The effects of exogenous inorganic [i.e., nitrate (NO3-)/ammonium (NH4+)] and organic [i.e., glutamate (Glu)/argine (Arg)] N alone and in combination on the accumulation of proline (Pro) in rice plant under trivalent chromium [Cr(III)] stress were studied through the mass balance matrix model (MBMM). ‘NH4+’ application showed the largest contribution to the Pro content in rice shoots under different concentrations of Cr(III), followed by ‘NO3-’, ‘Arg’, and ‘Glu’ application respectively. While, ‘Arg’ application displayed the largest contribution to the Pro content in roots under Cr(III) stress, followed by ‘NH4+’, ‘Glu’, and ‘NO3-’ application. Among the combination cases of N sources used, the application of ‘NH4++Arg’ showed the greatest contribution to the Pro content in both roots and shoots of Cr(III)-treated rice seedlings, while the application of ‘NO3-+Glu’ showed the least contribution to the Pro content in rice seedlings under Cr(III) stress. Results from this study indicated that the level of indigenous Pro in rice seedlings is quite sensitive to Cr(III) stress under different N sources, and mathematical modeling showed a reliable result to estimate the relationship between Pro content and N source application in rice plants in response to Cr(III) exposure .

Few-shot classification is challenging since the goal is to classify unlabeled samples with very few labeled samples provided. It has been shown that cross attention helps generate more discriminative features for few-shot learning. This paper extends the idea and proposes two cross attention modules, namely the cross scaled attention (CSA) and the cross aligned attention (CAA). Specifically, CSA scales different feature maps to make them better matched, and CAA adopts the principal component analysis to further align features from different images. Experiments showed that both CSA and CAA achieve consistent improvements over state-of-the-art methods on four widely used few-shot classification benchmark datasets, miniImageNet, tieredImageNet, CIFAR-FS, and CUB-200-2011, while CSA is slightly faster and CAA achieves higher accuracies.

The astro-structures with the shape of comet and semi-circle, are found in the electronegative inductively coupled plasmas (ICPs), e.g., Ar/O2 and Ar/SF6. They are formed by means of the self-coagulation theory. This theory is built and based on two-dimensional fluid model simulation dynamic data of the above ICP sources. Concretely, quasi-Helmholtz equation is constructed through the free diffusion transport component and a novel negative chemical source term. The absolute value of recombination rate is higher than the attachment rate and so the net source of simulated anion is negative. This is quite a new chemical phenomenon in the electronegative and gaseous discharging plasmas when compared to the previously reported normal positive chemical source that will generate ambi-polar diffusion potential. In electronegative plasma, the self-coagulation is ambi-polar to sustain the electrical neutrality. Besides, when the anions are accelerated by ambi-polar potential before self-coagulated, the self-coagulation is again advective which leads to the formation of blue sheath. At the ambi-polar self-coagulation of high electronegativity, the electrons dynamics are relatively decoupled from ions and meanwhile they have their own relatively weak, spontaneous, and monopolar self-coagulation in the periphery of astro-structure. At the ambi-polar self-coagulation, both the anion and cation are individually treated as mass point models that carry charge (point charge models, more precisely). When the charge amounts of two individual astr-structures, e.g., semi-circle SF3+ and Ar+, are equal, the coagulated profile of heavy species SF3+ collapses by the expelling effect of Coulomb force that exists between the two point-charges. This is an anti-collective behavior of astro-structure, instead of the collective interaction of plasma, since the collapse of coagulated heavy species creates spatially dispersed charge density that cannot be shielded. The simulation shows that the lighter the species, the easier it self-coagulates, determined by the inertial effect of density quantity. The discharge picture of electronegative plasma is combined by a dynamic continuum transport (e.g., forming the ellipse background) and the mechanical balance contained in the static self-coagulation process (proven by dimensional analysis of continuity equation). The popular astro-structure of electronegative ICP source awaits urgently for the validation of experiment.

Glass has emerged as a highly versatile substrate for various sensor and MEMS packaging applications, including electromechanical, thermal, optical, biomedical, and RF devices, due to its exceptional properties such as high geometrical tolerances, outstanding heat and chemical resistance, excellent high-frequency electrical properties, and the ability to be hermetically sealed. In these applications, Through-Glass-Via (TGV) plays a vital role in manufacturing and packaging by creating electrical interconnections through glass substrates. This paper provides a comprehensive summary of the research progress in TGV fabrication along with their integrations, including through-via formation and metallization. The paper also reviews the significant qualification and reliability achievements obtained by the scientific community for TGV. Additionally, the paper summarizes the application of TGV technology in various sensors.

In 2015, the new installed capacity of global renewable energy power generation exceeded the newly installed capacity of conventional energy power generation, marking a structural change in the construction of the global power system. With the continuous improvement of wind energy utilization technology, the global wind power industry has developed rapidly in recent years. The world's available wind energy is 20 billion kilowatts and has become one of the most economical green power. In China, wind power has become the third largest source of electricity, with the installed capacity increasing from 3.1% in 2010 to 9.2% in 2017. In 2017, China's new installed capacity was 19,660 MW, accounting for 37.45% of the world's new installed capacity. This paper evaluates and compares the efficiency of wind power industry in the four regions of eastern, central, western and northeastern China through EBM models based on radial and non-radial factors. This paper discusses the contribution of China's wind power industry to CO2 emission reduction from the relationship between installed capacity efficiency and CO2 emission reduction efficiency. The conclusions show that the overall efficiency score and ranking of wind power in 2013-2017 is the best in the eastern region, followed by the northeast region and the western and central regions.

Mulberry is an economically significant crop for the sericulture industry worldwide. Stresses such as drought exposure have a significant influence on plant survival. Metabolome directly reflects plant physiological status; thus, a way to assess this impact is to perform a global metabolomic analysis. This study investigated the effect of drought stress on mulberry Yu-711 metabolic balance using a liquid chromatography-mass spectrometry (LC-MS) based on an untargeted metabolomic approach. For this objective, Yu-711 leaves were subjected to two weeks of drought stress treatment and control without drought stress. Multivariate and univariate statistical analyses highlighted numerous differentially-accumulated metabolic elements as a function of time and treatment. Drought stress led to a more differentiated metabolites response than the control. We found that the levels of total lipids and galactolipids, and phospholipids (PC, PA, PE) were significantly altered, producing 48% of the total differentially expressed metabolites. Fatty acyls were the most abundant lipids expressed and decreased considerably by 73.6%. Prenol lipids class of lipids increased in drought leaves. Other classes of metabolites, including polyphenols( flavonoids and cinnamic acid), organic acid (amino acids), carbohydrates, benzenoids, and organoheterocyclic, all had a dynamic trend in response to the drought stress. However, their levels under drought stress generally decreased significantly compared to the control. These results provide an overview of the metabolic profile of the mulberry plant through differentially-accumulated compounds and provide a better understanding of global plant metabolic changes in defense mechanisms.

Rational delineation of urban–rural boundaries is a foundational prerequisite for holistic urban and rural development planning and rational resource allocation. However, the results of division of urban–rural boundaries extracted using a single data source are non-comprehensive. To address this problem, the present study proposes a method for using multiple sources such as population data, nighttime light data, land use, and points of interest (POI) data to extract urban–rural boundaries. Considering Guizhou Province for a case study, we here present a two-step method for identifying urban–rural boundaries. First, the random forest model was combined with the dasymetric mapping method to obtain the population spatialization data with a 30-m resolution in the studied province. Second, using the breaking point method, we extracted the urban–rural boundary for Guizhou Province in 2020 based on the spatialized population. This method fully integrated the benefits of various data and judiciously extracted the boundaries of the main urban areas and small- and medium-sized towns of each city in the study province at the same spatial scale. The stratified random sampling method revealed that the average overall accuracy was 88.05%. The method proposed has certain universality and application value and allows identifying the urban–rural boundaries more accurately and practically.

Continuous research into the availability of phosphorus (P) in forest soil is critical for sustainable management of forest ecosystems. In this study, we used sequential chemical extraction and 31P-nuclear magnetic resonance spectroscopy (31P-NMR) to evaluate the form and distribution of inorganic P (Pi) and organic P (Po) in Casuarina forest soils of a subtropical coastal sand dune at Houlong in Taiwan. The soil samples were collected from humic (+2-0 cm) and mineral layers (mineral-I: 0-10, mineral-II: 10-20 cm) at two topographic locations (upland and lowland) by elevation. Sequential chemical extraction revealed that the NaOH-Po fraction, as moderately recalcitrant P, was the dominant form in humic and mineral-I layers in both upland and lowland soils, whereas the cHCl-Pi fraction was the dominant form in the mineral-II layer. Resistant P content, including NaOH-Pi, HCl-Pi, cHCl-Pi, and cHCl-Po fractions, was higher in the upland than lowland in the corresponding layers; however, labile P content, NaHCO3-Po, showed the opposite pattern. Content of resistant Pi (NaOH-Pi, HCl-Pi, and cHCl-Pi) increased significantly with depth, but that of labile Pi (resin-Pi and NaHCO3-Pi) and recalcitrant Po (NaHCO3-Po, NaOH-Po, and cHCl-Po) decreased significantly with depth at both locations. 31P-NMR spectroscopy revealed inorganic orthophosphate and monoesters-P as the major forms in this area. The proportions of Pi and Po evaluated by sequential chemical extraction and 31P-NMR spectroscopy were basically consistent. The results indicated that the soils were in weathered conditions. Furthermore, the P distribution and forms significantly differed between the upland and lowland by variation in elevation and eolian aggradation effects in this coastal sand dune landscape.

Biomimetic design has recently received widespread attention. Inspired by the Terebridae structure, this paper provides a structural form for suppressing vortex-induced vibration (VIV) response. Four different structural forms are shown, including the traditional smooth cylinder (P0), the Terebridae-inspired cylinder with a helical angle of 30° (P30), the Terebridae-inspired cylinder with a helical angle of 60° (P60), and the Terebridae-inspired cylinder with a helical angle of 90° (P90). And computational fluid dynamics (CFD) method is adopted to solve the flow pass the Terebridae-inspired structures, and the vibration equation is solved using the Newmark-β method. The results show that the VIV responses are effectively controlled in the lock-in region for P30, P60, and P90, and P60 shows the best VIV suppression performance. The transverse amplitude and the downstream amplitude can be reduced by 82.67% and 91.43% respectively for P60 compared with that for P0, and the peak of the mean-drag coefficient is suppressed by 53.33%. The Q-criterion vortices of P30, P60, and P90 are destroyed, with irregular vortices shedding. It is also found that the boundary layer separation is located on the Terebridae-inspired ribs. The twisted ribs cause the separation point to constantly change along the spanwise direction, resulting in the development of the boundary layer separation being completely destroyed. The strength of the wake flow is significantly weakened for the Terebridae-inspired cylinder. In the lock-in region, the motion trajectory presents a typical 8-shaped for P0, while the motion trajectory of the Terebridae-inspired cylinder tends to be a flat 1-shaped.

The bilateral trade relationship between PRC and ASEAN is close. As early as 2012, China has been the largest trading partner of ASEAN, and ASEAN has also taken the place of the United States as PRC’s second largest trading partner in 2019.This paper uses the theory of ecological population evolution, selects the total import and export volume of PRC and the ten ASEAN countries from 2000 to 2019 as the data sample, studies the bilateral trade relations between PRC and the ten ASEAN countries, analyzes the competition and symbiotic relationship of bilateral trade between PRC and the ten ASEAN countries and the possibility of trade friction according to the results, and proposes corresponding improvement strategies. According to the results of the population evolution competition model, China has a competitive relationship with Indonesia, Malaysia, the Philippines, Singapore and Thailand, which is most likely to cause trade friction. China has a biased relationship with Brunei, Cambodia, Laos, Myanmar and Vietnam, which is more likely to cause trade friction. On this basis, in order to further strengthen the trade relations between PRC and the ten ASEAN countries, this paper puts forward policy suggestions on improving infrastructure, strengthening independent innovation, seeking cooperation fields and actively investing abroad.

In this study we used a non-autonomous Chua’s Circuit, and the fractional Lorenz chaos system together with a detection method from Extension theory to analyze the voltage signals. The measured bearing signals by acceleration sensor were introduced into the master and slave systems through a Chua’s Circuit. In a chaotic system minor differences can cause significant changes that generate dynamic errors, and extension matter-element models can be used to judge the bearing conditions. Extension theory can be used to establish classical and sectional domains using the dynamic errors of the fault conditions. The results obtained were compared with those from Discrete Fourier Transform analysis, Wavelet analysis and an integer order chaos system. The diagnostic ratio showed the fractional order master and slave chaos system calculations. The results show that the method presented in this paper is very suitable for monitoring the operational state of ball bearing system to be superior to the other methods. The diagnosis ratio was better and there were other significant advantages such as low cost and few.

Simply Summary: Translation of new cancer treatments between pets and human were noticed in comparative oncological investigation. The current study aims at evaluating a polyacetylenic glucoside purified from an edible herb, Bidens pilosa, to present its anti-angiogenic effects. We innovatively find this polyacetylenic glucoside, cytopiloyne, shows anti-angiogenic effect on different in vitro assays and various in vivo animal models under hypoxia. Based on results of this study, cytopiloyne will be a prospective herb angiogenesis inhibitor candidate to control animal or human cancer formation as adjuvant therapy. Abstract: Anti-angiogenesis is a pivotal combination treatment approach in cancer therapy but rare using on companion animals. This study aimed at evaluating the anti-angiogenic effect of a B. pilosa sourced polyacetylenic glucoside, cytopiloyne, on various in vitro assays and in vivo models. We provide evidences showing that CP has anti-angiogenic activities. Firstly, CP inhibited sponge/ Matrigel plug angiogenesis from tumor cells and decreased the survival of tumor cells on hypoxic conditions. Besides, CP declined PKCα protein expression which a protein leads to the growth and spread of tumors under hypoxia. Secondly, inhibitory effects of CP on endothelial angiogenesis were confirmed by chick chorioallantoic membrane assay, tube formation of SVEC4-10 cells and Matrigel plug assay. A dose-dependent CP treatment inhibited 4T1 cells proliferation under hypoxia and migration. It also suppresses VEGF transcription under hypoxia. Finally, we found that CP decreased PDIA4, a novel regulator of cancer growth, expression in endothelial cells. This effect was confirmed by PDIA4 knockout mice with reduced angiogenesis in Matrigel plug assay. Taken together, these results suggest that CP might act as a promising anti-angiogenic herbal agent candidate to be used in animal hypervascularized cancer of veterinary medicine or in combination to control human cancer as adjuvant therapy.

The mammalian or mechanistic target of rapamycin (mTOR) integrates multiple intracellular and extra-cellular upstream signals involved in the regulation of anabolic and catabolic processes in cells, and plays a key regulatory role in cell growth and metabolism. Activation of the mTOR signaling pathway has been reported to be associated with a wide range of human diseases. A growing number of in vivo and in vitro studies have demonstrated that the gut microbes and its complex metabolites can regulate host metabolic and immune responses through the mTOR pathway, and result in disorders of host phys-iological functions. In this review, we summarize the regulatory mechanisms of gut microbes and mTOR in different diseases, and discuss the crosstalk between gut microbes and their metabolites and mTOR in the disorders in gastrointestinal tract, liver, heart and other organs. We also discuss the promising appli-cation of multiple potential drugs that can adjust the gut microbiota and mTOR signal pathways. Despite the limited findings between gut microbes and mTOR, elucidating their relationship may provide new clues for the prevention and treatment of various diseases.

In this paper, the methodology using Insect Intelligent Building (I^2B) technology for establishing energy consumption monitoring system of public buildings is prevailed. The computing process node and distributed algorithm are utilized to implement the energy consumption collection and data transmission and data pre-processing. Taking a commercial building as a case study, CPNs are applied to set up the building energy consumption monitoring system, with the Spanning Tree Algorithm for generating network topology，and BPNN method for solving abnormal data and recovering missing data. The research results demonstrate the proposed method can effectively improve the performance of plug-and-play and self-identified and self-configuration of energy consumption monitoring system.

Digital Elevation Models (DEMs) are widely used in geographic and environmental studies. In the current work, the fusion of multi-source DEMs is investigated to improve the overall accuracy of public domain DEMs. Multi-scale decomposition is an important analytical method in data fusion. Three multi-scale decomposition methods – the wavelet transform (WT), bidimensional empirical mode decomposition (BEMD) and nonlinear adaptive multi-scale decomposition (N-AMD) - are applied to the 1-arc-second Shuttle Radar Topography Mission Global digital elevation model (SRTM-1 DEM) and the Advanced Land Observing Satellite World 3D – 30 m digital surface model (AW3D30 DSM) in China. Of these, the WT and BEMD are popular image fusion methods. A new approach for DEM fusion is developed using N-AMD (which is originally invented to remove the cycle from sunspots). Subsequently, a window-based rule is proposed for the fusion of corresponding frequency components obtained by these methods. Quantitative results show that N-AMD is more suitable for multi-scale fusion of multi-source DEMs, taking the ice cloud and land elevation satellite (ICESat) global land surface altimetry data as a reference. The vertical accuracy of the fused DEM shows significant improvements of 29.6% and 19.3% in a mountainous region and 27.4% and 15.5% in a low-relief region, compared to the SRTM-1 and AW3D30 respectively. Furthermore, a slope position-based linear regression method is developed to calibrate the fused DEM for different slope position classes, by investigating the distribution of the fused DEM error with topography. The results indicate that the accuracy of the DEM calibrated by this method is improved by 16% and 13.6%, compared to the fused DEM in the mountainous region and low-relief region respectively, proving that it is a practical and simple means of further increasing the accuracy of the fused DEM.

T-2 toxin produced by fungi of Fusarium genus is highly toxic to human and animals and has been shown to induce apoptosis in various organs/tissues. Apoptosis and autophagy are interconnected processes and these interactions are important for cellular homeostasis as well as pathogenesis. In this study, we report for the first time that T-2 toxin induced autophagy in human liver cells (L02). We showed that T-2 toxin induced the formation of acidic vesicular organelles, concordant with the time and dose-dependent alterations in LC3-phosphatidylethanolamine conjugate (LC3-II) LC3-I/II and p62/SQSTM1 suggesting an enhanced autophagic flux. The T-2 toxin-induced formation of autophagosome and lysosomal fusion was observed by expressing mRFP-GFP-LC3 in L02 cells by lentiviral transduction, and autophagosome was observed by transmission electron microcopy. We found that while T-2 toxin activated both apoptosis and autophagy, activation of autophagy appears to be a leading event reflecting the protective mechanism of cells against the insults by T-2 toxin. Activating autophagy by rapamycin (RAPA) inhibited the apoptosis while suppressing autophagy by chloroquine greatly enhanced the T-2 toxin-induced apoptosis suggesting the crosstalk of autophagy and apoptosis. In summary, our study showed that activation of autophagy protects liver cells from T-2 toxin-induced apoptosis suggesting autophagy may be targeted for prevention of the T-2 toxin-induced toxicity in human and animals.

Cordycepin has good antitumor activity, but its clinical application is limited due to the easy deamination of N6 in structure. In this study, a large lipopolysis group was introduced at the cordycepin N6 to improve the problem, Cordycepin derivatives(3a-4c) were synthesized, and biological evaluation of compounds were studied. In the study, the vitro antitumor activity of the compounds against MCF7 cells, HepG2 cells and SGC-7901 cells was evaluated by MTT assay. In the results, compound 4a showed the most obvious inhibitory effect on MCF7 cells with IC50 value of 27.566±0.52 μM, which was much lower than cordycepin. Compound 4a showed high selectivity between MCF7 and normal MCF-10A cells. Further biological evaluation showed that compound 4a promoted apoptosis and blocked the cell cycle in G0/G1 phase. Then, Western Blot was used to detect related apoptotic proteins. It was found that Compound 4a could down-regulate the expression of Bcl-2 protein and up-regulate the expression of p53, Bax, Caspase-3, and Caspase-9 proteins. The mitochondrial membrane potential decreased continuously and the positive expression rate decreased. It was speculated that compound 4a induced the apoptosis of MCF7 cells through the mitochondrial pathway.

High mountain areas are an appropriate indicator of anthropogenic lead (Pb), which can reach the remote mountain ranges through long distance atmospheric transport. We compared the content of Pb in ecologically equivalent rodent species from Tian-Shan with European mountain ranges Tatra, Vitosha and Rila mountains. We used bone tissues from terminal tail vertebrae of small rodents for detection of Pb levels by using electrothermal atomic absorption spectroscopy (AAS). The tail bones of Tian-Shan rodents had significantly lower Pb levels than snow voles from Tatra mountains, but there was no significant difference in comparison with Vitosha and Rila mountains. We can conclude that Tian-Shan shows lower pollution by Pb than Tatra mountains, what may be a reason of longer lasting industrialization of north-western Europe and strongly prevailing west winds in Tatra mountains.

In this paper, we present a complete, flexible and safe convex-optimization-based method to solve speed planning problems over a fixed path for autonomous driving in both static and dynamic environments. Our contributions are five fold. First, we summarize the most common constraints raised in various autonomous driving scenarios as the requirements for speed planner developments and metrics to measure the capacity of existing speed planners roughly for autonomous driving. Second, we introduce a more general, flexible and complete speed planning mathematical model including all the summarized constraints compared to the state-of-the-art speed planners, which addresses limitations of existing methods and is able to provide smooth, safety-guaranteed, dynamic-feasible, and time-efficient speed profiles. Third, we emphasize comfort while guaranteeing fundamental motion safety without sacrificing the mobility of cars by treating the comfort box constraint as a semi-hard constraint in optimization via slack variables and penalty functions, which distinguishes our method from existing ones. Fourth, we demonstrate that our problem preserves convexity with the added constraints, thus global optimality of solutions is guaranteed. Fifth, we showcase how our formulation can be used in various autonomous driving scenarios by providing several challenging case studies in both static and dynamic environments. A range of numerical experiments and challenging realistic speed planning case studies have depicted that the proposed method outperforms existing speed planners for autonomous driving in terms of constraint type covered, optimality, safety, mobility and flexibility.

The autonomous displacement and displacement measurement functions of the maglev ruler are performed by the mover core. The stability of the four magnetic field in air gaps and the levitation position of the maglev ruler is one of the key factors for the stability of the thrust force on the power core, and it is also one of the key factors for ensuring the precision of the maglev ruler. There is cross-coupling between the two ends of the mover core of the maglev ruler, resulting in a strongly coupled, nonlinear, multi-input and multi-output system for the levitating system of the maglev ruler. This paper establishes a mathematical model for the levitating system of the maglev ruler, and designs a levitating control system for the maglev ruler based on ADRC control algorithm to achieve decoupling and disturbance suppression. Through simulation analysis and experimental testing of the levitating system with starting and disturbance, it is proved that the levitating control system of the maglev ruler has good dynamic characteristics, static characteristics, and robustness.

Engineering of quantum computers requires reliable characterization of qubits, quantum operations, and even the entire hardware. Quantum tomography is an indispensable framework in quantum characterization, verification, and validation (QCVV), which has been widely accepted by researchers. According to the tomographic target, quantum tomography can be categorized into quantum state tomography (QST), quantum process tomography (QPT), gate set tomography (GST), process tensor tomography (PTT), and instrument set tomography (IST). Standard quantum tomography toolkits generally consist of basic linear inverse methods and statistical maximum likelihood estimation (MLE) based methods. Furthermore, the performance of standard methods, including effectiveness and efficiency, has been further developed by exploiting Bayesian estimation, neural networks, matrix completion techniques, etc. In this review, we introduce the fundamental quantum tomography techniques, including QST, QPT, GST, PTT, and IST. We first introduce the details of basic linear inverse methods. Then, the framework of MLE methods with constraints is summarized. Finally, we briefly introduce recent further research in developing the performance of tomography. This review provides a primary getting-start in developing quantum tomography, which promotes quantum computer development.

As one of the important components of underwater propulsion systems, water lubricated bearings are often failure due to mechanical wearing and vibrating, especially under high loads and prolonged friction. In this paper, a dual-network co-crosslinking strategy based on HNBR is proposed, in which the epoxy network connects with the rubber network through Epoxidized Eommia ulmoides gum. The damping, tribological and mechanical properties of the prepared composite are systematically investigated. The results show that this material has excellent friction and vibration damping properties, with a water-lubricated coefficient of friction as low as 0.022 and a wear resistance as high as 3.87 × 10-6mm3/Nm. Preparing HNBR-based composite by dual network co-crosslinked is proved being a feasible solution to improve the reliability and service life of water-lubricated bearings.

Taste determination in small molecules is critical in food chemistry, but traditional experimental methods can be time-consuming. Consequently, computational techniques have emerged as val-uable tools for this task. In this study, we explore taste prediction using various molecular feature representations and assess the performance of different machine learning algorithms on a dataset comprising 2,601 molecules. The results reveal that GNN-based models outperform other ap-proaches in taste prediction. Moreover, consensus models that combine diverse molecular repre-sentations demonstrate improved performance. Among these, molecular fingerprints + GNN con-sensus model emerges as the top performer, highlighting the complementary strengths of GNNs and molecular fingerprints. These findings have significant implications for food chemistry research and related fields. By leveraging these computational approaches, taste prediction can be expedited, leading to advancements in understanding the relationship between molecular structure and taste perception in various food components and related compounds.

Influenced by the quasi-stationary Mei-yu front and the development of mesoscale low vortices on the Mei-yu front, a torrential rain event occurred in Suzhou on July 6, 2020. The 24-hour rainfall recorded by the automatic station exceeded 200 millimeters, with the highest hourly intensity surpassing 70 millimeters, accompanied by thunderstorms and strong winds. This heavy precipitation process was characterized by suddenness, extremity, long duration, high precipitation efficiency, and backward propagation. Using various data sources such as the European ERA5 reanalysis data, ground-based automatic stations, sounding, Doppler weather radar, and wind profile radar, this paper analyzed in detail the circulation characteristics and radar echo structures of this torrential rain event, and further studied the triggering, feature evolution, and maintenance mechanisms of the heavy precipitation.The results show: (1) The continuously strengthening low-level jet stream propagates downward forming an ultra-low-level jet stream. Heavy precipitation is located on the left front side of the jet exit area, where strong convergence and lifting in the boundary layer overlap with the ascending branch of the secondary circulation above the shear line, resulting in heavy precipitation. (2) A supercell storm with intense precipitation produced this heavy rainfall event, characterized by a low centroid of strong echo; echo-free vault, bounded weak echo region, and other supercell structural features. During this event, the high reflectivity factor areas corresponded to high KDP value areas, indicating a large amount of liquid water content. Vertically, the KDP column can track the rainwater mixing ratio well, and its location corresponds to the vicinity of the short-term heavy precipitation occurrence. The high KDP value area mainly consists of numerous precipitation particles, and the vertical vortex wind field structure causes rapid growth of precipitation particles through continuous rolling. Furthermore, it can be found through correlation coefficients (CC) that there are always high-value areas for CC since they correspond to areas of intense precipitation. (3) Continuous triggering of mesoscale convective cloud clusters on the east-west ground convergence line leads to new development and forms a "train effect." Strong frontogenesis in both horizontal and vertical directions triggers and sustains this heavy precipitation event. The significant increase in liquid water and water vapor density has indicative significance for the occurrence of heavy precipitation.

In this study, based on frost formation data provided by Harbin Meteorological Bureau, combined with geographical factors, temperature and population density, linear fitting, Mann-Kendall mutation test, pettitt method and sliding T test were used to analyze the spatio-temporal variation characteristics of frost date in Harbin Municipality and the effects of geographical factors, temperature and population density on frost regularity. The results showed that (1) The earliest year of FSD appeared was 1966 and 1967, on the 255th, i.e., August 18th, and the latest was 283 days, i.e., October 10th, 2006. The earliest year in which the FED appeared was April 24th of 2015, the 114th day of that year, and the latest was April 21st of 1974, the 141st day of that year. The year with the most frost was 2012, with 161 days, and the year with the shortest was 1966, with 123 days. (2) Throughout the study period, FSD increased by 7.8 days at a rate of -1.27d/10a, FED increased by 10.9 days at a rate of 1.77d/10a, and FFS increased by 18.9 days at a rate of 3.05d/10a. The tendency rate of FSD and FFS at each site in Harbin showed an increasing trend. For FED, the tendency rate of some sites showed an increasing trend. In general, FSD showed a delayed trend, FED showed an advanced trend, and FFS showed a prolonged trend. Using the method of unary linear regression, FSD of each site showed an increasing trend, FFS showed an increasing trend, and FED showed a decreasing trend in general. (3) Throughout the study period, FSD was mutated in 2000, and the arrival time of it in the study area averaged the 265th, i.e., September 22nd, and after that, the arrival time of it changed to the 272nd, i.e., September 29th of that year. FED was mutated in 2006, and the arrival time of it in the study area averaged 128th, i.e., April 8th. After the mutation, the arrival time of FED changed to 121st, i.e., April 1st of that year. FFS was mutated in 2004. Before the mutation, with an average arrival time of 137days in the study area .But after that, the time changed to 150 days.(4) FSD and FFS in Harbin Municipality were negatively correlated with latitude and positively correlated with temperature, while FED was positively correlated with latitude and negatively correlated with temperature. The FSD, FED and FFS in the central part of Harbin Municipality were the earliest, the latest and the longest, respectively, so the Pearson correlation coefficient method and the influence of longitude could not be reflected in the multiple regression. Several factors were judged by grey correlation analysis method. The longitude is significantly related to FSD, FED and FFS.

Controlled drainage (CD) is an important agricultural measure for maintaining soil moisture and nutrients, controlling groundwater level, and increasing crop yield. In arid regions, CD can be used to improve the water supply in agriculture and reduce environmental pollution. In this study, we investigated the effect of CD, including a drainage depth of 40 cm (CWT1) and 70 cm (CWT2) during the plant growth period, free drainage (FD), and open ditch drainage (OD) on the migration of water, nutrients, and salts in the soil; the dynamics of groundwater level; the loss of soil nitrogen; and the growth of oilseed sunflower plants. Compared with FD, CD increased the water and nutrient content in the soil, reduced nitrogen loss, and enhanced the ability of the soil to continuously supply nitrogen to the oilseed sunflower plants, which benefited plant growth at later growth stages and reduced environmental pollution. During the period between irrigation at the budding stage and harvest stage, the average soil water content in the 0–20 cm soil layer in CWT1 increased by 3.67%, 4.78%, and 0.55%, respectively, compared with that in CWT2, FD, and OD. The soil mineral content in CWT1 was 25.17%, 35.05%, and 17.78% higher than that in CWT2, FD, and OD, respectively, indicating that higher soil salinity occurred at the later stage of plant growth in CWT1, which actually had little effect on the plants due to their enhanced salt tolerance and increased need for water and nutrients at that stage. In addition, CD delayed the decline in groundwater level, which allowed the plants to use groundwater at later growth stages, and as a result the yield and water use efficiency were improved. CWT1 significantly increased oilseed sunflower yield by 4.52–11.14% and increased water use efficiency by 1.16–10.8%. Moreover, CWT1 also increased the survival rate of the oilseed sunflower plants by 2.62–2.92%, and the plants demonstrated good growth. Therefore, under CD conditions, plants used soil water and nitrogen more efficiently and, as a result, their productivity was increased, and the water quality was improved.

Brassica napus is an important vegetable and oil crop worldwide. The research is meaningful for yield and plant architecture in B. napus. In this study, one natural mutant (MT) line with determinate and capitulum-like inflorescence was chosen for further study. The paraffin sectioning detected that the inflorescence apex began to split and developed into one terminal flower, starting from five-leaf stage. Genetic analysis indicated that the segregation patterns of inflorescences in the F2 populations supported a digenic inheritance model, which was further approved by BSA-Seq technique. The BSA-Seq method detected two QTL region on C02 (14.27-18.41 Mb) and C06 (32.98-33.68 Mb) for the genetic control of determinate inflorescences in MT plants. In addition, the expression profile in MT compared with WT was analysized, and a total of 133 candidate genes for regulating the flower development (75 genes, 56.4%), shoot meristem development (29 genes, 21.8%) and inflorescence meristem development (13 genes, 9.8%) were identified. Then one joint analysis combing BSA-Seq and RNA-Seq identified two candidate gene of BncTFL1 and BncAP1 for regulating the MT phenotype. Besides, the potential utilization of the MT plants was also discussed.

Glioblastoma (GBM) is the most common malignant brain tumor in adults. Despite advancements in treatment, the prognosis for patients with GBM remains poor due to its aggressive nature and resistance to therapy. CRISPR-based genetic screening has emerged as a powerful tool for identifying genes crucial for tumor progression and treatment resistance, offering promising targets for tumor therapy. In this review, we provide an overview of the recent advancements in CRISPR-based genetic screening approaches and their applications in GBM. We highlight how these approaches have been used to uncover genetic determinants of GBM progression and susceptibility to various therapies. Furthermore, we discuss ongoing challenges and future directions of CRISPR-based screening methods in advancing GBM research.

Abstract: Transcription factors are crucial pre-transcriptional regulatory mechanisms that can modulate the expression of downstream genes by binding to their promoter regions. DOF (DNA binding with One Finger) proteins are a unique class of transcription factors with extensive roles in plant growth and development. Our previous research indicated a decrease in iron content in chlorotic bamboo leaves. However, to our knowledge, genes related to iron metabolism pathways in bamboo species have not yet been studied. Therefore, in the current study, we identified iron metabolism-related (IMR) genes in bamboo and determined the transcription factors that significantly influence them. Among these, DOFs were found to have widespread effects and potentially significant impacts on their expression. We identified specific DOF members in Dendrocalamus latiflorus with binding abilities through homology with Arabidopsis DOF proteins, and established connections between some of these members and IMR genes using RNA-seq data. Additionally, molecular docking confirmed the binding interactions between these DlDOFs and the DOF binding sites in the promoter regions of IMR genes. The co-expression relationship between the two gene sets was further validated using q-PCR experiments. This study paves the way for research into iron metabolism pathways in bamboo and lays the foundation for understanding the role of DOF transcription factors in D. latiflorus.

A complex square matrix $A$ is said to be Hermitian if $A= A^{\ast}$, the conjugate transpose of $A$. The topic of the present note is concerned with the characterization of Hermitian matrix. In this note, the we show that each of the two triple matrix product equalities $AA^{\ast}A = A^{\ast}AA^{\ast}$ and $A^3 = AA^{\ast}A$ implies that $A$ is Hermitian by means of decompositions and determinants of matrices, which are named the two-sided removal and cancellation laws associated with Hermitian matrix, respectively. We also present several general removal and cancellation laws as the extensions of the preceding two facts about Hermitian matrix.

The total ionizing dose (TID) effect significantly impacts the electrical parameters of fully depleted silicon on insulator (FDSOI) devices and even invalidates the on-off function of devices. At present, most of the irradiation research on the circuit level is focused on the single event effect, and the research on the total ionizing dose effect is very little. Therefore, this study mainly analyzes the influence of TID effects on a CMOS inverter circuit based on 22 nm FDSOI transistors. First, we constructed and calibrated an N-type FDSOI metal-oxide semiconductor (NMOS) structure and P-type FDSOI metal-oxide semiconductor (PMOS) structure. The transfer characteristics and trapped charge distribution of these devices were studied under different irradiation doses. Next, we studied the TID effect on an inverter circuit composed of these two MOS transistors. The simulation results show that when the radiation dose is 400 krad (Si), the logic threshold drift of the inverter is approximately 0.052 V. These results help further investigate the impact on integrated circuits in the irradiation environment.

The process of shock wave focusing can make the strength of shock waves be continuously accumulated and turned into detonation wave in Pulse Detonation Engine (PDE). However, its effective application needs the inlet jets be in high temperature and velocity, which is difficult to be satisfied under certain conditions. Therefore, in this paper, metal magnesium assisted detonation initiation is proposed and the effect of magnesium particle addition on the shock wave focusing process in a kerosene-fueled PDE with cavity configuration is investigated through numerical simulation. The result showed that when the temperature of the premixed fuel/air jets injected in opposite direction was set as 650 K, the collision of leading shock waves on the central axis was the main source of energy deposition and the shock wave focusing could make the detonation be initiated in the cavity. When the temperature of jets is reduced to 550 K, fuel ignition and detonation could not be achieved through shock wave focusing. Then adding metal magnesium particles into the combustor made the energy deposition be enhanced and the detonation be induced. The diffusion of metal particles can significantly change the structure, motion, merging and dissipation of vortices in the flow field. Generally, the shock wave focusing process is basically not affected with metal particles injection. Therefore, this method can be successfully employed for detonation initiation in the cavity when the fuel/air premixed jet temperature is not high for PDE.

Steam Generator Level Control System (SGLCS) is one of the key instrumentations and control subsystems to ensure the safe operation of nuclear power plants. It is highly recommended to perform reliability analysis for SGLCS for making better maintenance strategy. SGLCS is a digital control system with complex redundant configuration and failure\self-diagnosis\repair action, traditional fault tree is not applicable due to its static property, Markov model is not a good choice too because of heavy burden of creating state transition graph for even medium-size system. Boolean Logic Driven Markov Process (BDMP) can describe complex failure-repair state transition via ‘trigger link’ and three kinds of leaf nodes, as well as keep compact and easy-read struct like fault tree. So BDMP is adopted to analysis reliability of SGLCS. Graphical BDMP modeling environment KB3 and Monte Carlo simulator YAMS is used for BDMP modeling and quantitative analysis respectively, and unavailability of SGLCS is obtained. The contribution of three parts of SGLCS to the unavailability of the system is also evaluated, and it is found that the water supply flow control part contributes the most to the failure of SGLCS.

Factorization reduces computational complexity and is therefore an important tool in statistical machine learning of high dimensional systems. Conventional molecular modeling, including molecular dynamics and Monte Carlo simulations of molecular systems, is a large research field based on approximate factorization of molecular interactions. Recently, the local distribution theory was proposed to factorize global joint distribution of a given molecular system into trainable local distributions. Belief propagation algorithms are a family of exact factorization algorithms for trees and are extended to approximate loopy belief propagation algorithms for graphs with loops. Despite the fact that factorization of probability distribution is their common foundation, computational research in molecular systems and machine learning studies utilizing belief propagation algorithms have been carried out independently with respective track of algorithm development. The connection and differences among these factorization algorithms are briefly presented in this perspective, with the hope to intrigue further development in factorization algorithms for physical modeling of complex molecular systems.

(-)-Zeylenone is a promising cytotoxic agent，which is a natural product isolated from Uvaria grandiflora Roxb. Though substantial antitumor mechanism has been researched , little has focused on its enantiomer (+)-Zeylenone.This article will try to find a gram scale synthesis method of (+)-Zeylenone and explain the structure-activity relationship of this kind of compound. Total synthesis of (+)-zeylenone was completed in 13 steps with quinic acid as starting material in 8.8% overall yield. The highlight of the route was the control of the three carbon’s chirality by clever use of single step dihydroxylation under the direction of the key C-3 chirality. In addition, zeylenone derivatives were designed and synthesized and their antitumor activity were evaluated against three human cancer cell lines using the CCK8 assay. Structure-activity relationship suggested compounds with both two absolute configurations exhibited good activity. Besides, hydroxyls at C-1/2 position were crucial for the activity and esterification of C-1 hydroxyl with large groups made the activity disappeared. Hydroxyl at C-3 position was also important as proper ester substituent could increase the potency.

Water pollution, intensified by the release of hard-to-degrade pollutants, poses severe threats to ecosystems, human health, and economic development. The existing advanced oxidation processes often involve high operational costs and may result in secondary pollution, highlighting the necessity for innovative and more sustainable solutions. To address these challenges, our study introduces a cost-effective and eco-friendly corona discharge barrier plasma discharger for wastewater treatment. Through the central composite design/response surface methodology, a high decolorization rate of 98% of methylene blue (MB) within 10 minutes was achieved by optimizing parameters such as pH and voltage. Furthermore, the mechanisms of the generation of reactive oxygen species via this device was discussed in detail and the degradation pathways of MB were described. Moreover, this device is also very energy-efficient, with a low energy density and electrical energy per order of 0.15 watt/mL and 5.79 kWh/m³/order, respectively. In conclusion, the plasma discharger developed in this study provides a cost-effective and environmentally sustainable solution for dye wastewater treatment. This research contributes significantly to the advancement of sustainable dye wastewater management practices, offering an innovative method that meets both environmental and economic objectives.

This note addresses a fundamental problem in matrix theory on establishing and characterizing range equalities for matrix expressions that involve generalized inverses. We first establish a group of necessary and sufficient conditions for the matrix range equality ${\rm range}(D_1 - C_1A_1^{\dag}B_1) = {\rm range}(D_2 - C_2A_2^{\dag}B_2)$ to hold, where $(\cdot)^{\dag}$ denotes the Moore--Penrose inverse of matrix. We then give several groups of range equalities with extrusion properties for multiple matrix products associated with two matrices and their conjugate transposes and Moore--Penrose inverses.

This article shows how to establish expansion formulas for calculating the mixed operations $(A^{\dag})^{\#}$, $(A^{\#})^{\dag}$, $((A^{\dag})^{\#})^{\dag}$, $((A^{\#})^{\dag})^{\#}$, $\ldots$ of generalized inverses, where $(\cdot)^{\dag}$ denotes the Moore--Penrose inverse of a matrix and $(\cdot)^{\#}$ denotes the group inverse of a square matrix. As applications of the formulas obtained, the author constructs and classifies some groups of matrix equalities involving the above mixed operations, and derives necessary and sufficient conditions for them to hold.

Aiming at the problems of inaccurate segmentation of long object and information loss of small object in real-time semantic segmentation algorithm, this paper proposes a lightweight multi-branch real-time semantic segmentation network based on BiseNetV2. The new auxiliary branch makes full use of spatial details and context information to cover the long object in the field of view. Meanwhile, in order to ensure the inference speed of the model, the asymmetric convolution is used in each stage of the auxiliary branch to design a structure with low computational complexity. In the multi-branch fusion stage, the alignment and fusion module is designed to provide guidance information for deep and shallow feature mapping, so as to make up for the problem of feature misalignment in the fusion of information at different scales, and thus reduce the loss of small target information. In order to further improve the model’s awareness of key information, a global context module is designed to capture the most important features in the input data. The proposed network uses NVIDIA GeForce RTX 3080 Laptop GPU experiment, on the road street view data set Cityscapes and CamVid average occurring simultaneously ratio reached 77.1% and 78.4% respectively, with running speed of 127 frames/s respectively and 112 frames/s. The experimental results show that the proposed algorithm can achieve real-time segmentation and improve the accuracy significantly, showing good semantic segmentation performance

One new cassane diterpene possessing an unusual N bridge between C-19 and C-20 named caesalsappanin R (1), as well as another new diterpene caesalsappanin S (2), were isolated from the seeds of Caesalpinia sappan with methanol extract. Their structures were determined by spectroscopic analysis and examined alongside existing data from prior studies. Their biological activities were profiled by their antiplasmodial activity.

In this study, we evaluated the effects of Cyclosporine A (CsA) on Lipopolysaccharide (LPS)-induced cytokine production in the genital tract of female rabbits. Twelve sexually mature and healthy female rabbits were randomly divided into four groups (n = 3 each). The rabbits in the LPS group were given an intrauterine infusion of Escherichia coli LPS (4 mg/kg body weight (BW)). Rabbits in the CsA group were given CsA (20 mg/kg BW). Rabbits in the LPS + CsA group were given LPS (4 mg/kg BW) and CsA (20 mg/kg BW). The control group received only LPS and CsA carrier. The gene expression and protein levels of pro- and anti-inflammatory cytokines were observed using qRT-PCR and immuno-histochemical (IHC) assay, respectively. Our study showed that IL-1β, IL-6, IL-8, TNF-α, IFN-γ, IL-4, IL-10, IL-13, and TGF-β were expressed in female genital organs. The LPS challenge increased the mRNA expression of IL-6 and TNF-α in the uterine body and IL-1β in the uterotubal junction compared to the control group. CsA increased the basal mRNA expression of anti-inflammatory cytokines (i.e., IL-4 in the uterine body, uterotubal junction, and oviductal ampulla; IL-10 in the cervix, oviductal isthmus, and ampulla; and TGF-β in the uterotubal junction and oviductal ampulla) and pro-inflammatory cytokines (i.e., IL-6 and IL-8 in the cervix; IL-1β in the oviductal isthmus; TNF-α in the oviductal ampulla; and IFN-γ in the uterine body compared to the control group). In addition, CsA inhibited the mRNA expression of pro-inflammatory cytokines, such as IL-6 in the uterine body, uterotubal junction, and oviductal isthmus; TNF-α in the uterine body; and IFN-γ in the uterotubal junction and oviductal isthmus induced by the LPS challenge. The IHC assay showed the LPS-induced increase in protein production of IL-6 in the uterine body and oviductal isthmus. CsA increased the protein production of IL-10 in the cervix, uterine body, oviductal ampulla, and isthmus. Moreover, CsA decreased the protein production of IL-6 in the uterine body and oviductal isthmus induced by LPS.

Background: Many randomized controlled trials (RCTs) and systematic reviews (SRs) on acupuncture treatment for post-acute stroke dysphagia have been published. Due to conflicting results an overview of SRs to summarize and assess the quality of this evidence to determine whether acupuncture is effective for this disease was conducted. Methods: Seven databases were searched for SRs and/or Meta-analysis of RCTs and quasi-RCTs on acupuncture for post-acute stroke dysphagia. Two authors independently identified SRs and meta-analyses, collected data to assess the quality of included SRs and meta analyses according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) and the revised Assessment of Multiple Systematic Reviews (AMSTAR 2). Results: 31 SRs were identified. Quality of 22 SRs was critically low, 5 SRs were low, and 4 Cochrane SRs were moderate when evaluated by AMSTAR2. 17 SRs reported 85.2-96.3% items of PRISMA. Five SRs included explanatory RCTs, 16 SRs included pragmatic RCTs, and 10 SRs included both. Conclusion: Currently evidence on the effectiveness of acupuncture on post-acute stroke dysphagia is low quality. Type of study appeared to have no direct influence on the result, but the primary outcome measures showed a relationship with the quality of SRs. High quality trials with large sample sizes should be the focus of future research. PROSPERO REGISTRATION NUMBER: CRD42019134163

One of matrix equalities composed of multiple products of matrices and their generalized inverses is given by $A_1B_1^{-}A_2B_2^{-} \cdots A_kB_k^{-}A_{k+1}= A$ where $A_1$, $B_1$, $A_2$, $B_2$, $\ldots$, $A_k$, $B_k$, $A_{k+1}$, and $A$ are given matrices of appropriate sizes, and $B_1^{-}$, $B_2^{-}$, $\cdots$, $B_k^{-}$ are generalized inverses of matrices. The cases for $k = 1, 2$ and their special forms were properly approached in the theory of generalized inverses of matrices. In this note, the author presents an algebraic procedure to derive explicit necessary and sufficient conditions for the equality with $k = 3$ to always hold using certain rank equalities for the block matrices constructed by the given matrices, and then mention a key step of extending the previous work to a general situation.

Given a square matrix $A$, we are able to construct numerous equalities that involve reasonable mixed operations of $A$ and its conjugate transpose $A^{\ast}$, Moore--Penrose inverse $A^{\dag}$, and group inverse $A^{\#}$. Such kind of equalities can be generally represented in the equation form $f(A, \, A^{\ast}, A^{\dag}, A^{\#}) =0$. In this article, the author constructs a series of simple or complicated matrix equalities, as well as matrix rank equalities involving the mixed operations of the four matrices. As applications, we give a sequence of necessary and sufficient conditions for a square matrix to be range-Hermitian.

Kronecker products of matrices have some striking operation properties, one of which is called the mixed-product property $(A \!\otimes\! B)(C \!\otimes\! D) = AC \!\otimes\! BD$. In view of this property, the two-term Kronecker product $A_1 \otimes A_2$ can be rewritten as $A_1 \otimes A_2 = (A_1 \otimes I_{m_2})(I_{m_1} \otimes A_2)$ of dilation forms of $A_1$ and $A_2$, and three-term Kronecker product $A_1 \otimes A_2 \otimes A_3$ can be rewritten as the products $A_1 \otimes A_2 \otimes A_3 = (A_1\otimes I_{m_2} \otimes I_{m_3})(I_{m_1} \otimes A_2 \otimes I_{m_3})(I_{m_1} \otimes I_{m_2} \otimes A_3)$ of the dilation forms of $A_1$, $A_2$, and $A_3$, respectively, where the matrices on the right-hand sides of the two factorizations are commutative. In this note, we approach the commutative Kronecker products on the right-hand sides of the two factorization equalities, and present a variety of new and useful analytical formulas for calculating the ranks, dimensions, orthogonal projectors, and ranges of matrices composed of these Kronecker products.

This note reconsiders a matrix equality $A_1A_2^{-}A_3A_4^{-}A_5 = A$ composed by six matrices of appropriate sizes, where $A_2^{-}$ and $A_4^{-}$ are generalized inverses of $A_2$ and $A_4$, respectively, and solves a selection of matrix set inclusion problems associated with various mixed reverse order laws for generalized inverses of products of two, three, and four matrices by means of this equality and its variations.

It is a classic topic in algebras to construct and verify equalities that are composed of various algebraic operations of elements and their inverses or generalized inverses. In this note, the author constructs a matrix equality $(AB)^{\dag} = B^{\ast}(A^{\ast}ABB^{\ast})^{\#}A^{\ast}$ (called a mixed reverse-order law), where $A$ and $B$ are two matrices of appropriate sizes, $(\cdot)^{\ast}$, $(\cdot)^{\dag}$, and $(\cdot)^{\#}$ denote the conjugate transpose, the Moore--Penrose inverse, and the group inverse of a matrix, respectively, and shows that the mixed reverse-order law always holds. A list of variation forms of this matrix equality are also given, and necessary and sufficient conditions are obtained for them to hold. Especially, we show a remarkable fact that the two reverse-order laws $(AB)^{\dag} = B^{\dag}A^{\dag}$ and $(A^{\ast}ABB^{\ast})^{\#} = (BB^{\ast})^{\#}(A^{\ast}A)^{\#}$ are equivalent.

Reverse order laws for generalized inverses of matrix products is a classic object of study in the theory of generalized inverses. One of the well-known reverse order laws for a matrix product $AB$ is $(AB)^{(i,\ldots,j)} = B^{(s_2,\ldots,t_2)}A^{(s_1,\ldots,t_1)}$, where $(\cdot)^{(i,\ldots,j)}$ denotes an $\{i,\ldots, j\}$-generalized inverse of matrix. Because $\{i,\ldots, j\}$-generalized inverse of a singular matrix is unique, the relationships between both sides of the reverse order law can be divided into four situations for consideration. This paper provides a thorough coverage of the reverse order laws for $\{i,\ldots, j\}$-generalized inverses of $AB$, from the development of background and preliminary tools to the collection of miscellaneous formulas and facts on the reverse order laws in one place with cogent introduction and references for further study. We begin with the introduction of a linear mixed model $y = AB\beta + A\gamma + \epsilon$ and the presentation of two least-squares methodologies to estimate the fixed parameter vector $\beta$ in the model, and the description of connections between the two types of least-squares estimators and the reverse order laws for generalized inverses of $AB$. We then prepare some valued matrix analysis tools, including a general theory on linear or nonlinear matrix identities, a group of expansion formulas for calculating ranks of block matrices, two groups of explicit formulas for calculating the maximum and minimum ranks of $B^{(s_2,\ldots,t_2)}A^{(s_1,\ldots,t_1)}$, as well as necessary and sufficient conditions for $B^{(s_2,\ldots,t_2)}A^{(s_1,\ldots,t_1)}$ to be invariant with respect to the choice of $B^{(s_2,\ldots,t_2)}A^{(s_1,\ldots,t_1)}$. We then present a unified approach to the 512 matrix set inclusion problems associated with the above reverse order laws for the eight commonly-used types of generalized inverses of $A$, $B$, and $AB$ through use of the definitions of generalized inverses, the block matrix method (BMM), the matrix rank method (MRM), the matrix equation method (MEM), and various algebraic calculations of matrices.

This study primarily investigates the effect of fly ash (FA) content on the mechanical properties and hydration performance of alkali-activated ground granulated blast furnace slag cements (AAGC), and compares the related properties with ordinary Portland cement (OPC). Additionally, the study examined the hydration products, thermal analysis, MIP, SEM, chemically bound water, and pH values of AAGC. The compressive strength of AAGC showed a retrogression phenomenon from 3 to 28 days, with the 14-day and 28-day compressive strengths of AAGC being higher than those of OPC. The AAGC with 20% FA content exhibits the highest 28-day compressive strength (75 MPa). The hydration heat release rate curved of OPC and AAGC can be divided into the initial induction period, induction period, acceleration period, deceleration period and steady period. As FA content increases, the 28-day pore volume of AAGC increased while pH values and chemically bound water decrease. SEM images of AAGC with low FA content showed more microcracks.

Accurate measurement of systemic financial risk is critical to maintaining the stability of financial markets. Taking China as the subject of investigation, the Chinese Financial Stress Index (CFSI) indicator system was con-structed by integrating six dimensions and employing Gray Relation Analysis (GRA) for dimensionality reduction of the indicators. The CFSI was derived using the Attribute Hierarchy Model (AHM) method with the Criteria Importance Through the Intercriteria Correlation (CRITIC) method, and an Improved Gravitational Search Algorithm (IGSA) optimized Radial Basis Function Neural Network (RBFNN) was proposed for out-of-sample prediction of CFSI trends from 2024 to 2026. By analyzing the trend of financial pressure indicators, the relationship between financial pressure and economic activity can be effectively identified. The research findings indicate that: (1) The CFSI is capable of accurately reflecting the current financial stress situation in China; (2) The IGSA-RBFNN demonstrates good robustness and generalization capabilities, predicting that the CFSI index will reach a peak value of 0.543 by the end of 2024, and there exists a regular pattern of stress rebound towards the end of each year. The novel methodology benefits policymakers and regulatory authorities to formulate preventive measures and risk management by identifying potential risks and vulnerabilities in advance.

Zinc cobalt oxide-zinc hydroxide (ZnCo2O4-Zn(OH)2) microspheres were successfully fabricated on carbon cloth via a sample hydrothermal method. The surface morphology of these microspheres and their efficacy in degrading methyl violet were further modulated by varying the thermal annealing temperatures. The manipulation of thermal annealing temperatures was pivotal in adjusting the porosity of ZnCo2O4-Zn(OH)2 microspheres to amplify their photocatalytic performance. Various analytical techniques were utilized to evaluate the physical and chemical properties of the ZnCo2O4-Zn(OH)2 microspheres, including field-emission scanning electron microscopy, energy-dispersive spectroscopy, X-ray diffraction, field-emission transmission electron microscopy, X-ray photoelectron spectroscopy, and UV-vis spectroscopy. Compared to untreated ZnCo2O4-Zn(OH)2 microspheres, those subjected to thermal annealing exhibited increased specific surface area and light absorption capacity, rendering them highly effective photocatalysts under UVC light exposure. Subsequent studies have confirmed the superior performance of ZnCo2O4-Zn(OH)2 microspheres as a reusable photocatalyst for degrading methyl violet and tetracycline. Additionally, trapping experiments during the photodegradation process involving ZnCo2O4-Zn(OH)2 microspheres have identified hydroxyl radicals (·OH) and superoxide radicals (·O2–) as the primary reactive species.

Quality assurance has been one of the major challenges in laser-based additive manufacturing (AM) processes. This study proposes a novel process modeling methodology for layer-wise in-situ quality monitoring based on image series analysis. An image-based autoregressive (AR) model has been proposed based on the image registration function between consecutively observed thermal images. Image registration is used to extract melt pool location and orientation change between consecutive images, which contains sensing stability information. Subsequently, a Gaussian process model is used to characterize the spatial correlation within the error matrix. Finally, the extracted features from the aforementioned processes are jointly used for layer-wise quality monitoring. A case study of a thin wall fabrication by a Directed Laser Deposition (DLD) process is used to demonstrate the effectiveness of the proposed methodology.

Achieving sustainable management of forests in China is becoming increasingly important with more awareness and realization of the importance of forests in environmental protection. Forest certification, a market-based instrument to promote sustainable forest management, has been recognized by many countries including China. While landowners’ perception and perspective regarding this voluntary program have been well-documented in literature, how to motivate and incentivize landowners to participate in forest certification remained under-studied questions. With the face-to-face survey of landowners in Shandong, China, this study analyzed landowners’ willingness to accept compensation for participating in forest certification. Results indicated that landowners average accepted compensation, in terms of increased timber price, was about RMB120 (~$17.2)/m3 to have their forests certified. Results from multiple regression showed that the level of such compensation required for certification adoption was influenced by ownership size, owners’ demographics, certification program requirements, as well as importance placed on timber sale. These findings would inform policy-makers in designing compensation-related polices and establish incentive-based mechanisms to motivate landowners participate in forest certification programs in China.

Previous studies found that corilagin inhibits the growth of many cancer cells. Ovarian cancer is the deadliest gynecological malignancy, but research on the effects of corilagin on ovarian cancer is limited. This experiment aims to explore the impact of corilagin on ovarian cancer A2780 cell apoptosis and its mechanism of action to evaluate the prospects of corilagin in treating ovarian cancer. Corilagin significantly affects the A2780 cell cycle, reducing the proportion of G0/G1 and G2/M phase cells and blocking them in the S phase. Corilagin at low concentrations can cause A2780 cell apoptosis, mitochondrial membrane potential decline, and calcium influx. After the cells were stained with Acridine Orange, autophagosomes were observed under a fluorescence microscope and increased with the increase in concentration. The results of transcriptome sequencing showed that the effect of corilagin could cause differential expression of apoptosis-related genes in A2780 cells and concentrated on the PI3K-AKT pathway. The qPCR results showed that the expression of genes P53 and Bax in cells increased while the expression of BCL-2 decreased. The expressions of apoptotic factors caspase-9, caspase-3, p53-upregulated modulator of apoptosis (PUMA), and cytochrome C increased after the action of corilagin, indicating that corilagin can induce cell apoptosis. Corilagin can effectively inhibit the proliferation of A2780 cells, cause cell cycle arrest, and induce cell apoptosis. Moreover, it can trigger autophagy and has in vitro antitumor effects. It is a promising drug for treating ovarian cancer through the PI3K/P53 pathway.

Molecular modeling is widely utilized in subjects including but not limited to physics, chemistry, biology, materials science and engineering. Impressive progress has been made in development of theories, algorithms and software packages. To divide and conquer, and to cache intermediate results have been long standing principles in development of algorithms. Not surprisingly, Most of important methodological advancements in more than half century of molecule modeling are various implementations of these two fundamental principles. In the mainstream classical computational molecular science based on force fields parameterization by coarse graining, tremendous efforts have been invested on two lines of algorithm development. The first is coarse graining, which is to represent multiple basic particles in higher resolution modeling as a single larger and softer particle in lower resolution counterpart, with resulting force fields of partial transferability at the expense of some information loss. The second is enhanced sampling, which realizes "dividing and conquering" and/or "caching" in configurational space with focus either on reaction coordinates and collective variables as in metadynamics and related algorithms, or on the transition matrix and state discretization as in Markov state models. For this line of algorithms, spatial resolution is maintained but no transferability is available. Deep learning has been utilized to realize more efficient and accurate ways of "dividing and conquering" and "caching" along these two lines of algorithmic research. We proposed and demonstrated the local free energy landscape approach, a new framework for classical computational molecular science and a third class of algorithm that facilitates molecular modeling through partially transferable in resolution "caching" of distributions for local clusters of molecular degrees of freedom. Differences, connections and potential interactions among these three algorithmic directions are discussed, with the hope to stimulate development of more elegant, efficient and reliable formulations and algorithms for "dividing and conquering" and "caching" in complex molecular systems.

The autonomic regulation of hepatic metabolism offers a novel target for the treatment of non-alcoholic fatty liver disease (NAFLD). However, the molecular characteristics of neurons that regulate the brain-liver axis remain unclear. Since mice lacking neuronal lipoprotein lipase (LPL) develop perturbations in neuronal lipid-sensing and systemic energy balance, we reasoned that LPL might be a component of pre-autonomic neurons involved in the regulation of hepatic metabolism. Here we show that despite obesity, mice with reduced neuronal LPL (NEXCreLPLflox [LPL KD]) show improved glucose tolerance and reduced hepatic lipid accumulation with aging compared to WT controls (LPLflox). To determine the effect of LPL deficiency on neuronal physiology, liver-related neurons were identified in the paraventricular nucleus (PVN) of the hypothalamus using the transsynaptic retrograde tracer PRV-152. Patch-clamp studies revealed reduced inhibitory post-synaptic currents in liver-related neurons of LPL KD mice. Fluorescence Lifetime Imaging Microscopy (FLIM) was used to visualize metabolic changes in LPL-depleted neurons. Quantification of the free vs. bound Nicotinamide Adenine Dinucleotide (NADH) and Flavin Adenine Dinucleotide (FAD) revealed increased glucose utilization and TCA cycle flux in LPL-depleted neurons compared to controls. Global metabolomics from hypothalamic cell lines either deficient in, or over-expressing, LPL recapitulated these findings. Our data suggest that LPL is a novel feature of liver–related preautonomic neurons in the PVN. Moreover, LPL loss is sufficient to cause changes in neuronal substrate utilization and function, which may precede changes in hepatic metabolism.

The radar sensor described realizes healthcare monitoring capable of detecting subject chest-wall movement caused by cardiopulmonary activities, and wirelessly estimating the respiration and heartbeat rates of the subject without attaching any devices to the body. Conventional single-tone Doppler radar can only capture Doppler signatures because of a lack of bandwidth information with noncontact sensors. In contrast, we take full advantage of impulse radio ultra-wideband (IR-UWB) radar to achieve low power consumption and convenient portability, with a flexible detection range and desirable accuracy. A noise reduction method based on improved ensemble empirical mode decomposition (EEMD) and a vital sign separation method based on the continuous-wavelet transform (CWT) are proposed jointly to improve the signal-to-noise ratio (SNR) in order to acquire accurate respiration and heartbeat rates. Experimental results illustrate that respiration and heartbeat signals can be extracted accurately under different conditions. This noncontact healthcare sensor system proves the commercial feasibility and considerable accessibility of using compact IR-UWB radar for emerging biomedical applications.

Peach (L.) is a kind of fruit tree with considerable economic and nutritional significance. However, it shows a high sensitivity to drought stress, which has a profound impact on its growth. L-methionine (MET) and L-proline (PRO) are two amino acids synthesized by plants, which play an important role in abiotic stress response. However, their exact mechanism of action remains elusive. Through physiological analysis, MET (500ppm) and PRO (500ppm) treatments can effectively reduce the adverse effects of drought stress on the growth of peach seedlings. The results show that MET and PRO can effectively inhibit the stomatal opening of plant leaves under drought conditions and reduce the water evaporation of leaves under drought conditions. In addition, the application of MET or PRO promoted the accumulation of carbohydrates in the leaf tissues of peach seedlings under drought conditions, increased the intracellular relative water content (24%, 24%), decreased the leaf electrical conductivity (21%, 24%), and alleviated the membrane damage caused by drought. Experimental studies have confirmed that the alleviation of drought stress is due to the removal of reactive oxygen species (ROS) in vivo, that is, the downregulation of malondialdehyde (18%, 19%)，peroxidase (50%, 5%) and superoxide dismutase (12%, 14%) activities. In addition, the application of exogenous amino acids also improved the root morphological structure and root vitality of peach seedlings，which was conducive to absorbing external buffer substances and alleviating drought stress. In summary, the application of exogenous amino acids can effectively alleviate the effects of drought stress on plants and reduce the harm.

3,4-Dihydroquinolin-2(1H)-ones represent a class of valuable bioactive compounds with six-membered nitrogen-containing heterocyclic structures. The development of simple, mild and efficient synthetic methods has been widely concerned by synthetic chemists. In this review, we have summarized a series of different synthetic strategies for the synthesis of dihydroquinoline-2(1H)-ones via catalytic annulation of α,β-unsaturated N-arylamides in the past decade, including covering electrophilic cyclization, radical initiated cyclization and photochemical cyclization reactions. Besides, the substrate scope and mechanistic details are also discussed. This paper will provide a useful reference for the development of diverse synthesis methodologies of 3,4-dihydroquinolin-2(1H)-ones.

Brassica yellows virus (BrYV) is a tentative species of the genus Polerovirus, which occurs widely and mostly damage Brassicaceae plants in East Asia. Since BrYV could not be transmitted mechanically, an insect transmission method is required for further virus research. Here, a reliable and unrestricted method was described, in which non-viruliferous aphids (Myzus persicae) acquired BrYV from transgenic Arabidopsis thaliana plants with virus full length genome germinated from seeds and frozen infected leaves were used to transmit the virus to healthy plants, and there was no significant difference in acquisition rate though transmission rate from frozen infected leaves was somehow lower compared to fresh infected leaves. This novel simple method could be applied to preservation of virus inocula, evaluation of variety resistance to BrYV, biological research on interaction among BrYV, aphid and host, which also provide a new idea on establishing a basic method using virus genomic transgenic plants or frozen infected leaves for other poleroviruses research.

Trueperella pyogenes (T. pyogenes) can cause a variety of infections in animals and lead to economic loss in animal husbandry. TatD DNases are considered to be potential virulence factors in Plasmodium falciparum and Streptococcus pneumoniae. However, the function of TatD DNases in T. pyogenes is still unclear. Therefore, the aim of this study was to illustrate the function of TatD DNases of T. pyogenes (TpTatDs) and investigate whether luteolin is able to inhibit DNase function. The findings of our study are anticipated to be crucial to treating infections caused by T. pyogenes. Bioinformatic analysis has been used for the prediction of crucial functional residues of TpTatDs. The function of TpTatDs was investigated in the presence of divalent cations by hydrolyzing DNA with recombinant TatD proteins. Luteolin is a candidate nuclease inhibitor evaluated in our study. The interactions between luteolin and TpTatDs were tested using molecular docking analysis and surface plasmon resonance (SPR) assays. The inhibitory effect of luteolin on TpTatDs was analyzed by agarose gel electrophoresis. Two genes in the genome of T. pyogenes are suspected to encode TatD DNases. According to the length of their nucleotide sequences, they were named tatD960 and tatD825. Both of the TpTatDs, which are magnesium-dependent, were able to hydrolyze linear DNA and plasmids. In this study, we found through molecular docking analysis and SPR assays that luteolin can stably bind with TpTatDs. The gel assay revealed that luteolin can inhibit the DNase activity of TpTatDs. Our results indicated that TatD DNases from T. pyogenes are Mg2+-dependent DNases and exhibit DNA endonuclease activity. Moreover, luteolin reduced their DNA hydrolysis ability by decreasing the binding between TpTatDs and DNA.

Land surface temperature (LST) is a critical parameter for the dynamic simulation of land surface processes and for analyzing variations on regional or global scales. Obtaining LST with high spatiotemporal resolution is a subject of intensive and ongoing research. This study proposes a pixel-wise temporal alignment iterative linear regression model for downscaling based on MODIS LST products. This approach allows us to address the problem of high temporal resolution but low spatial resolution of the ERA5 reanalysis LST product, while remaining immune to pixel loss caused by clouds. The hourly ERA5 LST of the study area for 2012–2021 was downscaled to 1000 m resolution, and its accuracy was verified by comparison with measured data from meteorological stations. The downscaled LST offers intricate details and is faithful to the LST characteristics of distinct land-cover categories. In comparison with other downscaling techniques, the proposed technique is more stable and preserves the spatial distribution of ERA5 LST with minimal missing pixels. The pixel-wise average R-squared and mean absolute error for MODIS view times are 0.87 and 2.7 K, respectively, for cloud-free conditions at a 1000 m scale. Accuracy verification using data from meteorological stations indicates that the overall error is lower during cloudless periods rather than during overcast periods, during the night rather than during the day, and at MODIS view times rather than at non-view times. The maximum and minimum mean errors are 0.13 K for cloud-free periods and −0.98 K for cloudy periods, indicating a slight underestimation and overestimation, respectively. Conversely, the maximum and minimum mean absolute errors are 2.01 K for the daytime and 0.85 K for the nighttime. Therefore, the model ensures higher accuracy during cloudy periods with only clear sky LST as input data, making it suitable for long-term, all-weather ERA5 LST downscaling.

Mountain ecosystems are crucial for global biodiversity conservation. However, their landscape features are constantly changing owing to urban expansion. Understanding the relationships between biotic communities and landscape features is essential for biodiversity conservation. This study aimed to examine the effect of land-cover type on avian communities in Lishui, a mountainous urban area in eastern China. Avian surveys were conducted using a total of 168 line transects across different land-cover types once per season from December 2019 to January 2021. We assessed the diversity of bird communities by calculating various metrics at both taxonomic and functional levels. Among the land-cover types measured, woodland, built-up land, cultivated land, and water bodies significantly influenced bird community diversity and composition. Species richness, species abundance, and functional richness were negatively correlated with the proportion of woodland but positively correlated with the proportion of non-natural land cover, such as built-up and cultivated land. In contrast, functional evenness was positively correlated with the proportion of woodland and grassland but negatively correlated with the proportion of non-natural land cover. Land-cover type also exhibited significant correlations with avian functional characteristics such as diet, foraging strata, and body mass, thereby influencing the overall community structure. Our results indicated that mountainous landscape patterns substantially affect avian communities. Different land-cover types possess varying resource endowments that affect the distribution of avian species. Therefore, urban landscape planning in mountainous areas should carefully consider the various functions provided to organisms by different types of land cover to promote biodiversity.

In this note, we provide some effective treatments of a general linear model with adding-up restrictions via algebraic operations of given vectors and matrices in the model, including analytic expressions of the well-known ordinary least-squares estimator (OLSE) and the best linear unbiased estimator (BLUE) of the unknown parameters in the model.

This note shows that the well-known reverse order law $(AB)^{\dag} = B^{\dag}A^{\dag}$ for the Moore--Penrose inverse of matrix product is equivalent to many other equalities for that are composed of multiple products $(AB)^{\dag}$ and $B^{\dag}A^{\dag}$ by means of the definition of the Moore--Penrose inverse and orthogonal projector theory.

The black hole information paradox is one of the most puzzling paradoxes in physics. Black holes trap everything that falls into them, while their mass may leak away through purely thermal Hawking radiation. When a black hole vanishes, all the information locked inside, if any, is just lost, thus challenging the principles of quantum mechanics. However, some information does have a way to escape from inside the black hole, that is, through gravitational waves. Here, a concise extension of this notion is introduced. When a black hole swallows something, whether it is a smaller black hole or an atom, the system emits gravitational waves carrying the information about the “food”. Although most of the signals are too weak to be detected, the information encoded within them will persist in the universe. This speculation provides an explanation for a large part, if not all, of the supposed “information loss” in black holes, and thus reconciles the predictions of general relativity and quantum mechanics.

One of the typical forms of linear matrix expressions (linear matrix-valued functions) is given by $A + B_1X_1C_1 + \cdots + B_kX_kC_k$, where $X_1, \ldots, X_k$ are independent variable matrices of appropriate sizes, which include almost all matrices with unknown entries as its special cases. The domain of the matrix expression is defined to be all possible values of the matrix expressions with respect to $X_1, \ldots, X_k$. I this article, we approach some problems on the relationships between the domains of two linear matrix expressions by means of the block matrix method (BMM), the matrix rank method (MRM), and the matrix equation method (MEM). As application, we discuss some topics on the relationships among general solutions of some linear matrix equations and their reduced equations.

The traditional Chinese drug Bombyx Batryticatus mori.L (BBm) which is also named the white stiff silkworm has been widely used in Chinese clinics for thousands of years. It is famous for its antispasmodic and blood circulation promoting effects. Cardiomyocyte hypertrophy, interstitial cell hyperplasia and myocardial fibrosis are closely related to the N-glycosylation of key proteins. To examine the alterations of N-glycosylation that occur in diabetic myocardium during the early stage of the disease and clarify the therapeutic effect of 1-DNJ extracted from BBm, we used the db/db mouse model and an approach based on hydrophilic chromatography solid-phase extraction integrated with an LC-MS/MS identification strategy to perform a site-specific N-glycosylation analysis of left ventricular cardiomyocyte proteins. AGEs, hydroxyproline, CTGF and other serum biochemical indicators were measured with ELISA. In addition, the α1,6-fucosylation of N-glycans was profiled with LCA lectin blots and FITC-labelled lectin affinity histochemistry. The results indicated that 1-DNJ administration obviously downregulated myocardium protein N-glycosylation in db/db mice. The expression levels of serum indicators and fibrosis-related cytokines were reduced significantly by 1-DNJ in a dose-dependent manner. The glycan α1,6-fucosylation level of the db/db mouse myocardium was elevated, and the intervention effect of 1-DNJ administration on N-glycan α1,6-fucosylation was significant. To verify this result, the well-known TGF-β/smad2/3 pathway was selected, and core α1,6-fucosylated TGFR-βⅡ was analysed semi-quantitatively with western blotting. The result supported the conclusions obtained from LCA lectin affinity histochemistry and lectin blot analysis. The expression level of FUT8 mRNA was also detected, and the results showed that 1-DNJ administration did not cause obvious inhibitory effects on FUT8 expression. Therefore, the mechanism of 1-DNJ to relieve the DCM-associated fibrosis can be concluded as the inhibition of N-GlcNAc formation and the reduction of substrate concentration.

In order to make full use of the complementarity of existing navigation systems to improve the navigation and positioning accuracy, this paper investigates the visual/INS integrated navigation system based on the factor graph optimization (FGO) algorithm. In the traditional visual/INS integrated navigation system, there is often the problem of image blurring due to the rapid change of light and shadow captured by the vision sensor and the attitude change of the carrier, which leads to the decrease of the positioning accuracy of the combined navigation system. Therefore, this paper firstly introduces Retinex algorithm and BID algorithm to carry out the design of image de-blurring method; then implements the visual/INS integrated navigation algorithm based on the factor graph optimization method; finally, the experimental scheme is designed, comparative experiments are carried out, and the researched method is verified by using the public dataset. The experimental results show that the combined navigation algorithm realized in this paper has high accuracy, and its positioning accuracy is improved by 40% compared with visual positioning.

Animal personalities play a crucial role in invasion dynamics during alien species invasions. The behavioral strategies adopted by native species varied among personalities when facing an invasion by alien species, just as the invasive species exhibited variations in behavior strategies across different personalities during the invasion process. However, the effects of personality interactions between native species and invasive species on behavior and growth are rarely illustrated. We used the globally invasive freshwater turtle Trachemys scripta elegans and the native freshwater turtle Mauremys reevesii to investigate how the personality combinations of native and invasive turtles would impact the foraging strategy and growth of both species. We found that M. reevesii exhibited bolder and more exploratory personalities than T. scripta elegans. The foraging strategy of M. reevesii was mainly affected by the personality of T. scripta elegans, while the foraging strategy of T. scripta elegans was influenced by both their own personality and M. reevesii's personality. In addition, we did not found that the personality combination would affect the growth of either T. scripta elegans or M. reevesii. Difference in foraging strategy may be due to the competitive advantage of invasive species and variations in the exploration-exploitation foraging strategy among different personalities. Overall, our results reveal the mechanisms of personality interaction effects on the foraging behavior of both native and invasive species during alien species invasion and provide empirical evidence to help understand the effects of personality in invasion dynamics.

Based on the perspective of complex directed weighted network analysis, this paper constructs a static resilience evaluation framework for trade networks from two dimensions: structural resilience and node resilience. It studies the evolution of static resilience in the upstream, midstream, downstream, and recycling trade networks of global wood forest products from 2002 to 2021. The study finds that the total trade volume of global wood forest products has increased by 58.0%, 77.3%, 71.2%, and 77.2% in the upstream, midstream, downstream, and recycling sectors, respectively. The downstream trade network exhibits efficient information transmission and resource mobility capabilities. All four types of trade networks exhibit scale-free characteristics, with core countries such as China, the United States, and Germany playing a dominant role in the network and playing a crucial role in network robustness, but also increasing network vulnerability. In terms of unweighted assortativity, all four networks exhibit the characteristic of "small countries relying on hubs," while the weighted assortativity of the downstream network is positive, indicating enhanced network resilience. In terms of node resilience, countries exhibit significant differences and dynamic changes. China demonstrates strong resilience and adaptability, while the United States maintains its core position. China's influence in the downstream network has significantly increased, and India has rapidly emerged in the recycling network. To enhance network resilience, it is necessary to increase diversity and redundancy, establish effective emergency response mechanisms, and promote the diversification and green transformation of the supply chain.

In recent years, the High Dynamic Range (HDR) image has gained widespread popularity 1 across various domains such as security, multimedia, and biomedical fields, owing to its ability 2 to deliver an authentic visual experience. However, the extensive dynamic range and rich detail 3 in HDR images present challenges in assessing their quality. Therefore, current efforts involve 4 constructing subjective databases and proposing objective quality assessment metrics to achieve 5 efficient HDR Image Quality Assessment (IQA). Recognizing the absence of a systematic overview 6 of these approaches, this paper provides a comprehensive survey of existing HDR IQA methods. 7 Furthermore, this paper aims to serve as a valuable resource for researchers by discussing the 8 limitations of current methodologies and potential research directions in the future.

Q345 steel is widely used in the construction industry, vehicle manufacturing industry, bridge construction industry and many other aspects due to its excellent comprehensive performance. However, due to its high silicon content, direct hot-dip galvanizing will lead to a series of problems, such as easy peeling of the coating due to the "silicon reactivity". In this paper, we adopt the "two-step hot-dipping method", first hot-dip aluminizing and then hot-dip galvanizing, to isolate the substrate and zinc liquid direct contact, so as to avoid the occurrence of "silicon reactivity". Through the microstructure characterization, neutral salt spray corrosion experiments, electrochemical experiments, the results show that: Al-Zn composite coatings from the inside out were perpendicular to the substrate growth of loose Fe2Al5 layer and Al-Zn layer, outbursts generation; Al-Zn composite coatings resistance to neutral salt spray corrosion was far more than the substrate; Al-Zn composite coatings polarization curve corrosion potential than the substrate was lower than that of the substrate by 0.512V, showing a strong corrosion resistance. It shows extremely strong corrosion resistance.

Magnesium and its alloys are not normally used as bio-resorbable temporary implants due to their high and uncontrolled degradation rate in physiological liquid environment. The improvement of corrosion resistance to simulated body fluids (SBF) of a Magnesium alloy (AZ31) coated with poly-β-hydroxybutyrate (PHB) was investigated. Scanning electron microscopy, Fourier transform infrared spectrometer, and contact angle measurements were used to characterize surface morphology, material composition and wettability, respectively. pH modification of the SBF corroding medium, mass of Mg2+ ions released, and weight loss of the samples exposed to the SBF solution, and electrochemical experiment were used to describe the corrosion process and its kinetics. Materials biocompatibility was described by evaluating the effect of corrosion by products collected in the SBF equilibrating solution on hemolysis ratio, cytotoxicity, Nitric Oxide (NO), and total antioxidant capacity (T-AOC). The results showed that the PHB coating can diffusively control the degradation rate of Magnesium alloy improving its biocompatibility: hemolysis rate of materials was lower than 5%, while in vitro Human Umbilical Vein Endothelial Cells（HUVECs) compatibility experiments showed that PHB coated Mg alloy promoted cell proliferation and had no effect on the NO content, the T-AOC was enhanced compared with the normal group and bare AZ31 alloy. PHB coated AZ31 Magnesium alloy extraction fluids have a less toxic behavior due to the lower concentration of corrosion by-products deriving from the diffusion control exerted by the PHB coating films both from metal surface to the solution and vice versa. These findings provide more reference value for the selection of such system as tunable bioresorbable prosthetic materials

Endotoxins are toxic substances that widely exist in the environment and can enter the intestine with food and other substances. Intestinal epithelial cells are protected by a mucus layer that contains MUC2 as its main structural component. However, a detailed understanding of the mechanisms involved in the function of the mucus barrier in endotoxin penetration is lacking. Here, we established the most suitable proportion of Caco-2/HT-29 co-culture cells as a powerful tool to evaluate the intestinal mucus layer. Our findings significantly advance current knowledge as focal adhesion and ECM-receptor interaction were identified as the two most significantly implicated pathways in MUC2 small interfering RNA (siRNA)-transfected Caco-2/HT-29 co-culture cells after 24 h of LPS stimulation. When the mucus layer was not intact, LPS was found to damage the tight junctions of Caco-2/HT29 co-cultured cells. Furthermore, LPS was demonstrated to inhibit the integrin-mediated focal adhesion structure and damage the matrix network structure of the extracellular and actin microfilament skeletons. Ultimately, LPS inhibited the interactive communication between the extracellular matrix and the cytoskeleton for 24 h in the siMUC2 group compared with the LPS(+) and LPS(-) groups. Overall, we recognized the potential of MUC2 as a tool for barrier function in several intestinal bacterial diseases.

Biological neural network (BNN) is the core brain for creature to accomplish its intelligent behaviors through unique network structure and mechanisms. It also inspires controlling human-designed autonomous agents including robots to generate more advanced intelligent behaviors by mimicking the neural control mechanism of creatures at a deeper and more interactive level. Here, we constructed a whole-brain neural network model of Caenorhabditis elegans (C. elegans), which characterizes the electrochemical processes at the level of cellular synapse. The neural network simulation integrates computational programming and visualization of neurons and synapse connections of C. elegans, containing the specific controllable circuits summarization with their dynamic characteristics within the whole network. To illustrate its particular intelligent control capability in terms of robotics, we introduce the first innovative methodology for applying the BNN model to a 12-legged robot’s movement control based on the established numerical simulation platforms. We accomplished and designed two methods and corresponding encoding processes, one involving orientation control and the other involving locomotion generation, to demonstrate the intelligent control performance of BNN. Both simulation and experiment results indicate that the robot exhibits stronger autonomy and more intelligent moving performance under the control of BNN. We then summarized the contributions for digitalizing the C. elegans’ whole-brain neural network in real-time and utilizing it to control robot in a closed loop to validate its advanced intelligence control ability in terms of a scientific robot.

In this paper we totally discard the traditional trial-and-error algorithms of choosing acceptable shape parameter c in the multiquadrics $-\sqrt{c^{2}+\|x\|^{2}}$ when dealing with differential equations. Instead, we choose c directly by the MN-curve theory and hence avoid the time-consuming steps of solving a linear system required by each trial of the c value in the traditional methods. The quality of the c value thus obtained is supported by the newly born choice theory of the shape parameter. Experiments show that the approximation error of the approximate solution to the differential equation is very close to the best approximation error among all possible choices of c.

Background: Coronavirus disease (COVID-19) related pneumonia is leaded by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), which infects host cells through receptors named Angiotensin-converting enzyme 2 (ACE2). Smoking is thought to be related to poor disease prognosis, as a large amount of evidence highlights the negative effects of smoking on lung health and its causal relationship with various respiratory diseases. Methods: We first evaluated the role of ACE2 expression level with tobacco effect. And correlation analyses were used to identify the related genes of ACE2 both in smoker trait and human normal multi-tissues. After intersections, hub genes were later used to further GSEA and co-regulated mechanisms were explored by GeneMANIA. We used UALCAN to perform survival curves of pan-cancers included 33 types of cancers. New clinical model of top co-occurrence cancer type was constructed and validated. Results: Effected by cigarette smoking, the expression level of ACE2 expressed statistically upwards in current smokers compared with never smokers, upwards in groups after acute smoke exposed compared with normal control. But no strong evidence detected in third-hand smoke, as poor amounts of samples, only 4. A little trend of expressing upwards became in groups after third-hand smoke compared with groups after clean air exposing. 4 genes included PIR, ADH7, AKR1C2 and AKR1C3 were identified as ACE2 related genes in smoker trait and human normal multi-tissues. Then, we made the survival curves of pan-cancers in 4 genes. Brain lower grade glioma was the co-occurrence type as both ACE2, PIR and AKR1C3 had the significantly prognostic situation. Later, we made the new clinical prediction model as the C-index was 0.827 and the Area Under Curves (AUCs) of 1-year survival, 2-year survival and 3-year survival were 0.921(95%CI, 0.882-0.961), 0.911(95%CI, 0.860-0.962) and 0.878(95%CI, 0.818-0.939). In inner validation, the AUCs of 1-year survival, 2-year survival and 3-year survival were 0.777(95%CI, 0.640-0.914), 0.916(95%CI, 0.842-0.990) and 0.888(95%CI, 0.768-1.000). In outer validation one, the AUCs of 1-year survival, 2-year survival and 3-year survival were 0.764(95%CI, 0.672-0.856), 0.848(95%CI, 0.783-0.913) and 0.748(95%CI, 0.656-0.841). And in outer validation two the AUCs of 1-year survival, 2-year survival and 3-year survival were 0.740(95%CI, 0.654-0.826), 0.766(95%CI, 0.688-0.843) and 0.794(95%CI, 0.721-0.866). Conclusions: In our study, we compared the ACE2 expression level between smokers and non-smokers crowds and identified associated hub genes. Then we explored the further role of hub genes in tumor fields to identify the correlation and influence between the avoidable host factors such as smoking on COVID-19 contamination and tumor. ACE2 and AKR1C3 are potential prognostic genes for brain lower grade glioma, and we created the web dynamic nomogram and encapsulation app through validations.

The genetic diversity of coronavirus (CoV) is high, and its infection in animals has not yet been fully revealed. By RT-PCR detection of partial RNA dependent RNA polymerase (RdRp) gene of CoV, we screened a total of 502 small mammals belonging to 18 species in 12 genera and 4 orders collected in Dali and Nujiang Prefecture of Western Yunnan Province, China. The prevalence of β-CoV in Chevrieri's field mouse (Apodemus chevrieri) and Lancangjiang field mouse (A. ilex) were 3.54% (4/113) and 6.67% (6/90), respectively; the prevalence of α-CoV in White-footed Indochinese rat (Rattus nitidus) and long-tailed red-toothed shrew (Episoriculus leucops) was 75% (3/4) and 5.88% (1/17), respectively. The co-infection rates of β-CoV and α-CoV in Kachin red-backed vole (Eothenomys cachinus), Norway rat (R. norvegicus) were 2.22% (2/90), 3.85% (1/26) respectively. The identity of the partial RdRp genes obtained of 13 strains of β-CoV was 83.42%-99.23% at nucleotide level, and it is worth noting that the two strains from Kachin red-backed vole showed highly homology to BOV-36/IND/2015 from Indian bovine and DcCoV-HKU23 from one-humped camel (Camelus dromedarius) in Morocco, the nucleotide similarity between 97.86%-98.33%. Similarly, the identity of the 7 strains of α-CoV among the partial RdRp sequences was 94.00%-99.18% at nucleotide levels. The viral load in different tissues was measured by quantitative RT-PCR (qRT-PCR). The average CoV viral load in small mammalian intestinal tissue was 1.25×106copies/g, differently, the mean CoV viral load in liver, heart, lung, spleen and kidney tissue was from 1.29×103 to 4.02×103copies/g, which revealed that CoV has extensive tropism of intestinal tissue in small mammals (P < 0.0001). This result revealed the genetic diversity, epidemiology, and infective tropism of α-CoV and β-CoV in small mammals from Dali and Nujiang, which deepens the comprehending of the retention and infection of coronavirus in natural hosts.

Large terrestrial carnivores play a crucial role in top-down control within terrestrial ecosystems, maintaining ecosystem stability and biodiversity. However, intense interspecific competition often arises among sympatric large carnivores, leading to population reductions or even extinctions. Spatial partitioning through divergent habitat selection helps mitigate such competition. In Xinlong County, Sichuan Province, we used 293 infrared cameras for monitoring from September to May 2016 and March to October 2022. By employing the Generalized Linear Model (GLM) and the Maximum Entropy Model (MaxEnt), we developed an ensemble model predicting the suitable habitat distribution of leopards (Panthera pardus) and wolves (Canis lupus). We analyzed the main environmental factors influencing habitat selection and the fragmentation of suitable habitats. We found that suitable habitat distribution differed significantly between them. Both species preferred areas with gentle slopes close to settlements. While leopards' habitat selection primarily depended on the distance from settlements, the slope was predominant for wolves. Suitable habitats displayed aggregation, yet wolves exhibited higher fragmentation and more complex patch shapes, indicating greater susceptibility to human activities. These results suggest that sympatric large carnivores, such as leopards and wolves, can reduce spatial competition intensity and promote spatial partitioning by selecting divergent suitable habitats, thereby facilitating species coexistence.

Hexabromocyclododecane (HBCD) was most important flame retardant in Expanded Polystyrene foam and Extruded Polystyrene foam in the past forty years in the world. China was the major producer and user of HBCD, and the total HBCD production was about 0.3 million tons. Although HBCD has been completely banned in China in 2021 because of its long-range transport, bioaccumulation and toxicity, there's still a lot of residues in environment. Therefore, we reviewed multiple studies concerning the distribution of HBCD in diverse environmental matrices, such as air, dust, soil, water, sediment and biota. Results revealed that HBCD levels in different environments in China present a geographical variation and were at high level compared with other countries. In all environmental media, relatively high HBCD concentrations have been found in industrial and urban areas. Industrialization and urbanization are two important factors that influence the concentration and distribution of HBCD in the environment. In terms of isomer, γ-HBCD was the dominant isomer in soil, water, and sediment, while in the biota, α-HBCD was the predominant isomer.

This study reports rapid hydrolysis, acylation, and lipolysis with lipase B from Candida antarctica (CalB) and nanofructosome encapsulated CalB (CalB@NF) enzymes immobilized on silica-coated magnetic nanoparticles (Si-MNPs). Enzymatic hydrolysis was confirmed for conversion to p-nitrophenol (p-NP, λex=400 nm) from p-nitrophenyl butyrate (p-NPB, λex=270 nm), and various catalytic parameters such as Km, Vmax, and Kcat were calculated from Michaelis-Menten and Lineweaver-Burk plot. Efficiency of enzymatic hydrolysis was in the order of CalB > Si-MNPs@CalB > CalB@NF > Si-MNPs@CalB@NF, and reusability was much better with the enzyme immobilized on Si-MNPs than with the native enzyme. Enzymatic acylation was confirmed by the formation of benzyl benzoate (λex=229 nm) from benzoic anhydride (λex=240 nm), and efficiency exceeded 99% in all samples. Finally, enzymatic lipolysis was confirmed by the decomposition of olive oil to fatty acid such as oleic acid (λex=230 nm) using thin-layer chromatography (TLC), column chromatography, and proton nuclear magnetic resonance (1H -NMR). The lipases immobilized on Si-MNPs have the advantage of good thermal stability and reusability and are thus applicable to a wide range of industries.

This paper presents a new semi-explicit algorithm for parameters estimation in a time-fractional generalization of dual-phase-lag heat conduction model with the Caputo fractional derivatives. It is shown that this model can be derived from a general linear constitutive relation for the heat transfer by conduction when the heat conduction relaxation kernel contains the Mittag-Leffler function. The model can be used to describe heat conduction phenomena in a material with power-law memory. The proposed algorithm of parameters estimation is based on the time integral characteristics method. The explicit representations of the thermal diffusivity and the fractional analogues of the thermal relaxation time and the thermal retardation are obtained via a Laplace transform of the temperature field and utilized in the algorithm. An implicit relation is derived for the order of fractional differentiation. In the algorithm, this relation is resolved numerically. An example illustrates the proposed technique.

Disparities between fold amplitude (A) and intrusion thickness (Hsill) are critical in identifying elastic or inelastic deformation in a forced fold. However, accurate measurement of these two parameters is challenging because of the limit in separability and detectability for the seismic data. In the TZ-47 exploring area from the Tarim Basin, Northwest China, we combined wireline data and 3-D seismic data, to accurately constrain the fold amplitude and total thickness of sills that inducing the roof uplift. The measurement results show that the forced fold amplitude is 155 m and the total sill thickness is 148.4 m. When using a magma density of 2.7 g/cm3, and solid rock density of 3 g/cm3, the molten magma thickness at the time of intrusion would be 153.8 m, which is almost no difference from the forced fold amplitude. Therefore, the TZ-47 fold is a pure elastic forced fold induced by emplacement of multiple sills. Measurement solely based on seismic data may not be able to detect some thin interlayers and may result in large errors.

The process of oxygenic photosynthesis is primarily driven by two multiprotein complexes known as photosystem II (PSII) and photosystem I (PSI). PSII facilitates the light–induced reactions of water–splitting and plastoquinone reduction, while PSI functions as the light–driven plastocyanin-ferredoxin oxidoreductase. In contrast to the highly conserved structure of PSII among all oxygen–evolving photosynthetic organisms, the structures of PSI exhibit remarkable variations, especially for photosynthetic organisms that grow in special environments. In this review, we make a concise overview of the recent investigations of PSI from photosynthetic microorganisms including prokaryotic cyanobacteria and eukaryotic algae from the perspective of structural biology. All known PSI complexes contain a highly conserved heterodimeric core; however, their pigment compositions and peripheral light-harvesting proteins are substantially flexible. This structural plasticity of PSI reveals the dynamic adaptation to environmental changes for photosynthetic organisms.

Due to the extraordinary mechanical properties of ultra-high-performance concrete (UHPC), the shear stirrups in UHPC beams could potentially be removed. The aim of this study is to determine the effect of beam height and steel fiber volume content on the shear behavior of non-stirrup UHPC beams under a larger shear span-depth ratio (up to 2.8). Eight beams were designed and fabricated, including six non-stirrup UHPC beams and two comparing stirrup-reinforced normal concrete (NC) beams. The experimental results demonstrated that the volume content of steel fiber could be a crucial factor affecting the ductility, cracking strength, and shear strength of non-stirrup UHPC beams and altering their failure modes. Additionally, the height of the beam had a considerable effect on its shear resistance. This study revealed that the French standard formulae were more accurate for the UHPC beams with larger shear span-depth ratios and PCI-2021 formulae greatly overestimate the shear capacity of UHPC beams with larger shear span-depth ratios. Xu’s formulae were more accurate for the steel fiber-reinforced UHPC beams with larger shear span-depth ratios.

Extracellular vesicles (EVs) are emerging mediators of intracellular and inter-organ communications in cardiovascular diseases (CVDs), especially in the pathogenesis of heart failure through the transference of EV-containing bioactive substances. microRNAs (miRNAs) are contained in EV cargo and are involved in the progression of heart failure. Over the past several years, a growing body of evidence has suggested that the biogenesis of miRNAs and EVs are tightly regulated, and the sorting of miRNAs into EVs is highly selective and tightly controlled. Extracellular miRNAs, in particular circulating EV-miRNAs, have shown promising potential as prognostic and diagnostic biomarkers for heart failure and as therapeutic targets. In this review, we summarize the latest progress concerning the role of EV-miRNAs in HF and their application in a therapeutic strategy development for heart failure.

In the paper, a fully discrete compact difference scheme with $O(\tau^{2}+h^{4})$ precision is established by considering the numerical approximation of the one-dimensional Allen-Cahn equation. The numerical solutions satisfy discrete maximum principle under reasonable step ratio and time step constraint is proved. And the energy stability for the fully discrete scheme is investigated. An example is finally presented to show the effectiveness of scheme.

Objective: To use the ancient and modern medical record cloud platform (V2.3.5) to organize and explore the medication patterns of the "Three Causes, Extremity, and One Disease Syndrome Formula" by Chen Wuxuan, and to summarize its therapeutic ideas. Method: Collect and organize the "San Yin Si Tian Fang" in the "San Yin Ji Yi Zheng Fang Lun", and use the modern medical record cloud platform (V2.3.5) to conduct medication frequency statistical analysis, cluster analysis, and complex network analysis. As a result, a total of 16 Chinese herbal medicines were collected in the "Three Causes, Extreme and One Disease Syndrome Formula", involving 75 traditional Chinese medicines. Statistical analysis showed that roasted licorice was the most commonly used, followed by Pinellia ternata, papaya, ginger, and Poria cocos; Medications mainly include warm drugs, sweet and pungent flavors, as well as drugs that promote lung and spleen meridians. Cluster analysis can divide the above-mentioned traditional Chinese medicine into two groups, with specific grouping as follows. Group 1: ginger, white peony, aconite, papaya, and achyranthes bidentata; Group 2: roasted licorice, poria cocos, dried ginger, pinellia ternata, and green peel. Conclusion: The characteristics of the 16 prescriptions are biased towards Xin Gan Wen, emphasizing the regulation of the spleen and stomach, which may be related to the common use of prescription by doctors in the Song Dynasty and the tendency towards warm and dry medication.

The potential effect of implementing environmental regulations on economic growth is a controversial issue for a long time. As portrayed by Porter hypothesis, environmental regulations may impact on economic growth by reconstructing the economic structure. A number of previous literature proved the connections between the above three parties. With the intention of exploring the nature of this mechanism, it is important to understand the internal inter-relation of the three parties, requiring data from a large economy experiencing the transition in economic structure. By constructing a panel containing data from 30 Chinese provinces over 10 years (2008-2019), this paper investigate the dynamic inter-relation of the three parties by introducing PVAR model with Granger Test. Results reveal that environmental regulations give a “U” shaped impact to economic growth. In return, economic growth promotes the development of economy with a weakening strength. In addition, results also support the hypothesis that economic structure is the intermediate of economic growth and environmental regulations. There is a rooftop for the effect of economic structure to environmental regulations. The rooftop may signify the best optimization of primary structure.

Piezoelectric ultrasonic motors (USMs) are actuators that use ultrasonic frequency piezoelectric vibration generated waves to transform electrical energy into rotary or translating motion. USMs are paid more attention because they offer distinct qualities over traditional magnet-coil-based motors, such as miniaturization, great accuracy, speed, non-magnetic nature, silent operation, straightforward construction, broad temperature operations, and adaptability. This review study focuses on the principle of USMs and their classifications, characterization, fabrication methods, applications, and future challenges. Firstly, the classifications of USMs, especially, standing wave, traveling wave, hybrid mode, multi degree of freedom USMs are summarized, and their respective functioning principles are explained. Secondly, the finite element modelling analysis for design and performance predictions, the conventional and nano/micro fabrication methods, and, the various characterization methods are presented. Thirdly, their advantages, such as high accuracy, small size, and silent operation and their benefits over conventional motors for the different specific applications are examined. In addition, the substantial contributions to a variety of tech-nical fields like surgical robots, industrial, aerospace, and biomedical applications are introduced. Finally, their future prospects and challenges in USMs development, with an emphasis on downsizing, increasing efficiency, and new materials are outlined.

Our results demonstrated that SWT stimulates osteoblastogenesis and increase the cell number of osteoblasts, suggesting positive regulatory effects on osteoblast differentiation. However, the effect of SWT on bone formation need further examination, since the expression of alp gene is downregulated. On the other hand, SWT appears to negatively regulate osteoclast differentiation and bone resorption, as number of osteoclasts and the expression of critical bone resorptive genes are all downregulated. Collectively, SWT might change the equilibrium of bone remodeling and increase the bone mass. Our data provided supportive evidences that this medicine formulation can be applied to treat osteoporosis or bone destructive diseases.

With prosperous development and successful application of deep learning technologies in the field of remote sensing, numerous deep-learning based methods have emerged for synthetic aperture radar (SAR) automatic target recognition (ATR) tasks over the past few years. Generally, most deep-learning based methods can achieve outstanding recognition performance in condition that an abundant of labeled samples are available to train the model. However, in real application scenarios, it is difficult and costly to acquire and to annotate abundant SAR images due to the imaging mechanism of SAR, which poses a big challenge to existing SAR ATR methods. Thereby, SAR target recognition under the situation of few-shot, where only a scarcely few of labeled samples are available, is a fundamental problem that needs to be solved. In this paper, we put forward a new method named enhanced prototypical network with customized region-aware convolution (CRCEPN) to specially tackle the few-shot SAR ATR tasks. To be specific, We first develop a feature extraction network based on a customized and region-aware convolution, which can adaptively adjust convolutional kernels and their receptive fields according to each SAR image’s own characteristics as well as the semantical similarity among spatial regions, thus augmenting its capability to extract more informative and discriminative features. To achieve accurate and robust target identity prediction under the few-shot condition, we then propose an enhanced prototypical network which can improve the representation ability of the class prototype by properly making use of training and test samples together, thus effectively raising the classification accuracy. Meanwhile, a new hybrid loss is designed to learn a feature space with both inter-class separability and intra-class tightness as much as possible, which can further upgrade the recognition performance of the proposed method. Experiments performed on the moving and stationary target acquisition and recognition (MSTAR) dataset and the OpenSARShip dataset demonstrate that the proposed method is competitive with some state-of-the-art methods for few-shot SAR ATR tasks.

Smart agriculture is a new way of farming that uses advanced technology. It makes a significant contribution to improving the efficiency and productivity of farming practices. Systems that use drones to monitor pests and spray pesticides greatly reduce the burden on farmers. In addition, remote sensing technology facilitates the monitoring of crop growth conditions and the early detection of diseases and pests. However, the high cost of equipment to communicate sensor data is preventing farmers from adopting sensing systems. As a result, many studies have been conducted to make the sensing system available at a low cost. Nevertheless, many farmers have not yet adopted them. Therefore, this paper proposes an agricultural sensor network system using drones and optical camera communication (OCC). The proposed system aims to achieve high-density farm sensing at low cost. The proposed system uses OCC as the communication method for sensor data. Low cost light sources such as LED panels can be used as transmitters. In addition, existing agricultural drones equipped with cameras can be used as receivers. We also propose a trajectory control algorithm for the receiving drone to efficiently collect the sensor data. The proposed system is suitable for deploying sensor networks in areas with underdeveloped infrastructure and radio silence. In this paper, we conducted a preliminary experiment at a leaf mustard farm in Kamitonda-cho, Wakayama to demonstrate the effectiveness of the proposed system using a Mavic 2 Pro drone, launched by DJI Co., Ltd.

Wenchuan earthquake that occurred in China in 2008 caused severe damage to a large number of electric substations. In this paper, Kriging interpolation method was used to calculate the impact area of the instrumental seismic intensity in Wenchuan earthquake, and to compare the intensities based on strong motion observation against the instrumental seismic intensities at locations where the observation data is available. The instrumental seismic intensities were calculated for the Wenchuan Earthquake at substations in the national power grid with voltage of 110kV or higher in areas of Mianyang, Deyang, Guangyuan and Chengdu. The cumulative Gaussian distribution function was then used to fit the relationship of the curves of the damage probabilities of high-voltage electrical equipment such as transformers, voltage mutual inductors, current mutual inductors, circuit breakers, isolating switches and lightning arrester with their instrumental seismic intensities. The damage probability density distribution curve of high-voltage electrical equipment based on the instrumental seismic intensities was obtained. The results showed that: (1) In the lower seismic intensity region, the mean instrumental seismic intensity was in good agreement with the traditional seismic intensity, but there was noticeable dispersion; in regions of intensity IX and above, the instrumental intensity was lower than the seismic intensity, but there was a lower degree of dispersion. (2) Among high-voltage electrical equipment, the transformers were most vulnerable to damage and they had some damage even under lower instrumental intensity. More damage would be produced when the instrumental intensity reached VIII or above; the second most vulnerable equipment was the circuit breaker, and the damage was most likely to occur when the instrument intensity was IX or above . (3) The damage rate curves of lightning arresters, current mutual inductors, voltage mutual inductors and isolating switches were relatively close to each other and the damage probability was the highest when the instrumental intensity was about X.

Wenchuan earthquake that occurred in China in 2008 caused severe damage to a large number of electric substations. In this paper, Kriging interpolation method was used to calculate the impact area of the instrumental seismic intensity in Wenchuan earthquake, and to compare the intensities based on strong motion observation against the instrumental seismic intensities at locations where the observation data is available. The instrumental seismic intensities were calculated for the Wenchuan Earthquake at substations in the national power grid with voltage of 110kV or higher in areas of Mianyang, Deyang, Guangyuan and Chengdu. The cumulative Gaussian distribution function was then used to fit the relationship of the curves of the damage probabilities of high-voltage electrical equipment such as transformers, voltage mutual inductors, current mutual inductors, circuit breakers, isolating switches and lightning arrester with their instrumental seismic intensities. The damage probability density distribution curve of high-voltage electrical equipment based on the instrumental seismic intensities was obtained. The results showed that: (1) In the lower seismic intensity region, the mean instrumental seismic intensity was in good agreement with the traditional seismic intensity, but there was noticeable dispersion; in regions of intensity IX and above, the instrumental intensity was lower than the seismic intensity, but there was a lower degree of dispersion. (2) Among high-voltage electrical equipment, the transformers were most vulnerable to damage and they had some damage even under lower instrumental intensity. More damage would be produced when the instrumental intensity reached VIII or above; the second most vulnerable equipment was the circuit breaker, and the damage was most likely to occur when the instrument intensity was IX or above . (3) The damage rate curves of lightning arresters, current mutual inductors, voltage mutual inductors and isolating switches were relatively close to each other and the damage probability was the highest when the instrumental intensity was about X.

To achieve n-type doping in diamond, extensive investigations employing first principles have been conducted on various models of phosphorus doping and boron-phosphorus co-doping. The primary focus of this study is to comprehensively analyze the formation energy, band structure, density of states, and ionization energy of these structures. It is observed that within a diamond structure solely composed of phosphorus atoms, the formation energy of an individual carbon atom is excessively high. However, the substitution of two carbon atoms leads to the conversion of diamond into a p-type semiconductor. Upon examining the P-B co-doping structure, it is revealed that the doped impurities exhibit a tendency to form more stable cluster configurations. As the separation between the freely doped atoms and the cluster impurity structure increases, the overall stability of the structure diminishes, consequently resulting in an elevation of the ionization energy. Analysis of the electronic density of states demonstrates that the electron orbit of the B atom makes negligible contributions to the impurity levels during P-B doping.

Background: The COVID-19 outbreak has accelerated the huge difference between medical care and disease prevention in Chinese medical institutions. This study aimed to investigated the relationship between the symbiotic units, environments, models, and effects of the integration of medical and disease prevention. Methods: This cross-sectional study involved 762 employees of public hospitals in 11 cities in Zhejiang Province by random stratified sampling. We analyzed the influence paths of elements in the mechanism of integration of medical and disease prevention and the mediating effect of symbiotic models among symbiotic units, symbiotic environments, and effects for on this integration. Results: The path coefficient of symbiotic unit on the symbiosis model was 0.46 (p<.001), the path coefficient of symbiotic environment on symbiosis model was 0.52 (p<.001). The path coefficient of the symbiotic unit and environment was 0.91 (p<.001). The symbiotic models exhibited a partial mediation effect between symbiotic units and the effect of this integration. Sobel test = 3.27, β = 0.152, and the mediating effect accounted for 34.6%. Conclusions: It is suggested that Health policy-makers and public hospital managers should provide sufficient symbiotic units, establish collaborative symbiotic models, and improve the effects of integration of medical and disease prevention in public hospitals.

Background: With the trend of intelligent display, the interface design of in-vehicle HUD is an expanding research field; Methods: To solve the subjectivity and uncertainty in the optimization of HUD interface design schemes, this paper proposed a hybrid scheme evaluation and optimization method based on entropy weight and VIKOR. The entropy weight method was used to reduce the subjectivity the decision-maker's weighting and obtain the objective weight of each indicator; The VIKOR method was used to obtain the best ranking of alternative schemes, and then the optimal interface design scheme was selected; Results: The evaluation of in-vehicle HUD interface design schemes were taken as an example for verification and calculation. The results showed that this method considers the subjectivity and uncertainty of the decision-making process in the optimization of design scheme, which can effectively improve the objectivity and accuracy of the evaluation results, and provide a reference for designers to optimize interface design schemes.

Abstract In order to solve the problem that it is difficult to obtain the accurate trigger signal moment when using the time difference of UAV flight acoustic signals collected by acoustic sensors arranged in advance to locate the position of UAVs when they cannot be tracked by radar and are difficult to be observed by the human eye, an acoustic source localisation method with improved empirical modal decomposition (REMD) under an adaptive frequency window is proposed. Firstly, the collected UAV flight signals are smoothed and filtered, then the robust empirical modal decomposition (REMD) is used for IMF modal decomposition and spectral analysis of the collected signals, and a panning frequency window with variable bandwidth is introduced for corresponding frequency locking and extracting the IMFs; the GWO optimisation is used and the sliding metrics are set to determine the position of the panning frequency window automatically; finally, the extracted Finally, the extracted IMF components are reconstructed according to the criterion, and the trigger signal moments in the reconstructed IMF components are resolved and recorded, and the algorithm is used to calculate the difference between the reception moments of different sensors; for the traditional sound source localisation algorithms with a small detection range, which are prone to fall into the no-solution or false-solution, i.e., unable to achieve the localisation, a weighted least-squares-based Chan-Taylor algorithm is proposed for the localisation computation, and a weighted least-squares algorithm is proposed for the localisation computation, through the Inputting the sensor delay parameter and solving the linear equation system to get the target position information; finally, this paper verifies the robustness and performance of the design method with simulated and actual signals. The results show that the maximum positioning error is no more than 5% in an area with a side length of 15m in the measurement area. With the improved accuracy of time delay estimation, the positioning simulation results meet the positioning requirements even though the positioning error is further expanded when the measurement area is further expanded.