Sinojackia Hu. comprises five to eight Chinese endemic species with high ornamental and medicinal value. However, the generic limits, interspecific relationships and evolutionary history of the genus remain unresolved. In this study, we newly sequenced and assembled three plastomes of S. oblongicarpa and compared them with those of the other congeneric species to explore the taxonomic delimitation of the species and the evolutionary history of the genus. Plastomes structure of Sinojackia species were extremely conserved in terms of number of genes, sequence length and GC content. Codon usage patterns revealed that natural selection may be the main factor shaping codon usage bias. Our phylogenetic tree shows that Sinojackia is monophyletic and can be divided into two clades. Sinojackia oblongicarpa as a distinct species is supported for it is distantly related to S. sarcocarpa. The evolutionary analysis of morphological features indicates that woody mesocarp is an ancestral feature, while mesocarp undeveloped, spongy and fleshy are the later derived. Sinojackia originated in Central-Southeast China during the early Miocene. In this period, it experienced elevated diversification and migrated from the Central-Southeast China to Hunan Province and Sichuan Province with the development of the Asian monsoon and East Asian flora. Sinojackia experienced elevated diversification at intraspecies levels that mainly occurred in the Quaternary. Glacial-interglacial interactions with the monsoon climate may provide favorable expansion conditions for Sinojackia on a small-scale.

This paper studies the impact of agricultural subsidies and product certification on the use rate of green pesticides based on experimental economics. We found that agricultural subsidies effectively increased the utilization rate of green pesticides. If the agricultural subsidies raised from 20% to 100%, the green pesticides’ using rate increased by 438.51%. We also found that product certification increased the utilization rate of green pesticides by 376.16%%.The increase of agricultural subsidies is more effective than the product certification. Under a higher proportion of agricultural subsidies, farmers’ behavior will maintain “status bias”. Therefore, there are three suggestions proposed. Firstly, because of high price of green pesticides and lower production, the subsidies for agricultural materials should raise greatly to effectively improve the utilization rate of green pesticides. It is recommended that green pesticide provided free of charge in some wealthy areas. Secondly, both subsidies and product certification can improve the use rate of green pesticides. However, since the effect of agricultural subsidies is better than product certification, and farmers may have status bias. Therefore, it is recommended to give priority to the substantial increase on the proportion of agricultural subsidies, and then to product certification.

Optical tweezers, as a kind of ultra-sensitive acceleration sensing platform, show a minimum measurable value inversely proportional to the square of the diameter of the levitated spherical particle. However, the coupling of the displacement measurement between axes becomes notable, along with the increasing of the diameter. This paper analyzes the source of coupling in a forward scattering far-field detection regime and proposes a novel method of suppression. We theoretically and experimentally demonstrated that when three variable irises added into detection optics, without changing other parts of optical structures, the decoupling of triaxial displacement signals mixed with each other show significant improvement. The detection coupling ratio reduction of 49.1 dB and 22.9dB has been realized in radial and axial direction respectively, which is principally in accord with simulations. This low cost and robust approach makes it possible to accurately measure three-dimensional mechanical quantities simultaneously and even go further such as active cooling the particle to quantum ground state.

Successful geophysical exploration works in Gucheng-Yaxi area located in Gaochun District, Jiangsu province, China, have been limited partly due to complex geological condition of the area and high artificial noise in data acquired using electrical and electromagnetic methods. In this work, we deployed the new anti-interference spread spectrum induced polarization method (SSIP) and audio magnetotellurics (AMT) method to detect a copper-polymetallic deposit in the area. Two-dimensional (2D) inversion results at Gucheng-Yaxi Area revealed a high chargeability anomalous zone on SSIP profile that coincided with a zone of moderate resistivity located between two resistor bodies on AMT profile. A follow up 1200 meters drill hole was established at this high chargeability-moderate resistivity zone which encountered polymetallic (copper, lead, zinc, gold and silver) mineralization at the depth ≥ 400 m. Drill hole data analysis showed that mineralization occurs interspaced in marble rock mass at varies depth. Furthermore, several low resistivity-weak chargeability sections were revealed and inferred attributed to Cretaceous sediments and faults. These faults are thought to have played critical role in the polymetallic mineralization genesis. In summary, this work demonstrated the successful of application of SSIP and AMT at detecting a metallic deposit in an area with high artificial noise. Hence the geophysical prospection potential of Gucheng-Yaxi area is great.

Cannabinoid metabolites have been reported to be more potent than the parent compounds. Among them, Ajulemic acid (AJA) is a synthetic analogue of Δ9-THC-11-oic which will be a good template structure for discovery of more potent analogues. Herein, we optimized the key allylic oxidation step to introduce the C-11 hydroxy group with high yield. And a series of compounds were prepared with this condition applied including HU-210, 11-Nor-Δ8-Tetrahydrocannabinol-9-carboxylic acid and Δ9-THC-COOH.

Nitric oxide (NO) is synthesized and is involved in various physiological and developmental process regulation in all kingdoms of life. Fungi have been less explored in terms of endogenous NO biology than mammals, plants, and bacteria. In this review, we summarize and discuss the studies to date on intracellular NO biosynthesis and function in fungi. Two mechanisms for NO biosynthesis, NO synthase (NOS)-mediated arginine oxidation, and nitrate and nitrite reductase-mediated nitrite reduction, are most frequently reported. Furthermore, we summarize the multifaceted functions of NO in fungi, as well as its role as a signaling molecule in fungal growth regulation, development, abiotic stress, virulence regulation, and metabolism. Finally, we present potential directions for future research on fungal NO biology.

HU is the Hypergeometrical Universe Theory (HU)[1-8], proposed in 2006, where the Universe is a Lightspeed Expanding Hyperspherical Hypersurface and Gravitation is an absolute-velocity-dependent, epoch-dependent force. Here we introduce the Big Pop Cosmogenesis and show our calculations associated with the Equation of State of the Universe. This article is the first in a series of articles[9-22] supporting the paradigm shift.

Lipid dysregulation is critically involved in hepatocellular carcinoma (HCC). Further, male predi-lection and Ras pathway hyperactivation are distinct characteristics of HCC. However, mecha-nisms underlying their connections remain unknown. The aim of the present study was to perform a comprehensive lipidomics analysis of a Hras12V transgenic mice (Ras-Tg) model of HCC induced by hepatocyte-specific Ras pathway activation and characterized by male predilection and a dis-rupted lipid metabolism. A total of 3437 lipids were identified in HCC (T) and peri-tumor tissues (P) of Ras-Tg mice and liver tissues of wild-type mice (W) of both sexes. Longitudinal comparisons of W, P, and T yielded 359 differentially expressed lipids (DELs) in male mice and 306 DELs in female mice. Generally, glycerolipid accumulation, glycerophospholipid reduction and monounsaturated fatty acid synthesis improvement were more frequent in T compared to P. The expression change pattern analysis revealed common and characteristic DELs positively/negatively associated with HCC or the Ras oncogene. Further lipid metabolism pathway investigations revealed that disordered lipid and fatty acid biosynthesis contributed to glycerolipid accumulation and glycerophospholipid re-duction in T. Comparisons between P and W suggests that different responses to the Ras oncogene in mice of different sexes, as well as higher amounts of aberrantly regulated lipids in males, may contribute to male-biased hepatocarcinogenesis. However, lateral comparisons between sexes showed a converging trend during hepatocarcinogenesis, explaining the poor efficacy for gen-der-specific therapies. In conclusion, the common and characteristic DELs and lipid metabolism pathways in HCC initiated by the Ras oncogene from sexually dimorphic hepatocytes provide novel insights into the clinical diagnosis and management of HCC.

Temperature and pressure sensors currently encounter challenges such as slow response times, large sizes, and insufficient sensitivity. To address these issues, we developed tetraphenylethylene (TPE)-doped polyvinylidene fluoride (PVDF) nanofiber membranes using electrospinning, with process parameters optimized through a convolutional neural network (CNN). We systematically analyzed the effects of PVDF concentration, spinning voltage, tip-to-collector distance, and flow rate on fiber morphology and diameter. The CNN model achieved high predictive accuracy, resulting in uniform and smooth nanofibers under optimal conditions. Incorporating TPE enhanced the hydrophobicity and mechanical properties of the nanofibers. Additionally, the fluorescent properties of the TPE-doped nanofibers remained stable under UV exposure and exhibited significant linear responses to temperature and pressure variations. The nanofibers demonstrated a temperature sensitivity of -0.976 gray value/°C and pressure sensitivity with an increase in fluorescence intensity from 537 a.u. to 649 a.u. under 600 g pressure. These findings highlight the potential of TPE-doped PVDF nanofiber membranes for advanced temperature and pressure sensing applications.

Nucleoid-associated proteins (NAPs) play an architectural role by bending, bridging, and wrapping the DNA along with a regulatory role of controlling various transcriptional units in the cell. Previews reviews have highlighted the role of HU and its paralog IHF plays in intracellular function as a transcriptional regulator, nucleoid bending protein and sometimes also moonlights in other functions. This review highlights along with the canonical functions of HU and IHF which affects genes responsible for translational machineries, cell wall biosynthesis, aerobic respiration and virulence ; other non-canonical roles which HU plays outside the cellular milieu, notably in acting as an adhesin and playing role in host-cell adhesion, its role in biofilm architecture and its association with cationic low complexity region, resembling histone like H1 proteins. HU and IHF thus has evolved as a hub protein performing a vast type of functions which makes it a important drug target for antibacterial therapy.

A reinforcement learning algorithm is proposed to improve the accuracy of short-term load forecasting (STLF) in this article. The proposed model integrates radial basis function neural network (RBFNN), support vector regression (SVR), and adaptive annealing learning algorithm (AALA). In the proposed methodology, firstly, the initial structure of RBFNN is determined by using SVR. Then, an AALA with time-varying learning rates is used to optimize the initial parameters of SVR-RBFNN (AALA-SVR-RBFNN). In order to overcome the stagnation for searching optimal RBFNN, a particle swarm optimization (PSO) is applied to simultaneously find promising learning rates in AALA. Finally, the short-term load demands are predicted by using the optimal RBFNN. The performance of the proposed methodology is verified on the actual load dataset from Taiwan Power Company (TPC). Simulation results reveal that the proposed AALA-SVR-RBFNN can achieve a better load forecasting precision as compared to various RBFNNs.

In order to sustain the marine environment relationship between the environmental factors and marine biota must be investigated. This study aims to study such a correlation in the adjacent waters of Nan Wan Bay, Kenting, Taiwan, and to explore the covariance of environmental factors on marine life (whether they enhance or diminish it). To achieve these objectives, factor analysis was used to identify potential latent variables that could affect the water quality of the adjacent waters, including phytoplankton (quantity), zooplankton (quantity), and fish (quantity and species). These potential variables were named based on the results of past studies and related literature. Finally, a structural equation model (SEM) was constructed to establish a marine ecological model among the potential variables. The factor analysis results revealed that nutrients, upwelling, and primary productivity are the primary factors affecting the environmental changes in the adjacent waters of Nan Wan Bay. The comprehensive SEM showed that nutrients and primary productivity significantly impact plankton. Path analysis indicated that primary productivity has the highest direct effect on the phytoplankton cluster. However, the upwelling has a low significance in its effect on phytoplankton, zooplankton, and fish clusters. Compared to the results of past related studies, the SEM proposed in this study can reflect a considerable degree of change in the waters.

Under the dual background of underemployment and health inequality, this paper empirically analyzes the impact of education level on underemployed workers’ health based on CLDS2016 data. The results show that underemployment is significantly related to the decline of self-rated health, increased depression tendency, and morbidity in a certain period. The results indicate that underemployment can significantly reduce the health level of workers in the low education level group and the high education level group. However, it has no significant impact on workers’ health in the middle education level group; even if we change the measurement method of indicators and consider endogeneity, the research conclusion is still robust. Moreover, this kind of health inequality mainly comes from the difference in economic effect and leisure effect of underemployment to workers with different educational levels. This paper provides empirical support for increasing the labor protection mechanism of underemployed people and reducing the health inequality caused by educational level differences.

Omicron SARS-CoV-2 variants have dominated the strains of COVID-19 circulating worldwide for the last two years. Although the mortality rate of the COVID-19 Omicron variants is only approximately half that of previous variants, vaccines effective against Omicron are needed. Demonstrating that a SARS-CoV-2 vaccine can protect against Omicron in an in vivo infection model, particularly in that of Syrian hamsters, is important for the preclinical characterization of SARS-CoV-2 vaccines. Here, we report on the evaluation of W-PreS-O for its ability to protect Syrian hamsters against infection by Omicron. W-PreS-O is a chimeric vaccine based on a single fusion protein (W-PreS-O), combining RBDs from Wuhan hu-1 wild-type and Omicron adsorbed to aluminum hydroxide. The Syrian hamsters were immunized three times at three-week intervals with W-PreS-O or with aluminum hydroxide (placebo), and then they were infected with Omicron BA.1. Non-infected and non-vaccinated animals served as controls. Neutralizing antibody (nAB) titers, weight, lung symptoms (i.e., edema and pneumonia index), and viral loads, as measured using RT-PCR in the upper and lower respiratory tracts, were determined. In addition, infectious virus titers from the lungs were measured using a plaque-forming assay. W-PreS-O-vaccinated hamsters developed robust nABs against Omicron, showed almost no development of pneumonia, and had significantly reduced infectious virus titers in the lungs. Importantly, the viral loads in the nasal cavities of W-PreS-O-vaccinated hamsters were close to or above the PCR cycle threshold considered to be non-infectious. Our data provide compelling evidence demonstrating that the W-PreS-O vaccine has protective effect against Omicron in a Syrian hamster in vivo infection model. W-PreS-O is therefore a highly promising candidate vaccine for Omicron infections, and it should be further evaluated in clinical studies.

At present, there are still no specific therapeutic drugs and appropriate vaccines for Dengue. Therefore, it is very important to explore distinct clinical diagnostic indicators. In this study, we combined differentially expressed genes (DEGs) analysis and weighted co-expression network analysis (WGCNA) to screen a stable and robust biomarker which can be used to distinguish three clinical stages of Dengue and severity of Dengue. CD38 can distinguish excellently Early Acute, Late Acute, Convalescent stages for Dengue patients, and ZNF595 can discriminate DHF from DF in whole acute stages. We also found that three clinical stages can be discriminated based on the fractions of Plasma cells, activated memory CD4+ T cells, and Monocytes. In different clinical stages different immune cells function positively. Negative inhibition of viral replication based on Gene Ontology (GO) enrichment, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis and Gene set enrichment analysis (GSEA), up-regulated autophagy genes and impairing immune system are potential reasons resulting in dengue hemorrhagic fever (DHF).

Molecularly imprinted polymers (MIPs) were synthesized and applied for the selective extraction of oblongifolin C (OC) from fruit extracts of Garcinia yunnanensis Hu. A series of experiments and computational approaches were employed to improve the efficiency of screening for optimal MIP systems in the study. The molar ratio (1:4) was chosen at last based on the comparison of the binding energy of the complexes between the template (OC) and functional monomers using density functional theory (DFT) at the RI-PBE-D3-gCP/def2-TZVP level of theory. The binding characterization and the molecular recognition mechanism of MIPs were further explained using the molecular modeling method and NMR and IR spectra data. The reusability of this approach was demonstrated in over 20 batch rebinding experiments. 140.5 mg of OC (>95% purity) was obtained from the 5 g extracts with 2 g of MIPs with the best binding properties through gradient elution program from 35% to 70% methanol-water solution. At the same time, another structural analog, 46.5 mg of guttiferone K (GK) (>88% purity), was also obtained by the gradient elution procedure. Our results showed that the structural analogs could be separated from the crude extracts by the molecularly imprinted solid-phase extraction (MISPE) using a gradient elution procedure for the first time.

Photovoltaic(PV) power generation is highly nonlinear and stochastic. Accurate prediction of PV power generation plays a crucial role in grid connection as well as the operation and scheduling of power plants. To predict the PV power combination model, this paper suggests a method based on Empirical Mode Decomposition (EMD), Ensemble Empirical Mode Decomposition (EEMD), Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN), Nonlinear Auto-Regressive Neural Networks with Exogenous Input (NARXNN), Long Short Term Memory (LSTM) Neural Network, and Light Gradient Boosting Machine (LightGBM) algorithms. To attempt to reduce the non-smoothness of PV power, the weather variable features with the greatest effect on PV power are first identified by correlation analysis. Following this, the PV power modal decomposition is split and reorganized into a new feature matrix. Finally， a NARX is used to obtain preliminary PV power components and residual vector features， and the PV power is predicted by combining three models of LightGBM， LSTM, and NARX and then the final prediction results are obtained by combining the PV power prediction results using error inverse method weighted optimization. The prediction results demonstrate that the model put forth in this paper outperforms those of other models and validate the model's validity by utilizing real measurement data from Andre Agassi College in the United States.

The testing of high-dimensional normality has been an important issue and has been intensively studied in literatures, it depends on the Variance-Covariance matrix of the sample, numerous methods have been proposed to reduce the complex of the Variance-Covariance matrix. The principle component analysis(PCA) was widely used since it can project the high-dimensional data into lower dimensional orthogonal space, and the normality of the reduced data can be evaluated by Jarque-Bera(JB) statistic on each principle direction. We propose two combined statistics, the summation and the maximum of one-way JB statistics, upon the independency of each principle direction, to test the multivariate normality of data in high dimensions. The performance of the proposed methods is illustrated by the empirical power of the simulated data of normal data and non-normal data. Two real examples show the validity of our proposed methods.

In this work, the Ni/Ti/Nb multilayer composite was successfully manufactured by accumulative pack-roll bonding. The microstructure evolution and mechanical properties of the composite during the accumulative roll bonding (ARB) process were investigated by scanning electron microscopy(SEM), energy dispersive spectrometer(EDS), transmission electron microscopy (TEM), micro-hardness and tensile tests. The results showed that after 5 passes of the ARB process, the deformations of layers were relatively uniform, and no large number of interlayer fractures occurred. The microstructures of Ni and Ti were both equiaxed grains with a grain size of 200 nm and 150 nm, respectively, and finer equiaxed grains of the Ni layer were observed at the interface. The laminar structure of Nb layer was observed. The tensile strength and micro-hardness increased significantly as the number of ARB increased. After 5 passes of the ARB process, the tensile strength of the composite reached 792.3 MPa, and the micro-hardness of Ni, Ti, and Nb were increased to 270.2, 307.4, and 243.4 HV, respectively.

The resilience of towns and cities refers to their ability to adapt and recover when confronted with pressures or challenges. This study employs ten variables as indicators to assess the resilience of urban areas by analyzing official data and constructing a multilevel mixed-effects structural equation model. The empirical findings demonstrate that enhancing resilience significantly influ-ences urban service functions, such as strengthening healthcare systems, stabilizing the real estate market, and addressing socio-economic challenges. Specifically, factors such as healthcare re-sources, housing demand, population structure, and social security exhibit varying levels of resil-ience, which profoundly impact the spatial distribution of these factors and socio-economic de-velopment. Disparities in healthcare resource allocation, demographic aging trends, and shifts in the housing market closely correlate with resilience levels in different regions. Additionally, the study emphasizes that improving resilience not only boosts the reliability and security of urban services but also ensures that communities receive necessary support and protection during times of adversity. Consequently, policymakers should recognize the pivotal role of urban resilience in resource allocation and social equity, devising corresponding strategies to enhance the resilience of these areas.

Background: Evidence suggests that children and young people (CYP) who present to the emergency department (ED) for mental health (MH) difficulties may have extended lengths of stay (LOS); however, there is a paucity of research in Australia regarding the factors associated with extended LOS. This study aimed to determine the factors associated with extended LOS for paediatric MH-related presentations to the EDs in South Western Sydney (SWS), a multicultural community in Australia. Methods: We analysed electronic medical records (eMR) of 7,409 MH-related ED encounters of CYP aged 0 up to 18 years from all six public hospitals in SWS from January 2016 to April 2022. Extended LOS was defined as encounters of more than 4 hours. We assessed factors associated with extended LOS using a multilevel logistic regression model, accounting for hospital-level clustering. Results: Approximately 57.6% of all ED presentations for paediatric MH involved extended LOS. ED presentations by adolescents (adjusted odds ratio (AOR) 2.23, 95% CI 1.20-4.17 for 12-14 years and AOR 2.69, 95% CI 1.44-5.00 for 15-17 years), and patients with a preferred language other than English (AOR 1.47, 95% CI 1.15-1.89) had increased odds of extended LOS compared to their counterparts. Deliberate self-harm related presentations, the most commonly presented MH condition, had higher odds of extended LOS than other MH-related presentations (AOR 1.77, 95% CI 1.59-1.98). Patients with MH presentations that required urgent evaluation (triage levels 1-2) had higher odds of extended LOS (AOR 1.38, 95% CI 1.15-1.65) compared to triage level 3, whereas those with triage levels 4-5 had lower odds (AOR 0.66, 95% CI 0.58-0.74). Further, patients with MH-related presentations that came by ambulance (compared to other mode of presentations) and presentations that happened at night and late at night (compared to early morning and daytime presentations). The odds of extended LOS were considerably lower during the COVID-19 period compared to the pre-COVID-19 period (AOR 0.74, 95% CI 0.67-0.82). Additionally, extended paediatric LOS for MH issues in the ED showed notable hospital-level heterogeneity. Conclusion: A large proportion of extended LOS in ED and sociodemographic disparities reflect inequality in access to paediatric MH care. Our findings highlight the need for equitable distribution of resources directed towards at-risk CYP to improve MH outcomes and reduce health system burden.

Integrated Fixed Film Activated Sludge (IFAS) technology greatly enhances nitrogen removal effectiveness and treatment capacity in municipal wastewater treatment plants, addressing the issue of limited land availability. Hence, this method is appropriate for treating household wastewater from office buildings. The research was conducted at the wastewater treatment plant in an office building in Ho Chi Minh City, Vietnam. Experiments were conducted to ascertain the most favorable working conditions, including Hydraulic Retention Time (HRT), alkalinity dosage, and Dissolved Oxygen (DO). According to the study, the IFAS system had the highest nitrogen removal effectiveness when operated at a hydraulic retention time (HRT) of 7 hours, an alkalinity dose of 7.14 mgCaCO3/mgN-NH4+, and a dissolved oxygen (DO) value of 6 mg/L. The nitrification efficiency ranges from 89.2% to 98.8%. The nitrate concentration post-treatment is within the range of 27 – 45 mg/L, which is lower than the allowable discharge limit of 60 mg/L as per Vietnam's wastewater discharge requirements. The research findings have enhanced the efficiency of the office building management process, thereby promoting the sustainable growth of society.

It was believed that the construction of large dams in the upper tributary basin of the Chao Phraya River (CPR) has caused sediment load reduction in the CPR system by 75–85%. Based on historical and observed river flow and sediment data measured during 1922–2019, we investigated the effects of three large dams, the Sirikit, Naresuan, and Khwae Noi dams, on river runoff and sediment loads supplied to the CPR using Mann-Kendall (MK) test and the double mass curve (DMC). Results from this study revealed that the Nan River contributed approximately 40% and 57% of the runoff and total sediment load (TSL) to the CPR, respectively. The water regulation by the Naresuan diversion dam has mainly caused the reduction on annual runoff and TSL downstream of each dam. The results from this study also reveal that the sediment load observed at the headwater (C.2) of the CPR still increased after the construction of the Sirikit dam due to the expansion of irrigation areas downstream of the dam and the channel improvement in the lower reach of Nan River. After the three major dams were operated, the sediment load at C.2 reduced by 31% compared that discharging during the pre-construction period.

A fundamental question in biology is how cell shapes are genetically encoded and enzymatically generated. Prevalent shapes among walled bacteria include spheres and rods. These shapes are chiefly determined by the peptidoglycan (PG) cell wall. Bacterial division results in two daughter cells, whose shapes are predetermined by the mother. This makes it difficult to explore the origin of cell shapes in healthy bacteria. In this review, we argue that the Gram-negative bacterium Myxococcus xanthus is an ideal model for understanding PG assembly and bacterial morphogenesis because it forms rods and spheres at different life stages. Rod-shaped vegetative cells of M. xanthus can thoroughly degrade their PG and form spherical spores. As these spores germinate, cells rebuild their PG and reestablish rod shape without preexisting templates. Such a unique sphere-to-rod transition provides a rare opportunity to visualize de novo PG assembly and rod-like morphogenesis in a well-established model organism.

Nowadays, considering the growing tendency of companies towards e-commerce as well as green production, and dual-channel green supply chain management has become particularly important. This paper investigates pricing decisions within a dual-channel green supply chain framework while considering the capital constraints faced by risk-averse manufacturer. Simultaneously, the impact of the degree of risk aversion, consumer green preferences, and channel preferences on the optimal decision-making process of green supply chain members is analyzed. We address the issue of financial constraints faced by manufacturer through bank loans and trade credit financing and compare the two cases. Our findings illustrate that trade credit financing outperforms bank loan financing in the dual-channel green supply chain. Moreover, pricing decisions under different models are influenced by consumer preferences and risk aversion. Specifically, the greenness of the product, wholesale price, and sale price exhibit negative correlations with manufacturers' risk aversion but positive correlations with consumer preferences.

Abstract: Droughts are complex and gradually evolving conditions of extreme water deficits which can compromise livelihoods and ecological integrity, especially in fragile arid and semi-arid regions that depend on rainfed farming, such as Kitui West in south-eastern Kenya. Against the background of low ground-station density, 10 gridded rainfall products and four gridded temperature products were used to generate an ensemble of 40 calculations of the Standardized Precipitation Evapotranspiration Index (SPEI) to assess uncertainties in the onset, duration and magnitude of past droughts. These uncertainties were driven more by variations between the rainfall products than variations between the temperature products. Remaining ambiguities in drought occurrence could be resolved by complementing the quantitative analysis with ground-based information from key informants engaged in disaster relief, effectively formulating an ensemble approach to SPEI-based drought identification to aid decision making. The reported trend towards drier conditions in Eastern Africa was confirmed for Kitui West by the majority of data products, whereas the rainfall effect on the increasingly dry conditions was more subtle than annual and seasonal declines and greater annual variation, which warrants further investigation. Nevertheless, the effects of increasing droughts are already felt on the ground and warrant decisive action.

Exercise-induced muscle injury is one of the most common types of sports injuries. Skeletal muscle troponin I (skTnI) serves as an ideal biomarker in assessing such injuries, facilitating timely detection and evaluation. In this study, we develop a fluorescent sandwich lateral flow immunoassay (LFIA) combined with a desktop analyzer for rapid detection of skTnI. Through optimizing the reaction system, the assay achieves a satisfying detection performance, reaching a limit of detection (LOD) of 0.5 ng/mL with a turnaround time of 15 minutes. The proposed de-tection platform offers portability, ease of use, and high sensitivity, which facilitates the moni-toring of exercise-induced muscle injuries at the point of care. This feature is particularly advan-tageous for end-users, enabling timely detection of sports-related injuries and ultimately en-hancing prognosis and sports life.

To enhance the safety of power grid operations, this study proposes a high-precision short-term photovoltaic power prediction method that integrates information from surrounding pho-tovoltaic stations and the Conv-LSTM-ATT model. In the deep learning prediction model, not only is numerical weather prediction (NWP) data from the target photovoltaic station used as input features, but also highly correlated features from nearby photovoltaic stations are incor-porated. The research begins by analyzing the correlation between irradiance and power se-quences, along with distance factors, to calculate a composite similarity index between the target and other regional photovoltaic stations. Stations with high similarity indices are then selected as data sources. Subsequently, Bayesian optimization techniques are employed to find the optimal data fusion ratios. Ultimately, using the selected data, power prediction mod-eling is conducted via the Conv-LSTM-ATT deep neural network. Experimental results con-firm the superiority of the proposed model, which demonstrates higher predictive accuracy compared to three other classical models. The data fusion strategy determined by Bayesian optimization significantly enhances prediction accuracy, reducing the root mean square error (RMSE) of the test set by 20.04%, 28.24%, and 30.94% for three weather types, respectively.

Tefluthrin (Tef) is categorized as a type-I pyrethroid insecticide, telmisartan (Tel) functions as an angiotensin II receptor blocker, and KB-R7943 was identified as an inhibitor of Na+-Ca2+ exchange process. However, the influence of these compounds on the amplitude and gating properties of voltage-gated Na+ current (INa) in neurons associated with pain signaling remains unclear. In cultured dorsal root ganglion (DRG) neurons, whole-cell current recordings revealed that Tef or Tel increased the peak amplitude of INa, concomitant with an elevation in the time constant of INa inactivation, particularly in the slow component. Conversely, exposure to KB-R7943 resulted in a depression in INa, coupled with a decrease in the slow component of the inactivation time constant of INa. Theoretical simulations and bifurcation analyses were performed on a modeled interneuron in the spinal dorsal horn. The occurrence of INa inactivation accentuated the subthreshold oscillations (SO) in the membrane potential. With an increase in applied current, SO became more pronounced, accompanied by the emergence of high-frequency spiking (HF) with a frequency of approximately 150 Hz. Moreover, an elevation in INa conductance further intensified both SO and HF. Consequently, through experimental and in silico studies, this work reflects that Tef, Tel, or KB-R7943 significantly impacts the magnitude and gating properties of INa in neurons associated with pain signaling. The alterations in INa magnitude and gating in these neurons suggest a close relationship with pain transmission.

Traditional methods of non-metallic materials joining for industrial uses are limited to lasers, or induction or conduction heating. The precision and efficiency for large-scale applications are difficult to be achieved at the same time. Here in this paper, we report a precise microwave welding method induced by localized surface plasmon of metallic macro-gaps under microwave excitation. The proposed method utilizes energy from well-developed commercial microwaver, and benefits from the precision of localized surface plasmon, an oscillating electron cloud excited by electromagnetic waves, which is currently under hot investigation only at micro- or nano-scales. The method is applied to the welding of polymers to solve the problems of complex processing equipment and high processing energy consumption in the traditional welding process, so as to cope with the growing energy and environmental crisis. Finite element numerical simulations are used to study the distribution characteristics of electric fields and temperature fields. The results show that the process is a high quality, efficient, low consumption and environmentally friendly green process compared to traditional polymer welding methods.

Amidst the escalating demands for efficient Intelligent Transportation Systems (ITS) management, the significance of accurate Origin-Destination (OD) data prediction has emerged as a paramount concern, given its indispensable role in the ITS domain. This paper introduces a groundbreaking integrated model, creatively fusing the unique strengths of Graph Convolutional Network (GCN), Residual Neural Network (ResNet), and Long Short-Term Memory Network (LSTM) into a single architecture, which we name GraphResLSTM, to exploit road segment average speed data for OD prediction. Compared with conventional road segment traffic volume data, average speed data is more readily available, significantly reducing the data accessibility barrier for OD prediction. We underscore the critical role of selection of key road segments and employs a combination of Entropy Weight Method and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to identify 41 representative road segments from the experimental road network. In the experimental phase, we simulate 86400000 seconds of traffic conditions, generating a total of 1440000 data records. Utilizing these simulated data, we design and conduct comparative experiments between models as well as data types. The results demonstrate that both the GraphResLSTM model and road segment average speed data outperform other models and data types notably in OD prediction tasks.

Research has shown that unsociability, reflecting as a personal choice, is not necessarily associated with socio-emotional problems in Western countries, and the associations between unsociability and peer problems are consistently evident in Chinese culture. Yet the strength and direction of the associations were mixed. The present study aimed to examine whether unsociability is associated with peer problems and explored the potential moderators among the associations. A meta-analysis was conducted using publications that measured unsociability and peer problems. A total of 21 articles involving 43 effect sizes from 12,696 Chinese children and adolescents were included. The results revealed that (1) unsociability was positively associated with peer problems (r = .32, p < .001) among children and adolescents. (2) informants (i.e., self-reports, peer nominations, teacher ratings, parent ratings) and living areas (i.e., urban, suburban, and rural areas) significantly moderated the associations between unsociability and peer problems. Specifically, the associations were stronger for peer-nominated unsociability, self-reported peer problems, and samples in suburban areas. These findings shed light on unsociability linked to higher levels of peer problems among Chinese children and adolescents. Still, the influences are unique to peer problems and moderated by both data sources and environmental factors.

There is a growing concern about climate change being a serious threat to insurance business sustainability. Knowing if climate warming is a cause for claims and losses increase, and how this cause-effect relationship will develop in the future are two open major questions. In this article, we answer both questions by particularizing the geographical area of Spain, and a precise risk, hailstorm in crop insurance in the line of business of wine grapes. We measure climate change thanks to the Spanish Actuarial Climate Index (SACI). We use a database containing all the claims caused by hail risk in Spain from 1990 to 2022. With homogenized data, we consider as dependent variables the monthly number of claims, monthly number of loss costs equal to one, and monthly total losses. The independent variable is the monthly Spanish Actuarial Climate Index (SACI). We try to explain the former through the latter using regression and quantile regression models. Our main finding is that climate change as measured by SACI explains these three dependent variables. We also give an estimation of the increase of the monthly total losses Value at Risk, corresponding to a future increase in climate change measured in units of SACI. Spanish crop insurance managers should carefully incorporate these conclusions into their decision-making process to keep this line of business sustainable in the future.

Surface Plasmon Resonance (SPR) technology has been known as a powerful tool for studying biomolecular interactions because it offers real-time and label-free multiparameter analysis with high sensitivity. This article summarizes the results that have been obtained from the use of SPR technology in studying the dynamics of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) mutations. This paper will begin by introducing the working principle of SPR and the kinetic parameters of the sensorgram which include the association rate constant (ka), dissociation rate constant (kd), equilibrium association constant (KA), and equilibrium dissociation constant (KD). At the end of the section, we will summarize kinetic data on the interaction of SARS-CoV-2 with different variants with various ligands which were obtained from the results of SPR signal analysis. These affinity-related kinetic data are very useful both in drug discovery for therapeutic purposes and in the detection of SARS-CoV-2.

Tourism is an important industry that promotes national economic and social progress. All-for-one tourism is a new concept of regionally coordinated development that uses the tourism industry as an engine to boost resource integration, industrial integration, and social sharing. Tourism service is the main embodiment of cultural ecosystem services for all-for-one tourism cities. Taking Liyang in China as an example, this paper used a combination of GIS spatial analysis and big data text mining to evaluate the tourism service from three aspects: the quality of tourism resources, the comprehensiveness of tourism service facilities, and the satisfaction of tourists. The results show that (1) the tourism service is better in the northwestern and eastern areas of the city, while it is lower in the northeastern and southwestern parts; (2) the hotspot areas should focus on improving the tour routes, the transport capacity, and excessive charges; the cold spot areas should work on ecological restoration and creating new tourism attractions by combining the local industries; (3) rural tourism integrating agriculture and visitation should be highlighted as a key growth point to improve the city’s tourism service function.

Abstract: Background: The optimal strategy for the microelimination of HCV within community settings remains ambiguous. We evaluated the percentage of participants who achieved linkage to care (LTC) following the conclusion of the screening campaign, and examined the diverse factors influencing LTC among these individuals. The effectiveness of recall intervention for the non-LTC population and its barriers were analyzed. Methods: We initiated an HCV patients recall program to identify the HCV participants who might not be treated after the HCV screening campaign. A program staff recalled HCV participants who lost to follow-up through the telephone from March 2019 to June 2019. They were informed of HCV treatment's importance, efficacy, availability, and safety. Result: Among 185 HCV-infected participants, 109 (58.9%) HCV-infected participants had obtained LTC. Compared with those who had LTC, those without LTC were older, lower education levels, were less aware of their HCV infection, less frequently lived in urban areas, and had less health insurance. At the end of the recall program, 125 (67.6 %) persons had liked to care. The proportion of LTC increased by 8.7 %. 119 persons had an HCV RNA test, and 82 (68.9%) had viremia. Of 82 patients with viremia, 78 (95.1%) received antiviral therapy. 76 (97.4 %) of them achieved a sustained virological response. Conclusion: After a community screening campaign, 59 % of participants with anti-HCV positive had LTC. The recall program can increase by 9 %. However, there were still 32% of HCV participants who couldn't be linked to care. Outreach care for non-LTC patients is a way worth trying to achieve micro-elimination of HCV in the rural community.

Two-dimensional (2D) of transition metal dichalcogenides (TMDCs) are potential candidates for thermoelectric (TE) applications due to their unique structural properties. In this paper, we constructed an 2D monolayer TMDCs semiconductor γ-PbSn2(X=S, Se, Te) and first-principles calculations and Boltzmann transport theory are used to study the thermoelectric performance. We found that γ-PbSnX2 had an ultra-high carrier mobility up to 4.04×103 cm2V−1s−1 leading to a metal-like electrical conductivity. Meanwhile, γ-PbSnX2 both have high Seebeck coefficients, resulting in high power-factors, and also shows intrinsic low lattice thermal conductivity of 6-8 W/mK at room temperature. The lower lattice thermal conductivity and high power-factors resulted in excellent thermoelectric performance. The high ZT values of γ-PbSnS2 and γ-PbSnSe2 were as high as 2.65 and 2.96 at 900 K, respectively. The result suggests that the monolayer γ-PbSnX2 are better candidates for excellent thermoelectric performance.

Exosomes are associated with cancer progression, pregnancy, cardiovascular diseases, central nervous system–related diseases, immune responses and viral pathogenicity. However, study on the role of exosomes in the immune response of teleost fish, especially antiviral immunity, is limited. Herein, serum-derived exosomes from mandarin fish were used to investigate antiviral effect for the exosomes of teleost fish. Exosomes were isolated from mandarin fish serum by ultracentrifugation could internalize into Mandarin fish fry (MFF-1) cells and inhibited Infectious spleen and kidney necrosis virus (ISKNV) infection. To further investigated the underlying mechanisms of exosomes in inhibiting ISKNV infection. The protein composition of serum-derived exosomes was by analysis mass spectrometry and found that myxovirus resistance 1 (Mx1) was incorporated in the exosomes. Furthermore, the scMx1 protein was proved transferred to the recipient cells though the exosomes. Our results found that the serum-derived exosomes from mandarin fish could inhibit ISKNV replication and suggested an underlying mechanism of the serum-derived exosomes antivirus is that serum-derived exosomes incorporation of the Mx1 protein into exosomes and delivery into recipient cells. This study provided an evidence for the important antiviral role of exosomes in the immune system of teleost fish.

This work compared the performance of three methods for constructing a regional ensemble prediction system (EPS) for wind speed forecasts: dynamical downscaling, breeding of growth modes (BGM), and blending method. The Weather Research and Forecasting (WRF) model was used to downscale the European Centre for Medium-range Weather Forecast (ECMWF) EPS. In addition, as the BGM method needs observation data for generating scaling factors, an alternative method for generating scaling factors was proposed to eliminate dependence on observation data. One-month tests between October 1st and October 30th, 2020, were implemented to evaluate the performance of three methods in the Gansu province of China. The results demonstrate that the blending method outperforms the other two methods. Furthermore, the difference in performance is evident mainly in early forecast lead time and becomes negligible as forecast time increases.

Along with the rapid development and wide application of Artificial Intelligence (AI), discussions regarding AI Sustainability have emerged. Employing a systematic mapping study, this paper reviews research about AI Sustainability from diverse fields and viewpoints, including three dimensions economic, social, and environmental. Our analysis indicates a transformative shift in research focus, evolving from fragmented approaches to a more holistic understanding of AI Sustainability. This maturation is reflected in the interplay between multiple dimensions and the integration of both "AI as a tool for sustainability" and "Sustainability of AI" perspectives. As the field continues to mature, researchers should embrace a comprehensive and unbiased exploration of AI Sustainability across all dimensions and approaches, ensuring a well-rounded foundation for future advancements in this rapidly evolving domain.

There has been a growing awareness of the need to implement environmentally friendly operations in the hotel industry, but most studies focus on guest behaviors. Only a few studies investigate employees’ willingness to comply with hotels’ green practices. This study seeks to further the investigation from the human resource perspective. Using alumni from a tourism and hospitality programs, this study collected 233 responses. The study hypothesizes that the employees’ green ability consisting of environmental awareness, environmental knowledge, and environmental skill creates a positive impact on hotels’ green ability. The results indicate that employees contribute approximately a fifth of hotels’ ability to implement greener practices.

In the context of global climate change, the frequency of sudden natural disasters is increasing. Assessing traffic road damage post-disaster is crucial for emergency decision-making and disaster management. Traditional ground observation methods for evaluating traffic road damage are limited by the timeliness and coverage of data updates. Relying solely on these methods does not adequately support rapid assessment and emergency management during extreme natural disasters. Social media, a major source of big data, can effectively address these limitations by providing more timely and comprehensive disaster information. Motivated by this, we utilized multi-source heterogeneous data to assess the damage to traffic roads under extreme conditions and established a new framework for evaluating traffic roads in cities prone to flood disasters caused by rainstorms. The approach involves several steps: First, extracting the surface area affected by precipitation using a threshold method constrained by confidence intervals derived from microwave remote sensing images; Second, collecting disaster information from the Sina Weibo platform, where social media information is screened and cleaned. A quantification table for road traffic loss assessment was defined, and a social media disaster information classification model combining text convolutional neural networks and attention mechanisms was proposed (TextCNN-Attention Disaster Classification); Finally, matching traffic road information on social media with basic geographic data, visualizing the classification of traffic road disaster risk levels, and completing the assessment of traffic road disaster levels based on multi-source heterogeneous data. Using the "7.20" rainstorm event in Henan Province as an example, this study categorizes the disaster impact on traffic roads into five levels: particularly severe, severe, moderate, mild, and affected, as interpreted from remote sensing images. The evaluation framework for flood disaster traffic roads based on multi-source heterogeneous data provides important data support and methodological support for enhancing disaster management capabilities and systems.

In order to assess the range of impact of thermal wastewater discharge from the third Nuclear Power Plant (NP_No.3) on the local ecosystem, a three-dimensional ocean model (MITgcm) driven by tidal and climatological forcings is employed to study the present work. Tides and daily wind forcings are incorporated into the MITgcm model to examine their effects on the thermal plume and the water circulation in Nan Wan Bay. The model results reveal that the thermal plume is most likely to disperse to the southwest in summer; it is unlikely to drift to the southeast or northeast because of the presence of gentle southwesterly monsoon. In winter, the thermal plume is most likely to be directed to the southwest but barely visible in the northeast or southeast directions because of prevailing northeasterly monsoon. Additionally, it is worth emphasizing that strong tidal currents generate a pair of counter-rotating eddies that significantly dominate the dispersal of the thermal plume. However, seasonal monsoons also play an essential role in modifying the plume’s direction and dispersion. The model results reveal that the flow field and thermal plume agree well with observational data.

Aim at a better understanding of the flow field around a fully appended Joubert BB2 submarine model and complementing the experimental investigations of the wake of the hydroplanes and sail, the Large eddy simulation (LES) with the dynamic Smagorinsky model is conducted. Three sets of grids with a maximum grid number of up to 228 million are designed, to perform the LES simulation for the Joubert BB2 at 10° yaw conditions, with a freestream Reynolds (Re) number based on the local freestream velocity and the hull length of ReL=2.2×107. And comparison of the wake of the cruciform appendage is made with experiments, to verify the computational accuracy and examine the influence of the spatial resolution. A satisfactory result shows more favorable agreement with experimental measurements as the improvement of spatial resolution, with the relative error of the vortice centers well within 7.2% in the most refined grid arrangement. And under this grid arrangement, the evolution characteristics of three co-rotating vortices originating from the cruciform appendage are further described in detail at straight ahead and 10° yaw conditions.

Reliable methods to confirm the diagnosis of COVID-19 are essential to the successful management and containment of the virus. Current diagnostic options are limited in type, supply, and reliability. This article explores the controversial unreliability of existing diagnostic methods and maintains that more reliable diagnostic methods, combinations, and sequencing are necessary to effectively assist in reducing the occurrence of discharge of the patient on false negative test results. This reduction would in effect reduce transmission of the disease.

Personalized recommendation is an important part of ecommerce platform. In the recommendation system, the neural network is used to enhance collaborative filtering to accurately capture user preferences, so as to obtain better recommendation performance. Traditional recommendation methods focused on the results of a single user behavior, ignoring the modeling of multiple interactive behaviors of users, such as click, add to cart and purchase. Although many studies had also focused on Multi-Behavior modeling, two important challenges remained. 1)Since multiple behavioral context information was ignored, it was still a challenge to identify the multimodal relationships of behaviors. 2) Surveillance signals were still sparse. In order to solve this problem, this paper proposes Two-path Multi-behavior Sequence Modeling(TP_MB). First, a two-path learning strategy is introduced to maximize the multiple interaction information of user items learned by the two paths, which effectively enhances the robustness of the model. Second, a multi-behavior dependent encoder is designed. Contextual information is obtained through behavior dependencies in the interaction of different user. In addition, three contrastive learning methods are designed, which not only obtain additional auxiliary supervision signals, but also alleviate the problem of sparse supervision signals. Extensive experiments on two real datasets demonstrate that our method outperforms state-of-the-art multi-behavior recommendation methods.

Bone growth plate abnormalities and skull shape defects are seen in hypophosphatasia, a heritable disorder in humans that occurs due to deficiency of Tissue Nonspecific Alkaline Phosphatase (TNAP, Alpl) enzyme activity. Abnormal development of the cranial base growth plates (synchondroses) and abnormal skull shapes have also been demonstrated in global TNAP-/- mice. To distinguish local vs. systemic effects of TNAP on skull development, we utilized P0-Cre to knockout TNAP only in cranial neural crest derived tissues using TNAP flox mice. Here we show that TNAP deficiency in cranial neural crest leads to leads to skull shape defects and deficient growth of the intersphenoid synchondrosis (ISS). ISS chondrocyte abnormalities included increased proliferation in resting and proliferative zones with decreased apoptosis in hypertrophic zones. ColX expression is increased, indicative of premature differentiation in the absence of TNAP. Sox9 expression is increased in both resting and prehypertrophic zones of mutant mice. Expression of PTHrP and IHH were also increased. Finally, cranial base organ culture revealed that inorganic phosphate (Pi) and pyrophosphate (PPi) have specific effects on cell signaling and phenotype changes in the ISS. Together, these results demonstrate that TNAP expression in growth plate chondrocytes is essential for normal development, and that the mechanism likely involves Sox9, PTHrP, IHH and PPi.

This literature review investigates the morphological and behavioral significance of the horns of Carnotaurus sastrei, a theropod dinosaur from the Late Cretaceous period. Through a comprehensive analysis of fossil specimens, comparative anatomy, and biomechanical modeling, this review explores the evolutionary adaptations and potential functions of these distinctive cranial structures. The horns of Carnotaurus are hypothesized to serve multiple roles, including species recognition, thermoregulation, and intraspecific combat. Our findings suggest that its cranial horns likely served a primary role in species recognition, intimidating rivals and signaling mating readiness. It also could have been used occasionally in head-butting contests, potentially as a display of dominance, but likely did not play a role in thermoregulation. Additionally, we examine the ecological context in which Carnotaurus lived, assessing how environmental factors could have influenced the development of such features. The implications of this study extend to broader discussions on the functional morphology and adaptive strategies of theropod dinosaurs, highlighting the complex relationship between form and function in the evolutionary history of predatory dinosaurs like Carnotaurus sastrei.

Revealing the spatial distribution mechanism of the coupling effect between soil water and salt is essential for managing saline-alkali farmland. This study utilized the multifractal method to analyze soil water and salt under varying water content levels in arid saline-alkali farmland. Soil samples were collected on the second (S1), fifth (S2), eighth (S3), eleventh (S4), and fourteenth (S5) days after a rainfall event. The findings showed that a significant decrease in soil water content, contrasting with an increase in soil salt content throughout the soil layers post-rainfall. As water content decreased, the spatial variability of soil water initially increased from S1-3 and then decreased, while the spatial variability of soil salt decreased. The spatial distribution between soil water and salt exhibited a high correlation at S3-4 (with relative water content of soil ranging from 0.52 to 0.75) due to their coupling effect. However, soil salt was unevenly leached by rainfall at high water content levels (S1-2) and precipitated at low water content levels (S5), resulting in low spatial variability correlations between soil water and salt. This study elucidated the coupling process of soil water and salt, identifying their spatiotemporal distribution mechanism in dryland agricultural areas.

The research of object classification and part segmentation is a hot topic in computer vision. A considerable number of studies have been carried out about deep learning on 3D point clouds. However,it is challenging to achieve effective feature learning due to sparsity of point clouds. Recently, a variety of Transformers have been adopted to improve point cloud processing and display great potential. Nevertheless, large numbers of Transformer layers tend to incur huge computational and memory costs. PointNet++ is one of the most influential neural architectures for point cloud understanding. Although the accuracy of PointNet++ has been largely surpassed by recent networks, this does not mean that PointNet++ has no potential.Thus, this paper offer two major contributions that significantly improve PointNet++ performance. Firstly, we introduce a novel contextual feature extraction (CFE) block that significantly enhances the feature extraction capabilities of PointNet++ networks. Secondly, to further enhance feature fusion, we seamlessly integrate a mutual learning (ML) block into the network architecture. By embedding these two innovative blocks within each layer of the network, we not only enrich the network's functionality but also impart it with greater robustness and adaptability. The specific experiments were conducted on the S3DIS (6-fold cross-validation) and Modelnet40 datasets with 86.5% and 92.7% accuracy, respectively, which proved that our model is comparable or even better than most existing methods for classification and segmentation tasks.

Recycled asphalt mixture is a material remixed with old asphalt recycled material (RAP) and new aggregate, and its application is of great significance in environmental protection.Due to the wear and tear of the old asphalt mixture, the road performance of the recycled asphalt mixture will decrease. This paper uses IPP software to obtain the shape characteristics of the old and new aggregates, and found that the roundness of the old aggregate of 9.5mm-16mm is the most serious wear. Therefore, the 30% RAP, and the influence of the roundness of the recycled asphalt mixture on the road performance is studied.

Ankylosaurus stands as a quintessential example of Cretaceous armored dinosaurs, renowned for its formidable defensive adaptations. This study explores the defensive mechanisms and paleoecology of Ankylosaurus, focusing on its unique armor and lifestyle. Through detailed morphological analysis of fossil specimens, we examine the structure and function of the robust osteoderms and the prominent tail club, evaluating their roles in defense against predators. The distribution and arrangement of these defensive features suggest a sophisticated strategy to deter and survive attacks from contemporary theropods. Additionally, we investigate the paleoenvironmental context of Ankylosaurus, assessing how its habitat and ecological interactions influenced its evolutionary adaptations. Comparative analysis with other ankylosaurids and contemporaneous species provides insights into the evolutionary pressures shaping its armor. Our findings highlight the balance between offensive and defensive strategies in the Late Cretaceous ecosystem, underscoring the role of Ankylosaurus as both a well-protected herbivore and a critical component of its ecological niche. This study contributes to a deeper understanding of the evolutionary dynamics of armored dinosaurs and their interaction with their environment, offering a comprehensive perspective on the adaptations that defined Ankylosaurus' survival strategy.

This literature review examines the function and evolution of cranial crests in Dilophosaurus wetherilli, a notable theropod dinosaur from the Early Jurassic period. The review synthesizes morphological data and behavioral theories to provide a comprehensive analysis of the crests' roles in the dinosaur's life. Cranial crests, characterized by their distinctive, elongated structures extending from the skull, have intrigued paleontologists due to their unique appearance and apparent function. This review utilizes findings from recent fossil discoveries, comparative anatomy, and biomechanical studies to explore hypotheses regarding the crests' primary functions. Key theories suggest these structures may have served for display purposes, thermoregulation, or defensive mechanisms. Evidence from cranial and postcranial anatomy, as well as comparisons with extant analogs, provides insights into the possible evolutionary pressures influencing the development of crests in Dilophosaurus wetherilli. Additionally, the review considers the role of sexual dimorphism and social behavior in shaping these features. By integrating these diverse lines of evidence, the review aims to offer a nuanced understanding of how cranial crests might have contributed to the survival and social interactions of Dilophosaurus. This analysis not only advances our knowledge of Dilophosaurus wetherilli but also contributes to broader discussions on the evolution and functional morphology of early theropods.

The tumor microenvironment plays a pivotal role in the behavior and development of solid tumors as well as shaping the immune response against them. As the tumor cells proliferate, the space they occupy and their physical interactions with the surrounding tissue increases. The growing tumor tissue becomes a complex dynamic structure, containing connective tissue, vascular structures, and extracellular matrix that facilitates stimulation, oxygenation, and nutrition, necessary for its fast growth. Mechanical cues such as stiffness, solid stress, interstitial fluid pressure, matrix density, and microarchitecture influence cellular functions and ultimately tumor progression and metastasis. In this fight, our body is equipped with T cells as its spearhead against tumors. However, the altered biochemical and mechanical environment of the tumor niche affects T cell efficacy and leads to their exhaustion. Understanding the mechanobiological properties of the tumor microenvironment and their effects on T cells is key for developing novel adoptive tumor immunotherapies.

In this paper we re-investigated the relationship between the symmetry of inertial systems and the Lorentz transformation. We found that when we just follow the following three principles: (1)we can define the time in the whole space with a prescribed clock synchronization, (2)the time-space is uniform and the space is isotropic and (3)all the inertial systems are equivalent, then we can totally construct a general coordinate transformation to meet the symmetry of inertial systems, and with a special assumption on the speed of light, we can construct a non-Lorentz transformation between inertial systems to make the particle’s energy have a limited value, which is similar to the rainbow model. Similar to the usual Lorentz violating models, the non-Lorentz transformation in this paper lead to a new modified disperse relation. We applied the obtained disperse relation to analyze the photon’s arrival time lag effect in astronomy and found that the "maximum energy" derived in our model is somewhat related to the "maximum energy" assumed in the rainbow model.

Host immunological pathways have been proposed including TH1, TH2, TH3, TH9, TH17, TH22, TH1-like, and THαβ immune reactions. Besides TH2 and TH9 immune responses which are against multicellular parasites, host immunological pathways against viruses, intracellular micro-organisms (bacteria, protozoa, and fungi), and extracellular micro-organisms can use programmed cell death pathways to trigger immune reactions or to execute effective strategies to eliminate these pathogens. These programmed cell deaths include apoptosis, autophagic death, pyroptosis, ferroptosis, necroptosis, and NETosis. Apoptosis is related to host anti-virus eradicable THαβ immunity. Autophagic death is related to host anti-virus tolerable TH3 immunity. Pyroptosis is related to host anti-intracellular micro-organism eradicable TH1 immunity. Ferroptosis is related to host anti-intracellular micro-organism tolerable TH1-like immunity. Necroptosis is related to host anti-extracellular micro-organism eradicable TH22 immunity. NETosis is related to host anti-extracellular micro-organism tolerable TH17 immunity.

In order to cope with the limited supply of feed for global animal production, there is a pressing need to explore alternative feed resources. Orange pulp, a by-product of agriculture and industry, has shown potential to positively or neutrally impact pig productive performance when included in their diet. However, there is a lack of research on the effects of fermented navel orange pulp (FNOP) on pig growth and productive performance. This study aimed to investigate the effects of FNOP as a dry matter substitute on pig’s growth performance, carcass characteristics, meat quality, meat nutrition, and serum biochemical indicators. The experiment involved 128 finishing Tibetan pigs, divided into four feed treatment groups, with varying levels (0%, 5%, 10% and 15%) of FNOP replacing dry matter in the basal diet. The results indicated that substituting 5% to 15% FNOP had no adverse effects on pig growth performance. However, at a 15% substitution rate, there was a decrease in serum growth hormone and IGF-1 levels, along with an increase in feed-to-gain ratio. A 10% FNOP replacement notably increased the eye muscle area of pigs. Additionally, 5% and 10% FNOP substitutions reduced the drip loss of pork. The study also found that substituting 5% to 15% FNOP increased unsaturated fatty acids and umami nucleotide contents in pork, as well as raised serum total protein and uric acid (nucleotide metabolism related-product) levels. These findings suggest that moderate FNOP substitution might enhance meat quality and maintain growth and productive performance in Tibetan pigs by improving protein synthesis and nucleotide metabolism, while also reducing feed costs. The optimal substitution ratio identified was 10%.

Exposure to psychosocial stress is a risk factor for cardiovascular disease, including vascular aging, angiogenesis, and atherosclerosis-based cardiovascular disease (ACVD). Dipeptidyl peptidase-4 (DPP-4) is a complex enzyme (also called CD26) that acts as a membrane-anchored cell surface exopeptidase. DPP4 is upregulated in metabolic and inflammatory cardiovascular disorders. The widespread expression of DPP4 macrophages and immune cells and the noncatalytic function of DPP4 (also called CD26) as a signaling and binding protein across a wide range of species suggest a teleological role for DPP4 in inflammation and immune response. DPP-4 exhibits many physiological and pharmacological functions by regulating its extremely abundant substrates [e.g., stromal cell-derived factor-1α/ C-X-C chemokine receptor type-4, glucagon-like peptide-1 (GLP-1), etc.]. Over last ten year, emerging data demonstrated unexpected roles for GLP-1 and DPP-4 in extracellular and intracellular signaling, immune activation, inflammation, oxidative stress production, cell apoptosis, insulin resistance, and lipid metabolism,. This mini review has focuses on recent novel findings in this field, highlighting an imbalance between GLP-1 and DPP4 as a potential therapeutic molecular target in treatments of chronic psychological stress-related atherosclerotic cardiovascular disease in humans and animals.

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

Developing particles of different anisotropic shapes are the hot topic since decades as they guarantee some special features of properties not possible through other means. Again, controlling atoms to develop certain size and shape particle is a quite challenging job. In this study, gold particles of different shapes are developed via pulse-based electronphoton-solution interface process. Gold atoms of certain transition state develop monolayer assembly at solution surface around the light glow (known in argon plasma) being generated at bottom of copper capillary (known in cathode). The rate of uplifting gold atoms to solution surface is being controlled by forcing energy (travelling photons) pursuing electrons and high energy photons (in high density) entering to solution. Gold atoms dissociated from the precursor under dissipating heat energy into the solution supplied under propagating photons characteristic current through immersed graphite rod (known in anode). Placing packets of nano shape energy of tuned pulse protocol over compact monolayer assembly comprising transition state atoms develop tiny-sized particles of formed shape. On separation of joint tiny particles into two equilateral triangular-shaped tiny particles, exerting forces of surface format elongate atoms of one-dimensional arrays converting them into structures of smooth elements. Due to immersing level of force, such tiny-shaped particles pack from different zones at centre of light glow where they assembled structures of smooth elements for developing mono-layers of different shapes of particles. Developing one-dimensional particles deal assembling of structures of smooth elements of packing tiny-shaped particles from nearly rearward zones of reflection of north-south poles, whereas, developing multi-dimensional particles deal assembling of structures of smooth elements of packing tiny-shaped particles from the east-west poles and near regions. Depending on the number of assembled structures of smooth elements at point of nucleation, packing of tiny-shaped particles from different zones develop different shapes of the anisotropic particles. At fixed precursor concentration, increasing the process time results into develop particles of low aspect ratio. Under tuned parameters, developing mechanisms of particles exhibiting unprecedented features are discussed.

This literature review provides a comprehensive analysis of the functional morphology and paleoecology of Pteranodon, a prominent genus of Pterosaur from the Late Cretaceous period. By synthesizing recent research findings with classic studies, this paper elucidates the aerodynamic and ecological adaptations of Pteranodon, which was one of the largest pterosaurs to ever soar the skies. The review examines the distinctive cranial features, including its elongated cranial crest and its implications for sexual dimorphism and species identification. Detailed analysis of wing morphology and limb proportions reveals insights into its flight mechanics, suggesting that Pteranodon was adapted for dynamic soaring, leveraging its expansive wingspan for efficient long-distance travel. Additionally, the paper explores Pteranodon's feeding habits and dietary preferences based on dental and jaw structure, indicating a diet primarily consisting of fish and other aquatic prey. The review also integrates fossil evidence with ecological models to reconstruct the paleoenvironment of the Late Cretaceous, highlighting the role of Pteranodon in its ecosystem as both a predator and a competitor. This synthesis not only enhances our understanding of Pteranodon’s physiological and ecological roles but also contributes to broader discussions on pterosaur evolution and behavior.

Therizinosaurs, a unique clade of theropod dinosaurs, are characterized by their distinct morphological features and enigmatic ecological role. This review provides a comprehensive analysis of the functional morphology and ecological significance of these remarkable dinosaurs. Therizinosaurs are distinguished by their elongated, often curved claws, robust postcranial skeletons, and herbivorous diet, which starkly contrasts with their carnivorous theropod relatives. We explore the evolutionary implications of their morphology, focusing on adaptations such as their specialized feeding apparatus and limb structure. These features suggest a complex interplay between their herbivorous lifestyle and ecological niche. The review synthesizes recent findings from fossil evidence, including detailed studies of cranial and postcranial anatomy, to elucidate the functional mechanisms behind their unique adaptations. Additionally, we discuss the broader ecological role of therizinosaurs within their Mesozoic ecosystems, highlighting their interactions with contemporaneous flora and fauna. By integrating paleontological data with comparative anatomy and ecological modeling, this review aims to shed light on the evolutionary trajectory of therizinosaurs and their impact on our understanding of theropod diversity and adaptation. This focused review contributes to a more nuanced appreciation of therizinosaurs' place in dinosaur evolution and their adaptive strategies in prehistoric environments.

Soil organic matter (SOM) is important for the global carbon cycle, and hyperspectral remote sensing has proven a promising method for fast SOM content estimation. However, soil physical properties significantly affect the sensitivity of satellite hyperspectral imaging to SOM, leading to poor generalization ability of the estimation model. This study aims to improve the spatiotemporal transferability of the SOM prediction model by alleviating the coupling effect of soil physical properties on the spectra. Based on satellite hyperspectral images and soil physical variables, including soil moisture (SM), soil surface roughness (root mean squared height, RMSH), and soil bulk weight (SBW), a soil spectral correction strategy was established based on the information unmixing method. Two important grain-producing areas in Northeast China were selected as study areas to verify the performance and transferability of the spectral correction model and SOM content prediction model. The results showed that soil spectral corrections based on fourth-order polynomials and the XG-Boost algorithm had excellent accuracy and generalization ability, with residual predictive deviations (RPD) exceeding 1.4 in almost all bands. In addition, when the soil spectral correction strategy was adopted, the accuracy of the SOM prediction model and the generalization ability after model migration were significantly improved. The SOM prediction accuracy based on the XG-Boost corrected spectrum was the highest, with a coefficient of determination (R2) of 0.76, root mean square error (RMSE) of 5.74 g/kg, and RPD of 1.68. The prediction accuracy, R2, RMSE, and RPD of the model after migration were 0.72, 6.71 g/kg, and 1.53, respectively. Compared with the direct migration prediction of the model, adopting the soil spectral correction strategy based on fourth-order polynomials and XG-Boost reduced the RMSE of the SOM prediction results by 57.90% and 60.27%, respectively. The performance comparison highlighted the advantages of considering soil physical properties in regional-scale SOM prediction.

This paper applies conceptualization from Paulo Freire, Tracey Nicholls, and bell hooks to develop a framework to understand art- and media-based communication of knowledge. Increasing use of art and digital media in research and formal educational settings emphasize knowledge-communication intent, and the theory attempts to rationalize why individuals potentially devalue, discard, or misconstrue messaging. Drawing upon two case studies: children’s literature, and existing scholarship on true crime as a media genre, the framework proposes art and media consumption based on perceived task-applicability of art and media. Stemming from the complex nature of socially-imposed, self-determined, and art- & media-instated tasks that an individual may face throughout their lifetime, an individual may be drawn to Freirean power and privilege - even fictional depictions - as societal structures can grant power and privilege with universal task-applicability. Potential usage of this framework towards participatory, qualitative inquiries conclude the paper, in attempt to support future art and media designed with knowledge-communication intent.

This article obtains data through questionnaire survey, and then uses the Multiple Indicators Multiple Causes (MIMIC) Model to establish the Taoyuan City’s quality of life quantifying framework in a city-level community context. Statistical test results show that the reliability of overall model is high and is suitable for policy analysis. There are thirteen variables in the structural model that significantly affect the quality of life as well as eleven indicators in the measurement model that can significantly measure the quality of life. Then, half of the observations are substituted back to calculate the quality of life. Via ArcGis operation, it finds that the quality of life of Longtan District is the best as well as Dayuan District is the worst one. LISA cluster of quality of life illustrates hot spots areas are distributed in Longtan, Daxi, and Pingzhen Districts.

Laser scanning is an effective tool for acquiring geometric attributes of trees and vegetation, which lays a solid foundation for 3-dimensional tree modelling. Existing studies on tree modelling from laser scanning data are vast. Nevertheless, some works don’t ensure sufficient modelling accuracy, while some other works are mainly rule-based and therefore highly depend on user inputs. In this paper, we propose a novel method to accurately and automatically reconstruct tree branches from laser scans. We first extract an initial tree skeleton from the input tree point cloud, then simplify the skeleton through iteratively removing redundant components. A global-optimization approach is performed to fit a sequence of cylinders to approximate the geometry of the tree branches. Experiments on various types of trees from different data sources demonstrate the effectiveness and robustness of our method. The resulted tree models can be further applied in the precise estimation of tree attributes, urban landscape visualization, etc.

Gigantism in theropods represents one of the most intriguing phenomena in dinosaur evolution, showcasing extreme adaptations in body size and ecological roles. This literature review focuses on Giganotosaurus carolinii, one of the largest known theropods to have ever existed, to explore its unique aspects of gigantism and the subsequent ecological impacts. By analyzing features such as its skeletal morphology, comparative anatomy, and paleoenvironmental data, we assess the evolutionary pressures and biological constraints that shaped the gigantism observed in Giganotosaurus. We discover that the species exhibited a combination of physiological and ecological adaptations that allowed it to thrive as an apex predator in its Cretaceous environment. We will also further examine the implications of its size on prey dynamics, competition with other large theropods, and the overall ecosystem structure. Through a thorough, multidisciplinary approach, this research enhances our understanding of how gigantism influenced theropod behavior, interspecies interactions, and the broader paleoecological landscape.

Logistics plays an important role in globalized companies and contributes to the development of foreign trade. A large number of external conditions, such as recession and inflation, affect logistics. Therefore, managers should find ways to improve operational performance, enabling them to increase efficiency while considering environmental sustainability due to the industry’s large scale of energy consumption. Based on data collected from the financial reports of top global logistics companies, this study uses a DEA model to calculate corporate efficiency by implementing a Grey forecasting approach to forecast future sustainability values. Consequently, the study addresses the problem of how to enhance operational performance while accounting for the impact of external conditions. This research can help logistics companies develop operation strategies in the future that will enhance their competitiveness vis-à-vis rivals in a time of global economic volatility.

Internet-led labour market has become so competitive forcing many organisations from different sectors to embrace e-recruitment. However, realising the value of the e-recruitment from a Requirements Engineering (RE) analysis perspective is challenging. This research is motivated by the results of a failed e-recruitment project conducted in military domain which is used as a case study in this research. After reviewing the various challenges faced in that project through a number of related research domains, this research focuses on two major problems which are the (1) difficulty of scoping, representing, and systematically transforming recruitment problem knowledge towards e-recruitment solution specification; and (2) the difficulty of documenting e-recruitment best practices for reuse purposes in an enterprise recruitment environment. In this paper, a Problem-Oriented Conceptual Model (POCM) with a complementary Ontology for Recruitment Problem Definition (Onto-RPD) is proposed to contextualise the various recruitment problem viewpoints from an enterprise perspective and to elaborate those problem viewpoints towards a comprehensive recruitment problem definition. The POCM and Onto-RPD are developed incrementally using action-research conducted on three real case studies: (1) Secureland Army Enlistment, (2) British Army Regular Enlistment, and (3) UK Undergraduate Universities and Colleges Admissions Service (UCAS). They are later evaluated in a focus group study against a set of criteria. The study showed that the POCM and Onto-RPD provide a strong foundation for representing and understanding the e-recruitment problems from different perspectives.

This literature review presents a comparative analysis of cranial morphology in Allosaurus, focusing on its implications for feeding mechanics. Allosaurus, a large theropod dinosaur from the Late Jurassic period, exhibits distinct cranial features that are pivotal for understanding its predatory behaviors and ecological role. By examining fossilized skulls and employing advanced imaging techniques, this research identifies key morphological traits such as tooth structure, jaw articulation, and cranial robusticity. The analysis reveals that Allosaurus had a specialized cranial architecture that supported a powerful bite force and efficient processing of prey. Comparative metrics are applied to assess similarities and differences with other theropods, such as Tyrannosaurus rex, to elucidate variations in feeding strategies among theropods. The findings suggest that Allosaurus possessed adaptations that allowed it to exploit a diverse range of prey, indicating a versatile feeding strategy. These results enhance our understanding of theropod evolution and ecological interactions, providing insights into the functional significance of cranial morphology in dinosaurian predation. This review underscores the importance of cranial features in reconstructing the behavior and diet of extinct species and contributes to the broader field of vertebrate functional morphology.

The rapid advancement of large language models (LLMs), such as ChatGPT, has revolutionized natural language processing, enabling these models to generate coherent and contextually relevant text. These capabilities hold significant potential for various applications, particularly in the medical field. LLMs can assist healthcare professionals by providing accurate information, supporting diagnostic processes, and enhancing medical education. However, the implementation of LLMs in clinical settings faces several barriers, including technical limitations, ethical concerns, regulatory constraints, and practical challenges. Ensuring accuracy, reliability, and interpretability is crucial, along with addressing biases, ensuring data privacy, and establishing ethical guidelines. Future research should focus on improving training techniques, developing explainable AI methods, and creating efficient, resource-saving models. Expanding applications through domain-specific models and multi-modal integration can further unlock the potential of LLMs. By addressing these challenges and prioritizing responsible development, LLM technology can be safely and effectively integrated into various domains, driving innovation and improving outcomes. This paper explores the current state of LLM technology, its medical applications, barriers to implementation, and directions for future research and development

This literature review aims to gain a deeper understanding of the anatomy behind the jaw strength of Tyrannosaurus rex and analyze how these features contribute to its predatory behavior. This review will examine various studies and fossil excavations, exploring ideas such as the bite force of T. rex and its variations across different life stages. This will be obtained from numerous biomechanical models of both juvenile and adult Tyrannosaurus rex, as well as reference animals and dinosaurs for comparison. To provide additional information behind T. rex’s hunting techniques, we will also discuss the fauna of herbivorous dinosaurs that were part of T. rex’s diet. Furthermore, we will explore how mandibular stress concentration can vary between ages, a crucial topic in determining what T. rex could consume at certain stages of its life. Finally, we obtain a well-evidenced analysis of the various aspects of Tyrannosaurus rex’s hunting strategies throughout its lifetime.

Although the concept of additive manufacturing has been proposed for several decades, momentum of selective laser melting (SLM) is finally starting to build. In SLM, density and surface roughness, as the important quality indexes of SLMed parts, are dependent on the processing parameters. However, there are few studies on their collaborative optimization in SLM to obtain high relative density and low surface roughness simultaneously in the previous literature. In this work, the response surface method was adopted to study the influences of different processing parameters (laser power, scanning speed and hatch space) on density and surface roughness of 316L stainless steel parts fabricated by SLM. The statistical relationship model between processing parameters and manufacturing quality is established. A multi-objective collaborative optimization strategy considering both density and surface roughness is proposed. The experimental results show that the main effects of processing parameters on the density and surface roughness are similar. It is noted that the effects of the laser power and scanning speed on the above objective quality show highly significant, while hatch space behaves an insignificant impact. Based on the above optimization, 316L stainless steel parts with excellent surface roughness and relative density can be obtained by SLM with optimized processing parameters.

Regulatory T cells are key immune cells to initiate tolerable immune responses. TGFβ is the key cytokine of regulatory T cells. TGFβ is also the master cytokine to stimulate tissue fibrosis. Systemic sclerosis is an autoimmune disease related to overt organ fibrosis. Thus, systemic sclerosis is a disease related to regulatory T cell over-representation. Besides, many end stage organ failures including heart failure, liver cirrhosis, uremia, and pulmonary fibrosis also related to tissue fibrosis. Thus, TGFβ producing regulatory T cells are also involved in the pathogenesis of these end stage organ failure. Once we know the significance of TGFβ and it induced tolerable immune reactions in the pathophysiology of end organ failure, we can develop better prevention or therapeutic strategies to combat these detrimental disorders.

Vanadium is a well-known essential trace element, which usually exists in oxidation states in form of vanadate cation intracellularly. The pharmacological study of vanadium begins at the discovery of its unexpected inhibitory effect on ATPase. Thereafter, the protective effects on cells and the abilities in glucose metabolism regulation were observed from vanadium compound, leading to the application of vanadium compounds in clinical trials for curing diabetes. Alzheimer’s dis-ease (AD) is the most common dementia disease in elderly people. However, there is still no efficient agents for treating AD safely to date. This is mainly because of the complexity of the pathology, which are characterized by the senile plaques composed by amyloid-beta (Aβ) protein in the parenchyma of brain and the neurofibrillary tangles (NFTs) derived from hyperphosphorylated tau protein in neurocyte, along with mitochondrial damage, and eventually the central nervous system (CNS) atrophy. AD was also illustrated as type-3 diabetes, because of the observations of insulin deficiency and the high level of glucose in cerebrospinal fluid (CSF), as well as the im-paired insulin signaling in brain. In this review, we summarized the advance of applicating vanadium compound on AD treatment in experimental research and pointed out the limitation of the current study on using vanadium compounds in AD treatment. We hope it will help the future study in this field.

Drone imagery has the potential to enrich urban planning and preservation, especially where it converges with the growing creation and use of 3D models. The authors have conducted a systematic literature review of articles published between 2002 and 2022, drawing from reputable academic repositories including Science Direct, Web of Science, and China National Knowledge Infrastructure (CNKI), to identify current gaps in existing research in the application of UAVs to the creation of 3D models in urban planning and preservation. Findings indicate five research shortcomings: limited participation of planning experts, research focus imbalance, lack of usage for special scenarios, lack of integration with smart city planning, and limited interdisciplinary collaboration. The study also acknowledges current limitations with UAV applications and discusses possible countermeasures as well as future prospects.

Photosynthetic function, photoprotection, and the response of related proteomics of mulberry (Morus alba L.) seedling leaves under NaCl and NaHCO3 stress with the same Na+ concentration (100 mmol•L-1) were studied by using photosynthetic gas exchange and chlorophyll fluorescence techniques combined with TMT proteomics. The results showed that NaCl stress had no significant effect on photosystem II (PSII) activity in mulberry seedling leaves, and the expressions of the related proteins, OEE3-1 and PPD4, of the PSII oxygen-evolving complex (OEC) and the antenna proteins, CP24 10A, CP26, and CP29, of LHCII in the leaves also increased to varying degrees. The photosystem I (PSI) activity in the leaves of mulberry seedling also increased, and the expressions of some proteins, PsaF, PsaG, PsaH, PsaL, PsaN, and Ycf4, in PSI increased significantly under NaCl stress. Under NaHCO3 stress, the activity of PSII and PSI and the expression of their protein complexes and the electron transfer-related proteins significantly decreased. NaCl stress had little effect on RuBP regeneration during dark reaction in the leaves and the expressions of glucose synthesis related proteins and net photosynthetic rate (Pn) did not decrease significantly. The leaves could adapt to NaCl stress by reducing stomatal conductance (Gs) to increase water use efficiency (WUE). Under NaHCO3 stress, the expression of dark reaction-related proteins was mostly down-regulated, and Gs was significantly reduced, which indicated that non-stomatal factors were important reasons for the significant inhibition of carbon assimilation. In the photoprotective mechanism under NaCl stress, the expression of cyclic electron flow (CEF) related proteins, ndhH, ndhI, ndhK, and ndhM, involved in NAD(P)H dehydrogenase (NDH) and the key enzyme of the xanthophyll cycle, violaxanthin de-epoxidase (VDE) were up-regulated. In addition, the ratio of xanthophyll cycle components (A+Z)/(V+A+Z) was increased. The expressions of proteins FTR and Fd-NiR, which are related to Fd-dependent ROS metabolism and nitrogen metabolism, were also significant up-regulated under NaCl stress, which can effectively reduce the electronic pressure on Fd. Under NaHCO3 stress, the expressions of CEF-related proteins, VDE, ZE, FTR, Fd-NiR, Fd-GOGAT, SGAT, and GGAT, were significant down-regulated, and the photoprotective mechanism, like the xanthophyll cycle, CEF, and photorespiration, might be damaged, resulting in the inhibition of PSII activity and carbon assimilation in leaves of mulberry seedling under NaHCO3 stress.

Ultra-high temperature oxidation-resistant alloys (UTORAs) have received a lot of attention due to the increased research demand for deep space exploration around the world. But UTORAs have the disadvantages of easy oxidation and chalking. So, in this study, a UTORA was prepared by hot-press sintering on VZrHfNbTa (HEA) substrate coated with hafnium. The bonding mechanism, resistance to high-temperature oxidation, and hardness of the sample tests were carried out. The results show that zirconium in the matrix will diffuse into the hafnium coating during the high-temperature sintering process and form the HfZr alloy transition layer, the coating thickness of the composite is about 120 μm, and the diffusion distance of zirconium in the hafnium coating is about 60 μm, this transition layer chemically combines the hafnium coating and the HEA substrate into a monolithic alloy composite. The results of high-temperature oxidation experiments show that the oxidation degree of the hafnium-coated VZrHfNbTa composite material was significantly lower than that of the VZrHfNbTa HEA after oxidation in air at 1600 °C for 5 h. The weight gain of the coated sample after oxidation is 56.56 mg/cm2, which was only 57.7 % compared to the weight gain of the uncoated sample (98.09 mg/cm2 for uncoated), and the surface of the uncoated HEA showed obvious dents, oxidation, and pulverization occurred on the surface and interior of the sample. In contrast, the coated composite alloy sample mainly underwent surface oxidation sintering to form a dense HfO2 protective layer, and the internal oxidation of the hafnium-coated VZrHfNbTa composite alloy was significantly lower than that of the uncoated VZrHfNbTa HEA.

Diffuse large B cell lymphoma (DLBCL), the most frequent type of non-Hodgkin lymphoma in adulthood, remains challenging clinical issues. Despite enhanced remission rates can be achieved, there are one-third of patients who will not respond to current treatment or will relapse with resistant disease, necessitating ongoing efforts on effective treatment strategies and agents. The vacuole H+-ATPase inhibitor bafilomycin A1 is broadly used to block late stage of autophagy flux at high concentration. In this study, we show that, to our surprise, bafilomycin A1 effectively inhibited and killed DLBCL cells at nanomolar concentrations (5nM). Bafilomycin A1 targeted cell cycle regulators cyclin D1 and cyclin E2 to induce cell cycle arrest in G0/G1 phase. Meanwhile, it induced caspase-dependent apoptosis with concomitant cleaved caspase-3 and Parp. Furthermore, we found that bafilomycin A1 inhibited autophagy flux at both early and late stages of the autophagy flux through activating ERK and mammalian target of rapamycin signaling, as well as by inhibiting the degradation of autolysosomes. We speculated that bafilomycin A1 as autophagy inhibitor might enhance the effect of DLBCL chemotherapeutic drug rituximab. Accordingly, our results provided evidence that the combination of bafilomycin A1 with rituximab enhanced the inhibition of DLBCL cells notably. Taken together, our data suggest that bafilomycin A1 may be a promising candidate drug in the therapy of diffuse large B cell lymphoma.

As matrix representations of magic labelings of related hypergraphs, magic squares and their various variants have been applied to many domains. Among various subclasses, trimagic squares have been investigated for over a hundred years. The existence problem for trimagic squares with singly even orders and orders 16n has been solved completely. However, very little is known for the existence of trimagic squares with other even orders except for the only three examples and three families. We construct normal trimagic squares by using product constructions, row-square magic rectangles, and trimagic pairs of orthogonal diagonal Latin squares. We give a new product construction: For positive integers p, q, and r having the same parity other than 1, 2, 3, 6, if normal p × q and r × q row-square magic rectangles exist, then a normal trimagic square with order pqr exists. As its application, we construct normal trimagic squares of orders 8q^3 and 8pqr for all odd integers q not less than 7 and p,r ∈ {7, 11, 13, 17, 19, 23, 29, 31, 37}. Our construction can easily be extended to construct multimagic squares.

In this paper we study a class of impulsive delayed neural networks with parameter uncertainties and reaction-diffusion terms. Using the properties of M-matrices and some inequality techniques, some sufficient conditions are derived to guarantee the global exponential stability of the given system. The results obtained are presented by simple algebraic inequalities, which are certainly more concise than previous methods. Finally, the validity and usefulness of our results are illustrated by arithmetic examples.

Demand response flexible loads can provide fast regulation and ancillary services as reserve capacity in power systems. This paper proposes a joint optimization dispatch control strategy for source-load system with stochastic renewable power injection and flexible thermostatically controlled loads (TCLs) and plug-in electric vehicles (PEVs). Specifically, the optimization model is characterized by a chance constraint look-ahead programming to maximal the social welfare of both units and load agents. By solving the chance constraint optimization with sample average approximation (SAA) method, the optimal power scheduling for units and TCL/PEV agents can be obtained. Secondly, two demand response control algorithms for TCLs and PEVs are proposed respectively based on the aggregate control models of the load agents. The TCLs are controlled by its temperature setpoints and PEVs are controlled by its charging power such that the DR control objective can be fulfilled. The effectiveness of the proposed dispatch and control algorithm has been demonstrated by the simulation studies on a modified IEEE 39 bus system with a wind farm, a photovoltaic power station, two TCL agents and two PEV agents.

The fractional reduced differential transform method is a finite iterative method based on infinite fractional expansions. The result obtained is the approximation of the real value. There are few reports on the approximate error and the applicable condition. In this paper, according to the fractional expansions, we study the factors related to the approximate errors. Our research shows that the approximate errors relate not only to fractional order but also to time $t$ and increase rapidly with time $t$. This method can only be applied within a certain time range and the time range is relevant to fractional order and fractional expansions. Then, many obtained achievements may be incorrect if the applicable conditions are not satisfied. Some examples presented in this paper verify our analysis.

With the proliferating of video surveillance system deployment and related applications, real-time video analysis is very critical to achieve intelligent monitoring, autonomous driving, etc. It is non-trivial to achieve high accuracy and low latency video stream analysis through the traditional cloud computing. In this paper, we propose a non-orthogonal multiple access (NOMA) based edge real-time video analysis framework with one edge server (ES) and multiple user equipments (UEs). A cost minimization problem composed of delay, energy and accuracy is formulated to improve the QoE of UEs. In order to efficiently solve this problem, we propose the joint video frame resolution scaling, task offloading, and resource allocation algorithm based on the Deep Q-Learning Network (JVFRS-TO-RA-DQN), which effectively overcomes the sparsity of the single-layer reward function and accelerates the training convergence speed. JVFRS-TO-RA-DQN consists of two DQN networks to reduce the curse of dimension, which respectively select the offloading and resource allocation action, the resolution scaling action. Experimental results show that JVFRS-TO-RA-DQN can effectively reduce the cost of transmission and computation, and have better performance in convergence compared to other baseline.

The metrological performance of FBG strain sensing systems is a critical premise for the precision of plastics water support pipeline structural deformation measurement, but the strain transfer loss of FBG attached on the plastics pipe subjected by dynamic force is unclear. This paper presents the first study on the effects of strain transfer between FBG, and acrylate polymer blended with poly resin (ABR)pipe sheets loaded by static and dynamic force. Theoretical methods of dynamic strain transfer theory combine with the exponentially decaying sinusoidal shock force time course is deduced and various dynamic parameters sensitivities studies are carried out, as well as that of the geometric parameters. The result of the dynamic theory is compared with the calibration test outcomes, while the ASTR of FBG attached on ABR sheet is compared with distributed optical fiber sensors (DOFS) and other pipe materials such as PVC, concrete, and steel. Results show that the ASTR of FBG is more accurate than that of the DOFS, and the grows of ASTR depending on the paste length of FBG, the Young's modulus of the middle materials, the thickness of the middle materials and attenuation coefficient. Paste length produced the largest increase, yet the magnitude and loading speed of the external force has unexpectedly little effect on ASTR. FBG seem low error, insensitive with dynamic force and independent with the material of matrix, and this demonstrates benefits that are stronger across the board than DOFS. This is not currently recognized by standards or by most reported studies.

The mechanism of immune activation and de-activation is very important. Host should trigger effective immunity against pathogen infection. And, host cannot trigger immunity against self-antigens that will lead to detrimental autoimmune disorders. Spleen and liver have opposite roles in mediating immune responses. Spleen is the organ involving in immune activation, and liver is the organ involving in immune de-activation. Sympathetic nerve system and parasympathetic nerve system have opposite roles in mediating immune responses. Sympathetic nerve system is involving in pro-inflammatory, and parasympathetic nerve system is involving in anti-inflammatory. ACTH and glucocorticosteroid have opposite roles in mediating immune responses. ACTH is involving in activating adaptive immunity with inhibiting innate immunity, and glucocorticosteroid is involving in activating innate immunity with inhibiting adaptive immunity. The molecular chaperons, heat shock proteins, which are induced by fever, have the vital roles in immune activation. On the contrary, IgD B cells and gamma-delta T cells are causing immune de-activation via the mechanism of clonal anergy. These mechanism can help us the know the work of immunological pathways better for better control of infectious diseases and autoimmune disorders.

Maize varieties with high amylose proportion are more valuable for starch industry. The SBEⅡb gene encodes one of the starch branching isozymes (SBEⅠ, SBEⅡa, and SBEⅡb). Its recessive mutant amylose-extender (ae/sbe2b) decreases the total activities of SBEs and increases amylose proportion up to 60%. Here, the breeding potential of introduced germplasm line GEMS-0067 was evaluated by genotyping and phenotyping. The deletion of the ninth exon of the SBEⅡb gene, high amylose proportion, and the typical irregular granules suggested that this germplasm line was derived from the same resource of high amylose line AE11. The gelatinization and thermal properties, and degree of polymerization of starch chain showed its advantages used for high amylose breeding. However, the negative correlation between amylose proportion and starch content, as well as ker-nel filling characteristics should be overcome during breeding process.

In this study, a matched-mode autoregressive source depth estimation method (MMAR) based on autoregressive (AR) wavenumber estimation is proposed for a moving source in shallow water waveguides. The signal original frequency and the environmental parameters, namely, the sound speed profile and bottom properties are known as a prior knowledge. The mode wavenumbers are estimated by the AR modal wavenumber spectrum. On the basis of the mode wavenumber estimation, the mode amplitudes can be estimated by the wavenumber spectrum that is obtained by generalized Hankel transform. The source depth estimation is determined by the peak of source depth function wherein the data mode best matches the replica mode that is calculated using a propagation model. Compared with other methods of moving source depth estimation, the proposed method exhibits a better performance in source depth estimation under low signal-to-noise ratio or the small range span. The selection of horizontal line array depth is illustrated by simulation and normal mode theory in details.

The present study was conducted to investigate the effects of rhizome extract of Dioscorea batatas (Dioscoreae Rhizoma, Chinese Yam) and its bioactive compound, allantoin, on myoblast differentiation and mitochondrial biogenesis in skeletal muscle cells. Yams were extracted in water and the extract was analyzed by HPLC. The expression of C2C12 myotubes differentiation and mitochondrial biogenesis regulators were determined by reverse transcriptase (RT)-PCR or Western blot. The glucose levels and total ATP contents were determined by glucose consumption, glucose uptake and ATP assays, respectively. Treatment with yam extract (1 mg/mL) and allantoin (0.2 and 0.5 mM) significantly increased of MyHC expression compared with non-treated myotubes. Yam extract and allantoin significantly increased the expression of mitochondrial biogenesis regulating proteins, PGC1?, Sirt-1, NRF-1, and TFAM, as well as the phosphorylation of AMPK and ACC in C2C12 myotubes. Furthermore, yam extract and allantoin significantly increased the glucose uptake levels and the ATP contents. Finally, HPLC analysis revealed that the yam extract contained 1.53% of allantoin. Yam extract and allantoin, stimulated myoblast differentiation into myotubes and increased energy production through upregulation of mitochondrial biogenesis regulators. These findings indicate that yam extract and allantoin can help to prevent the skeletal muscle dysfunction through stimulation of energy metabolism.

To achieve user retention through multifactor synergy, Internet enterprises must reduce costs and increase efficiency and sustainable development. In response to the dilemma that Internet compa-nies are experiencing increasingly high user acquisition costs and serious user churn, this paper uses a sample of 46,695 user reviews of nine product series from Xiaomi Ecological Chain. Case studies and qualitative comparative analysis are used to explore the influence mechanisms of quality of experience, brand trust, and brand attachment on users' retention intentions. Our find-ings are as follows. (1) Brand attachment alone is not necessary for high user retention intention, but user perception, cognition, and brand trust are necessary. (2) Quality of experience positively impacts brand trust, attachment, and user retention intention. Therefore, improving user perception and cognition is critical in generating high user retention intention. (3) Five configuration paths can achieve high user retention intention, three configuration paths lead to low user retention intention, and there is an asymmetric relationship between these paths. Among them, the role of quality of experience-driven configuration paths in generating user retention intention is the most prominent. (4) In the substitution relationship between configuration paths, user perception, and cognition can substitute with brand trust and attachment. Our findings have important theoretical and practical implications for revealing the realization paths of high user retention intention in Internet companies and provide a new perspective for future research.

We analyzed the SARS-CoV-2 spike (S) protein amino acid sequence extracted from 11,542 viral genomic sequences submitted to the Global Initiative on Sharing All Influenza Data (GISAID) database through April 27, 2020. Consistent with prior reports, we found a major S protein mutation, D614 to G614, that was represented in 56% of all the analyzed sequences. All other mutations combined were less than 10%. After parsing the data geographically, we found most of the Chinese patient samples showed D614 (97%). By contrast, most patient samples in many European countries showed G614 (51 to 88%). In the United States, the genotypic distribution in California and Washington was similar to Asian countries, while the distribution in other US states was comparable to Europe. We observed a dramatic increase in the frequency of G614 over time in multiple regions, surpassing D614 when both were present, suggesting G614 S protein virus outcompetes D614 S protein virus. To gain insight into the consequences of the D614G mutation, homology modeling using a multi-template threading mechanism with ab initio structural refinement was performed for a region of the S protein (S591 to N710) spanning the D614G mutation and the S1 furin cleavage site. Molecular models of this region containing D614 or G614 revealed a major difference in secondary structure at the furin domain (RRARS, R682 to S686). The D614 model predicted a random coil structure in the furin domain whereas the G614 model predicted an alpha helix. Critical residues in the cleavage domain of G614 model were found to better align with the PDB structure of a furin inhibitor. Thus, homology modeling studies suggest a potential mechanism whereby the D614G mutation may confer a competitive advantage at the furin binding domain that may contribute to the rise of the D614G SARS-CoV-2 mutant.

In this 2 x 2 between-subjects experimental study, a virtual reality (VR) laboratory simulation is paired with a VR molecular world intervention to teach chemistry concepts. The independent variables are the implementation timing of the molecular world intervention (Pre-lab vs. Integrated) and the level of embodiment (Traditional vs. VR). Eighty students (N = 80), ages 11-18 years old, from a community center in New York City participated, completing a pretest, the laboratory simulation, the molecular intervention, and a post-test. The pre- and post-test measures included multiple-choice, free-response, and drawing questions. A key finding was that integrating the intervention within the lab simulation, no matter which level of embodiment, led to significantly higher gains in learning. The combination of using physical manipulatives and integrating them within the lab exercise (Integrated Traditional condition) demonstrated the greatest gains overall. On drawing measures, the Integrated VR condition showed significant improvement in three out of the four drawing categories (i.e., molecule shape, atom quantity, and relative sizes). The implications are that even though using a VR molecular world intervention can lead to significant learning of abstract chemistry content, the use of physical manipulatives is still a more effective tool.

The high-quality development of urban-rural integration is a vital component of China's economy, serving as a strategic response to the in-depth deployment of new urbanization and rural revitalization strategies. This integration is underscored by the promotion of entrepreneurship in agriculture, rural areas, and among farmers, which acts as a driver for fostering high-quality development in urban-rural areas through market competition. The resulting influx of resources and commodities with similar characteristics plays a crucial role in bridging the urban-rural divide. To maintain objectivity, it is important to adopt a balanced approach and refrain from using biased language. This study delves into the connotation and internal mechanism of the high-quality development of urban-rural integration, centering on the principle of 'quality'. Specifically, it examines the role of entrepreneurship in agriculture, rural areas, and among farmers, and evaluates its direct impact and transmission mechanism. The research employs balanced panel data from 41 cities in the Yangtze River Delta region spanning from 2003 to 2021. The findings reveal that entrepreneurship in agriculture, rural areas, and among farmers serves as a catalyst for promoting high-quality urban-rural development through the construction of a virtuous cycle, whereby resource factors and commodity services are exchanged. Moreover, this deep integration yields diverse effects across economic, spatial, demographic, social, and ecological domains, underscoring the necessity of continued support for entrepreneurship in agriculture, rural areas, and among farmers to facilitate a seamless urban-rural economic cycle and fully realize the benefits of high-quality development.

Objective: To study the factors affecting the time of umbilical cord shedding in premature infants.Methods: A total of 151 premature infants who were born in the obstetrics department of a Class III hospital in Hefei from November 2020 to June 2021 were selected as subjects. All premature infants and their families met the complete inclusion criteria. A total of 33 related factors from 3 aspects, including the birth situation of premature infants, the condition of premature infants in hospital and the condition of pregnant mothers, were collected for univariate analysis and multiple Logistic regression analysis. The relevant factors affecting the umbilical cord shedding time of premature infants were screened through the univariate analysis results, and the main factors affecting the umbilical cord shedding time of premature infants were screened through the multiple Logistic regression analysis results.it was found that the weight, gestural age, admission age, whether the premature infants were combined with NRDS, the use of antibiotics, the duration in the warm box, the initial temperature in the warm box, the duration of light therapy, the degree of Apgar for 1 minute, the maternal education level had an effect on the time of umbilical cord shedding of premature infants (P < 0.05). Through Logistic multiple regression analysis, it was screened that the duration of premature infants in the incubator was the main factor affecting the umbilical cord shedding time of premature infants (P < 0.05).Conclusion: Factors such as premature infants' weight, gestural age, admission age, whether they are combined with NRDS, antibiotic use, duration in the incubator, initial temperature in the incubator, duration of phototherapy, Apgar level of 1 minute, and maternal education level will affect the umbilical cord shedding time of premature infants. Among them, duration in the incubator is the main factor affecting the umbilical cord shedding time of premature infants.

Feedback trading theory is one of the most primitive theories about financial market. But for a long time，researches and modelings on this topic are rarely seen. The model in this paper shows the effects of sentiment shocks on asset prices in a market characterized by feedback trading in the long run. We find that，generally，feedback trading will lead to cognitive bias effect and trading inducement effect. Cognitive bias effect increases with the feedback trading parameter ( FTP) . In our model，the abnormal volatility of asset prices is captured by cognitive bias effect，sentiment shock effect and trading inducement effect．

African swine fever has damaged the foundation of China’s hog industry, caused a serious decline in hog production, highlighted the contradiction between supply and demand in the pork market, and led to major economic and social impacts. This study measured the industrial resilience of 31 Chinese provinces which faced the African swine fever shock and its spatial and temporal differentiation characteristics from 2018-2021 in terms of the two dimensions of resistance and recoverability. Using Geodetector, the study explored the key factors influencing the resilience of China’s hog industry. The results showed that 2018-2019 and 2020-2021 were the resistance and recovery periods of the hog industry under the African swine fever shock, respectively, with poor resilience characterizing the resistance period and improved resilience exemplifying the recovery period. At the early stage of the African swine fever outbreak, Tianjin, Shanxi, Guangxi and Yunnan had robust resistance in the hog industry, and the slaughter rate, economic level, mortality rate, carcass weight and culling rate showed the highest explanation for the resistance. At the most severe stage of the outbreak, the resistance of the hog industry in all provinces was generally poor, and the slaughter rate, per capita consumption and scale level showed the highest explanation for the resistance. In the period of rapid recovery of hog production, the recoverability of each province was very strong, and the industrial structure, culling rate, economic level and resource carrying capacity showed the highest explanation for the recoverability. In the reasonable adjustment period of hog production capacity, the recoverability based on the breeding sow inventory in 13 provinces, including Henan, Shandong and other large hog breeding provinces, was negative, and the scale level, slaughter rate, per capita consumption and resource carrying showed the highest explanation for the recoverability. It is recommended to take measures to enhance the resilience of the hog industry, strengthen the prevention and control of hog epidemics, improve the monitoring and early warning mechanism, and strive to enhance the ability of the hog industry to cope with major animal epidemics.

In this paper, under the symmetric entropy and the scale squared error loss functions, we consider the maximum likelihood (ML) estimation and Bayesian estimation of the Shannon entropy and Rényi entropy of the two-parameter inverse Weibull distribution. In the ML estimation, the dichotomy is used to solve likelihood equation. In addition, the approximation confidence interval is given by the Delta method. Because the form of estimation results is more complex in the Bayesian estimation, the Lindley approximation method is used to achieve the numerical calculation. Finally, Monte Carlo simulations and a real data set are used to illustrate the results derived. By comparing the mean square error between the estimated value and the real value, it can be found that the performance of ML estimation of Shannon entropy is better than that of Bayesian estimation, and there is no significant difference between the performance of ML estimation of Rényi entropy and that of Bayesian estimation.

The scheme to realize high speed (~250Gb/s) all-optical Boolean logic gates using semiconductor optica amplifiers with quantum-dot (QD-SOA) is introduced and analyzed in this review. Numerical simulation method was presented by solving the rate equation and taking into account nonlinear dynamics including carrier heating and spectral hole-burning. Binary phase shift keyed (BPSK) signal and on-off keyed signal are used to generate high speed all-optical logic gates. The applications based on all-optical logic gates such as, all-optical latches, pseudo random bit sequence (PRBS) generation and all-optical encryption, are also discussed in this review. Results show that the scheme based on QD-SOA is a promising method for the realization of high speed all-optical communication system in the future.

Positioning based on wireless signals such as mobile communication networks has become an important means to provide high-precision location services in environments where satellite signals are blocked. In complex environments such as indoor and underground, wireless signal propagation is obstructed and non-line-of-sight (NLOS) phenomena appears due to serious occlusion and reflection. The time delay caused by NLOS effects has little impact on communication system but can significantly increase positioning errors in positioning systems. Therefore, effective suppression of NLOS errors is crucial to improving 5G positioning accuracy. To address the insufficient feature extraction of existing NLOS error suppression methods, the neglect of residual NLOS measurement errors, and poor stability of position estimation results, this paper innovatively proposes a NLOS mitigation and location estimation method for 5G positioning terminals. Simulation and experimental test results demonstrate that the proposed method outperforms the comparative methods both theoretically and practically, achieving an average positioning accuracy of 1.85 meters in complex indoor NLOS environments. The method proposed in this paper provides a new strategy for NLOS error suppression in indoor 5G positioning, which can significantly contribute to high-precision location services based on commercial 5G networks.

Wind energy is a kind of renewable energy with great potential for development. This study mainly investigated the application of shock waves generated by high-pressure gases (wind energy) for generating energy. In this study, we designed a new supersonic shock wave generator that can be reused without disassembling and assembling bolts and developed a supersonic shock wave monitoring system. This system monitored the velocity of the generated shock waves, which was Mach 3-5, and the output pressure was more than 100 times higher than the input pressure of the shock wave generator tank.Then, we developed a power generation system driven by supersonic shock waves based on the characteristics of the new shock wave generator, which can generate high-pressure and high-speed blast waves and can be reused. The shock wave generator can repeatedly generate high-pressure waves to drive the Tesla turbine and then the magnetic energy generator for power generation. We established a complete control process for power generation driven by shock waves by controlling the valve stem. The system can detect the tank pressure, output pressure, gas flow, rotation speed, voltage, and current during the control process for the performance analysis of power generation.