Notes

Robot-Assisted Walking Training Policy for Patients inside Poststroke Period of recovery: A Single Window blind Randomized Controlled Trial.
Complete separation of water and solute is the ultimate goal of water treatment, for maximized resource recycling. However, commercialized approaches such as evaporative crystallizers consume a large amount of electricity with a significant carbon footprint, leading to calls for alternative energy-efficient and eco-friendly strategies. Here, inspired by schooling fish, we demonstrate a collective system self-assembled by expanded polystyrene (EPS)-core/graphene oxide (GO)-shell particles, which enables autonomous, efficient and complete water-solute separation powered by sunlight. By taking advantage of surface tension, these tailored particles school together naturally and are bonded as a system to function collectively and coordinatively, to nucleate, grow and output salt crystals continuously and automatically out of even saturated brine, to complete water-solute separation. Solar-vapor conversion efficiency over 90% and salt production rate as high as 0.39 kg m-2 h-1 are achieved under 1-sun illumination for this system. It reduces the carbon footprint of ∼50 kg for treating 1-ton saturated brine compared with the commercialized approaches.Extreme El Niño events severely disrupt the global climate, causing pronounced socio-economic losses. A prevailing view is that extreme El Niño events, defined by total precipitation or convection in the Niño3 area, will increase 2-fold in the future. However, this projected change was drawn without removing the potential impacts of Coupled Model Intercomparison Project phase 5 (CMIP5) models' common biases. Here, we find that the models' systematic biases in simulating tropical climate change over the past century can reduce the reliability of the projected change in the Pacific sea surface temperature (SST) and its related extreme El Niño frequency. The projected Pacific SST change, after removing the impacts of 13 common biases, displays a 'La Niña-like' rather than 'El Niño-like' change. Consequently, the extreme El Niño frequency, which is highly linked to the zonal distribution of the Pacific SST change, would remain mostly unchanged under CMIP5 warming scenarios. This finding increases confidence in coping with climate risks associated with global warming.Advances in development of artificial muscles have enabled creation of soft robots with biological dexterity and self-adaption in unstructured environments; however, production of scalable artificial muscles with multiple-mode actuations remains elusive. Inspired by muscle-fiber arrays in muscular hydrostats, we present a class of versatile artificial muscles called MAIPAMs (muscle-fiber array inspired pneumatic artificial muscles), capable of multiple-mode actuations (such as parallel elongation-bending-spiraling actuations, 10 parallel bending actuations and cascaded elongation-bending-spiraling actuations). Our MAIPAMs consist of active 3D elastomer-balloon arrays reinforced by a passive elastomer membrane, achieved through a planar design and one-step rolling fabrication approach. We introduce prototypical designs for the MAIPAMs and demonstrate their muscle-mimic structures and versatility, as well as their scalable ability to integrate flexible but non-stretchable layers for contraction and twisting actuation modes and compliant electrodes for self-sensing. We further demonstrate that this class of artificial muscles shows potential for versatile robotic applications, such as carrying a camera for recording videos, gripping or manipulating objects, and climbing a pipe-line.Polarization-sensitive photodetection is central to optics applications and has been successfully demonstrated in photodetectors of two-dimensional (2D) materials, such as layered hybrid perovskites; however, achieving high polarization sensitivity in such a photodetector remains extremely challenging. Here, for the first time, we demonstrate a high-performance polarization-sensitive photodetector using single-crystalline 2D/3D perovskite heterostructure, namely, (4-AMP)(MA)2Pb3Br10/MAPbBr3 (MA = methylammonium; 4-AMP = 4-(aminomethyl)piperidinium), which exhibits ultrahigh polarization sensitivity up to 17.6 under self-driven mode. To our knowledge, such a high polarization selectivity has surpassed all of the reported perovskite-based devices, and is comparable to, or even better than, the traditional inorganic heterostructure-based photodetectors. Further studies reveal that the built-in electric field formed at the junction can spatially separate the photogenerated electrons and holes, reducing their recombination rate and thus enhancing the performance for polarization-sensitive photodetection. This work provides a new source of polarization-sensitive materials and insights into designing novel optoelectronic devices.The global deposition of superheavy pyrite (pyrite isotopically heavier than coeval seawater sulfate in the Neoproterozoic Era and particularly in the Cryogenian Period) defies explanation using the canonical marine sulfur cycle system. Here we report petrographic and sulfur isotopic data (δ34Spy) of superheavy pyrite from the Cryogenian Datangpo Formation (660-650 Ma) in South China. Our data indicate a syndepositional/early diagenetic origin of the Datangpo superheavy pyrite, with 34S-enriched H2S supplied from sulfidic (H2S rich) seawater. Instructed by a novel sulfur-cycling model, we propose that the emission of 34S-depleted volatile organosulfur compounds (VOSC) that were generated via sulfide methylation may have contributed to the formation of 34S-enriched sulfidic seawater and superheavy pyrite. The global emission of VOSC may be attributed to enhanced organic matter production after the Sturtian glaciation in the context of widespread sulfidic conditions. These findings demonstrate that VOSC cycling is an important component of the sulfur cycle in Proterozoic oceans.The extent to which key factors at the global scale influence plant biomass allocation patterns remains unclear. Here, we provide a theory about how biotic and abiotic factors influence plant biomass allocation and evaluate its predictions using a large global database for forested communities. Our analyses confirm theoretical predictions that temperature, precipitation, and plant height and density jointly regulate the quotient of leaf biomass and total biomass, and that they have a much weaker effect on shoot (leaf plus stem) biomass fractions at a global scale. Moreover, biotic factors have larger effects than abiotic factors. Climatic variables act equally on shoot and root growth, and differences in plant body size and age, as well as community species composition, which vary with climate in ways that drown out the variations in biomass fractions. The theory and data presented here provide mechanistic explanations of why climate has little effect on biomass fractions.Somatic mutations of the chromatin remodeling gene ARID2 are observed in ∼7% of human lung adenocarcinomas (LUADs). However, the role of ARID2 in the pathogenesis of LUADs remains largely unknown. Here we find that ARID2 expression is decreased during the malignant progression of both human and mice LUADs. Using two KrasG12D -based genetically engineered murine models, we demonstrate that ARID2 knockout significantly promotes lung cancer malignant progression and shortens overall survival. Consistently, ARID2 knockdown significantly promotes cell proliferation in human and mice lung cancer cells. Through integrative analyses of ChIP-Seq and RNA-Seq data, we find that Hspa1a is up-regulated by Arid2 loss. Knockdown of Hspa1a specifically inhibits malignant progression of Arid2-deficient but not Arid2-wt lung cancers in both cell lines as well as animal models. Treatment with an HSPA1A inhibitor could significantly inhibit the malignant progression of lung cancer with ARID2 deficiency. Together, our findings establish ARID2 as an important tumor suppressor in LUADs with novel mechanistic insights, and further identify HSPA1A as a potential therapeutic target in ARID2-deficient LUADs.Zeolites, as efficient and stable catalysts, are widely used in the environmental catalysis field. Typically, Cu-SSZ-13 with small-pore structure shows excellent catalytic activity for selective catalytic reduction of NO x with ammonia (NH3-SCR) as well as high hydrothermal stability. This review summarizes major advances in Cu-SSZ-13 applied to the NH3-SCR reaction, including the state of copper species, standard and fast SCR reaction mechanism, hydrothermal deactivation mechanism, poisoning resistance and synthetic methodology. The review gives a valuable summary of new insights into the matching between SCR catalyst design principles and the characteristics of Cu2+-exchanged zeolitic catalysts, highlighting the significant opportunity presented by zeolite-based catalysts. Principles for designing zeolites with excellent NH3-SCR performance and hydrothermal stability are proposed. On the basis of these principles, more hydrothermally stable Cu-AEI and Cu-LTA zeolites are elaborated as well as other alternative zeolites applied to NH3-SCR. Finally, we call attention to the challenges facing Cu-based small-pore zeolites that still need to be addressed.Retrieving historical fine particulate matter (PM2.5) data is key for evaluating the long-term impacts of PM2.5 on the environment, human health and climate change. Satellite-based aerosol optical depth has been used to estimate PM2.5, but estimations have largely been undermined by massive missing values, low sampling frequency and weak predictive capability. Here, using a novel feature engineering approach to incorporate spatial effects from meteorological data, we developed a robust LightGBM model that predicts PM2.5 at an unprecedented predictive capacity on hourly (R2 = 0.75), daily (R2 = 0.84), monthly (R2 = 0.88) and annual (R2 = 0.87) timescales. By taking advantage of spatial features, our model can also construct hourly gridded networks of PM2.5. This capability would be further enhanced if meteorological observations from regional stations were incorporated. Our results show that this model has great potential in reconstructing historical PM2.5 datasets and real-time gridded networks at high spatial-temporal resolutions. The resulting datasets can be assimilated into models to produce long-term re-analysis that incorporates interactions between aerosols and physical processes.As a promising low-cost energy storage device, the development of a rechargeable potassium-ion battery (KIB) is severely hindered by the limited capacity of cathode candidates. Regarded as an attractive capacity-boosting strategy, triggering the O-related anionic redox activity has not been achieved within a sealed KIB system. Herein, in contrast to the typical gaseous open K-O2 battery (O2/KO2 redox), we originally realize the reversible superoxide/peroxide (KO2/K2O2) interconversion on a KO2-based cathode. Controlled within a sealed cell environment, the irreversible O2 evolution and electrolyte decomposition (induced by superoxide anion (O2 -) formation) are effectively restrained. selleck kinase inhibitor Rationally controlling the reversible depth-of-charge at 300 mAh/g (based on the mass of KO2), no obvious cell degradation can be observed during 900 cycles. Moreover, benefitting from electrolyte modification, the KO2-based cathode is coupled with a limited amount of K-metal anode (merely 2.5 times excess), harvesting a K-metal full-cell with high energy efficiency (∼90%) and long-term cycling stability (over 300 cycles).
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