The fluorinated organic compounds have superior physicochemical properties than general organic compounds due to the strong C-F single bond, and widely used in medicine, biology, pesticides, and materials science. In order to gain a deeper understanding of the physicochemical properties of fluorinated organic compounds, fluorinated aromatic compounds have been investigated by various spectroscopic techniques. 2-Fluorobenzonitrile and 3-fluorobenzonitrile are important fine chemical intermediates, and their excited state S1 and cationic ground state D0 vibrational features remain unknown. In this paper, we used two-color resonance two photon ionization (2-color REMPI) and mass analyzed threshold ionization (MATI) spectroscopy to study S1 and D0 states vibrational features of 2-fluorobenzonitrile and 3-fluorobenzonitrile. The precise excitation energy (band origin) and adiabatic ionization energy were determined to be 36028 2 cm-1 and 78650 5 cm-1 for 2-fluorobenzonitrile; and 35989 2 cm-1 and 78873 5 cm-1 for 3-fluorobenzonitrile, respectively. The density functional theory (DFT) at the levels of RB3LYP/aug-cc-pvtz, TD-B3LYP/aug-cc-pvtz, and UB3LYP/aug-cc-pvtz were used to calculate the stable structures and vibrational frequencies for the ground states S0, excited state S1, and cationic ground state D0, respectively. Franck-Condon spectral simulations for transitions of S1 S0 and D0 S1 were performed based on above DFT calculations. The theoretical and experimental results are in good agreement. The observed vibrational features in S1 and D0 states are assigned according to the simulated spectra and the comparison with structurally similar molecules. Several experimental findings and molecular features were discussed in detail.

This research investigates the complex transformation of the Baltic Clean and Dirty Tankers markets from 1998 to 2023. Our study quantifies the market multifractality in two distinct periods, from 1998 to 2010 and 2010 to 2023. We compare multifractal measures of the original, surrogated, and shuffled data, which indicate high multifractality and a complex market structure influenced by temporal organization and inherent volatility. Shuffled data analysis emphasizes the critical role of temporal sequences within market behaviour. Additionally, the study delves into external factors such as regulatory changes, economic disturbances, technological innovation, and environmental concerns contributing to market complexity. A distinct shift in multifractal values between the two periods suggests an evolution from crisis-induced complexities to a market influenced by diversified and modern dynamics. Our findings offer a concise understanding of the multifractal nature of the tanker markets and how global crises can impact the markets, emphasizing the importance of considering systemic risks in freight market analysis.

Recent research has highlighted associations between sleep and microbial taxa and pathways. However, the causal effect of these associations remains unknown. To investigate this, we performed a two-sample bidirectional Mendelian randomization (MR) analysis using summary statistics of genome-wide association studies (GWAS) from 412 gut microbiome traits (N = 7,738) and GWAS studies from seven sleep-associated traits (N = 345,552 to 386577). We employed multiple MR methods to assess causality, with Inverse Variance Weighted (IVW) as the primary method. We further applied Cochran’s Q statistical analysis, MR-Egger intercept, and MR-PRESSO for heterogeneity and pleiotropy assessment, alongside a Bonferroni correction ((P

The real systems are often complex, nonlinear, and noisy in various areas including mathematics, natural science, and social science. We present the symplectic entropy (SymEn) measure as well as an analysis method based on SymEn to estimate the nonlinearity of the complex system by analyzing the given time series. The SymEn estimation is a kind of entropy based on symplectic principal component analysis (SPCA) which represent organized but unpredictable behaviors of systems. The key to SPCA is to preserve the global submanifold geometrical properties of the systems through symplectic transform in the phase space, which is a kind of the measure-preserving transforms. The capability of preserving the global geometrical characteristics makes the SymEn a test statistic to detect the nonlinear characteristics in several typical chaotic time series and the stochastic characteristic in the Gaussian white noise. The results are in agreement with findings in the approximate entropy (ApEn), the sample entropy (SampEn) and the fuzzy entropy (FuzzyEn). Moreover, the SymEn method is also used to analyze the nonlinearities of the real signals (including the EEG signals for ASD and healthy subjects, and the sound and vibration signals for the mechanical systems). The results indicate that the SymEn estimation can be taken as a measure for describing the nonlinear characteristics in the data collected from the natural complex systems.

To characterize the fecal microbiota of lactating Bactrian camels, this study employed a random selection of camels, assigning them to three groups: the first parity group, the third parity group, and the fifth parity group. The fecal microbial community of lactating camels was assessed using 16S rRNA amplicon sequencing, and the resulting library was sequenced on an Illumina NovaSeq platform. The first parity group was characterized by Verrucomicrobiaceae as a distinctive bi-omarker, whereas Clostridiaceae exhibited a similar role to the third parity group. In terms of functional analysis, the relative abundance of the Steroid biosynthesis pathway was highest in the first parity group, whereas the fifth parity group demonstrated a higher relative abundance of the Tuberculosis pathway compared to the other groups. The first parity group exhibited the greatest presence of seven types of enzymes, whereas the fifth parity group displayed the highest levels of two specific enzymes. Additionally, a positive association was observed between the relative abundance of the Steroid biosynthesis pathway and Verrucomicrobiaceae. Furthermore, the relative abundance of the Tuberculosis pathway displayed positive correlations with 14 enzymes. In conclusion, this study revealed that different parity was associated with distinct fecal microbial ecologies in lactating Bactrian camels.

The foot-mounted inertial navigation system is an important application of pedestrian navigation as it in principle does not rely any external assistance. A real-time range decomposition constraint method is proposed in this paper to combine the information of dual foot-mounted inertial navigation systems. It is well known that low-cost inertial sensors with ZUPT (zero-velocity update) and range decomposition constraint perform better than in either single way. This paper recommends that the distance of separation between the position estimates of feet-mounted inertial navigation systems be restricted in the ellipsoidal constraint which relates to the maximum step and leg height. The performance of the proposed method is studied utilizing experimental data. The results indicate that the method can effectively correct the dual navigation systems’ position over the existing spherical constraint.

Kidney disease is a significant health problem worldwide, affecting an estimated 10% of the global population. Kidney disease encompasses a diverse group of disorders that vary in their underlying pathophysiology, clinical presentation, and outcomes. These disorders include acute kidney injury (AKI), chronic kidney disease (CKD), glomerulonephritis, nephrotic syndrome, polycystic kidney disease, diabetic kidney disease, and many others. Despite their distinct etiologies, these disorders share a common feature of immune system dysregulation and metabolic disturbances. The immune system and metabolic pathways are intimately connected and interact to modulate the pathogenesis of kidney diseases. The dysregulation of immune responses in kidney diseases includes a complex interplay between various immune cell types, including resident and infiltrating immune cells, cytokines, chemokines, and complement factors. These immune factors can trigger and perpetuate kidney inflammation, causing renal tissue injury and progressive fibrosis. In addition, metabolic pathways play critical roles in the pathogenesis of kidney diseases, including glucose and lipid metabolism, oxidative stress, mitochondrial dysfunction, and altered nutrient sensing. Dysregulation of these metabolic pathways contributes to the progression of kidney disease by inducing renal tubular injury, apoptosis, and fibrosis. Recent studies have provided insights into the intricate interplay between immune and metabolic pathways in kidney diseases, revealing novel therapeutic targets for the prevention and treatment of kidney diseases. Potential therapeutic strategies include modulating immune responses through targeting key immune factors or inhibiting pro-inflammatory signaling pathways, improving mitochondrial function, and targeting nutrient-sensing pathways such as mTOR, AMPK, and SIRT1. This review highlights the importance of the interplay between immune and metabolic pathways in kidney diseases and the potential therapeutic implications of targeting these pathways.

In a vacuum tube two identical and parallel Ag-O-Cs emitters A and B (work function 0.8eV) ceaselessly emit thermal electrons at room temperature. The thermal electrons are controlled by a static uniform magnetic field so that the number of electrons migrate from A to B exceeds the one from B to A (or vice versa). The net migration of thermal electrons from A to B quickly results in a charge distribution of A charged positively and B negatively, and a potential difference between A and B emerges, enabling a continuous output current and a stable power to an external load (e.g., a resistor). Thus, the tube cools down (slightly). The (slightly) cooled tube extracts heat from ambient air, and all the heat is converted into electric energy without other effect. We believe the experiment is in contradiction to the Kelvin statement of the second law.

This study investigates the influence of expectations and trust on farmers' decisions regarding contractual choices in land transfer. The dataset used for analysis consists of 1101 households in Guizhou Province. The research focuses on two aspects: the selection between written and oral contracts, and the decision to continue the contractual relationship. The findings reveal that farmers' choices are significantly affected by their expectations and levels of trust.Specifically, when farmers' expectations regarding the land transfer process are not met, they tend to prefer written contracts over oral ones. This preference can be attributed to the greater clarity and risk reduction offered by written contracts. On the other hand, higher levels of trust increase the likelihood of farmers continuing the land transfer contract, as trust fosters a sense of confidence and security in the ongoing relationship.Interestingly, trust also plays a moderating role. Farmers who have aligned expectations and high levels of trust are more inclined to opt for oral contracts. This preference for oral contracts can be attributed to their flexibility and emphasis on interpersonal relationships, allowing for better adaptation to the changing dynamics of land transfer.These findings contribute to a deeper understanding of the factors influencing farmers' decision-making processes regarding contractual choices in land transfer. They provide valuable insights for policymakers involved in land transfer, enabling them to optimize policies and facilitate farmers' decision-making processes.

At present paper, we aim to study the long-time behavior of a stochastic semi-linear degenerate parabolic equation on bounded or unbounded domain and driven by a nonlinear noise and defined. Since the theory of pathwise random dynamical systems can not be applied directly to the equation with nonlinear noise, first, we establish the existence of weak pullback mean random attractors for the equation by applying the theory of mean-square random dynamical systems; then, we prove the existence of (pathwise) pullback random attractors for the Wong-Zakai approximate system of the equation. In addition, we establish the upper semicontinuity of pullback random attractors for the Wong-Zakai approximate system of the equation under consideration driven by a linear multiplicative noise.

The 2019 novel coronavirus (2019-nCoV) causes novel coronavirus pneumonia (NCP). Given that approved drug repurposing becomes a common strategy to quickly find antiviral treatments, a collection of FDA-approved drugs can be powerful resources for new anti-NCP indication discoveries. In addition to synthetic compounds, Chinese Patent Drugs (CPD), also play a key role in the treatment of virus related infections diseases in China. Here we compiled major components from 38 CPDs that are commonly used in the respiratory diseases and docked them against two drug targets, ACE2 receptor and viral main protease. According to our docking screening, 10 antiviral components, including hesperidin, saikosaponin A, rutin, corosolic acid, verbascoside, baicalin, glycyrrhizin, mulberroside A, cynaroside, and bilirubin, can directly bind to both host cell target ACE2 receptor and viral target main protease. In combination of the docking results, the natural abundance of the substances, and botanical knowledge, we proposed that artemisinin, rutin, glycyrrhizin, cholic acid, hyodeoxycholic acid, puerarin, oleanic acid, andrographolide, matrine, codeine, morphine, chlorogenic acid, and baicalin (or Yinhuang Injection containing chlorogenic acid and baicalin) might be of value for clinical trials during a 2019-nCov outbreak.

Cost-efficient catalyst for hydrogen evolution reaction (HER) and methanol oxidization reaction (MOR) is of great importance for industrial application. The alloying of platinum with cheap transition metal offers a great opportunity to reduce cost and enhance the electro-catalytic performance. Herein, we report a simple and green route to synthesize porous Pt-Cu catalysts, where Pt-Cu solid particles were first produced by using cuprous chloride (CuCl) nanoparticles as the template, followed by a dealloying treatment to obtain final porous product. The porous alloy nanoparticles show higher catalytic activity and superior stability for HER and methanol oxidation reaction, which is beneficial from the porous structure and synergetic effect between Pt and Cu.

Fresh water is valuable nonrenewable resource and plays an important role of maintaining economic and social development. Condisering its large population and consumption potential, water resources deficit will certainly impede basic industries sustainable development of China in the near future. Application of sewage irrigation, to some extent, was regarded as an alternative way to solve the problem of agricultural irrigation water shortage in some areas (such as North China). However, accompanied with extensive implementation of sewage irrigation, some problems on sewage irrigation in agriculture are gradually obvious, especially serious pollution and destruction for farmland. In this paper, the effects of sewage irrigation on soil physical (soil bulk density, soil resistance to penetration and field capacity), chemical (pH, soil organic matter, nitrogen, phosphrous, patassium, heavy metal and organic pollutants) and biological characteristics (soil microorganism and enzyme activities) of farmland in China were systematically reviewed on the base of the current utilization status of China’s farmland sewage irrigation and some feasible suggestions were put forward to the development prospect for the future. This review will be beneficial for promoting healthy development of sewage irrigation and providing theoretical support for reclamation and high efficiency of effluents in China.

A spinning gyroscope precesses about the vertical due to a torque acting upon the wheel. The torque is generated by the shift of moment of force by gravity and it points to the vertical instead of the tangential direction of precession. This intuition offers an alternative and straightforward view of precession dynamics in comparison with the literature. It also presumes a dynamic balance of momentum between circular motions of the wheel spin and precession. Accordingly, the gyroscopic dynamics is then applied to the study of galactic motion of the solar system in space and the Galactic mass is calculated with the inclusion of gyroscopic effect of the solar planets. Results indicate that the gyroscopic effect of Mercury orbiting around the Sun can increase the calculated Galactic mass by 23% in comparison with the result obtained by the classic approach.

Mesoporous silica nanoparticles (MSNs) can be used as carrier materials for the controlled release of pesticides while reducing their negative environmental impact. In this study, we screened an active ingredient, p-cymene (PC), with an excellent inhibitory effect on rice bacterial blight. Subsequently, the PC was successfully loaded onto MSNs via physisorption(PC@MSNs). PC@MSNs, characterized by a regular spherical shape, smooth surface, and an MSN average size of 262.9 nm, achieved an 8.6 % drug loading capacity. The release kinetics of the PC from the PC@MSNs demonstrated a sustained release (288 h) pattern influenced by drug diffusion. The efficacy of the PC@MSNs against Xanthomonas oryzae pv. Oryzae paralleled those of PC. Acute toxicity assays re-vealed that the PC@MSNs were less toxic to aquatic life (LC50=257.867 mg/L) and that the formu-lation showed no adverse effects on rice seedling growth. In summary, these results suggest that PC@MSNs can broaden PC's application scope in managing rice diseases.

A self-consistent charge density-functional tight-binding method combined with molecular dynamics simulations is employed to reveal the effect of polymorph on the thermal decomposition stability of 1,1-Diamino-2,2-Dinitroethylene (FOX-7). Two types of heating, constant temperature heating and temperature-programmed heating, are adopted. Potential evolution indicates that γ-FOX-7 possesses the lowest thermal stability, as it is closer to the decomposition state. Crystal form has an important influence on the thermal decomposition of FOX-7, resulting in different decomposition rates and initial reactions. In general, β- and γ-FOX-7 always decompose more completely than α-FOX-7. This work emphases the importance of polymorph dependent initial decay of an energetic polymorphic compound once heated in a volume constrained condition.

Software fault prediction is the very consequent research topic for software quality assurance. Data driven approaches provide robust mechanisms to deal with software fault prediction. However, the prediction performance of the model highly depends on the quality of dataset. Many software datasets suffers from the problem of class imbalance. In this regard, under-sampling is a popular data pre-processing method in dealing with class imbalance problem, Easy Ensemble (EE) present a robust approach to achieve a high classification rate and address the biasness towards majority class samples. However, imbalance class is not the only issue that harms performance of classifiers. Some noisy examples and irrelevant features may additionally reduce the rate of predictive accuracy of the classifier. In this paper, we proposed two-stage data pre-processing which incorporates feature selection and a new Rough set Easy Ensemble scheme. In feature selection stage, we eliminate the irrelevant features by feature ranking algorithm. In the second stage of a new Rough set Easy Ensemble by incorporating Rough K nearest neighbor rule filter (RK) afore executing Easy Ensemble (EE), named RKEE for short. RK can remove noisy examples from both minority and majority class. Experimental evaluation on real-world software projects, such as NASA and Eclipse dataset, is performed in order to demonstrate the effectiveness of our proposed approach. Furthermore, this paper comprehensively investigates the influencing factor in our approach. Such as, the impact of Rough set theory on noise-filter, the relationship between model performance and imbalance ratio etc. comprehensive experiments indicate that the proposed approach shows outstanding performance with significance in terms of area-under-the-curve (AUC).

The traditional receiver employs scalar tracking loops, resulting in degraded navigation performance in weak signal and high dynamic scenarios. An innovative design of a vector tracking receiver based on nonlinear Kalman filter (KF) tracking loops is proposed in this paper, which combines the strengths of both vector tracking and KF tracking loops. Firstly, a comprehensive description of the vector tracking receiver model is presented, and unscented Kalman filter (UKF) is applied to nonlinear tracking loop. Secondly, to enhance the stability and robustness of the KF tracking loop, we introduce square root filtering and an adaptive mechanism. The tracking loop based on square root UKF (SRUKF) can dynamically adjust its filtering parameters based on signal noise and feedback Doppler error. Finally, the proposed method is implemented on a software-defined receiver (SDR), and the field vehicle experiment demonstrates the superiority of this method over other receivers in complex dynamic environments.

The integration of metal nanoparticles and solid carriers can achieve ideal stability, high load and good conductivity. In this work, copper nanoparticles (Cu NPs) were sequentially deposited on a cobalt metal-organic framework (Co-MOF) by bonding with exposed imino groups, followed by a reduction reaction to prepare a new Cu@Co-MOF composite. Cu@Co-MOF acts as a non-enzymatic electrochemical sensor to detect glucose (Glu) in an alkaline medium. The composite working electrode of Cu@Co-MOF/GCE (GCE = glassy carbon electrode) improves the electrocatalytic activity for Glu oxidation. Cu@Co-MOF/GCE shows excellent electrocatalytic performances in Glu concentration ranging 0.005~1.8 mmol∙L⁻¹ (mM): the sensitivities are 282.89 μA∙mM⁻¹∙cm⁻² in 0.005-0.4 mM Glu and 113.15 μA∙mM⁻¹∙cm⁻² in 0.4-1.8 mM Glu respectively with low detection limit of 1.6 μM (S/N = 3) and high selectivity and stability.

The recent outbreak of coronavirus disease 2019 caused by the new coronavirus, SARS-CoV-2, has become an international emergency. Since there is no effective therapy for the treatment of this disease, drugs or vaccine that can prevent or cure the SARS-CoV-2 infection are urgently needed. The viral 3-chymotrypsin-like cysteine protease (3CLpro), which plays a key role in the replication of coronavirus, is a potential drug target for the development of anti-SARS-CoV-2 drugs. With the crystal structure of 3CLpro, we performed virtual screening from a small chemical library of a Traditional Chinese Medicine recipe- FuFang Zhenzhu Tiaozhi (FTZ). Five compounds with the best scores were screened and could be considered as potential hit compounds to be investigated further with bioassays for their anti-virus effects.

Translation is spatiotemporally regulated and ER-associated mRNAs are generally in efficient translation. It is unclear whether the ER-associated mRNAs are deadenylated or degraded on the ER surface in situ or in the cytosol. Here, we showed that ER possessed active deadenylases, particularly the poly(A)-specific ribonuclease (PARN), in common cell lines and mouse tissues. Consistently, purified recombinant PARN exhibited a strong ability to insert into the Langmuir monolayer and liposome. ER-anchored PARN was found to be able to reshape the poly(A) length profile of the ER-associated RNAs by suppressing long poly(A) tails without significantly influencing the cytosolic RNAs. The shortening of long poly(A) tails did not affect global translation efficiency, suggesting that the non-specific action of PARN towards long poly(A) tails was beyond the scope of translation regulation on the ER surface. Transcriptome sequencing analysis indicated that the ER-anchored PARN trigged the degradation of a small subset of ER-enriched transcripts. The ER-anchored PARN modulated the translation of its targets by redistributing ribosomes to heavy polysomes, suggesting that PARN may play a role in dynamic ribosome reallocation. During DNA damage response, MK2 phosphorylated PARN-Ser557 to modulate PARN translocation from the ER to cytosol. By promoting the decay of ER-associated MDM2 transcripts with low ribosome occupancy, the ER-anchored PARN modulated DNA damage response and thereby cell viability. These findings revealed that a highly regulated communication between mRNA degradation rate and translation efficiency is present on the ER surface in situ and that PARN may contribute to this communication by modulating the dynamic ribosome reallocation between transcripts with low and high ribosome occupancies.

To study the influence of Latin dance and Tai Chi on knee joint proprioception and balance. Method: All experiments were performed in the Beijing Normal University School of Physical Education and Sport Biomechanics Laboratory. An isokinetic test system (Biodex system 4, BS4) and a balance testing system (Biodex Balance System, BBS)from the United States Biodex medical system were used to test related indexes. Results: In the LOS test, the overall score of Latin group is much better than sedentary group. In the ASL test, Latin group have a better balance ability in anterior and posterior direction and overall score than sedentary group(p＜0.05); TAI CHI group have a better balance ability than sedentary group in anterior and posterior direction(p＜0.05)and right and left direction (p＜0.01). When the knee joint was at 15, 30, and 45degree positions, the Tai Chi exercise group was much better than sedentary group (P < 0.05), and the 45 degree position in the Tai Chi group was much better than that in the Latin dance group (P < 0.01).When the knee joint was at the 30 degree position, the quadriceps force sense was significantly better in the Tai Chi group than in the Latin dance and sedentary groups. In a test of the four angles, the hamstring force sense in the Tai Chi exercise group was obviously better than that in the sedentary group (P < 0.05); at the 15 degree position, the Tai Chi group was significantly better than the Latin group (P < 0.05); and at 30 degree position, the hamstring force sense of the Latin group was obviously better than that of the sedentary group (P < 0.05).

The organic coating of bridge steel girders is subjected to physical scratches, corrosion, and aging in natural weathering. The breakdown of the coating may cause serviceability and safety problems if left unnoticed. A hyperspectral imaging method is proposed to detect the condition of steel coatings based on coating-responsive features in reflectance spectra. A field test was conducted on the real-world bridge which shows obvious signs of degradation. The hyperspectral signature enables an assessment of the coating health and defect severity. The results indicated that the coating scratch can be effectively located in the domain of a hyperspectral image and the scratch depth can be determined by mapping a scratch depth indicator (SDI=R532nm / R641nm). Rust sources and products in steel girders can be identified by the unique spectral signatures and the rust stains (and thus stain areas) scattered on the coating can be pinpointed at pixel level by the corrosion rust indicators. The chemical integrity of a topcoat is demonstrated by the short-wave infrared spectroscopy and the topcoat degradation can be evaluated by the absorption at 8000 cm-1 and 5850 cm-1.

Ligand-based virtual screening (LBVS) is a promising approach for rapid and low-cost screening of potentially bioactive molecules in the early stage of drug discovery. Compared with traditional similarity-based machine learning methods, deep learning frameworks for LBVS can more effectively extract high-order molecule structure representations from molecular fingerprints or structures. However, the 3D conformation of a molecule largely influences its bioactivity and physical properties, and has rarely been considered in previous deep learning-based LBVS methods. Moreover, the relative bioactivity benchmark dataset is still lacking. To address these issues, we introduce a novel end-to-end deep learning architecture trained from molecular conformers for LBVS. We first extracted molecule conformers from multiple public molecular bioactivity data and consolidated them into a large-scale bioactivity benchmark dataset, which totally includes millions of endpoints and molecules corresponding to 954 targets. Then, we devised a deep learning-based LBVS called EquiVS to learn molecule representations from conformers for bioactivity prediction. Specifically, graph convolutional network (GCN) and equivariant graph neural network (EGNN) are sequentially stacked to learn high-order molecule-level and conformer-level representations, followed by attention-based deep multiple-instance learning (MIL) to aggregate these representations and then predict the potential bioactivity for the query molecule on a given target. We conducted various experiments to validate the data quality of our benchmark dataset, and confirmed EquiVS achieved better performance compared with 10 traditional machine learning or deep learning-based LBVS methods. Further ablation studies demonstrate the significant contribution of molecular conformation for bioactivity prediction, as well as the reasonability and non-redundancy of deep learning architecture in EquiVS. Finally, a model interpretation case study on CDK2 shows the potential of EquiVS in optimal conformer discovery. The overall study shows that our proposed benchmark dataset and EquiVS method have promising prospects in virtual screening applications.

The composite post insulator composed of a large diameter mandrel and flange pressed by one-time integral pultrusion has high strength and good toughness, widely used in the existing flexible converter valve. For constructing the finite element model of the crimped post insulator, most of the flange surface and the mandrel surface are directly connected, making the simulation model's stiffness deviate from the actual model and the model distortion. Based on this, this study proposes a new finite element simplified model of crimped composite post insulator based on Multi-Point Constraints (MPC), which accurately simulates the crimping area of man-drel and flange in engineering practice. It verifies the model's reliability through static tests and characteristic vibration tests. The results show that the difference between the finite element simulation and test results is within 5 %. The finite element modeling method based on MPC local constraints is very reliable in applying crimped composite post insulators. Based on the proposed model, the influence of flange height and thickness on the mechanical properties of composite post-insulators is further explored. The results show that the influence of flange height on mechanical properties can be ignored when the height of the insulator stiff-ener ( non-press common area ) is constant. Within the allowable thickness range of the flange crimping process, the increase in flange thickness will significantly reduce the maximum bend-ing stress of the insulator and increase its safety margin. It provides a good design idea for the design of crimping composite insulators.

The prevalence of antiviral drugs (AVTs) has seen a substantial increase in response to the COVID-19 pandemic, leading to heightened concentrations of these pharmaceuticals in wastewater systems. The hydrophilic nature of AVTs has been identified as a significant factor contributing to the low degradation efficiency observed in wastewater treatment plants. This characteristic often necessitates the implementation of additional treatment steps to achieve complete degradation of AVTs. Semiconductor-based photocatalysis has garnered considerable attention due to its promising potential in achieving efficient degradation rates and subsequent mineralization of pollutants, leveraging the inexhaustible energy of sunlight. However, in recent years, there have been few comprehensive reports that have thoroughly summarized and analyzed the application of photocatalysis for the removal of AVTs. This review commences by summarizing the types and occurrence of AVTs. Furthermore, it places a significant emphasis on delivering a comprehensive summary and analysis of the characteristics pertaining to the photocatalytic elimination of AVTs. Ultimately, the review sheds light on the identified research gaps and key concerns, offering invaluable insights to steer future investigations in this field.

Single image deraining (SID) has shown its importance in many advanced computer vision tasks. Though many CNN based image deraining methods have been proposed, how to effectively remove raindrops while maintaining background structure remains a challenge that needs to be overcome. Most of the deraining work focuses on removing rain streaks, but in heavy rain images, the dense accumulation of rainwater or the rain curtain effect significantly interferes with the effective removal of rain streaks, and often introduces some artifacts that make the scene more blurry. In this paper, we propose a new network structure R-PReNet for single image deraining with good background structure maintaining. This framework fully utilizes the cyclic recursive structure of PReNet. Moreover, we introduce residual channel prior (RCP) and feature fusion modules for better deraining performance by focusing on background feature information. Compared with the previous methods, our method has significantly improvement effect on the rainstorm image with the artifacts removing and good visual detail restoring.

Previous studies have mostly examined how sustainable cities try to promote non-motorized travel by creating a walking-friendly environment. Such existing studies provide little research that identifies how the built environment affects pedestrian volume in high-density areas. This paper presents a methodology that combines person correlation analysis, stepwise regression, and principal component analysis for exploring the internal correlation and potential impact of built environment variables. To study this relationship, cross-sectional data in the Melbourne central business district were selected. Pearson’s correlation coefficient confirmed that visible green index and intersection density were not correlated to pedestrian volume. The results from stepwise regression showed that land-use mix degree, public transit stop density, and employment density could be associated with pedestrian volume. Moreover, two principal components were extracted by factor analysis. The result of the first component yielded an internal correlation where land-use and amenities components were positively associated with the pedestrian volume. Component 2 presents parking facilities density, which negatively relates to the pedestrian volume. Based on the results, existing street problems and policy recommendations were put forward to suggest diversifying community service within walking distance, improving the service level of the public transit system, and restricting on-street parking in Melbourne.

Vanadium titano-magnetite is a significant resource in China, and in this study, we characterize its isothermal reduction mechanisms in the mixture of H₂, CO, and N₂ where the variables considered here include reduction time, reduction temperature, gas composition, and pellet size. The kinetics of the reduction process are mainly studied, which follows a shrinking core model. The results indicate that the reduction degree of oxidized VTM pellets increases with the increase of reduction time, reduction temperature but decreases with the increase of pellet size. Moreover, we found that an increase of H₂/(H₂+CO) ratio induces an increase of the reduction degree. Then the transformation of main Ti-bearing mineral phases is discussed, and the most probable reaction mechanism is revealed. In the whole reduction process, the kinetic results confirm the existence of an early stage and a latter stage, which are controlled by interface chemical reaction and diffusion, respectively. Furthermore, the results show that the diffusion-control step can be observably shortened with the decrease of pellet size because a thinner product layer is formed during the reduction process. Our study thus provides a valuable technical basis on the VTM industrial application.

Shale gas content is the key parameter for shale gas potential evaluation and favorable area prediction. Therefore, it is very important to determine shale gas content accurately. Generally, we use the USBM method for coal reservoirs to calculate gas content of shale reservoirs. However, shale reservoirs are different from coal reservoirs in depth, pressure, core collection, etc. This method would inevitably cause problems. In order to make the USBM method more suitable for shale reservoir, an improved USBM method is put forward on the basis of systematic analysis of core pressure history and temperature history during shale gas desorption. The improved USBM method modifies the calculation method of the lost time, and determines the temperature balance time of water heating. In addition, we give the calculation method of adsorption gas content and free gas content, especially the new method of calculating the oil dissolved gas content and water dissolved gas content which are easily neglected. We used the direct method (USBM and the improved USBM) and the indirect method (adsorption gas, free gas and dissolved gas) to calculate the shale gas content of 16 shale samples of the Triassic Yanchang Formation in the Southeastern Ordos Basin, China. The results of the improved USBM method show that the total shale gas content is high, with an average of 3.97 m³/t, and the lost shale gas content is the largest proportion with an average of 62%. The total shale gas content calculated by the improved USBM method is greater than that of the USBM method. The results of the indirect method show that the total shale gas content is large, with an average of 4.11 m³/t, and the adsorption shale gas content is the largest proportion with an average of 71%. The oil dissolved shale gas content which should be taken attention accounts for about 7.8%. The relative error between the improved USBM method and indirect method is much smaller than that between USBM method and indirect method, which verifies the accuracy of the improved USBM method.

As one of the fastest-growing new energy sources, wind power technology has attracted widespread attention from all over the world. In order to improve the quality of wind power generation, wind speed prediction is an indispensable task. In this paper, an error correction based Variational Mode Decomposition and Broad Learning System (VMD-BLS) hybrid model is proposed for wind speed prediction. First, the wind speed is decomposed into multiple components by the VMD algorithm, and then an ARMA model is established for each component to find the optimal number of sequence divisions. Second, the BLS model is used to predict each component, and the prediction results are summed to obtain the wind speed forecast value. However, in some traditional methods, there is always time lag, which will reduce the forecast accuracy. To deal with this, a novel error correction technique is developed by utilizing BLS. Through verification experiment with actual data, it proves that the proposed method can reduce the phenomenon of prediction lag, and can achieve higher prediction accuracy than traditional approaches, which shows our method’s effectiveness in practice.

The global usage of veterinary antibiotics is significant. These antibiotics can be released into the aquatic environment and exert toxic effects on non-target organisms. To explore the physiological effects of tetracycline antibiotics on aquatic life, the growth characteristics of and toxin release from the cyanobacterium Microcystis aeruginosa (M. aeruginosa) were studied. Results showed that the toxicity order of the three target antibiotics was TC (tetracycline) > CTC (chlortetracycline hydrochloride) > OTC (oxytetracycline) in terms of inhibition occurrence time and the EC₁₀ and EC₂₅ values. Further, the target antibiotics regulated the production of MC-LR (microcystin-LR) to different degrees. CTC destroyed the M. aeruginosa cells and resulted in a decreased MC-LR release but stimulated the ability to synthesise MC-LR. OTC had a relatively weaker toxicity compared with CTC, while TC was the most toxic among the three antibiotics. Therefore, TC is friendly to the aquatic environment because it simultaneously reduced the intracellular and extracellular MC-LR content. These results aid our understanding of the effects of tetracycline antibiotics on Microcystis aeruginosa, which is important for environmental evaluation and protection. These results are also helpful for guiding the application of veterinary antibiotics in agricultural settings.

In the paper, the authors find closed forms for derangement numbers in terms of the Hessenberg determinants, discover a recurrence relation of derangement numbers, present a formula for any higher order derivative of the exponential generating function of derangement numbers, and compute some related Hessenberg and tridiagonal determinants.

Novel 1,2,3-triazole compounds 3–4 were synthesised via the regioselective addition and cyclization reaction of 1,1-enediamines (EDAMs) 1 with p-methylbenzenesulfonyl azide (TsN₃) 2 in 1,4-dioxane at refluxing for 5 hours. As a result, 1,2,3-triazoles 3–4 can be easily and efficiently obtained via catalyst-free click chemistry. The reactions have some advantages such as metal-free catalyst, excellent yield, inexpensive raw materials, and convenient final treatment.

Measuring and predicting Carbon Emission (CE) is important to enabling the main culprit of various urgent environmental issues including global warming. However, prior studies did not fully incorporate the impact of micro-level urban streetscapes, which might lead to biased prediction of urban CE. To fill the gap, we developed an effective framework to predict residential CE in urban areas from widely existing and publicly available street-view images (SVI) using machine learning. First, we used a semantic segmentation algorithm to classify more than 30 streetscape elements from SVI images to describe the built environment whose features might affect residential and transportation CE. Second, based on the streetscapes quantified, we trained a 10-fold cross-validation method with various machine learning models to predict the CE at the 1KM grid level using CE data from the PlanetData. We found first, built environment features such as sidewalks, roads, fences, buildings, and walls are significantly correlated with the residential CE. Second, the presence of buildings and subtle streetscape features (e.g., walls, fences) indicates higher-density residential areas which are related to more residential CE. Third, vegetation (e.g., trees and grass) are reversely related to residential CE. Our findings shed light on the feasibility of using a single and open data source (i.e., the SVI) to effectively model neighborhood-level CE for regions across diverse urban forms. Our framework is useful for urban planners to inform new town development and urban regeneration towards the low CE goals.

Background: Atypical teratoid/rhabdoid tumor (AT/RT) is an uncommon and aggressive pediatric central nervous system neoplasm. However, a universal clinical consensus or reliable prognostic evaluation system for this malignancy is lacking. Our study aimed to develop a risk model based on comprehensive clinical data to assist in clinical decision-making. Methods: We conducted a retrospective study by examining data from the Surveillance, Epidemiology, and End Results (SEER) repository, spanning 2000 to 2019. The external validation cohort was sourced from the Children's Hospital Affiliated to Chongqing Medical University, China. To discern independent factors affecting overall survival (OS) and cancer-specific survival (CSS), we applied Least Absolute Shrinkage and Selection Operator (LASSO) and Random Forest (RF) regression analyses. Based on these factors, we structured nomogram survival predictions and initiated a dynamic online risk-evaluation system. To contrast survival outcomes among diverse treatments, we used propensity score matching (PSM) methodology. Molecular data with the most common mutations in AT/RT were extracted from the Catalogue of Somatic Mutations in Cancer (COSMIC) database. Results: The annual incidence of AT/RT showed an increasing trend (APC, 2.86%; 95% CI:0.75-5.01). Our prognostic study included 316 SEER database participants and 27 external validation patients. The entire group had a median OS of 18 months (range 11.5 to 24 months) and median CSS of 21 months (range 11.7 to 29.2). Evaluations involving C-statistics, DCA, and ROC analysis underscored the distinctive capabilities of our prediction model. An analysis via PSM highlighted that individuals undergoing triple therapy (integrating surgery, radiotherapy, and chemotherapy) had discernibly enhanced OS and CSS. The most common mutations of AT/RT identified in the COSMIC database were SMARCB1, BRAF, SMARCA4, NF2, and NRAS. Conclusions: In this study, we devised a predictive model that effectively gauges the prognosis of AT/RT and briefly analyzed its genomic features, which might offer a valuable tool to address existing clinical challenges.

Synthesis of ZSM-5 zeolite from OSDA-free systems has been a very interesting alternative method because it can avoid the usage of organic templates and consequent calcination step. However, in opened reports, organic substance such as alcohol is more or less involved. In the present work, a calcined commercial ZSM-5 zeolite was used as a seed, sodium aluminate as an aluminum source, silica sol as a silicon source, which ensures that there is no any organics (template) in the synthesis system, and polycrystalline ZSM-5 aggregates consisting of rod-like nanocrystals are successfully prepared in a completely OSDA-free system. The effects of seed (chemical component, dosage) and crystallization conditions on the synthesis of ZSM-5 were systematically investigated. The results show that highly crystallinity ZSM-5 aggregate consisting of primary nano-sized crystals with a size of less than 100 nm can be yielded from a gel precursor with 5.6 wt.% seed after hydrothermal treatment for 48 h. The results also shows that the chemical composition of the seeds had little effect on the topological structure and pore structure of the synthesized samples, but the seed with a low Si/Al ratio is more conducive to the rapid crystallization of zeolite and to the improvement of the acid, especially the strong acid centers of the catalyst.

The base excitation of mechanical equipment can result in pipeline system vibration which seriously affects the safe operation of the equipment. Particle damping technology is based on the particle collision dissipation principle to realize the structural vibration energy dissipation. This paper introduces the particle damping method into the vibration control of pipeline system. A particle damper has been designed for the structural characteristics of the pipeline. The influence of the material and structure of the pipeline particle damper, the external excitation and other parameters on the energy dissipation characteristics of particle damping are revealed. The energy dissipation mechanism of the pipeline particle collision damper under various parameter is analyzed. A pipeline vibration reduction test system with particle damping has been established. The effects of different excitation conditions, damper materials and number of unit structures of particle damper on the vibration damping effect of pipeline systems are investigated comparatively. The influence of damper parameters on the vibration suppression of pipeline system is obtained. The research in this paper can provide technical references for vibration suppression of pipeline systems.

Multi-sensor data fusion of E-tongue and E-nose can provide a more comprehensive and more accurate analysis results. However, it also brings some redundant information, it is a hot issue to reduce the feature dimension for pattern recognition. In this paper, the taste-olfactory data fusion based on E-tongue and E-nose combined with Support Vector Machine (SVM) was used to classify five different beers. First, the taste and olfactory feature information were obtained based on E-tongue and E-nose. Second, the original feature data of single system were fused, then Principal Component Analysis (PCA) was applied to extract principal components, Genetic Algorithm-Partial Least Squares (GA-PLS) was used to select the characteristic variables, 20 subsets were generated with those variables based on the best Variable Importance of Projection (VIP) score. Finally, the classification models based on SVM were established, also c and g of SVM were calculated by Grid Search (GS), Genetic Algorithm (GA), and Particle Swarm Optimization (PSO), the classification results of all subsets were obtained. The results showed that the classification accuracy using data fusion was much higher over single E-tongue and single E-nose, and the variable selection method by VIP had the best classification performance in #12 subset coupled with GA-SVM.

To address the trajectory tracking issue for quadrotors working under the influence of external disturbances, a control scheme is designed for position and attitude trajectory tracking. Firstly, the quadrotor dynamic model is derived for control design. Secondly, adaptive integral backstepping control (AIBS) is employed in the position loop in which adaptive estimation is used to estimate the upper bounds of disturbances. Subsequently, a new adaptive backstepping fast nonsingular integral terminal sliding mode control (ABFNITSM) is proposed to follow desired Euler angles. The intro-duction of fast nonsingular terminal sliding mode and integral element is to realize fast convergence and accurate tracking. Dead zone technique is applied to minimize estimation errors. Besides, a saturation function is utilized to eliminate chattering phenomenon. Finally, simulation experiments are conducted under the Simulink environment. The proposed control is verified by comparing it with traditional integral terminal sliding mode control (ITSM) and integral backstepping control (IBS).

Water area segmentation in remote sensing is of great importance for flood monitoring. To overcome some challenges in this task, we construct the Water Index and Polarization Information (WIPI) multi-modality dataset and propose a multi-Modality Fusion and Gated multi-Filter U-Net (MFGF-UNet) convolutional neural network. The WIPI dataset enhances the water information and reduces the data dimension. In particular, the Cloud-Free label provided in the database effectively mitigates the issue of scarcity of labeled samples Since a single form or uniform kernel size cannot handle the variety in size and shape of water bodies, we proposed the gated multi-filter inception (GMF-Inception) module in our MFGF-UNet. Moreover, we utilize the attention mechanism by introducing the Gated Channel Transform (GCT) skip connection and integrating GCT into GMF- Inception to further improve model performance. Extensive experiments on three benchmarks, including WIPI, Chengdu and GF2020 datasets demonstrate that our method achieves favorable performance with lower complexity and better robustness against six competing approaches. For example, on WIPI, Chengdu and GF2020 datasets, the proposed MFGF-UNet model achieves F1 of 0.9191, 0.7410, and 0.8421, respectively, which average F1 on three datasets is 0.0045 higher than the U-Net model and reduces 62% average GFLOPs. New WIPI dataset, code and trained models have been released on GitHub

Jellyfish search (JS) algorithm impersonates the foraging behavior of jellyfish in the ocean. It is a new developed meta-heuristic algorithm that solves complex and real world optimization problems. The global explore capability and robustness of JS are strong, but JS still has great development space in solving complex optimization problems with high dimensions and multiple local optima. Therefore, an enhanced jellyfish search (EJS) algorithm is developed in this study, and three improvements are made: (i) By adding sine and cosine learning factors, the jellyfish can learn from both random individual and best individual during Type B motion in swarm to enhance the optimization capability and convergence speed; (ii) Adding local escape operator can skip local optimal trap and boost the exploitation ability of JS; (iii) Opposition-based learning operator and quasi-opposition learning operator can increase and strengthen the population distribution more diversified, and better individuals are selected from present and new opposition-solution to participates in the next iteration, which can boost the solution’s quality, meanwhile convergence speed is fasted and its precision is increased. In addition, the performance contrast of the developed EJS and some previous outstanding and advanced methods are evaluated on CEC2017, CEC2019 test suite and six real engineering example of case. It is demonstrated that EJS algorithm escaped the trap of local optimum, enhanced the solution’s quality and the calculation speed. What’s more, the practical engineering applications of EJS algorithm also verify its superiority and effectiveness in solving both constrained and unconstrained optimization problems, and it stretched one’s mind for solving such optimization problems.

In recent years, frequent occurrences of low temperature disasters due to global climate change have significantly impacted the normal growth of crops. Research has indicated that inorganic selenium (which is more toxic) can not only enhance the effects of low temperature stress but also increase selenium content on plants; however, there is a scarcity of studies investigating the impacts of organic selenium and nano-selenium on crops. In order to investigate whether organic selenium and nano-selenium can enhance low-temperature tolerance and increase selenium content in pak choi (Brassica chinensis var. pekinensis. cv. ‘Suzhouqing’), different concentrations (0, 5, 10, 20 mg L-1) of exogenous selenium were applied in this experiment to assess their effects on plant growth, nutritional quality and antioxidant properties. RNA-Seq technology was used to sequence the transcriptome of the leaves. Based on the transcriptome data, a Weighted Gene Co-expression Network Analysis (WGCNA) was employed to construct a network that associates with physiological traits related to stress resistance. Two highly correlated gene co-expression modules were identified, and within them, nine hub genes associated with endocytosis, antioxidant stress, absorption, transport, and metabolism of selenium were discovered. The results indicated that the beneficial effects on yield and total selenium content under low temperature were attributed to (1) protection of photosynthetic pigments for enhancing photosynthetic capacity by the up-regulation of LHca2, LHcb1, LHca1, LHcb4 in KEGG pathway: photosynthesis-antenna proteins; (2) activation of antioxidant system for efficient ROS homeostasis such as SOD, POD and CAT by the genes such as Superoxide dismutase, Monodehydroascorbate and (3) selenium absorption by endocytosis, seleninum transportation by ABC transporter gene family and selenium metabolism related genes such as Cysteine synthase, Glutaredoxin. These findings provide a foundation for further investigation into the molecular mechanisms underlying the effects of organic selenium and nano-selenium on cyanochloride production at low temperatures.

With the advancement of next generation sequencing in past several years, a rising number of non-coding RNAs have been found as new actors to regulate gene expression. Non-coding RNAs not only play important roles in carcinogenesis, but also affect the clinical treatment strategies. They have been proved to be deeply correlated with chemoresistance in several cancers. Ovarian cancer is the leading cause of death in gynecological malignancy, with low 5-year survival rate. Most patients are identified when they have late-stage disease. This review mainly makes a compilation of the most relevant research literature in this field with the purpose of shedding light on the relation between ncRNAs and chemoresistance in ovarian cancer.

Copper mine tailings are the residual products after the purification of precious copper from copper ores, and their storage can create numerous environmental problems. Many researchers have used copper mine tailings for preparation of geopolymer. This paper studies the enhancement of the cementitious activity of copper mine tailings in geopolymer system. First, copper mine tailings are activated through a mechanical grinding activation. Afterward, the mechanically activated copper mine tailings are further processed through thermal activation and alkaline roasting activating. The cementitious activity index of copper mine tailings is characterized through the degree of concentration of alkali leaching silicon and aluminum. It was observed that the Si and Al alkali leaching concentration of mechanical activated tailings was increased by 26.03% and 93.33%, respectively. The concentration of Si and Al was increased by 54.19% and 119.92%, respectively. For alkaline roasting activating, roasting time, temperature and (C/N ratio) were evaluated through the orthogonal test, and the best condition was activation for 120 min at 600℃ with C/N ratio is 5:1. In this study, the SEM, XRD and IR analysis show that mechanically activation, thermal activation and alkaline roasting activating can improve the cementitious activity index of copper mine tailings.

The next generation of wireless and mobile networks will have to handle a significant increase in traffic load compared to the actual one. This situation calls for novel ways to increase spectral efficiency. Therefore in this paper, we propose a wireless spectrum hypervisor architecture that abstracts a radio frequency (RF) front-end into a configurable number of virtual RF front-ends. The proposed architecture has the ability to enable flexible spectrum access in existing wireless and mobile networks, which is a challenging task due to the limited spectrum programmability, $i.e.$, the capability a system has to change the spectral properties of a given signal to fit an arbitrary frequency allocation. The main goal of the proposed approach is to improve spectral efficiency by efficiently using vacant gaps in congested spectrum-bandwidths or adopting network densification through infrastructure sharing. We demonstrate mathematically how our proposed approach works and present several simulation results proving its functionality and efficiency. Additionally, we designed and implemented an open-source and free proof of concept prototype of the proposed architecture, which can be used by researchers and developers to run experiments or extend the concept to other applications. We present several experimental results used to validate the proposed prototype. We demonstrate that the prototype can easily handle up to 12 concurrent physical layers.

The explosive emergence of wireless technologies and standards, covering licensed and unlicensed spectrum bands has triggered the appearance of a huge amount of wireless technologies, with many of them coexisting in the same band. Unfortunately, the wireless spectrum is a scarce resource, and the available frequency bands will not scale with the foreseen demand for new capacity. Certain parts of the spectrum, in particular the license-free ISM bands, are overcrowded, while other parts, mostly licensed bands, may be significantly underutilized. As such, there is a need to introduce more advanced techniques to access and share the wireless medium, either to improve the coordination within a given band, or to explore the possibilities of intelligently using unused spectrum in underutilized (e.g., licensed) bands. Therefore, in this paper, we present an open source SDR-based framework that can be employed to devise disruptive techniques to optimize the sub-optimal use of radio spectrum that exists today. Additionally, we describe three use cases where the proposed framework can be employed along with intelligent algorithms to achieve improved spectrum utilization.

Real-time strategy (RTS) game has proposed many challenges for AI research for its large state spaces, enormous branch factors, limited decision time and dynamic adversarial environment. To tackle above problems, the method called Adversarial Hierarchical Task Network planning (AHTN) has been proposed and achieves favorable performance. However, the HTN description it used cannot express complex relationships among tasks and impacts of environment on tasks. Moreover, the AHTN cannot handle task failures during plan execution. In this paper, we propose a modified AHTN planning algorithm named AHTNR. The algorithm introduces three elements essential task, phase and exit condition to extend the HTN description. To deal with possible task failures, the AHTNR first uses the extended HTN description to identify failed tasks. And then a novel task repair strategy is proposed based on historical information to maintain the validity of previous plan. Finally, empirical results are presented for the μRTS game, comparing AHTNR to the state-of-the-art search algorithms for RTS games.

Abstract: The chemical mechanical polishing (CMP) has been widely used for surface modification of critical materials and components and provided global planarization of topography with a low post-planarization slope high quality and efficiency. The colloidal silica slurries play an important role in the finishing processes of optical components. Monodisperse mesoporous silica nanospheres were synthesized with different surfactant by Stöber method. Their architectural features and texture parameters were characterized by XRD, FTIR, N2 adsorption–desorption isotherms, SEM, XPS, and TGA techniques. The spherical SiO2 products presented with the controllable 50-150 nm particle size and distribution. The AFM micrographs reveal that flat and smooth surfaces without distinct scratches residual particles are achieved by using the as-obtained composite particles as abrasives[The particle size of SiO2 slurry plays a critical role in the chemical-mechanical polishing process.

Rare study on quantitative relationship between energetic impact of debris flows on the intensity and duration of growth disturbances of tree rings was carried out, partly due to lack of feasible approaches and detailed field evidence. In this study, we firstly determine the age of a recent debris flow derived from historic landslide deposits at Qingyang mountain (QYM) on the northeastern Tibet plateau by dendrogeomorphic technique. We acquired the quantitative data of annual widths of tree rings in history and confirmed the influence of debris flow rather than other factors (e.g. climatic event and inset outbreaking) in disturbing the growth of tree rings in a specific year. Using the approach, we determined the age of the debris flow at QYM occurred in 1982, which was speculated to be triggered by high monthly precipitation of July in 1982. Subsequently, based on the boundaries of historic debris flow identified on remote sensing images before and after 1982 and depth-integrated continuum model, we reconstructed the process of 1982-debris flow and obtained the kinematic energy of debris flow impacting on the sampled trees. Based on the study, we observed that two growth disturbance patterns of tree rings influenced by the reconstructed 1982-debris flow were revealed including growth suppression and asymmetric growth. A raw logarithm relationship between duration (i.e. lasting time for the disturbed tree rings to recover the initial width) and intensity of growth disturbances (i.e. growth suppression ratio of disturbed tree rings) was obtained. We concluded that there is a negative exponential relationship between simulated kinematic energy of debris flow impacting on the disturbed trees and time to recover the initial width of corresponding tree rings.

Porcine sapovirus (PoSaV) is a significant pathogen causing diarrhea with high morbidity and mortality rates. Given its zoonotic characteristics, this study conducts a comprehensive genetic evolutionary analysis of PoSaV. Results confirmed PoSaV as the primary RNA virus in piglet feces (27.54%). Phylogenetic analysis identifies the prevalent PoSaV strain SHCM/Mega2023 in the GIII genogroup, involving a recombinant event with MK962338 and KT922089. The time tree revealed that the GIII genogroup exhibits the widest divergence time span, indicating a high likelihood of viral recombination. Further selective pressure calculations demonstrate that PoSaV was under purifying selection (dN/dS &lt; 1), with seven positively selected sites in VP1 protein which might be related to the antigencity. In conclusion, this study presents a novel genomic evolution of PoSaV, offering valuable insights into antigenicity and vaccine research.

Raindrop size distribution (RSD) is an index for reflecting precipitation characteristics. Analyzing the differences of RSD plays an important role in understanding the precipitation microphysical processes and improving quantitative precipitation prediction of radar. In this paper, the RSD data of Dafang (57708) station, Majang (57828) station, and Luodian (57916) station (with an altitude of 1722.7m, 985.0m, and 441.5m, respectively) in Guizhou are analyzed according to the precipitation microphysical characteristics. First,Particles with particle size less than 1mm contributes the highest value to the density of particle number , and decrease with the descending altitude. Second, the GAMMA distribution fit shows a better fit compare to M-P distribution fit, and GAMMA distribution fit increases with the ascending altitude. Third, the mass-weighted average diameter is not sensitive enough to the change of precipitation intensity with correlation coefficients of 54.84%, but there is a obvious relationship between the average volume diameter and the precipitation intensity with correlation coefficients of 69.15%. Then, the precipitation prediction model is established using LSTM neural network after fusing the representative microphysical characteristics of RSD with radar and rain gauge data. The precipitation prediction model is applied to the Dafang (57708) site to predict precipitation for time range of 0-180 minutes, and it is found that for the prediction of convective cloud and stratiform cloud precipitation, the 60-minute prediction results are the most consistent with the actual precipitation, where the correlation coefficients are 92.87% and 92.57%, respectively. Conclusively, the results demonstrate that combining with the RSD base data could improve the reliability of precipitation forecasting.

After more than 20 years of market-oriented reforms, China's economy has developed significantly so far. Guangzhou, in particular, has been developing rapidly, with its urbanisation rate increasing and its gross domestic product climbing, all of which have prompted Guangzhou to pay more attention to the ecological aspects of its development. The Nansha Coastal Wetland Scenic Area, located in the southernmost part of Guangzhou, is the largest coastal wetland in Guangzhou and the largest habitat for migratory birds in the city, as well as an important exemplary ecological reserve in Guangzhou's "Road to Ecological Civilisation". With the inclusion of Nansha in the national development strategy of Guangzhou's "Southward Expansion", the conflict between ecological protection of coastal wetlands and urban development has become increasingly prominent. In this regard, this study intends to use theoretical analysis, literature research, comparative analysis, fieldwork, data analysis and case studies to analyse the current state of the ecological environment in Nansha, explore the main problems in the process of its "southern development", and propose practical solutions for the construction and development of the ecological environment in Guangzhou, combining the theories of ecological economy, public goods and dissipative structure in Nansha. This paper is divided into seven chapters. This paper is divided into seven chapters. Chapter 1 presents the significance, purpose, content, methodology and technical approach of the study. Chapter 2 defines the basic concepts and the characteristics of the terms "Nantuo", "Nansha New Area", "coastal wetland" and "Nansha Binhai Wetland Scenic Area". The terms "Nansha New Area", "coastal wetland" and "Nansha Coastal Wetland Scenic Area" are defined. The theoretical basis of ecological economy theory, public goods theory, dissipative structure theory and sustainable development theory is used to explain the importance of protecting wetlands. It also demonstrates the importance that countries attach to the conservation of wetland ecology through a review of domestic and international literature. Chapter 3 describes the formation process, development status, conservation content and conservation actions of the Nansha Binhai wetland. Chapter 4 analyses the apparent and invisible problems faced by the Nansha coastal wetlands. Chapter 5 draws lessons from the experience of wetland resources development and conservation in China and overseas. Chapter 6 presents recommendations and solutions to the existing wetland problems in the Nansha coastal area. Chapter 7 provides conclusions and outlook. The ecological vulnerability of the Nansha wetlands is obvious. The government has to speed up the construction of logistics, industries, railways and ports while protecting a large area of wetlands. In the conflict between industrial civilization and ecological civilization, maintaining the integrity of the Nansha wetland requires the participation of the whole society, so as to finally achieve a balance between economic development and ecological protection, providing important theoretical guidance for the protection of the ecological environment of the Nansha wetland, ecological planning and scenic area development under the development strategy of the "southern expansion" of Guangzhou's urban space.

Abstract：Commuting of residents in big city often brings tidal traffic pressure or congestions. Understanding the causes behind this phenomenon is of great significance for urban space optimization. Various spatial big data make possible the fine description of urban residents travel behaviors, and bring new approaches to related studies. The present study focuses on two aspects: one is to obtain relatively accurate features of commuting behaviors by using mobile phone data, and the other is to simulate commuting behaviors of residents through the agent-based model and inducing backward the causes of congestion. Taking the Baishazhou area of Wuhan, a local area of a mega city in China, as a case study, travel behaviors of commuters are simulated: the spatial context of the model is set up using the existing urban road network and by dividing the area into travel units; then using the mobile phone call detail records (CDR) of a month, statistics of residents' travel during the four time slots in working day mornings are acquired and then used to generated the OD matrix of travels at different time slots; and then the data are imported into the model for simulation. By the preset rules of congestion, the agent-based model can effectively simulate the traffic conditions of each traffic intersection, and can also induce backward the causes of traffic congestion using the simulation results and the OD matrix. Finally, the model is used for the evaluation of road network optimization, which shows evident effects of the optimizing measures adopted in relieving congestion, and thus also proves the value of this method in urban studies.

Repeated exposure to pathogens leads to evolutionary selection of adaptive traits. Many species transfer immunological memory to their offspring to counteract future immune challenges. Transfer factor such as that found in colostrum is among the many mechanisms where transfer of immunologic memory from one generation to the next can be achieved for enhanced immune response. Here, a library of 100 plants with high protein contents were screened to find plant-based proteins that behave like a transfer factor moiety to boost human immunity. Aqueous extracts from candidate plants were tested on a human peripheral blood mononuclear cell (PBMC) cytotoxicity assay using human cancerous lymphoblast cells - K562 cells as a target and Natural Killer cells as an effector. Plant extracts that caused PBMCs to exhibit enhanced killing beyond the capability of the colostrum-based transfer factor were considered hits. Primary screening yielded an 11% hit rate. Protein content of these hits were tested by Bradford Assay and Coomassie stained-SDS-PAGE, where three extracts were confirmed to have high protein contents. Plants with high protein contents underwent C18 column fractionation using methanol gradients followed by membrane ultrafiltration to isolate proteins with molecular weight &lt;3 kDa, 3-30 kDa, and &gt;30 kDa fractions. It was found that the 3-30 kDa and &gt;30 kDa fractions had high activity in the PBMC cytotoxicity assay. The 3-30 kDa ultrafiltrates from the top two hits, seeds from Raphanus sativus and Brassica juncea, were then selected for protein identification by mass spectrometry. The majority of the proteins in the fractions were found to be seed storage proteins, with low abundance of proteins involved in plant defense and stress response. These findings suggest that Raphanus sativus or Brassica juncea extracts could be considered for further characterization and immune functional exploration with a possibility of supplemental use to bolster recipients’ immune response.

Mechanical equipment is composed of several parts, the interaction between the parts exists throughout whole life cycle leads to the widespread phenomenon of fault coupling and the diagnosis of independent faults cannot meet the requirements of the health management of mechanical equipment under actual working conditions. In this paper, the topological structure of graph neural network is used to describe the correlation of coupling faults and multiple fault types are regarded as network nodes respectively. The fault features are fused and extracted by graph convolution to achieve the classification of coupling faults. In this paper, dynamic vertexes are defined in data topology and the parameters of DIGNN classification model are optimized by changing the fault type of dynamic vertexes during training stage. The data is loaded into dynamic vertexes for classification and analysis during testing stage. The one-dimensional vibration data is converted into two-dimensional time-frequency domain data by wavelet transform making the input features of the model interpretable to reduce the uncertainty of model training. The data topology is then fed into DIGNN for fault classification, and GCN's node aggregation gives interpretability to each layer of network data processing. The method proposed in this paper can realize accurate diagnosis of independent faults on the data set, and can effectively judge the coupling mode of coupling faults, which is suitable for coupling fault analysis of mechanical equipment.

In the full load operating range, wind turbines typically use pitch control to maintain rotor speed and output power at their rated values to guarantee the whole system’s safety. Blade pitch actuators are subject to physical limitations and safety requirements, which imposes strict constraints on pitch angle’s amplitude and rate of change. These constraints will bring windup problem to the integral part of the pitch controller. It leads to deterioration of the pitch control system’s performance or even the instability problem, especially for large-scale turbines operating in extreme uncertain wind conditions or suffering from cyber attacks. This paper designs an anti-windup robust pitch angle control strategy to deal with pitch rate constraint issue to enhance the security of control system. First, to facilitate controller design, a filtered tracking error technique is employed to transform the nonaffine form into an affine one. Subsequently, a feedback robust controller based on UDE is developed to handle the model’s uncertainty and external disturbances. To address the issue of integral saturation in the pitch system and guarantee its safety, an elliptical bounded constraint is integrated into the designed UDE strategy. This bounded UDE controller can improve the stability of power generation quality, reduces the mechanical loads on components and enhance the whole system’s safety. Finally, the effectiveness of the proposed scheme is verified on the Wind Turbine Blockset platform in Matlab/Simulink. It can achieve better performance than the traditional method.

A simulation test system for the two-dimensional (2D) fuze overload loading process was designed to address the loading issues of recoil overload and centrifugal overload in fuze safety and arming (S&amp;A) devices. By incorporating centrifuge rotation energy storage, impact acceleration simulation, and equivalent centrifugal rotation simulation, a block equipped with a fuze S&amp;A device was accelerated instantly upon being impacted by a centrifuge-driven impact hammer, simulating recoil overload loading. The impact hammer was retracted instantaneously by adopting an electromagnetic brake, which resulted in the centrifugal rotation of the block around its track, to simulate the centrifugal overload loading. The dynamic equations of the simulation test system and the equations of impact hammer motions were established, whereby the rotation speed of the centrifuge and the braking force of the electromagnetic brake were calculated and selected. A dynamic model of the collision between the impact hammer and block was established using ANSYS/LS-DYNA software for simulation analysis. The acceleration curves of the recoil overload and centrifugal overload with variations in the centrifuge speed, cushion material, and buffer thickness were obtained, which verified the feasibility of the proposed loading simulation method. 2D overload loading simulation tests were performed using the developed simulation system, and the acceleration curves of the recoil overload and centrifugal overload were measured. The test results indicated that the proposed system can accomplish 2D overload loading simulations for a recoil overload of several 10000 g and centrifugal overload of several 1000 g.

The papaya mealybug Paracoccus marginatus is an invasive, polyphagous pest and poses a quarantine threat to tropical and subtropical countries. Infested commodity internationally should be undergoing phytosanitary treatment, while irradiation is recommended to replace methyl bromide fumigation. Dose-response tests were conducted on the 2-, 4-, and 6-d-old eggs and gravid females of P. marginatus using the X-ray radiation doses of 15–105 Gy with an interval of 15 Gy, respectively. Radiotolerance was compared using fiducial overlapping and lethal dose ratio (LDR) test, resulting in insignificant difference except for LDR test at LD90 (leading 90% mortality at 95% confidence level (CL)); the estimated dose for 99.9968% mortality at 95% CL was 176.5–185.2 Gy, which was validated in the confirmatory tests using gamma irradiation because gammy and X-rays have equal biological effect on pests. Therefore, a total of estimating 60,386 gravid females of papaya mealybug irradiated with 146.8–185.0 Gy resulted in no F1 nymphs developing. Eggs can therefore be used as an alternative to gravid females for dose-response tests; the recommended minimum dose for phytosanitary treatment of P. marginatus on infested commodity is 185 Gy, with treatment efficacy ≥ 99.9950% at 95% CL.

Mapping building roof plane structures is an active research direction in urban-related studies, as understanding roof structure provides essential information for generating highly detailed 3D building models. Traditional deep learning models have been the main focus of most recent research endeavours aiming to extract pixel-based building roof plane areas from remote sensing imagery. However, significant challenges arise, such as delineating complex roof boundaries and invisible boundaries. Additionally, challenges during the post-processing phase, where pix-el-based building roof plane maps are vectorized, often result in polygons with irregular shapes. In order to address this issue, this study explores a state-of-the-art method for planar graph reconstruction applied to building roof plane extraction. We propose a framework for reconstructing regularized building roof plane structures using aerial imagery and cadastral information. Our framework employs a holistic edge classification architecture based on an attention-based neural network to detect corners and edges between them from aerial imagery. Our experiments focused on three distinct study areas characterized by different roof structure topologies: Stadsveld – 't Zwering neighbourhood and Oude Markt area, located in Enschede, The Netherlands, and the Lozenets district in Sofia, Bulgaria. The outcomes of our experiments revealed that a model trained with a combined dataset of two different study areas demonstrated superior performance, capable of delineating edges obscured by shadows or canopy. Our experiment in the Oude Markt area resulted in building roof plane delineation with an F-score value of 0.43 when the model trained on the combined dataset was used. In comparison, the model trained only on the Stadsveld – 't Zwering dataset achieved an F-score value of 0.37, and the model trained only on the Lozenets dataset achieved an F-score value of 0.32. The results from the developed approach are promising and can be used for 3D city modelling in different urban settings.

Accurate determination of protein localization, levels, or protein-protein interactions is pivotal for the study of their function, and in situ protein labeling via homologous recombination has emerged as a critical tool in many organisms. While this approach has been refined in various model fungi, the study of protein function in most plant pathogens has predominantly relied on ex-situ or overexpression manipulations. To dissect the molecular mechanisms of development and infection for Verticillium dahliae, a formidable plant pathogen responsible for vascular wilt diseases, we have established a robust, homologous recombination-based in situ protein labeling strategy in this organism. Utilizing Agrobacterium tumefaciens-mediated transformation (ATMT), this methodology facilitates the precise tagging of specific proteins at their C-termini with epitopes, such as GFP and Flag, within the native context of V. dahliae. We demonstrate the efficacy of our approach through the in situ labeling of VdCf2 and VdDMM2, followed by subsequent confirmation via subcellular localization and protein-level analyses. Our findings confirm the applicability of homologous recombination for in situ protein labeling in V. dahliae and suggest its potential utility across a broad spectrum of filamentous fungi. This labeling method stands to significantly advance the field of functional genomics in plant pathogenic fungi, offering a versatile and powerful tool for the elucidation of protein function.

The explosive emergence of wireless technologies and standards, covering licensed and unlicensed spectrum bands has triggered the appearance of a huge amount of wireless technologies, with many of them coexisting in the same band. Unfortunately, the wireless spectrum is a scarce resource, and the available frequency bands will not scale with the foreseen demand for new capacity. Certain parts of the spectrum, in particular the license-free ISM bands, are overcrowded, while other parts, mostly licensed bands, may be significantly underutilized. As such, there is a need to introduce more advanced techniques to access and share the wireless medium, either to improve the coordination within a given band, or to explore the possibilities of intelligently using unused spectrum in underutilized (licensed) bands. Therefore, in this paper, we present a SDR based framework that can be employed to devise disruptive techniques to optimize the sub-optimal use of radio spectrum that exists today. Additionally, we describe two use cases for the proposed framework.

Sea cucumber peptides are small molecular peptides with biological function obtained from fresh sea cucumber as feedstock, which were hydrolyzed by protease, separated ,and purified. As the main product of sea cucumber refinement, it more accurately expresses the nutritional effect of sea cucumber and has a wide range of potential applications. It has been demonstrated that sea cucumber has a certain value-added effect on bone mineral density regulation, but the differences in bone mineral density regulation of extracts from different parts of sea cucumber and the techniques contributing to the efficient isolation of bone sea cucumber peptides have not been reported. Firstly, the aim of this study was to reveal the differences in osteogenic activities of enzymatic peptides from three major parts of sea cucumber: the body wall, the egg protein, and the intestinal protein. Then, the bone-enhancing sea cucumber peptides were isolated based on the characteristics of the dif-ferences in molecular weight distribution, hydrophilicity, and ionisation degree of sea cucumber, and to explore the possible mechanisms of their action. The findings indicated that sea cucumber peptides extracted from three distinct sites exhibited a dose-dependent enhancement of osteoblast proliferation and differentiation. Upon evaluating the three methods of sea cucumber peptide separation based on molecular weight distribution, hydrophilicity, and ionization, it was observed that the fraction isolated by hydrophobicity and

Panax ginseng C. A. Meyer (P. ginseng), has been widely used in traditional Chinese medicine (TCM). It contains a number of chemical components and possesses a variety of pharmacological activities. Alzheimer's disease (AD) is neurodegenerative disease that creates a huge burden on the lives and health of individuals. In recent years, studies have indicated that the chemical components of P. ginseng, especially ginsenosides, play a pronounced positive role in the prevention and treatment of neurological diseases. This review aimed to summarize currently studies on chemical components and the mechanisms action in AD intervention treatment of P. ginseng, especially ginsenosides. In this review, the components of P. ginseng and their respective active effects were first introduced. Then the key molecular mechanisms and signaling pathways of P. ginseng were introduced, and its different active ingredients in the prevention and treatment of Alzheimer's disease-related pathogenesis were also summarized from the pathogenesis of AD Aβ generation and aggregation, hyperphosphorylation of tau protein，oxidant stress，neuroinflammation，mitochondrial damage，disorder of neurotransmitter and gut microbiota. Signaling pathway networks related to the action of ginseng active ingredients was constructed, which could serve as a therapeutic target for Alzheimer's disease. In addition to a detailed report on P. ginseng in improving Alzheimer's disease-related pathogenesis, the application of the current technology, spatial metabonomics in AD therapeutics and diagnostics were later discussed. Spatial metabonomics could be applied to investigate the multi-target intervention of P. ginseng on Alzheimer's disease. Research perspectives for the study of P. ginseng in the treatment of Alzheimer's disease were provided for further studies.

Hot rolling tests of a low-alloy steel were conducted at a rolling temperature of 850 ℃ under different lubrication conditions, including benchmarks (dry condition and water) and water-based nanolubricants containing different concentrations of nano-TiO₂ from 1.0 to 8.0 wt%. The effects of nanolubricants on rolling force, surface roughness, thickness of oxide scale and microstructure were systematically investigated through varying nano-TiO₂ concentrations. The results show that the application of nanolubricants can decrease the rolling force, surface roughness and oxide scale thickness of rolled steels, and refine ferrite grains. In particular, the nanolubricant containing an optimal concentration (4.0 wt%) of nano-TiO₂ demonstrates the best lubrication performance, owing to the synergistic effect of lubricating film, rolling, polishing and mending generated by nano-TiO₂.

Low-sodium salt substitute (LSSS) has the potential in regulating sodium and potassium intake and has been available in China market for years. However, its real-world use and impact to sodium\potassium intake is unclear. Baseline data of 4000 adult participants who participated in three similar-designed randomized controlled trails were pooled together for this study. Self-reported awareness and use of LSSS were collected using the uniform questionnaire, and the 24-h urinary sodium and potassium excretion was used to estimate their dietary intake. Mixed-effects models were developed to assess the relationship between LSSS and 24-h urinary sodium and potassium excretion. 32.0% of the participants reported awareness of LSSS and 11.7% reported its current use. After adjusting location, sex, age, and education, compared with the group of participants unaware of LSSS, participants who were aware but not using LSSS and those who were using LSSS had a lower 24-h urinary sodium excretion by –356.1(95% CI: –503.9, –205.9) mg/d and –490.6(95% CI: –679.2, –293.7), respectively (p&lt;0.001). No significant difference was found for 24-h urinary potassium excretion and sodium-to-potassium ratio among the three groups (p&gt;0.05). In conclusion, although associated with lower sodium intake, the awareness and real-world use of LSSS are still very low in China.

A series of Ni/KIT6 catalystprecusors with 25wt.%Ni loading amount were reduced in H₂ at 400, 450, 500, and 550ºC, respectively. The studied catalysts were investigated by XRD, Quasiin-situ XPS, BET, TEM, and H₂-TPDanalysis methods.It was found that reduction temperature is an important factor affecting the hydrodeoxygenation (HDO) performance of the studied catalysts. The reduction temperature influences mainly the content of active components, crystal size, and the abilityfor adsorbing and activatingH2. The developed pore structure and large specific surface area of the KIT-6 support favored the Ni dispersion.The RT450 catalyst, which was prepared in H₂ atmosphere at 450 ºC, has the best HDO performance. Ethyl acetate can be completely transformed, and maintain 96.8% ethane selectivity and 3.2% methane selectivity at 300 ºC. The calculated apparent activation energies of the prepared catalysts increased in the following order: RT550 > RT400 > RT500 > RT450.

Ceftiofur (CEF) sodium is a third-generation broad-spectrum cephalosporin commonly used in an extra-label manner in dogs for the treatment of respiratory and urinary system infections. To contribute to the literature supporting CEF use in companion animals, we have developed a compartmental, nonlinear mixed-effects (NLME) model of CEF pharmacokinetics in dogs (PK). We then used the mathematical model to predict (via Monte Carlo simulation) the duration of time for which plasma concentrations of CEF and its pharmacologically active metabolites remained above minimum inhibitory concentrations (respiratory tractEscherichia coli spp). Twelve healthy beagle dogs were administered either 2.2 mg/kg ceftiofur-sodium (CEF-Na) intravenously (I.V) or 2.2 mg/kg CEF-Na subcutaneously (S.C). Plasma samples were collected over a period of 72 hours post-administration. To produce a measurement of total CEF, both CEF and CEF metabolites were derivatized into desfuroylceftiofur acetamide (DCA) before analysis by UPLC-MS/MS. No adverse effects were reported after I.V or S.C dosing. The NLME PK models were parameterized using the stochastic approximation expectation maximization algorithm as implemented in Monolix 2018R2. A two-compartment mamillary model with first-order elimination and first-order S.C absorption best described the available kinetic data. Final parameter estimates indicate that CEF has a low systemic clearance (0.25 L/h/kg) associated with a low global extraction ratio E = 0.02) and a moderate volume of distribution (2.97 L/kg) in dogs. The absolute bioavailability after S.C administration was high (93.7%). Gender was determined to be a significant covariate in explaining the variability of S.C absorption. Our simulations predicted that a dose of 2.2 mg/kg CEF-Na S.C would produce median plasma concentrations of CEF of at least 0.5 µg/mL (MIC₅₀) for approximately 30 hours.

The COVID-19 pandemic measures have negatively impacted education worldwide via travel restrictions, student visas, and physical attendanc,e among many other fac-tors. As one of the first places to impose strict pandemic measures and one of the last places to lift the measures, Mainland China provided a unique venue to investigate the effect of public health pandemic control policies on tertiary education. Considering the large portion of international students in medical schools and the higher susceptibility to the pandemic measures due to the natural synergy with teaching hospitals, medical schools can be an early forefront indicator of the impact of the pandemic on tertiary education. We surveyed 513 participants international medical students from Wen-zhou Medical University’s school of international studies in 2019 and 2022 about their satisfaction and demographic and cultural adaptation parameters. We found that the pandemic restrictions did not generally impact student satisfaction. Further analyzing the associated parameters, we found teaching satisfaction to be independent of age (P=.159), years in China (P=.896) and Chinese Level (P=.577) in the medical university. Teaching satisfaction is associated with the region of origin (P <0.001), acceptance of local social norms (P <0.001), satisfaction with the core values of Chinese culture (P <0.001), acclimatization to life in China (P <0.001), can easily make Chinese friends (P <0.001) among other factors. The findings of this study provide an understanding of the effects of pandemic measures on tertiary education satisfaction and other factors that can aid in international student satisfaction.

Three new cembranoids (1–3) and a new casbanoid (4), along with three known analogues (5–7), have been isolated from the soft coral Sinularia nanolobata collected off Ximao Island. The structures including the absolute configurations of new compounds were established by extensive spectro-scopic data analysis, time-dependent density functional theory/electronic circular dichroism (TDDFT-ECD) calculations and the comparison with spectroscopic data of known compounds. In in vitro bioassay, compounds 1 and 5 exhibited moderate cytotoxic activities against human erythroleukemia (HEL) cells line with IC50 values of 37.1 and 42.4 uM, respectively.

Physical inactivity increases the risk of many adverse health conditions, including the world’s major non-communicable diseases, such as coronary heart disease, type 2 diabetes, and breast and colon cancers, shortening life expectancy. There are minimal medical care and personal trainers’ methods to monitor a patient’s actual physical activity types. To improve activity monitoring, we propose an artificial-intelligence-based approach to classify the physical movement activity patterns. In more detail, we employ two deep learning (DL) methods, namely a deep feed-forward neural network (DNN) and a deep recurrent neural network (RNN) for this purpose. We evaluate the proposed models on two physical movement datasets collected from several volunteers who carried tri-axial accelerometer sensors. The first dataset is from the UCI machine learning repository, which contains 14 different activities-of-daily-life (ADL) and is collected from 16 volunteers who carried a single wrist-worn tri-axial accelerometer. The second dataset includes ten other ADLs and is gathered from 8 volunteers who placed the sensors on their hips. Our experiment results show that the RNN model provides the accuracy performance compared to the state-of-the-art methods in classifying the fundamental movement patterns with an overall accuracy of 84.89% and an overall F1-score of 82.56%. Our results indicate that the proposed method will provide the medical doctors and trainers a promising way to precisely track and understand a patient’s physical activities for better treatment.

DARPA, the Defense Advanced Research Projects Agency from the United States, has started the Spectrum Collaboration Challenge with the aim to encourage research and development of coexistence and collaboration techniques of heterogeneous networks in the same wireless spectrum bands. Team SCATTER has been participating in the challenge since its beginning, back in 2016. SCATTER’s open-source software-defined physical layer (SCATTER PHY) has been developed as a standalone application, with the ability to communicate with higher layers of SCATTER’s system via ZeroMQ, and uses USRP X310 software-defined radio devices to send and receive wireless signals. SCATTER PHY relies on USRP’s ability to schedule timed commands, uses both physical interfaces of the radio devices, utilizes the radio’s internal FPGA board to implement custom high-performance filtering blocks in order to increase its spectral efficiency as well as enable reliable usage of neighboring spectrum bands. This paper describes the design and main features of SCATTER PHY and showcases the experiments performed to verify the achieved benefits.

Variable and sometimes contrasting effects of using artificial rhizobium inocula to increase grain legume performance have been reported. The objectives of this systematic review and meta-analysis were therefore to (i) estimate the overall effect of rhizobium inocula on grain yield and protein content and (ii) identify potential confounding factors that explain the observed variation. A web of Science database literature search was carried out in 2016. Data from all field experiments, greenhouse and pot experiments that compared grain yields and protein contents in Rhizobium/Bradyrhizobium-inoculated with non-inoculated control crops were extracted and analyzed using previously described unweighted and weighted meta-analysis protocols. GRADE assessments of the strength of evidence of results from the weighted meta-analyses were carried which included an assessment of the risk of publication bias. Results: For unweighted meta-analyses we identified eligible data in 236 and 36 studies for grain yield and protein content respectively. For weighted meta-analyses we identified eligible data in 92 and 8 studies for grain yield and protein content respectively. Rhizobium inoculation was found to (i) significantly increase grain yield in both the unweighted (mean percent difference: 41%, 95%CI 36,46, p&lt;0.0001) and weighted meta-analysis (Standardized mean difference: 1.56, 95%CI 1.26,1.87, p&lt;0.0001) and (ii) significantly increase protein content in the unweighted meta-analysis (mean percent difference: 11%, 95%CI 5,18, p&lt;0.0001), but not the weighed meta-analyses which only detected a trend (0.1&gt;p&gt;0.05) towards higher protein content in inoculated grain legume crops. Multi-level model-based weighted meta-analyses suggest that the (i) type of experiment, (ii) type of fertilizer used in experiments, (iii) grain legume type/species and (iv) the country in which experiments were carried out, were confounding factors. The main limitation of the evidence is that a large number of publications did not report measures of variation and could therefore not be included in the more scientifically sound weighted meta-analyses. However based on the large evidence-base available for grain yield it can be concluded that overall Bradyrhizobium/Rhizobium seed inoculation results can increase grain yield by ~40% compared with non-inoculated grain legume crops.

Intercropping of maize (Zea mays L.) and peanuts (Arachis hypogaea L.) (M||P) significantly enhances crop yield. In a long-term M||P field experiment with two P fertilizer levels, we examined how long-term M||P affects topsoil aggregate fractions and stability, organic carbon (SOC), available phosphorus (AP), and total phosphorus (TP) in each aggregate fraction, along with crop yields. Compared to their respective monocultures, long-term M||P substantially increased the proportion of topsoil mechanical macroaggregates (7.6–16.3%) and water-stable macroaggregates (>1 mm) (13.8–36.1%), while reducing the unstable aggregate index (ELT) and the percentage of aggregation destruction (PAD). M||P significantly boosted the concentration (12.9–39.9%) and contribution rate (4.1–47.9%) of SOC in macroaggregates compared to single crops. Moreover, the concentration of TP in macroaggregates (>1 mm) and AP in each aggregate fraction of M||P exceeded that of the respective single crops (P<0.05). Furthermore, M||P significantly increased the Ca2-P, Ca8-P, Al-P, and Fe-P concentrations of intercropped maize (IM) and the Ca8-P, O-P, and Ca10-P concentrations of intercropped peanuts (IP). The land equivalent ratio (LER) of M||P was higher than one, and M||P stubble improved the yield of subsequent winter wheat (Triticum aestivum L.) compared with sole-crop maize stubble. P application augmented the concentration of SOC, TP, and AP in macroaggregates, resulting in improved crop yields. In conclusion, our findings suggest that long-term M||P combined with P application, sustains farmland productivity in the North China Plain by increasing SOC and macroaggregate fractions, improving aggregate stability, and enhancing soil P availability.

To investigate the variation patterns of spectral characteristics of main branches in fruit trees due to uneven distribution of growth, pruning, and fruit quality, as well as to determine the optimal fruit vi-bration harvesting, a vibration differential model of tree branches was constructed using the concen-trated mass method. A three-dimensional model of the fruit tree was built using finite element software. The spectral characteristics of each branch were obtained using the linear sweep frequency method. The method of changing the mass of each branch was employed to simulate the variation in branch mass. The frequency of occurrence, mean acceleration, and coefficient of variation of the inherent frequencies were used as evaluation indicators. The results revealed that when the vibration frequency of the fruit tree was at the peak frequency in the tree trunk spectrum, the frequency of occurrence and mean accel-eration were optimal. And the coefficient of variation of branch acceleration was less than 1, indicating a moderate dispersion. Additionally, reducing the branch mass resulted in an increase in the peak fre-quency of the tree trunk spectrum. Therefore, the growth, pruning, and uneven distribution of the branches in fruit trees can alter the spectral characteristics. When harvesting fruit by vibration, selecting the peak frequency in the trunk vibration spectrum as the excitation force frequency yields the best fruit detachment.

The rural population in the Dry Zone of Sri Lanka is largely affected by Chronic Kidney Disease of Unknown etiology (CKDu). According to the multidisciplinary research carried out so far, quality of groundwater was considered one of the possible causative factors for CKDu. Therefore, the assessment of water quality variations and evolution mechanism of water quality parameters of drinking water sources is important for identifying any relationships between CKDu and the drinking water quality. The current study aimed to perform a detailed hydrogeochemical investigation using isotopic and chemical methods on selected groundwater sources in the CKDu-endemic, non-endemic and control areas. TDS, hardness, Mg2+, Na+ and F- are the main parameters that cause water quality deterioration but, their derived mechanism in these three regions are completely different. The excess concentrations of F- and Mg2+ in the CKDu endemic area, low F- and high Mg2+in the CKDu non-endemic sedimentary formation, and either combinations of low F- and low Mg2+, high F- and low Mg2+ or low F- with high Mg2+ in the control area are the distinct features. The primary processes that regulate the evolution of groundwater types in CKDu endemic and control area is the weathering of silicates. Similarly, in the CKDu endemic area, carbonate dissolution and reverse ion exchange are prominent. Cation exchange and evaporite dissolution are more pronounced in the control area. Shallow groundwaters are evapo-concentrated hence it further deteriorates quality when compared to the deep groundwater with non-mixed, non-evaporated, and higher elevation recharge effect (from 100 m altitude) in the CKDu endemic area. Dilution decreases the ion content in the CKDu endemic area while evaporite dissolution further increase it in the control area after the rainy season. Evaporation, and seawater mixing affected the quality of groundwater in the non-endemic sedimentary formation. A statistically significant difference of F- ionic ratio with Na+, Mg2+, Ca2+ in the endemic and control areas. Intense rock weathering combined with the desorption added excess F- to the groundwater in the CKDu endemic area while the cation exchange and fluorite dissolution is contributing factor in CKDu control area. All the groundwater samples analyzed have exceeded the moderate hardness threshold. However, prominent Mg hardness proportion together with excess F- in the CKDu endemic area may produce nephrotoxic MgF2 complexes that may trigger renal damage. In contrast, produced NaF complexes in the CKDu control area leads to reduction of F- toxicity in the human body. Therefore, increased levels of magnesium, fluoride and TDS in the shallow groundwater, along with geochemical, hydrogeological and climatic factors, may contribute to the CKDu in the Dry Zone of Sri Lanka.

Dredging is a common technique for managing eutrophication problems in waters, reducing the accumulation of pollutants by removing sediments from the bottom of water bodies. However, dredging can cause complex impacts on lake ecosystems, and it is crucial to understand benefits and mechanisms for environments. In this paper, the dredged and undredged areas in the Caohai portion of Dianchi Lake were studied to analyze the effects of dredging on nitrogen-phosphorus transport and conversion and changes in nitrogen-phosphorus morphology content and its mechanisms by comparing the nitrogen-phosphorus morphology content, percentage; nitro-gen-phosphorus ratio, and release contribution of the two areas. It was found that the ratio of sta-bilized nitrogen (SN) to stabilized phosphorus (SP) in the dredged area was lower than that in the non-dredged area; the BD-P and TOC contents had a large turnaround at the 16-20 cm position of the sediment in the dredged area; and the main conclusions were that the dredging would disrupt the internal equilibrium of the lake system for many years, and in particular, it would have the greatest effect on the balance of the BD-P in the phosphorus forms of the sediment, and that the column cores of the dredged area from 0 to 16 cm might be newly accumulated sediments after the dredging project. However, with time, the distribution of nitrogen and phosphorus forms in the newly accumulated sediments will gradually reach a new equilibrium. In addition, dredging will also cause significant changes in the retention efficiency of nitrogen and phosphorus in the sediment, and the stable nitrogen and phosphorus forms will be released and transformed into unstable ni-trogen and phosphorus forms.

Background: The proportion of dietary protein may play a key role in the development of obesity in children and adolescents. Methods: Cross-sectional data of 4,336 children and adolescents from the National Health and Nutrition Survey (NHANES) during 2011 to March 2020 were analyzed. Multivariate logistic regression analysis was used to estimate odds ratios (OR) and 95% confidence intervals, and restriction cubic spline was uesd to explore nonlinear relationships of dietary protein energy supply ratio and obesity in children and adolescents. Results:In the adjusted logistic regression model, for every 1% increase in dietary protein energy ratio in children and adolescents, the increased risk of obesity was 4% (OR=1.04,95%CI:1.01-1.08). The restrictive cubic spline showed a nonlinear relationship between dietary protein energy ratio and obesity in children aged 6-11 years (P <0.05). The dietary protein energy supply ratio was included in the logistic regression model after converting to quartiles into categorical variables. The adjusted OR of children aged 6-11 years was 2.08 (95%CI:1.34, 3.23,P <0.01) for the highest quartile of dietary protein energy supply ratio compared with the lowest quartile. Conclusion: In American children, dietary protein energy supply ratios was positively correlated with obesity, independent of individual characteristics and energy.

Many researches have identified that adverse childhood experiences (ACEs) are associated with non-suicidal self-injury (NSSI) and suicidality. However, most studies have been restricted to a few types of ACEs. This study aims to investigate associations of 13 common types of ACEs with NSSI, suicidal ideation (SI) and suicide attempt (SA), as well as the mediation of depressive and anxiety symptoms therein. A total of 1771 students aged 11-16 years who participated in the baseline survey of the Chinese Adolescent Health Growth Cohort study were included for the analysis. ACEs, SI, SA, depressive and anxiety symptoms were recorded by standard questionnaire. Of included participants, 92.0% reported one or more category of ACEs. Smoking, parent-child separation, emotional abuse, physical abuse and being bullied were positively associated with NSSI, with the adjusted odds ratio (aOR) of 2.41(95%CI, 1.01-5.75), 1.80(1.28-2.54), 1.69(1.21-2.37), 2.08(1.44-3.01) and 1.87(1.35-2.59), respectively; smoking (4.03, 1.66-9.81), parent-child separation (1.42, 1.07-1.90), emotional abuse (1.91, 1.41-2.59), physical abuse (1.80, 1.27-2.57), emotional neglect (1.78, 1.28-2.49) and being bullied (2.08, 1.54-2.81) were positively associated with SI; smoking(4.30, 1.67-11.10), emotional abuse (2.42, 1.58-3.72) and being bullied (1.75, 1.17-2.60) were positively associated with SA. The associations of ACEs with NSSI, SI and SA were each partially or completely mediated through depressive and anxiety symptoms. Children and adolescents who had experiences of smoking, physical abuse and being bullied during childhood are consistently and independently associated with NSSI and suicidality, and these associations may be largely mediated through depressive and anxiety symptoms.

The ground surface deformation induced by shield tunnels passing through enclosure structure of existing tunnels is a particular underground construction scenario, which is encountered in Wuhan metro line 12 engineering cases in China. The classic ground deformation theory is difficult to accurately predict this ground deformation. This paper develops a semi-analytical method to predict ground heave considering space effect in this engineering condition. Based on improved ground deformation theory, a novel deformation prediction method of ground and enclosure structure is derived combined with Kirchhoff plate theory. Comparing with field deformation measurements, the maximum difference between measured and calculated deformation is 14.6%, which demonstrating that the proposed method can be used to predict the ground heave induced by shield tunnels passing through the enclosure structure of existing tunnels. The parameters of underground diaphragm wall used in Wuhan metro line 12 are further studied in detail. The results show that the ground heaves have positive correlation with embedded ratio of diaphragm wall, but negative correlation with its elastic modulus and thickness. But the thickness and embedded ratio has a limited effect on ground heaves. This study provides a technical reference for optimization setting of enclosure structure in protecting existing building.

In this paper, COMSOL Multiphysics software was used to simulate and analyze the process of cleaning oily sludge by high-speed stirring rotor. The physical phenomena such as velocity field, pressure field, heat dissipation and cavitation generated by the rotor during the process of the oily sludge cleaning were analyzed. The results showed that in the process of cleaning the oily sludge by high-speed stirring rotor, the shear force, heat dissipation and pressure increased with the enhance in the rotor speed. Cavitation occurs in the impeller area of the rotor because of the change of pressure, so the cavitation bubbles were formed. Shear force, heat dissipation and cavitation contributed to the separation of oil phase in oily sludge. Meanwhile, the simulation results were verified by experiments.

Dual specificity phosphatase 2 (DUSP2) regulates the activation of members in the mitogen-activated protein kinase (MAPK) family, which is involved in a variety of cellular processes like cell proliferation, differentiation, apoptosis and migration. DUSP2 also regulates the expression of inflammatory mediators in macrophages, however, it remains unknown whether DUSP2 participates in macrophage migration. Here, using the tail fin injury model in zebrafish larvae, we found that deletion of DUSP2 inhibited expression of pro-inflammatory cytokines and macrophage chemokines. Moreover, live imaging results showed that migration of macrophages to the injury site was inhibited after DUSP2 deletion. This inhibitory effect was mediated through reduced activation of extracellular regulated protein kinases (ERK) in DUSP2 knockout zebrafish.

Introduction: Spinal epidural arteriovenous fistulas (SEDAVFs) are extremely rare and the pathological process still remains unclear. Nevertheless, neurofibromatosis, surgery, as well as trauma have been implicated as causes. Nevertheless, long standing chronic vertebral compression fractures (VCFs) as a cause of SEDAVFs has not been reported in literature. Case Presentation: Our cases comprised of a male and female with ages 67 and 62 year respectively. They presented with weakness of bilateral lower extremities and back pain. Their symptoms deteriorated into mild recto-bladder dysfunction as well as hypoesthesia of lower limbs. They both had history of road traffic accidents (RTAs) prior to their symptomatology. In both cases, Magnetic resonance imaging (MRI) revealed VCFs prior to the above symptomatology. Spinal digital subtraction angiography (DSA) was used to confirm SEDAVFs in both cases. We utilized the trans-arterial route with Onyx embolization agent to obliterate both fistulae and their symptom resolved after the embolization. Two-years follow-ups revealed no recurrence of their fistulae. Conclusion: The initial long standing VCFs caused by trauma resulted in perforation of the dorsal somatic branches of the radicular artery leading to the occurrences of SEDAVFs in our cases.

In this paper, the effects of different food-grade enzymes on the antigenicity of casein (CN), β- lactoglobulin (β-LG) and ɑ-lactalbumin (ɑ-LA) in natural cow milk were studied. The degree of hydrolysis (DH), SDS-PAGE and molecular mas (MW) distribution of cow milk (CM) hydrolysates was assessed. Additionally, the residual antigenicity of CM hydrolysates was evaluated by using ELISA and western blotting with anti-CN, anti-β-LG and anti-ɑ-LA rabbit polyclonal antibody. The results showed that Alcalase and Protamex hydrolysis could efficiently reduce the antigenicity of CN, β-LG, ɑ-LA, showed a higher DH and the loss of density of CM proteins, as indicated by SDS-PAGE. The increasing of the low MW (<3 kDa) in CM hydrolysates was also presented. It was also found that Protamex, Alcalase could be more efficiently hydrolyzed major allergenic of CM than other enzymes for the development of hypoallergenic cow milk. Our research will lay a theoretical foundation for the study of hypoallergenic cow milk.

The paper focuses on the application of a multilevel, integrative and territorial approach to the protection of cultural heritage through planning instruments in Serbia. It points out the problems of the sectoral approach and discusses international recommendations that can be integrated into the planning methodology. The case study is the area of Djerdap National Park, which has an already established international and national importance. The research suggests that the cultural heritage in the area, with the exception of the Roman limes, is still recognized at the level of individual localities. The study emphasizes the importance of aligning all levels of governance to safeguard the whole spatial entity rather than focusing solely on its particular areas. The interna-tional and national importance of the planning area contributes to the strengthening of awareness of heritage and its institutional protection. However, the vitality of the area, which is key to its sustainable development, comes from the local level. Planning documents contribute to the inte-gration of local values and local communities into development programs and projects.

Nonconventional luminescent materials (NLMs) that do not contain traditional aromatic chromophores are of great interest due to their unique chemical structures, optical properties and their potential applications in various areas such as cellular imaging and chemical sensing. However, most reported NLMs show weak or no emission in dilute solutions, severely limiting their applications. In this work, the dynamic hydrogen bonds were utilized to design NLMs with efficient emission in dilute solutions. To further validate the results, polymers P1 and P2 were successfully prepared and investigated. It was found that luminescence quantum efficiency of P1 and P2 at concentration of 0.1 mg/mL in water solution is 8.9 and 0.6%, respectively. The high efficiency can be attributed to the fact that polymer P1 has more intra- or intermolecular dynamic hydrogen bonds and other short interactions than P2 in dilute solutions, allowing P1 to achieve the through-space conjugation effect to increase the degree of system conjugation, restrict molecular motion, and decrease non-radiative transitions, which can effectively improve luminescence. In addition, polymer P2 exhibits the characteristics of clustering-triggered emission, excitation wavelength-dependent and concentration-dependent fluorescence properties, excellent photobleaching resistance, low cytotoxicity and selective recognition of Fe3+. This work is a preliminary study of the luminescence properties of NLMs in dilute solutions via modulating dynamic hydrogen bonds, which can be used as a semi-empirical method to design and construct novel NLMs in future.

Glycosidic linkage analysis was conducted on the unfractionated polysaccharides in the alcohol-insoluble residues (AIRs) prepared from six red seaweeds (Gracilariopsis sp., Prionitis sp., Mastocarpus papillatus, Callophyllis sp., Mazzaella splendens, and Palmaria palmata) using GC-MS/FID analysis of partially methylated alditol acetates (PMAAs). The cell walls of P. palmata primarily contained mixed-linkage xylans and small amounts of sulfated galactans and cellulose. In contrast, the unfractionated polysaccharides of the other five species were rich in galactans displaying diverse 3,6-anhydro-galactose and galactose linkages with varied sulfation patterns. Different levels of cellulose were also observed. This glycosidic linkage method offers advantages for cellulose analysis over traditional monosaccharide analysis that is known for underrepresenting glucose in crystalline cellulose. Relative linkage compositions calculated from GC-MS and GC-FID measurements showed that anhydro sugar linkages generated more response in the latter detection method. This improved linkage workflow presents a useful tool for studying polysaccharide structural variations across red seaweed species. Furthermore, for the first time, relative linkage compositions from GC-MS and GC-FID measurements, along with normalized FID and total ion current (TIC) chromatograms without peak assignments, were analyzed using principal component analysis (PCA) as a proof-of-concept demonstration of the technique's potential to differentiate various red seaweed species.

Background: Educating college students about the importance of good sleep habits could lead to the adoption of healthier sleep routines, including sufficient sleep duration and sleep quality. The current pre-post study examines the impact of completing a sleep education program called “Sleep 101” on (1) sleep hygiene practices, (2) sleep quality, and (3) weekday and weekend sleep behaviors among college students. “Sleep 101” is an interactive online course developed to educate college students about the importance of sleep by addressing basic sleep physiology, the impact of sleep on mood, academic and physical performance, the interactions between sleep and various substances, and common sleep disorders. Methods: 338 college students were recruited from a midsized public university in the US and invited to participate in “Sleep 101”, of which 25 participants completed the baseline and post-intervention questionnaire. The Sleep Hygiene Index (SHI) was utilized to evaluate sleep hygiene practices, while standard questions were employed to assess weekday and weekend sleep behaviors and overall sleep quality. Results: Those who completed the study demonstrated a significant increase in weekday sleep duration and were less likely to engage in negative prior bedtime activities. In addition, 40% of those who completed baseline and post-intervention assessments noticed improvements in their sleep quality. Conclusion: These findings suggest that a brief online program is beneficial in improving sleep behaviors among college and could be a scalable approach to addressing current sleep issues and preventing future sleep problems in college students.

The profile of secondary metabolites occurring in apple cuticular layer is not only characteristic for particular apple cultivar, but also dynamically reflects various external factors in growing environment. In this study, the possibility to authenticate apple samples based on analysis of their cuticular layer extracts was investigated. Ultra-high-performance liquid chromatography coupled to high resolution tandem mass spectrometry (UHPLC-HRMS/MS) was employed for obtaining metabolomic fingerprints. In total, 274 authentic apple samples, four cultivars harvested within the seasons 2020 to 2022 in the Czech Republic and Poland were analysed. The generated complex data processed by univariate and multivariate statistical methods enabled to build classification models for discrimination of apple cultivars as well as their geographical origin. The models showed very good performance in differentiation of Czech and Polish samples for three of four cultivars: ‘Gala’, ‘Golden Delicious’ and ‘Idared’, moreover, the validity of the models was verified over harvest seasons. The diagnostic markers, besides metabolites of triterpene biosynthetic pathway, mainly represented wax esters. ‘Jonagold’, which is known to be susceptible to mutations, was the only cultivar for which the unambiguous classification of geographical origin was not possible.

Strawberry root rot caused by Neopestalotiopsis clavispora is one of the main diseases of strawberry and significantly impacts the yield and quality of strawberry fruit. There are now no effective control techniques available except for fungicide sprays, which may directly impact consumers. Biological control is becoming an alternative method for the control of plant diseases to replace or decrease the application of traditional synthetic chemical fungicides. Trichoderma is widely used as a biological agent for controlling strawberry root rot. In order to provide resources for screening the highly effective biocontrol fungus for controlling strawberry root rot caused by Neopestalotiopsis clavispora, the biocontrol mechanism,the control effects of Trichoderma asperellum CMT10 against strawberry root rot and growth-promoting effects on strawberry seedlings were investigated by plate culture, microscopy observation and root drenching methods.The results showed that CMT10 had obvious competitive, antibiotic and hyperparasitism effects on Neopestalotiopsis clavispora CMGF3. The CMT10 could quickly occupy nutritional space, and the inhibition rates of CMT10 against CMGF3 in confrontation culture on 7 d was 65.49%. The inhibition rates of volatile metabolite and fermentation metabolite produced by CMT10 against CMGF3 were 79.67% and 69.84%, respectively. The mycelium of strain CMT10 can act as hyperparasites by making contacting, winding and penetrating hyphae of CMGF3. Pot experiment showed that the biocontrol efficacy of CMT10 on strawberry root rot caused by Neopestalotiopsis clavispora was 63.00%. CMT10 had obvious promotion effect on strawberry growth, the plant height, root length, total fresh weight, root fresh weight, stem fresh weight and root dry weight, with the promotion rates were 20.09%, 22.39%, 87.11%, 101.58%, 79.82% and 72.33%, respectively. Overall, this study showed the ability of Trichoderma asperellum CMT10 to control strawberry root rot and their potential to develop as novel biocontrol agents to replace chemical fungicides for eco-friendly, sustainable agriculture.

Apis mellifera, especially weak ones, are highly vulnerable to Carpoglyphus lactis mites, which can rapidly infest and consume stored pollen, leading to weakened colonies and potentially colony collapse. This study aimed to ascertain and investigate the prevalence of this mite in honeybee colonies across 9 provinces in the Republic of Korea (ROK). A total of 615 honeybee colonies were collected, from 66 apiaries during the spring and 58 apiaries during the summer of 2023. A 1,242 bp segment of the the Cytochrome c oxidase subunit 1 (COI) gene was amplified using the polymerase chain reaction method. The detection levels of C. lactis in the honeybees were compared between winter and summer. Based on the COI sequence analysis, the nucleotide sequence similarity of C. lactis mites isolated in the ROK with those from China (NC048990.1) was found to be 99.5%, and with those from the United Kingdom (KY922482.1) was 99.3%. This study is the first report of C. lactis in Korean apiaries. The findings in this study demonstrate a significantly higher detection rate in winter, which is 4.1 times greater than that in summer (p &lt; 0.001). Furthermore, the results underscore the usefulness of molecular diagnostic techniques for detecting C. lactis mites.

COX II containing a dual core CuA active site is one of the three core subunits of mitochondrial Cco, which plays a significant role in the physiological process. In this report, the full-length cDNA of COXⅡ gene was cloned from Sitophilus zeamais, which had an ORF of 684 bp encoding 227 amino acids residues. The predicted COXⅡ protein had a molecular mass of 26.2 kDa with pI value of 6.37, and multiple sequence alignment and phylogenetic analysis indicated that Sitophilus zeamais COXⅡ had high sequence identity 78.51% with the COXⅡ of other insect species, especially similarity to sitophilus oryzae. This gene was subcloned into the prokaryotic expression vector pET-32a, and induced by IPTG in E.coli Transetta (DE3) expression system. Finally the COXⅡ with 6-His tag was purified using affinity chromatography with Ni²⁺-NTA agarose. WB showed the recombinant COXⅡ was about 44 kD, and the concentration of fusion protein was 50μg/mL. UV-spectrophotometer and infrared spectrometer analysis showed that recombinant COXⅡ could catalyze the oxidation of substrate Cytc, and influenced by AITC. It was found that AITC could form a hydrophobic region with COXⅡ protein via molecular docking, besides, a sulfur atom of AITC structure could form a length of 2.9 Å hydrogen bond with Leu-31. These results will provide valuable information for elucidating the role of COXⅡ in Sitophilus zeamais responses to AITC, meanwhile, it will helpful to carry out a point mutation in AITC binding sites for the future research.

The properties of the annual, semiannual and triennial oscillations (AO, SAO and TO) in the middle atmosphere have been investigated using the TIMED/SABER temperature data. The Lomb-Scargle and wavelet spectra were used to determine the dominant oscillations in the background temperature field. The AO is prominent at the mid-latitudes. The AO amplitudes present an asymmetry between the two Hemispheres, being larger in the mesosphere than in the stratosphere. The SAO dominates the tropical regions, with three amplitude maxima at altitudes of 45, 75, and 85 km. The SAOs in the upper mesosphere (75 km) are out of phase with those in the mesopause (85 km) in the tropical regions, which can generate an enhancement of 11 K at each equinox, contributing to the lower mesospheric inversion layer. The TO is significant in the tropical region, with amplitude being maximum at 35, 45 and 85 km. Result shows that there may be potential interaction by the TO with SAO at 85km at the equator. The relation between ENSO and TO has also been discussed. The ENSO signal may modulate the amplitude of the TO, mainly in the lower stratosphere. The real origin of the TO may lie in the wave-mean-flow interaction.

This paper is focused on typical rural settlements in the Stara Planina Mountain area in Serbia. They are distinguished by their authenticity, identity and character, and they have still not been destroyed by inappropriate development as is the case in some other mountain areas in Serbia, where the effects of urbanization, globalization and homogenization are obvious. Consequently, there is a need to prevent these effects in mountain areas where there is a threat of disbalance between development and the inherited natural and cultural values. The paper starts from several important concepts that relate contemporary approaches to cultural heritage preservation, place morphology and planning future development. The concept definitions from recent documents from related fields are used. These concepts are then applied to the area of Stara Planina Mountain and its rural settlements. The necessity for an integrative approach to planning this area with significant natural and anthropogenic potential is pointed out, including its integration into international programs of sustainable development.

The research reported on this paper was aimed at improving the overall efficiency of a PDO certified artisanal cheese production process. Being a PDO certified foodstuff by the EU, it is considered to have properties and qualities determined by the geographical environment in which is made, with its production taking place in a specific and determined geographical location, in this case the Serra da Estrela region. In that sense, the authors conducted a mapping according to a systemic perspective of the processes involved in the context of manufacturing and distribution of certified Serra da Estrela cheese. Numerous methods were used throughout the process, such as a systemic design analysis, and techniques derived from ethnographic methods, which led to the collection of data in the field and consequently provided the immersion of the researcher in genuine work situations. Critical points were identified and emphasized in the systemic map with the purpose of encouraging initiatives to address and overcome the gaps and inefficiencies detected. The systemic design analysis triggered the development of design work. Observations following an ethnographic approach identified ergonomic risks in cheese making during the process of cutting excess chips, fostering the emergence of musculoskeletal disorders at the wrist. A tool that fits best to the task at hand was developed. A prototype of the new tool enabled collecting feedback from use in the work context, in order to inform product development. The domains of agricultural production and microbiology, considering the specific microorganisms developed trough the ripening process of the cheese, turned out to be aspects of high importance for the issue under focus, contributing to a broader understanding of the ripening process and its risks, simultaneously improving the efficiency and success of cheese production. If it were not for the systemic analysis, which served as a link between the boundaries of distinct domains such as the risk of microorganism contamination, ergonomics, energy efficiency, legislation and regulation policies, transportation challenges and economic viability, approached throughout the research. Simultaneously creating bridges between them, the various problems might not have been detected in the first place, as they are usually addressed in specialized disciplines, predetermined by the restrictions of each specific area of knowledge. As a consequence of the development of this research, which was based on an analysis that sought to establish possible connections between various disciplines and tried to constantly maintain a holistic perspective, making new connections and observing the issues from a new angle, apart from the already established methodologies. All this allowed to lay out the seeds for the development of a plan to tackle the critical points identified by the systemic analysis reported in this paper.

Promoting green development has become an important way to optimize the ecological and economic structure and promote sustainable development. The Yangtze River Economic Belt is an important economic corridor in China, and it remains to be examined whether the implementation of environmental regulations has enhanced the green total factor productivity (GTFP) of cities. This paper calculates the green total factor productivity of 107 cities within the Yangtze River Economic Belt by using the super-efficient SBM model and the GML index with Chinese city panel data from 2007-2019 and measures the intensity of environmental regulations through textual analysis. The bidirectional fixed-effects model constructed in this paper suggests an inverted U-shaped relationship between environmental regulation and GTFP, which is confirmed by a series of robustness tests. Green technology innovation and advanced industrial structure play a mechanism role in this. In regions with lower levels of green technology and industrial structure, the inverted U-shaped relationship between environmental regulation and green total factor productivity is more significant. In addition, the phenomenon of GTFP rising and then falling because of environmental regulation is more obvious in cities in the middle and upper reaches of the Yangtze River and outside the urban agglomerations. Therefore, when formulating environmental regulation policies, it is necessary to balance the relationship between economic development and environmental protection and harmonize the environment and economic development of the entire Yangtze River Basin.

The wetlands in northeastern Bangladesh are home to some of the most prolific and valuable ecosystems on the planet, offering a wide range of benefits to both the local and wider communities. A limited number of research on this topic have been carried out in various wetlands in coastal hilsa, but none have been located in the northeastern region of Bangladesh. Thus, the goal of this study was to better understand the most commercially relevant species (anadromous hilsa) in northeastern Bangladesh as well as to assess the wetland ecosystem services more thoroughly with the contribution of their fish genetic resources. In addition to laboratory studies, fieldwork was done in the fishing settlements along the Surma River, Hakaluki Haor, and Tanguar Haor. The study classified 77 fish species into 21 subcategories of ecosystem services, of which 56% were not threatened, 17% were vulnerable, and 10% were highly endangered. The species Hilsa was found to be the most economically significant, accounting for 1% of the GDP overall. The study determined if the hilsa stock of the examined wetlands maintains a single or several subpopulations in comparison to other parts of the country when they migrate from saline water to northeastern Bangladesh (freshwater). But when compared to other groups, the FST score was between 0.000 to 0.017, indicating that the populations are identical and that there is genetic material sharing between them. Additionally, these statistics imply that the Sylhet haor and adjacent river systems contain a single stock of Hilsa fish. Nevertheless, a number of stresses and risks, including overexploitation, illicit and destructive fishing, siltation, and natural disasters like flash floods, have been linked to changes in the supply of hilsa and other ecosystem services. This study also emphasizes the necessity of policy attention and research to address the concerns.

In this paper, we introduce a specialized, fully automated experimental arrangement designed for assessing the effectiveness of augmented and virtual reality technologies in healthcare setting and explore its design principles focusing on depth sensor characterization. The main goal of this project is to establish a robust benchtop platform for the quantitative evaluation of extended reality technologies in a controlled environment, emphasizing the practical assessment of augmented reality head-mounted devices. We outline a design concept and considerations for an experimental configuration aimed at creating a realistic testing environment. This apparatus comprises an observation platform mounted on a three-degree-of-freedom motorized system and a test phantom stage. Focusing on real-case scenarios, we utilized a range of sensors, including readily available range-sensing cameras and commercial augmented reality headsets, such as the Intel RealSense L515 LiDAR camera, mounted on the motion control system. The setup enabled automated data collection and facilitates controlled assessments and validation of various facets of augmented reality technologies, including object, hand, and head tracking, as well as static and dynamic image registration. This paper describes the system architecture, the process of automated data collection, and presents several evaluation studies conducted with this setup, providing insights into the quality and temporal noise associated with static or moving objects or observers in augmented reality applications.

To conduct high-precision and high-resolution numerical simulation of complex flow structures in turbomachinery, a high-order finite volume weighted essentially non-oscillatory (WENO) scheme for the large eddy simulation (LES) is improved and embedded into the three-dimensional viscous unsteady CFD solver NUAA-Turbo. Firstly, the spectral characteristics and unsteady convergence of the improved WENO scheme are studied. Compared with the classical WENO scheme, the improved WENO scheme has better dissipation and dispersion characteristics and faster convergence speed. Then, the coefficient CW of the Wall-Adapting Local Eddy-viscosity (WALE) model is calibrated by decaying homogeneous isotropic turbulence (DHIT) test case. Finally, the scheme is applied to conduct high-precision LES calculations of turbulent boundary layer flow, supersonic compression corner flow, and low-pressure turbine cascade separation flow. The numerical simulation results show that this WENO scheme has excellent shock wave capture ability and turbulence resolution and can capture more flow field details with less mesh size, greatly reducing the computational cost and laying a foundation for large-scale engineering application of LES.

To secure logic circuits against the illegal copying the insertion of the so-called key bit inputs using XOR/XNOR gates has been proposed in . The inserted gates modify (lock) the behavior of the original circuit and only the correct choice of the secret key bits guarantees the equivalent behaviour of the locked circuit to the original circuit. To break this kind of security, i.e. to find the secret key bits, there was a SAT solver based attack proposed in . The aim of this work is to experimentally verify this attack on several locked circuits with various number of primary inputs and outputs and with various number of gates. Except for the random placement of the key gates we evaluate also the positioning with chaining elimination. The obtained and presented results show that we were able to unlock 10 of 11 circuits within few minutes on a common PC.