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Autonomous navigation in farmlands is one of the key technologies for achieving autonomous management in maize fields. Among various navigation techniques, visual navigation using widely available RGB images is a cost-effective solution. However, current mainstream methods for maize crop row detection often rely on highly specialized, manually devised heuristic rules, limiting the scalability of these methods. To simplify the solution and enhance its universality, we propose an innovative crop row annotation strategy. This strategy, by simulating the strip-like structure of the crop row's central area, effectively avoids interference from lateral growth of crop leaves. Based on this, we developed a deep learning network with a dual-branch architecture, InstaCropNet, which achieves end-to-end segmentation of crop row instances. Subsequently, through the row anchor segmentation technique, we accurately locate the positions of different crop row instances and perform line fitting. Experimental results demonstrate that our method has an average angular deviation of no more than 2°, and the accuracy of crop row detection reaches 96.5%.

Driven by rapid advancements in technology and data science, a revolutionary transformation is sweeping across environmentally friendly cities worldwide. This surge stems from a pressing need to tackle the intricate complexities of urban sustainability, encompassing everything from infrastructure and governance to fragmented design and technological solutions. To effectively manage these complexities and accurately measure, assess, and optimize their sustainability performance, sustainable communities are increasingly tapping into the potential of smart city technologies, particularly big data and its fictionalized applications. This trend culminates in the emergence of smart cities. This article delves into the current state of research surrounding data-driven, environmentally conscious smart cities, aiming to assess the extent to which these two concepts are currently being integrated and identify potential gaps in this field. Through a strong emphasis on evidence-based research, the study underscores the potential of big data technologies to offer innovative approaches for monitoring, comprehending, evaluating, and ultimately managing sustainable urban development. It further highlights the crucial role of data-driven advancements in formulating strategic development policies and operational management procedures, ensuring that environmentally conscious cities can continue to contribute to sustainability goals even amidst rapid urbanization.

The influence of the sub-nano Ni3P and Cu3P phases on the microstructure, mechanical properties, and strengthening mechanism of Cu–20Pb–5Sn-xP (x = 0,0.05,0.1,0.3,0.5) alloy were discussed under the addition of P to obtain a new Pb–Sn bronze alloy applying for bimetallic cylinder block. The results showed that the tensile strength and hardness of the Pb–Sn bronze alloy increase with the P contents, while the elongation increased first and then decreased. The main strengthen mechanism was that sub-nano Ni3P and Cu3P phases dispersed in the matrix, hindering the movement of dislocations during deformation. Additionally, the grain refinement also contributed to the improvement of mechanical properties. The Ni3P phase is easier to form than the Cu3P phase. And it is easier to combine with the matrix and more stable. The Ni3P and Cu3P phases were studied by using different characterization techniques, such as OM, SEM, EDS, XRD, TEM and First-principles, Phase diagram calculation method. When P is added to the alloy, the Ni3P phase first appears in the alloy, and when the P content increases to more than 0.3 wt%, the Cu3P phase begins to appear. This is because the Ni3P phase is easier to form than the Cu3P phase and is more stable. Only after part of P reacts with Ni dissolved in copper to form Ni3P, the remaining P and Cu can form Cu3P.

Tin-based Babbitt alloys are a widely used bearing bushing material which have good comprehensive properties. However, problems such as high-temperature softening and insufficient bearing capacity occur during their use, so the optimization of tin-based Babbitt alloys has become a research hotspot. In this paper, ZChSnSb11-6 alloy was mainly prepared by the gravity casting method, and different amounts of Zn were added to the alloy (the mass fraction values were 0 wt.%, 0.05 wt.%, 0.1 wt.%, 0.15 wt.%, and 0.2 wt.%, respectively). Through the hardness test, the tensile test, the friction and wear test, and the microstructure observation of the prepared alloy, the influence of Zn on the organization and properties of the ZChSnSb11-6 alloy was analyzed. The results show that the size of the SnSb hard phase changed with the increasing content of Zn. The size of the hard phase of the SnSb tended to increase first and then decrease, and the number of phase particles increased first and then decreased, resulting in changes in performance. Through comparison, it was learned that the addition of Zn can effectively improve the hardness, tensile strength, yield strength, and wear resistance of the alloy, but the elongation rate was reduced. When the Zn content was 0.1 wt.%, the hardness value of the alloy reached the maximum value, 25.82 HB, which increased by 7.3% when compared with the sample without Zn. The hardness of the Zn, 0.15 wt.%, is close to that of the Zn, 0.1 wt.%. Compared to the sample without Zn, the tensile strength and elongation of the alloy were maximized at a Zn content of 0.15 wt.%. Compared to the sample without the Zn, the tensile strength was increased by 21.29%, and the elongation rate was increased by 46%. An analysis showed that the alloy has good comprehensive mechanical properties when the Zn content is 0.15 wt.%.

Weed competitiveness monitoring is crucial for field management at specific locations. Recent research in the fusion of multimodal data from unmanned aerial vehicles (UAVs) has propelled this advancement. However, these studies merely stack extracted features equivalently, neglecting the full utilization of fused information. This study utilizes hyperspectral and LiDAR data collected by UAVs to proposes a multimodal deep fusion model (MulDFNet) using Transformer and multi-layer residuals. It utilizes a comprehensive competitive index (CCI-A) based on multidimensional phenotypes of maize to assess the competitiveness of weeds in farmland ecosystems. To validate the effectiveness of this model, a series of ablation studies were conducted involving different modalities data, with/without the Transformer Encoder (TE) modules, and different fusion modules (shallow residual fusion module, deep feature fusion module). Additionally, a comparison was made with early/late stacking fusion models, traditional machine learning models, and deep learning models from relevant studies. The results indicate that the multimodal deep fusion model utilizing HSI, VI, and CHM data achieved a predictive effect of R2 = 0.903 (RMSE = 0.078). Notably, the best performance was observed during the five-leaf stage. The combination of shallow and deep fusion modules demonstrated better predictive performance compared to a single fusion module. The positive impact of the TE module on model performance is evident, as its multi-head attention mechanism aids in better capturing the relationships and importance between feature maps and competition indices, thereby enhancing the model's predictive capability. In weed competition prediction, the multimodal deep fusion model proposed in this study has demonstrated significantly better predictive performance compared to early/late stacking fusion models and other machine learning models (RF, SVR, PLS, DNN-F2 and Multi-channel CNN). Overall, the multimodal deep fusion model developed in this study demonstrates outstanding performance in assessing weed competitiveness and can predict the competitive intensity of weeds in maize across various growth stages on a broad scale.

The current aseismic design has seldom considered the effect caused by underlain tunnels. Previous studies focused on the scenarios of tunnels embedded in homogeneous soil under transverse seismic excitation. This paper aims to investigate the tunnel effect on the surface acceleration response in soil-rock strata by shaking table tests. Three sets of excitations are employed and input along the shaking table in both transverse and longitudinal directions. The soil-rock site is classified as four micro-zones with varying conditions, to mount observation stations of acceleration sensors. Dynamic characteristics of the four zones are identified by the transfer function (TF) method, and the tunnel effect on the ground acceleration response is obtained by comparing the spectral acceleration results between the free-field and ground-tunnel models. The test results indicate that the tunnel effect varies with the site conditions. Distinctively, a significant amplification effect is observed at the A4 zone, located on the soil deposit near the soil-rock interface. Then, it is proved that the scattering waves generated at the interface and the standing waves trapped between the tunnel and upper ground surface account for the amplification, revealed by the discrepancies of the TF results and acceleration details between the free-field and ground-tunnel models.

Bee products, abundant in bioactive ingredients, have been utilized in both traditional and contemporary medicine. Their antioxidant, antimicrobial, and anti-inflammatory properties make them valuable for food, preservation, and cosmetics applications. Honeybees are a vast reservoir of potentially beneficial products such as honey, bee pollen, bee bread, beeswax, bee venom, and royal jelly. These products are rich in metabolites vital to human health, including proteins, amino acids, peptides, enzymes, sugars, vitamins, polyphenols, flavonoids, and minerals. The advancement of nanotechnology has led to a continuous search for new natural sources that can facilitate the easy, low-cost, and eco-friendly synthesis of nanomaterials. Nanoparticles (NPs) are actively synthesized using honeybee products, which serve dual purposes in preventive and interceptive treatment strategies due to their richness in essential metabolites. This review aims to highlight the potential role of bee products in this line and their applications as catalysts and food preservatives and to point out their anticancer, antibacterial, antifungal, and antioxidant underlying impacts. The research used several online databases, namely Google Scholar, Science Direct, and Sci Finder. The overall findings suggest that these bee-derived substances exhibit remarkable properties, making them promising candidates for the economical and eco-friendly production of NPs.

This paper describes the design and implementation of a novel three-axis attitude control autopilot scheme for tube-launched, air-deployed UAVs. In early flight tests, various factors, such as model uncertainties during launch, aerodynamic uncertainties, geometric parameter changes during deployment, and significant uncertainties in booster rocket installation, exceeded the control capabilities of the attitude autopilot, causing flight instability. In order to address these issues, a numerical simulation model of the full launch process considering deviations was established based on early flight tests. A cascade attitude controller was then designed using an extended state observer (ESO), and the boundedness of control errors under unknown bounded disturbances was theoretically proven, providing requirements for the parameter tuning of the cascade controller. Comparative experiments and a second flight test both demonstrate that the ESO-based cascade attitude controller exhibits strong feedforward disturbance compensation under high-uncertainty conditions, effectively achieving stable control within the flight envelope.

With the increase in the number of Global Navigation Satellite System (GNSS) satellites and their operating frequencies, richer observation data are provided for the tightly coupled Global Navigation Satellite System/Inertial Navigation System (GNSS/INS). In this paper, we propose an efficient and robust combined navigation scheme to address the key issues of system accuracy, robustness, and computational efficiency. The tightly combined system fuses multi-source data such as the pseudo-range, the pseudo-range rate, and dual-antenna observations from the GNSS and the horizontal attitude angle from the vertical gyro (VG) in order to realize robust navigation in a sparse satellite observation environment. In addition, to cope with the high computational load faced by the system when the satellite observation conditions are good, we propose a weighted quasi-optimal satellite selection algorithm that reduces the computational burden of the navigation system by screening the observable satellites while ensuring the accuracy of the observation data. Finally, we comprehensively evaluate the proposed system through simulation experiments. The results show that, compared with the loosely coupled navigation system, our system has a significant improvement in state estimation accuracy and still provides reliable attitude estimation in regions with poor satellite observation conditions. In addition, in comparison experiments with the optimal satellite selection algorithm, our proposed satellite selection algorithm demonstrates greater advantages in terms of computational efficiency and engineering practicability.

Abstract Pangolin is a mysterious animal in the Family Pholidota, Mammalia. Malayan pangolin (Manis javanica) is one of eight existing species and is listed in Manis. With the number of wild pangolins (Manis spp.) rapidly decreasing, captive breeding has become an important way to protect them from extinction. The research on mating behavior of pangolins is an important content to understand its reproductive characteristics and develop breeding management. From 2016 to 2022, a total of 360 mating events were observed in six males and 24 females through closed circuit television (CCTV) surveillance. The results show that males do not engage in complex courtship behavior before mating. In addition, we found that male pangolins adopted a ventrolateral mating position. Once males selected the side (left/right) of the female pangolin from which to approach to mate, they usually remained on the same side for subsequent mating, suggesting that male pangolins may have a preference in mating position. Finally, all mating events were observed at 1.72 ± 1.47 (n = 83, Mean ± SD) days after cohabitation and adjustment time before mating (from the male touching the female to intromission) took 4.98 ± 3.86 mins (n = 323). During mating, males hugged females and remained still for 47.37 ± 10.08 seconds (n = 323), which is the ejaculation and post-ejaculation quiescent time. Remarkably, we observed for the first time two peak mating times, 19:00 to 22:00 and 1:00 to 3:00, suggesting that they may have a preference for mating times. This study provides new insight into the mating behavior of M. javanica and contributes to the development of scientific conservation measures to improve the reproductive capacity of M. javanica.

For interconnected system, this paper proposes a control strategy of virtual oscillators with adjustable tie line power. A distributed intra-region control layer is designed based on the dispatchable virtual oscillator-controlled converters. It achieves the distribution of power and maintains frequency stability in different regions. The dispatchable virtual oscillator control improves the transient stability of the system, and the distributed structure enhances the system communication reliability. Further, a centralized inter-region control layer is designed based on the existing scheduling system. It enables power regulation of tie lines and maintains the frequency stability of the whole system. The proposed control strategy is simulated in a high percentage of new energy interconnected system for both sudden load changes and tie line power regulation. The results verify the effectiveness of the method for tie line power regulation and frequency recovery in the interconnected system.

Object detection in computer vision requires a sufficient amount of training data to produce an accurate and general model. However, aerial images are difficult to acquire, so the collection of aerial image datasets is a priority issue. Building on the existing research on image generation, the goal of this work is to create synthetic aerial image datasets that can be used to solve the problem of insufficient data. We generated three independent datasets for ship detection using engine and generative model. These synthetic datasets are rich in virtual scenes, ship categories, weather conditions, and other features. Moreover, we implemented domain-adaptive algorithms to address the issue of domain shift from synthetic data to real data. To investigate the application of synthetic datasets, we validated the synthetic data using six different object detection algorithms and three existing real-world, ship detection datasets. The experimental results demonstrate that the methods for generating synthetic aerial image datasets can complete the insufficient data in aerial remote sensing. Additionally, domain-adaptive algorithms could further mitigate the discrepancy from synthetic data to real data, highlighting the potential and value of synthetic data in aerial image recognition and comprehension tasks in the real world.

Apples are usually bagged during the growing process, which can effectively improve the quality. Establishing an in situ nondestructive testing model for in-tree apples is very important for fruit companies in selecting raw apple materials for valuation. Low-maturity apples and high-maturity apples were acquired separately by a handheld tester for the internal quality assessment of apples developed by our group, and the effects of the two maturity levels on the soluble solids content (SSC) detection of apples were compared. Four feature selection algorithms, like ant colony optimization (ACO), were used to reduce the spectral complexity and improve the apple SSC detection accuracy. The comparison showed that the diffuse reflectance spectra of high-maturity apples better reflected the internal SSC information of the apples. The diffuse reflectance spectra of the high-maturity apples combined with the ACO algorithm achieved the best results for SSC prediction, with a prediction correlation coefficient (Rp) of 0.88, a root mean square error of prediction (RMSEP) of 0.5678 °Brix, and a residual prediction deviation (RPD) value of 2.466. Additionally, the fruit maturity was predicted using PLS-LDA based on color data, achieveing accuracies of 99.03% and 99.35% for low- and high-maturity fruits, respectively. These results suggest that in-tree apple in situ detection has great potential to enable improved robustness and accuracy in modeling apple quality.

Metabolic disorders, encompassing diabetes mellitus, cardiovascular diseases, gastrointestinal disorders, etc., pose a substantial global health threat, with rising morbidity and mortality rates. Addressing these disorders is crucial, as conventional drugs often come with high costs and adverse effects. This review explores the potential of royal jelly (RJ), a natural bee product rich in bioactive components, as an alternative strategy for managing metabolic diseases. RJ exhibits diverse therapeutic properties, including antimicrobial, estrogen-like, anti-inflammatory, hypotensive, anticancer, and antioxidant effects. This review’s focus is on investigating how RJ and its components impact conditions like diabetes mellitus, cardiovascular disease, and gastrointestinal illnesses. Evidence suggests that RJ serves as a complementary treatment for various health issues, notably demonstrating cholesterol- and glucose-lowering effects in diabetic rats. Specific RJ-derived metabolites, such as 10-hydroxy-2-decenoic acid (10-HDA), also known as the “Queen bee acid,” show promise in reducing insulin resistance and hyperglycemia. Recent research highlights RJ’s role in modulating immune responses, enhancing anti-inflammatory cytokines, and suppressing key inflammatory mediators. Despite these promising findings, further research is needed to comprehensively understand the mechanisms underlying RJ’s therapeutic effects.

Abstract In this paper, graphene reinforced aluminum matrix composites are successfully prepared by high-energy ball milling. The results show that no graphene agglomeration is found in the mixed powder. The complex composites prepared by high energy ball milling and powder metallurgy have approximately 4–5 layers of graphene and the thickness of single-layer graphene is approximately 0.334 nm. The final experimental results confirm the formation of compound AlC3 in the microstructure, and its diffraction spot index is ( $$\overline{2 }$$ 2 ¯ 00), ( $$\overline{1 }$$ 1 ¯ 1 $$\overline{1 }$$ 1 ¯ ) and (11 $$\overline{1 }$$ 1 ¯ ). The maximum friction coefficient is 0.126, and the average friction coefficient is 0.027, suggesting good wear resistance and corrosion resistance. Additionally, the friction corrosion mechanism of the material is deeply analyzed. The results of strengthening mechanism analysis show that the main strengthening mechanism of the materials designed in this experiment is thermal mismatch strengthening. It can be concluded that the yield strength of the material calculated by the modified model is 227.75 MPa. This value is slightly lower than the calculated value of the general shear lag model (237.68 MPa). However, it is closer to the yield strength value of the actual material (211 MPa).

The use of gelatin and gelatin-blend polymers as environmentally safe polymers to synthesis electrospun nanofibers, has caused a revolution in the biomedical field. The development of efficient nanofibers has played a significant role in drug delivery, and for use in advanced scaffolds in regenerative medicine. Gelatin is an exceptional biopolymer, which is highly versatile, despite variations in the processing technology. The electrospinning process is an efficient technique for the manufacture of gelatin electrospun nanofibers (GNFs), as it is simple, efficient, and cost-effective. GNFs have higher porosity with large surface area and biocompatibility, despite that there are some drawbacks. These drawbacks include rapid degradation, poor mechanical strength, and complete dissolution, which limits the use of gelatin electrospun nanofibers in this form for biomedicine. Thus, these fibers need to be cross-linked, in order to control its solubility. This modification caused an improvement in the biological properties of GNFs, which made them suitable candidates for various biomedical applications, such as wound healing, drug delivery, bone regeneration, tubular scaffolding, skin, nerve, kidney, and cardiac tissue engineering. In this review an outline of electrospinning is shown with critical summary of literature evaluated with respect to the various applications of nanofibers-derived gelatin.

Fast nondestructive detection technology in food quality and safety evaluation is a powerful support tool that fosters informatization and intelligence in the food industry, characterized by its rapid processing, convenient operation, and seamless online inspection [...]

Arctium lappa L. is a medicinal edible homologous plant, commonly known as burdock or bardana, which belongs to the Asteraceae family. It is widely distributed throughout Northern Asia, Europe, and North America and has been utilized for hundreds of years. The roots, fruits, seeds, and leaves of A. lappa have been extensively used in traditional Chinese Medicine (TCM). A. lappa has attracted a great deal of attention due to its possession of highly recognized bioactive metabolites with significant therapeutic potential. Numerous pharmacological effects have been demonstrated in vitro and in vivo by A. lappa and its bioactive metabolites, including antimicrobial, anti-obesity, antioxidant, anticancer, anti-inflammatory, anti-diabetic, anti-allergic, antiviral, gastroprotective, hepatoprotective, and neuroprotective activities. Additionally, A. lappa has demonstrated considerable clinical efficacies and valuable applications in nanomedicine. Collectively, this review covers the properties of A. lappa and its bioactive metabolites, ethnopharmacology aspects, pharmacological effects, clinical trials, and applications in the field of nanomedicine. Hence, a significant attention should be paid to clinical trials and industrial applications of this plant with particular emphasis, on drug discovery and nanotechnology.

IntroductionIntercropping has a potential to reduce the CO2 emission from farmlands. Limited information is available on the underlying reasons.MethodsThis study investigated the effect of milk vetch (Astragalus sinicus L.) (MV), rapeseed (Brassica napus L.) monoculture (RS) and intercropping (Intercrop) on soil CO2 emissions, moisture and temperature in a bucket experiment during 210 days from October 2015 to May 2016 on Chongqing, China.ResultsThe results showed that soil CO2 efflux of MV, RS and Intercrop was 1.44, 1.55 and 2.08 μmol·m-2·s-1 during seedling and stem elongation stages and 3.08, 1.59 and 1.95 μmol·m-2·s-1 during flowering and podding stages. At seeding and stem elongation stages Intercrop had 1.4 times higher soil CO2 efflux than the mean of MV and RS. In contrast, MVhad 1.6 times higher soil CO2 efflux than Intercrop thereafter, which shows it was inhibited if milk vetch presents as Intercrop only. Decreased sensitivity of soil respiration to temperature in 1.4 times and lower soil moisture by Intercrop were found compared to MV. Intercrop decreased soil moisture, especially at the seedling and stem elongation stages, compared to the monoculture. The fluctuation on soil respiration in RS and Intercrop was slight with changes in soil moisture.ConclusionThus, milk vetch-rapeseed system has a potential to decrease CO2 emission from farmland, however soil moisture should be regulated properly.

This article is concerned with the dynamics of malaria infection model with diffusion and delay. The disease free threshold $ \Re _0 $ and the immune response threshold value $ \Re _1 $ of the malaria infection are obtained, which characterize the stability of the disease free equilibrium and infection equilibrium (with or without immune response). In addition, fluctuations occur when the model undergoes Hopf bifurcation as the delay passes through a certain critical value $ \tau _0 $ . In this case, periodic oscillation appears near the positive steady state, which implies the recurrent attacks of disease. Finally, numerical simulations are provided to illustrate the theoretical results.

Marine cyanobacteria are an ancient group of photosynthetic microbes dating back to 3.5 million years ago. They are prolific producers of bioactive secondary metabolites. Over millions of years, natural selection has optimized their metabolites to possess activities impacting various biological targets. This paper discusses the historical and existential records of cyanobacteria, and their role in understanding the evolution of marine cyanobacteria through the ages. Recent advancements have focused on isolating and screening bioactive compounds and their respective medicinal properties, and we also discuss chemical property space and clinical trials, where compounds with potential pharmacological effects, such as cytotoxicity, anticancer, and antiparasitic properties, are highlighted. The data have shown that about 43% of the compounds investigated have cytotoxic effects, and around 8% have anti-trypanosome activity. We discussed the role of different marine cyanobacteria groups in fixing nitrogen percentages on Earth and their outcomes in fish productivity by entering food webs and enhancing productivity in different agricultural and ecological fields. The role of marine cyanobacteria in the carbon cycle and their outcomes in improving the efficiency of photosynthetic CO2 fixation in the chloroplasts of crop plants, thus enhancing the crop plant’s yield, was highlighted. Ultimately, climate changes have a significant impact on marine cyanobacteria where the temperature rises, and CO2 improves the cyanobacterial nitrogen fixation.

In the process of storage and cold chain logistics, apples are prone to physical bumps or microbial infection, which easily leads to spoilage in the micro-environment, resulting in widespread infection and serious post-harvest economic losses. Thus, development of methods for monitoring apple spoilage and providing early warning of spoilage has become the focus for post-harvest loss reduction. Thus, in this study, a spoilage monitoring and early warning system was developed by measuring volatile component production during apple spoilage combined with chemometric analysis. An apple spoilage monitoring prototype was designed to include a gas monitoring array capable of measuring volatile organic compounds, such as CO2, O2 and C2H4, integrated with the temperature and humidity sensor. The sensor information from a simulated apple warehouse was obtained by the prototype, and a multi-factor fusion early warning model of apple spoilage was established based on various modeling methods. Simulated annealing–partial least squares (SA-PLS) was the optimal model with the correlation coefficient of prediction set (Rp) and root mean square error of prediction (RMSEP) of 0.936 and 0.828, respectively. The real-time evaluation of the spoilage was successfully obtained by loading an optimal monitoring and warning model into the microcontroller. An apple remote monitoring and early warning platform was built to visualize the apple warehouse’s sensors data and spoilage level. The results demonstrated that the prototype based on characteristic gas sensor array could effectively monitor and warn apple spoilage.

The main focus of this article is on the jump-takeoff method for autogyros. On the basis of a high-confidence autogyro model, we design a jump-takeoff simulation experiment to study and optimize jump-takeoff performance. Using a simplified version of blade element theory, we conduct secondary development on the YASim dynamics library in FlightGear software and construct a highly accurate auto-rotation rotor model. The implementation of jump-takeoff requires appropriate control parameters for collective angle and pre-rotation speed. We explore the minimum collective angle condition and minimum pre-rotation speed condition to obtain the jump-takeoff envelope, and we investigate the effect of changes in control parameters within the jump envelope on jump-takeoff performance. Furthermore, we optimize the jump-takeoff performance by varying the rotor diameter and blade tip weighting. Through this study of jump-takeoff performance, we are able to determine appropriate control parameters and rotor parameters for jump-takeoff schemes, establish parameter settings for simulations of jump-takeoff tests, and thereby lay the foundation for future experimental investigations of jump-takeoff of actual autogyros.

Dicofol is a highly toxic residual pesticide in tea, which seriously endangers human health. A method for detecting dicofol in tea by combining stoichiometry with surface-enhanced Raman spectroscopy (SERS) technology was proposed in this study. AuNPs were prepared, and silver shells were grown on the surface of AuNPs to obtain core–shell Au@AgNPs. Then, the core–shell Au@AgNPs were attached to the surface of a PDMS membrane by physical deposition to obtain a Au@AgNPs/PDMS substrate. The limit of detection (LOD) of this substrate for 4-ATP is as low as 0.28 × 10−11 mol/L, and the LOD of dicofol in tea is 0.32 ng/kg, showing high sensitivity. By comparing the modeling effects of preprocessing and variable selection algorithms, it is concluded that the modeling effect of Savitzky–Golay combined with competitive adaptive reweighted sampling–partial least squares regression is the best (Rp = 0.9964, RPD = 10.6145). SERS technology combined with stoichiometry is expected to rapidly detect dicofol in tea without labels.

Tea plants absorb chromium-contaminated soil and water and accumulate in tea leaves. Hexavalent chromium (Cr6+) is a very toxic heavy metal; excessive intake of tea containing Cr6+ can cause serious harm to human health. A reliable and sensitive surface-enhanced Raman spectroscopy (SERS) method was developed using Au@Ag nanoparticles as an enhanced substrate for the determination of Cr6+ in tea. The Au@AgNPs coated with carbimazole showed a highly selective reaction to Cr6+ in tea samples through a redox reaction between Cr6+ and carbimazole. The Cr6+ in the contaminated tea sample reacted with methimazole—the hydrolysate of carbimazole—to form disulfide, which led to the decrease in the Raman intensity of the peak at 595 cm−1. The logarithm of the concentration of Cr6+ has a linear relationship with the Raman intensity at the characteristic peak and showed a limit of detection of 0.945 mg/kg for the tea sample. The carbimazole functionalized Au@AgNPs showed high selectivity in analyzing Cr6+ in tea samples, even in the presence of other metal ions. The SERS detection technique established in this study also showed comparable results with the standard ICP-MS method, indicating the applicability of the established technique in practical applications.

Honey intake is advantageous to human health due to its antioxidant, anticancer, anti-inflammatory, and antimicrobial properties, all of which are attributed to the rich bioactive compound contents. Moreover, hepatoprotective, wound healing, and gastrointestinal protective properties have been documented. Honey’s nutritional value is significantly affected by its chemical composition, which varies depending on botanical and geographical origin. In particular, after Manuka honey, Sidr honey from the Ziziphus species is the most popular. The chemical compositions, physicochemical properties, bioactive compounds, and sensory characteristics of two Sidr honey samples from Egypt and Saudi Arabia were investigated in the current study. Moisture content, electrical conductivity (EC), pH, free acidity (FA), total acidity, lactone hydroxymethylfurfural (HMF) content, and diastase (α-amylase) activity were measured. By using high-performance liquid chromatography (HPLC), mass spectrometry (LC-MS/MS), nuclear magnetic resonance (1HNMR), and solid-phase micro-extraction (SPME) coupled with gas chromatography (GC-MS) analyses, the sugar profile, non-volatile, and volatile compounds were also identified. The physicochemical analysis revealed the following results for Sidr honey from Saudi Arabia and Egypt, respectively: a moisture content of 18.03 ± 0.05% and 19.03 ± 0.06%, EC values of 1.18 ± 0.05 and 1.16 ± 0.01 mS/cm, pH values of 4.87 ± 0.08 and 5.10 ± 0.01, FA of 37.50 ± 0.05 and 36.50 ± 0.05 meq/kg, total acidity of 41.06 ± 0.05 and 37.50 ± 0.05 meq/kg, lactone of 3.49 ± 0.005 and 1 ± 0.0 meq/kg, HMF of 20.92 ± 0.02 and 11.33 ± 0.01 mg/kg, and diastase of 59.97 ± 0.05 and 8.64 ± 0.06g/100 g. Honey from Saudi Arabia and Egypt displayed 22.51 ± 0.05 and 26.62 ± 0.16 % glucose, 40.33 ± 0.06 and 35.28 ± 0.01% fructose, 8.94 ± 0.17, and 8.87 ± 0.01% sucrose, and 8.22 ± 0.006 and 8.13 ± 0.01% maltose, respectively. According to the International Honey Commission (IHC) and GCC Standardization Organization (GSO) regulations, the levels of glucose, fructose, sucrose, and maltose were near the standard levels. Flavonoids, sugars, vitamins, and nitrogen contents were additionally measured using LC-MS/MS, whereas GC-MS was employed to identify aldehydes, ketones, phenols, acids, esters, anthraquinone, hydrocarbons, and nitrogenous compounds. The results of a study on the effect of honey’s geographic origin on its broad quality are summarized. As a result, knowing its optimal chemical and physical characteristics served as the criterion and indicator of the honey’s quality.

The convergent illuminating beam is the key factor during the individual measurement of suspended particles in aquatic suspensions. When the illuminating beam propagates in the suspension, the particle scattering in the optical path may destroy the convergence of the illuminating beam, especially in suspensions with a high particle concentration. In this paper, using the Monte Carlo simulation, the convergence of the illuminating beam is investigated by changing the physical properties of particles, such as size and concentration, and the optical path length of the illuminating beam. A dimensionless quantity, as the product of the scattering coefficient of suspension and the optical path length, is found to determine the achievement of the convergent beam. Moreover, an individual measurement setup based on the convergence of the illuminating beam is used to measure polystyrene microspheres with different concentrations. The experiment results are consistent with those of the simulations. Furthermore, improvement strategies are proposed and proved to effectively keep the convergence of the illuminating beam in turbid water. The results in this work can provide clues for designing a similar optical apparatus used in aquatic environment monitoring.

This paper is concerned with the free boundary problem for a reaction-diffusion SIRI model with relapse and bilinear incidence rate. After studying the (global) existence and uniqueness of solutions, we provide some sufficient conditions on the disease spreading-vanishing dichotomies for both cases with and without relapse.

This paper proposes a malaria transmission model to describe the dynamics of malaria transmission in the human and mosquito populations. This model emphasizes the impact of limited resource on malaria transmission. We derive a formula for the basic reproductive number of infection and investigate the existence of endemic equilibria. It is shown that this model may undergo backward bifurcation, where the locally stable disease-free equilibrium co-exists with an endemic equilibrium. Furthermore, we determine conditions under which the disease-free equilibrium of the model is globally asymptotically stable. The global stability of the endemic equilibrium is also studied when the basic reproductive number is greater than one. Finally, numerical simulations to illustrate our findings and brief discussions are provided.

Scientists have been seeking ways to use Wolbachia to eliminate the mosquitoes that spread human diseases. Could Wolbachia be the determining factor in controlling the mosquito-borne infectious diseases? To answer this question mathematically, we develop a reaction-diffusion model with free boundary in a one-dimensional environment. We divide the female mosquito population into two groups: one is the uninfected mosquito population that grows in the whole region while the other is the mosquito population infected with Wolbachia that occupies a finite small region. The mosquito population infected with Wolbachia invades the environment with a spreading front governed by a free boundary satisfying the well-known one-phase Stefan condition. For the resulting free boundary problem, we establish criteria under which spreading and vanishing occur. Our results provide useful insights on designing a feasible mosquito releasing strategy that infects the whole mosquito population with Wolbachia and eradicates the mosquito-borne diseases eventually.

The nitrogen nutrition status affects the main factors of rice yield. In traditional rice nitrogen nutrition monitoring methods, most experts enter the farmland to observe leaf color and growth and apply an appropriate amount of nitrogen fertilizer according to the results. However, this method is labor- and time-consuming. To realize automatic rice nitrogen nutrition monitoring, we constructed the Jiangxi rice nitrogen nutrition monitoring model based on a convolution neural network (CNN) using the same region rice canopy image in different generation periods. Our CNN model was evaluated using multiple evaluation criteria (Accuracy, Recall, Precision, and F1 score). The results show that the same CNN model could distinguish the rice nitrogen nutrition status in different periods, which can completely realize the automatic discrimination of nitrogen nutrition status so as to guide the scientific nitrogen application of rice in this area. This will greatly improve the discrimination efficiency of the nitrogen nutrition status and reduce the time and labor cost. The application of the proposed method also proved that the CNN model can be applied in the discrimination of the nitrogen nutrition status. Among CNN models, GoogleNet model proposed a CNN architecture named Inception which can improve the depth of the network and extract higher-level features without changing the amount of calculation of the model. The GoogleNet model achieved the highest accuracy, 95.7%.

Graduate students are an important engine of national and regional development and the dominant force of contemporary scientific and technological innovation. It has become the historical mission of high-level research universities to provide strong talent support for the construction of innovative powerful countries with human resources. This investigation performed a systematic and comparative analysis of international postgraduate training models. The whole process of multidimensional training countermeasures and suggestions were proposed. Those specifically included updating the training concept, optimizing the curriculum structure, innovating teaching methods, strengthening practical training, strengthening the responsibility of the tutor, and expanding the international vision. After investigation and analysis, this research pointed out that the conditions of establishing and perfecting the examination system, evaluation mechanism, and incentive measures related to postgraduate education were guaranteed. Multiple measures to improve the quality of graduate students have certain reference significance for the current graduate education.

Abstract This paper proposes a system of difference equations to model mosquito population. In this study, we develop and analyze the stage-structured models which consist of four distinct mosquito metamorphic stages: eggs, larvae, pupae, and adults. First, a model with constant birth rate is studied, and the inherent net reproduction number ℜ0 $\Re _{0}$ of the model is derived. If ℜ01 $\Re _{0}>1$, there exists a unique positive equilibrium which is uniformly persistent. When breeding is seasonal for a special case, it indicates that a unique globally asymptotically stable periodic solution is admitted when the net reproductive number is larger than one. When this value is less than one, the mosquito population goes to extinction. Finally, numerical simulations to demonstrate our findings and brief discussion are also provided.

The kingdom of Saudi Arabia (SA) ranks fifth in Asia in terms of area. It features broad biodiversity, including interesting flora, and was the historical origin of Islam. It is endowed with a large variety of plants, including many herbs, shrubs, and trees. Many of these plants have a long history of use in traditional medicine. The aim of this review is to evaluate the present knowledge on the plants growing in SA regarding their pharmacological and biological activities and the identification of their bioactive compounds to determine which plants could be of interest for further studies. A systematic summary of the plants’ history, distribution, various pharmacological activities, bioactive compounds, and clinical trials are presented in this paper to facilitate future exploration of their therapeutic potential. The literature was obtained from several scientific search engines, including Sci-Finder, PubMed, Web of Science, Google Scholar, Scopus, MDPI, Wiley publications, and Springer Link. Plant names and their synonyms were validated by ‘The Plant List’ on 1 October 2021. SA is home to approximately 2247 plant species, including native and introduced plants that belong to 142 families and 837 genera. It shares the flora of three continents, with many unique features due to its extreme climate and geographical and geological conditions. As plants remain the leading supplier of new therapeutic agents to treat various ailments, Saudi Arabian plants may play a significant role in the fight against cancer, inflammation, and antibiotic-resistant bacteria. To date, 102 active compounds have been identified in plants from different sites in SA. Plants from the western and southwestern regions have been evaluated for various biological activities, including antioxidant, anti-cancer, antimicrobial, antimalarial, anti-inflammatory, anti-glycation, and cytotoxic activities. The aerial parts of the plants, especially the leaves, have yielded most of the bioactive compounds. Most bioactivity tests involve in vitro assessments for the inhibition of the growth of tumour cell lines, and several compounds with in vitro antitumour activity have been reported. More in-depth studies to evaluate the mode of action of the compounds are necessary to pave the way for clinical trials. Ecological and taxonomical studies are needed to evaluate the flora of SA, and a plan for the conservation of wild plants should be implemented, including the management of the protection of endemic plants.

Foreign matter (FM) in mixed congee not only reduces the quality of the congee but may also harm consumers. However, the common computer vision methods with poor recognition ability for the homochromatic FM. This study used hyperspectral reflectance images with the pattern recognition model to detect homochromatic FM on the mixed congee surface. First, spectral features corresponding to homochromatic FM and background were extracted from hyperspectral images. Then, based on the optimal spectral preprocessing method, LDA, K-nearest neighbor, backpropagation artificial neural network, and support vector machine (SVM) were used to classify the spectral features. The results revealed that the SVM model input with raw spectra principal components exhibited optimal identification rates of 99.17%. Finally, most of the pixels for homochromatic FM were classified correctly by using the SVM model. To summarized, hyperspectral images combined with pattern recognition are an effective method for recognizing homochromatic FM in mixed congee.

Releasing mosquitoes infected with the endosymbiotic bacterium Wolbachia to invade and replace the wild populations can effectively interrupt dengue transmission. Recently, a reasonable discrete competitive non-spatial model was developed and the conditions for the successful invasion of Wolbachia were given. However, Wolbachia propagation is a matter of spatial dynamics. In this paper, we introduce a dispersal kernel and establish integrodifference equations, a class of discrete-time spatial diffusion systems that have recently gained much attention as an important tool for spatial ecology. We analyzed the spatial model by average dispersal success approximation to find the criteria for the successful spread of Wolbachia, and then compared it with the non-spatial model to discuss the effect of spatial parameters.

The honey bee is an important economic insect due to its role in pollinating many agricultural plants. Unfortunately, bees are susceptible to many pathogens, including pests, parasites, bacteria, and viruses, most of which exert a destructive impact on thousands of colonies. The occurrence of resistance to the therapeutic substances used against these organisms is rising, and the residue from these chemicals may accumulate in honey bee products, subsequently affecting the human health. There is current advice to avoid the use of antibiotics, antifungals, antivirals, and other drugs in bees, and therefore, it is necessary to develop alternative strategies for the treatment of bee diseases. In this context, the impact of nosema diseases (nosemosis) on bee health and the negative insults of existing drugs are discussed. Moreover, attempts to combat nosema through the use of alternative compounds, including essential oils, plant extracts, and microbes in vitro and in vivo, are documented.

Egypt has an ongoing long history with beekeeping, which started with the ancient Egyptians making various reliefs and inscriptions of beekeeping on their tombs and temples. The Egyptian honeybee (Apis mellifera lamarckii) is an authentic Egyptian honeybee subspecies utilized in apiculture. A. m. lamarckii is a distinct honeybee subspecies that has a particular body color, size, and high levels of hygienic behavior. Additionally, it has distinctive characteristics; including the presence of the half-queens, an excessive number of swarm cells, high adaptability to climatic conditions, good resistance to specific bee diseases, including the Varro disorder, and continuous breeding during the whole year despite low productivity, using very little propolis, and tending to abscond readily. This review discusses the history of beekeeping in Egypt and its current situation in addition to its morphology, genetic analysis, and distinctive characters, and the defensive behaviors of native A. m. lamarckii subspecies.

Cardiotonic steroids (CTS) were first documented by ancient Egyptians more than 3000 years ago. Cardiotonic steroids are a group of steroid hormones that circulate in the blood of amphibians and toads and can also be extracted from natural products such as plants, herbs, and marines. It is well known that cardiotonic steroids reveal effects against congestive heart failure and atrial fibrillation; therefore, the term "cardiotonic" has been coined. Cardiotonic steroids are divided into two distinct groups: cardenolides (plant-derived) and bufadienolides (mainly of animal origin). Cardenolides have an unsaturated five-membered lactone ring attached to the steroid nucleus at position 17; bufadienolides have a doubly unsaturated six-membered lactone ring. Cancer is a leading cause of mortality in humans all over the world. In 2040, the global cancer load is expected to be 28.4 million cases, which would be a 47% increase from 2020. Moreover, viruses and inflammations also have a very nebative impact on human health and lead to mortality. In the current review, we focus on the chemistry, antiviral and anti-cancer activities of cardiotonic steroids from the naturally derived (toads) venom to combat these chronic devastating health problems. The databases of different research engines (Google Scholar, PubMed, Science Direct, and Sci-Finder) were screened using different combinations of the following terms: “cardiotonic steroids”, “anti-inflammatory”, “antiviral”, “anticancer”, “toad venom”, “bufadienolides”, and “poison chemical composition”. Various cardiotonic steroids were isolated from diverse toad species and exhibited superior anti-inflammatory, anticancer, and antiviral activities in in vivo and in vitro models such as marinobufagenin, gammabufotalin, resibufogenin, and bufalin. These steroids are especially difficult to identify. However, several compounds and their bioactivities were identified by using different molecular and biotechnological techniques. Biotechnology is a new tool to fully or partially generate upscaled quantities of natural products, which are otherwise only available at trace amounts in organisms.

Cancer is one of the major causes of death globally. Currently, various methods are used to treat cancer, including radiotherapy, surgery, and chemotherapy, all of which have serious adverse effects. A healthy lifestyle, especially a nutritional diet, plays a critical role in the treatment and prevention of many disorders, including cancer. The above notion, plus the trend in going back to nature, encourages consumers and the food industry to invest more in food products and to find potential candidates that can maintain human health. One of these agents, and a very notable food agent, is royal jelly (RJ), known to be produced by the hypopharyngeal and mandibular salivary glands of young nurse honeybees. RJ contains bioactive substances, such as carbohydrates, protein, lipids, peptides, mineral salts and polyphenols which contribute to the appreciated biological and pharmacological activities. Antioxidant, anticancer, anti-inflammatory, antidiabetic, and antibacterial impacts are among the well-recognized benefits. The combination of RJ or its constituents with anticancer drugs has synergistic effects on cancer disorders, enhancing the drug’s effectiveness or reducing its side effects. The purpose of the present review is to emphasize the possible interactions between chemotherapy and RJ, or its components, in treating cancer illnesses.

Anastatica hierochuntica L. (Cruciferae) has been known in Egyptian folk medicine as a remedy for gastrointestinal disorders, diabetes and heart diseases. Despite the wide usage, A. hierochuntica research provides insufficient data to support its traditional practice. The cytotoxicity of A. hierochuntica methanolic extract was investigated on acute myeloid leukemia blasts (AML) and normal human peripheral leucocytes (NHPL). The phytochemical identification of bioactive compounds using 1H-NMR and LC-ESI-MS was also performed. A. hierochuntica extract caused non-significant cytotoxicity on NHPL, while the cytotoxicity on AML was significant (IC50: 0.38 ± 0.02 μg/mL). The negative expression of p53, upregulation of Caspase-3 and increase in the BAX/BCL-2 ratio were reported at the protein and mRNA levels. The results suggest that A. hierochuntica extract induced AML cell death via the p53-independent mitochondrial intrinsic pathway and further attention should be paid to this plant as a promising natural anticancer agent.

The Mg-6Zn-0.5Zr (ZK60) alloy has attracted extensive attention as one of the hopeful biomedical material candidates for bone implant applications on account of its unique degradability, favorable biocompatibility as well as mechanical compatibility. Nevertheless, the rapid degradation rate in the biological environment is the major hurdle for its clinical application in the field of bone implants. In this study, nanodiamond (ND) was incorporated into ZK60 alloy via selective laser melting technology to enhance its degradation resistance. The results showed that compared with selective laser-melted ZK60 (SLMed ZK60), the selective laser-melted ZK60 with 6 wt.% ND (SLMed ZK60−6ND) possessed the better degradation resistance with the lower degradation rate of 0.5 ± 0.1 mm/year. The enhancement of the degradation resistance was attributed to the fact that ND could promote the deposition of apatite and build up a dense and insoluble protective layer through the dissociation of the carboxyl groups on the ND surface, which could effectively hinder the further degradation of the Mg matrix. Meanwhile, the compressive strength and hardness were improved mainly due to grain refinement strengthening and ND dispersion strengthening. In addition, the SLMed ZK60−6ND possessed good cytocompatibility. These results suggested that the SLMed ZK60−6ND, with enhanced degradation resistance, improved mechanical properties, and good cytocompatibility, was an excellent biomedical material candidate for bone implant applications.

Releasing mosquitoes with Wolbachia into the wild mosquito population is becoming the very promising strategy to control mosquito-borne infections. To investigate the effects of wind and critical patch size on the Wolbachia establishment in the wild mosquito population, in this paper, we propose a diffusion-reaction-advection system in a heterogeneous environment. By studying the related eigenvalue problems, we derive various conditions under which Wolbachia can fully establish in the entire wild mosquito population. Our findings may provide some useful insights on designing practical releasing strategies to control the mosquito population.

In this paper, a new mathematical model (a system of delay differential equation) is proposed to describe dynamical behaviors of malaria in an infected host with red blood cells (RBCs), infected red blood cells (iRBCs) and immune factors. The basic reproduction number $\Re_0$ of the malaria infection is derived. If $\Re_{0}\leq1$, the uninfected equilibrium $E_0$ is globally asymptotically stable. If $\Re_{0}>1$, there exists two kinds of infection equilibria. The conditions of these equilibria with respect to the existence, stability and uniform persistence are given. Furthermore, fluctuations occur when the model undergoes Hopf bifurcation, and periodic solution appears near the positive equilibrium. The direction and stability of Hopf bifurcation are also obtained by applying the center manifold method and the normal form theory. Numerical simulations are provided to demonstrate the theoretical results.

Oncolytic virotherapy is an emerging treatment modality which uses replication-competent viruses to destroy cancers without causing harm to normal tissues. By the development of molecular biotechnology, many e ective viruses are adapted or engineered to make them cancer-specific, such as measles, adenovirus, herpes simplex virus and M1 virus. A successful design of virus needs a full understanding about how viral and host parameters influence the tumor load. In this paper, we propose a mathematical model on the oncolytic virotherapy incorporating viral lytic cycle and virus-specific CTL response. Thresholds for viral treatment and virus-specific CTL response are obtained. Di erent protocols are given depending on the thresholds. Our results also support that immune suppressive drug can enhance the oncolytic e ect of virus as reported in recent literature.

Abstract In this paper we study a predator–prey system with free boundary in a one-dimensional environment. The predator v is the invader which exists initially in a sub-interval [0,s0] $[0, s_{0}]$ of [0,L] $[0,L]$ and has the Leslie–Gower terms that measure the loss in the predator population due to rarity of the prey. The prey u (the native species) is initially distributed over the whole region [0,L] $[0,L]$. Our primary goal is to understand how the success or failure of the predator’s invasion is affected by the initial datum v0 $v_{0}$. We derive a spreading–vanishing dichotomy and give sharp criteria for spreading and vanishing in this model.

Bee pollen is a natural cocktail of floral nectar, flower pollen, enzymes, and salivary secretions produced by honeybees. Bee pollen is one of the bee products most enriched in proteins, polysaccharides, polyphenols, lipids, minerals, and vitamins. It has a significant health and medicinal impact and provides protection against many diseases, including diabetes, cancer, infectious, and cardiovascular. Bee pollen is commonly promoted as a cost-effective functional food. In particular, bee pollen has been applied in clinical trials for allergies and prostate illnesses, with a few investigations on cancer and skin problems. However, it is involved in several patents and health recipes to combat chronic health problems. This review aimed to highlight the clinical trials and patents involving bee pollen for different cases and to present the role of bee pollen as a supplementary food and a potential product in cosmetic applications.