Search

Abstract Many of the most sensitive physics experiments searching for rare events, like neutrinoless double beta ( $$0\nu \beta \beta $$ 0 ν β β ) decay, coherent elastic neutrino nucleus scattering and dark matter interactions, rely on cryogenic macro-calorimeters operating at the mK-scale. Located underground at the Gran Sasso National Laboratory (LNGS), in central Italy, CUORE (Cryogenic Underground Observatory for Rare Events) is one of the leading experiments for the search of $$0\nu \beta \beta $$ 0 ν β β decay, implementing the low-temperature calorimetric technology. We present a novel multi-device analysis to correlate environmental phenomena with the low-frequency noise of low-temperature calorimeters. Indeed, the correlation of marine and seismic data with data from a couple of CUORE detectors indicates that cryogenic detectors are sensitive not only to intense vibrations generated by earthquakes, but also to the much fainter vibrations induced by marine microseisms in the Mediterranean Sea due to the motion of sea waves. Proving that cryogenic macro-calorimeters are sensitive to such environmental sources of noise opens the possibility of studying their impact on the detectors physics-case sensitivity. Moreover, this study could pave the road for technology developments dedicated to the mitigation of the noise induced by marine microseisms, from which the entire community of cryogenic calorimeters can benefit.

Climate change influences the water cycle and alters the spatiotemporal distribution of hydrological variables, thus complicating the projection of future streamflow and hydrological droughts. Although machine learning is increasingly employed for hydrological simulations, few studies have used it to project hydrological droughts, not to mention bivariate risks (referring to drought duration and severity) as well as their socioeconomic effects under climate change. We developed a cascade modeling chain to project future bivariate hydrological drought characteristics in 179 catchments over China, using five bias-corrected global climate model (GCM) outputs under three shared socioeconomic pathways (SSPs), five hydrological models, and a deep-learning model. We quantified the contribution of various meteorological variables to daily streamflow by using a random forest model, and then we employed terrestrial water storage anomalies and a standardized runoff index to evaluate recent changes in hydrological drought. Subsequently, we constructed a bivariate framework to jointly model drought duration and severity by using copula functions and the most likely realization method. Finally, we used this framework to project future risks of hydrological droughts as well as the associated exposure of gross domestic product (GDP) and population. Results showed that our hybrid hydrological–deep-learning model achieved > 0.8 Kling–Gupta efficiency in 161 out of the 179 catchments. By the late 21st century, bivariate drought risk is projected to double over 60 % of the catchments mainly located in southwestern China under SSP5-85, which shows the increase in drought duration and severity. Our hybrid model also projected substantial GDP and population exposure by increasing bivariate drought risks, suggesting an urgent need to design climate mitigation strategies for a sustainable development pathway.

ABSTRACT This study aimed to identify candidate genes regulating ovarian development following ovarian tissue transplantation through transcriptome sequencing (RNA-seq) and weighted gene co-expression network analysis (WGCNA). Ovarian tissues were collected from 10 thirty-day-old donor chickens, and each ovary was divided equally into three parts of similar size, and transplanted in situ into two-day-old recipient chickens. Samples were collected on days 0 (untransplanted), 6, and 12 after transplantation. RNA was extracted from ovarian samples for construction of a transcriptome library, and then sequenced on the IlluminaHiSeqTM2000 sequencing platform. The sequencing results were evaluated to determine differentially expressed genes (DEGs) through GO function and the KEGG pathway analyses, Gene Set Enrichment Analysis (GSEA), WGCNA, and PPI networks. Some candidate genes were further validated through real-time fluorescence quantitative PCR (RT-qPCR). RNA-seq analysis identified 2242 up-regulated and 3095 down-regulated DEGs at 6 days after ovarian transplantation, and 2181 up-regulated and 2129 down-regulated DEGs were identified at 12 days after transplantation. Enrichment analysis showed that the genes were enriched in multiple inflammatory pathways, pathways involved in signal transduction and cellular processes. Through the WGCNA, five modules were constructed, from which 4 and 5 candidate genes were mined at 6 and 12 days after ovarian transplantation, respectively. Transcription factor prediction showed that GTF3A was the most important transcription factor. The results of RT-qPCR verification confirmed that the expression profile of 8 candidate genes was consistent with that of the sequencing results. In summary, this study presents the candidate genes involved in ovarian vascular remodeling and ovarian proliferation after ovarian transplantation.

Addressing the tremendous burden of early-life adversity requires constructive dialogues between scientists and policy makers to improve population health. Whereas dialogues focused on several aspects of early-life adversity have been initiated, discussion of an underrecognized form of adversity that has been observed across multiple contexts and cultures is only now emerging. Here we provide evidence for “why unpredictability?”, including: 1. Evidence that exposures to unpredictability affect child neurodevelopment, with influences that persist into adulthood. 2. The existence of a translational non-human animal model of exposure to early life unpredictability that can be capitalized upon to causally probe neurobiological mechanisms. 3. Evidence that patterns of signals in the early environment promote brain maturation across species. 4. The uneven distribution of unpredictability across demographic populations that illuminates a possible focal point for enhancing health equity. We then outline the potential of unpredictability in terms of the “what”; that is, how might the concept of unpredictability be leveraged to inform policy? We emphasize the importance of interdisciplinary and community partnerships to the success of this work and describe our community-engaged research project. Finally, we highlight opportunities for the science of unpredictability to inform policies in areas such as screening, immigration, criminal justice, education, childcare, child welfare, employment, healthcare and housing.

Bulk W-0.5 wt%ZrC (W-ZrC), W-1 wt%Re-0.5 wt%ZrC (W-1Re-ZrC), and W-3 wt%Re-0.5 wt%ZrC (W-3Re-ZrC) alloys were prepared and exposed to He2+ ion irradiation with an incident energy of 500 keV at 400 °C. Post-irradiation analysis revealed the formation of He bubbles, with consistent number density and average size across all alloys. However, the W-3Re-ZrC alloy exhibited a notably higher density of dislocation loops within grain interiors compared to W-ZrC and W-1Re-ZrC. This led to a significant increase in the hardening rate of W-3Re-ZrC to 61.5 %, nearly twice that of the other alloys. By considering the binding energies of He-vacancy, He-He, and Re-He, the formation and growth behavior of irradiation-induced defects, including He bubbles and dislocation loops, were also discussed. This work provides valuable insight into the relationships among Re alloying, He-induced defects, and irradiation hardening in Re-alloyed W materials, thus offering valuable guidance for the design of W-based plasma-facing materials.

To reveal the effects of aging state on the low-cycle fatigue (LCF) performance of 2024 Al alloy, LCF experiments were conducted on the 2024 Al alloy with three aging states (underaged (UA), peak-aging (PA) and overaged (OA)), respectively. It is found that under the total strain amplitude and plastic strain amplitude control, the Al alloy at UA and OA states exhibits higher LCF lives than that at PA state, respectively. For a more comprehensive evaluation, a hysteretic energy model with W0 as the fatigue damage capacity and β as the fatigue damage resisting exponent was used, which also shows the advantages of the OA states. This is because although the OA state has lower fatigue damage capacity W0 for the inferior strength-plasticity combination compared to the UA state, it has higher fatigue damage resistance exponent β because the obvious wavy slip manner of dislocations is conducive to strain homogenization, which is more important for increasing the fatigue life. Therefore, this study gives a comprehensive evaluation and revelation on the effects of aging state on the LCF properties of 2024 alloy.

Abstract TadA-derived cytosine base editors (TadCBEs) enable programmable C•G-to-T•A editing while retaining the small size, high on-target activity, and low off-target activity of TadA deaminases. Existing TadCBEs, however, exhibit residual A•T-to-G•C editing at certain positions and lower editing efficiencies at some sequence contexts and with non-SpCas9 targeting domains. To address these limitations, we use phage-assisted evolution to evolve CBE6s from a TadA-mediated dual cytosine and adenine base editor, discovering mutations at N46 and Y73 in TadA that prevent A•T-to-G•C editing and improve C•G-to-T•A editing with expanded sequence-context compatibility, respectively. In E. coli, CBE6 variants offer high C•G-to-T•A editing and no detected A•T-to-G•C editing in any sequence context. In human cells, CBE6 variants exhibit broad Cas domain compatibility and retain low off-target editing despite exceeding BE4max and previous TadCBEs in on-target editing efficiency. Finally, we show that the high selectivity of CBE6 variants is well-suited for therapeutically relevant stop codon installation without creating unwanted missense mutations from residual A•T-to-G•C editing.

Due to a robust emission control policy, significant reductions in major air pollutants, such as PM2.5, SO2, NO2, and CO, were observed in China between 2015 and 2020. On the other hand, during the same period, there was a notable increase in ozone (O3) concentrations, making it a prominent air pollutant in eastern China. The annual mean concentration of maximum daily 8 h average (MDA8) O3 exhibited alarming linear increases of 2.4, 1.1, and 2.0 ppb yr−1 (ppb is for parts per billion) in three megacity clusters: Beijing–Tianjin–Hebei (BTH), the Yangtze River Delta (YRD), and the Pearl River Delta (PRD), respectively. Meanwhile, there was a significant 3-fold increase in the number of O3-exceeding days, defined as MDA8 O3 > 75 ppb. Our analysis indicated that the upward increases in the annual mean concentration of MDA8 were primarily driven by the rise in consecutive O3-exceeding days. There were expansions of high O3 in urban centers to rural areas accompanied by a saturation effect so that MDA8 O3 concentrations at the high-O3 stations in 2015 remained nearly constant at 100 ppb. Last, we found a close association between O3 episodes with 4 or more consecutive O3-exceeding days and the position and strength of tropical cyclones (TCs) in the northwest Pacific and the West Pacific subtropical high (WPSH). The TC and WPSH contributed to meteorological conditions characterized by clear skies, subsiding air motion, high vertical stability in the lower troposphere, increased solar radiation, and a positive temperature anomaly at the surface. These favorable meteorological conditions greatly facilitated the formation of O3. Thus, we propose that the worsening O3 increases observed in the BTH, YRD, and PRD regions from 2015 to 2020 can be mostly attributed to enhanced photochemical O3 production resulting from an increased occurrence of meteorological conditions with high solar radiation and positive temperature anomalies under the influence of the WPSH and TCs.

Traditional methods such as Steinmetz's equation (SE) and its improved variant (iGSE) have demonstrated limited precision in estimating power loss for magnetic materials. The introduction of Neural Network technology for assessing magnetic component power loss has significantly enhanced accuracy. Yet, an efficient method to incorporate detailed flux density information—which critically impacts accuracy—remains elusive. Our study introduces an innovative approach that merges Fast Fourier Transform (FFT) with a Feedforward Neural Network (FNN), aiming to overcome this challenge. To optimize the model further and strike a refined balance between complexity and accuracy, Multi-Objective Optimization (MOO) is employed to identify the ideal combination of hyperparameters, such as layer count, neuron number, activation functions, optimizers, and batch size. This optimized Neural Network outperforms traditionally intuitive models in both accuracy and size. Leveraging the optimized base model for known materials, transfer learning is applied to new materials with limited data, effectively addressing data scarcity. The proposed approach substantially enhances model training efficiency, achieves remarkable accuracy, and sets an example for Artificial Intelligence applications in loss and electrical characteristic predictions with challenges of model size, accuracy goals, and limited data.

As a typical cutting tool with good performance and high processing efficiency, metallurgical saw blades are widely used in various industries, but surface defects are inevitably generated in the manufacturing process. To solve this problem, this paper proposes a YOLOv5-based surface defect detection model for product quality, which can distinguish three common metallurgical sawblade surface defects with mAP value of 96,1 % in each defect category detection of metallurgical sawblades and detection time of 139,8 ms per image.

In the process of urban construction and development, the ecological environment has always been an important consideration factor. How to quickly monitor the long-term ecological environment quality changes in large urban areas is currently one of the main research hotspots. With the continuous development of remote sensing intelligent cloud computing technology, the application of remote sensing methods to monitor urban ecological environment quality changes is becoming more efficient and convenient. Based on the remote sensing ecological index (RSEI) on the remote sensing intelligent cloud platform Google Earth Engine (GEE), this article innovatively proposes an improved remote sensing ecological index (DS-RSEI, Downscale-RSEI). Using the normalized difference vegetation index (NDVI) and land cover data (LULC), terrain data as auxiliary data, the method of moving window and principal component analysis is used to implement spatial downscaling of the heat components in the index, which increases the resolution of the original MODIS land surface temperature (LST) 1000-meter resolution product to 500 meters. When fusing with other images, it can supplement missing image details and improve the ability to evaluate the ecological spatial details of complex urban blocks. Through a comparative analysis of the RSEI index and the DS-RSEI index proposed in this article, it can be seen that DS-RSEI can express the details of ecological environment changes better in complex blocks.

Abstract Gene editing strategies for cystic fibrosis are challenged by the complex barrier properties of airway epithelia. We previously reported that the amphiphilic S10 shuttle peptide non-covalently combined with CRISPR-associated (Cas) ribonucleoprotein (RNP) enabled editing of human and mouse airway epithelial cells. Here, we derive the S315 peptide as an improvement over S10 in delivering base editor RNP. Following intratracheal aerosol delivery of Cy5-labeled peptide in rhesus macaques, we confirm delivery throughout the respiratory tract. Subsequently, we target CCR5 with co-administration of ABE8e-Cas9 RNP and S315. We achieve editing efficiencies of up-to 5.3% in rhesus airway epithelia. Moreover, we document persistence of edited epithelia for up to 12 months in mice. Finally, delivery of ABE8e-Cas9 targeting the CFTR R553X mutation restores anion channel function in cultured human airway epithelia. These results demonstrate the therapeutic potential of base editor delivery with S315 to functionally correct the CFTR R553X mutation in respiratory epithelia.

In order to improve the image registration accuracy of heterogeneous remote sensing images with large radiation differences, an improved image registration algorithm for thermal infrared and panchromatic images is proposed. This method uses the phase consistency of intensity and direction to construct a geometric structure feature descriptor called the Histogram of Oriented Phase Congruency (HOPC) for image registration. It employs the Curvature Scale Space (CSS) corner detection to concentrate and extract feature points in contour areas, and defines a similarity metric (called HOPCn) based on the Euclidean distance between the descriptors for high-precision heterogeneous images registration. Five sets of panchromatic and thermal infrared images were selected for verification. The results show that the improved algorithm can match the homonymy points around the image contour, and the Correct Matching Rate (CMR) is improved by 2.7% and the Root Mean Square Error (RMSE) is improved by 3.7% compared to the original algorithm. This proves that the proposed method has good robustness under conditions of large radiation differences.

Animal nutritionists continue to investigate new strategies to combat the challenge of methane emissions from ruminants. Medicinal plants (MPs) are known to be beneficial to animal health and exert functional roles in livestock due to their phytogenic compounds with antimicrobial, immunostimulatory, antioxidative, and anti-inflammatory activities. Some MP has been reported to be anti-methanogenic and can effectively lower ruminants' enteric methane emissions. This review overviews trends in MP utilization in ruminants, their bioactivity and their effectiveness in lowering enteric methane production. It highlights the MP regulatory mechanism and the gaps that must be critically addressed to improve its efficacy. MP could reduce enteric methane production by up to 8–50% by regulating the rumen fermentation pathway, directing hydrogen toward propionogenesis, and modifying rumen diversity, structure, and population of the methanogens and protozoa. Yet, factors such as palatability, extraction techniques, and economic implications must be further considered to exploit their potential fully.

Oases and deserts generally act as a landscape matrix and mosaic in arid and semiarid regions. The significant difference in thermal and dynamic characteristics between an oasis and desert surface will result in oasis–desert interaction. Specifically, this refers to the interaction between an oasis and desert system via the exchange of momentum, energy, water, and carbon, which can lead to a series of microclimate effects that affect the structure of the atmospheric boundary layer, changes in carbon sources and sinks in an oasis, and the local ecological environment. Therefore, studying water, heat, and carbon exchange is significant to achieve the goals of carbon peaking and carbon neutrality in oasis–desert areas and support the ecological security and sustainable development of oases. To monitor energy, water vapor, and carbon exchange between the land surface and atmosphere, a land surface process integrated observatory network was established in the oasis–desert area in the middle and lower reaches of the Heihe River basin, the second largest endorheic basin in China. In this study, we present a suite of observational datasets from artificial and natural oasis–desert systems that consist of long-term energy, water vapor, carbon and methane fluxes as well as auxiliary data involving hydrometeorology, vegetation, and soil parameters from 2012 to 2021. Half-hourly turbulent flux data were acquired by an eddy covariance system and scintillometer. The hydrometeorological data (including radiation, soil heat flux, and soil temperature profiles; gradients of air temperature and humidity and of wind speed and direction; and air pressure, precipitation, and soil moisture profiles) were observed from automatic weather stations with a 10 min average period as well as the groundwater table data. Moreover, vegetation and soil parameters were also supplemented in the datasets. Careful data processing and quality control were implemented during data production, including data collection, processing, archiving, and sharing. The current datasets can be used to explore the water–heat–carbon process and its mechanism of influence; to calibrate and validate related remote-sensing products; to simulate energy, water vapor, and carbon exchange in oasis and desert areas; and to provide references and representatives for other similar artificial and natural oases along the “Silk Road”. The data are available from the National Tibetan Plateau Third Pole Environment: https://doi.org/10.11888/Terre.tpdc.300441 (Liu et al., 2023).

This paper deals with the construction of a novel family of multimode deployable mechanisms based on reconfigurable Bricard-like mechanisms. By connecting a number of identical threefold-symmetric (TFS) Bricard-like mechanisms, a multimode deployable arch is proposed for the first time, which can switch between the scissor-like deployable mode and the arch deformable mode through the transition configuration. Then new multimode center-driven deployable mechanisms can be obtained by connecting three and six multimode deployable arches. The obtained mechanism can switch between the scissor-like deployable mode and spherical deformable mode, and it can be reassembled by adjusting the number of TFS Bricard-like mechanisms to change its size. Finally, physical prototypes of the multimode deployable arch and multimode center-driven deployable mechanisms are fabricated and tested to validate the feasibility of the proposed approach and analysis.

Abstract Atmospheric muon neutrinos are produced by meson decays in cosmic-ray-induced air showers. The flux depends on meteorological quantities such as the air temperature, which affects the density of air. Competition between decay and re-interaction of those mesons in the first particle production generations gives rise to a higher neutrino flux when the air density in the stratosphere is lower, corresponding to a higher temperature. A measurement of a temperature dependence of the atmospheric $$\nu _{\mu }$$ ν μ flux provides a novel method for constraining hadronic interaction models of air showers. It is particularly sensitive to the production of kaons. Studying this temperature dependence for the first time requires a large sample of high-energy neutrinos as well as a detailed understanding of atmospheric properties. We report the significant ( $$> 10 \; \sigma $$ > 10 σ ) observation of a correlation between the rate of more than 260,000 neutrinos, detected by IceCube between 2012 and 2018, and atmospheric temperatures of the stratosphere, measured by the Atmospheric Infrared Sounder (AIRS) instrument aboard NASA’s AQUA satellite. For the observed 10 $$\%$$ % seasonal change of effective atmospheric temperature we measure a 3.5(3) $$\%$$ % change in the muon neutrino flux. This observed correlation deviates by about 2-3 standard deviations from the expected correlation of 4.3 $$\%$$ % as obtained from theoretical predictions under the assumption of various hadronic interaction models.

Canonical splice site variants affecting the 5′ GT and 3′ AG nucleotides of introns result in severe missplicing and account for about 10% of disease-causing genomic alterations. Treatment of such variants has proven challenging due to the unstable mRNA or protein isoforms that typically result from disruption of these sites. Here, we investigate CRISPR-Cas9-mediated adenine base editing for such variants in the cystic fibrosis transmembrane conductance regulator (CFTR) gene. We validate a CFTR expression minigene (EMG) system for testing base editing designs for two different targets. We then use the EMG system to test non-standard single-guide RNAs with either shortened or lengthened protospacers to correct the most common cystic fibrosis-causing variant in individuals of African descent (c.2988+1G>A). Varying the spacer region length allowed placement of the editing window in a more efficient context and enabled use of alternate protospacer adjacent motifs. Using these modifications, we restored clinically significant levels of CFTR function to human airway epithelial cells from two donors bearing the c.2988+1G>A variant.

Abstract Mutations in Atp2b2, an outer hair cell gene, cause dominant hearing loss in humans. Using a mouse model Atp2b2 Obl/+, with a dominant hearing loss mutation (Oblivion), we show that liposome-mediated in vivo delivery of CRISPR-Cas9 ribonucleoprotein complexes leads to specific editing of the Obl allele. Large deletions encompassing the Obl locus and indels were identified as the result of editing. In vivo genome editing promotes outer hair cell survival and restores their function, leading to hearing recovery. We further show that in a double-dominant mutant mouse model, in which the Tmc1 Beethoven mutation and the Atp2b2 Oblivion mutation cause digenic genetic hearing loss, Cas9/sgRNA delivery targeting both mutations leads to partial hearing recovery. These findings suggest that liposome-RNP delivery can be used as a strategy to recover hearing with dominant mutations in OHC genes and with digenic mutations in the auditory hair cells, potentially expanding therapeutics of gene editing to treat hearing loss.

In pursuit of design solutions that reduce energy loss and improve wear resistance for the piston–cylinder interface in an axial piston motor, a fluid-structure interaction numerical model and a new test rig of the friction force of the piston–cylinder pair are developed to achieve the analysis and design of the micro-geometric tapered-shape surface of a piston bore. The piston bore with the tapered-shape surface axial distribution length ratio of 49.44 % of the overall length is found to be the relatively optimized one. Furthermore, how the shaft speed, load pressure, and swash plate angle influence the performance of the two-type interface is analyzed. Numerical analysis results show that, compared with the traditional cylindrical piston bore design, the piston–cylinder interface with the optimized tapered-shape piston bore in the axial piston motor can achieve a significant reduction in leakage flow and friction force, and the experimental results are consistent with the simulation results.

The energy and water vapor exchange between the land surface and atmospheric boundary layer plays a critical role in regional climate simulations. This paper implemented a hybrid data assimilation and machine learning framework (DA-ML method) into the Weather Research and Forecasting (WRF) model to optimize surface soil and vegetation conditions. The hybrid method can integrate remotely sensed leaf area index (LAI), multi-source soil moisture (SM) observations, and land surface models (LSMs) to accurately describe regional climate and land–atmosphere interactions. The performance of the hybrid method on the regional climate was evaluated in the Heihe River basin (HRB), the second-largest endorheic river basin in Northwest China. The results show that the estimated sensible (H) and latent heat (LE) fluxes from the WRF (DA-ML) model agree well with the large aperture scintillometer (LAS) observations. Compared to the WRF (open loop – OL), the WRF (DA-ML) model improved the estimation of evapotranspiration (ET) and generated a spatial distribution consistent with the ML-based watershed ET (ETMap). The proposed WRF (DA-ML) method effectively reduces air warming and drying biases in simulations, particularly in the oasis region. The estimated air temperature and specific humidity from WRF (DA-ML) agree well with the observations. In addition, this method can simulate more realistic oasis–desert boundaries, including wetting and cooling effects and wind shield effects within the oasis. The oasis–desert interactions can transfer water vapor to the surrounding desert in the lower atmosphere. In contrast, the dry and hot air over the desert is transferred to the oasis from the upper atmosphere. The results show that the integration of LAI and SM will induce water vapor intensification and promote precipitation in the upstream of the HRB, particularly on windward slopes. In general, the proposed WRF (DA-ML) model can improve climate modeling by implementing detailed land characterization information in basins with complex underlying surfaces.

To investigate the light intensity suitable for the growth of Ardisia gigantifolia Stapf, morphology, photosynthetic parameters, and indicators of oxidative stress were analyzed under different light intensities. Compared to high-irradiance treatment, medium and low-irradiance treatments promoted plant growth and restricted transpiration. Compared to medium irradiance, plants under high and low irradiance exhibited significantly lower maximal photochemical efficiency, potential photochemical efficiency, and electron transport rate, but significantly higher malondialdehyde content. This indicated that both excessive light and severe shading inhibited photosynthetic activity and induced oxidative stress, which resulted in a significant decrease in net photosynthetic rate. A. gigantifolia can adapt to different light intensities, improving light harvesting and utilizing capacity under low irradiance by increasing Chl (a+b) content and reducing Chl a/b ratio, and adapting to high irradiance by enhancing heat dissipation and activity of peroxidase. A. gigantifolia showed the best performance in growth and photosynthesis under medium irradiance treatment.

Vegetation, water, and carbon dioxide have complex interactions on carbon mitigation in vegetation–water ecosystems. As one of the major global change drivers of carbon sequestration, flooding disturbance is a fundamental but poorly discussed topic to date. The aquatic and associated riparian systems are highly dynamic vegetation–water carbon capture systems driven by fluvial processes such as flooding. However, their global carbon offset potential is largely unknown. This study examines daily CO2 perturbations under flooding disturbance in the river (fluvial area) and associated riparian areas with 2 year in situ observations along the Lijiang. We find that, though the submerged riparian area behaved as a carbon source during the flooding season (CO2 flux: 2.790 gm-2d-1), the riparian area and the fluvial area as a whole transformed from a carbon source in pre-flooding season (1.833 gm-2d-1) to a carbon sink after recovery in post-flooding season (−0.592 gm-2d-1). The fluvial area sequestered carbon (−0.619 gm-2d-1) in post-flooding season instead of releasing carbon as in pre-flooding season (2.485 gm-2d-1). Also, the carbon sequestration capacity of the riparian area was enhanced in post-flooding season (pre-flooding season: −0.156 gm-2d-1, post-flooding season: −0.500 gm-2d-1). We suggest that post-disturbance recovery of riparian vegetation played a vital role in this transformation, due to its stronger carbon uptake capacity after recovery from the flooding disturbances. The findings shed light on the quantitative modelling of the riparian carbon cycle under flooding disturbance and underlined the importance of the proper restoration of riparian systems to achieve global carbon offset.

In this study, we analyze the diurnal variations and formation mechanisms of low clouds at different elevations. We further discuss whether there exists a triggering mechanism for convection over the Tibetan Plateau (TP) and whether there is an association among low air density, strong turbulence, and ubiquitous “popcorn-like” cumulus clouds. The buoyancy term (BT) and shear term (ST) over the TP are significantly greater than those at low elevations, which is favorable for the formation of an increasing planetary boundary layer height (PBLH) and also plays a key role in the convective activities in the lower troposphere. From the viewpoint of global effects, the triggering of convection by boundary layer dynamics is analyzed over the TP, but also in the Northern Hemisphere over the Rocky Mountains. It is found that ST and BT are strong over both high-elevation regions. The strong thermal turbulence and large-scale ascending motion jointly result in obvious positive values of PBLH–LCL (lifting condensation level) under low relative humidity (RH) conditions over the TP. The obvious large-scale subsidence on both sides of the Rocky Mountains, especially the western side, leads to inversion above the PBL and lower RH within the PBL, which further leads to negative values of PBLH–LCL and decreased low cloud cover (LCC) in most parts of the Rocky Mountains. The slightly greater-than-zero PBLH–LCL corresponds spatially to increased LCC in the partial regions of the central Rocky Mountains. Thus, less LCC is generated at the Rocky Mountains compared to the TP.

Considerable effort has been devoted to developing adeno-associated virus (AAV)-based vectors for gene therapy in cystic fibrosis (CF). As a result of directed evolution and capsid shuffling technology, AAV capsids are available with widespread tropism for airway epithelial cells. For example, AAV2.5T and AAV6.2 are two evolved capsids with improved airway epithelial cell transduction properties over their parental serotypes. However, limited research has been focused on identifying their specific cellular tropism. Restoring cystic fibrosis transmembrane conductance regulator (CFTR) expression in surface columnar epithelial cells is necessary for the correction of the CF airway phenotype. Basal cells are a progenitor population of the conducting airways responsible for replenishing surface epithelial cells (including secretory cells and ionocytes), making correction of this cell population vital for a long-lived gene therapy strategy. In this study, we investigate the tropism of AAV capsids for three cell types in primary cultures of well-differentiated human airway epithelial (HAE) cells and primary human airway basal cells. We observed that AAV2.5T transduced surface epithelial cells better than AAV6.2, while AAV6.2 transduced airway basal cells better than AAV2.5T. We also investigated a recently developed capsid, AAV6.2FF, which has two surface tyrosines converted to phenylalanines. Next, we incorporated reciprocal mutations to create AAV capsids with further improved surface and basal cell transduction characteristics. Lastly, we successfully employed a split-intein approach using AAV to deliver an adenine base editor (ABE) to repair the CFTRR553X mutation. Our results suggest that rational incorporation of AAV capsid mutations improves AAV transduction of the airway surface and progenitor cells and may ultimately lead to improved pulmonary function in people with CF.

Clinical genome editing is emerging for rare disease treatment, but one of the major limitations is the targeting of CRISPR editors’ delivery. We delivered base editors to the retinal pigmented epithelium (RPE) in the mouse eye using silica nanocapsules (SNCs) as a treatment for retinal degeneration. Leber congenital amaurosis type 16 (LCA16) is a rare pediatric blindness caused by point mutations in the KCNJ13 gene, a loss of function inwardly rectifying potassium channel (Kir7.1) in the RPE. SNCs carrying adenine base editor 8e (ABE8e) mRNA and sgRNA precisely and efficiently corrected the KCNJ13W53X/W53X mutation. Editing in both patient fibroblasts (47%) and human induced pluripotent stem cell–derived RPE (LCA16-iPSC-RPE) (17%) showed minimal off-target editing. We detected functional Kir7.1 channels in the edited LCA16-iPSC-RPE. In the LCA16 mouse model (Kcnj13W53X/+ΔR), RPE cells targeted SNC delivery of ABE8e mRNA preserved normal vision, measured by full-field electroretinogram (ERG). Moreover, multifocal ERG confirmed the topographic measure of electrical activity primarily originating from the edited retinal area at the injection site. Preserved retina structure after treatment was established by optical coherence tomography (OCT). This preclinical validation of targeted ion channel functional rescue, a challenge for pharmacological and genomic interventions, reinforced the effectiveness of nonviral genome-editing therapy for rare inherited disorders.

IntroductionEvidence suggests that executive function (EF) may play a key role in development of PTSD, possibly influenced by factors such as trauma type and timing. Since EF can be improved through intervention, it may be an important target for promoting resilience to trauma exposure. However, more research is needed to understand the relation between trauma exposure, EF, and PTSD. The goal of this study was to improve understanding of EF as a potential antecedent or protective factor for the development of PTSD among military personnel.MethodIn a cohort of U.S. Marines and Navy personnel (N = 1,373), the current study tested the association between exposure to traumatic events (pre-deployment and during deployment) and PTSD severity, and whether EF moderated these associations. Three types of pre-deployment trauma exposure were examined: cumulative exposure, which included total number of events participants endorsed as having happened to them, witnessed, or learned about; direct exposure, which included total number of events participants endorsed as having happened to them; and interpersonal exposure, which included total number of interpersonally traumatic events participants’ endorsed. EF was measured using the Penn Computerized Neurocognitive Battery.ResultsEF was associated with less PTSD symptom severity at pre-deployment, even when adjusting for trauma exposure, alcohol use, traumatic brain injury, and number of years in the military. EF also moderated the relation between cumulative trauma exposure and interpersonal trauma exposure and PTSD, with higher EF linked to a 20 and 33% reduction in expected point increase in PTSD symptoms with cumulative and interpersonal trauma exposure, respectively. Finally, higher pre-deployment EF was associated with reduced PTSD symptom severity at post-deployment, independent of deployment-related trauma exposure and adjusting for pre-deployment PTSD.ConclusionOur results suggest that EF plays a significant, if small role in the development of PTSD symptoms after trauma exposure among military personnel. These findings provide important considerations for future research and intervention and prevention, specifically, incorporating a focus on improving EF in PTSD treatment.

In Earth observation, multimodal data fusion is an intuitive strategy to break the limitation of individual data. Complementary physical contents of data sources allow comprehensive and precise information retrieval. With current satellite missions, such as ESA Copernicus programme, various data will be accessible at an affordable cost. Future applications will have many options for data sources. Such a privilege can be beneficial only if algorithms are ready to work with various data sources. However, current data fusion studies mostly focus on the fusion of two data sources. There are two reasons; first, different combinations of data sources face different scientific challenges. For example, the fusion of synthetic aperture radar (SAR) data and optical images needs to handle the geometric difference, while the fusion of hyperspectral and multispectral images deals with different resolutions on spatial and spectral domains. Second, nowadays, it is still both financially and labour expensive to acquire multiple data sources for the same region at the same time. In this paper, we provide the community with a benchmark multimodal data set, MDAS, for the city of Augsburg, Germany. MDAS includes synthetic aperture radar data, multispectral image, hyperspectral image, digital surface model (DSM), and geographic information system (GIS) data. All these data are collected on the same date, 7 May 2018. MDAS is a new benchmark data set that provides researchers rich options on data selections. In this paper, we run experiments for three typical remote sensing applications, namely, resolution enhancement, spectral unmixing, and land cover classification, on MDAS data set. Our experiments demonstrate the performance of representative state-of-the-art algorithms whose outcomes can serve as baselines for further studies. The dataset is publicly available at https://doi.org/10.14459/2022mp1657312 (Hu et al., 2022a) and the code (including the pre-trained models) at https://doi.org/10.5281/zenodo.7428215 (Hu et al., 2022b).

The nonlinear rational model is a generalized nonlinear model and has been gradually applied in modelling many dynamic processes. The parameter identification of a class of nonlinear rational models is studied in this paper. This identification problem is very challenging because of the complexity of the rational model and the coupling between model inputs and outputs. To identify the nonlinear model, a bias compensated multi-innovation stochastic gradient algorithm is presented. The multi-innovation technique replacing the scalar innovation with an information vector is adopted to accelerate the traditional stochastic gradient algorithm. However, the estimate obtained by the accelerated algorithm is biased because of the correlation between the information vector and the noise. To overcome this difficulty, a bias compensation strategy is used. The bias is calculated and compensated to get an unbiased estimate. Theoretical analysis shows that the proposed algorithm can give biased estimates with linear complexity. The proposed algorithm is validated by a numerical experiment and the modelling of the propylene catalytic oxidation.

Zinc finger (ZF) arrays are programmable DNA-binding proteins. Here the authors report ZF-DddA-derived cytosine base editors (DdCBEs) and optimise their architectures to improve targeting; they apply these variants in vitro and in vivo to mitochondrial base editing and show higher editing than ZF deaminases.

Abstract Base editing introduces precise single-nucleotide edits in genomic DNA and has the potential to treat genetic diseases such as the blistering skin disease recessive dystrophic epidermolysis bullosa (RDEB), which is characterized by mutations in the COL7A1 gene and type VII collagen (C7) deficiency. Adenine base editors (ABEs) convert A-T base pairs to G-C base pairs without requiring double-stranded DNA breaks or donor DNA templates. Here, we use ABE8e, a recently evolved ABE, to correct primary RDEB patient fibroblasts harboring the recurrent RDEB nonsense mutation c.5047 C > T (p.Arg1683Ter) in exon 54 of COL7A1 and use a next generation sequencing workflow to interrogate post-treatment outcomes. Electroporation of ABE8e mRNA into a bulk population of RDEB patient fibroblasts resulted in remarkably efficient (94.6%) correction of the pathogenic allele, restoring COL7A1 mRNA and expression of C7 protein in western blots and in 3D skin constructs. Off-target DNA analysis did not detect off-target editing in treated patient-derived fibroblasts and there was no detectable increase in A-to-I changes in the RNA. Taken together, we have established a highly efficient pipeline for gene correction in primary fibroblasts with a favorable safety profile. This work lays a foundation for developing therapies for RDEB patients using ex vivo or in vivo base editing strategies.

Abstract High-energy tau neutrinos are rarely produced in atmospheric cosmic-ray showers or at cosmic particle accelerators, but are expected to emerge during neutrino propagation over cosmic distances due to flavor mixing. When high energy tau neutrinos interact inside the IceCube detector, two spatially separated energy depositions may be resolved, the first from the charged current interaction and the second from the tau lepton decay. We report a novel analysis of 7.5 years of IceCube data that identifies two candidate tau neutrinos among the 60 “High-Energy Starting Events” (HESE) collected during that period. The HESE sample offers high purity, all-sky sensitivity, and distinct observational signatures for each neutrino flavor, enabling a new measurement of the flavor composition. The measured astrophysical neutrino flavor composition is consistent with expectations, and an astrophysical tau neutrino flux is indicated at 2.8 $$\sigma $$ σ significance.

Previous work has described a neuroprosthesis to directly decode full words in real time during attempts to speak. Here the authors demonstrate that a patient with anarthria can control this neuroprosthesis to spell out intended messages in real time using attempts to silently speak.

Dynamic monitoring of geological hazards is an important project. Photogrammetry plays an important role in geological hazard monitoring, because of its advantages of convenient data processing, low cost, non-contact, direct texture information and intricate 3-D real scene model. For the traditional photogrammetry can not meet the needs of dynamic monitoring, based on multi-period nap-of-the-object photogrammetry, this paper obtains high-precision images and produces a refined 3D real scene model to carry out the dynamic monitoring of geological disasters. A deformation detection method of geological hazards based on the comparison of three-dimensional model differences is proposed to locate the position with serious deformation. Then, based on the severely deformed area, the multi-period generalized orthophotos are produced, and the image feature matching is used to find the homonymous points between the generalized orthophotos. The two-dimensional and three-dimensional coordinate forward and inverse transformation of the generalized orthophotos are used to calculate the size and direction of the deformation displacement, analyze the deformation trend of geological disasters, and finally realize accurate monitoring of the deformation trend of geological disasters. The results show that the deformation area detection method proposed in this paper is simple and effective, which can quickly find the deformation position. The deformation trend prediction based on multi-period generalized orthophotos is feasible, and the displacement with deformation of 3CM can be accurately pointed out.

The extent of surface water has been changing significantly due to climatic change and human activities. However, it is challenging to capture the interannual changes of inland water bodies due to their high seasonal variation and abrupt change. In this paper, a global annual surface water cover frequency dataset (GLOBMAP SWF) was generated from the MODIS land surface reflectance products during 2000–2020 to describe the seasonal and interannual dynamics of surface water. Surface water cover frequency (SWF) was proposed as the percentage of the time period when a pixel is covered by water in a year. Instead of determination of the water directly, the SWF was estimated indirectly by identifying land observations among annual clear-sky observations to reduce the influence of clouds and variability of water bodies and surface background characteristics, which helps to improve the applicability of the algorithm for different regions across the globe. The generated dataset shows better performances for frozen water, saline lakes, bright surfaces and regions with frequent cloud cover compared with the two high-frequency surface water datasets derived from MODIS data, and it captures more intermittent surface water but may underestimate small water bodies when compared with two high-resolution datasets derived from Landsat data. Compared with the high-resolution SWF maps extracted from Sentinel-1 data in eight regions that cover lakes, rivers and wetlands, the R2 reaches 0.46 to 0.97, RMSE ranges from 7.24 % to 22.62 %, and MAE is between 2.07 % and 7.15 %. In 2020, the area of global maximum surface water extent is 3.38×106 km2, of which the permanent surface water accounts for approximately 54 % (1.83×106 km2), and the other 46 % is intermittent surface water (1.55×106 km2). The area of global maximum and permanent surface water has been shrinking since 2001, with a change rate of −7577 and −4315 km2 yr−1 (p), respectively, while the intermittent surface water with the SWF above 50 % has been expanding (1368 km2 yr−1, p). This dataset can be used to analyze the interannual variation and change trend of highly dynamic inland waters extent with consideration of its seasonal variation. The GLOBMAP SWF data are available at https://doi.org/10.5281/zenodo.6462883 (Liu and Liu, 2022).

Multiple linear regression (MLR) models are used to assess the contributions of meteorology/climate and anthropogenic emission control to linear trends of PM2.5 concentration during the period 2013–2018 in three regions in eastern China, namely Beijing–Tianjin–Hebei (BTH), the Yangtze River Delta (YRD), and the Pearl River Delta (PRD). We find that quantitative contributions to the linear trend of PM2.5 derived based on MLR results alone are not credible because a good correlation in the MLR analysis does not imply any causal relationship. As an alternative, we propose that the correlation coefficient should be interpreted as the maximum possible contribution of the independent variable to the dependent variable and the residual should be interpreted as the minimum contribution of all other independent variables. Under the new interpretation, the previous MLR results become self-consistent. We also find that the results of a short-term (2013–2018) analysis are significantly different from those of a long-term (1985–2018) analysis for the period 2013–2018 in which they overlap, indicating that MLR results depend critically on the length of time analyzed. The long-term analysis renders a more precise assessment because of additional constraints provided by the long-term data. We therefore suggest that the best estimates of the contributions of emissions and non-emission processes (including meteorology/climate) to the linear trend in PM2.5 during 2013–2018 are those from the long-term analyses: i.e., emission % and non-emission >49 % for BTH, emission % and non-emission >56 % for YRD, and emission % and non-emission >12 % for PRD.

Abstract CUPID will be a next generation experiment searching for the neutrinoless double $$\beta $$ β decay, whose discovery would establish the Majorana nature of the neutrino. Based on the experience achieved with the CUORE experiment, presently taking data at LNGS, CUPID aims to reach a background free environment by means of scintillating Li $$_{2}$$ 2 $$^{100}$$ 100 MoO $$_4$$ 4 crystals coupled to light detectors. Indeed, the simultaneous heat and light detection allows us to reject the dominant background of $$\alpha $$ α particles, as proven by the CUPID-0 and CUPID-Mo demonstrators. In this work we present the results of the first test of the CUPID baseline module. In particular, we propose a new optimized detector structure and light sensors design to enhance the engineering and the light collection, respectively. We characterized the heat detectors, achieving an energy resolution of (5.9 ± 0.2) keV FWHM at the Q-value of $$^{100}$$ 100 Mo (about 3034 keV). We studied the light collection of the baseline CUPID design with respect to an alternative configuration which features gravity-assisted light detectors’ mounting. In both cases we obtained an improvement in the light collection with respect to past measures and we validated the particle identification capability of the detector, which ensures an $$\alpha $$ α particle rejection higher than 99.9%, fully satisfying the requirements for CUPID.

Understanding the hydrological processes related to snow in global mountainous regions under climate change is necessary for achieving regional water and food security (e.g., the United Nation's Sustainable Development Goals 2 and 6). However, the impacts of future snow changes on the hydrological processes in the high mountains of the “Third Pole” are still largely unclear. In this study, we aimed to project future snow changes and their impacts on hydrology in the upstream region of the Salween River (USR) under two shared socioeconomic pathway (SSP) scenarios (SSP126 and SSP585) using a physically based cryosphere–hydrology model. We found that the climate would become warmer (0.2 ∘C per decade under SSP126 and 0.7 ∘C per decade under SSP585) and wetter (5 mm per decade under SPP126 and 27.8 mm per decade under SSP585) in the USR in the future under these two SSPs. In this context, the snowfall, snow cover, snow water equivalent, and snowmelt runoff are projected to exhibit significant decreasing trends during 1995–2100, and the decreases are projected to be most prominent in summer and autumn. The future (2021–2100) snowmelt runoff is projected to significantly increase in spring compared with the reference period (1995–2014), which would benefit the availability of water resources in the growing season. The annual total runoff would significantly increase in all of the future periods due to increased rainfall, which would increase the availability of water resources within the basin, but the high peak flow that occurs in summer may cause rain flooding with short duration and high intensity. Compared with the reference period (the contribution of snowmelt runoff to the total runoff was determined to be 17.5 %), the rain- and snow-dominated pattern of runoff would shift to a rain-dominated pattern after the near term (2021–2040) under SSP585, whereas it would remain largely unchanged under SSP126. Climate change would mainly change the pattern of the snowmelt runoff, but it would not change the annual hydrograph pattern (dominated by increased rainfall). These findings improve our understanding of the responses of cryosphere–hydrological processes under climate change, providing valuable information for integrated water resource management, natural disaster prevention, and ecological environmental protection at the Third Pole.

Abstract The reconstruction of event-level information, such as the direction or energy of a neutrino interacting in IceCube DeepCore, is a crucial ingredient to many physics analyses. Algorithms to extract this high level information from the detector’s raw data have been successfully developed and used for high energy events. In this work, we address unique challenges associated with the reconstruction of lower energy events in the range of a few to hundreds of GeV and present two separate, state-of-the-art algorithms. One algorithm focuses on the fast directional reconstruction of events based on unscattered light. The second algorithm is a likelihood-based multipurpose reconstruction offering superior resolutions, at the expense of larger computational cost.

9Cr-F/M−xSi (x = 0–1.0 wt%) steels were fabricated through vacuum induction melting technique and processed by hot forging, hot rolling, normalizing and tempering, subsequently. Their microstructure and mechanical properties were characterized using OM, SEM, TEM, Vickers hardness tester and tensile tester. The steel has a typical ferrite/martensitic structure, with M23C6 and MX phases precipitated at the martensite lath boundary or in the lath. With Si content increasing, the average ultimate tensile strength (UTS) and hardness of 9Cr-F/M−xSi increase simultaneously from 678 MPa and 235 HV for 9Cr-F/M−0Si steel to 788 MPa and 265 HV for 9Cr-F/M−1.0Si steel, respectively, while the total elongation kept almost constant at 22.5%. The main strengthening mechanism is the solid solution strengthening due to silicon addition and the change in the carbide precipitation behavior caused no remarkable hardening contribution. These results can provide a reference for the composition design of structural materials for nuclear reactors.

SUMMARY: With the overselection of broiler body weight (BW) and breast muscle weight (BMW), the incidence of leg disease has been gradually increasing, which has seriously affected the welfare and industrial economic development of broilers. In this study, we used gait score and X-ray to evaluate the leg health of fast large white-feather broiler chickens at the age of 6 to 7 wk. The combined use of the 2 methods improved the detection rate and accuracy of diagnosing chicken leg disease. Moreover, more than 70% of chickens with abnormal gait scores also appeared abnormal on X-ray. At the same time, the 40-day BW, 42-day BMW, 28- to 40-day body weight gain (BWG) and tibial bone strength (BS) of the abnormal broilers were significantly lower than those of normal chickens. The 28- to 40-day feed conversion rate (FCR) significantly increased relative to normal chickens (P < 0.05). The comprehensive application of this method would be more suitable for evaluating of commercial broiler leg diseases, and providing a more complete set of in vitro evaluation criteria for broiler leg diseases.