
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