Search

Hydrological models with conceptual tipping bucket and process-based evapotranspiration formulations are the most common tools in hydrology. However, these models consistently fail to replicate long-term and slow dynamics of a hydrological system, indicating the need for model augmentation and a shift in formulation approach. This study employed an entirely different approach – system dynamics – towards more realistic replication of the observed slow hydrological behaviors at inter-annual and inter-decadal scales. Using the headwaters of Baiyang Lake in China as a case study, the endogenous linking structure of the hydrological system was gradually unraveled from 1982 to 2015 through wavelet analysis, Granger's causality test, and a system dynamics model. The wavelet analysis and Granger's causality test identified a negatively correlated and bidirectional causal relationship between actual evapotranspiration and catchment water storage change across distinct climatic periodicities, and the system dynamics approach suggested a combined structure of a vegetation reinforcing feedback and a soil water–vegetation balancing feedback in the hydrological system. The system dynamics' structure successfully captured the slow hydrological behaviors under both natural and human-intervention scenarios, demonstrating a self-sustained oscillation arising within the system's boundary. Our results showed that the interaction between the vegetation structure and the soil-bound water dominates the hydrological process at an inter-annual scale, while the interaction between the climatic oscillation and the soil-water-holding capacity dominates the hydrological process at an inter-decadal scale. Conventional hydrological models, which typically employ physiological-based evapotranspiration formulations and assume invariable soil characteristics, ignore vegetation structure change at the inter-annual scale and soil-water-holding capacity change at the inter-decadal scale, leading to failure in predicting the observed long-term hydrological behaviors. The system dynamics model is in its early stage with applications primarily confined to water-stressed regions and long-term scales. However, the novel insights proposed in our study, including the different hierarchies corresponding to distinct mechanisms and timescales and the endogenous linking structure among stocks being a more important driver of the hydrological behaviors, offer potential solutions for better understanding a hydrological system and guidelines for improving the configuration and performance of conventional hydrological models.

Land-use and land-cover change (LUCC) is a key factor in determining regional vegetation greenness, impacting terrestrial carbon, water, and energy budgets. As a global LUCC hot spot, Southeast Asia has experienced intensive cropland and plantation expansion over the past 50 years; however, the impacts of these changes on the regional greenness have not been elucidated. Here, we harmonized multiple land-cover datasets, and used the satellite-derived leaf area index (LAI) in combination with a machine learning approach to quantify the impacts of LUCC on vegetation greenness in insular Southeast Asia (i.e. Peninsular Malaysia, Sumatra, and Borneo). We found that the regional LAI shows almost no trend (0.04 × 10−2 m2 m−2 yr−1) from 2000 to 2016: the net effect of an increased LAI (+5.71 × 10−2 m2 m−2 yr−1) due to CO2 fertilization is offset by a decreased LAI mainly due to cropland expansion (−4.46 × 10−2 m2 m−2 yr−1). The impact of croplands on greenness in Southeast Asia contrasts with that in India and China. Meanwhile, oil palm expansion and climate change induced only small decreases in the LAI in Southeast Asia (−0.41 × 10−2 and −0.38 × 10−2 m2 m−2 yr−1, respectively). Our research unveils how the LAI changes with different LUCC processes in Southeast Asia and offers a quantitative framework to assess vegetation greenness under different land-use scenarios.

Summary: Continuing advancements in human pluripotent stem cell (hPSC)-derived complex three-dimensional (3D) cardiac tissues require the development of novel technologies or adaptation of existing technologies to understand the physiology of the derived 3D cardiac tissues. In this protocol, we describe the use of multielectrode array (MEA) and sharp electrode electrophysiology techniques to investigate the electrical properties of 3D cardiac organoids. This protocol deciphers the electrical behavior of 3D cardiac organoids at both the single-cell level and tissue level. : Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics.

Abstract Age-related microangiopathy, also known as small vessel disease (SVD), causes damage to the brain, retina, liver, and kidney. Based on the DNA damage theory of aging, we reasoned that genomic instability may underlie an SVD caused by dominant C-terminal variants in TREX1, the most abundant 3′−5′ DNA exonuclease in mammals. C-terminal TREX1 variants cause an adult-onset SVD known as retinal vasculopathy with cerebral leukoencephalopathy (RVCL or RVCL-S). In RVCL, an aberrant, C-terminally truncated TREX1 mislocalizes to the nucleus due to deletion of its ER-anchoring domain. Since RVCL pathology mimics that of radiation injury, we reasoned that nuclear TREX1 would cause DNA damage. Here, we show that RVCL-associated TREX1 variants trigger DNA damage in humans, mice, and Drosophila, and that cells expressing RVCL mutant TREX1 are more vulnerable to DNA damage induced by chemotherapy and cytokines that up-regulate TREX1, leading to depletion of TREX1-high cells in RVCL mice. RVCL-associated TREX1 mutants inhibit homology-directed repair (HDR), causing DNA deletions and vulnerablility to PARP inhibitors. In women with RVCL, we observe early-onset breast cancer, similar to patients with BRCA1/2 variants. Our results provide a mechanistic basis linking aberrant TREX1 activity to the DNA damage theory of aging, premature senescence, and microvascular disease.

A closed-loop control framework is developed for the co-flow jet (CFJ) airfoil by combining the numerical flow field environment of a CFJ0012 airfoil with a deep reinforcement learning (DRL) module called tensorforce integrated in Python. The DRL agent, which is trained through interacting with the numerical flow field environment, is capable of acquiring a policy that instructs the mass flow rate of the CFJ to make the stalled airfoil at an angle of attack (AoA) of 18 degrees reach a specific high lift coefficient set to 2.0, thereby effectively suppressing flow separation on the upper surface of the airfoil. The subsequent test shows that the policy can be implemented to find a precise jet momentum coefficient of 0.049 to make the lift coefficient of the CFJ0012 airfoil reach 2.01 with a negligible error of 0.5%. Moreover, to evaluate the generalization ability of the policy trained at an AoA of 18 degrees, two additional tests are conducted at AoAs of 16 and 20 degrees. The results show that, although using the policy gained under another AoA cannot help the lift coefficient of the airfoil reach a set target of 2 accurately, the errors are acceptable with less than 5.5%, which means the policy trained under an AoA of 18 degrees can also be applied to other AoAs to some extent. This work is helpful for the practical application of CFJ technology, as the closed-loop control framework ensures good aerodynamic performance of the CFJ airfoil, even in complex and changeable flight conditions.

The thermal performance of rural building envelopes is mostly non-standardized in Northern China, resulting in significant heat loss. In this study, we take, as an example, the central area of Liaoning province, with the objective of proposing some low-cost and energy-efficient solutions. Through our investigations, we found that heating energy consumption was reduced by 20% and construction costs increased by less than CNY 8000 (USD 1108), which can be accepted by rural residents. In order to achieve this target, the NSGA-II algorithm integrated with Rhino + Grasshopper and EnergyPlus simulation kernel was used to establish a thermal performance optimization model for the heat transfer of rural building envelopes in this severe cold region. Among the above-calculated Pareto optimal solutions, the recommended thickness of insulation layers for room floors, roofs, and external walls was about 70 mm, 50 mm, and 40 mm, respectively. Furthermore, we tried to reduce the window-to-wall ratio as much as possible. Finally, based on both the lower building renovation cost and energy-saving rate, three technical solutions from which rural residents could select, according to their specific needs, are put forward.

Given the increasing complexity of the chemical composition of PM2.5, identifying and quantitatively assessing the contributions of pollution sources has played an important role in formulating policies to control particle pollution. This study provides a comprehensive assessment between PM2.5 chemical characteristics, sources, and health risks based on sampling data conducted over 1 year (March 2018 to February 2019) in Nanjing. Results show that PM2.5 exhibits a distinct variation across different seasons, which is primarily driven by emissions, meteorological conditions, and the chemical conversion of gaseous pollutants. First, the chemical mass reconstruction shows that secondary inorganic aerosols (62.5 %) and carbonaceous aerosols (21.3 %) contributed most to the PM2.5 mass. The increasing oxidation rates of SO2 and NO2 from summer to winter indicate that the secondary transformation of gaseous pollutants is strongly positively correlated with relative humidity. Second, the positive matrix factorization (PMF) method shows that identified PM2.5 sources include secondary inorganic aerosol source (SIS, 42.5 %), coal combustion (CC, 22.4 %), industry source (IS, 17.3 %), vehicle emission (VE, 10.7 %), fugitive dust (FD, 5.8 %), and other sources (1.3 %). The Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model and the concentration-weighted trajectory (CWT) analysis are used to further explore different spatial distributions and regional transport of sources. The concentrations (10–11 µg m−3) of SIS and CC distribute in Nanjing and central China in winter. The concentrations (8–10 µg m−3) of IS and VE are potentially located north of Jiangsu, Anhui, and Jiangxi. Finally, the health risk assessment indicates that the carcinogenic and non-carcinogenic risks of toxic elements (Cr, As, Ni, Mn, V, and Pb) mainly come from IS, VE, and CC, which are within the tolerance or acceptable level. Although the main source of pollution in Nanjing is SIS at present, we should pay more attention to the health burden of vehicle emissions, coal combustion, and industrial processes.

Abstract The determinants of severe disease caused by West Nile virus (WNV) and why only ~1% of individuals progress to encephalitis remain poorly understood. Here, we use human and mouse enteroids, and a mouse model of pathogenesis, to explore the capacity of WNV to directly infect gastrointestinal (GI) tract cells and contribute to disease severity. At baseline, WNV poorly infects human and mouse enteroid cultures and enterocytes in mice. However, when STAT1 or type I interferon (IFN) responses are absent, GI tract cells become infected, and this is associated with augmented GI tract and blood-brain barrier (BBB) permeability, accumulation of gut-derived molecules in the brain, and more severe WNV disease. The increased gut permeability requires TNF-α signaling, and is absent in WNV-infected IFN-deficient germ-free mice. To link these findings to human disease, we measured auto-antibodies against type I IFNs in serum from WNV-infected human cohorts. A greater frequency of auto- and neutralizing antibodies against IFN-α2 or IFN-ω is present in patients with severe WNV infection, whereas virtually no asymptomatic WNV-infected subjects have such antibodies (odds ratio 24 [95% confidence interval: 3.0 − 192.5; P = 0.003]). Overall, our experiments establish that blockade of type I IFN signaling extends WNV tropism to enterocytes, which correlates with increased gut and BBB permeability, and more severe disease.

Decreasing sea ice extent caused by climate change is affecting the carbon cycle of the Arctic Ocean. In this study, surface sediments across the western Arctic Ocean are investigated to characterize sources of sedimentary organic carbon (OC). Bulk organic parameters (total organic carbon, total nitrogen, δ13Corg, and δ15N) and molecular organic biomarkers (e.g., sterols and highly branched isoprenoids – HBIs) are combined to distinguish between sympagic, pelagic, and terrestrial OC sources. Their downcore profiles generated at the Chukchi Sea R1 core site (74∘ N) are then used to evaluate changes in the relative contribution of these components of sedimentary OC over the last 200 years with decreasing sea ice. Our data evidence that, from the 1820s to the 1930s, prevailing high sea ice cover inhibited in situ primary production, resulting in prominent land-derived material in sediments. Then, from the 1930s to the 1980s, primary production started increasing with the gradual decline of summer sea ice. The ratio of sympagic and pelagic OC began to rise to account for the larger portion of sedimentary OC. Since the 1980s, accelerated sea ice loss led to enhanced primary production, stabilizing over the last decades due to freshwater-induced surface ocean stratification in summer.

Granite residual soil landslides are widely distributed in the southeast of Guangxi, China. They pose threats to local communities, economic development and ecological restoration. To understand the failure mode, the landslide can provide a scientific basis for early warning and prevention. In this study, we conducted artificial flume model tests to investigate the failure mode of granite residual soil landslide. The macroscopic phenomena of landslides were observed and summarized. The response and variations of soil moisture content and pore water pressure were analyzed. And the discrepancies in landslide initiation were explored. The results had three aspects: (1) the response of volume moisture content was not synchronized with that of pore water pressure. Their variations were influenced by initial dry density, slope angle and rainfall intensity. The fluctuation of pore water pressure depended on soil mechanical behavior and its diffusion. (2) The differences in the formation process of granite residual soil landslides included the initiation time and mode. The starting time of landslide was delayed with increasing initial dry density and slope angle but shortened with increasing rainfall intensity. The failure mode could be changed from a sudden type to a progressive type due to the increase in initial dry density. (3) There are five stages in the landslide mobilization as follows: rain infiltration and crack generation, soil slide at the slope toe, occurrence of surface runoff and soil erosion, formation of steep-free surface, and soil slide at the upper slope. This research can provide valuable reference for the prevention and early warning of granite residual soil landslide in southeastern Guangxi.

Cu-Mn hopcalite, as a conventional catalyst showing potential in many chemical reactions, has been rarely researched for its applications in H2O2-activated Fenton-like reactions for the decomposition of refractory pollutants. In this work, an amorphous Cu-Mn hopcalite catalyst (CMO-200) was prepared by simple calcination of their precursors at 200 °C. At circumneutral pH, CMO-200 behaved more efficiently than several commercial manganese oxides, CuO, and Fe2O3, as well as its crystalline analogues in catalytic degradation of tetracycline (TC) with H2O2 as oxidant. The excellent performance can be kept without remarkable loss during its 6 cycles of reuse. Singlet oxygen, superoxide anion radical and hydroxyl radical were found to be active species for the degradation reaction. The amorphous structure and high contents of chemically adsorbed oxygen, Cu+ and Mn4+ species are speculated as the reasons for its high catalytic performance.

Forest roads provide access to remote wooded areas, serving as key transportation routes and contributing to human impact on the local environment. However, large animals, such as bears (Ursus sp.), moose (Alces alces), and caribou (Rangifer tarandus caribou), are affected by their presence. Many publicly available road layers are outdated or inaccurate, making the assessment of landscape objectives difficult. To address these gaps in road location data, we employ CubeSat Imagery from the Planet constellation to predict the occurrence of road probabilities using a SegNet Convolutional Neural Network. Our research examines the potential of a pre-trained neural network (VGG-16 trained on ImageNet) transferred to the remote sensing domain. The classification is refined through post-processing, which considers spatial misalignment and road width variability. On a withheld test subset, we achieve an overall accuracy of 99.1%, a precision of 76.1%, and a recall of 91.2% (F1-Score: 83.0%) after considering these effects. We investigate the performance with respect to canopy coverage using a spectral greenness index, topography (slope and aspect), and land cover metrics. Results found that predictions are best in flat areas, with low to medium canopy coverage, and in the forest (coniferous and deciduous) land cover classes. The results are vectorized into a drivable road network, allowing for vector-based routing and coverage analyses. Our approach digitized 14,359 km of roads in a 23,500 km2 area in British Columbia, Canada. Compared to a governmental dataset, our method missed 10,869 km but detected an additional 5774 km of roads connected to the network. Finally, we use the detected road locations to investigate road age by accessing an archive of Landsat data, allowing spatiotemporal modelling of road access to remote areas. This provides important information on the development of the road network over time and the calculation of impacts, such as cumulative effects on wildlife.

Intestinal dysmotility syndromes have been epidemiologically associated with several antecedent bacterial and viral infections. To model this phenotype, we previously infected mice with the neurotropic flavivirus West Nile virus (WNV) and demonstrated intestinal transit defects. Here, we found that within 1 week of WNV infection, enteric neurons and glia became damaged, resulting in sustained reductions of neuronal cells and their networks of connecting fibers. Using cell-depleting antibodies, adoptive transfer experiments, and mice lacking specific immune cells or immune functions, we show that infiltrating WNV-specific CD4+ and CD8+ T cells damaged the enteric nervous system (ENS) and glia, which led to intestinal dysmotility; these T cells used multiple and redundant effector molecules including perforin and Fas ligand. In comparison, WNV-triggered ENS injury and intestinal dysmotility appeared to not require infiltrating monocytes, and damage may have been limited by resident muscularis macrophages. Overall, our experiments support a model in which antigen-specific T cell subsets and their effector molecules responding to WNV infection direct immune pathology against enteric neurons and supporting glia that results in intestinal dysmotility. [ABSTRACT FROM AUTHOR]

BackgroundAlthough SARS-CoV-2 vaccines have proven effective in eliciting a protective immune response in healthy individuals, their ability to induce a durable immune response in immunocompromised individuals remains poorly understood. Primary antibody deficiency (PAD) syndromes are among the most common primary immunodeficiency disorders in adults and are characterized by hypogammaglobulinemia and impaired ability to mount robust antibody responses following infection or vaccination.MethodsHere, we present an analysis of both the B and T cell response in a prospective cohort of 30 individuals with PAD up to 150 days following initial COVID-19 vaccination and 150 days post mRNA booster vaccination.ResultsAfter the primary vaccination series, many of the individuals with PAD syndromes mounted SARS-CoV-2 specific memory B and CD4+ T cell responses that overall were comparable to healthy individuals. Nonetheless, individuals with PAD syndromes had reduced IgG1+ and CD11c+ memory B cell responses following the primary vaccination series, with the defect in IgG1 class-switching rescued following mRNA booster doses. Boosting also elicited an increase in the SARS-CoV-2-specific B and T cell response and the development of Omicron-specific memory B cells in COVID-19-naïve PAD patients. Individuals that lacked detectable B cell responses following primary vaccination did not benefit from booster vaccination.ConclusionTogether, these data indicate that SARS-CoV-2 vaccines elicit memory B and T cells in most PAD patients and highlights the importance of booster vaccination in immunodeficient individuals.

Mn3Sn is an anti-ferromagnetic material which displays a large magneto-optical Kerr effect, despite lacking a ferromagnetic moment. Here, the authors show that likewise, Mn3Sn, also presents a particularly large magneto-optical Voigt signal, with a negligible change in the quench time over a wide temperature range.

STING gain-of-function mutations cause STING-associated vasculopathy with onset in infancy (SAVI) in humans, a disease characterized by spontaneous lung inflammation and fibrosis. Mice with STING gain-of-function mutations (SAVI mice) develop αβ T cell–dependent lung disease and also lack lymph nodes. Although SAVI has been regarded as a type I interferonopathy, the relative contributions of the three interferon receptors are incompletely understood. Here, we show that STING gain of function led to upregulation of IFN-γ–induced chemokines in the lungs of SAVI mice and that deletion of the type II IFN receptor (IFNGR1), but not the type I IFN receptor (IFNAR1) or type III IFN receptor (IFNλR1), ameliorated lung disease and restored lymph node development in SAVI mice. Furthermore, deletion of IFNGR1, but not IFNAR1 or IFNλR1, corrected the ratio of effector to Tregs in SAVI mice and in mixed bone marrow chimeric mice. Finally, cultured SAVI mouse macrophages were hyperresponsive to IFN-γ, but not IFN-β, in terms of Cxcl9 upregulation and cell activation. These results demonstrate that IFNGR1 plays a major role in autoinflammation and immune dysregulation mediated by STING gain of function.

Ecohydrological sensitivity, defined as the response intensity of streamflow to per unit vegetation change is an integrated indicator for assessing hydrological sensitivity to vegetation change. Understanding ecohydrological sensitivity and its influencing factors is crucial for managing water supply, reducing water-related hazards and ensuring aquatic functions by vegetation management. Yet, there is still a systematic assessment on ecohydrological sensitivity and associated driving factors especially at a seasonal scale lacking. In this study, 14 large watersheds across various environmental gradients in China were selected to quantify their ecohydrological sensitivities at a seasonal scale and to examine the role of associated influencing factors such as climate, vegetation, topography, soil and landscape. Based on the variables identified by correlation analysis and factor analysis, prediction models of seasonal ecohydrological sensitivity were constructed to test their utilities for the design of watershed management and protection strategies. Our key findings were the following: (1) ecohydrological sensitivities were more sensitive under dry conditions than wet conditions – for example, 1 % LAI (leaf area index) change, on average, induced 5.05 % and 1.96 % change in the dry and wet season streamflow, respectively; (2) seasonal ecohydrological sensitivities were highly variable across the study watersheds with different climate conditions, dominant soil types and hydrological regimes; and (3) the dry season ecohydrological sensitivity was mostly determined by topography (slope, slope length, valley depth and downslope distance gradient), soil (topsoil organic carbon and topsoil bulk density) and vegetation (LAI), while the wet season ecohydrological sensitivity was mainly controlled by soil (topsoil-available water-holding capacity), landscape (edge density) and vegetation (leaf area index). Our study provided a useful and practical framework to assess and predict ecohydrological sensitivities at the seasonal scale. The established ecohydrological sensitivity prediction models can be applied to ungauged watersheds or watersheds with limited hydrological data to help decision makers and watershed managers effectively manage hydrological impacts through vegetation restoration programs. We conclude that ecohydrological sensitivities at the seasonal scale are varied by climate, vegetation and watershed property, and their understanding can greatly support the management of hydrological risks and protection of aquatic functions.

Abstract Background Osteoporosis is becoming more prevalent in aging societies worldwide, and the economic burden attributable to osteoporotic fractures is substantial. The medications presently available to treat osteoporosis have side effects. Acupuncture is widely used for treating osteoporotic postmenopausal women because it is non-invasive and has fewer side effects, but the powerful clinical evidence for its efficacy remains insufficient. Our study intends to explore the effect of overall adjustment acupuncture (OA) in the treatment of postmenopausal osteoporosis (PMOP). Methods/design This study is a randomized, sham-controlled, patient- and assessor-blinded trial and aims to evaluate the effect of OA in women with PMOP. We will recruit 104 women aged 45–70 years with a diagnosis of PMOP. Participants will be randomly allocated in a 1:1 ratio to the OA group and the sham acupuncture (SA) group. Both groups will receive real herbal medicine treatment as a basic treatment twice a day for 3 months, the OA group receives real acupuncture treatment and the SA group receives placebo acupuncture treatment (non-penetrating, sham skin-needle therapy, sham cupping). All patients will receive acupuncture treatment twice per week for 3 months. The primary outcome is bone mineral density (BMD) and the secondary outcomes include estradiol (E2), follicle-stimulating hormone (FSH), bone gla protein (BGP), bone alkaline phosphatase (BALP), total antioxidant capacity (TAC), advanced oxidation protein products (AOPP), PPARγ, β-catenin, FoxO3a levels, visual analog pain scale score (VAS), Traditional Chinese medicine (TCM) syndrome scores and quality of daily life score (QOL). Outcome measures will be collected at baseline, middle of the treatment (1.5 months), the end of treatment (3 months). The present protocol followed the SPIRIT guidelines and fulfills the SPIRIT Checklist. Conclusion This study will be conducted to compare the efficacy of OA versus SA. This trial should help to evaluate whether OA can effectively prevent and treat PMOP by improving the estrogen levels of postmenopausal women. The mechanism is to improve the imbalance of osteogenic differentiation and lipogenesis of bone-marrow cells under oxidative stress. Trial registration Chinese Clinical Trial Registry, ID: ChiCTR1800017581 . Registered on 5 August 2018. URL: http://www.chictr.org.cn .

We have delineated ten years of urban subsidence derived from continuous GPS stations operated by the Crustal Movement Observational Network of China (CMONOC) within and adjacent to the municipality of Tianjin. A method for obtaining accurate site velocities with respect to a stable regional reference frame is described. CMONOC stations in Jizhou (JIXN) and Baodi (TJBD) districts recorded minor subsidence of approximately 1 to 2 mm yr−1 during the period from 2010 to 2019. One station in Wuqing (TJWQ) district and one station in Binhai (TJBH) district recorded steady subsidence of approximately 5 and 2 cm yr−1 from 2010 to 2019, respectively. One station in Cangzhou (HECX) of Hebei Province, adjacent to Tianjin, recorded steady subsidence of approximately 2.4 cm yr−1 during 2010–2014 and more rapid subsidence of 4 cm yr−1 since 2015. TJWQ recorded the most rapid land subsidence and the most significant seasonal ground oscillations (uplift and subsidence) among these five stations. This study indicates that subsidence rates in Tianjin vary significantly in space and time. Particular attention should be paid, therefore, to extrapolate or infer a rate of subsidence for an area on the basis of a subsidence rate obtained from previous GPS observations or proximal GPS sites. The subsidence time series presented in this study provide reliable “ground truth” and constraints for calibrating or validating subsidence estimations from numerical modeling and repeated surveys using other remote sensing techniques, such as Interferometric Synthetic Aperture Radar (InSAR).

The energy sector has been the highest contributor of green-house gases (GHG) emission in Japan. To reduce GHG emissions, the development and applications of cleaner technologies supported by effective policies are required. In this study, the effectiveness of Japanese government policies related to climate change mitigation especially in the technology development sector was analyzed. To do so, two methodologies; 1) results-based approach (RBA) and 2) case-based approach (CBA) will be combined to test the effectiveness of government policies. This combination was conducted to fill the missing data required to conduct the two methodologies. The merging of the two methodologies produced indexes where the proximity of the performance of each policy measured to it would determine its effectiveness. In order to verify the results, the number of projects related to the policy took place over the years was also observed. The results show that the most effective policies were related to the following technologies: 1) Energy management, 2) Biomass energy production, and 3) Electric power storage.

An experiment was conducted to investigate the effects of dietary riboflavin levels on reproductive performance, riboflavin status, and antioxidant status of laying duck breeders, to estimate the requirement of this vitamin for duck breeders. Different levels crystalline riboflavin (0, 2.5, 5, 10, and 15 mg/kg) were supplemented to a corn–soybean–corn gluten meal basal diet to produce 5 dietary treatments with different analyzed total riboflavin levels (1.48, 3.20, 6.30, 11.71, and 16.83 mg/kg). A total of 80 White Pekin duck breeders aged 40 wk were allotted to 5 dietary treatments of 16 birds each (8 replicates per treatment and 2 breeders per replicate), and all birds were raised individually for 9 wk. At the end of the experiment, reproductive performance, tissue riboflavin concentrations, and antioxidant status of White Pekin duck breeders were measured. The results showed that body weight, egg weight, egg production, and egg fertility were not affected by dietary riboflavin levels. However, among all of the laying duck breeders, the birds fed the basal diet without riboflavin supplementation had the lowest egg hatchability, plasma riboflavin, egg yolk riboflavin, and egg albumen riboflavin (P

Sponges are commonly known as general nutrient providers for the marine ecosystem, recycling organic matter into various forms of bioavailable nutrients such as ammonium and nitrate. In this study we challenge this view. We show that nutrient removal through microbial denitrification is a common feature in six cold-water sponge species from boreal and Arctic sponge grounds. Denitrification rates were quantified by incubating sponge tissue sections with 15NO3--amended oxygen-saturated seawater, mimicking conditions in pumping sponges, and de-oxygenated seawater, mimicking non-pumping sponges. It was not possible to detect any rates of anaerobic ammonium oxidation (anammox) using incubations with 15NH4+. Denitrification rates of the different sponge species ranged from below detection to 97 nmol N cm−3 sponge d−1 under oxic conditions, and from 24 to 279 nmol N cm−3 sponge d−1 under anoxic conditions. A positive relationship between the highest potential rates of denitrification (in the absence of oxygen) and the species-specific abundances of nirS and nirK genes encoding nitrite reductase, a key enzyme for denitrification, suggests that the denitrifying community in these sponge species is active and prepared for denitrification. The lack of a lag phase in the linear accumulation of the 15N-labelled N2 gas in any of our tissue incubations is another indicator for an active community of denitrifiers in the investigated sponge species. Low rates for coupled nitrification–denitrification indicate that also under oxic conditions, the nitrate used to fuel denitrification rates was derived rather from the ambient seawater than from sponge nitrification. The lack of nifH genes encoding nitrogenase, the key enzyme for nitrogen fixation, shows that the nitrogen cycle is not closed in the sponge grounds. The denitrified nitrogen, no matter its origin, is then no longer available as a nutrient for the marine ecosystem. These results suggest a high potential denitrification capacity of deep-sea sponge grounds based on typical sponge biomass on boreal and Arctic sponge grounds, with areal denitrification rates of 0.6 mmol N m−2 d−1 assuming non-pumping sponges and still 0.3 mmol N m−2 d−1 assuming pumping sponges. This is well within the range of denitrification rates of continental shelf sediments. Anthropogenic impact and global change processes affecting the sponge redox state may thus lead to deep-sea sponge grounds changing their role in marine ecosystem from being mainly nutrient sources to becoming mainly nutrient sinks.

Loss-of-function mutations in the depalmitoylating enzyme palmitoyl protein thioesterase 1 (PPT1) cause neuronal ceroid lipofuscinosis (NCL), a devastating neurodegenerative disease. The substrates of PPT1 are largely undescribed, posing a limitation on molecular dissection of disease mechanisms and therapeutic development. Here, we provide a resource identifying >100 novel PPT1 substrates. We utilized Acyl Resin-Assisted Capture (Acyl RAC) and mass spectrometry to identify proteins with increased in vivo palmitoylation in PPT1 knockout (KO) mouse brains. We then validated putative substrates through direct depalmitoylation with recombinant PPT1. This stringent screen elucidated diverse PPT1 substrates at the synapse, including channels and transporters, G-protein-associated molecules, endo/exocytic components, synaptic adhesion molecules, and mitochondrial proteins. Cysteine depalmitoylation sites in transmembrane PPT1 substrates frequently participate in disulfide bonds in the mature protein. We confirmed that depalmitoylation plays a role in disulfide bond formation in a tertiary screen analyzing posttranslational modifications (PTMs). Collectively, these data highlight the role of PPT1 in mediating synapse functions, implicate molecular pathways in the etiology of NCL and other neurodegenerative diseases, and advance our basic understanding of the purpose of depalmitoylation.

One of the main sources of decoherence in silicon electron spin qubits is their interaction with nearby fluctuating nuclear spins. Zhao et al. present a device made from enriched silicon to reduce the nuclear spin density and find its performance is still limited by fluctuations of residual spins.

Abstract Accurate knowledge of spatiotemporal characteristics of land surface energy budget is essential to understand the Earth's surface system. To some extent, the continuous development of remote sensing technology makes the estimation of global high‐resolution surface energy budget possible. However, it is still challenging to accurately derive the global longwave downward radiation (LWDR) from space. In this study, two advanced methods were proposed to estimate clear‐sky LWDR based on Moderate‐resolution Imaging Spectroradiometer (MODIS) products and corresponding ground measured LWDR from several global distributed radiation networks. One is a sensor‐based Random Forest (RF) method that uses MODIS's surface elevation, sensor zenith angle, column precipitable water vapor (PWC), top of atmosphere radiance of band 28, 31, 34, and 36 as inputs; the other is a sensor‐independent nonlinear regression method, which only uses the land surface temperature (LST) and PWC as inputs. The validation results show that the root mean square errors of RF and nonlinear regression method are less than 25.5 W/m2 and bias are less than 0.5 W/m2 under different tenfold cross‐validation schemes. In addition, the sensitivity analysis indicates that the two models are very stable, and the retrieval errors are independent of changes of LST and PWC, and the accuracy does not rely on variations of land cover types, different observing angles, and different seasons. The comparison analysis indicates that the proposed methods are comparable or even better than existing algorithms. More importantly, the proposed sensor‐independent regression method was designed for generality purpose so can easily be utilized with reasonable accuracy.

Quantifying landscape heterogeneity and its organization at different scales is essential for understanding ecosystems and landscapes. Among hundreds of landscape metrics, entropy-related index represents an efficient tool to quantify and characterize landscape patterns. A recent development is Spatial Entropy index (Hs), and it has been validated as flexible and effective in landscape pattern analysis. However, the effects of changing spatial scale on Hs has not been quantified. This paper applies the fractal method to measure the spatial scale (grain size) sensitivity of Hs. Using the initial land-use data of Yanhe watershed, which is located in northwest of China, eleven different spatial scales were created in order to investigate the scale effects on Hs. A linear log–log regression model was then constructed based on the power law to calculate the coefficient of determination (COD) of the model and the fractal dimension (FD) of Hs. The result indicates that Spatial Entropy index shows a robust fractal feature, and it decreases as the spatial scale (or grain size) becomes lager in a moderate degree. In total, we believe that this study will help us to get a better understanding of Hs, and to facilitate further applications of this entropy-related index.

Buildings, where most human activities happen, are one of the most important crucial objects in remote sensing images. Extracting building information is of great significance importance for conducting sustainable development-related researches. The extracted building information is a fundamental data source for further researches, including evaluating the living conditions of people, monitoring building conditions, predicting disaster risks and so on. In recent years, convolutional neural networks have been widely employed in building detection, and have gained significant progresses. However, in these automatic detection procedures, the critical brightness information is often neglected, with all buildings simply classified into the same category. To make the building detection more efficient and precise, we propose a simple yet efficient multitask method employing several lightness detectors, each of which is dedicated to the building detection in a specific brightness interval. Experiment results show that the building detection accuracy could be improved by 8.1% with the assistance of the additional lightness information.

Approximately 3 billion people worldwide cook with solid fuels, such as wood, charcoal, and agricultural residues. These fuels, also used for residential heating, are often combusted in inefficient devices, producing carbonaceous emissions. Between 2.6 and 3.8 million premature deaths occur as a result of exposure to fine particulate matter from the resulting household air pollution (Health Effects Institute, 2018a; World Health Organization, 2018). Household air pollution also contributes to ambient air pollution; the magnitude of this contribution is uncertain. Here, we simulate the distribution of the two major health-damaging outdoor air pollutants (PM2.5 and O3) using state-of-the-science emissions databases and atmospheric chemical transport models to estimate the impact of household combustion on ambient air quality in India. The present study focuses on New Delhi and the SOMAARTH Demographic, Development, and Environmental Surveillance Site (DDESS) in the Palwal District of Haryana, located about 80 km south of New Delhi. The DDESS covers an approximate population of 200 000 within 52 villages. The emissions inventory used in the present study was prepared based on a national inventory in India (Sharma et al., 2015, 2016), an updated residential sector inventory prepared at the University of Illinois, updated cookstove emissions factors from Fleming et al. (2018b), and PM2.5 speciation from cooking fires from Jayarathne et al. (2018). Simulation of regional air quality was carried out using the US Environmental Protection Agency Community Multiscale Air Quality modeling system (CMAQ) in conjunction with the Weather Research and Forecasting modeling system (WRF) to simulate the meteorological inputs for CMAQ, and the global chemical transport model GEOS-Chem to generate concentrations on the boundary of the computational domain. Comparisons between observed and simulated O3 and PM2.5 levels are carried out to assess overall airborne levels and to estimate the contribution of household cooking emissions. Observed and predicted ozone levels over New Delhi during September 2015, December 2015, and September 2016 routinely exceeded the 8 h Indian standard of 100 µg m−3, and, on occasion, exceeded 180 µg m−3. PM2.5 levels are predicted over the SOMAARTH headquarters (September 2015 and September 2016), Bajada Pahari (a village in the surveillance site; September 2015, December 2015, and September 2016), and New Delhi (September 2015, December 2015, and September 2016). The predicted fractional impact of residential emissions on anthropogenic PM2.5 levels varies from about 0.27 in SOMAARTH HQ and Bajada Pahari to about 0.10 in New Delhi. The predicted secondary organic portion of PM2.5 produced by household emissions ranges from 16 % to 80 %. Predicted levels of secondary organic PM2.5 during the periods studied at the four locations averaged about 30 µg m−3, representing approximately 30 % and 20 % of total PM2.5 levels in the rural and urban stations, respectively.

The highest concentration of PM2.5 in cold rural dwellings of Northeast China is often generated by using mini stoves for cooking and heating, which can directly influence human health. As of yet, little is known about the impact of different daily life behavior on PM2.5 diffusion and residents’ exposure in rural dwellings. In this study, the characteristics of indoor PM2.5 variation and diffusion in rural dwellings was described by measuring some rural dwellings and establishing a multi-zone network model. The calculated results indicated that the relative errors between theoretical calculated results and experimental measured results are within 10%. PM2.5 diffusion in a rural dwelling can be predicted. Furthermore, the impacts of daily life behavior on PM2.5 diffusion and exposure assessment can be analyzed. Through discussion, heating behavior is the most important factor causing high concentrations of PM2.5 in each room, followed by cooking, smoking, and cleaning. Door opening time can lead to different interzonal airflows and PM2.5 diffusion rates. By reducing the inner door opening time to less than 1 min, PM2.5 could decrease to 300 μg/m3. Door closing behavior could decrease risk that PM2.5 diffuses to bedrooms by more than 50%, and exposure of residents in bedrooms could reduce to 100 (μg·h)/m3 effectively.

Intrauterine adhesions (IUAs) refer to the repair disorder after endometrial injury and may lead to uterine infertility, recurrent miscarriage, abnormal menstrual bleeding, and other obstetric complications. It is a pressing public health issue among women of childbearing age. Presently, there are limited clinical treatments for IUA, and there is no sufficient evidence that these treatment modalities can effectively promote regeneration after severe endometrial injury or improve pregnancy outcome. The inhibitory pathological micro-environment is the main factor hindering the repair of endometrial damaged tissues. To address this, tissue engineering and regenerative medicine have been achieving promising developments. Particularly, biomaterials have been used to load stem cells or therapeutic factors or construct an in situ delivery system as a treatment strategy for endometrial injury repair. This article comprehensively discusses the characteristics of various bio-scaffold materials and their application as stem cell or therapeutic factor delivery systems constructed for uterine tissue regeneration.

Quadratic magneto-optical (MO) effects can be utilized to investigate the spin order in antiferromagnetic (AFM) materials; however, the previously reported studies were all limited in antiferromagnets with collinear AFM order. Here, we develop a phenomenological theory to investigate the quadratic MO effects in hexagonal non-collinear AFM crystals with triangular spin structures. Based on the permittivity tensor up to the second-order in magnetization, we derive the formula to describe the quadratic MO responses and perform numerical calculations to obtain the MO rotation angle for different AFM spin configurations and sample orientations. For the sample with its spin plane lying perpendicular to the surface plane, we have revealed the emergence of quadratic MO response, which exhibits a strong dependence on the light incident angle. The MO rotation angle shows an approximately sinusoidal variation with a periodicity of 180° when the sample is rotated around its surface normal. The size of the MO response and its deviation from the sinusoidal form are analyzed for different values of the second-order permittivity tensor elements. This study provides important insights into the non-collinear AFM spin-induced quadratic MO effect, which may be used as a guidance for optical detections of the non-collinear AFM order, and, in particular, the ultrafast spin dynamics using the optical pump–probe technique.

Nrf2, a transcription factor that regulates the response to oxidative stress, has been shown to rescue cone photoreceptors and slow vision loss in mouse models of retinal degeneration (rd). The retinal pigment epithelium (RPE) is damaged in these models, but whether it also could be rescued by Nrf2 has not been previously examined. We used an adeno-associated virus (AAV) with an RPE-specific (Best1) promoter to overexpress Nrf2 in the RPE of rd mice. Control rd mice showed disruption of the regular array of the RPE, as well as loss of RPE cells. Cones were lost in circumscribed regions within the cone photoreceptor layer. Overexpression of Nrf2 specifically in the RPE was sufficient to rescue the RPE, as well as the disruptions in the cone photoreceptor layer. Electron microscopy showed compromised apical microvilli in control rd mice but showed preserved microvilli in Best1-Nrf2–treated mice. The rd mice treated with Best1-Nrf2 had slightly better visual acuity. Transcriptome profiling showed that Nrf2 upregulates multiple oxidative defense pathways, reversing declines seen in the glutathione pathway in control rd mice. In summary, Nrf2 overexpression in the RPE preserves RPE morphology and survival in rd mice, and it is a potential therapeutic for diseases involving RPE degeneration, including age-related macular degeneration (AMD).

Cereal grains treated with organic acids were proved to increase ruminal resistant starch and can relieve the risk of ruminal acidosis. However, previous study mainly focussed on acid-treated barley, the effects of organic acid-treated corn is still unknown. The objectives of this study were to evaluate whether feeding ground corn steeped in citric acid (CA) would affect ruminal pH and fermentation patterns, milk production and innate immunity responses in dairy goats. Eight ruminally cannulated Saanen dairy goats were used in a crossover designed experiment. Each experimental period was 21 day long including 14 days for adaption to new diet and 7 days for sampling and data collection. The goats were fed high-grain diet contained 30% hay and 70% corn-based concentrate. The corn was steeped either in water (control) or in 0.5% (wt/vol) CA solution for 48 h. Goats fed CA diet showed improved ruminal pH status with greater mean and minimum ruminal pH, and shorter (P

Superhydrophobic coatings have drawn much attention in recent years for their widespread potential applications. However, there are challenges to find a simple and cost-effective approach to prepare superhydrophobic materials and coatings using natural polymer. Herein, we prepared a kraft lignin-based superhydrophobic powder via modifying kraft lignin through 1H, 1H, 2H, 2H-perfluorodecyl-triethoxysilane (PFDTES) substitution reaction, and constructed superhydrophobic coatings by direct spraying the suspended PFDTES-Lignin powder on different substrates, including glass, wood, metal and paper. The prepared lignin-based coatings have excellent repellency to water, with a water contact angle of 164.7°, as well as good friction resistance, acid resistance, alkali resistance, salt resistance properties and quite good self-cleaning performance. After 30 cycles of sand friction or being stayed in 2 mol/L HCl, 0.25 mol/L NaOH and 2 mol/L NaCl solution for 30 min, the coatings still retain super hydrophobic capability, with contact angles higher than 150°. The superhydrophobic performance of PFDTES-Lignin coatings is mainly attributed to the constructed high surface roughness and the low surface energy afforded by modified lignin. This lignin-based polymer coating is low-cost, scalable, and has huge potential application in different fields, providing a simple way for the value-added utilization of kraft lignin.

Metabotropic glutamate receptor 5 (mGluR5) has been implicated in Alzheimer’s disease (AD) pathology. We sought to understand whether mGluR5’s role in AD requires glutamate signaling. We used a potent mGluR5 silent allosteric modulator (SAM, BMS-984923) to separate its well-known physiological role in glutamate signaling from a pathological role in mediating amyloid-β oligomer (Aβo) action. Binding of the SAM to mGluR5 does not change glutamate signaling but strongly reduces mGluR5 interaction with cellular prion protein (PrPC) bound to Aβo. The SAM compound prevents Aβo-induced signal transduction in brain slices and in an AD transgenic mouse model, the APPswe/PS1ΔE9 strain. Critically, 4 weeks of SAM treatment rescues memory deficits and synaptic depletion in the APPswe/PS1ΔE9 transgenic mouse brain. Our data show that mGluR5’s role in Aβo-dependent AD phenotypes is separate from its role in glutamate signaling and silent allosteric modulation of mGluR5 has promise as a disease-modifying AD intervention with a broad therapeutic window.

Flow tube reactors are widely employed to study gas-phase atmospheric chemistry and secondary organic aerosol (SOA) formation. The development of a new laminar-flow tube reactor, the Caltech Photooxidation Flow Tube (CPOT), intended for the study of gas-phase atmospheric chemistry and SOA formation, is reported here. The present work addresses the reactor design based on fluid dynamical characterization and the fundamental behavior of vapor molecules and particles in the reactor. The design of the inlet to the reactor, based on computational fluid dynamics (CFD) simulations, comprises a static mixer and a conical diffuser to facilitate development of a characteristic laminar flow profile. To assess the extent to which the actual performance adheres to the theoretical CFD model, residence time distribution (RTD) experiments are reported with vapor molecules (O3) and submicrometer ammonium sulfate particles. As confirmed by the CFD prediction, the presence of a slight deviation from strictly isothermal conditions leads to secondary flows in the reactor that produce deviations from the ideal parabolic laminar flow. The characterization experiments, in conjunction with theory, provide a basis for interpretation of atmospheric chemistry and SOA studies to follow. A 1-D photochemical model within an axially dispersed plug flow reactor (AD-PFR) framework is formulated to evaluate the oxidation level in the reactor. The simulation indicates that the OH concentration is uniform along the reactor, and an OH exposure (OHexp) ranging from ∼ 109 to ∼ 1012 molecules cm−3 s can be achieved from photolysis of H2O2. A method to calculate OHexp with a consideration for the axial dispersion in the present photochemical system is developed.