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Osteoarthritis is a chronic inflammatory disease characterized by cartilage degeneration. Anti‐inflammatory therapy has limited effects, and effective reduction of cartilage wear through lubrication is essential. In vivo stability and lubricity of commercial lubricants are insufficient, leading to failure of lubricating treatment and progression of osteoarthritis. To address these issues, new therapeutic methods combining anti‐inflammation and stable high‐performance lubrication are developed. Inspired by the sliding mechanism of snowboards, a "nano‐snowboard" by modifying molybdenum disulfide (MoS2) with a biomimetic phospholipid polymer poly (dopamine methacrylamide‐co‐2‐methacryloyloxyethyl phosphorylcholine) (PDMPC) and loading anti‐inflammatory drug diclofenac sodium (DS), namely MoS2‐PDMPC‐DS, has been synthesized. MoS2 with a 2D layered structure and photothermal properties, serves as solid lubricant and drug carrier. Meanwhile, the modification of PDMPC on the surface of MOS2 avoids the oxidative denaturation of MoS2 in a physiological environment, forming solid–liquid composite lubrication and improving the lubricity and stability of MoS2 in the joint cavity. In vitro and in vivo experiments show that MoS2‐PDMPC‐DS can stay in the joint cavity for more than one week and exert long‐lasting lubrication and anti‐inflammatory effects to treat osteoarthritis effectively. This solid–liquid composite lubricating nano‐snowboard provides a new idea for synergistic anti‐inflammatory and lubricating treatment of osteoarthritis. [ABSTRACT FROM AUTHOR]

As the global semiconductor industry has entered a new round of rapid growth, it has also entered a golden cycle of economic growth. Semiconductor companies increase their intrinsic value through financing, industry mergers and acquisitions, and venture capital searches. At the same time, market investors pay more attention to the intrinsic value of companies when looking for good investment targets. Therefore, the systematic risk assessment of the global semiconductor market has become a common concern of market investors and corporate management. In this context, this paper found a method that can assess the systemic risk of the semiconductor global market, which is to use the K-means algorithm based on deep feature fusion. This paper analyzed the algorithm in depth, analyzed the quantum space of tensors, and used the definition of cluster fusion to obtain the relationship between the projection matrices U and V. Experiments were carried out on the improved algorithm, and market research was conducted on a multinational semiconductor company A, which mainly included the basic statistics of the rate of return and the ACF and PACF coefficients of the rate of return series. Finally, the stock risk comparison of company A and company B in the same period was carried out. The experimental results showed that comparing the three items of compound growth rate, coefficient of variation, and active rate coefficient, the highest compound growth rate was 0.41, which came from Category 2, the highest variation coefficient was 2.31, which came from Category 10, and the highest active rate coefficient was 1.78, which came from Category 9. The experimental content was completed well. [ABSTRACT FROM AUTHOR]

CO2 + O2in-situ leaching (ISL) of sandstone-type uranium ore represents the third generation of solution mining in China. In this study, reactive transport modeling of the interaction between hydrodynamic and geochemical reactions is performed to enable better prediction and regulation of the CO2 + O2in-situ leaching process of uranium. Geochemical reactions between mining solutions and rock, and the kinetic uranium dissolution controlled by O2 (aq) and bicarbonate ( HCO 3 - ) are considered in the CO2 + O2 ISL reactive transport model of a typical sandstone-hosted uranium ore deposit in northern China. The reactive leaching of uranium is most sensitive to the spatial distribution of the mineralogical properties of the uranium deposit. Stochastic geostatistical models are used to represent the uncertainty on the spatial distribution of mineral grades. A Monte Carlo analysis was also performed to simulate the uranium production variability over an entire set of geostatistical realizations. The ISL stochastic simulation performed with the selected geostatistical realizations approximates the uranium production variability well. The simulation results of the ISL reactive transport model show that the extent of the uranium plume is highly dependent on mineralogical heterogeneity. The uncertainty analysis suggests the effect of uranium grade heterogeneity was found to be important to improve the accurate capture of the uncertainty. This study provides guidance for the accurate simulation and dynamic regulation of the CO2 + O2 leaching process of uranium at the scale of large mining areas. [ABSTRACT FROM AUTHOR]

This paper presents a high-stability and low-jitter Arbitrary Timing Generator (ATG) design based on the Xilinx Field Programmable Gate Array (FPGA) and its special integrated delay line. In recent years, FPGA-based or application specific integrated circuit-based delay lines have been used to achieve picosecond-level timing resolution. Devices with pure digital delay methods can only acquire triggers at the clock rising edges when triggered externally. Therefore, there is a large time irregularity caused by the uncertainty of the entry time of the trigger, which is difficult to compensate and leads to a large time jitter of outputs. We describe the design of an ATG that includes jitter self-measurement and calibration methods, which is available for both internal and external trigger modes. This structure is completely based on the FPGA's own resources and has the advantages of being simple and flexible. Experimental results show a sub-nanosecond timing resolution of 78 ± 20 ps with a minimum of 120 ps and a time jitter of 160 ± 20 ps in the external trigger mode after compensation. [ABSTRACT FROM AUTHOR]

AbstractThis study investigated the strength characteristics of dredged marine clays treated with fly ash with varying porewater salinities. A series of laboratory tests were conducted on fly ash-treated dredged marine clay specimens with various salinities and curing times. In the direct shear tests, observed patterns revealed a consistent initial rapid increase in shear stress with the increase of horizontal displacement, followed by either a gradual decline or stabilization after reaching the peak shear stress. The variation curve consistently positioned the lower salinity or longer curing time above the higher salinity or shorter curing time. Furthermore, the shear strength at a given vertical stress consistently decreases with increasing salinity while ascending with increasing curing time. This indicated that curing time positively influences shear strength development, while the presence of salt negatively affects it. Both strength parameters cohesion and friction angle exhibited growth trends with increased curing time but displayed a decline as salinity increased from 0% to 6%. Unconfined compressive strength test results showed a strain-softening behavior for all tested specimens. The compressive strength demonstrated a declining trend with rising salinity, with a more pronounced decrease observed within the initial 7d compared to the less significant change between 7d and 28d. [ABSTRACT FROM AUTHOR]

The complex behavior of uranium in recovery is mostly driven by water-rock interactions following lixiviant injection into ore-bearing aquifers. Significant challenges exist in exploring the geochemical processes responsible for uranium release and mobilization. Herein this study provides an illustration of a ten-year field scale CO 2 and O 2 in-situ leaching (ISL) process at a typical sandstone-hosted uranium deposit in northern China. We also conducte a three-dimensional (3-D) multicomponent reactive transport model to assess the effects of potential chemical reactions on uranium recovery, in particular, to focus on the role of sulfide mineral pyrite (FeS 2). Numerical simulations are performed considering three potential ISL reaction pathways to determine the relative contributions to uranium release, and the results indicate that bicarbonate promotes the oxidative dissolution of uranium-bearing minerals and further accelerates the uranium leaching in a neutral geochemical system. Moreover, the presence of FeS 2 exerts a strong competitive role in the uranium-bearing mineral dissolution by increasing oxygen consumption, favoring the formation of iron oxyhydroxide, and therefore causing an associated decrease in uranium recovery rates. The simulation model demonstrates that dissolution of carbonate neutralizes acidic water generated from pyrite oxidation and aqueous CO 2 dissociation. In addition, the cation concentrations (i. e., Ca and Mg) are increasing in the pregnant solutions, showing that the recycling of lixiviants and kinetic dissolution of carbonate generates a larger number of dissolved Ca and Mg and inevitably triggers the secondary dolomite mineral precipitation. The findings improve our fundamental understanding of the geochemical processes in a long-term uranium ISL system and provide important environmental implications for the optimal design of uranium recovery, remediation, and risk exposure assessment. [Display omitted] • Process-based reactive transport modeling is developed for clarifying uranium recovery processes. • Assessment of multi-reaction showed dissolved oxygen dominates the CO 2 and O 2 in-situ leaching of uranium. • Co-existing pyrite plays a significant role in uranium mobilization. • Chemical clogging induced by secondary mineral precipitates is non-ignorable. [ABSTRACT FROM AUTHOR]

Under the new development philosophy of carbon peaking and carbon neutrality, CO2 and O2 in situ leaching (ISL) has been identified as a promising technique for uranium mining in China, not only because it solves carbon dioxide utilization and sequestration, but it also alleviates the environmental burden. However, significant challenges exist in assessment of CO2 footprint and water‐rock interactions, due to complex geochemical processes. Herein this study conducts a three‐dimensional, multicomponent reactive transport model (RTM) of a field‐scale CO2 and O2 ISL process at a typical sandstone‐hosted uranium deposit in Songliao Basin, China. Numerical simulations are performed to provide new insight into quantitative interpretation of the greenhouse gas (CO2) footprint and environmental impact (SO42–) of the CO2 and O2 ISL, considering the potential chemical reaction network for uranium recovery at the field scale. RTM results demonstrate that the fate of the CO2 could be summarized as injected CO2 dissolution, dissolved CO2 mineralization and storage of CO2 as a gas phase during the CO2 and O2 ISL process. Furthermore, compared to acid ISL, CO2 and O2 ISL has a potentially smaller environmental footprint, with 20% of SO42– concentration in the aquifer. The findings improve our fundamental understanding of carbon utilization in a long‐term CO2 and O2 ISL system and provide important environmental implications when considering complex geochemical processes. [ABSTRACT FROM AUTHOR]

Background: While pathogenic mutations in BSCL2/Seipin cause congenital generalized lipodystrophy, the underlying mechanism is largely unknown. In this study, we investigated whether and how the pathogenic missense A212P mutation of Seipin (Seipin-A212P) inhibits adipogenesis. Methodology/Results: We analyzed gene expression and lipid accumulation in stable 3T3-L1 cell lines expressing wild type (3T3-WT), non-lipodystrophic mutants N88S (3T3-N88S) and S90L (3T3-S90L), or lipodystrophic mutant A212P Seipin (3T3-A212P). When treated with adipogenic cocktail, 3T3-WT, 3T3-N88S and 3T3-S90L cells exhibited proper differentiation into mature adipocytes, indistinguishable from control 3T3-L1 cells. In contrast, adipogenesis was significantly impaired in 3T3-A212P cells. The defective adipogenesis in 3T3-A212P cells could be partially rescued by either PPARγ agonist or PPARγ overexpression. Gene expression profiling by microarray revealed that inhibition of adipogenesis was associated with activation of inflammatory genes including IL-6 and iNOS. We further demonstrated that Seipin-A212P expression at pre-differentiation stages significantly activated inflammatory responses by using an inducible expression system. The inflammation-associated inhibition of adipogenesis could be rescued by treatment with anti-inflammatory agents. Conclusions: These results suggest that pathogenic Seipin-A212P inhibits adipogenesis and the inhibition is associated with activation of inflammatory pathways at pre-differentiation stages. Use of anti-inflammatory drugs may be a potential strategy for the treatment of lipodystrophy. [ABSTRACT FROM AUTHOR]

The rational control of intrinsic defects in materials can significantly enhance their scientific and technological potentials, but it remains a long‐standing challenge in nanocrystal‐in‐glass composites (NGCs). Herein, a defect engineering strategy mediated by the mixed alkali effect is proposed and experimentally demonstrated for NGCs. Interestingly, the hybridization of large alkali ions can effectively increase the barrier of Li+ migration and reduce the Li‐related defects in LiNbO3 NGC. As a result, a novel LiNbO3 NGC with greatly reduced Li‐related defects, high crystallinity of over 60%, and excellent optical transmission are successfully fabricated. This unique NGC configuration facilitates efficient transverse second harmonic generation (TSHG) in a broad wavelength region. Based on the above effects, a standard TSHG device is fabricated and implemented to monitor ultrashort optical pulses with duration in the order of ≈10−13 s over a broad wavelength region, down to 780 nm. The proposed strategy not only provides a new idea for defect engineering in materials science but also has great significance for boosting the practical applications of NGCs in ultrashort optical pulse monitoring. [ABSTRACT FROM AUTHOR]

Automation is an inevitable trend in the development of tunnel shotcrete machinery. Tunnel environmental perception based on 3D LiDAR point cloud has become a research hotspot. Current researches about the detection of tunnel point clouds focus on the completed tunnel with a smooth surface. However, few people have researched the automatic detection method for steel arches installed on a complex rock surface. This paper presents a novel algorithm to extract tunnel steel arches. Firstly, we propose a refined function for calibrating the tunnel axis by minimizing the density variance of the projected point cloud. Secondly, we segment the rock surface from the tunnel point cloud by using the region-growing method with the parameters obtained by analyzing the tunnel section sequence. Finally, a Directed Edge Growing (DEG) method is proposed to detect steel arches on the rock surface in the tunnel. Our experiment in the highway tunnels under construction in Changsha (China) shows that the proposed algorithm can effectively extract the points of the edge of steel arches from 3D LiDAR point cloud of the tunnel without manual assistance. The results demonstrated that the proposed algorithm achieved 92.1% of precision, 89.1% of recall, and 90.6% of the F-score. [ABSTRACT FROM AUTHOR]

Aptamers can bind specifically to heavy metal ions, and aptamer-based biosensors for heavy metal detection with high sensitivity have been extensively developed. However, their detection sensitivity is quite limited to specific conditions due to unknown mechanisms of environmental influence, such as the pH factor, which restrict the development and application of biosensors. In this work, the intrinsic mechanism of pH influence on CD-2-1 aptamer binding with Cd2+ in aqueous solution was investigated with molecular dynamics (MD) simulation. The calculated data demonstrated that as the pH value increased in the range of 2.40–7.90, the capability of aptamer binding to Cd2+ was enhanced, which was consistent with experimental results. The intrinsic reason lies in the protonation of three key bases: 7G, 12C, and 16C. With a decrease in pH value, several bases were protonated, causing a rearrangement of hydrogen bonds and structural change to the aptamer. Finally, the stem–loop structure of the aptamer was totally destroyed, and it became unlikely to bind Cd2+. The decrease in the absolute value of binding free energy also indicated weakened binding interactions. It has been emphasized that the stem–loop structure and the C-shape loop character are the specific spatial structures for Cd2+ binding. This work reveals the mechanism behind the influence of pH on aptamer binding to Cd2+ in aqueous solution, providing a theoretical reference for heavy metal detection in complicated environments, which is helpful for the development and application of aptamer-based biosensors. [ABSTRACT FROM AUTHOR]

Heterozygosity for missense mutations in Seipin, namely N88S and S90L, leads to a broad spectrum of motor neuropathy, while a number of loss-of-function mutations in Seipin are associated with the Berardinelli-Seip congenital generalized lipodystrophy type 2 ( CGL2, BSCL2), a condition that is characterized by severe lipoatrophy, insulin resistance, and intellectual impairment. The mechanisms by which Seipin mutations lead to motor neuropathy, lipodystrophy, and insulin resistance, and the role Seipin plays in central nervous system ( CNS) remain unknown. The goal of this study is to understand the functions of Seipin in the CNS using a loss-of-function approach, i.e. by knockdown ( KD) of Seipin gene expression. Excitatory post-synaptic currents ( EPSCs) were impaired in Seipin- KD neurons, while the inhibitory post-synaptic currents ( IPSCs) remained unaffected. Expression of a sh RNA-resistant human Seipin rescued the impairment of EPSC produced by Seipin KD. Furthermore, α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid ( AMPA)-induced whole-cell currents were significantly reduced in Seipin KD neurons, which could be rescued by expression of a sh RNA-resistant human Seipin. Fluorescent imaging and biochemical studies revealed reduced level of surface AMPA receptors, while no obvious ultrastructural changes in the pre-synapse were found. These data suggest that Seipin regulates excitatory synaptic function through a post-synaptic mechanism. [ABSTRACT FROM AUTHOR]

• The relationship between the buoyancy and gravity is analyzed when the thermal effects are considered. • Three station-keeping scenarios are proposed and compared for the stratospheric airship. • The significance of pressure control and altitude control is revealed by the calculation and analysis. • An effective way to specify the helium's mass is presented when the thermal effects are considered. • The airspeed control is shown as an efficient way to cut down the energy consumption during the long-endurance flight. The ability to achieve long-endurance station-keeping flights makes stratospheric airships desirable platforms for the provision of communication and surveillance services. To maintain long-endurance flights, it is necessary to consider the problem of energy consumption. In this paper, we discuss long-endurance flight scenarios of stratospheric airships in the presence of thermal effects. The balance between buoyancy and gravity is influenced by thermal effects during the diurnal cycle. We perform a theoretical analysis based on the helium's mass, pressure differential, and altitude as the main factors. To verify the effectiveness of the control over the pressure differential and the altitude, three long-endurance flight scenarios are proposed and compared. Then, the corresponding optimization problems are constructed to determine the energy-minimum flight. Finally, further efforts are made to reduce energy consumption. The realization and limitations of two strategies for improvement are analyzed. A comparison with other scenarios shows the effectiveness of energy conservation. The study in this paper thus provides a reference for station-keeping applications of stratospheric airships. [ABSTRACT FROM AUTHOR]

Solid phase peptide synthesis (SPPS) strategy based on diaminodiacids had become an effective method for the synthesis of disulfide‐containing polypeptides. At present, it remains necessary to develop a diaminodiacid with more abundant chain structures to study the structure‐activity relationship. In this work, we developed a new type of diaminodiacids containing a six‐atom thioether (C−C‐S−C‐C−C, C−C‐C−S‐C−C) bridge. The key segment protected homo‐homocystine can be efficiently obtained by converting a side chain carboxyl group into a thiol group, which contribute to the facile and efficient synthesis of new diaminodiacid. With this diaminodiacid in hand, we successfully obtained tachyplesin containing new disulfide bond mimic by solid phase peptide synthesis. The tachyplesin analog not only has similar activity as natural counterpart, but also exhibits increased stability under reducing conditions. [ABSTRACT FROM AUTHOR]

The effectiveness of a concomitant intra-aortic balloon pump (IABP) with veno-arterial extracorporeal membrane oxygenation (VA-ECMO) intervention in acute myocardial infarction with cardiogenic shock (AMICS) patients is contested in the literature. This study sought to compare short-term mortality weaning rate from VA-ECMOin AMICS cases.We conducted a literature review and compared the primary and secondary endpoints in the following treatment groups of AMICS patients: (1) VA-ECMO plus IABP vs. IABP alone and (2) VA-ECMO plus IABP vs. VA-ECMO alone. The primary endpoint was in-hospital all-cause mortality; while 30-days mortality, weaning from VA-ECMO, and vascular complications comprised secondary endpoints.VA-ECMO concomitant with IABP was administered to 3,580 (76.4%) patients, while IABP alone and VA-ECMO alone treatments accounted for 1.7% and 21.9% of the patients, respectively. We found that in-hospital mortality was significantly lower in patients treated with VA-ECMO plus IABP vs. VA-ECMO alone (odds ratio (OR) = 0.52; 95% Confidence Interval (CI) = 0.21–1.31; I-squared statistic (I2 = 30%) or IABP alone (OR = 0.20; 95% CI = 0.08–0.55; I2 = 0%). Additionally, 30-days mortality was significantly lower in patients treated with VA-ECMO plus IABP vs. VA-ECMO alone (OR = 0.31; 95% CI = 0.25–0.40; I2 = 0%) or IABP alone (OR = 0.24; 95% CI = 0.11–0.50; I2 = 0%). A significant difference was observed in weaning from VA-ECMO in patients treated with VA-ECMO plus IABP vs. VA-ECMO alone (OR = 1.91; 95% CI = 1.09–3.33; I2 = 0%).In-hospital and 30-days mortality were significantly lower in AMICS patients treated with VA-ECMO plus IABP vs. VA-ECMO alone or IABP alone. VA-ECMO with concomitant IABP could increase the proportion of patients weaned from VA-ECMO, significantly reducing in-hospital mortality, without increasing complications. [ABSTRACT FROM AUTHOR]

• A deep learning LSTM is developed to forecast water temperature in rivers. • The LSTM model outperforms air2stream, RF and BPNN models. • LSTM accurately predicts mean daily variations in thermal regime. • LSTM can be used to reconstruct daily water temperature in the absence of dam. • The Three Gorges dam has strong seasonal effects on water temperature. Accurate water temperature forecasting is essential for understanding thermal regimes of rivers in the context of climate change and anthropogenic disturbances, such as dam construction. Machine-learning models proffer an empirically based approach to predicting water temperatures with a high degree of accuracy. This study explores the potential of long short-term neural network (LSTM), a type of deep learning method, to forecast daily river water temperatures and quantify temporal variations in thermal regime induced by changes in climate and by dam construction. The performance of LSTM is compared with that of several other models using daily water-temperature data for nine river gauges around the world. In a detailed analysis, the models are evaluated for the Yichang gauge on the Yangtze River to reconstruct the natural thermal conditions and help to assess daily water temperature variations induced by operation of the Three Gorges Reservoir (TGR). The collective results show that LSTM outperforms other methods for predicting mean daily water temperature in rivers, capturing accurately mean daily variations in thermal regime. The construction of the TGR strongly influenced water temperature variations at Yichang, producing the strongest cooling effect from mid-April to mid-May and the greatest warming effect in late December and early January. These marked effects are most prominent at the highest water levels in the TGR. The enhanced predictive capabilities of the LSTM model provide a powerful tool for water temperature forecasting and ecological management of rivers in the Anthropocene. [ABSTRACT FROM AUTHOR]

Water temperature is a controlling indicator of river habitat since many physical, chemical and biological processes in rivers are temperature dependent. Highly precise and reliable predictions of water temperature are important for river ecological management. In this study, a hybrid model named BP_PSO3, based on the BPNN (back propagation neural network) optimized by the PSO (particle swarm optimization) algorithm, is proposed for water temperature prediction using air temperature (Ta), discharge (Q) and day of year (DOY) as input variables. The performance of the BP_PSO3 model was compared with that of the BP_PSO1 (with Ta as the input) and BP_PSO2 (with Ta and Q as the inputs) models to evaluate the importance of the inputs. In addition, a comparison among the BPNN, RBFNN (radial basis function neural network), WNN (wavelet neural network), GRNN (general regression neural network), ELMNN (Elman neural network), and BP_PSO-based models was carried out based on the MAE, RMSE, NSE and R2. The eight artificial intelligence models were examined to predict the water temperature at the Cuntan and Datong stations in the Yangtze River. The results indicated that the hybrid BPNN-PSO3 model had a stronger ability to forecast water temperature under both normal and extreme drought conditions. Optimization by the PSO algorithm and the inclusion of Q and DOY could help capture river thermal dynamics more accurately. The findings of this study could provide scientific references for river water temperature forecasting and river ecosystem protection. Unlabelled Image • A novel hybrid prediction model is proposed for water temperature forecasting. • The PSO algorithm is utilized to optimize the BPNN network. • The BP_PSO3 model outperformed than BPNN, RBFNN, WNN, GRNN and ELMNN models. [ABSTRACT FROM AUTHOR]

Magnesium hydride is one of the most ideal solid hydrogen storage materials (HSMs). However, its sluggish absorption/desorption kinetics and undesirable thermodynamics create a burden for industrial-scale applications. In this paper, the effects of micro-Ni and nano-Ni on the dehydrogenation properties of Mg–Al alloys were compared and studied. All the samples were prepared by hydriding combustion synthesis (HCS) and mechanical milling (MM). Temperature programmed desorption (TPD) and differential scanning calorimeter (DSC) analyses showed that the catalytic effect of nano-Ni was vastly superior to that of micro-Ni and the catalytic effect of Ni was more excellent than Al 3 Ni 2 on the dehydrogenation of Mg–Al alloy. Mg 90 Al 10 -5nanoNi-MM exhibited the best dehydrogenation property, in which, two dehydrogenation peaks at 260 °C and 343 °C in the DSC curve (10 °C/min) were observed and the main dehydrogenation occurred at the lower temperature. The apparent activation energy for dehydrogenation of MgH 2 was reduced from 144.8 kJ/mol to 88.8 and 65.5 kJ/mol for the two dehydrogenation peaks. Ex-situ X-ray differential (XRD) and high resolution transmission electron microscope (HRTEM) were conducted to understand the microstructure evolution during dehydrogenation. Nano-inducement of nano-Ni dramatically promotes the regulation of Al on MgH 2 thus improving the dehydrogenation performance. Image 1 • Effects of micro-Ni and nano-Ni on dehydrogenation of Mg–Al alloy were studied. • Mg 90 Al 10 -5nanoNi-MM mainly dehydrogenated at the lower temperature of 260 °C. • Catalytic effect of Ni is better than Al 3 Ni 2 on the dehydrogenation of Mg 90 Al 10. • Nano-Ni dramatically promotes the regulation of Al on the dehydrogenation of MgH 2. [ABSTRACT FROM AUTHOR]