The twisted Wang transform distribution family, defined as the composition of parameter shifted inverse CDF function with an original CDF function, is found to be most suitable for matching low shape factor distributions, characterizing hard to fit or to simulate reinsurance portfolio losses for some perils from our previous study. Among them, the best form for matching a hard-to-fit empirical loss distribution for a specific peril, is the Exponential Fractional Extra Power 0 Distribution in (0,1) with CDF:.The simplest yet still a good form of this family is the Transformed Hyperbolic Tangent Distribution with CDF:,which has analytical formulas for the moments. The twisted Wang transform distribution family is compared and confirmed to be superior to all other well-known distribution families through extensive numerical optimization practice, distribution forms guesses, and computer-aided exploration experiments.

The lower reaches of the Changhua River are located in the northwest of Hainan Island, and the shallow groundwater in this area is the main water source for residents living at both sides of the river. In order to sustain the exploitation and use of water resources in this area, it is essential to clarify the chemical characteristics and the formation mechanism of the groundwater. We collected 100 sets of shallow groundwater samples from the lower reaches of the Changhua River, and analyzed the chemical characteristics of the groundwater in shallow aquifers as well as its controlling factors by means of the methods including descriptive statistical analysis, Piper diagram, Gibbs diagram, and ion ratio. The results show that the overall characteristics of groundwater in the study area are near-neutral to weakly alkaline nature, indicating a generally oxidized environment. The groundwater involves in 56 chemical types, and the most predominant types are Ca•Na-HCO3 and Ca-HCO3, respectively. NO- 3 has become a macro component exceeding SO2- 4in most of the sampling groundwater, suggesting a significant impact of human activities in this area. At the same time, the chemical characteristics of groundwater in the study area are mainly affected by the water-rock interaction, while the water-rock interaction is mostly affected by the dissolution of silicate rocks and less by the dissolution of carbonate rocks and evaporite rocks. According to the ion ratio results, Na+ and K+ in the study area are mainly from the leaching of silicate rocks, Ca2+ and Mg2+ are mainly from the dissolution of carbonate rocks, in addition to a certain degree of cationic exchange. NO- 3 is mainly related to human activities, and the human activities are more affected by agricultural activities and domestic sewage than by industrial and mining activities. This study can provide a reference for the development and protection of shallow groundwater in the lower reaches of the Changhua River.

We report a prebiotically relevant solution to the N1-ribosylation of pyrimidine nucleobases, a well-known challenge in the RNA World hypothesis. It is found that the presence of metal cations and clay mineral enables the previously unachievable direct ribosylation of uracil, providing by far the highest yield. Spectroscopy and chromatography analyses confirmed the formation of ribosylated uracil. The method can also be extended to the ribosylation of 2-pyrimidinone. These findings are also compatible with the metal-doped-clay model developed by our lab for the unified route of the selection of ribose and subsequent syntheses of nucleotide and RNA.

Land plants have undergone their great diversification and evolution in the past 400 million years. Although appearing complex and hard to grasp, the evolution of plants centers around an invariable core development process, SRC (Sexual Reproductive Cycle). Various modifications have been added sequentially to this core process, and thus creating various novel organs and distinguishing their bearers one from another. Reproductive organs of all land plants, including sporangium, megasporangium, metamegasporangium (= ovule), and various metamegasporangium complexes, are derived from terminal sporangia in the earliest land plants. Throughout the million-year-long evolution, plants sequentially recruit associating accessories to protect their vulnerable core parts (spore and gamete). The occurrence of every single of these novelties is a stair marking land plant reproduction evolution and leads to enhanced offspring development conditioning (ODC).

The Yixian Formation (Lower Cretaceous) of China is famous worldwide for its fossils of early angio-sperms, but there is only one record of flower bud hitherto. A previous fossil record of flower bud just showed the appearance and lacked any internal details. Such a lacuna in knowledge of flower buds hin-ders our understanding of the evolution of flowers. Our new specimen was collected from an outcrop of the Yixian Formation (the Barremian-Aptian, Lower Cretaceous) near Dawangzhangzi, Lingyuan, Liao-ning, China. The specimen was observed and photographed using a Sony ILCE-7 digital camera and a Nikon SMZ1500 stereomicroscope, and details were observed using a TESCAN MAIA3 SEM. Our ob-servations document a fossil flower bud, Archaebuda cretaca sp. nov, from the Lower Cretaceous of China. The occurrence of two species of Archaebuda in the Yixian Formation not only confirms the ex-istence of the expected gynoecium (and possible androecium) in a flower bud, but also underscores the occurrence of typical flowers in the Early Cretaceous.

A previously undescribed malformed half-engorged female Dermacentor nuttalli was noticed in our tick specimen collection. This tick exhibited abnormal legs compared with normal D. nuttalli ticks. The first leg on the right side and the third leg on the left side were much smaller than normal ticks, and reduced to a small and degenerated appendix, respectively. Both of their pulvillus and claws were absent.

The Goldbach Conjecture, which is frequently termed as “1 + 1”, has been a fascinating goal for many mathematicians over centuries. A Chinese mathematician, Dr. Jingrun Chen, proved 1 + 2, which is a great success and the best result so far achieved. Although there were several attempts proving the conjecture, these attempts are either tediously long, complicated, or logically imperfect, thus not widely accepted. Taking advantage of the periodicity of primes, here the author provides a straight forward rigorous proof for the Conjecture.

Catalyst with high catalytic activity and good stability are desirable in the electrocatalytic oxidation of glucose. Herein, Pt concave nanocubes with high-index facets (HIFs) supported by carbon black (Pt CNC/CB) are prepared through a hydrothermal method. The experimental results demonstrate that the peak current densities in different potential regions on the Pt CNC/CB anode are 0.22, 0.20, and 0.60 mA cm−2, respectively. The glucose oxidation reaction shows superior performances in basic and neutral conditions than in acid conditions. Better stability is achieved by Pt CNC/CB than Pt concave nanocubes (Pt CNCs). Abundant surface defects with low-coordinated atom numbers, such as the steps, kinks, and edges, are served as active sites in the electrocatalytic oxidation of glucose. With the addition of carbon black, the catalytic activity can be improved by facilitating the full exposure of the active surface defects on the HIFs of Pt CNCs. Moreover, to address the aggregation of Pt CNCs, caused by the high surface energy of HIFs, the introduction of carbon material is an effective way to preserve the HIFs, and thus enhance the stability of the catalyst. Hence, the prepared Pt CNC/CB electrocatalyst has great potential to be applied in the electrooxidation of glucose.

The greatly diversified flowering plants (angiosperms) are the dominating and defining group in the current earth ecosystem. However, from which group by what way the flowers, especially their gynoecia (key characteristics of angiosperms), are derived have been the questions in botany unanswered over centuries. Such an embarrassing situation can be attributed to the lack of plants with partially enclosed ovules, which are supposed to be a post between gymnosperms and angi-osperms. Here we report a fossil plant that has an apparent coniferous vegetative and reproduc-tive morphologies but has a single seed partially wrapped by the subtending bract. Such a mor-phology suggests that the carpels in angiosperms may be equivalent to bracts enclosing their axil-lary seed(s). Such a non-traditional interpretation of the homology of angiosperm carpels is com-patible with various new progresses made in botany and is in line with Tomlinson’s recent hy-pothesis. Together with other fossil evidence reported recently, it appears that gynoecia in angio-sperms are derived in multiple ways.

Digital twin, an innovative technology propelled by data and models, plays a seminal role in the digital transformation and intelligent upgrade of ships. This study introduces a digital twin methodology for real-time monitoring of ship structure deformation fields, based on finite discrete strain data, and a visualization tool framework is developed using virtual reality technology. First, the inverse Finite Element Method (iFEM) is employed to derive the deformation field of the ship structure in real time via sensor strain data. Secondly, the deformation field data obtained based on the iFEM algorithm is converted into general visualization data conducive to interpretation within VR applications. Lastly, a digital twin software tool is built to enable synchronous response and interaction between the virtual scene and the physical scene, directly superposing particular virtual objects (data acquired by sensors, CAD virtual models, and deformation field cloud images) onto the physical scene in real-time. The digital twin tool embodies a virtual reality visualization system framework integrating physical data measurement, reconstruction, analysis, expression, storage, rendering and interaction of deformation field data. Through practical application, the flexibility, effectiveness and compatibility of the developed prototype tool are verified. According to the results, the system can enhance the efficiency of scientific communication, model validation, and interdisciplinary sharing during the analysis and evaluation of mechanical properties of ship structures.

Abstract: Safety issues related to the electrification of more electric aircraft (MEA) need to be addressed because of the increasing complexity of aircraft electrical power systems and the growing number of safety-critical sub-systems that need to be powered. Managing the energy storage systems and the flexibility in the load-side plays an important role in preserving the system’s safety when facing an energy shortage. This paper presents a system-level centralized operation management strategy based on model predictive control (MPC) for MEA to schedule battery systems and exploit flexibility in the demand-side while satisfying time-varying operational requirements. The proposed online control strategy aims to maintain energy storage (ES) and prolong the battery life cycle, while minimizing load shedding, with fewer switching activities to improve devices lifetime and to avoid unnecessary transients. Using a mixed-integer linear programming (MILP) formulation, different objective functions are proposed to realize the control targets, with soft constraints improving the robustness of the model. Besides, an evaluation framework is proposed to analyze the effects of various objective functions and the prediction horizon on system performance, which provides the designers and users of MEA and other complex systems with new insights into operation management problem formulation.

This paper investigates the evolution of microstructures and precipitations of an ultra-low iron alloy 625 subjected to long term aging treatment by scanning electron microscope (SEM) and X-ray diffraction(XRD). Use ASTM G28A acid Fe3(SO4)2 erosion to represent intergranular corrosion weightlessness and corrosive morphology. The result shows that alloy at 750C by aging treatment for 40h, precipitated γ'' phase in the grain boundary. In high density area of γ'' phase, occurs γ'' phase to δ phase degeneration transformation by aging treatment for 200h and the needle-like δ phase becomes more with time prolonged. And γ'' phase degenerated to δ phase completely until treated for 1000h. The sample which has aging treatment tends to have intergranular corrosion and mainly because alloy element spreading leads to dilution area and grain boundary precipitated phase, plus interlaced δ phase’s dissolving, which makes sample grain particle fall off and this results in apparent weightlessness. The weightlessness rate(WLR) is related with precipitated volume score. With aging sensitization time change, can be described by Johnson-Mehl-Avrami equation, i.e.: $WLR=44.32\left[1-\text{exp}\left(-\frac{t}{10.99}\right)\right]+44.62\left[1-\text{exp}\left(-\frac{t}{327.8}\right)\right]+1.267\left(mm/a\right)$

The surface velocity of the Amery Ice Shelf (AIS) is vital to assessing its stability and mass balance. Previous studies have shown that the AIS basin has a stable multi-year average surface velocity. However, spatiotemporal variations in the surface velocity of the AIS and the underlying physical mechanism remain poorly understood. This study combined offset tracking and DInSAR methods to extract the monthly average surface velocity of the AIS and obtained the inter-annual surface velocity from the ITS_LIVE product. An uneven spatial distribution in inter-annual variation of the surface velocity was observed between 2000–2022, although the magnitude of variation was small at less than 20.5 m/yr. The increase and decrease in surface velocity on the eastern and western-central sides of the AIS, respectively, could be attributed to the change in the thickness of the AIS. There was clear seasonal variation in monthly average surface velocity at the eastern side of the AIS between 2017–2021, which could be attributed to variations in the area and thickness of fast-ice and also to variations in ocean temperature. This study suggested that changes in fast-ice and ocean temperature are the main factors driving spatiotemporal variation in the surface velocity of the AIS.

This paper presents the results of an experimental and analytical study on the behavior of cold-formed thick-walled steel plates connected by a single bolt under double shear. Experimental studies were conducted on a total of 54 bolted connections fabricated from two thickness of cold-formed thick-walled steel plates with the nominal thickness of 6 mm and 10 mm. The effects of end distance, edge distance and steel plate thickness were investigated on the bolt bearing behavior. Codes of (modified) ANSI/AISC 360-16 and EN1993-1-8 were applied to predict failure modes and bearing resistance of connections and the predictions were compared with that of measurements. A method was proposed to calculate the elongation of bolt hole at ultimate load. The studies show that fractures occurred on shear planes of specimens failed by shear out due to reduced ductility caused by cold forming process. The modified ANSI/AISC gives the most accurate predictions of failure modes and bearing resistance. However, the bearing resistance will be overestimated if the reduction in area of shear planes caused by occurrence of fracture is ignored for specimens with end distance being higher than 2.0d0 and a reduction factor is needed for calculating bearing resistance of connections. The method proposed in our paper can predict the elongation of bolt hole very well.

As the COVID-19 pandemic has caused enormous damage to society, economy and public health security, it is crucial to combat the epidemic and allocate social and health resources effectively. Global optimization algorithms are extensively used in many domains to find optimal solutions to complex problems. Thus, a survey of three typical global optimizations applied on the COVID-19 pandemic is timely. This article is structured into three typical global optimization algorithms - Genetic Algorithm, Particle Swarm Optimization, and Cat Swarm Optimization - and summarizes the framework models and practical applications, as well as other optimization methods that may be applied to COVID-19. Finally, current unresolved challenges and future research opportunities to be explored are summarized.

In recent years, intelligent identification and prediction of ore deposits based on deep learning algorithm and image processing technology has gradually become one of the research frontiers in the field of geological and metallogenic prediction. However, this method also has many problems that need to be solved. For example, (1) very few trainable image samples containing mineral point labels; (2) The geological image features are small and irregular, and the image similarity is high; (3) It is difficult to calculate the influence of different geological prospecting factors on ore mineralization. Based on this, this paper constructs a deep learning network model Multiscale Feature Attention Framework (MFAF) based on geo-image data. The results show that MFCA-Net module in MFAF model can solve the problem of scarce mine label images to a certain extent. In addition, the channel attention mechanism SE-Net module can quantify the difference of influence of different source factors on mineralization. The prediction map is obtained by applying the MFAF model in the study of deposit identification and prediction in the research area of the southern section of Qin-hang metallogenic Belt. In the forecast map, many regions have high metallogenic potential. Through observation, it is found that the above predicted area covers 100% of the known ore deposits at present, which has a good prediction effect. Later, we can find out the specific reasons through field verification. The multi-scale feature fusion and attention mechanism MFA Framework in this paper can provide a new way of thinking for geologists in mineral exploration. The research of this paper also provides resource guarantee and technical support for the sustainable exploitation of mineral resources and the sustainable growth of society and economy.

Thin-film lithium niobate has gained significant attention in photonics due to its broad optical transparency, high refractive index, nonlinear coefficient, and substantial electro-optic coefficient. It holds great promise for developing electro-optic modulators with low loss, a compact size, and wide bandwidth. This study focuses on a meticulous investigation utilizing microwave photonics to establish a high-performance electro-optic modulator. Specifically, we analyze the optical mode field distribution and traveling wave electrode structure of lithium niobate thin-film materials. The proposed modulator achieves an impressive half-wave voltage-length product of 1.69 V·cm, a negligible metal loss of 0.01 dB/cm, and a substantial 3dB electro-optic bandwidth of 50 GHz. This research successfully realizes low-loss, high-efficiency LNOI electro-optical modulators, providing a strong foundation for large-scale integrated optoelectronic systems.

We propose a computer-generated hologram method for near-eye virtual reality and augmented reality 3D display. A 3D object located near the holographic plane is projected onto a projection plane to obtain a plurality of projected images with different angles. The hologram is calculated by superposition of projected image convolution with a specific PSF through the interference of reference wave with object wave. Holographic 3D display systems with LED as illumination, 4f optical filtering system and lens as eyepiece for near-eye VR display and HOE as combiner for near-eye AR display are designed. The results show that the proposed method is about 38 times faster than the conventional point cloud method. The proposed method is flexible to produce speckle noise free high-quality VR and AR images with efficient focus and defocus capabilities.

The development and application of marine current energy are attracting more and more attention around the world. Due to the hardness of its working environment, it is important and difficult to study the fault diagnosis of a marine current generation system. In this paper, an underwater image is chosen as the fault-diagnosing signal, after different sensors are compared. This paper proposes a diagnosis method based on the sparse autoencoder (SA) and softmax regression (SR). The SA is used to extract the features and SR is used to classify them. Images are used to monitor whether the blade is attached by benthos and to determine its corresponding degree of attachment. Compared with other methods, the experiment results show that the proposed method can diagnose the blade attachment with higher accuracy.

This empirical research is part of a larger project beginning in 2020 and ongoing until 2023 exploring the impact of the COVID-19 pandemic on young caregivers aged 5-25 years and their families in Canada. Utilizing the social determinants of health as a conceptual framework, this case study emphasizes the voices of professionals offering services to young caregiver clients during the pandemic, and explores their perspectives on the impact of the pandemic on young caregivers and their families. Across three (3) different organizations offering programs and services to young caregiver clients in Ontario, six (6) individual interviews were conducted with directors/program managers and four (4) group interviews were conducted with thirteen (13) staff members who worked directly with young caregivers and their families. Nineteen (19) service providers participated in total. The results of this study highlight five (5) primary themes that emerged through data analysis: i) the role of service providers, ii) the impact of the COVID-19 pandemic on organizations and service providers supporting young caregivers and their families, iii) barriers for service users, iv) helpful resources for service providers and organizations, and v) resources needed/preferred by service providers and organization. The pandemic significantly impacted young caregivers and their families, as reported by professionals, and organizations working with young caregivers and their families were tasked with addressing increased service demands and adapting service delivery to follow public health guidelines.

Renal cell carcinoma (RCC) is the most common kidney cancer, accounting for approximately 80–90 % of all primary kidney cancer. Treatment for patients with advanced RCC remains unsatisfactory. Rare cancer stem cells (CSCs) are proposed to be responsible for failure of current treatment. Here, we investigate the effects of CBFA2T2 on CSCs regulation in RCC, as well as to elucidate the possible mechanisms. We showed that CBFA2T2 expression can significantly predict the survival of RCC patients. Functional assays showed that knocking-down of CBFA2T2 can inhibit cell migration and invasion in 786-O and A-498 cells in vitro, and reduce ALDH^high CSCs populations. Furthermore, CBFA2T2 expression is necessary for sphere-forming ability and cancer stem cells marker expression in RCC cell lines. Collectively, our data suggest that CBFA2T2 expression correlates with aggressive characteristics of RCC and CBFA2T2 is required for maintenance of “stemness” through regulation of stem cells factors, thereby highlighting CBFA2T2 as a potential therapeutic target for RCC treatment.

This work investigated the influence of current density, plating solution flow rate, and nozzle outlet-cathode distance on the properties of Ni-diamond composite coatings. A multi-physics field simulation is employed to analyze the interplay between current density, plating solution flow rate, and nozzle outlet-cathode distance on the flow field and electric field distribution. Additionally, particle tracing simulations were incorporated into the model to evaluate the incorporation efficiency of diamond particles during composite electrodeposition. Experimental validation of the findings shows a significant increase in the diamond particle content of the coating. This combined approach provides valuable insights for optimizing the jet electrodeposition process for Ni-diamond composite coatings with superior properties.

This qualitative research study is a part of a larger research project exploring the experiences of young caregivers aged 5-26 years and their families navigating the COVID-19 pandemic between 2020 to 2023. Data was collected from 14 young caregivers who participated in baseline interviews. The central research question guiding this study: What was, is, and will be the impact of changing public health restrictions on young caregivers and their families during the pandemic and pandemic recovery? Seven themes emerged through analysis: 1) Navigating Care During the Height of Public Health Restrictions, 2) Neighbourhood and Built Environment During the Pandemic, 3) Perceptions Towards COVID and Public Health Restrictions/Efforts, 4) The Impact of Public Health Restrictions on Relationships, 5) Mental Health Challenges of Being a Young Caregiver During a Pandemic, 6) Navigating Formal Services and Supports and 7) Recommendations from Young Caregivers. The findings from this empirical research suggest that young caregivers found it easier to navigate their caregiving responsibilities when public health restrictions and work-from-home mandates were initially implemented, however, this later changed due to challenges in finding respite from caregiving, maintaining social connections with friends, creating personal space at home, and finding adequate replacements of programs once offered in-person.

The influence of pH, temperature, biopolymer ratio, total concentration, and ionic concentration on the interaction between egg white protein (EWP) and chitosan (CS) was investigated through turbidity, zeta potential, and state diagram in our research. In addition, phase behavior was observed under various conditions. The turbidity of EWP remained low (turbidity<0.03) and basically unchanged at a wide range of pH (4.0-8.0), while the turbidity of CS was slightly higher (turbidity<0.2) after pH 7.0 than before. Moreover, under the same conditions, a sharply rising peak pattern was observed for the complex between EWP and CS. The maximum turbidity value was observed at 55°C, and the temperature had a mild effect on turbidity. The optimum EWP to CS ratio was found to be 12:1 based on the experiment of the turbidity curves and state diagrams influenced by different biopolymer mixing ratios. With the enhanced concentrations of total biopolymer, the maximum turbidity rose insignificantly above 0.1%.

Purpose:To explore (theoretically) the key parameters and their influence on the time profiles of photosensitizer (riboflavin), free radicals, singlet oxygen, oxygen and the efficacy of corneal collagen crosslinking (CXL)in both type-I and oxygen-mediated type-II mechanisms, specially the role of oxygen and the initiator regeneration. Methodology:Coupled kinetic equations are derived and numerically solved under the quasi-steady state condition for the 2-pathway mechanisms of CXL. The key parameters explored include (bI, V, Q', K, K',Q,P) and their influence on the time profiles of photosensitizer (riboflavin, C), radicals (R), singlet oxygen(S), oxygen (X) and efficacy (E), parameters of (K,K',Q) define the relative strength of type-I and type-II process. The oxygen depletion profile, X(t), and the associated singlet oxygen, S(t), depend on the parameters of V, Q' and the initial value of oxygen. The coupling strength given by (bI) governs almost all profiles, where b is an effective absorption parameter and I is the UV light intensity.Results:Our numerical method for CXL dynamic profiles demonstrated the following important features: (i) Type-I and type-II coexit in CXL, in the presence of oxygen. However, there is no type-II when oxygen is depleted or in a condition without oxygen. (ii) Type-I with bimolecular termination, the radical R(t) is a function of [K'(bIgC)]^0.5, leading to the steady-state efficacy given by a scaling law of 1/(bI)^0.5, in contract to that of type-II which is almost independent to the light intensity. (iii) The depletion rate (2 to 5 minutes) of X(t) is much faster than that of C(t) (10 to 20 minutes), (iv) Thepure type-II profile, has a transition point from straight line to saturating curve and matches the depletion point of singlet oxygen S(t). (v) Improved CXL efficacy of type-I and type-II may be achieved by external supply of photoinitiator (riboflavin) and oxygen, respectively.

Excessive nitrogen application has become a hidden danger threatening the sustainable development of agriculture. Exploring the potential genes will help to improve the nitrogen availability of wheat through molecular breeding. We therefore conducted wheat transcriptomics and proteomics researches under complete culture medium without nitrogen (N0) and complete culture medium with nitrogen (N1). The results showed that, the nitrogen deficit decreased the fresh weight, N content and net photosynthetic rate of winter wheat. 3949 and 2675 differentially expressed genes (DEGs) were identified in the shoot and root, respectively, while 164 and 129 differentially expressed proteins (DEPs) were identified in the shoot and root respectively. 9 genes in shoot and 26 genes in root showed the same trends in RNA and protein levels. 5 genes in shoot and 4 genes in root showed the opposite trends in RNA and protein levels. Pathway enrichment of wheat transcriptome and proteome under nitrogen deficit proposed 3 candidate genes related to photosynthesis in shoot, 4 candidate genes related to carbon metabolism in shoot, and 12 candidate genes related to carbon metabolism in root. Meanwhile, the chromosomal and subcellular localization of these genes were listed, which will provide reference for improving nitrogen availability through molecular breeding.

Ce-promoted NiMgAl mixed-oxide (NiCex-C, x = 0, 1,5,10) catalysts were prepared from the quaternary hydrotalcite precursors for CO2 hydrogenation to methane. By engineering the Ce contents, NiCe5-C showed its prior catalytic performance in low-temperature CO2 hydrogenation, being about 3 times higher than that of Ce-free NiCe0-C catalyst (TOF of NiCe5-C and NiCe0-C: 1.19 h-1 vs 0.39 h-1 @ 250 oC). With extensive characterization, it was found that Ce dopants promoted the reduction of NiO by adjusting the interaction between Ni and Mg(Ce)AlOx support. The higest ratio of surface Ni0/(Ni2+Ni0) was obtained over NiCe5-C. Meanwhile, the surface basicity was tailored with Ce dopants. The strongest medium-strength basicity and highest capacity of CO2 adsorption was achieved on NiCe5-C with 5wt% Ce content. The TOF tests indicated a good correlation with medium-strength basicity over the NiCex-C samples. The results showed that the high medium-strength and Ce-promoted surface Ni0 species endows the enhanced low-temperature catalytic performance in CO2 hydrogenation to methane.

Observe the synergistic effect and dose-effect relationship of Trimethoprim (TMP) on bactericidal activity with Flos Lonicerae in vitro. Microamount chessboard dilution method was conducted to determine the minimal inhibitory concentration (MIC) of Trimethoprim, Flos Lonicerae, as well as the combination of Trimethoprim and Flos Lonicerae separately against Staphylococcus aureus, Escherichia coli in vitro and Salmonella. The pour plate count method was used to determine the combined bactericidal activity of Flos Lonicerae combined with Different concentrations TMP. The results showed that the MIC values of the combination of Flos Lonicerae with TMP was much less than the MIC values of the independent use of Flos Lonicerae or TMP, The FIC values of the combination of Flos Lonicerae with TMP were between 0.5 and 1, there was additive effect between them. The bactericidal rates were fitted with least square method, the 95% confidence intervals of the optimal blending quantity about the combination of Flos Lonicerae with TMP on the test organisms were 231μg·mL^-1-249μg·mL^-1, 237μg·mL^-1-259μg·mL^-1, and 235 -259μg·mL^-1

The portal website of a university or a college usually represents the cultural characteristics and teaching advantages and plays a vital role in higher education, showing the style of the university or college to society and improving the admission rate. Mississippi State (MS) is bounded by the Mississippi River in the west and the Gulf of Mexico in the south, with a population of 3.1 million. It has a rich cultural heritage, and many universities, especially historically black colleges and universities (HBCUS), have strong scientific research strength in agriculture, medicine, petrochemicals and papermaking. Therefore, this article will analyze the design of the portal websites of four HBCUs in Mississippi from two aspects: user experience (UE) and functional architecture (FA), determine their advantages, disadvantages, similarities and differences, and propose some optimization suggestions.

Directed energy deposition (DED) is an efficient method to fabricate functionally graded materials (FGMs) with gradient composition and complex structures, allowing for local tailoring of properties instead of the costly need for extraneous welds and joints. In this study, a FGM from stainless steel to Inconel alloy was successfully fabricated using the powder-based laser DED. A very refined grain structure has been observed in at the composition with 75 wt.% Inconel alloy content, which also exhibits the highest (entropy). For the first time, the post heat treatments, microstructure and aging precipitation behaviors of FGMs were systematically studied via experimental characterization and computation, to elucidate their effects on the gradient smoothing and mechanical properties. The diffusion and segregation of Ni, Nb and Ti elements underly the transformation mechanism between Laves, δ, γ’ and γ’’ phases during precipitation. Homogenization on FGMs not only eliminates the heterogeneity inherited from the AM process, but also provides a practical way to smoothen the gradient on composition and microstructure for the eventual good gradient properties. It has a direct influence on the following precipitation behaviors in the FGM, which highly relies on the diffusion degree of the elements in the matrix and grain boundaries. The high-throughput thermodynamic modeling and kinetic modeling were exploited to evaluate the experimental microstructure and address computational uncertainty using different thermodynamic conditions and databases, which enables an accelerated design through local tailoring of process-structure-property relationships to develop new functional materials.

The human serotonin transporter (hSERT) terminates neurotransmission by removing serotonin from the synaptic cleft, which is an essential process plays an important role in depression. In addition to substrate serotonin, hSERT is also the target of drugs of abuse like cocaine and clinically used antidepressants such as escitalopram and paroxetine. To date, few studies attempt to investigate the unbinding mechanism underlying the orthosteric and allosteric modulation of hSERT. The high-resolution X-ray structure of hSERT resolved recently enables us to theoretically study the unbinding of the above four ligands against the S1 or S2 site of hSERT, by means of molecular docking, molecular dynamics (MD) and potential of mean force (PMF) simulations. We proved that for either the S1 or S2 site, the other three ligands (cocaine, escitalopram and paroxetine) are much more favorable than the original substrate serotonin, whether in kinetics along the unbinding pathways or in thermodynamics at the equilibrium states. Furthermore, the S1 site is much more favorable than the S2 site, for each ligand. Interestingly, inspection revealed that there are ~ 3Å lengths between the allosteric site of serotonin and cocaine, and an unseen un-binding pathway for escitalopram at the S1 site except for verification of the broadest trail.

Aero-fuel centrifugal pumps are important power plants in aero-engines. Unlike most of the existing centrifugal pumps, a combination impeller is integrated with the pump to improve its performance. First, the critical geometrical parameters of combination impeller and volute are given. Then, the effects of combination impeller on flow characteristics inside the impeller and volute are clarified by comparing simulation results with that of the conventional impeller, where the effectiveness of selected numerical method is validated by an acceptable agreement between simulation and experiment. Finally, the experiment is performed to test the external performance of studied pump. A significant feature of this study is that the flow characteristics are significantly ameliorated by reducing the flow losses emerged in impeller inlet, impeller outlet and volute tongue. Correspondingly, the head and efficiency of combination impeller are higher with comparison to conventional impeller. Consequently, it is a promising approach in ameliorating flow field and improving external performance by applying a combination impeller to an aero-fuel centrifugal pump.

Ti and its alloys are the most commonly used materials for biomedical applications. However, bacterial infection after implant placement is still one of the significant rising complications. Therefore, the application of the antimicrobial agents into implant surfaces to prevent implant-associated infection has attracted lots of attention. Scientific papers have shown that inorganic antibacterial metal element (e.g. Ag, Cu, Zn) can be introduced to implant surfaces with the addition of metal nanoparticles or metallic compounds into electrolyte via micro-arc oxidation (MAO) technology. In this review, the effects of the composition and concentration of electrolyte and process parameters (e.g. voltage, current density, oxidation time) on morphological characteristics (e.g. surface morphology, bonding strength), antibacterial ability and biocompatibility of MAO antimicrobial coating were discussed in detail. Anti-infection and osseo-integration can be simultaneously accomplished with the selection of the proper antibacterial elements and operating parameters. Besides, MAO assisted by magnetron sputtering (MS) to endow Ti-based implant materials with superior antibacterial ability and biocompatibility was also discussed. Finally, the development trend of MAO technology in the future was forecasted.

We report a simple and high-performance flexible strain sensor based on liquid metal nanoparticles (LMNPs) on polyimide substrate by laser induced deposition. The LMNPs were prepared by ultrasonic method, and then the femtosecond laser direct writing technology was used to induce the assembly and deposition of the LMNPs to form liquid metal microwires. Laser local sintering enhances the connection between particles, and a wearable strain sensor was fabricated with the high sensitivity as high as 76.18, the good linearity (a correlation coefficient of 0.999) in a wide sensing rage, the fast response/recovery time of 159 ms/120 ms. Attributed to these extraordinary strain sensing performances, the sensor can sense various dynamic strains in real time, monitor both subtle physiological activities and large human motions. It can be adhered to human skin, and well reflect the change of facial expression and realize real-time monitoring of facial expression. And the vocal cord vibration can be detected for speech recognition while the sensor attached to the outside of the throat.

With the increasing of copper consumption, the in-use stock of copper tends to increase. This paper used the “average use life method” to quantify the amount of copper in-use stock, and calculated the average age of in-use stock. It was indicated that the total in-use stock had an overall smooth trends, and reached its peak in 2007 was about 68.9 Mt (million tons), in addition, in-use stock per capita reached its peak ,234 kg/capita in 2001. The results demonstrated that during the period 1992-2002, the average age of copper in-use stock was continually decreased, but gradually increased since the year 2003. The fixed assets depreciation method used in this paper is applied to analyze depreciated copper in-use stock, and to analyze the relationship with economic indicator (GDP). It is demonstrated that it was inconsistent with the theory of Environmental Kuznets Curve (EKC) before 2000, this might be the demand for copper in the service sector is greater than the reduced strength of alternatives. Finally, scenario analysis of future copper in-use stock and depreciated copper in-use stock per capita in the U.S. were presented. The corresponding average age of the in-use stock will have a slight rise in the next decade.

With the rapid advancements in remote sensing technology, the spectral information from hyperspectral remote sensing images has become increasingly rich, facilitating detailed spectral analysis of the Earth's surface objects. However, this abundance of spectral data poses significant challenges in data processing, such as the curse of dimensionality leading to the “Hughes” phenomenon, "strong correlation" due to high resolution, and "non-linear characteristics" caused by varied surface reflectance rates. Therefore, dimensionality reduction of hyperspectral data has become a crucial task. This paper, grounded in manifold theory and manifold learning techniques, and considering the non-linear structures and features in hyperspectral remote sensing data, elucidates the principles and processes of dimensionality reduction in hyperspectral remote sensing images using manifold learning, with a formalized expression of the process. This article introduces spectral information divergence (SID) into the nearest neighbor graph computation of manifold learning algorithms. The principles and computational processes of nearest neighbor graph algorithms based on Euclidean distance (ED), spectral angle mapping (SAM), and SID are studied, and a comparative analysis of the dimensionality reduction effects under these three metrics in hyperspectral data is conducted. Experiments on feature extraction under different metrics were performed using the publicly available Indian Pines hyperspectral dataset. The intrinsic features obtained post-dimensionality reduction were used as inputs for classification algorithms in ground objects classification experiments, with algorithm runtime, overall accuracy, and Kappa coefficient as evaluation metrics for dimensionality reduction quality. The results demonstrate that nearest neighbor graph computation based on SAM and SID outperforms traditional ED methods; SAM-based computation has the lowest time complexity, while SID-based manifold learning yields the highest accuracy in ground objects classification. Thus, manifold learning based on SAM and SID metrics proves to be an effective method for feature extraction in hyperspectral remote sensing data, underscoring the potential of manifold learning techniques in the dimensionality reduction of hyperspectral remote sensing images.

It is always a difficult task to assign the peaks recorded from vibrational spectrum. Herein we explored a new pathway of density functional theory (DFT) simulation to present three kinds of spectra of ice XIV and can be referenced as inelastic neutron scattering (INS), IR, and Raman experimental spectrum. The INS spectrum is proportional to phonon density of states (PDOS) while the photon scattering signals reflect the normal vibration frequencies near the Brillouin zone (BZ) center. Based on good agreements with experimental data, we identified the relative frequency and made scientific assignments by normal vibration modes analysis. The debating two hydrogen bond (H-bond) peaks among ice phases from INS have been discussed and the dynamic process of H-bond vibrations were found to be classified into two basic modes. we deduce that two H-bond modes are a general rule among ice family and more works are ongoing to investigate this subject.

Although the Orthotropic steel decks (OSDs) have been widely used in the construction of long-span bridges, there are frequently reported fatigue cracks after years of operation, and the bridge deck overlay also presents severe damage due to OSD crack-induced stiffness reduction. The ultra-high performance concrete (UHPC), recognized as the most innovative cementitious composites and the next generation of high-performance materials, shows high strength, ductility, toughness and well performance on durability. After its first application to the OSD bridge in early 2000s, the orthotropic Steel-UHPC composite deck has been comprehensively studied worldwide. This review will summarize some important studies and findings on behavior and fatigue performance of orthotropic steel-UHPC composite deck. The existing studies and engineering application indicate that such deck system presents good bending behavior and high fatigue performance. The failure mode of shear studs in UHPC layer is dominated by shear fractures. The cracking of UHPC layer shall consider the superposition effect of stress from both the whole bridge structure and local decks. While some reasonable structural details in the traditional OSD may not work for the orthotropic steel-UHPC composite deck. It is recommended to evaluate the stress behavior and structural parameters, as well as fatigue life by conducting the field test under in-service traffic conditions.

This study aims to explore predictors of the foreign investment from China coming into Rwanda. One of the components of Rwanda’s economy is the investment it receives from other countries. In order to achieve these objectives, the study gathers econometric secondary data from 2007 to 2020 quarterly which were availably provided by National Statistics of China, World Bank, UNCTAD, National Institute of Statistics of Rwanda, and the National bank of Rwanda. From literature and based on the availability of data, market size, trade openness, infrastructure, and human capital were measured as predictors of Chinese FDI. The data is analyzed using linear regression in Stata. The finding of the study showed that variables have a positive effect on FDI from China, and it found that though FDI had an effect on overall economy of Rwanda, the effect was not statistically significant. The study suggested that Rwanda’s policy on foreign investment should aim to attract and encourage Chinese investment to increase the economy of Rwanda. To encourage more FDI, the Rwandan government can offer Chinese investors greater ownership, locational, and internalization benefits. It also should continue to strengthen economic policy transparency since it lowers transaction costs and hence improves incentives for foreign investment.

In view of the problem that the hot and cold loads of mushroom houses are affected by multiple factors such as environment, mushrooms, and equipment, which are difficult to accurately model, this paper proposes a short-term load prediction method based on empirical wavelet transform (EWT) and mixed autoregressive integrated moving average (ARIMA) and convolutional bi-directional short- and long-term attention mechanism (CNN-BiLSTM-Attention). The method first uses the Boruta algorithm to filter the input characteristics, and then uses the EWT method to decompose the mushroom house load data into 4 modal components. Then the Lempel-Ziv method is introduced to divide the modal components into two categories of high and low frequencies, and the CNN-BiLSTM-Attention and ARIMA prediction models are constructed separately. Finally, the two types of prediction results are superimposed and reconstructed to obtain the final load prediction value. The test results show that the Boruta algorithm can effectively filter out the characteristics of key influencing factors. Compared with the Spearman and Pearson correlation coefficient methods, the mean absolute error (MAE) of the prediction results is reduced by 14.72% and 3.75%, respectively; compared with the ensemble empirical mode decomposition (EEMD) method, the EWT method can increase the decomposition and reconstruction error by 103 orders of magnitude, which can effectively improve the prediction accuracy of the model; compared with the individual neural network model, the prediction effect of the model proposed in this paper has obvious advantages, and the MAE, root mean square error (RMSE) and mean absolute percentage error (MAPE) of the prediction results are reduced respectively. 31.06%, 26.52% and 39.27%.

This paper presents three types of tensor Conjugate-Gradient methods for solving large-scale linear discrete ill-posed problems based on the t-product between third-order tensors. An automatical determination strategy of a suitable regularization parameter is proposed for the tensor conjugate gradient (tCG) method. A truncated version and a preprocessed verion of the tCG method are further presented. The discrepancy principle is employed to determine a suitable regularization parameter. Several numerical examples are given to show the effectiveness of the proposed tCG methods in image and video restoration.

Abstract Plant uptake and assimilation of essential nitrogen compounds from the soil are mainly in the form of nitrate and ammonium ions. Plant nitrate transporters (NRTs) play a crucial role in nitrate uptake from the soil into the roots. NRT structural analysis reveals the mechanisms by which these transporters function. Similarly, plant ammonium transporters (AMTs) mediate the uptake of ammonium ions, and their structural analysis has provided valuable information on their mechanisms. After nitrogen uptake by plant roots, the nitrogen metabolism pathway involves the incorporation of nitrogen into organic compounds. Glutamine synthetase (GS) and glutamate synthase (GoGAT) are the master players in this pathway. They work together to convert ammonium ions into glutamine and glutamate, respectively. Different isoforms of GS and GoGAT exist, enabling plants to fine-tune nitrogen metabolism based on environmental cues. Under severe abiotic stress conditions, nitric oxide (NO) has been found to enhance plant survival under drought. Furthermore, the interaction between salinity stress and nitrogen availability in plants has been studied, with NO identified as a potential mediator of responses to salt stress. On the other hand, excessive use of nitrate fertilizers can lead to health and environmental issues. Therefore, alternative strategies, such as establishing nitrogen fixation in plants through diazotrophic microbiota, have been explored to reduce reliance on synthetic fertilizers. Ultimately, genomics can identify new genes related to nitrogen fixation, which could be harnessed to improve plant productivity. By deciphering the genetic basis of nitrogen-fixing traits, researchers aim to develop crops that efficiently utilize nitrogen from the environment.

With the aim to improve cladding coating quality and prevent cracking, this paper established an extreme high-speed laser cladding thermo-mechanical coupling simulation model to study the evolution of the temperature field and residual stress distribution. Process parameters that impacted the macroscopic morphology of single-pass coatings were investigated. Numerical calculations and temperature field simulations were performed based on the process parameter data to validate the effect of the temperature gradient and cooling rate on the coating structure and the residual stress distribution. The results showed that a good coating quality could be achieved using a laser power of 2400 W, a cladding rate of 20 m/min, and a powder feeding rate of 20.32 g/min. The coatings’ cross-sectional morphology corresponded well with the temperature distribution predicted by numerical modeling of the melt pool. The microstructure of the molten coatings is affected by the temperature gradient and cooling rate, which vary greatly from the bottom to the middle to the top. Maximum residual stress appears between the bonding region of the coatings and the substrate, and the coatings themselves have significant residual stress in the form of tensile strains that are mostly distributed in the direction of the laser cladding speed.

The aim of this paper is to use the elementary method and the properties of the second kind Stirling numbers to study the congruence properties of a new sequence, which is closely related to Fubini polynomials and Euler numbers, and give some interesting congruences for it. This solves a problem proposed by the first author at an unpublished paper.

This article presents, for the first time, the efficacy and curing depth analysis of photo-thermal dual polymerization in metal (Fe) polymer composites for 3D printing of a 3-component (A/B/M) system based on the proposed mechanism of our group, in which the co initiators A and B are Irgacure-369, and charge-transfer complexes (CTC), respectively; and the monomer M is filled by Fe. Our formulas show the depth of curing (Zc) is an increasing function of the light intensity, but a decreasing function of the Fe and photoinitiator concentrations. Zc is enhanced by the additive [B] which produces extra thermal radical for polymerization under high temperature. The heat (or temperature) increase in the system has two components : (i) due to the light absorption of Fe filler, and (ii) heat released from the exothermic photopolymerization of the monomer. The heat is transported to the additive (or co-initiator) [B] to produce extra radical R' and enhance the monomer conversion function (CF). The Fe filler leads to temperature increase, but also limits the light penetration leading to lower CF and Zc, which could be overcome by the additive initiator [B] in thick polymers. Optimal Fe for maximal CF and Zc are explored theoretically.

Under the development mode of deep blending of emerging technologies, major projects are important for enhancing China's comprehensive national strength and independent innovation capability. Based on the social benefits of major projects, and considering the influence of reputation factors, an evolutionary game model composed of a general contractor and subcontractor of major projects is established. This paper studies the influence of various factors including the income distribution coefficient of collaborative innovation, and MATLAB simulation software is analyzed the influence of factors on an evolutionary path. The results show that a reasonable income distribution coefficient can promote the game behavior of both parties to the direction of active collaborative innovation; The reduction of innovation cost and the improvement of spillover technology absorption capacity can make innovation subjects tend to choose active collaborative innovation strategies. In addition, reputation loss above a specific threshold can effectively inhibit free-riding behavior and encourage innovation subjects to choose active collaborative innovation strategies. The research results provide reference for promoting major projects' technology innovation.

Near-surface humidity (Qa) is a key parameter that modulates oceanic evaporation and influences the global water cycle. Remote sensing observations act as feasible sources for long-term and large-scale Qa monitoring. However, existing satellite Qa retrieval models are subject to apparent uncertainties due to model errors and insufficient training data. Based on in situ observations collected over the China Seas over the last two decades, a deep learning approach named Ensemble Mean of Target deep neural networks (EMTnet) was proposed to improve the satellite Qa retrieval over the China Seas for the first time. The EMTnet model outperforms five representative existing models by nearly eliminating the mean bias and significantly reducing the root-mean-square error in satellite Qa retrieval. According to its target deep neural networks selection process, the EMTnet model can obtain more objective learning results when the observational data are divergent. The EMTnet model was subsequently applied to produce a 30-year monthly gridded Qa data over the China Seas. It indicates that the climbing rate of Qa over the China Seas under the background of global warming are probably underestimated by current products.

Directional Modulation (DM) technique, as an emerging promising approach to secure wireless communications, has been attracting increasing attention for its unique characteristic in the past decade. The baseband signal is synthesized at the antenna level for maintaining the standard constellation format along the prescribed direction(s) while simultaneously distorting the signal constellations in other undesired directions. In this paper, we present a novel DM signal synthesis method based on phased array using a hybrid genetic algorithm (GA) and particle swarm optimization (PSO) algorithm, which takes advantages of both GA and PSO algorithm. Then, the bit error rate of the proposed method is analyzed and simulated. Simulation results are presented to verify that the proposed DM signal have a narrower information beam-width. Therefore, it can offer a better physical layer security (PLS) performance compared with the conventional directional modulation signal.

Visual question answering (VQA) is receiving increasing attention from researchers in both the computer vision and natural language processing fields. There are two key components in the VQA task: feature extraction and multi-modal fusion. For feature extraction, we introduce a novel co-attention scheme by combining Sentence-guide Word Attention (SWA) and Question-guide Image Attention (QIA) in a unified framework. To be specific, the textual attention SWA relies on the semantics of the whole question sentence to calculate contributions of different question words for text representation. For the multi-modal fusion, we propose a “Cross-modal Multistep Fusion (CMF)” network to generate multistep features and achieve multiple interactions for two modalities, rather than focusing on modeling complex interactions between two modals like most current feature fusion methods. To avoid the linear increase of the computational cost, we share the parameters for each step in the CMF. Extensive experiments demonstrate that the proposed method can achieve competitive or better performance than the state-of-the-art.

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.

A significant number of persons with coronavirus disease 2019 (COVID-19) experience persistent, recurrent, or new symptoms several months after the acute stage of severe acute respiratory syndrome coronavirus 2 (SARS‑CoV‑2) infection. This phenomenon, termed Post-Acute Sequelae of SARS-CoV-2 (PASC) or Long COVID, is associated with high viral titers during acute infection, a persistently hyperactivated immune system, tissue injury by NETosis-induced micro-thrombofibrosis (NETinjury), microbial translocation, complement deposition, fibrotic macrophages, the presence of auto-antibodies, and lymphopenic immune environments. Here, we review the current literature on the immunological imbalances that occur during PASC. Specifically, we focus on data supporting common immunopathogenesis and tissue injury mechanisms shared across this highly heterogenous disorder including NETosis, coagulopathy, and fibrosis. Mechanisms include changes in leukocyte subsets/functions, fibroblast activation, cytokine imbalances, lower cortisol, autoantibodies, co-pathogen reactivation, and residual immune activation driven by persistent viral antigens and/or microbial translocation. Taken together, we develop the premise that SARS-CoV-2 infection results in PASC as a consequence of acute and/or persistent single or multiple organ injury mediated by PASC determinants to include degree of host response (inflammation, NETinjury), residual viral antigen (persistent antigen) and exogenous factors (microbial translocation). Determinants of PASC may be amplified by co-morbidities, age, and sex. Keywords: long COVID, PASC, long haulers, NETosis, T cell, NK cell, DC, neutrophil,

Carpels are a reproductive feature restricted to angiosperms, therefore they are a focus of many botanical studies. However, there are controversies over the nature of carpels. A reason underly-ing these controversies is mixing implications given by conflicting interpretations on fossil carpels in early fossil angiosperms from the Cretaceous. These controversies hinder a clear understanding of angiosperm evolution and systematics. A key to these questions is older fossil fruits bearing concerned information. Here we report a new fossil fruit, Xenofructus dabuensis gen. et sp. nov, from the Middle Jurassic of Liaoning, China. Unlike previously reported fruits of early angio-sperms that were interpreted as bearing seeds either on adaxial or abaxial margin by various au-thors, our fossil demonstrates clearly that the seeds in Xenofructus are neither borne on the adaxial nor abaxial margin of the fruit, instead the seeds of Xenofructus are borne on an axis positioned between two margins. This new feature implies that a placenta in carpels is an ovule/seed-bearing axis, a carpel is a composite organ comprising an enclosing leaf (fruit wall) and an axis (placenta). The adaxial or abaxial position of ovules/seeds frequently seen in fossil and extant angiosperms is a consequence derived through long time evolution (coalescence of placenta with either margin of fruits). Carpels can be taken as foliar structures enclosing their associated ovulate branches.

A typical vibrational spectrum in the ice phase has four separate bands: translation, libration, bending and stretching. Ice X, the final ice phase under high pressure, shows an exotic vibrational spectrum. Theoretically, an ideal crystal of ice X only has one peak at 998 cm-1 for Raman scattering and two peaks at 450 cm-1 and 1507 cm-1 for infrared absorption in this work. These three characteristic peaks are indicators of the phase transition between ice VII/VIII and ice X. Despite much experimental and theoretical work on ice X, only this study has clearly indicated these characteristic peaks in the region of the IR band. The phonon density of states shows quite different features than ice VIII, which could be verified by inelastic neutron scattering in the future. The dynamic processes of 15 vibrational normal modes are discussed and the typical hydrogen bonds are missing.

Searching over a sorted list is a classical problem in computer science. Binary Search takes at most log2n+1 tries to find an item in a sorted list of size n. Interpolation Search achieves an average time complexity of Ο(loglogn) for uniformly distributed data. Hybrids of Binary Search and Interpolation Search are also available to handle data with unknown distributions. This paper analyzes the computation cost of these methods and shows that interpolation can significantly affect their performance — accordingly, a new method, Interpolation Once Binary Search (IOBS), is proposed. The experimental results show that IOBS outperforms the hybrids of Binary Search and Interpolation Search for nonuniformly distributed data.

Recently, the phase-sensitive OTDR (Φ-OTDR) based vibration sensor system has gained the focus of many researchers and some efforts have been undertaken to push further the limitations imposed on the performance of the Φ-OTDR sensor system. Then, progress in the different areas of its performance evaluation factors such as: improvement of the signal-to-noise ratio (SNR), spatial resolution (SR) in the sub-meter range, enlargement of the sensing range, frequency response bandwidth over the conventional limit and phase signal demodulation for quantitative measurement have been realized. This paper presents an overview of the recent progress in the Φ-OTDR based vibration sensing system in the different areas mentioned above.

The unique characteristics of frescoes on overseas Chinese buildings can attest to the integration and historical background of Chinese and Western cultures. Reasonable analysis and preservation of overseas Chinese frescoes can provide sustainable development for culture and history. This research adopts the image analysis technology based on artificial intelligence, and proposes a ResNet-34 model and method integrating transfer learning. This deep learning model can identify and classify the source of the frescoes of the emigrants, and can effectively deal with the problems such as the small number of fresco images on the emigrants' buildings, poor quality, difficulty in feature extraction, and similar pattern text and style. The experimental results show that the training process of the model proposed in this article is stable. On the constructed Jiangmen and Haikou fresco JHD datasets, the final accuracy is 98.41%, and the recall rate is 98.53%. The above evaluation indicators are superior to classic models such as AlexNet, GoogLeNet, and VGGNet. It can be seen that the model in this article has strong generalization ability and is not prone to overfitting. It can effectively identify and classify the cultural connotations and regions of frescoes.

Concrete cracks have a detrimental effect on the strength properties and durability of the structures. So, repairing of concrete cracks to recover their strength parameters is more important task in civil engineering. To repair concrete cracks, MICP has been widely analysed in recent times; but, zero research is conducted to deeply investigate the repair effects of MICP on concrete cracks with rough surface by using the theoretic model. In current research, MICP with a novel mathematical model was attained by taking the precipitation of calcium carbonate (CaCO3), ureolysis, suspended biomass, geochemistry, transport of solute and biofilm growth. Furthermore, crack repair experiments were performed to check the workability of the new mathematical method. The outcomes revealed that the designed suspended biomass concentrations in cracks diminished step by step. The comparison in between the experimental results and calculated results verified the precision of migration behaviour of the suspended biomass. At the inlet, the solute concentrations and biofilm volume fractions was higher, causing in rise of yield amounts for calcium carbonate. The consumed solutes concentrations were higher for cracks of less rough surface, ultimately causing in smaller sonic time; and the values of sonic time for upper portions of cracks was smaller, showing good repair impacts. The recommended mathematical model provides a better tool that controls repair time and microbial metabolism process to report a new adjustive, bioremediation and biomineralization to concrete, which could provide a firm base for remediation of material in civil engineering field.

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.

Based on the resource-based theory, the current study examines the relationship between competitive strategies and strategic alliance performance. Furthermore, big data predictive analytics is treated as a boundary condition between competitive strategies and strategic alliance performance. Big data of predictive analytics in operations and industrial management has been a focal point in the current era. There has been little attention has about big data predictive analytics influences on competitive strategies and strategic alliance performance, especially in developing countries like Pakistan. A survey instrument was used to record the responses from 331 employees of the telecom sectors companies working in Pakistan. Study findings show that big competitive strategies have a positive and significant relationship with strategic alliances performance. It was also found that big data predictive analytics plays the role of moderator between competitive strategies and strategic alliance performance. The study add a new perspective and contribution to the literature on big data predictive analytics, strategic alliance performance, and competitive strategies in Pakistan's telecom sector companies. Further, the study results explain that big data analytics is just like the companies' lifeblood in the current era. The efficient and effective use of big data analytics, companies can boost their standards in a competitive environment.

A large core size and bending resistance are very important properties of mid-infrared energy transfer fibers, but large core sizes usually lead to a deterioration of bending properties. A negative-curvature nested node-free anti-resonant hollow-core fiber (AR-HCF) based on quartz is proposed. It was made by adding a nested layer to a previous AR-HCF design to provide an additional anti-resonance region while keeping the gap between adjacent tubes strictly correlated to the core diameter to produce a node-free structure. These features improve the fiber’s bending resistance while achieving a larger core diameter. The simulation results show that the radial air-glass anti-resonant layer is increased by the introduction of the nested anti-resonant tube, and the weak interference overlap between the fiber core and the cladding mode is reduced, so the fiber core’s limiting loss and the sensitivity to bending are effectively reduced. When the capillary wall thickness t of the fiber is 0.71 μm, the core diameter D is 70 μm, the ratio of the inner diameter of the cladding capillary to the core diameter d/D is 0.62, and the diameter of the nested tube is d0=29 μm, the fiber has a lower limiting loss at the wavelength of 2.79 μm, and the limiting loss is 3.28×10-4 dB/m. At the same time, the optimized structure also has good bending resistance. When the bending radius is 30 mm, the bending loss is only 4.72×10-2 dB/m. To our knowledge, this is the first research to achieve an anti-bending low-loss micro-structure hollow fiber with a bending radius of less than 30 mm in the 2.79 μm band. An anti-bending low-loss anti-resonant hollow-core fiber with this structure constitutes a reliable choice for the light guiding system of a 2.79 μm band erbium laser therapy instrument.

Plant height is significantly correlated with grain traits, which is a component of wheat yield. The purpose of this study is to investigate the main QTLs that control plant height and grain-related traits in multiple environments. In this study, we constructed a high-density genetic linkage map using the Wheat50K SNP Array to map quantitative trait loci (QTLs) for these traits in 198 recombinant inbred lines (RILs). The two ends of the chromosome were identified as re-combination-rich areas in all chromosomes except chromosome 1B. The middle area of the chro-mosomes was identified as the recombination-barren area. Both the genetic map and the physical map showed a significant correlation when p=0.001, with a correlation coefficient between 0.63 and 0.99. However, there was almost no recombination between 1RS and 1BS. In terms of plant height, 1RS contributed to the reduction of plant height by 3.43cm. In terms of grain length, 1RS contributed to the elongation of grain by 0.11mm. A total of 43 QTLs were identified, including 8 QTLs for Plant height(PH), 11 QTLs thousand grain weight(TGW), 15 QTLs for grain length(GL),and 9 QTLs for grain width(GW), which explained 1.36%–33.08% of the phenotypic variation. Seven were environment-stable QTLs, including two loci Qph.nwafu-4B and Qph.nwafu-4D that determined plant height. The explanation rates of phenotypic variation were 7.39%-12.26% and 20.11%-27.08%, respectively. One QTL, Qtgw.nwafu-4B, which influenced TGW, showed an explanation rate of 3.43%-6.85% for phenotypic variation, two co-segregating KASP markers were developed, the physical locations corresponding to KASP_AX-109316968 and KASP_AX-109519968 were 25.888344 MB and 25.847691 MB. Another QTL, Qgw.nwafu-4D, which determined grain width, had an explanation rate of 3.43%-6.85%. Three loci that affected the grain length were Qgl.nwafu-5A, Qgl.nwafu-5D.2 and Qgl.nwafu-6B, illustrating the explana-tion rates of phenotypic variation as 6.72%-9.59%, 5.62%-7.75%, and 6.68%-10.73%, respectively. Two QTL clusters were identified on chromosomes 4B and 4D.

Biotic and abiotic factors influence the formation of fungal-algal pairings in lichen symbiosis. It is poorly known which factors determine the specific associations, especially when distantly related fungi are considered. Here, we investigated the effect of different drivers on the association patterns of taxonomically diverse lichenized fungi and their trebouxioid symbiotic partners. In 200 samples collected across three biomes, we found 41 species of lichenized fungi, associating with 16 species of trebouxioid green algae, of which 62% were previously unreported. Species identity of the fungal and algal partner had the greatest effect on the outcome of the symbiosis compared with abiotic factors such as climatic variables and geographic distance. Partner specificity was found to be higher in tropical regions than in temperate and arctic regions. Co-phylogenetic analyses indicated congruent phylogenies of trebouxioid algae and associated fungi, rejecting their random associations. Evolutionary mechanisms contributing most to the observed phylogenetic patterns were ‘loss’ and ‘failure to diverge’ of the algal partners. This study broadens our knowledge of fungi-algae symbiotic patterns in view of Trebouxia-associated fungi.

Coalbed Methane(CBM) production enhancement for single wells is a big problem to CBM industrialization. Low production is due to insufficient gas generation by thermogenic. Luckily, Biogenic gas was found in many areas and its supply is assumed to improve coalbed methane production. Therefore, microbial simulation experiment will demonstrate the effectiveness of the assumption. From microbial simulation experiment on different coal ranks, it is found that microbes can use coals to produce biogas under laboratory conditions. With different temperatures for different experiments, it turns out that the gas production at 35 ℃ is greater than that at 15℃,indicating that 35℃ is more suitable for microbes to produce gas. According to quantitative experiments, adding exogenous nutrients or exogenous bacteria can improve CBM production. Moreover, the production enhancement ratio can reach up to 115% under the condition of adding exogenous bacterial species, while the ratio for adding nutrients can be up to 144%.

The minimum dominating tree (MDT) problem consists of finding a minimum weight sub-graph from an undirected graph, such that each vertex not in this sub-graph is adjacent to at least one of the vertices in it, and the sub-graph is connected without any ring structures. This paper presents a Dual Neighborhoods Search (DNS) algorithm for solving the MDT problem, which integrates several distinguishing features, such as two neighborhoods collaboratively working for optimizing the objective function, a fast neighborhood evaluation method to boost the searching effectiveness, and several diversification techniques to help the searching process jump out of the local optimum trap thus obtaining better solutions. DNS improves the previous best-known results for 4 public benchmark instances while providing competitive results for the remaining ones. Several ingredients of DNS are investigated to demonstrate the importance of the proposed ideas and techniques.

The problem of health status prediction of insulated-gate bipolar transistors (IGBTs) gains a lot of attention in the field of health management of power electronic equipment. The performance degradation of IGBT gate oxide layer is one of the important failure modes. In view of failure mechanism analysis and easy implementation of monitoring circuit, this paper selects the gate leakage current of IGBT as the precursor parameter of gate oxide degradation, and uses time domain characteristic analysis, gray correlation degree, Mahalanobis distance, Kalman filter and other methods to carry out feature selection and fusion, and finally obtains a health indicator characterizing the degradation of IGBT gate oxide. Based on the Convolutional Neural Network and Long Short-Term Memory (CNN-LSTM) network, this paper constructs an IGBT gate oxide degradation prediction model, and performs experimental analysis on the dataset released by NASA-Ames Laboratory, and the average absolute error of performance degradation prediction is as low as 0.0216. Compared with Long Short-Term Memory (LSTM), Convolutional Neural Network (CNN), Support Vector Regression (SVR) and CNN-LSTM models, CNN-LSTM network has the highest prediction accuracy. These results show the feasibility of gate leakage current as a precursor parameter of IGBT gate oxide layer failure, as well as the accuracy and reliability of the CNN-LSTM prediction model.

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

Hepatitis B is a potentially life-threatening infectious disease caused by the hepatitis B virus (HBV), which affects the liver. Every year, about 390,000 people die from HBV-related diseases in China, about 86 million people are carriers of HBV, accounting for about 6% of the total population, and 30 million people are chronically infected. From 2002 to 2007, though China government launched “The Global Alliance for Vaccines and Immunization (GAVI)” program to reduce HBV infection in children, but the number of hepatitis B cases in China remains high. Reasonable estimation of potential HBV carriers is crucial to prevention and control the spread hepatitis B virus. This study is based on the case data from the National Bureau of Statistics of China from 2003 to 2021. We build a dynamic model that includes potential hepatitis B virus carriers, use nonlinear least squares and genetic algorithms to fit the parameters in the model, and calculate the reproduction number of hepatitis B virus transmission in the population and obtain R_c=1.741. The number of potential hepatitis B virus carriers is estimated to be 449,535 (95%CI [415651 to 483420]) based on our model, which is 30.49% of the total number of hepatitis B cases, and the simulation results show the number of chronic hepatitis B incidence decreases as the vaccination rate α increases, increasing α by 20%, the number of chronic hepatitis B incidence decreases by 169,469 on average.

The Drosophila spermatogenesis has the renewal of germline stem cells, meiosis of spermatocytes, and morphological transformation of spermatids into mature sperm. We previously demonstrated that Ocnus (ocn) plays an essential role in spermatogenesis. ValRS-m (Valyl-tRNA synthetase, mito-chondrial) gene was downregulated in ocn RNAi testes. By hatchability testing, we found that ValRS-m-knockdown induced complete sterility of male flies. We also concluded that ValRS-m-knockdown inhibited the transition from spermatogonia to spermatocytes and caused accumulated spermatogonia in testes. To understand the intrinsic reason for this destruction, we further conducted transcriptome sequencing analysis in ValRS-m RNAi testes. A total of 7710 dif-ferentially expressed genes (DEGs) were identified to have at least a 2-fold change with a p-value of

There are close dynamic relationships among the livelihood, well-being, and ecological environment of farm households. It is of great significance to scientifically clarify the impact of the grain for green policy on the livelihoods and well-being of farm households in mountainous areas. Based on data from a survey of 392 farm households in Zhangbei County, a system of indicators for farm household livelihood assets and farm household well-being was constructed, drawing on a sustainable livelihood framework (SLF). The livelihood assets and well-being levels of different types of farm households were measured, and a multiple linear regression model was used to analyze the impact of the grain for green policy implementation on the well-being levels of farm households. The three main results are as follows: (1) The level of natural assets among the total average livelihood assets of farm households in Zhangbei County is the highest at 0.374, while the level of physical assets is the lowest at 0.018. The level of livelihood assets of returned farmland households (0.948) is lower than that of nonreturned farmland households (1.117). (2) The level of well-being of all farm households in Zhangbei County is 0.517, with the level of wealth contributing the most to the well-being of farm households at 40.20% and the quality of the ecological environment contributing the least at 11.99%. The level of well-being of returned farmland households (0.518) was slightly higher than that of nonreturned farmland households (0.514). (3) The degree of influence of each influence factor on the level of well-being of farm households varies significantly. Household size was the strongest driver, at 0.366, while educational attainment of household members, household labor capacity, annual household expenditure, livelihood diversity, number of large production tools, and total value of livestock were also important drivers of household well-being, and area of arable land is negatively associated with household well-being. There are also differences in the factors influencing the level of well-being of different types of farming households.

To effectively estimate airport terminal area capacity and assess the maximum throughput the sector can achieve when the capacity is given, this research proposes an approach to assess the terminal area capacity from the viewpoint of service provision resources. Terminal area capacity is optimized based on the equilibrium of air traffic service resource supply and demand. The supply-demand nexus is examined in consideration of terminal area route structure, traffic flow characteristics, and safety regulations. A flight service probability matrix and a terminal area demand and supply service time model are constructed to quantify resource expenditure at varied capacity levels. A optimization model is then developed to apportion maximal capacity under resource limitations. Model computation and computation results demonstrate the deviation between estimated and amended capacities is under 0.3 flight sorties per hour. The outcomes are congruent with historical statistics, thereby validating the accuracy and reliability of the model proposed in this study. Given capacity parameters, the model can deduce the maximal aircraft quantity served concurrently in terminal areas during peak periods. These revelations indicate the submitted model furnishes theoretical foundation and reference for terminal area sector partition and traffic alerting.

Deposition/printing of materials with sub-1 μm precision and size (cross sections) is required for optical and electrical micro-devices. Crystalline c-ITO (Indium tin oxide) nanostructures were patterned on glass with a precision that formed gaps of 20-50 nm between individual disks or lines of ∼ 250 nm diameter or width. The absorbed energy density [J/cm3] followed the second order dependence on pulse energy. This facilitated high resolution and precision for nanoscale laser writing at the 515 nm laser wavelength. Patterns for optical elements such as circular gratings and micro-disks were laser printed using ITO as a resist. Unexposed amorphous a-ITO was chemically removed in aqueous 1% vol. HF solution. This use of a-ITO as solid-resist is promising for metamaterial and micro-optical applications.

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

In our article in Genome Biology Ecology six years ago, one complete plastid genome of Belian was assembled for comparative analyses of the plastomes in Lauraceae. However, Ariati et al. (2023) concluded that our sequenced Belian individual could be located in the clade of Myristicaceae instead of that of Lauraceae. Here, we performed re-analyses of additional two Belian plastomes, along with 42 plastomes from plants spanning ten families of the Magnoliids. The plastomes of the three Belian individuals range from 157,535 to 157,577 bp in length. Comparative genomic analysis revealed 170 mutation sites in their plastomes, which include 111 substitutions, 53 indels, and six microinversions. Phylogeny was reconstructed using maximum likelihood and Bayesian approaches for 44 magnoliids species indicated that our three Belian individuals are nested among the species in the family Lauraceae rather than Myristicaceae.

The impacts of inflation on international finance are generally reflected in the decline of buying power, risks of investment and deposit loss from currency devaluation. For the purpose of optimized allocation and management of asset values, i.e., annual income or research grants, a framework of a three-level model for static financial management is presented to maximize banking interests, bonuses, and the remaining balance after spending necessary expenditures. Meanwhile, in retrospect to higher-level financial inflation, strategies of dynamic investment, i.e., posing regular tests of flipping coins, exploiting variations of the currency exchange rate, as well as applying the theory of broad money, are presented to increase the appreciation rate of net assets in and post the era of COVID-19. Quantitative evaluations in case studies verify the feasibility of improving the financial situation, indicating broader applications for budgeting and investing when US inflation rate is below 3.0%. Besides, combining approaches of static and dynamic strategies, the expected annual growth rate of individual zero-risk asset investment is predicted as within the range of 8.30~9.62% according to budgeted appreciation on net assets in 12 months, which is capable of overcoming negative impacts from higher level annual inflation, i.e., those as highest as 8.01% in the Year 2022.

With the rapid development of Internet of Things (IoT)-based near-earth remote sensing technology, the problem of network intrusion for near-earth remote sensing systems has become more complex and large-scale. Therefore, it is essential to seek an intelligent, automated, and robust network intrusion detection method. In recent years, network intrusion detection methods based on graph neural networks (GNNs) have been proposed. However, there are still some practical issues with these methods. For example, they have not taken into consideration the characteristics of near-earth remote sensing systems, the state of the nodes, and the temporal features. Therefore, this article analyzes the characteristics of existing near-earth remote sensing systems and proposes a spatio-temporal graph attention network (N-STGAT) that considers the state of nodes. The proposed network applies spatiotemporal graph neural networks to the network intrusion detection of near-earth remote sensing systems and validates the effectiveness of the proposed method on the latest flow-based dataset.

Background: The association between the individual and combined effects of moderate-to-vigorous physical activity (MVPA) and sleep quality with physical frailty in community-dwelling older adults is still unknown. Subjects and Methods: A cross-sectional study was conducted with a participants pool comprising older adults who had not been officially assessed as requiring nursing care or support services.. Physical frailty was assessed using Liu's definition based on Fried's concept. MVPA was measured by a triaxial accelerometer, and individuals who meet either MPA for ≥300 min/week, VPA for ≥150 min/week, or both of them were defined as "MVA+." "SLP+" was defined as a Pittsburgh Sleep Quality Index score <5.5 points. We performed an ordinal logistic regression analysis to calculate the odds ratios (ORs) and 95% confidence intervals (CI) regarding the relationship between MVPA and sleep quality with physical pre-frailty and frailty. Results: The final analysis included 811 participants. After multivariate adjustment, compared to the MVA+SLP+, the MVA−SLP+ (OR 2.56, 95%CI: 1.80–3.62) and the MVA−SLP− (OR 3.97, 95%CI: 2.33–6.74) participants showed significantly higher ORs for physical pre-frailty and frailty. Conclusion: Community-dwelling older adults who did not meet MVPA criteria, regardless of sleep quality, had a higher risk of physical pre-frailty and frailty.

The phenomenon of seat occupancy in university libraries is a prevalent issue. However, existing solutions, such as software-based seat reservations and sensors-based occupancy detection, have proven to be inadequate in effectively addressing this problem. In this study, we propose a novel approach: a serial dual-channel object detection model based on Faster RCNN. Furthermore, we develop a user-friendly web interface and mobile APP to create a computer vision-based platform for library seat occupancy detection. To construct our dataset, we combine real-world data collection with UE5 virtual reality. The results of our tests also demonstrate that the utilization of personalized virtual dataset significantly enhances the performance of the convolutional neural network (CNN) in dedicated scenarios. The serial dual-channel detection model comprises three essential steps. Firstly, we employ Faster RCNN algorithm to determine whether a seat is occupied by an individual. Subsequently, we utilize an object classification algorithm based on transfer learning, to classify and identify images of unoccupied seats. This eliminates the need for manual judgment regarding whether a person is suspected of occupying a seat. Lastly, the web interface and APP provide seat information to librarians and students respectively, enabling comprehensive services. By leveraging deep learning methodologies, this research effectively addresses the issue of seat occupancy in library systems. It significantly enhances the accuracy of seat occupancy recognition, reduces the computational resources required for training CNNs, and greatly improves the efficiency of library seat management.

Intelligent systems are increasingly present in various areas of society, gaining special relevance in healthcare environments. In this work, grounded on previous developments proposed by the authors, the evolution and improvement of a novel intelligent system focused on the diagnosis of obstructive sleep apnea (OSA) is addressed. To do this, starting from two packages of information of a heterogeneous nature, and deploying a set of Machine Learning classification algorithms, focused each of them on different levels of the apnea-hypopnea index (AHI), as well as a set of cascaded expert systems, it is possible to obtain a series of risk metric pairs (Statistical Risk, Symbolic Risk) for each AHI level, understood as a warning forecast associated with the early detection of the pathology. The risk indicators of each pair are subsequently aggregated by means of a symbolic inference system, whose knowledge base was determined using the automatic rule generation approach proposed by Wang and Mendel. At the output of each inference system, a risk indicator is obtained for each AHI level, the Apnea Risk, whose interpretation makes it possible to discriminate between patients who could suffer OSA and those who do not, as well as to generate the appropriate recommendations. For the initial tests of the system, the design and development of a specific software artifact was carried out using data from 4,400 patients from the Álvaro Cunqueiro Hospital in Vigo, obtaining when applied to the test set AUC values within the range 0.74–0.88, which invites optimism and points to the benefits expected from the architecture of the proposed intelligent system.

Plants of the genus Monochoria have long been utilized in food, cosmetics, and traditional herbal treatment. Thailand has the highest species diversity of this genus and a new member, Monochoria angustifolia (G. X. Wang) Boonkerd & Tungmunnithum has been recently described. This plant is called “Siam Violet Pearl” as a common name or “ไข่มุกสีม่วงแห่งสยาม” as its vernacular name in the same meaning in Thai language. Despite their importance, few researches on Monochoria species have been conducted. This study, thus, provided the results to fill in this gap by: i) determining flavonoids phytochemical profiles of 25 natural populations of M. angustifolia covering the whole floristic regions in Thailand, and ii) determining antioxidant activity using various antioxidant assays to investigate the probable mechanism. The results revealed that M. angustifolia presented a higher flavonoid content than the outgroup, M. hastata. Our results also revealed that flavonoids might be used to investigate Monochoria evolutionary connections and for botanical authentication. The various antioxidant assays revealed that M. angustifolia extracts preferentially act through a hydrogen atom transfer antioxidant mechanism. Pearson correlation analysis indicated significant correlations emphasizing that the antioxidant capacity is most probably the result of a complex phytochemical combinations rather than of a single molecule. Altogether, these results showed that this new species provide an attractive alternative starting material with phytochemical variety and antioxidant potential for the phytopharmaceutical industry.

The active power-assist function greatly expands the potential applications of exoskeleton robots, yet the motion intention estimation (MIE) for active power-assist strategy is quite problematic. Through the analysis of the conduction path and the different stage manifestations of motion intention in human body, we confirmed that the joint torque of human body meets the basic requirements of MIE for the active power-assist that we suggest, namely: (i) it reflects the direction and intensity of the wearer’s efforts; (ii) it precedes the human limb motion; (iii) it generates real-time and continuous output. Thus, an online calculation method of human joint torque was proposed. The sensing system integrated in exoskeleton robots was designed to perceive motion data and foot contact force of a human body. A special inverse dynamics with a parameterized model of the human body was proposed. Contrast experiments were carried out with the motion capture system, which results’ accuracy and similarity were evaluated via the root mean square error and correlation coefficient. The comparative analysis of two synchronous results shows good accuracy of the proposed MIE method, which lays the foundation for the realization of active power-assist.

Mesoporous TiO2/reduced graphene oxide/Ag (TiO2/RGO/Ag) ternary nanocomposite with effective electrons transfer pathway is obtained by an electrostatic self-assembly method and photo-assisted treatment. Compared with bare mesoporous TiO2 (MT) and mesoporous TiO2/RGO (MTG), the ternary mesoporous TiO2/RGO/Ag (MTGA) nanocomposite exhibited superior photocatalytic performance for the degradation of MB under visible light, and the degradation rate reached 0.017 min-1, which was 3.4 times higher than that of MTG. It is proposed that Ag nanoparticles can form the local surface plasmon resonance (LSPR) to absorb the visible light and distract the electrons into MT, and RGO can accept the electrons from MT to accelerate the separation efficiency of carriers. The establishment of MTGA ternary nanocomposite make the three components act synergistic effect to enhance the photocatalytic performance.

Understanding the thermal cracks of rock caused by high temperature is of great help to the development of underground engineering, such as geothermal mining, underground coal gasification. Although there has been many study on thermal cracking, it is not systematic and in-depth enough. In order to deeply study the thermal crack mechanism of rock, this paper conducted thermal cracking experiments on granite at different temperatures and heating/cooling paths, and qualitative and quantitative analysis was conducted on the crack initiation characteristics, propagation paths, and crack network morphology of rock thermal crack under different test conditions. The thermal crack mechanism was also analyzed from the perspectives of mineral petrology, fracture mechanics, thermodynamics, and other aspects. The research results show that there are two obvious mutation points in the study temperature range for samples with fast cooling paths (SF path: slow heating and fast cooling; FF path: fast heating and fast cooling), around 200-300 ℃ and 600 ℃, respectively, while for samples with slow cooling paths (SS path: slow heating and slow cooling; FS path: fast heating and slow cooling), there is only one mutation point around 600 ℃. The initiation positions of thermal cracking under all temperature paths are relatively similar, with intergranular crack located between particles at the edge of the sample or intercrystalline crack in the middle of feldspar or quartz aggregates. The initiation temperature of SF and FF path specimens is relatively low compared to SS and FS path specimens, and the number and size of cracks is small. The crack network structure formed by the SF path is the most complex, with the largest crack ratio and cumulative crack length; The crack network structure formed by the FF path is relatively complex, with a larger main crack size but relatively fewer secondary cracks; The FS and SS paths do not form a complex network with good connectivity. The process of thermal crack development can be divided into three stages: the development of small cracks, the joint development of main cracks and small cracks, and the connection of cracks into a network structure. The mechanism of thermal crack propagation is that the expansion and thermal conductivity between different crystals are different. The thermal stress caused by temperature gradient and the tension or shear stress caused by the inconsistent deformation of crystals form stress concentration in weak areas such as particles boundary, cleavage, and original cracks. Firstly, it causes some crystals with smaller strength or less rounded shape to crack, and when the combined stress is large, the cracks will gradually expand along the existing fine cracks. This also explains that the most main cracks of the SF and FF path specimens mainly surround some large mineral aggregates or between particles.

Solidification cracking is a major obstacle when joining dissimilar alloys using additive manufacturing. In this work, location-specific solidification cracking susceptibility has been investigated using an integrated computational materials engineering (ICME) approach for a graded alloy formed by mixing P91 steel and Inconel 740H superalloy. An alloy derived from a mixture of 26 wt.% P91 steel and 74 wt.% Inconel 740H, with high configurational and total entropy, was fabricated using wire-arc additive manufacturing. Microstructure characterization revealed intergranular solidification cracks, which increased in length along with the build height. With inputs from experiments, such as secondary dendrite arm spacing, the DICTRA (diffusion-controlled transformations) module within the Thermo-Calc software was used to model location-specific solidification cracking susceptibility. The top region, with the highest cooling rate, has the highest solidification cracking susceptibility and is in good agreement with the experimentally observed crack length. From Scheil simulations, it was deduced that pronounced segregation of Nb and Cu within the cracks increased the solidification range by suppressing the solidus temperature. The overall solidification cracking susceptibility and freezing range was highest for the 26 wt.% P91 alloy amongst the mixed compositions between P91 steel and 740H superalloy, proving that solidification characteristics play a major role in alloy design for additive manufacturing.

The spectra and global distributions of the X-ray emissions generated by the solar wind charge-exchange (SWCX) process in the terrestrial magnetosheath are investigated based on a global hybrid model and a global geocoronal hydrogen model. The solar wind O6+ ions which are the primary charge state for oxygen ions in solar wind are considered. The line emissivity of the charge-exchange born O5+ ions are calculated by Spectral Analysis System for Astrophysical and Lab oratory (SASAL). It is found that the emission lines from the O5+ ranges from 105.607 to 118.291 eV with the strong line at 107.047 eV. We then simulated the magnetosheath X-ray emission intensity distributions with a virtual camera at two positions of north pole and dusk at six stages during the passing of a perpendicular interplanetary shock combined with a tangential discontinuity structure through the Earth’s magnetosphere. During this process, the X-ray emission intensity increases with time, and the maximum value is 27.11 keV cm-2 s-1 sr-1 on the dayside, which is 4.5 times that before the solar wind structure reaches the Earth. A clear shock structure can be seen in the magnetosheath and moves earthward. The maximum emission intensity seen at dusk is always higher than that seen at north pole.

Fiber coupling efficiency is one of the key technical indicators of atmospheric laser communication, which directly affects the communication system BER. According to the optical fiber coupling efficiency model, the optical fiber coupling model under atmospheric slant link is established, and the relationship between wavelength, zenith angle, receiving aperture, altitude and coupling efficiency is studied through numerical simulation. Based on the principle of adaptive optics turbulence correction, the relationship between fiber coupling efficiency and adaptive optics order is established. A fast method for estimating the coupling efficiency based on Strehl ratio is proposed. According to the principle of laser communication system, the semi-physical simulation experimental system of atmospheric slant-range channel coupling efficiency is constructed, and the coupling efficiency test and analysis are completed.

Coal mining has caused a significant loss of nitrogen content of soil in mining areas. This article studies the effects of organic fertilizer, inorganic fertilizer, and combined application of Pseudomonas fluorescens with the ability of nitrogen fixation on soil nitrogen accumulation and composition in the reclamation area of Tunlan Coal Mine from 2016 to 2022 under the condition of equal nitrogen application, providing scientific basis for microbial fertilization and rapid increase of nitrogen content in the reclaimed soil of mining areas. The results showed that as the reclamation time increased, the nitrogen content and its composition structure of the soil treated with fertilization rapidly evolved towards normal farmland soil. The soil nitrogen content increased the fastest in the treatment of Pseudomonas fluorescens + organic fertilizer (MB), compared with inorganic fertilizer (CF), organic fertilizer (M), and Pseudomonas fluorescens + inorganic fertilizer (CFB) treatments, the treatment of Pseudomonas fluorescens + organic fertilizer (MB) can bring the total nitrogen (TN) content of the soil to normal farmland soil levels 1-3 years earlier. The comprehensive scores of Pseudomonas fluorescens + organic fertilizer (MB) and Pseudomonas fluorescens + inorganic fertilizer (CFB) on the two principal components were increased 1.58 and 0.79 than those of organic fertilizer (M) and inorganic fertilizer (CF) treatments, respectively. This further indicates that the combination of Pseudomonas fluorescens and organic fertilizer has a better effect on improving soil nitrogen accumulation than the combination of Pseudomonas fluorescens and inorganic fertilizer. At the same time, the application of Pseudomonas fluorescens will increase the content of unknown nitrogen (UN) in acid-hydrolysable nitrogen (AHN), and decrease the content of amino acid nitrogen (AAN) and ammonia nitrogen (AN), relatively. However, there was no significant effect on the content of ammonium nitrogen (NH4+-N) and nitrate nitrogen (NO3--N) in soil inorganic nitrogen (SMN). When combined with inorganic fertilizer, the contribution of soil mineralized nitrogen (SMN) to total nitrogen (TN) increased by 14.78%, while when combined with organic fertilizer, the contribution of acid-hydrolysable nitrogen (AHN) to total nitrogen (TN) increased by 44.77%. In summary, the use of Pseudomonas fluorescens is beneficial for nitrogen recovery in the reclaimed soil of coal mining areas. The optimal fertilization method under the experimental conditions is the combination of Pseudomonas fluorescens and organic fertilizer.

Synthetic Aperture Radar (SAR) is an active sensor that uses microwave for sense, it is unrestricted by weather and illumination conditions, and it can observe targets all day and weather. Aircraft targets are important monitoring objects in military and civilian fields, and how to efficiently detect and recognize aircraft targets is an important topic in the field of SAR image interpretation. Based on the features of SAR images, such as complex background, high resolution, and multi-scale, we proposed an improved method based on YOLOv5s. Firstly, this paper proposed the structure of the multi-scale receptive field and channel attention fusion, which is applied to the shallow layer of the backbone of YOLOv5s, it can adjust the weights of the multi-scale receptive field during the training process to enhance the extraction ability of feature information. Secondly, we proposed four de-coupled detection heads to replace the original part in YOLOv5s, which can improve the efficiency and accuracy of SAR image interpretation for small targets. Thirdly, in the case of the limited amount of SAR images, this paper proposed multi methods of data augmentation, which can enhance the diversity and generalization of the network. Fourthly, this paper proposed the K-means++ to re-place the original K-means to improve the network convergence speed and detection accuracy. Finally, Experiments demonstrate that the improved YOLOv5s can enhance the accuracy of SAR image interpretation by 9.3%, and the accuracy of small targets is improved more obviously, reaching 13.1%.

The log interpretation and evaluation of Chang 8 tight sandstone reservoir in Longdong West area, Ordos Basin, is facing great challenges due to the existence of low resistivity contrast oil pays. To better guide the exploration of oil resources in this area, the characteristics and control mechanism of low resistivity contrast oil pays were studied in this research. Firstly, according to the relative value of apparent resistivity increase rate of the target formation, the reservoir was divided into two types: low resistivity contrast oil pay (LRCP) and high resistivity oil pay (HRP). Then, the reservoir characteristics were studied by comparing and analyzing the experimental data, formation water data and logging data collected from the two reservoir types. On this basis, the control mechanism of LRCP was studied and summarized into reservoir micro factors and regional macro factors, respectively. It is found that the reservoir rock composition between LRCP and HRP is basically the same. Compared with HRP reservoir, the average porosity and permeability of LRCP reservoir are relatively better, but the pore structure is relatively poorer because of the high content of micro pores. When the filling pressure of crude oil is sufficient enough, the high oil saturation can be formed in LRCP reservoir. The high irreducible water saturation and high formation water salinity are the main micro factors reduced the reservoir resistivity. Besides, the difference of hydrocarbon expulsion capacity of source rock and the regional difference of formation water salinity are the macro factors influenced the distribution of LRCP and HRP from vertical and horizontal of the region. The formation of LRCP is controlled by the comprehensive influence of reservoir micro factors and regional macro factors. And the comprehensive consideration of the influence of micro factors and macro factors on LRCP is suggested during the log interpretation and evaluation.

The main idea of this paper is to investigate the exact solutions and dynamic properties in optical nanofibers, which is modeled by space-time fractional perturbed nonlinear schr\"odinger equation involving Kerr law nonlinearity with conformal fractional derivative. Firstly, by the complex fractional traveling wave transformation, the traveling wave system of the original equation is obtained, then a conserved quantity, namely the Hamiltonian is constructed, and the qualitative analysis of this system is conducted via this quantity by classifying the equilibrium points. Moreover, the prior estimate of the existence of the soliton and periodic solution is established via the bifurcation method. Furthermore, all exact traveling wave solutions are constructed to illustrate our results explicitly by the complete discrimination system for polynomial method.

The retinoblastoma (RB) transcriptional corepressor 1 (RB1) is a critical tumor suppressor gene, governing diverse cellular processes implicated in cancer biology. Dysregulation or deletion in RB1 contributes to the development and progression of various cancers, making it a prime target for therapeutic intervention. RB1's canonical function in cell cycle control and DNA repair mechanisms underscores its significance in restraining aberrant cell growth and maintaining genomic stability. Understanding the complex interplay between RB1 and cellular pathways is beneficial to fully elucidate its tumor-suppressive role across different cancer types and for therapeutic development. As a result, investigating vulnerabilities arising from RB1 deletion-associated mechanisms offers promising avenues for targeted therapy. Recently, several findings highlighted multiple methods as a promising strategy for combating tumor growth driven by RB1 loss, offering potential clinical benefits in various cancer types. This review summarizes the multifaceted role of RB1 in cancer biology and its implications for targeted therapy.

Yellow nanorod Mg-MOF-74 was obtained by solvothermal synthesis method. XRD、N2 adsorption-desorption isotherms、SEM and TGA results suggest that the particle size of Mg-MOF-74 reaches 400 nm after the introduction of sodium acetate in the precursor of Mg-MOF-74. Besides, the morphology of Mg-MOF-74 was changed from cauliflower to rod particles. At the same time, the BET specific surface area and pore volume of Mg-MOF-74 were also increased a lot. Then the CO2 dynamic adsorption capacity of Mg-MOF-74 was measured by self-made fix bed under 30 ℃、0.1 bar CO2 partial pressure. The results show that the CO2 adsorption capacity of Mg-MOF-74-N2 reaches 3.67 mmol/g and its CO2 adsorption capacity remains unchanged after 10 times CO2 adsorption-desorption cycles.

The key links of face recognition are digital image preprocessing, facial feature extraction and pattern recognition, this article aimed at the current problem of slow speed and low recognition accuracy of face recognition , from the above three key links, on the basic of analyzing the therories of Fractional Differential Masks Operator (FDMO), Principal Component Analysis (PCA) and Support Vector Machine (SVM), design a kind of FDMO+PVA+SVM coupling algorithm that applies to face recognition to improve the speed and accuracy of it. To realize FDMO+PCA+SVM coupling algorithm, first, we should apply FDMO to face image processing binary marginalization, the purpose is getting face contour; Then, we apply PCA to get the feature of face image which is disposed by binary marainalization. At last, we can apply One-Against All of the SVM classifier and LibSVM software package to realize face recognition. Beside, the article with nine different coupling algorithm design four groups of experimental reaults on the ORL face database verified by comparative analysic FDMO+PCA+SVM coupling algorithm in the superiority of face recognition accuracy and speed.

Arylsulfatase and β-glucuronidase are two important enzymes in human, which play important role on dynamic equilibrium of steroidal estrogens. This work probably for the first time reported that hydrogen peroxide (H2O2), hypochlorite and peracetic acid (PAA) could effectively inhibit the activities of arylsulfatase and/or β-glucuronidase. The 50 percent of inhibitions (IC50) of H2O2, and PAA on arylsulfatase were found to be 142.90±9.00, 91.83±10.01, and 43.46±2.92 μM, respectively. The corresponding respective IC50 of hypochlorite and PAA on β-glucuronidase were 704.90±41.40 and 23.26±0.82 μM, while H2O2 showed no inhibition on β-glucuronidase. It was further revealed that the inhibition of hypochlorite on both arylsulfatase and β-glucuronidase was irreversible. On the contrary, the inhibition by H2O2 and PAA was reversible. Moreover, it was found that the inhibitions of arylsulfatase and/or β-glucuronidase by these three chemicals were pH-dependent, among which the inhibition by H2O2 was competitive and non-competitive for PAA. In general, H2O2 and hypochlorite can be endogenously produced in human, which suggested that the two compounds are potential endocrine disruption compounds (EDCs) as they can cause endocrine disruption via inhibition of arylsulfatase and β-glucuronidase. This work further indicated that any agent that can induce production of H2O2 or hypochlorite in human is potential EDC, which explains why some EDCs with very weak or no estrogenic potency can cause endocrine disruption that confirmed in epidemiological studies.

Forest-grass intercropping patterns of protected cultivation has been widely used to increase productivity and sustainability in modern agriculture. However, there have been few studies of wolfberry (L. barbarum) intercropping and it is cultivated mostly by clean tillage. This paper takes 10 kinds of wolfberry-forage intercropping patterns, compares the effects of different planting modes on the growth, yield, photosynthetic characteristics, nutritional quality, and the degree of occurrence of diseases and pests, which aims to make clear the effects of wolfberry-forage intercropping patterns on wolfberry. The results showed that different intercropping combinations had different effects on wolfberry. The overall effect of Wolfberry-forage intercropping patterns on the growth of wolfberry were promote the photosynthetic characteristics. Ryegrass could increase the branch number, Lvyuan 5 and mangel increase branch length; Mangel, clover, sweet sorghum, ryegrass and stipas could reduce the damage of powdery mildew by 69%, and alfalfa, stipa and ryegrass could reduce the occurrence of aphids by 67% (P<0.05). Intercropping could increase carotenoids, flavonoids and ascorbic acid contents to improve wolfberry quality by 21%, 53% and 127%, respectively (P<0.05). Among all the performances, wolfberry-mangel intercropping has absolute advantages in promoting wolfberry yield and quality increase. Therefore the best patterns of wolfberry-mangel, wolfberry-ryegrass, wolfberry-alfalfa and wolfberry-clover were chosen.

In the process of oil and gas development and production, when the flow rate in the wellbore is large, the materials underground will be eroded, causing the operation to be unable to proceed smoothly and reducing the efficiency of oil and gas production. Therefore, optimizing the anti-erosion coating under high-speed flow conditions in wellbore is a very interesting thing. It can greatly improve operational efficiency. In this paper, laser cladding was used to prepare the new coating used in the PDC drill bit. Then, the effects of tungsten carbide and multi-layer graphene on the microstructure and properties of the tungsten carbide coating were studied. The research results indicate that, for new coatings, 60% tungsten carbide and 0.3% graphene are the optimal ratios. After adding WC, the hardness has significantly improved. However, when the WC content further increases more than 30%, the increase in hardness is relatively small. In addition, when the content of graphene is more than 0.3%, the branched structure became thicker, and not only the segregation of Cr, Si and W became very obvious again, but also the segregation of Fe occurred at the Ni enrichment site. The research results contribute to improving oil and gas production and operational efficiency under high-speed fluid flow conditions in the wellbore.

As an important support for power system with high penetration of renewable energy, energy storage system (ESS) has changed the traditional model of simultaneous implementation of electricity production and consumption, and its installed capacity under the source-grid-load scenario is rising year by year, but it faces the problems of insufficient utilization and benefits. This study analyzes the functional combination of ESS under the source-grid-load scenarios, and proposes a comprehensive benefit evaluation method of energy storage projects based on fuzzy decision-making trial and evaluation laboratory (DEMATEL) and super efficiency data envelopment analysis (DEA) model, which considers the perspective of economic and social environment. Firstly, the functional requirements of energy storage on the source-grid-load scenarios are explored respectively, and the characteristics of various functions are analyzed to form functional combination schemes. Secondly, index modeling is carried out from three aspects: the whole life cycle cost, functional combination benefit and social environmental benefit, and the comprehensive benefit evaluation index system of energy storage project is proposed, which includes both economic and social environment. Then, the intuitionistic trapezoidal fuzzy number is combined with DEMATEL to form an effective analysis method for the input-output relationship of the indexes, and the comprehensive evaluation is realized based on the super efficiency DEA model. Finally, the effectiveness of the proposed evaluation method and the rationality of the functional combination are verified under source-grid-load scenarios respectively.

Time series ground deformation monitoring and reservoir parameter inversion are crucial for the dynamic assessment of oilfield resources and sustainable exploitation in an oilfield. As one of the regions with the richest oil reserves in China, the oilfield areas in the western Qaidam Basin are selected as a typical study area. Firstly, we used SAR images collected by the Sentinel-1A satellite from January 2021 to December 2022 and applied the Multidimensional Small Baseline Subset (MSBAS) method to obtain vertical and east-west deformation measurements. On this basis, a nonlinear Bayesian inversion method was applied to model the shallow reservoir in a series of complex deformation areas, based on a single-source model and a multi-source model, respectively. As a result, the ground deformation monitoring results obtained by long time series InSAR clearly reflect the uneven ground deformation caused by the oil extraction and water injection operation process. There is slight subsidence in the Huatugou oilfield, while significant uplift deformation occurred in the Ganchaigou oilfield and the Youshashan oilfield, with a maximum uplift rate of 48 mm/year. Further analysis indicates that the introduction of the 2D deformation field helps to improve the robustness of oilfield reservoir parameter inversion. Moreover, the dual-source model is more suitable than the single-source model for inverting complex deformation reservoir parameters. This study not only fills the blank of InSAR deformation monitoring for the oilfields in the western Qaidam Basin but also provides a theoretical reference for model and method selection of reservoir parameter inversion in other oilfields.

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.

Sea cucumber detection represents a significate step in underwater environmental perception, which is an indispensable part of the intelligent subsea fishing system. However, various complex factors such as water turbidity declines the clarity of underwater images, presenting a challenge to vision-based underwater target detection. Therefore, accurate, real-time and lightweight detection models are required. First of all, the development of subsea target detection is summarized in this presented work. Besides, since target detection methods based on deep learning such as YOLOv5 and DETR, which are respectively examples of one-stage and anchor-free deep leaning methods, have been increasingly applied in underwater detection scenarios. Based on the analysis of state-of-the-art underwater sea cucumber detection approaches and aiming to provide a reference for practical subsea identification, the sea cucumber detection based on the YOLOv5 and DETR are investigated and compared in detail. For each approach, the detection experiment is carried out on the derived dataset which contains a wide variety of sea cucumber sample images. The compared experiments demonstrate that the overall outperformance of YOLOv5 in terms of low computing consumption and high precision, particularly in detection of small and dense features. Nevertheless, the DETR exhibits rapid development and holds promising prospects in underwater object detection applications, owing to its relatively simple architecture and ingenious attention mechanism.

Chrysoeriol (CHE) is a flavonoid substance that exists in many plants and has various physiological and pharmacological effects, including anti-inflammatory, antioxidant, anti-tumor, and protective activity, especially for the cardiovascular system and liver. This study aimed to analyze the results and possible mechanisms of CHE on early porcine embryo development. Adding CHE to the culture media can improve the development quality of early porcine embryos. CHE significantly increased the blastocyst rate and total cell number of embryos in vitro. The apoptosis of blastocyst in CHE-treated culture also decreased significantly compared with untreated culture. Furthermore, CHE downregulated intracellular reactive oxygen species (ROS) and increased glutathione (GSH) in embryos. CHE was also shown to improve the activity of mitochondria and inhibit the occurrence of autophagy. In addition, antioxidant-related genes (SOD1, SOD2, and CAT) and cell pluripotency-related genes (SOX2, OCT4, and NANOG) were upregulated, while those related to apoptosis (Caspase 3) and autophagy (LC3B) showed a downward trend after supplementation with CHE. These results indicated that CHE improved the development of porcine embryos in vitro by reducing oxidative stress and autophagy levels.