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Large-scale downscaling plays an important role in assessing global impacts on hydrological sphere due to climate changes. In such downscaling efforts, it is essential to consider the various climate regimes. Although previous studies have indirectly suggested that the accuracy of downscaling might differ among climate regimes, research that systematically understands or quantifies the variability of this accuracy remains scarce. This study addresses this gap by systematically quantifying the performance of five different large-scale downscaling methods across various climate regimes in the context of downscaling hydroclimatic indicators. Our findings indicate that large-scale downscaling yields the highest accuracy on average when applied to temperature, precipitation, and runoff in tropical, arid, and temperate climate regimes, respectively, while showing poor accuracy in polar regimes for all variables. The maximum difference of normalized root mean squared errors for hydroclimate indicators is 69 % across climate zones, and the spatial distribution of downscaling accuracy aligns with spatial distribution of climate zones. The variation of downscaling accuracy is particularly significant in temperature, precipitation, and seasonal runoff indicators. Furthermore, linkages between accuracy of climate and hydrological indicators differ by climate zones. The underlying reasons for the different accuracy of downscaling are spatially different accuracy of global climate models (GCMs) and interaction of downscaling structure and climate regimes. This study articulated the source of spatially different accuracy/uncertainties for large-scale downscaling that have never been addressed before. The findings of this study provide valuable support in selecting appropriate downscaling methods, ultimately enhancing the spatial reliability and accuracy of large-scale downscaling methods. 

Articular cartilage is the avascular and aneural tissue which is the primary connective tissue covering the surface of articulat- ing bone. Traumatic damage or degenerative diseases can cause articular cartilage injuries that are common in the population. As a result, the demand for new therapeutic options is continually increasing for older people and traumatic young patients. Many attempts have been made to address these clinical needs to treat articular cartilage injuries, including osteoarthritis (OA); however, regenerating highly qualified cartilage tissue remains a significant obstacle. 3D bioprinting technology combined with tissue engineering principles has been developed to create biological tissue constructs that recapitulate the anatomical, structural, and functional properties of native tissues. In addition, this cutting-edge technology can precisely place multiple cell types in a 3D tissue architecture. Thus, 3D bioprinting has rapidly become the most innovative tool for manufacturing clinically applicable bioengineered tissue constructs. This has led to increased interest in 3D bioprinting in articular cartilage tissue engineering applications. Here, we tissue engineering. 

Sulfated glycans from marine organisms are excellent sources of naturally occurring glycosaminoglycan (GAG) mimetics that demonstrate therapeutic activities, such as antiviral/microbial infection, anticoagulant, anticancer, and anti-inflammation activities. Many viruses use the heparan sulfate (HS) GAG on the surface of host cells as co-receptors for attachment and initiating cell entry. Therefore, virion–HS interactions have been targeted to develop broad-spectrum antiviral therapeutics. Here we report the potential anti-monkeypox virus (MPXV) activities of eight defined marine sulfated glycans, three fucosylated chondroitin sulfates, and three sulfated fucans extracted from the sea cucumber species Isostichopus badionotus, Holothuria floridana, and Pentacta pygmaea, and the sea urchin Lytechinus variegatus, as well as two chemically desulfated derivatives. The inhibitions of these marine sulfated glycans on MPXV A29 and A35 protein–heparin interactions were evaluated using surface plasmon resonance (SPR). These results demonstrated that the viral surface proteins of MPXV A29 and A35 bound to heparin, which is a highly sulfated HS, and sulfated glycans from sea cucumbers showed strong inhibition of MPXV A29 and A35 interactions. The study of molecular interactions between viral proteins and host cell GAGs is important in developing therapeutics for the prevention and treatment of MPXV. 

Abstract We have observed thez= 4.3 protocluster SPT2349−56 with the Australia Telescope Compact Array (ATCA) with the aim of detecting radio-loud active galactic nuclei (AGNs) among the ∼30 submillimeter (submm) galaxies (SMGs) identified in the structure. We detect the central complex of submm sources at 2.2 GHz with a luminosity ofL_2.2= (4.42 ± 0.56) × 10²⁵W Hz⁻¹. MeerKAT and the Australian Square Kilometre Array Pathfinder also detect the source at 816 MHz and 888 MHz, respectively, constraining the radio spectral index toα= −1.45 ± 0.16, implyingL_1.4,rest= (2.2 ± 0.2) × 10²⁶W Hz⁻¹. The radio observations do not have sufficient spatial resolution to uniquely identify one of the three Atacama Large Millimeter/submillimeter Array (ALMA) galaxies as the AGN, however the ALMA source properties themselves suggest a likely host. This radio luminosity is ∼100× higher than expected from star formation, assuming the usual far-infrared–radio correlation, indicating an AGN driven by a forming brightest cluster galaxy. None of the SMGs in SPT2349−56 show signs of AGNs in any other diagnostics available to us, highlighting the radio continuum as a powerful probe of obscured AGNs. We compare these results to field samples of radio sources and SMGs, along with the 22 gravitationally lensed SPT-SMGs also observed in the ATCA program, as well as powerful radio galaxies at high redshifts. The (3.3 ± 0.7) × 10³⁸W of power from the radio-loud AGN sustained over 100 Myr is comparable to the binding energy of the gas mass of the central halo, and similar to the instantaneous energy injection from supernova feedback from the SMGs in the core region. The SPT2349−56 radio-loud AGNs may be providing strong feedback on a nascent intracluster medium. 

Abstract The leakage of quantum information out of the two computational states of a qubit into other energy states represents a major challenge for quantum error correction. During the operation of an error-corrected algorithm, leakage builds over time and spreads through multi-qubit interactions. This leads to correlated errors that degrade the exponential suppression of the logical error with scale, thus challenging the feasibility of quantum error correction as a path towards fault-tolerant quantum computation. Here, we demonstrate a distance-3 surface code and distance-21 bit-flip code on a quantum processor for which leakage is removed from all qubits in each cycle. This shortens the lifetime of leakage and curtails its ability to spread and induce correlated errors. We report a tenfold reduction in the steady-state leakage population of the data qubits encoding the logical state and an average leakage population of less than 1 × 10⁻³throughout the entire device. Our leakage removal process efficiently returns the system back to the computational basis. Adding it to a code circuit would prevent leakage from inducing correlated error across cycles. With this demonstration that leakage can be contained, we have resolved a key challenge for practical quantum error correction at scale. 

We demonstrate a high dynamic range Josephson parametric amplifier (JPA) in which the active nonlinear element is implemented using an array of rf-SQUIDs. The device is matched to the 50 Ω environment with a Klopfenstein-taper impedance transformer and achieves a bandwidth of 250–300 MHz with input saturation powers up to −95 dBm at 20 dB gain. A 54-qubit Sycamore processor was used to benchmark these devices, providing a calibration for readout power, an estimation of amplifier added noise, and a platform for comparison against standard impedance matched parametric amplifiers with a single dc-SQUID. We find that the high power rf-SQUID array design has no adverse effect on system noise, readout fidelity, or qubit dephasing, and we estimate an upper bound on amplifier added noise at 1.6 times the quantum limit. Finally, amplifiers with this design show no degradation in readout fidelity due to gain compression, which can occur in multi-tone multiplexed readout with traditional JPAs. 

Abstract Practical quantum computing will require error rates well below those achievable with physical qubits. Quantum error correction^1,2offers a path to algorithmically relevant error rates by encoding logical qubits within many physical qubits, for which increasing the number of physical qubits enhances protection against physical errors. However, introducing more qubits also increases the number of error sources, so the density of errors must be sufficiently low for logical performance to improve with increasing code size. Here we report the measurement of logical qubit performance scaling across several code sizes, and demonstrate that our system of superconducting qubits has sufficient performance to overcome the additional errors from increasing qubit number. We find that our distance-5 surface code logical qubit modestly outperforms an ensemble of distance-3 logical qubits on average, in terms of both logical error probability over 25 cycles and logical error per cycle ((2.914 ± 0.016)% compared to (3.028 ± 0.023)%). To investigate damaging, low-probability error sources, we run a distance-25 repetition code and observe a 1.7 × 10⁻⁶logical error per cycle floor set by a single high-energy event (1.6 × 10⁻⁷excluding this event). We accurately model our experiment, extracting error budgets that highlight the biggest challenges for future systems. These results mark an experimental demonstration in which quantum error correction begins to improve performance with increasing qubit number, illuminating the path to reaching the logical error rates required for computation.