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Olivine is a mineral indicative of water activity in the mantle, and its presence can elucidate the petrological evolution and history of magmatic igneous rocks. In this work, we conducted a preliminary investigation into the characteristics and patterns of the spatial relationships between representative Martian mineral (i.e., olivine) and geomorphic features, aiming to provide geographical insights into the potential habitable environment of Mars. Specifically, an analytical framework is constructed to explore the spatial connection between hydrated minerals like olivine and topographic features regarding the relationship between environmental factors and mineral distributions. Furthermore, an analytical paradigm for responding to the spatial relationship is established. The spatial distribution pattern of olivine in Valles Marineris and Nili Fossae on Mars is depicted using kernel density analysis and bivariate spatial autocorrelation models. Based on this, the coupling relationship between olivine and environmental factors is constructed to quantify the strength of the link, and the interaction mechanism between olivine and geomorphological terrain is identified. The study results demonstrate that the distribution of olivine exhibits pronounced spatial clustering characteristics. Furthermore, the spatial distribution pattern of olivine and topographic features displays elevation differentiation characteristics. In the study region, topographic features dominate the spatial differentiation of olivine, specifically within the context of Valles Marineris. The spatial linkage strengths between the factors in the area vary considerably.

High-resolution digital terrain models (DEM) are crucial for Mars scientific exploration and engineering demands, such as mission route planning, landing site selection, and topography research. However, DEMs generated based on photogrammetry or photometry suffer from limited stereo coverage and complex generative processes. Therefore, we propose a GAN-based monocular 3D reconstruction method, which utilizes high-resolution monocular orbital images to achieve pixel-level Martian terrain reconstruction. We preprocess the image data and then invert the elevation using the trained generative model. Finally, we recover the absolute scale through post-processing. In this work, we use HiRISE orthorectified images and DEMs with a resolution of 2 m and 0.25 m to validate the effectiveness of our method. We evaluated our method in four areas with different landforms and found that the predicted DEM and HiRISE DEM have height consistency with the root mean square error of about 2 m. This indicates that the proposed GAN-based method has certain effectiveness and generalization and great potential in high-resolution monocular Martian DEM reconstruction.

Abstract Plasma turbulence plays a key role in space and astrophysical plasma systems, enabling the energy of magnetic fields and plasma flows to be transported to particle kinetic scales at which the turbulence dissipates and heats the plasma. Identifying the physical mechanisms responsible for the dissipation of the turbulent energy is a critical step in developing the predictive capability for the turbulent heating needed by global models. In this work, spacecraft measurements of the electromagnetic fields and ion velocity distributions by the Magnetospheric Multiscale (MMS) mission are used to generate velocity-space signatures that identify ion cyclotron damping in Earth’s turbulent magnetosheath, in agreement with analytical modeling. Furthermore, the rate of ion energization is directly quantified and combined with a previous analysis of the electron energization to identify the dominant channels of turbulent dissipation and determine the partitioning of energy among species in this interval.

Abstract The current experiments searching for neutrinoless double- $$\beta $$ β ( $$0\nu \beta \beta $$ 0 ν β β ) decay also collect large statistics of Standard Model allowed two-neutrino double- $$\beta $$ β ( $$2\nu \beta \beta $$ 2 ν β β ) decay events. These can be used to search for Beyond Standard Model (BSM) physics via $$2\nu \beta \beta $$ 2 ν β β decay spectral distortions. 100Mo has a natural advantage due to its relatively short half-life, allowing higher $$2\nu \beta \beta $$ 2 ν β β decay statistics at equal exposures compared to the other isotopes. We demonstrate the potential of the dual read-out bolometric technique exploiting a 100Mo exposure of 1.47 kg $$\times $$ × years, acquired in the CUPID-Mo experiment at the Modane underground laboratory (France). We set limits on $$0\nu \beta \beta $$ 0 ν β β decays with the emission of one or more Majorons, on $$2\nu \beta \beta $$ 2 ν β β decay with Lorentz violation, and $$2\nu \beta \beta $$ 2 ν β β decay with a sterile neutrino emission. In this analysis, we investigate the systematic uncertainty induced by modeling the $$2\nu \beta \beta $$ 2 ν β β decay spectral shape parameterized through an improved model, an effect never considered before. This work motivates searches for BSM processes in the upcoming CUPID experiment, which will collect the largest amount of $$2\nu \beta \beta $$ 2 ν β β decay events among the next-generation experiments.

In this study, we utilised ground-based in situ measurements of the aerosol chemical composition and particle size distribution, along with meteorological data from the European Centre for Medium-Range Weather Forecasts (ECMWF), to predict vertical profiles of aerosol optical properties, including the aerosol scattering coefficient, backscatter coefficient, extinction coefficient, and lidar ratio. The predicted ambient profiles were compared to retrievals by a multi-wavelength Raman lidar during the Ruisdael Land–Atmosphere Interactions Intensive Trace-gas and Aerosol (RITA) campaign in the Netherlands in 2021 for 26 time periods of approximately 1 h each. Predicted and retrieved extensive aerosol properties (scattering, backscatter, and extinction coefficient) were comparable only approximately 35 % of the time, mostly under the condition of well-mixed boundary layers. In this case, ground-based measurements can provide a way to extend extinction profiles to lower altitudes, where they cannot be retrieved, and to verify the lidar-measured profiles. Accurate representation of hygroscopic growth is required for adjusting the dry size distribution to ambient size distribution, and the estimated relative humidity profile may have a substantial influence on the shape of the calculated profiles. On the other hand, the lidar ratio profiles predicted by ground-based data also compared reasonably well to the retrieved lidar profiles (starting at 800 m) for conditions where the predicted and retrieved backscatter profiles differed considerably. The difference in the predicted and retrieved lidar ratio is usually less than ±30 %. Our study thus shows that, for well-mixed boundary layers, a representative lidar ratio can be estimated from ground-based in situ measurements of chemical composition and dry size distribution. This approach offers a method of providing lidar ratios calculated from independent in situ measurements for simple backscatter lidars or at times when Raman lidar profiles cannot be measured (e.g. during the daytime). It only uses data that are routinely available at aerosol measurement stations and is therefore not only useful for further validating lidar measurements but also for bridging the gap between in situ measurements and lidar remote sensing.

The present study investigated the transmission of exhaled particles generated by coughing inside a car cabin, considering eleven different window opening configurations. The results indicated that particle dispersion and removal were mainly affected by the airflow, which was largely determined by the window opening configurations. Notably, efficient ventilation and a large number of open windows did not necessarily result in lower infection risk. Given the complex structure and formation of intricate airflow patterns within the cabin, airborne particles could spread throughout the cabin and deposit on the interior walls. As particles tended to escape or deposit rapidly within the first 10 s, precautionary measures were necessary during this time frame following a passenger's coughing activity. Furthermore, closing the window adjacent to the driver effectively reduced the proportion of exhaled particles passing through the driver's breathing zone due to the rear-in and front-out airflow pattern, thus mitigating the risk of infection.

Increasing trends of atmospheric nitrogen (N) deposition resulting from a large number of anthropogenic emissions of reactive N are dramatically altering the global biogeochemical cycle of N. Nitrogen uptake by mosses occurs mainly from the atmosphere, making it a competent bio-indicator of N deposition. However, high uncertainties exist when using mosses to indicate N deposition, especially in choosing sampling periods and sampling frequencies. In this study, atmospheric N deposition and moss N content in the urban–agro–forest transition, a region with a high N deposition level of 27.46–43.70 kg N hm−2 yr−1, were monitored, and the method for monitoring atmospheric N deposition by mosses was optimized. We found that the optimal sampling frequency is within 6 months per time, and the optimal sampling times are winter (January and February), autumn (October and November), and summer (July and August), which provides us with a more accurate estimation of atmospheric N deposition than other scenarios. In addition, the moss N content serves as a more reliable N species. This study eventually allowed mosses to be used more effectively and sensibly as an indicator of atmospheric N deposition and helped to improve the accuracy of the model for quantifying N deposition.

The recently developed time-of-flight aerosol chemical speciation monitor with a capture vaporizer and a PM2.5 aerodynamic lens (TOF-ACSM-CV-PM2.5) aims to improve the collection efficiency and chemical characterization of aerosol particles with a diameter smaller than 2.5 µm. In this study, comprehensive cross-comparisons were performed between real-time online measurements and offline filter analysis with 24 h collection time. The goal was to evaluate the capabilities of the TOF-ACSM-CV-PM2.5 lens, as well as the accuracy of the TOF-ACSM-CV-PM2.5. The experiments were conducted at Cabauw Experimental Site for Atmospheric Research (CESAR) during the RITA-2021 campaign. The non-refractory fine particulate matter (PM1.0 and PM2.5) was measured by two collocated TOF-ACSM-CV-PM2.5 instruments by placing them behind a PM2.5 and PM1.0 inlet, respectively. A comparison between the ACSMs and PM2.5 and PM1.0 filter samples showed a much better accuracy than ±30 % less given in the previous reports, with average differences less than ±10 % for all inorganic chemical species. In addition, the ACSMs were compared to the Monitoring Instrument for Aerosol and Gas (MARGA) (slope between 0.78 and 0.97 for inorganic compounds, R2≥ 0.93) and a mobility particle size spectrometer (MPSS), measuring the particle size distribution from around 10 to 800 nm (slope was around 1.00, R2= 0.91). The intercomparison of the online measurements and the comparison between the online and offline measurements indicated a low bias (< 10 % for inorganic compounds) and demonstrated the high accuracy and stability of the TOF-ACSM-CV-PM2.5 lens for the atmospheric observations of particle matter. The two ACSMs exhibited an excellent agreement, with differences less than 7 %, which allowed a quantitative estimate of PM1.0 vs. PM2.5 chemical composition. The result showed that the PM1.0 accounted for about 70 %–80 % of the PM2.5 on average. The NO3 mass fraction increased, but the organic carbon (OC) mass fraction decreased from PM1.0 to PM2.5, indicating the size dependence on chemical composition.

Abstract Background Little is known about the long-term impact of hearing and vision impairment on social isolation. This study quantifies the association between hearing, vision, and concurrent hearing and vision impairment (dual sensory impairment) and social isolation over 8 years among older adults. Methods Data were from the National Health and Aging Trends Study (NHATS), a cohort study (2011 – 2019) of U.S. Medicare beneficiaries aged 65 years and older. Social isolation was measured by a binary indicator incorporating four domains: living arrangement, core discussion network size, religious attendance, and social participation. Hearing, vision, and dual sensory impairments were measured by self-report and modeled categorically (no impairment [ref.], hearing impairment only, vision impairment only, dual sensory impairment). Associations between sensory impairments and odds of social isolation over 8 years were assessed using multivariate generalized logistic mixed models and adjusted for demographic and health characteristics. Results Among 5,552 participants, 18.9% self-reported hearing impairment, 4.8% self-reported vision impairment, and 2.3% self-reported dual sensory impairment. Over 8 years, hearing impairment only was associated with 28% greater odds of social isolation. Participants with hearing impairment only were more likely to live alone and have limited social participation. Conclusion Greater clinical awareness of hearing impairment as a risk factor for social isolation can increase opportunities to identify and aid older adults who may benefit from resources and interventions to increase social connection and mitigate social isolation.

PM2.5 pollution is a major air quality issue that deteriorates human health, and numerous studies have focused on PM2.5 pollution in major regions such as the North China Plain (NCP) and Yangtze River Delta (YRD). However, the characteristics of PM2.5 concentrations and the associated formation mechanism in the transport corridor (referred to as SWLY) between the NCP and YRD are largely ignored. Based on observational data, we find that the number of PM2.5 pollution events in SWLY is comparable to that in the NCP, far exceeding that in the YRD, which is indicative of the severity of air pollution in this area. Utilizing a regional climate and air quality model, we isolate the effect of seesaw transport events, e.g., transport between the NCP and YRD, and atmospheric stagnation on the accumulation of PM2.5 over SWLY. Specifically, seesaw events and stagnation, comparable to each other, collectively account for an average of 67 % of pollution days, with PM2.5 exceeding 75 µg m−3, and this fraction (85 %) is even larger for severe haze events, with PM2.5 exceeding 150 µg m−3. Furthermore, the connection between seesaw transport and large-scale circulation is examined. The transregional transport of pollutants from the NCP to the YRD (YRD to NCP) is likely stimulated by positive (negative) to negative (positive) geopotential height anomalies at 500 hPa located in northern China. The health effect due to short-term PM2.5 exposure induced by the transregional transport and stagnation is investigated, yielding a total of 8634 (95 % CI: 6023–11 223) and 9496 (95 % CI: 6552–12 413) premature deaths, respectively, in SWLY during winter 2014–2019, which is as high as 9 % of the total premature deaths in China, even though SWLY takes up less than 1 % of China's area. While atmospheric stagnation is in general projected to occur more frequently under a warming climate, this study indicates the importance of regional emission control to alleviate PM2.5 pollution from seesaw transport and stagnation.

ABSTRACT The study aimed to investigate the effect of methionine deficiency on conventional nutrient composition, NO and NOS activity in the liver and kidney, and expression of genes related to the NF-κB signal pathway. One hundred 1-day-old broilers were divided into control and methionine deficiency group, and provided with a standard diet. The methionine-deficient group was fed with a methionine-deficient diet for 42 days. Moisture content, protein content, and crude lipid content were determined by freeze drying, the Kjeldahl method, and the ether extraction method. The concentration of NO was measured using the nitrate reductase method, and the activity of NOS was measured using colorimetry. mRNA expression of related genes in the NF-κB signal pathway was detected by reverse transcription-polymerase chain reaction (RT-PCR). The results showed the contents of crude protein and crude lipid in the liver and kidney of the methionine-deficient group were significantly higher than those in the control group (p0.05). Methionine deficiency resulted in significantly increased NO concentration and total nitric oxide synthase (TNOS) activities in the liver and kidney (p

Abstract BACKGROUND Cognitive training is delivered visually and aurally. It is unknown whether self‐reported sensory difficulty modifies the effects of cognitive training on cognition. METHODS Participants (N = 2788) in the Advanced Cognitive Training for Independent and Vital Elderly Study were randomized to training in memory, reasoning, speed of processing, or control. Differences in the 10‐year effect of cognitive training on cognition by self‐reported vision and hearing difficulty were assessed using linear mixed effect models. RESULTS Benefit (intervention vs. control) of reasoning training was smaller among participants with versus without vision difficulty (difficulty: –0.25, 95% confidence interval: [–0.88, 0.39], no difficulty: 0.58 [0.28, 0.89]). Benefit of memory training was greater for participants with versus without hearing difficulty (difficulty: 0.17 [–0.37, 0.72], no difficulty: –0.20 [–0.65, 0.24]). DISCUSSION Older adults with sensory loss have increased risk for cognitive decline; benefits of cognitive training may be greater for these individuals. Sensory loss should be considered in training design. Highlights Memory training was more beneficial for participants with hearing loss. Participants with vision difficulties did not benefit as much from reasoning training. Low accessibility in design and learned compensation strategies may contribute. Consideration of sensory impairment in study design is needed. Inclusion of older adults with sensory impairment in cognitive training is needed.

Stereo vision has been proven to be an efficient tool for 3D reconstruction in lunar topographic mapping. However, point clouds reconstructed from pairs of stereo images always suffer from occlusions and illumination changes, especially in Lunar environments, resulting in incomplete geometric information. 3D point cloud completion is usually required for refining photogrammetric point clouds and enabling further applications. In this work, we address the problem of completing and refining 3D photogrammetric point clouds based on the assumption that 3D terrain should be continuous and with consistent slope change. We proposed a generalized strategy for 3D point cloud completion of lunar topographic mapping, including distance-weighted point cloud interpolation, terrian-continuous constrained outlier detection, and contour-based hole filling. We carried out experiments on two datasets of point clouds generated from 12 pairs and 6 pairs of stereo LROC NAC images covering the Apollo 17 and the Chang’E-4 landing sites, respectively. As a result, the holes in the initial DTM have been smoothly filled and the completeness of the whole DTM has been greatly improved. The incomplete area of the experimental areas has dropped by 100% and 93%, respectively. Finally, we constructed DTM with a resolution of 10 m covering a 33 km × 60 km area of the Apollo 17 landing site with RMSE of 4 m and a 12 km × 56 km area of Chang’E-4 landing site with RMSE of 4 m compared with LOLA laser points as a reference.

Abstract CUPID-Mo, located in the Laboratoire Souterrain de Modane (France), was a demonstrator for the next generation $$0\nu \beta \beta $$ 0 ν β β decay experiment, CUPID. It consisted of an array of 20 enriched Li $$_{2}$$ 2 $$^{100}$$ 100 MoO $$_4$$ 4 bolometers and 20 Ge light detectors and has demonstrated that the technology of scintillating bolometers with particle identification capabilities is mature. Furthermore, CUPID-Mo can inform and validate the background prediction for CUPID. In this paper, we present a detailed model of the CUPID-Mo backgrounds. This model is able to describe well the features of the experimental data and enables studies of the $$2\nu \beta \beta $$ 2 ν β β decay and other processes with high precision. We also measure the radio-purity of the Li $$_{2}$$ 2 $$^{100}$$ 100 MoO $$_4$$ 4 crystals which are found to be sufficient for the CUPID goals. Finally, we also obtain a background index in the region of interest of 3.7 $$^{+0.9}_{-0.8}$$ - 0.8 + 0.9 (stat) $$^{+1.5}_{-0.7}$$ - 0.7 + 1.5 (syst) $$\times ~10 ^{-3}$$ × 10 - 3 counts/ $$\Delta E_{\text {FWHM}}/\text {mol}_{\text {iso}}/\text {year},$$ Δ E FWHM / mol iso / year , the lowest in a bolometric $$0\nu \beta \beta $$ 0 ν β β decay experiment.

Abstract INTRODUCTION Hearing loss is highly prevalent among older adults and independently associated with cognitive decline. The Aging and Cognitive Health Evaluation in Elders (ACHIEVE) study is a multicenter randomized control trial (partially nested within the infrastructure of an observational cohort study, the Atherosclerosis Risk in Communities [ARIC] study) to determine the efficacy of best‐practice hearing treatment to reduce cognitive decline over 3 years. The goal of this paper is to describe the recruitment process and baseline results. METHODS Multiple strategies were used to recruit community‐dwelling 70–84‐year‐old participants with adult‐onset hearing loss who were free of substantial cognitive impairment from the parent ARIC study and de novo from the surrounding communities into the trial. Participants completed telephone screening, an in‐person hearing, vision, and cognitive screening, and a comprehensive hearing assessment to determine eligibility. RESULTS Over a 24‐month period, 3004 telephone screenings resulted in 2344 in‐person hearing, vision, and cognition screenings and 1294 comprehensive hearing screenings. Among 1102 eligible, 977 were randomized into the trial (median age = 76.4 years; 53.5% female; 87.8% White; 53.3% held a Bachelor's degree or higher). Participants recruited through the ARIC study were recruited much earlier and were less likely to report hearing loss interfered with their quality of life relative to participants recruited de novo from the community. Minor differences in baseline hearing or health characteristics were found by recruitment route (i.e., ARIC study or de novo) and by study site. DISCUSSION The ACHIEVE study successfully completed enrollment over 2 years that met originally projected rates of recruitment. Substantial operational and scientific efficiencies during study startup were achieved through embedding this trial within the infrastructure of a longstanding and well‐established observational study. Highlights The ACHIEVE study tests the effect of hearing intervention on cognitive decline. The study is partially nested within an existing cohort study. Over 2 years, 977 participants recruited and enrolled. Eligibility assessed by telephone and in‐person for hearing, vision, and cognitive screening. The ACHIEVE study findings will have significant public health implications.

Global climate change leads to simultaneous changes in multiple environmental drivers in the marine realm. Although physiological characterization of coccolithophores has been studied under climate change, there is limited knowledge on the biochemical responses of this biogeochemically important phytoplankton group to changing multiple environmental drivers. Here, we investigate the interactive effects of reduced phosphorus availability (4 to 0.4 µmol L−1), elevated pCO2 concentrations (426 to 946 µatm), and increasing light intensity (40 to 300 µmol photons m−2 s−1) on elemental content and macromolecules of the cosmopolitan coccolithophore Emiliania huxleyi. Reduced phosphorus availability reduces particulate organic nitrogen (PON) and protein contents per cell under 40 µmol photons m−2 s−1 but not under 300 µmol photons m−2 s−1. Reduced phosphorus availability and elevated pCO2 concentrations act synergistically to increase particulate organic carbon (POC) and carbohydrate contents per cell under 300 µmol photons m−2 s−1 but not under 40 µmol photons m−2 s−1. Reduced phosphorus availability, elevated pCO2 concentrations, and increasing light intensity act synergistically to increase the allocation of POC to carbohydrates. Under elevated pCO2 concentrations and increasing light intensity, enhanced carbon fixation could increase carbon storage in the phosphorus-limited regions of the oceans where E. huxleyi dominates the phytoplankton assemblages. In each type of light intensity, elemental-carbon-to-phosphorus (C:P) and nitrogen-to-phosphorus (N:P) ratios decrease with increasing growth rate. These results suggest that coccolithophores could reallocate chemical elements and energy to synthesize macromolecules efficiently, which allows them to regulate their elemental content and growth rate to acclimate to changing environmental conditions.

This work investigated seasonal variation of aerosol iron (Fe) solubility for coarse (>1 µm) and fine ( µm) particles at Xi'an, a megacity in northwestern China impacted by anthropogenic emission and desert dust. Total Fe concentrations were lowest in summer and were similar in other seasons for coarse particles but lowest in summer and highest in spring for fine particles; for comparison, dissolved Fe concentrations were higher in fall and winter than spring and summer for coarse particles but highest in winter and lowest in spring and summer for fine particles. Desert-dust aerosol was always the major source of total Fe for both coarse and fine particles in all four seasons, but it may not be the dominant source of dissolved Fe. Fe solubility was lowest in spring for both coarse and fine particles and highest in winter for coarse particles and in fall for fine particles. In general, aerosol Fe solubility was found to be higher in air masses originating from local and nearby regions than those arriving from desert regions after long-distance transport. Compared to coarse particles, Fe solubility was similar for fine particles in spring but significantly higher in the other three seasons, and at a given aerosol pH range, Fe solubility was always higher in fine particles. Aerosol Fe solubility was well correlated with relative abundance of aerosol acidic species, implying aerosol Fe solubility enhancement by acid processing; moreover, such correlations were better for coarse particles than fine particles in all four seasons. Fe solubility was found to increase with relative humidity and acid acidity for both coarse and fine particles at Xi'an, underscoring the importance of aerosol liquid water and aerosol acidity in regulating Fe solubility via chemical processing.

Evaporation from global oceans is an important moisture source for glaciers and headwaters of major Asian rivers in the Tibetan Plateau (TP). Although the accelerated global hydrological cycle, the altered sea–land thermal contrast and the amplified warming rate over the TP during the past several decades are known to have profound effects on the regional water balance, the spatial distribution of oceanic moisture contributions to the vast TP remains unclear. This hinders the accurate quantification of regional water budgets and the reasonable interpretation of water isotope records from observations and paleo archives. Based on historical data and moisture tracking, this study systematically quantifies the absolute and relative contributions of oceanic moisture to long-term precipitation in the TP. Results show that the seasonal absolute and relative oceanic contributions are generally out of phase, revealing the previously underestimated oceanic moisture contributions brought by the westerlies in winter and the overestimated moisture contributions from the Indian Ocean in summer. Quantitatively, the relative contribution of moisture from the Indian Ocean is only ∼30 % in the south TP and further decreases to below 10 % in the northernmost TP. The absolute oceanic contribution exhibits a spatial pattern consistent with the dipole pattern of long-term precipitation trends across the Brahmaputra Canyon region and the central-northern TP. In comparison, relative oceanic contributions show strong seasonal patterns associated with the seasonality of precipitation isotopes across the TP.

Understanding the patterns of atmospheric phosphorus (P) deposition is essential for assessing the global P biogeochemical cycle. Atmospheric P is an essential source of P in agricultural activities as well as eutrophication in waters; however, the information on P deposition is paid relatively less attention, especially in the anthropogenic influencing region. Therefore, this study chose a typical urban–rural transition as a representative case to monitor the dry and wet P depositions for 2 years. The results showed that the fluxes of atmospheric total P deposition ranged from 0.50 to 1.06 kg P hm−2 yr−1, and the primary form was atmospheric dry P deposition (76.1 %, 0.76–0.84 kg P hm−2 yr−1). Moreover, it was found that the monthly variations of P deposition were strongly correlated with meteorological factors, including precipitation, temperature and relative humidity. However, the fluxes of dry P deposition and total P deposition were more affected by land use, which increased with the agro-facility, town and paddy field areas but decreased with the forest and country road areas. These findings suggested that dry P deposition was the primary form of total P deposition, and P deposition could be affected both by meteorological factors and land-use types. Thus, proper management of land use may help mitigate the pollution caused by P deposition.

Abstract The CUPID-Mo experiment to search for 0 $$\nu \beta \beta $$ ν β β decay in $$^{100}$$ 100 Mo has been recently completed after about 1.5 years of operation at Laboratoire Souterrain de Modane (France). It served as a demonstrator for CUPID, a next generation 0 $$\nu \beta \beta $$ ν β β decay experiment. CUPID-Mo was comprised of 20 enriched $$\hbox {Li}_{{2}}$$ Li 2 $$^{100}$$ 100 $$\hbox {MoO}_4$$ MoO 4 scintillating calorimeters, each with a mass of $$\sim 0.2$$ ∼ 0.2 kg, operated at $$\sim 20$$ ∼ 20 mK. We present here the final analysis with the full exposure of CUPID-Mo ( $$^{100}$$ 100 Mo exposure of 1.47 $$\hbox {kg} \times \hbox {year}$$ kg × year ) used to search for lepton number violation via 0 $$\nu \beta \beta $$ ν β β decay. We report on various analysis improvements since the previous result on a subset of data, reprocessing all data with these new techniques. We observe zero events in the region of interest and set a new limit on the $$^{100}$$ 100 Mo 0 $$\nu \beta \beta $$ ν β β decay half-life of $$T_{1/2}^{0\nu }$$ T 1 / 2 0 ν $$> {1.8}\times 10^{24}$$ > 1.8 × 10 24 year (stat. + syst.) at 90% CI. Under the light Majorana neutrino exchange mechanism this corresponds to an effective Majorana neutrino mass of $$\left$$ m β β $$

The most common complication in older surgical patients is postoperative delirium (POD). POD is associated with preoperative cognitive impairment and longer durations of intraoperative burst suppression (BSup) – electroencephalography (EEG) with repeated periods of suppression (very low-voltage brain activity). However, BSup has modest sensitivity for predicting POD. We hypothesized that a brain state of lowered EEG power immediately precedes BSup, which we have termed “pre-burst suppression” (preBSup). Further, we hypothesized that even patients without BSup experience these preBSup transient reductions in EEG power, and that preBSup (like BSup) would be associated with preoperative cognitive function and delirium risk. Data included 83 32-channel intraoperative EEG recordings of the first hour of surgery from 2 prospective cohort studies of patients ≥age 60 scheduled for ≥2-h non-cardiac, non-neurologic surgery under general anesthesia (maintained with a potent inhaled anesthetic or a propofol infusion). Among patients with BSup, we defined preBSup as the difference in 3–35 Hz power (dB) during the 1-s preceding BSup relative to the average 3–35 Hz power of their intraoperative EEG recording. We then recorded the percentage of time that each patient spent in preBSup, including those without BSup. Next, we characterized the association between percentage of time in preBSup and (1) percentage of time in BSup, (2) preoperative cognitive function, and (3) POD incidence. The percentage of time in preBSup and BSup were correlated (Spearman’s ρ [95% CI]: 0.52 [0.34, 0.66], p < 0.001). The percentage of time in BSup, preBSup, or their combination were each inversely associated with preoperative cognitive function (β [95% CI]: −0.10 [−0.19, −0.01], p = 0.024; −0.04 [−0.06, −0.01], p = 0.009; −0.04 [−0.06, −0.01], p = 0.003, respectively). Consistent with prior literature, BSup was significantly associated with POD (odds ratio [95% CI]: 1.34 [1.01, 1.78], p = 0.043), though this association did not hold for preBSup (odds ratio [95% CI]: 1.04 [0.95, 1.14], p = 0.421). While all patients had ≥1 preBSup instance, only 20.5% of patients had ≥1 BSup instance. These exploratory findings suggest that future studies are warranted to further study the extent to which preBSup, even in the absence of BSup, can identify patients with impaired preoperative cognition and/or POD risk.

Some antimethanogenic feed additives for ruminants promote rumen dihydrogen (H2) accumulation potentially affecting the optimal fermentation of diets. We hypothesised that combining an H2 acceptor with a methanogenesis inhibitor can decrease rumen H2 build-up and improve the production of metabolites that can be useful for the host ruminant. We performed three in vitro incubation experiments using rumen fluid from lactating Holstein cows: Experiment 1 examined the effect of phenolic compounds (phenol, catechol, resorcinol, hydroquinone, pyrogallol, phloroglucinol, and gallic acid) at 0, 2, 4, and 6 mM on ruminal fermentation for 24 h; Experiment 2 examined the combined effect of each phenolic compound from Experiment 1 at 6 mM with two different methanogenesis inhibitors (Asparagopsis taxiformis or 2-bromoethanesulfonate (BES)) for 24 h incubation; Experiment 3 examined the effect of a selected phenolic compound, phloroglucinol, with or without BES over a longer term using sequential incubations for seven days. Results from Experiment 1 showed that phenolic compounds, independently of the dose, did not negatively affect rumen fermentation, whereas results from Experiment 2 showed that phenolic compounds did not decrease H2 accumulation or modify CH4 production when methanogenesis was decreased by up to 75% by inhibitors. In Experiment 3, after three sequential incubations, phloroglucinol combined with BES decreased H2 accumulation by 72% and further inhibited CH4 production, compared to BES alone. Interestingly, supplementation with phloroglucinol (alone or in combination with the CH4 inhibitor) decreased CH4 production by 99% and the abundance of methanogenic archaea, with just a nominal increase in H2 accumulation. Supplementation of phloroglucinol also increased total volatile fatty acid (VFA), acetate, butyrate, and total gas production, and decreased ammonia concentration. This study indicates that some phenolic compounds, particularly phloroglucinol, which are naturally found in plants, could improve VFA production, decrease H2 accumulation and synergistically decrease CH4 production in the presence of antimethanogenic compounds.

Most mitigation strategies to reduce enteric methane (CH4) production in the rumen induce an excess of rumen dihydrogen (H2) that is expelled and consequently not redirected to the synthesis of metabolites that can be utilised by the ruminant. We hypothesised that phenolic compounds can be potential H2 acceptors when added to the diet, as they can be degraded to compounds that may be beneficial for the animal, using part of the H2 available when ruminal methanogenesis is inhibited. We performed four in vitro incubation experiments using rumen inoculum from Murciano-Granadina adult goats: Experiment 1 examined the inhibitory potential of Asparagopsis taxiformis (AT) at different concentrations (0, 1, 2, 3, 4 and 5% of the substrate on a DM basis) in 24 h incubations; Experiment 2 investigated the effect of a wide range of phenolic compounds (phenol, catechol, resorcinol, hydroquinone, pyrogallol, phloroglucinol, gallic acid and formic acid) at different doses (0, 2, 4, and 6 mM) on rumen fermentation for 24 h; Experiment 3 evaluated the combined effect of each phenolic compound at 6 mM with AT at 2% DM in sequential batch cultures for 5 days; and Experiment 4 examined the dose–response effect of phloroglucinol at different concentrations (0, 6, 16, 26 and 36 mM) combined with AT in sequential batch cultures for 5 days. Results from Experiment 1 confirmed that AT at 2% DM substantially inhibited CH4 production while significantly increasing H2 accumulation and decreasing the acetate:propionate ratio. Results from Experiment 2 showed that phenolic compounds did not negatively affect rumen fermentation at any dose. In Experiment 3, each phenolic compound at 6 mM combined with AT at 2% DM inhibited CH4 production. Phloroglucinol numerically decreased H2 accumulation and significantly increased total gas production (TGP), volatile fatty acid (VFA) production and the acetate:propionate ratio. In Experiment 4, phloroglucinol at increasing doses supplemented with AT at 2% DM significantly decreased H2 accumulation and the abundances of archaea, protozoa and fungi abundances, and increased TGP, total VFA production and the acetate:propionate ratio in a dose-dependent way. In conclusion, combined treatment with AT and phloroglucinol was successful to mitigate CH4 production while preventing the accumulation of H2, leading to an increase in acetate and total VFA production and therefore an improvement in rumen fermentation in goats.

Natural disasters cause considerable losses to people’s lives and property. Satellite images can provide crucial information of the affected areas for the first time, conducive to relieving the people in disaster and reducing the economic loss. However, the traditional satellite image analysis method based on manual processing drains workforce and material resources, which slowed the government’s response to the disaster. Aiming at the natural disasters like floods and earthquakes that often happen in the south of China, we propose a dual-stage damage assessment method based on LEDNet and ResNet. Our method detects the changes between the satellite images captured before and after a disaster of the same area, segments the buildings, and evaluates the damage level of affected buildings. In addition, we calculate influence maps based on the damage scale to the building and estimate the damage situation for electrical facilities. We used images related to earthquakes and floods in the xBD dataset to train the network model. Moreover, qualitative and quantitative evaluations demonstrated that our method has higher accuracy than the xBD baseline.

Vegetation management is important to the power transmission and distribution networks. The encompassed towering tree is always the key factor of the high impedance faults(HIFs).LiDAR is an efficient way to detect trees with 3D point cloud. The classical tree detection algorithm can handle the tree with high and distinct trunk,but limited to the tree with messy trunks. While the deeplearning based detection algorithms are also suffered from the terrain noise points. In this paper, we propose an efficient LiDAR reconstruction system which can efficiently reconstruct the point cloud of surrounding vegetation without the ground plane noise. We also use different weight strategies to improve the localization accuracy. We have conducted our system on the real power network environment and the height detection result shows that our algorithm has a better accuracy and robustness compared with the classical methods.

The tropical western Pacific (TWP) is a preferential area of air uplifting from the surface to the upper troposphere. A significantly intensified upward motion through the troposphere over the TWP in the boreal wintertime (November to March of the following year, NDJFM) has been detected using multiple reanalysis datasets. The upward motion over the TWP is intensified at rates of 8.0 ± 3.1 % per decade and 3.6 ± 3.3 % per decade in NDJFM at 150 hPa from 1958 to 2017, using JRA55 and ERA5 reanalysis datasets, while the MERRA-2 reanalysis data show a 7.5 ± 7.1 % per decade intensified upward motion for the period 1980–2017. Model simulations using the Whole Atmosphere Community Climate Model, version 4 (WACCM4), suggest that warming global sea surface temperatures (SSTs), particularly SSTs over the eastern maritime continent and tropical western Pacific, play a dominant role in the intensification of the upward motion by strengthening the Pacific Walker circulation and enhancing the deep convection over the TWP. Using CO as a tropospheric tracer, the WACCM4 simulations show that an increase in CO at a rate of 0.4 ppbv (parts per billion by volume) per decade at the layer 150–70 hPa in the tropics is mainly resulted from the global SST warming and the subsequent enhanced upward motion over the TWP in the troposphere and strengthened tropical upwelling of Brewer–Dobson (BD) circulation in the lower stratosphere. This implies that more tropospheric trace gases and aerosols from both natural maritime sources and outflow from polluted air from South Asia may enter the stratosphere through the TWP region and affect the stratospheric chemistry and climate.

Well-estimated air pollutant concentration fields are critically important to compensate for observations that are only sparsely available, especially over non-urban areas. Previous data fusion methods generally used statistical models to relate observations of target variables to proxy data and supporting variables at known stations. In this study, we developed a new data fusion paradigm by designing a deep-learning model framework and workflow to learn multivariable spatial correlations from chemical transport model (CTM) simulations, before using it to estimate PM2.5 reanalysis fields from station observations. The model was composed of two modules as an explainable PointConv operation to pre-process isolated observations and a regression grid-to-grid network to build correlations among multiple variables. The model was trained with only CTM simulations and supporting geographical covariates. The trained model was evaluated in two aspects of (1) reproducing raw PM2.5 CTM simulations and (2) generating reanalysis and fused PM2.5 fields. First, the model was able to reproduce the CTM simulations well on a full domain from sampled CTM data items at sparse locations with an average R2=0.94 and RMSE = 4.85 µg m−3. Second, the fused PM2.5 fields estimated from observations achieved a good performance with R2=0.77 (RMSE = 14.29 µg m−3) and R2=0.84 (RMSE = 12.96 µg m−3) respectively evaluated at the stringent city level and station level. The generated reanalysis PM2.5 fields have complete spatial coverage within the modeling domain. One significant benefit of the fusion framework is that the model training does not rely on observations, which can be used to predict PM2.5 fields in newly set up observation networks such as those using portable sensors. Meanwhile, in the prediction procedure, only station observations are used along with supporting covariates. The fusion model has high computing efficiency (< 1 s d−1) due to acceleration using a graphical processing unit (GPU). As an alternative to generate chemical reanalysis fields, the method can be readily implemented in near-real time and be universally applied for other simulated variables with measurements available.

Background: Medical learners develop a more positive attitude toward Interprofessional Collaboration (IPC) following Interprofessional Education (IPE) programs. However, IPE is not standardized and the most effective teaching tool is unclear. The purpose of our study was to develop an IPE teaching tool for medical residents during an inpatient geriatric medicine rotation at an academic hospital, evaluate and explore the impact of the program on resident attitudes towards teamwork, and identify barriers and facilitators to interprofessional collaboration. Methods: An innovative video was developed which simulated a common IPC scenario. Near the start of the rotation, learners watched the video then participated in a facilitated discussion around principles of IPE, using the Canadian Interprofessional Health Collaborative (CIHC) framework, which highlights interprofessional communication, patient-centered care, role clarification, team functioning, collaborative leadership, and interprofessional conflict resolution. At the end of their four-week rotation, focus groups were conducted to explore resident attitudes towards IPE. The Theoretical Domain Framework (TDF) was used for qualitative analysis. Results: Data from 23 participants in five focus groups were analyzed using the TDF framework. Residents were able to identify barriers and facilitators to IPC in five TDF domains: environmental context and resources, social/professional role and identity, knowledge, social influences and skills. Their observations correlated with the CIHC framework. Conclusion: The use of a scripted video and facilitated group discussion gave insights into residents’ attitudes, perceived barriers and facilitators towards IPC on a geriatric medicine unit. Future research could explore the use of this video intervention in other hospital services where team-based care is important

Techniques for the ultrasensitive detection of cancer cell derived extracellular vesicles (EVs) surface protein are limited. Detection of cancer EVs directly from clinical samples is even more challengeable. Here we developed a droplet digital branched rolling circle amplification (ddBRCA) platform for the rapid and sensitive detection of cancer EVs. The design includes a hairpin structure DNA containing a cancer EVs specific aptamer sequence and BRCA primer sequence. The presence of target EVs could cause the conformational switching of the hairpin DNA, which subsequently triggers the BRCA. The reaction mixture was encapsulated in nanoliter droplets and allowed to incubate at 30 °C for 45 min. The fluorescent signal of each droplet was then measured using a microchip scanner. The results showed that our platform could detect EVs effectively with a limit of detection down to 12 particles/μL. Furthermore, the platform was tested using serum samples to validate its good prospect for clinical applicability. To sum it up, our platform was the first droplet digital RCA method so far, with advancements such as favorable rapidity (∼2 h), high sensitivity, and no washing step requirement, the proposed biosensor is expected to become a promising tool to be applied in clinical routines to assist in cancer diagnosis.

Cardiovascular disease (CVD) is one of the leading causes of mortality worldwide, and frequently leads to massive heart injury and the loss of billions of cardiac muscle cells and associated vasculature. Critical work in the last 2 decades demonstrated that these lost cells can be partially regenerated by the epicardium, the outermost mesothelial layer of the heart, in a process that highly recapitulates its role in heart development. Upon cardiac injury, mature epicardial cells activate and undergo an epithelial-mesenchymal transition (EMT) to form epicardium-derived progenitor cells (EpiPCs), multipotent progenitors that can differentiate into several important cardiac lineages, including cardiomyocytes and vascular cells. In mammals, this process alone is insufficient for significant regeneration, but it might be possible to prime it by administering specific reprogramming factors, leading to enhanced EpiPC function. Here, we show that oxytocin (OXT), a hypothalamic neuroendocrine peptide, induces epicardial cell proliferation, EMT, and transcriptional activity in a model of human induced pluripotent stem cell (hiPSC)-derived epicardial cells. In addition, we demonstrate that OXT is produced after cardiac cryoinjury in zebrafish, and that it elicits significant epicardial activation promoting heart regeneration. Oxytocin signaling is also critical for proper epicardium development in zebrafish embryos. The above processes are significantly impaired when OXT signaling is inhibited chemically or genetically through RNA interference. RNA sequencing data suggests that the transforming growth factor beta (TGF-β) pathway is the primary mediator of OXT-induced epicardial activation. Our research reveals for the first time an evolutionary conserved brain-controlled mechanism inducing cellular reprogramming and regeneration of the injured mammalian and zebrafish heart, a finding that could contribute to translational advances for the treatment of cardiac injuries.

Nano-TiO2 was prepared with butyl titanate as a precursor by sol-gel method. The samples were analysed by TG-DTA, X-ray diffraction, TEM and so on to assess the effects of different temperatures on the crystal structure, grain size, and microstructure of nano-TiO2. Meanwhile, the catalytic effect of heat treatment temperature on the degradation performance of TiO2 to methyl orange was investigated. The dynamic process of grain growth was preliminarily analysed by Eastman’s particle growth theory. The result shows that TiO2 particle size gradually increases with the heat treatment temperature. At 450 to 550°C, the grain is mainly anatase phase, a mixture of anatase and rutile phase was found at 650°C (mass ratio A:R = 9:1), and the degradation rate of nano-TiO2 on methyl orange reaches 97.75%. When the calcination temperature exceeds 850°C, TiO2 particles almost entirely are composed of rutile phase, and the photocatalytic activity decreases significantly. At 730°C, half of the crystalline TiO2 is transformed from anatase to rutile form. The apparent activation energies of the anatase and rutile crystals of nano-TiO2 are 18.15 kJ/mol and 42.56 kJ/mol, and the fastest grain growth occurs at 546°C and 1280°C respectively.

Registration of multiple point clouds acquired via terrestrial laser scanning (TLS) is usually compulsory to obtain the scanned data covering a whole urban scene. However, the automated processing of aligning multiple scans is still a concern because of the complex urban environment. To this end, we propose a fast and sturdy estimation of 3D shifts between point clouds by an automated markerfree process using global features, converting translation measurement between two point clouds in the space domain to the frequency domain and estimating the phase difference. By using the low-frequency components from the normalized cross-power spectrum, accurate 3D shifts are calculated by solving parameters in the linear equation representing phase difference angles, with the help of a robust estimator. The results of experiments using TLS datasets of different scenes show that the proposed approach is both practical and efficient. In particular, the proposed approach can achieve results with a translation error of less than about 1.0 m on test datasets.

Registration of point clouds is a fundamental problem in the community of photogrammetry and 3D computer vision. Generally, point cloud registration consists of two steps: the search of correspondences and the estimation of transformation parameters. However, to find correspondences from point clouds, generating robust and discriminative features is of necessity. In this paper, we address the problem of extracting robust rotation-invariant features for fast coarse registration of point clouds under the assumption that the pairwise point clouds are transformed with rigid transformation. With a Fourier-based descriptor, point clouds represented by volumetric images can be mapped from the image to feature space. It is achieved by considering a gradient histogram as a continuous angular signal which can be well represented by the spherical harmonics. The rotation-invariance is established based on the Fourier-based analysis, in which high-frequency signals can be filtered out. This makes the extracted features robust to noises and outliers. Then, with the extracted features, pairwise correspondence can be found by the fast search. Finally, the transformation parameters can be estimated by fitting the rigid transformation model using the corresponding points and RANSAC algorithm. Experiments are conducted to prove the effectiveness of our proposed method in the task of point cloud registration. Regarding the experimental results of the point cloud registration using two TLS benchmark point cloud datasets, featuring with limited overlaps and uneven point densities and covering different urban scenes, our proposed method can achieve a fast coarse registration with rotation errors of less than 1 degree and translation errors of less than 1m.

Abstract We report the measurement of the two-neutrino double-beta ($$2\nu \beta \beta $$ 2νββ ) decay of $$^{100}$$ 100 Mo to the ground state of $$^{100}$$ 100 Ru using lithium molybdate ($$\hbox {Li}_2^{\;\;100}\hbox {MoO}_4$$ Li2100MoO4 ) scintillating bolometers. The detectors were developed for the CUPID-Mo program and operated at the EDELWEISS-III low background facility in the Modane underground laboratory (France). From a total exposure of 42.235 kg$$\times $$ × day, the half-life of $$^{100}$$ 100 Mo is determined to be $$T_{1/2}^{2\nu }=[7.12^{+0.18}_{-0.14}\,\mathrm {(stat.)}\pm 0.10\,\mathrm {(syst.)}]\times 10^{18}$$ T1/22ν=[7.12-0.14+0.18(stat.)±0.10(syst.)]×1018 years. This is the most accurate determination of the $$2\nu \beta \beta $$ 2νββ half-life of $$^{100}$$ 100 Mo to date.

Individual, large thrusting earthquakes can cause hundreds to thousands of years of exhumation in a geologically instantaneous moment through landslide generation. The bedrock landslides generated are important weathering agents through the conversion of bedrock into mobile regolith. Despite this, orogen-scale records of surface uplift and exhumation, whether sedimentary or geochemical, contain little to no evidence of individual large earthquakes. We examine how earthquakes and landslides influence exhumation and surface uplift rates with a zero-dimensional numerical model, supported by observations from the 2008 Mw 7.9 Wenchuan earthquake. We also simulate the concentration of cosmogenic radionuclides within the model domain, so we can examine the timescales over which earthquake-driven changes in exhumation can be measured. Our model uses empirically constrained relationships between seismic energy release, weathering, and landsliding volumes to show that large earthquakes generate the most surface uplift, despite causing lowering of the bedrock surface. Our model suggests that when earthquakes are the dominant rock uplift process in an orogen, rapid surface uplift can occur when regolith, which limits bedrock weathering, is preserved on the mountain range. After a large earthquake, there is a lowering in concentrations of 10Be in regolith leaving the orogen, but the concentrations return to the long-term average within 103 years. The timescale of the seismically induced cosmogenic nuclide concentration signal is shorter than the averaging time of most thermochronometers (>103 years). However, our model suggests that the short-term stochastic feedbacks between weathering and exhumation produce measurable increases in cosmogenically measured exhumation rates which can be linked to earthquakes.

Abstract CUPID-Mo is a bolometric experiment to search for neutrinoless double-beta decay ($$0\nu \beta \beta $$ 0νββ ) of $$^{100}\hbox {Mo}$$ 100Mo . In this article, we detail the CUPID-Mo detector concept, assembly and installation in the Modane underground laboratory, providing results from the first datasets. The CUPID-Mo detector consists of an array of 20 $$^{100}\hbox {Mo}$$ 100Mo -enriched 0.2 kg $$\hbox {Li}_2\hbox {MoO}_4$$ Li2MoO4 crystals operated as scintillating bolometers at $$\sim 20\hbox { mK}$$ ∼20mK . The $$\hbox {Li}_2\hbox {MoO}_4$$ Li2MoO4 crystals are complemented by 20 thin Ge optical bolometers to reject $$\alpha $$ α events by the simultaneous detection of heat and scintillation light. We observe a good detector uniformity and an excellent energy resolution of 5.3 keV (6.5 keV) FWHM at 2615 keV, in calibration (physics) data. Light collection ensures the rejection of $$\alpha $$ α particles at a level much higher than 99.9% – with equally high acceptance for $$\gamma $$ γ /$$\beta $$ β events – in the region of interest for $$^{100}\hbox {Mo}$$ 100Mo $$0\nu \beta \beta $$ 0νββ . We present limits on the crystals’ radiopurity: $$\le 3~\mu \hbox {Bq/kg}$$ ≤3μBq/kg of $$^{226}\hbox {Ra}$$ 226Ra and $$\le 2~\mu \hbox {Bq/kg}$$ ≤2μBq/kg of $$^{232}\hbox {Th}$$ 232Th . We discuss the science reach of CUPID-Mo, which can set the most stringent half-life limit on the $$^{100}\hbox {Mo}$$ 100Mo $$0\nu \beta \beta $$ 0νββ decay in half-a-year’s livetime. The achieved results show that CUPID-Mo is a successful demonstrator of the technology developed by the LUMINEU project and subsequently selected for the CUPID experiment, a proposed follow-up of CUORE, the currently running first tonne-scale bolometric $$0\nu \beta \beta $$ 0νββ experiment.

Abstract COVID‐19 is infected by severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) and can cause severe multiple organ injury and death. Kidney is one of major target organs of COVID‐19 and acute kidney injury (AKI) is common in critically ill COVID‐19 patients. However, mechanisms through which COVID‐19 causes AKI remain largely unknown and treatment remains unspecific and ineffective. Here, the authors report that normal kidney‐specifically overexpressing SARS‐CoV‐2 N develops AKI, which worsens in mice under ischemic condition. Mechanistically, it is uncovered that SARS‐CoV‐2 N‐induced AKI is Smad3‐dependent as SARS‐CoV‐2 N protein can interact with Smad3 and enhance TGF‐β/Smad3 signaling to cause tubular epithelial cell death and AKI via the G1 cell cycle arrest mechanism. This is further confirmed in Smad3 knockout mice and cells in which deletion of Smad3 protects against SARS‐CoV‐2 N protein‐induced cell death and AKI in vivo and in vitro. Most significantly, it is also found that targeting Smad3 with a Smad3 pharmacological inhibitor is able to inhibit SARS‐CoV‐2 N‐induced AKI. In conclusion, the authors identify that SARS‐CoV‐2 N protein is a key mediator for AKI and induces AKI via the Smad3‐dependent G1 cell cycle arrest mechanism. Targeting Smad3 may represent as a novel therapy for COVID‐19‐asscoaited AKI.

In this paper, we propose a framework for obtaining semantic labels of LiDAR point clouds and refining the classification results by combining a deep neural network with a graph-structured smoothing technique. In general, the goal of the semantic scene analysis is to assign a semantic label to each point in the point cloud. Although various related researches have been reported, due to the complexity of urban areas, the semantic labeling of point clouds in urban areas is still a challenging task. In this paper, we address the issues of how to effectively extract features from each point and its local surrounding and how to refine the initial soft labels by considering contextual information in the spatial domain. Specifically, we improve the effectiveness of classification of point cloud in two aspects. Firstly, instead of utilizing handcrafted features as input for classification and refinement, the local context of a point is embedded into deep dimensional space and classified via a deep neural network (PointNet++), and simultaneously soft labels are obtained as initial results for next refinement. Secondly, the initial label probability set is improved by taking the context both in the spatial domain into consideration by constructing a graph structure, and the final labels are optimized by a graph cuts algorithm. To evaluate the performance of our proposed framework, experiments are conducted on a mobile laser scanning (MLS) point cloud dataset. We demonstrate that our approach can achieve higher accuracy in comparison to several commonly-used state-of-the-art baselines. The overall accuracy of our proposed method on TUM dataset can reach 85.38% for labeling eight semantic classes.

GPRs (Ground Penetrating Radar) are widely adopted in underground space survey and mapping, because of their advantages of fast data acquisition, convenience, high imaging resolution and NDT (Non Destructive Testing) inspection. However, at present, the automation of the GPR data post-processing is low and the identification of underground objects needs expert interpretation. The heavy manual interpretation labor limits the GPR applications in large-scale urban scenarios. According to the latest research, it is still an unsolved problem to detect targets or defects in GPR data automatically and needs further exploration. In this paper, we propose a deep learning method for real-time detection of underground targets from GPR data. Seven typical targets in urban underground space are identified and labelled to construct the training dataset. The constructed dataset is consist of 489 labelled samples including rainwater wells, cables, metal/nonmetal pipes, sparse/dense steel reinforcement, voids. The training dataset is further augmented to produce more samples. DarkNet53 convolutional neural network (CNN) is trained using the constructed training dataset including realistic data and augmented data to extract features of the buried objects. And then the end-to-end YOLO detection framework is used to classify and locate the seven specific categories buried targets in the GPR data in real time. Experiments show that the automatic real-time detection method proposed in this paper can effectively detect the buried objects in the ground penetrating radar image in real time at Shenzhen test site (typical urban road scene).

The morphology and effective density of externally mixed black carbon (extBC) aerosols, important factors affecting the radiative forcing of black carbon, were studied using a tandem technique coupling a differential mobility analyzer (DMA) with a single-particle soot photometer (SP2). The study extended the mass–mobility relationship to large extBC particles with a mobility diameter (dmob) larger than 350 nm, a size range seldom included in previous tandem measurements of BC aggregates in the atmosphere. The experiment was conducted at an urban site in Beijing during a 19 d winter period from 23 January to 10 February 2018. Ambient dry particles were selected by the DMA, and the size-resolved extBC particles were distinguished from particles with a thick coating (internally mixed) according to the time delay between the incandescence signal peak and the scattering peak detected by the SP2. The masses of the extBC particles were then quantified. The time differences between the DMA size selection and the SP2 measurement were processed previously. The normalized number size distributions were investigated at the prescribed dmob sizes in the range of 140–750 nm to provide the typical mass of extBC at each dmob. On this basis, the mass–mobility relationship of the ambient extBC was established, inferring a mass–mobility scaling exponent (Dfm) (an important quantity for characterizing the morphology of fractal-like BC aggregates) with a value of 2.34±0.03 in the mobility range investigated in this study. This value is comparable with those of diesel exhaust particles, implying a predominant contribution of vehicle emissions to the ambient extBC in urban Beijing. Compared to the clean period, a higher Dfm value was observed in the polluted episode, indicating a more compact BC aggregate structure than that in the clean period. The effective densities (ρeff) of the extBC in the same dmob range were also derived, with values gradually decreasing from 0.46 g cm−3 at 140 nm mobility to 0.14 g cm−3 at 750 nm mobility. The ρeff values were slightly lower than those measured using the DMA–aerosol particle mass analyzer (APM) system. The difference in ρeff values was likely due to the lower BC masses determined by the SP2 compared to those measured by the APM at the same mobility, since the SP2 measured the refractory BC (rBC) mass instead of the total mass of the BC aggregate, which consists of both rBC and a possible fraction of nonrefractory components measured by the APM. The ρeff values in the 280–350 nm dmob range were much closer to the values for soot aggregates reported in the literature. It might be related to the more compact structure of BC aggregates in this range, resulting from the reconstruction effect by volatile and/or semivolatile components in the atmosphere. The reconstruction effect might also result in a hiatus in the increased dynamic shape factor in the range of 200–350 nm, which presented an overall increase from 2.16 to 2.93 in the 140–750 nm dmob range.

For conducting change detection using 3D scans of a construction site, the registration between point clouds at different acquisition times is normally necessary. However, due to the complexity of constructing areas, the automatic registration of temporal scans is a challenging problem. In this work, we propose a fast and maker-free method for coarse registration between point clouds by converting the 3D matching problem into a 2D correlation problem, taking the special properties of building structures into consideration. Our proposed method consists of two major steps: the conversion from 3D points to 2D image data and the estimation of transformation parameters between 2D images in the frequency domain. In the conversion step, the point cloud of each scan is projected into a 2D grey image, by which the ground footprint of the point cloud is obtained. In the following step, we represent the 2D image in frequency-domain and estimate the horizontal transformation parameters by using Fourier-Mellin transformation. A real application is performed to validate the feasibility and effectiveness of our workflow using photogrammetric point clouds of a construction site in two different acquisition time. Regarding the real application of coarse registration of point clouds, our proposed method can achieve a registration error of less than 1 degree and more efficient than the classical baseline methods for the fast orientation between scans.

Organic aerosol (OA) concentrations are simulated over the Beijing–Tianjin–Hebei (BTH) region from 9 to 26 January 2014 using the Weather Research and Forecasting model coupled with chemistry (WRF-CHEM), with the goal of examining the impact of heterogeneous HONO sources on SOA formation and SOA formation from different pathways during wintertime haze days. The model generally shows good performance with respect to simulating air pollutants and organic aerosols against measurements in BTH. Model results show that heterogeneous HONO sources substantially enhance near-surface SOA formation, increasing the regional average near-surface SOA concentration by about 46.3 % during the episode. Oxidation and partitioning of primary organic aerosols treated as semi-volatile dominate SOA formation, contributing 58.9 % of the near-surface SOA mass in BTH. Irreversible uptake of glyoxal and methylglyoxal on aerosol surfaces constitutes the second most important SOA formation pathway during the episode, with the SOA contribution increasing from 8.5 % under non-haze conditions to 30.2 % under haze conditions. Additionally, direct emissions of glyoxal and methylglyoxal from residential sources contribute about 25.5 % of the total SOA mass on average in BTH. Our study highlights the importance of heterogeneous HONO sources and primary residential emissions of glyoxal and methylglyoxal to SOA formation over the BTH region in winter.