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China's Ecological Protection Red Lines (ERLs) policy has proven effective in constructing regional ecological security patterns and protecting ecological space. However, the existing methods for the identification of high conservation value areas (HCVAs) usually use physical models, whose parameters and processes are complex and only for a single service, affecting the ERL delineation. In this study, the data-driven machine learning (ML) models were innovatively applied to construct a framework for ERL identification. First, the One-Class Support Vector Machine (OC-SVM) was used to generate negative samples from natural reserves and ecological factors. Second, the supervised ML models were applied to predict the HCVAs by using samples. Third, by applying the same ecological factors, the traditional physical models were used to assess the ecological services of the study area for reference and comparison. Take Chengdu–Chongqing Urban Agglomeration (CY) as a case study, wherein data from 11 factors and 1822 nature reserve samples were prepared for feasibility verification of the proposed framework. The results showed that the area under the receiver operating characteristic curve (AUC) of all ML models was more than 97%, and random forest (RF) achieved the best performance at 99.57%. Furthermore, the land cover had great contributions to the HCVAs prediction, which is consistent with the land use pattern of CY. High-value areas are distributed in the surrounding mountains of CY, with lush vegetation. All of the above results indicated that the proposed framework can accurately identify HCVAs, and that it is more suitable and simpler than the traditional physical model. It can help improve the effectiveness of ERL delimitation and promote the implementation of ERL policies. [ABSTRACT FROM AUTHOR]

As an important irritant trace gas in the atmosphere, ammonia (NH3) significantly impacts human health and environment. Bottom-up emission inventories are widely used to estimate ammonia emissions and their geographical distributions over China. However, high uncertainties are still associated with emission inventories due to inaccurate emission factors used. The Differential Evolution (DE) algorithm is a population-based stochastic optimization algorithm used to solve complicated optimization problems. We quantify NH3 emissions and lifetime from Infrared Atmospheric Sounding Interferometer (IASI) NH3 observations together with MERRA-2 wind fields based on the DE algorithm. Two inland cities, Urumchi and Golmud in China, are chosen to study of the NH3 emissions based on the distributions of NH3 total columns and wind fields. The NH3 emissions rate estimated is about 5.84 × 10−11 and 4.19 × 10−11 kg·m−2s−1 in Urumchi and in the Golmud area from May to September from 2008 to 2023, respectively. The lifetime of NH3 estimated in the two areas is 4.31 and 9.19 h, respectively. We compare the NH3 emissions and lifetime estimated in this study with the values in other studies, and the results show the reliability of the method used. This work is one of few quantitative studies of NH3 emissions from cities using satellite observations in China. [ABSTRACT FROM AUTHOR]

With the continuous development of satellite payload and system-on-chip (SoC) technology, spaceborne real-time synthetic aperture radar (SAR) imaging systems play a crucial role in various defense and civilian domains, including Earth remote sensing, military reconnaissance, disaster mitigation, and resource exploration. However, designing high-performance and high-reliability SAR imaging systems that operate in harsh environmental conditions while adhering to strict size, weight, and power consumption constraints remains a significant challenge. In this paper, we introduce a spaceborne SAR imaging chip based on a SoC architecture with system fault-tolerant technology. The fault-tolerant SAR SoC architecture has a CPU, interface subsystem, memory subsystem, data transit subsystem, and data processing subsystem. The data processing subsystem, which includes fast Fourier transform (FFT) modules, coordinated rotation digital computer (CORDIC) modules (for phase factor calculation), and complex multiplication modules, is the most critical component and can achieve various modes of SAR imaging. Through analyzing the computational requirements of various modes of SAR, we found that FFT accounted for over 50% of the total computational workload in SAR imaging processing, while the CORDIC modules for phase factor generation accounted for around 30%. Therefore, ensuring the fault tolerance of these two modules is crucial. To address this issue, we propose a word-length optimization redundancy (WLOR) method to make the fixed-point pipelined FFT processors in FFT modules fault tolerant. Additionally, we propose a fault-tolerant pipeline CORDIC architecture utilizing error correction code (ECC) and sum of squares (SOS) check. For other parts of the SoC architecture, we propose a generic partial triple modular redundancy (TMR) hardening method based on the HITS algorithm to improve fault tolerance. Finally, we developed a fully automated FPGA-based fault injection platform to test the design's effectiveness by injecting errors at arbitrary locations. The simulation results demonstrate that the proposed methods significantly improved the chip's fault tolerance, making the SAR imaging chip safer and more reliable. We also implemented a prototype measurement system with a chip-included board and demonstrated the proposed design's performance on the Chinese Gaofen-3 strip-map continuous imaging system. The chip requires 9.2 s, 50.6 s, and 7.4 s for a strip-map with 16,384 × 16,384 granularity, multi-channel strip-map with 65,536 × 8192 granularity, and multi-channel scan mode with 32,768 × 4096 granularity, respectively, and the system hardware consumes 6.9 W of power to process the SAR raw data. [ABSTRACT FROM AUTHOR]

In brain–computer interface (BCI) systems, motor imagery electroencephalography (MI-EEG) signals are commonly used to detect participant intent. Many factors, including low signal-to-noise ratios and few high-quality samples, make MI classification difficult. In order for BCI systems to function, MI-EEG signals must be studied. In pattern recognition and other fields, deep learning approaches have recently been successfully applied. In contrast, few effective deep learning algorithms have been applied to BCI systems, especially MI-based systems. In this paper, we address these problems from two aspects based on the characteristics of EEG signals: first, we proposed a combined time–frequency domain data enhancement method. This method guarantees that the size of the training data is effectively increased while maintaining the intrinsic composition of the data. Second, our design consists of a parallel CNN that takes both raw EEG images and images transformed through continuous wavelet transform (CWT) as inputs. We conducted classification experiments on a public data set to verify the effectiveness of the algorithm. According to experimental results based on the BCI Competition IV Dataset2a, the average classification accuracy is 97.61%. A comparison of the proposed algorithm with other algorithms shows that it performs better in classification. The algorithm can be used to improve the classification performance of MI-based BCIs and BCI systems created for people with disabilities. [ABSTRACT FROM AUTHOR]

Predicting products of organic chemical reactions is useful in chemical sciences, especially when one or more reactants are new organics. However, the performance of traditional learning models heavily relies on high-quality labeled data. In this work, to utilize unlabeled data for better prediction performance, we propose a method that combines semi-supervised learning with graph convolutional neural networks for chemical reaction prediction. First, we propose a Mean Teacher Weisfeiler–Lehman Network to find the reaction centers. Then, we construct the candidate product set. Finally, we use an Improved Weisfeiler–Lehman Difference Network to rank candidate products. Experimental results demonstrate that, with 400k labeled data, our framework can improve the top-5 accuracy by 0.7% using 35k unlabeled data. When the proportion of unlabeled data increases, the performance gain can be larger. For example, with 80k labeled data and 35k unlabeled data, the performance gain with our framework can be 1.8%. [ABSTRACT FROM AUTHOR]

A human can infer the magnitude of interaction force solely based on visual information because of prior knowledge in human–robot interaction (HRI). A method of reconstructing tactile information through cross-modal signal processing is proposed in this paper. In our method, visual information is added as an auxiliary source to tactile information. In this case, the receiver is only able to determine the tactile interaction force from the visual information provided. In our method, we first process groups of pictures (GOPs) and treat them as the input. Secondly, we use the low-rank foreground-based attention mechanism (LAM) to detect regions of interest (ROIs). Finally, we propose a linear regression convolutional neural network (LRCNN) to infer contact force in video frames. The experimental results show that our cross-modal reconstruction is indeed feasible. Furthermore, compared to other work, our method is able to reduce the complexity of the network and improve the material identification accuracy. [ABSTRACT FROM AUTHOR]

In the era of big data, using big data to realize the online estimation of battery SOH has become possible. Traditional solutions based on theoretical models cannot take into account driving behavior and complicated environmental factors. In this paper, an approximate SOH degradation model based on real operating data and environmental temperature data of electric vehicles (EVs) collected with a big data platform is proposed. Firstly, the health indicators are extracted from the historical operating data, and the equivalent capacity at 25 °C is obtained based on the capacity–temperature empirical formula and the capacity offset. Then, the attenuation rate during each charging and discharging process is calculated by combining the operating data and the environmental temperature. Finally, the long short-term memory (LSTM) neural network is used to learn the degradation trend of the battery and predict the future decline trend. The test results show that the proposed method has better performance. [ABSTRACT FROM AUTHOR]

Individuals with autism spectrum disorders (ASD) have impairment in interpreting emotional communication and the mental states of others, which limits their social competence. Mounting evidence has suggested that theory of mind (ToM) is a vital strategy to enhance social communication and interaction skills of children with ASD. However, very little research has looked at how ToM and social skills training affect social competence in adolescents with autism. This study examined the effectiveness of an intervention program, ToM-SS, which integrated the ToM and social skills training to improve the social competence of three adolescents with autism. A multiple baseline across behaviors design was adopted to evaluate the participants' learning outcomes and demonstrated a functional relationship between intervention and skill mastery. Results show that the intervention produced substantial improvements in students' acquisition of ToM (e.g., seeing leads to knowing and identifying desire-based and context-based emotions) and targeted social skills (e.g., praising others, expressing emotion and seeking help). Feedback and comments from teachers and parents also indicate good social validity of the intervention program. [ABSTRACT FROM AUTHOR]

Robot-assisted surgery is of growing interest in the surgical and engineering communities. The use of robots allows surgery to be performed with precision using smaller instruments and incisions, resulting in shorter healing times. However, using current technology, an operator cannot directly feel the operation because the surgeon-instrument and instrument-tissue interaction force feedbacks are lost during needle insertion. Advancements in force feedback and control not only help reduce tissue deformation and needle deflection but also provide the surgeon with better control over the surgical instruments. The goal of this review is to summarize the key components surrounding the force feedback and control during robot-assisted needle insertion. The literature search was conducted during the middle months of 2017 using mainstream academic search engines with a combination of keywords relevant to the field. In total, 166 articles with valuable contents were analyzed and grouped into five related topics. This survey systemically summarizes the state-of-the-art force control technologies for robot-assisted needle insertion, such as force modeling, measurement, the factors that influence the interaction force, parameter identification, and force control algorithms. All studies show force control is still at its initial stage. The influence factors, needle deflection or planning remain open for investigation in future. [ABSTRACT FROM AUTHOR]

In the process of using photocatalysts to treat tetracycline (TC) wastewater, the degradation efficiency of soybean powder carbon material (SPC) can be improved by loading it with cerium oxide (CeO2). In this study, firstly, SPC was modified by phytic acid. Then, the CeO2 was deposited on modified SPC using the self-assembly method. Catalyzed cerium (III) nitrate hexahydrate (CeH3NO4) was treated with alkali and calcined at 600 °C under nitrogen. XRD, XPS, SEM, EDS, UV-VIS /DRS, FTIR, PL and N2 adsorption–desorption methods were used to characterize the crystal structure, chemical composition, morphology, surface physical and chemical properties. The effects of catalyst dosage, monomer contrast, pH value and co-existing anions on TC oxidation degradation were investigated, and the reaction mechanism of a 600 Ce-SPC photocatalytic reaction system was discussed. The results show that the 600 Ce-SPC composite presents uneven gully morphology, which is similar to the natural "briquettes". The degradation efficiency of 600 Ce-SPC reached about 99% at 60 min under light irradiation when the optimal catalyst dosage and pH were 20 mg and 7. Meanwhile, the reusability of the 600 Ce-SPC samples showed good stability and catalytic activity after four cycles. [ABSTRACT FROM AUTHOR]

Mangrove ecosystems play a dominant role in global, tropical, and subtropical coastal wetlands. Remote sensing plays a central role in mangrove conservation, as it is the preferred tool for monitoring changes in spatiotemporal distribution. To improve correlated estimation accuracies and explore the influencing mechanisms based on the mangrove ground survey, this study used a support vector machine (SVM) machine learning and Res-UNet deep learning algorithms to identify the land area of mangrove forests and the crown surface cover area of mangrove forests in the Hainan Island from 1991 to 2021. Both classification techniques were verified by a confusion matrix, which from 1991 to 2021, revealed overall accuracies of 93.11 ± 1.54% and 96.43 ± 1.15% for SVM and Res-UNet, respectively. Res-UNet was more accurate in identifying the crown surface cover area, whereas SVM was more suitable for obtaining the land area. Furthermore, based on the crown surface cover area of the mangrove forests on the Hainan Island, influencing mechanisms were analyzed through dynamic changes and landscape patterns. Since 1991, the Hainan Island mangrove forest area has increased, with the center of mass moving from coastal areas to the ocean and increasing the overall landscape fragmentation. Moreover, the change in the mangrove forests area was correlated with economic development and the increasingly urban population of the entire island. Altogether, the reliable assessment of the tropical mangrove forest land area and crown surface cover provides an important research foundation for the protection and restoration plans of tropical mangrove forests. [ABSTRACT FROM AUTHOR]

Cadmium (Cd) is one of the toxic heavy metals found widely in the environment. Skin is an important target organ of Cd exposure. However, the adverse effects of Cd on human skin are still not well known. In this study, normal human skin keratinocytes (HaCaT cells) were studied for changes in cell viability, morphology, DNA damage, cycle, apoptosis, and the expression of endoplasmic reticulum (ER) stress-related genes (XBP-1, BiP, ATF-4, and CHOP) after exposure to Cd for 24 h. We found that Cd decreased cell viability in a concentration-dependent manner, with a median lethal concentration (LC50) of 11 µM. DNA damage induction was evidenced by upregulation of the level of γ-H2AX. Furthermore, Cd induced G0/G1 phase cell cycle arrest and apoptosis in a dose-dependent manner and upregulated the mRNA levels of ER stress biomarker genes (XBP-1, BiP, ATF4, and CHOP). Taken together, our results showed that Cd induced cytotoxicity and DNA damage in HaCaT cells, eventually resulting in cell cycle arrest in the G0/G1 phase and apoptosis. In addition, ER stress may be involved in Cd-induced HaCaT apoptosis. Our data imply the importance of reducing Cd pollution in the environment to reduce its adverse impacts on human skin. [ABSTRACT FROM AUTHOR]

Pretreatment ischemic location may be an important determinant for functional outcome prediction in acute ischemic stroke. In total, 143 anterior circulation ischemic stroke patients in the THRACE study were included. Ischemic lesions were semi-automatically segmented on pretreatment diffusion-weighted imaging and registered on brain atlases. The percentage of ischemic tissue in each atlas-segmented region was calculated. Statistical models with logistic regression and support vector machine were built to analyze the predictors of functional outcome. The investigated parameters included: age, baseline National Institutes of Health Stroke Scale score, and lesional volume (three-parameter model), together with the ischemic percentage in each atlas-segmented region (four-parameter model). The support vector machine with radial basis functions outperformed logistic regression in prediction accuracy. The support vector machine three-parameter model demonstrated an area under the curve of 0.77, while the four-parameter model achieved a higher area under the curve (0.82). Regions with marked impacts on outcome prediction were the uncinate fasciculus, postcentral gyrus, putamen, middle occipital gyrus, supramarginal gyrus, and posterior corona radiata in the left hemisphere; and the uncinate fasciculus, paracentral lobule, temporal pole, hippocampus, inferior occipital gyrus, middle temporal gyrus, pallidum, and anterior limb of the internal capsule in the right hemisphere. In conclusion, pretreatment ischemic location provided significant prognostic information for functional outcome in ischemic stroke. [ABSTRACT FROM AUTHOR]

With the development of biotechnology, luminescent nanoprobes for biological disease detection are widely used. However, the further application in clinic is limited by the reduced penetration depth in the tissues and light scattering. In this work, we have synthesized NaYF4:Yb,Er,Ce@SiO2-OAlg nanomaterials, which have both upconversion and near-infrared (NIR) luminescence. The optimized probes were determined to achieve cell imaging by its upconversion (UCL) luminescence and in vivo imaging through collection of NIR fluorescence signals simultaneously. The research is conducive to developing accurate diagnostic techniques based on UCL and NIR fluorescence imaging by a single nanoparticle. [ABSTRACT FROM AUTHOR]

Hypoeutectic Al-Si-Mg alloys with a silicon content of around 10 wt % are widely used in the aerospace and automotive fields due to their excellent casting properties. However, the occurrence of "silicon poisoning" weakens the refinement effect of a conventional refiner system such as Al-5Ti-1B. In this paper, we proposed the "pre-refinement" method to avoid the "Si poisoning" to recover the refinement effect of Al-5Ti-1B. The core concept was to adjust the order of adding the Si element to form the TiAl3 before forming the Ti-Si intermetallic compound. To prove the effectiveness of the "pre-refinement" method, three alloys of "pre-refinement", "post-refinement", and "non-refinement" of an Al-10Si-0.48Mg alloy were prepared and characterized in as-cast and heat-treatment states. The results showed that the average grain diameter of the "pre-refinement" alloy was 60.19% smaller than that of the "post-refinement" one and 81.34% smaller than that of the "non-refinement" one, which demonstrated that the proposed method could effectively avoid the "silicon poisoning" effect. Based on a refined grain size, the "pre-refinement" Al-10Si-0.48Mg alloy showed the best optimization effect in mechanical properties after a solid-solution and subsequent aging heat treatments. The best mechanical properties were found in the "pre-refinement" alloy with 2 h of solid solution treatment and 10 h of aging treatment: a hardness of 92 HV, a tensile strength of 212 MPa, and an elongation of 20%. [ABSTRACT FROM AUTHOR]

The correct Table 1 is as below: Table 1 Clinical and intracranial plaque characteristics of study population and comparison between stroke and non-stroke patients. B Text Correction b In Abstract, the sentence "They were assigned to the posterior circulation stroke (49 patients) and non-posterior circulation stroke group (159 patients) based on clinical presentation and diffusion-weighted imaging (DWI)" should be replaced with "They were assigned to the posterior circulation stroke (59 patients) and non-posterior circulation stroke group (149 patients) based on clinical presentation and diffusion-weighted imaging (DWI)". A Predictive Model for the Risk of Posterior Circulation Stroke in Patients with Intracranial Atherosclerosis Based on High Resolution MRI. [Extracted from the article]

Graph neural networks (GNNs) with feature propagation have demonstrated their power in handling unstructured data. However, feature propagation is also a smooth process that tends to make all node representations similar as the number of propagation increases. To address this problem, we propose a novel Block-Based Adaptive Decoupling (BBAD) Framework to produce effective deep GNNs by utilizing backbone networks. In this framework, each block contains a shallow GNN with feature propagation and transformation decoupled. We also introduce layer regularizations and flexible receptive fields to automatically adjust the propagation depth and to provide different aggregation hops for each node, respectively. We prove that the traditional coupled GNNs are more likely to suffer from over-smoothing when they become deep. We also demonstrate the diversity of outputs from different blocks of our framework. In the experiments, we conduct semi-supervised and fully supervised node classifications on benchmark datasets, and the results verify that our method can not only improve the performance of various backbone networks, but also is superior to existing deep graph neural networks with less parameters. [ABSTRACT FROM AUTHOR]

The combustion characteristics of laminar biogas premixed and diffusion flames in the presence of upward decreasing magnetic fields have been investigated in this study. The mechanism of magnet–flame interaction in the literature, in which magnetic fields change the behaviors of laminar flames due to the paramagnetic and diamagnetic properties of the constituent gases, is examined and the results are as follows. The magnetic field has no noticeable effect on premixed flames due to low oxygen concentration of the mixed gas at the injection and the relatively high flow momentum. However, due to the diffusion nature of diffusion flames and paramagnetic property of oxygen in ambient air, oxygen distributions are subjected to the gradient of magnetic flux, thus shortening the height of diffusion flames. Results also show that the flame volume is more strongly varied than flame height. Altered oxygen distributions result in improved combustion and higher flame temperature. In the case of current magnet–flame interaction, the magnetic driving force is combined with gravitational force, and a modified gravity g* as well as gravity modification factor G are derived to characterize the paramagnetism theory of oxygen. [ABSTRACT FROM AUTHOR]

Intracranial vertebrobasilar atherosclerosis is the main cause of posterior circulation ischemic stroke. We aimed to construct a predictive model for the risk of posterior circulation ischemic stroke in patients with posterior circulation atherosclerosis based on high-resolution MRI (HR-MRI). A total of 208 consecutive patients with posterior circulation atherosclerosis confirmed by HR-MRI, from January 2020 to July 2021, were retrospectively assessed. They were assigned to the posterior circulation stroke (49 patients) and non-posterior circulation stroke group (159 patients) based on clinical presentation and diffusion-weighted imaging (DWI). Demographic data, risk factors of atherosclerosis, laboratory findings, and imaging characteristics were extracted from electronic health records. Plaque features were investigated by HR-MRI. Fifty-three clinical or imaging features were used to derive the model. Multivariable logistic regression analysis was employed to construct the prediction model. The nomogram was evaluated for calibration, differentiation, and clinical usefulness. Plaque enhancement, plaque irregular surface morphology, artery location of plaque, and dorsal quadrant of plaque location were significant predictors for posterior circulation stroke in patients with intracranial atherosclerosis. Subsequently, these variables were selected to establish a nomogram. The model showed good distinction (C-index 0.830, 95% CI 0.766-0.895). The calibration curve also showed excellent consistency between the prediction of the nomogram and the observed curve. Decision curve analysis further demonstrated that the nomogram conferred significantly high clinical net benefit. The nomogram calculated from plaque characteristics in HR-MRI may accurately predict the posterior circulation stroke occurrence and be of great help for stratification of stroke decision making. [ABSTRACT FROM AUTHOR]

Hericium erinaceus, a culinary and medicinal mushroom, is widely consumed in Asian countries. Chemical investigation on the fruiting bodies of Hericium erinaceus led to the isolation of one new ergostane-type sterol fatty acid ester, erinarol K (1); and eleven known compounds: 5α,8α -epidioxyergosta-6,22-dien-3β-yl linoleate (2); ethyl linoleate (3); linoleic acid (4); hericene A (5); hericene D (6); hericene E (7); ergosta-4,6,8(14),22-tetraen-3-one (8); hericenone F (9); ergosterol (10); ergosterol peroxide (11); 3β,5α,6α,22E-ergosta-7,22-diene-3,5,6-triol 6-oleate (12). The chemical structures of the compounds were determined by 1D and 2D NMR (nuclear magnetic resonance) spectroscopy, mass spectra, etc. Anti-inflammatory effects of the isolated aromatic compounds (5–7, 9) were evaluated in terms of inhibition of pro-inflammatory mediator (TNF-α, IL-6 and NO) production in lipopolysaccharide (LPS)-stimulated murine RAW 264.7 macrophage cells. The results showed that compounds 5 and 9 exhibited moderate activity against TNF-α (IC50: 78.50 μM and 62.46 μM), IL-6 (IC50: 56.33 μM and 48.50 μM) and NO (IC50: 87.31 μM and 76.16 μM) secretion. These results supply new information about the secondary metabolites of Hericium erinaceus and their anti-inflammatory effects. [ABSTRACT FROM AUTHOR]

Intersex(ix), a gene involved in the sex-determining cascade of Drosophila melanogaster, works in concert with the female-specific product of doublesex (dsx) at the end of the hierarchy to implement the sex-specific differentiation of sexually dimorphic characters in female individuals. In this study, the ix homolog was identified in the brown planthopper (BPH), Nilaparvata lugens, which contained two splice variants expressed in both female and male insects. We found that Nlix played a vital role in the early nymphal development of BPH, showing an accumulated effect. RNAi-mediated knockdown of Nlix at 4th instar led to the external genital defects in both sexes, consequently resulting in the loss of reproductive ability in female and male individuals. After dsRNA injection, the males were normal on testes, while the females had defective ovarian development. Nlix was also required for early embryogenesis. Notably, when the dsNlix microinjection was performed in newly emerged females, the copulatory bursas were abnormally enlarged while the other tissues of the reproductive system developed normally. Our results demonstrated the pleiotropic roles of Nlix in embryogenesis and development of the reproductive system in a hemimetabolous insect species. [ABSTRACT FROM AUTHOR]

An accurate forecast of Global Horizontal solar Irradiance (GHI) and Direct Normal Irradiance (DNI) in cloudy conditions remains a major challenge in the solar energy industry. This study focuses on the impact of cloud microphysics on GHI and its partition into DNI and Diffuse Horizontal Irradiance (DHI) using the Weather Research and Forecasting model specifically designed for solar radiation applications (WRF-Solar) and seven microphysical schemes. Three stratocumulus (Sc) and five shallow cumulus (Cu) cases are simulated and evaluated against measurements at the US Department of Energy's Atmospheric Radiation Measurement (ARM) user facility, Southern Great Plains (SGP) site. Results show that different microphysical schemes lead to spreads in simulated solar irradiance components up to 75% and 350% from their ensemble means in the Cu and Sc cases, respectively. The Cu cases have smaller microphysical sensitivity due to a limited cloud fraction and smaller domain-averaged cloud water mixing ratio compared to Sc cases. Cloud properties also influence the partition of GHI into DNI and DHI, and the model simulates better GHI than DNI and DHI due to a non-physical error compensation between DNI and DHI. The microphysical schemes that produce more accurate liquid water paths and effective radii of cloud droplets have a better overall performance. [ABSTRACT FROM AUTHOR]

Under the control of the Montreal Protocol and its amendments, hydrofluorocarbons (HCFCs) are used as temporary substitutes for ozone-depleting substances, such as chlorofluorocarbons, and are regulated for consumption and production. China plans to phase out HCFCs by 2030, and HCFC-22 (CHClF2) is currently the most abundant HCFC in the atmosphere. This study measures the vertical profiles and total columns of atmospheric HCFC-22 from January 2017 to December 2022, based on the mid-infrared solar spectra recorded by the ground-based high-resolution Fourier transform infrared (FTIR) spectrometer at the Hefei remote sensing station. The HCFC-22 total columns over Hefei increased from 2017–2018 and gradually decreased in 2018–2022, with an annual variation rate of 5.98% and −1.02% ± 0.02%, respectively. Compared with the ACE-FTS satellite independent dataset, the FTIR data indicate good consistency with the ACE-FTS data at a 5–25 km altitude, with an average relative difference of −4.38 ± 0.83% between the vertical profiles. HCFC-22 emissions in the Yangtze River Delta from 2017 to 2022 are estimated, derived from measured total columns combined with the Lagrangian transport model and the Bayesian inversion technique. In the Yangtze River Delta, HCFC-22 emissions were high in 2017, with a value of 33.3 ± 16.8 kt, and decreased from 2018 to 2022, with a minimum of 27.3 ± 13.6 kt in 2022 during the observations. [ABSTRACT FROM AUTHOR]

To address the limitation of existing excavator optimization methods, which primarily focus on the force performance while neglecting energy consumption and fail to realize environmentally friendly and low-carbon designs, this paper proposes a new multi-objective collaborative optimization method for an excavator to reduce energy consumption during the working process while maintaining optimal performance. By formulating a mathematical model that quantifies the energy consumption during the working process, this paper optimizes the working conditions by analyzing the energy consumption characteristics under typical working conditions. To overcome the limitation of existing linear weighting methods in multi-objective optimization, such as imbalanced optimization quality among sub-objectives, this paper proposes a new modeling approach based on the loss degree of sub-objectives. A multi-objective collaborative optimization model for the excavator with reduced energy consumption is established, and a corresponding multi-objective collaborative optimization algorithm is developed and applied to achieve optimal solutions for sub-objectives. The optimization results demonstrate that applying the new multi-objective collaborative optimization method to the excavator achieves better optimization quality than traditional methods. It also provides a more balanced improvement in the optimization values of each sub-objective, resulting in a significant reduction in the energy consumption of the excavator during operation. [ABSTRACT FROM AUTHOR]

Simultaneous localization and mapping (SLAM) algorithms are widely applied in fields such as autonomous driving and target tracking. However, the effect of moving objects on localization and mapping remains a challenge in natural dynamic scenarios. To overcome this challenge, this paper proposes an algorithm for dynamic point cloud detection that fuses laser and visual identification data, the multi-stage moving object identification algorithm (MoTI). The MoTI algorithm consists of two stages: rough processing and precise processing. In the rough processing stage, a statistical method is employed to preliminarily detect dynamic points based on the range image error of the point cloud. In the precise processing stage, the radius search strategy is used to statistically test the nearest neighbor points. Next, visual identification information and point cloud registration results are fused using a method of statistics and information weighting to construct a probability model for identifying whether a point cloud cluster originates from a moving object. The algorithm is integrated into the front-end of the LOAM system, which significantly improves the localization accuracy. The MoTI algorithm is evaluated on an actual indoor dynamic environment and several KITTI datasets, and the results demonstrate its ability to accurately detect dynamic targets in the background and improve the localization accuracy of the robot. [ABSTRACT FROM AUTHOR]

Understanding the distribution of atmospheric water vapor (H2O) is crucial for global warming studies and climate change mitigation. In this study, we retrieved the ground layer, tropospheric and total columns of H2O using ground-based high-resolution Fourier transform infrared spectrometry (FTIR). The H2O total columns are obtained from near-infrared (NIR) and mid-infrared (MIR) spectra, and the ground layer and tropospheric H2O columns are retrieved from the MIR spectrum. The total columns of H2O retrieved from NIR and MIR have a good consistency (R = 0.989). Additionally, the ground layer H2O columns have a similar seasonal variation to total columns and tropospheric columns but have a higher seasonal amplitude. The ground layer H2O columns are close to the total columns and tropospheric columns in winter; however, in summer, the average difference between the ground layer and total columns and the value between the ground layer and tropospheric columns are large. This is mostly due to temperature variation. The temperature has a linear response to H2O, and the relationship between surface temperature and ln(XH2O) values in the ground layer, the entire atmosphere and the troposphere show a significantly positive correlation, and the correlation coefficient R is 0.893, 0.882 and 0.683, respectively. Furthermore, we selected the HYSPLIT model to simulate the back trajectories of air parcels in the four seasons in Hefei and find that the air mass transport has a significant impact on the local H2O change. These results demonstrate that ground-based high-resolution FTIR technology has high accuracy and precision in observing the vertical distribution and seasonal changes of H2O in different atmospheres. [ABSTRACT FROM AUTHOR]

Polygonati Rhizoma is a widely used traditional Chinese medicine (TCM) with complex pre-processing steps. Fermentation is a common method for processing TCM to reduce herb toxicity and enhance their properties and/or produce new effects. Here, in this study, using Bacillus subtilis and Saccharomyces cerevisiae, we aimed to evaluate the potential application of solid fermentation in isolating different functional polysaccharides from Polygonatum cyrtonema Hua. With hot water extraction, ethanol precipitation, DEAE anion exchange chromatography and gel filtration, multiple neutral and acidic polysaccharides were obtained, showing different yields, content, compositions and functional groups after fermentation. Combining in vitro experiments and in vivo aging and immunosuppressed mouse models, we further compared the antioxidant and immunomodulating bioactivities of these polysaccharides and found a prominent role of a natural polysaccharide (BNP) from fermented P. cyrtonema via Bacillus subtilis in regulating intestinal antioxidant defense and immune function, which may be a consequence of the ability of BNP to modulate the homeostasis of gut microbiota. Thus, this work provides evidence for the further development and utilization of P. cyrtonema with fermentation, and reveals the potential values of BNP in the treatment of intestinal disorders. [ABSTRACT FROM AUTHOR]

BaFe12O19-polypyrrolenanocomposites were prepared via the in situ chemical oxidative polymerization of pyrrole monomers in the presence of BaFe12O19 powder, with ammonium persulfate as an oxidant and sodium dodecyl benzene sulfonate as a dopant. X-ray diffraction measurements and Fourier-transform infrared spectroscopy indicated that there were no chemical interactions between BaFe12O19 and polypyrrole. In addition, scanning electron microscopy showed that the composites exhibited a core–shell structure. Subsequently, the prepared nanocomposite was used as a filler to prepare a coating suitable for ultraviolet curing. The performance of the coating was investigated by evaluating its hardness, adhesion, absorbance, and resistance to acids and alkalis. Importantly, the addition of BaFe12O19-polypyrrole nanocomposites not only improved the coating hardness and adhesion but also produced a coating with a good microwave absorption performance. The results suggested that BaFe12O19/PPy composite has a lower reflection loss peak and a larger effective bandwidth at the X band when the proportion of the absorbent sample is 5–7%, when the absorption performance is the best. The reflection loss is in the range of 8.88–10.92 GHz below −10 dB. [ABSTRACT FROM AUTHOR]

Through a two-step solvothermal method, different molar ratios of BiPO4 were grown in situ on the surface of oxygen-vacancy-rich BiOBr (Ov-BiOBr), successfully constructing a BiPO4/Ov-BiOBr heterojunction composite material. By constructing a novel type I high-low junction between the semiconductor BiPO4 and Ov-BiOBr, stronger oxidative holes or reductive electrons were retained, thereby improving the redox performance of the photocatalyst. The composite catalyst with a 10% molar content of BiPO4 demonstrated the highest degradation rate of tetracycline (TC), degrading over 95% within 90 min, with a rate constant of 0.02534 min−1, which is 2.3 times that of Ov-BiOBr and 22 times that of BiPO4. The 10% BiPO4/Ov-BiOBr sample displayed the best photocatalytic activity, producing 139 μmol·L−1 H2O2 in 120 min, which is 3.6 times the efficiency of Ov-BiOBr and 19 times that of BiPO4. This was due to the appropriate bandgap matching between BiPO4 and Ov-BiOBr, the photo-generated electron transfer channel via Bi-bridge, and efficient charge separation. It was inferred that the free radical species ·OH and ·O2− played the dominant role in the photocatalytic process. Based on experimental and theoretical results, a possible photocatalytic mechanism was proposed. [ABSTRACT FROM AUTHOR]

Elevated heart rate (HR) can be hypothesized to be involved in the pathways by which ambient air pollution, especially fine particulate matter (PM2.5), causes cardiovascular morbidity and mortality. However, evidence concerning long-term PM2.5 exposure and HR is still limited. Therefore, in this study, we assessed the associations of PM2.5 with HR levels and tachycardia prevalence and explored potential modifiers of the associations. We used baseline data of 1,802,207 adults from the Kashgar Prospective Cohort Study (KPCS). PM2.5 exposure was assessed based on satellite sensing data, meteorological factors, multi-resolution emission inventory, and measurements from ground-based surface monitors measurements. HR was measured using a calibrated electronic sphygmomanometer, and tachycardia was defined as resting heart rate (RHR) equal to or greater than 80 beats per minute. Linear regression and logistic regression models were employed to evaluate the associations of PM2.5 levels with RHR levels and tachycardia prevalence, respectively. Stratified analyses by sex, age, ethnicity, smoking status, alcohol use, and physical activity were also performed. The mean (standard deviation) age of the study participants was 39.4 (15.5) years old. In the adjusted models, an interquartile range (8.8 µg/m3) increase in PM2.5 levels was associated with 0.515 (95% confidence interval: 0.503–0.526) bpm increase in RHR levels and with 1.062-fold (95% confidence interval: 1.059–1.064) increase in the odds of tachycardia. The results were robust against several sensitivity analyses. In addition, we observed the above associations were stronger in participants that were men, of Uyghur ethnicity, smoking cigarettes, drinking alcohol, and having physical inactivity, compared to their counterparts. In summary, our findings indicate that long-term exposure to ambient PM2.5 may be hazardously associated with HR, and women, Uyghur people, and those with unhealthy lifestyles may be more vulnerable to the hazardous effects. [ABSTRACT FROM AUTHOR]

Advances in information technology have led to the proliferation of data in the fields of finance, energy, and economics. Unforeseen elements can cause data to be contaminated by noise and outliers. In this study, a robust online support vector regression algorithm based on a non-convex asymmetric loss function is developed to handle the regression of noisy dynamic data streams. Inspired by pinball loss, a truncated ε -insensitive pinball loss (TIPL) is proposed to solve the problems caused by heavy noise and outliers. A TIPL-based online support vector regression algorithm (TIPOSVR) is constructed under the regularization framework, and the online gradient descent algorithm is implemented to execute it. Experiments are performed using synthetic datasets, UCI datasets, and real datasets. The results of the investigation show that in the majority of cases, the proposed algorithm is comparable, or even superior, to the comparison algorithms in terms of accuracy and robustness on datasets with different types of noise. [ABSTRACT FROM AUTHOR]

Photocatalysis is a hopeful technology to solve various environmental problems, but it is still a technical task to produce large-scale photocatalysts in a simple and sustainable way. Here, nano-flower β-Bi2O3/TiO2 composites were prepared via a facile solvothermal method, and the photocatalytic performances of β-Bi2O3/TiO2 composites with different Bi/Ti molar ratios were studied. The nano-flower Bi2O3/TiO2 composites were studied by SEM, XRD, XPS, BET, and PL. The PL result proved that the construction of staggered heterojunction enhanced the separation efficiency of carriers. The degradation RhB was applied to study the photocatalytic performances of prepared materials. The results showed that the degradation efficiency of RhB increased from 61.2% to 99.6% when the molar ratio of Bi/Ti was 2.1%. It is a mesoporous approach to enhance photocatalytic properties by forming heterojunction in Bi2O3/TiO2 composites, which increases the separation efficiency of the generated carriers and improves photocatalytic properties. The photoactivity of the Bi2O3/TiO2 has no evident changes after the fifth recovery, indicating that the Bi2O3/TiO2 composite has distinguished stability. [ABSTRACT FROM AUTHOR]

Heterojunction photocatalytic materials show excellent performance in degrading toxic pollutants. This study investigates the influence of calcination temperature on the performances of floral Bi2O3/TiO2 composite photocatalyst crystal, which was prepared with glycerol, bismuth nitrate, and titanium tetrachloride as the major raw materials via the solvothermal method. XRD, SEM/TEM, BET, Uv-vis, and XPS were employed to analyze the crystal structure, morphology, specific surface area, band gap, and surface chemical structure of the calcined temperature catalysts. The calcination temperature influence on the catalytic performance of composite photocatalysis was tested with rhodamine B (RhB) as the degradation object. The results revealed the high catalytic activity and higher photocatalytic performance of the Bi2O3/TiO2 catalyst. The degradation efficiency of the Bi2O3/TiO2 catalyst to RhB was 97%, 100%, and 91% at 400 °C, 450 °C, and 500 °C calcination temperatures, respectively, in which the peak degradation activity appeared at 450 °C. The characterization results show that the appropriate calcination temperature promoted the crystallization of the Bi2O3/TiO2 catalyst, increased its specific surface area and the active sites of catalytic reaction, and improved the separation efficiency of electrons and holes. [ABSTRACT FROM AUTHOR]

Mining of closely spaced multilayer orebodies brings the problems of significant disturbance between adjacent mining layers and drastic structural changes in surrounding rock, which brings the need for a more effective stope support method. Previous research has made sound analysis on filling or bolt support, but neither of them can solely provide ideal support effects. Thus, a novel bolt-filling support method is proposed by utilizing the synergistic effect of rock bolts (cable bolts) and filling. Numerical simulation and similarity experiments were conducted in this research to analyze the support effect of this method for multilayer ore mining. For numerical simulation, the distinct-element modelling framework PFC2D (Particle Flow Code in 2 Dimensions) was applied for four support scenarios based on the calibration of the microscopic parameters of particles in vanadium shale ores. The numerical simulation results show that the number of fractures decreases from 1311 without support through 652 with 95% filling support to 410 with bolt-filling support, which is resulted from the redistribution of the force chains due to support change. On the other hand, a 300 cm ×180 cm × 40 cm similarity model with a geometry similarity constant of 100 was established based on the 4# rock layer profile of Mount Shangheng. Two parts of similarity experiments were conducted to investigate the strains around the stopes in multi-layer ore mining for three support scenarios. The experiment results prove that the highest strain is in the center of the roof on the upper goaf, and the roof-bolt filling support induces smaller strains than zero support and conventional filling support. Finally, an effective bolt-filling support system has been developed and validated, which can improve the safety and the stability of the roofs and interlayers during the mining process of closely spaced multilayer orebody by reducing the overall load and fractures in surrounding rock. [ABSTRACT FROM AUTHOR]

Background Understanding the transmission source, pattern, and mechanism of infectious diseases is essential for targeted prevention and control. Though it has been studied for many years, the detailed transmission patterns and drivers for the seasonal influenza epidemics in China remain elusive. Methods In this study, utilizing a suite of epidemiological and genetic approaches, we analyzed the updated province-level weekly influenza surveillance, sequence, climate, and demographic data between 1 April 2010 and 31 March 2018 from continental China, to characterize detailed transmission patterns and explore the potential initiating region and drivers of the seasonal influenza epidemics in China. Results An annual cycle for influenza A(H1N1)pdm09 and B and a semi-annual cycle for influenza A(H3N2) were confirmed. Overall, the seasonal influenza A(H3N2) virus caused more infection in China and dominated the summer season in the south. The summer season epidemics in southern China were likely initiated in the "Lingnan" region, which includes the three most southern provinces of Hainan, Guangxi, and Guangdong. Additionally, the regions in the south play more important seeding roles in maintaining the circulation of seasonal influenza in China. Though intense human mobility plays a role in the province-level transmission of influenza epidemics on a temporal scale, climate factors drive the spread of influenza epidemics on both the spatial and temporal scales. Conclusion The surveillance of seasonal influenza in the south, especially the "Lingnan" region in the summer, should be strengthened. More broadly, both the socioeconomic and climate factors contribute to the transmission of seasonal influenza in China. The patterns and mechanisms revealed in this study shed light on the precise forecasting, prevention, and control of seasonal influenza in China and worldwide. [ABSTRACT FROM AUTHOR]

Solar forecasting constitutes a critical tool for operating, producing and storing generated power from solar farms. In the framework of the International Energy Agency's Photovoltaic Power Systems Program Task 16, the solar irradiance nowcast algorithms, based on five all-sky imagers (ASIs), are used to investigate the feasibility of ASIs to foresee ramp events. ASIs 1–2 and ASIs 3–5 can capture the true ramp events by 26.0–51.0% and 49.0–92.0% of the cases, respectively. ASIs 1–2 provided the lowest (<10.0%) falsely documented ramp events while ASIs 3–5 recorded false ramp events up to 85.0%. On the other hand, ASIs 3–5 revealed the lowest falsely documented no ramp events (8.0–51.0%). ASIs 1–2 are developed to provide spatial solar irradiance forecasts and have been delimited only to a small area for the purposes of this benchmark, which penalizes these approaches. These findings show that ASI-based nowcasts could be considered as a valuable tool for predicting solar irradiance ramp events for a variety of solar energy technologies. The combination of physical and deep learning-based methods is identified as a potential approach to further improve the ramp event forecasts. [ABSTRACT FROM AUTHOR]

There are many reports on g-C3N4 nanosheet and BiOCl nanosheet, but few studies on other morphologies of g-C3N4 and BiOCl. Herein, a g-C3N4 nanoball/BiOCl nanotube heterojunction prepared by a simple one-step acetonitrile solvothermal method is reported. The XRD results prove that the g-C3N4/BiOCl composites can be prepared in one step. SEM results revealed that the g-C3N4 was spherical and the BiOCl was tubular. The HRTEM results indicate that g-C3N4 has an amorphous structure and that the (100) crystal plane of BiOCl borders the g-C3N4. Spherical g-C3N4 has a narrow band gap (approximately 1.94 eV), and the band gap of g-C3N4/BiOCl after modification was also narrow. When the BiOCl accounted for 30% of the g-C3N4/BiOCl by mass, the quasi-primary reaction rate constant of RhB degradation was 45 times that of g-C3N4. This successful preparation method for optimizing g-C3N4 involving simple one-step template-free synthesis may be adopted for the preparation of diverse-shapes and high-performance nanomaterials in the future. [ABSTRACT FROM AUTHOR]

In the construction of the new shield tunnels crossing existing tunnels, grouting rings are often installed in the existing tunnels for protection. To study the effect of grouting rings on the settlement of existing tunnels, the variations of soil properties and relevant parameters before and after the grouting are analyzed. By considering the effect of the grouting ring on the reduction of the stress and the reinforcement of the surrounding foundation soil, the stress reduction model of the heterogeneous soil layer and the model of the tunnel settlement calculation are proposed. The formula for the reduction of the stress after passing through the grouting ring is deduced. Moreover, by comprehensively taking the influences of the shield excavation and grouting ring into account, the formula for calculating the vertical displacement of the existing tunnel caused by the excavation of the new tunnel is derived. Further, the impacts of the length and the thickness of the grouting ring on the settlement of the existing tunnel are studied. The results of the theoretical calculation method proposed herein are well consistent with the data computed by the finite element model, and both follow a relatively similar change trend. According to the obtained results, installing the grouting ring on the existing tunnel can effectively reduce the tunnel settlement. Finally, the results demonstrate that increasing the length and the thickness of the grouting ring can strengthen the protection of the existing tunnel, but the effect gradually decreases. [ABSTRACT FROM AUTHOR]

In order to reduce the disturbance to adjacent tunnels caused by tunnel crossing, the existing tunnels are often reinforced by setting grouting rings along the pipe piece ring. In this context, the volume expansion of the grouted soil has to be taken into account, and a mechanical model of the volume expansion of the grouting rings is proposed here to study the effect of the grouting rings of new tunnels on the additional stress on the existing tunnels as well as their vertical displacement. The additional stresses on and the vertical displacement of the axis of the existing tunnels caused by the expansion of the grouting rings were deduced based on the stochastic medium theory. The influences of various volumetric expansion rates (Q) of the grouting rings, different lengths of the grouting rings, and different tunnel crossing angles on the settlement of and the additional stress on the existing tunnels were studied. The results demonstrate that the grouting rings can effectively reduce the impacts of the additional stress and the settlement deformation on the existing tunnels. The results of the tunnel settlement obtained from the calculation method proposed in this paper are in good agreement with the measured engineering data. [ABSTRACT FROM AUTHOR]

Real-time (RT) ocean surface wind can make key improvements to disaster alarmingand safety of maritime navigation to avoid loss in property and human lives. Wind scatterometry is a well-acquainted way of obtaining good quality ocean surface winds, and it has been in application for decades. Existing wind-obtaining chains employ ground stations for receiving observations and can, at best, provide products in around 30 minutes for limited regions. In recent years, a satellite information-obtaining and transmission network is the new trend of Earth observation. In this research, on-board wind retrieval environment and procedures, which are different from traditional wind-obtaining chains, are proposed. First, the establishment of the on-board environment is instructed. Structures of each module are provided. The ground simulation system is been established based on this. After that, existing observing and processing routines of wind scatterometry are described, and then an on-board processing chain proposed and described. Modifications to existing satellite-ground chains are highlighted. The proposed method is validated in Level 0 data from the Chinese–French Oceanic SATellite (CFOSAT). Experiments indicate that the proposed on-board processing procedure can provide comparable results to ground-processed wind products. The root-mean-square error (RMSE) of wind speed for a track of data used in the experiment was about 0.26 m/s, and it was about 0.8° for wind direction. By decreasing wind field result quality, calculation time can be lessened in the on-board environment. However, it is found that in the whole chain of on-board wind generation, the most time-consuming procedure is observation-obtaining. The proposed on-board processing method can achieve good wind accuracy while meeting RT applications with good processing time. This provides a good complement to existing on-board-observing-ground-processing chains for RT applications. [ABSTRACT FROM AUTHOR]

As a new and emerging technology, photocatalytic oxidation is widely used in the fields of sewage treatment and organic pollution control. In this study, CdS nanoparticles were prepared at room temperature by an innovative preparation method, then TiO2 nanorod–CdS nanoparticle heterojunction photocatalysts were prepared using the solvothermal method, with TiCl3 used as the precursor for TiO2 nanorods. This study mainly took advantage of the small size of the CdS nanoparticles in combination with TiO2 nanorods, and the resultant heterojunctions had large specific surface areas, thereby increasing the contact area between the catalysts and the contaminants. In addition, due to the lower band gap energy (2.4 eV) of CdS, the photo response range of the heterojunction photocatalysts was also increased. In an experimental study, through photocatalytic performance tests of the catalysts with different weight ratios, it was found that the TiO2(40%)@CdS composite had the best photocatalytic performance and the highest catalytic rate. BET, SEM, and other tests showed that the specific surface area of the TiO2(40%)@CdS composite was the largest. TiO2 nanorods and CdS particles were uniformly distributed in the composite, and the optical response range was extended to the visible light region. [ABSTRACT FROM AUTHOR]

The Jiashengpan Zn–Pb deposit is located in the Langshan-Zhaertai region of the North China Craton. Zinc-lead mineralization at the Jiashengpan shows characteristics of shear-zone controlled syn-metamorphic mineralization. The 39Ar/40Ar ages of syn-ore hydrothermal muscovite averages at ~380 Ma, suggesting that the Zn–Pb mineralization took place in the Devonian. These results agree with zircon U–Pb ages of post-ore granite, which constrain the ore formation to be older than 277 ± 2 Ma. Ore formation was coeval with the emplacement of regional orogenic belts that formed as result of subduction associated with the closure of the eastern Paleo-Asian Ocean (~400 Ma). The Jiashengpan deposit provides evidence for base metal mineralization associated with metamorphogenic and shear-zone controlled characteristics during continental-continental collision, stressing the significance of orogenic activities for enrichment of base metals. [ABSTRACT FROM AUTHOR]

Histone acetylation or deacetylation is closely associated with the progression of multiple myeloma (MM). Currently, many histone deacetylase (HDAC) inhibitors have been approved for being used in clinical trials, but theirtherapeutic effectsarestill not ideal. As a novel HDAC inhibitor, hydroxamicacid-based small-molecule N-hydroxy-4-(2-[(2-hydroxyethyl)(phenyl)amino]-2-oxoethyl)benzamide (HPOB)’s possible roles in MM have not been studied. In this present study, the effect of HPOB as a potential anti-tumor agent in preventingproliferation and inducing apoptosis of MM cells had been investigated in detail. Our results showed that HPOB decreased the survival of MM cells in dose- and time-dependent manner. In addition, HPOB caused the accumulation of MM cells in G1 phase compared with the dimethylsulfoxide (DMSO) control group. Interestingly, we found that HPOB could overcome bortezomib (BTZ) resistance inMM cells and combining HPOB with BTZ could further sensitize MM cells. Certainly, our data illuminated that HPOB-mediated cell death occurs via transcriptional activation of p21, which was associated with an elevated level of global histone 3 acetylation (H3Ac) modification. Therefore, HPOB could be a potential candidate for MM treatment and the combination of HPOB and bortezomibcould bea possible therapeutic strategy for relapsed and refractory MM. [ABSTRACT FROM AUTHOR]

In this paper, we establish the solvability conditions and the formula of the general solution to a Sylvester-like quaternion matrix equation. As an application, we give some necessary and sufficient conditions for a system of quaternion matrix equations to be consistent, and present an expression of the general solution of the system when it is solvable. We present an algorithm and an example to illustrate the main results of this paper. The findings of this paper generalize the known results in the literature. [ABSTRACT FROM AUTHOR]

Herein, a facile method for the preparation of an acrylic resin-based superhydrophobic coating is provided. Firstly, ZnO nanoparticles were modified with silane to obtain hydrophobic ZnO, which was then homogeneously blended with acrylic resin. Subsequently, the mixture was sprayed on an aluminum sheet to form a cured coating. The surface composition and morphology of the coating were characterized using X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), and scanning electron microscopy (SEM). The hydrophobicity, wear resistance, and antibacterial properties of the prepared samples were tested. The optimized hydrophobicity was achieved with 10 wt% modification agent and resin-to-ZnO mass ratio of 1:4, exhibiting contact and sliding angles of 168.11° and 7.2°, respectively. Wear resistance was insufficient with a low resin content, while it grew with the increase in the resin content. However, when the resin content was excessively high, the hydrophobicity was reduced because the resin could wrap the modified ZnO nanoparticles and decrease the number of hydrophobic groups on the surface. Compared with the pure acrylic resin coating, the ZnO nanoparticle/acrylic resin superhydrophobic coating demonstrated a significant enhancement in the antibacterial properties. [ABSTRACT FROM AUTHOR]

Vertical profiles and stratospheric HNO3 and HCl columns are retrieved by ground-based high resolution Fourier transform infrared spectroscopy (FTIR) remote sensing measurements at the Hefei site in China. The time series of stratospheric HNO3 and HCl columns from January 2017 to December 2019 showed similar annual variation trends, with an annually decreasing rate of (−9.45 ± 1.20)% yr−1 and (−7.04 ± 0.81)% yr−1 for stratospheric HNO3 and HCl, respectively. The seasonal amplitudes of stratospheric HNO3 and HCl are 2.67 × 1015 molec cm−2 and 4.76 × 1014 molec cm−2 respectively, both reaching their maximum in March and their minimum in September, due to the tropopause height variation. Further, HNO3 and HCl data were used to compare with Microwave Limb Sounder (MLS) satellite data. MLS satellite data showed similar seasonal variations and annual rates with FTIR data, and the stratospheric HNO3 and HCl columns of the two datasets have correlation coefficients (r) of 0.87 and 0.88, respectively. The mean bias between satellite and FTIR data of stratospheric HNO3 and HCl columns are (−8.58 ± 12.22)% and (4.58 ± 13.09)%, respectively. [ABSTRACT FROM AUTHOR]

With the rapid consumption of fossil fuels, along with the ever-increasing environmental pollution, it is becoming a top priority to explore efficient photocatalysts for the production of renewable hydrogen and degradation of pollutants. Here, we fabricated a composite of g-C3N4/TiO2 via an in situ growth method under the conditions of high-temperature calcination. In this method, TiO2 nanowires with a large specific surface area could provide enough space for loading more g-C3N4 nanoparticles to obtain C3N4/TiO2 composites. Of note, the g-C3N4/TiO2 composite could effectively photocatalyze both the degradation of several pollutants and production of hydrogen, both of which are essential for environmental governance. Combining multiple characterizations and experiments, we found that the heterojunction constructed by the TiO2 and g-C3N4 could increase the photocatalytic ability of materials by prompting the separation of photogenerated carriers. Furthermore, the photocatalytic mechanism of the g-C3N4/TiO2 composite was also clarified in detail. [ABSTRACT FROM AUTHOR]

Distribution mismatch caused by various resolutions, backgrounds, etc. can be easily found in multi-sensor systems. Domain adaptation attempts to reduce such domain discrepancy by means of different measurements, e.g., maximum mean discrepancy (MMD). Despite their success, such methods often fail to guarantee the separability of learned representation. To tackle this issue, we put forward a novel approach to jointly learn both domain-shared and discriminative representations. Specifically, we model the feature discrimination explicitly for two domains. Alternating discriminant optimization is proposed to obtain discriminative features with an l2 constraint in labeled source domain and sparse filtering is introduced to capture the intrinsic structures exists in the unlabeled target domain. Finally, they are integrated in a unified framework along with MMD to align domains. Extensive experiments compared with state-of-the-art methods verify the effectiveness of our method on cross-domain tasks. [ABSTRACT FROM AUTHOR]

In insect parasitoids, fatty acid synthases (FASs) have received less attention and their roles associated with lipogenesis loss are far from clear. Meteorus pulchricornis is a solitary endoparasitoid wasp of many larvae of lepidopteran pests. The lipid content during developmental stages of M. pulchricornis was measured; it was higher in the larval and pupal stages but declined from six-day-old pupae. Lipid accumulation constantly decreased in the adult stage, even after feeding on honey solutions. To investigate the roles of FASs in lipid synthesis in M. pulchricornis, four FAS genes (MpulFAS1~4) were identified from the transcriptome database of M. pulchricornis. All FAS genes included full-length open reading frames and shared 72–79% similarity with the sequences of Microplitis demolitor. qRT-PCR validation showed that all four FASs had the highest expression after the adult wasps were fed on honey diets. MpulFAS1 and MpulFAS2 reached their expression peaks at the adult stage but MpulFAS3 and MpulFAS4 peaked at the larval stage. To further study the function of FASs, dsRNA injection knocked down the expression of four MpulFASs and resulted in a significant decline of lipid content at the adult stage in M. pulchricornis. Results from this study suggest that M. pulchricornis adults cannot accumulate lipid content effectively and FASs may still contribute to lipid synthesis in the adult stage. This broadens the knowledge on the ability of lipid synthesis in parasitoid wasps and provides insight into the roles of FASs in insects with parasitic life-history traits. [ABSTRACT FROM AUTHOR]

The electron transport layer (ETL) is very crucial for enhancing the device performance of polymer solar cells (PSCs). Meanwhile, thickness-insensitive and environment-friendly water/alcohol soluble processing are two essential requirements for large-scale roll-to-roll commercial application. Based on this, we designed and synthesized two new n-type ETLs with tetraethylene pentamine or butyl sulfonate sodium substituted tetraethylene pentamine as the branched side chains and high electron affinities perylene diimide (PDI) as the central core, named as PDIPN and PDIPNSO3Na. Encouragingly, both PDIPN and PDIPNSO3Na can effectively reduce the interfacial barrier and improve the interfacial contact. In addition, both of them can exhibit strong n-type self-doping effects, especially the PDIPN with higher density of negative charge. Consequently, compared to bare ITO, the PCE of the devices with ITO/PDIPN and ITO/PDIPNSO3Na ETLs has increased to 3–4 times. Our research results indicate that n-type self-doping PDI-based ETL PDIPN and PDIPNSO3Na could be promising candidates for ETL in environment-friendly water/alcohol soluble processing large-scale PSCs. [ABSTRACT FROM AUTHOR]