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This paper presents the establishment of a sensory evaluation system for purple sweet potato rice steamed sponge cake (PSPRSSC) utilizing fuzzy mathematics. Initially, eight key sensory evaluation indices were identified through expert consultations. These indices were subsequently prioritized using fuzzy binary comparison, resulting in the following order: aroma, taste, crust color, elasticity, viscosity, chewiness, hardness, and brightness. The corresponding weight values assigned to each index were 23%, 18%, 16%, 13%, 12%, 8%, 6%, and 4%, respectively. Notably, aroma was found to have a more significant impact than visual attributes in the sensory evaluation of PSPRSSC. Based on this prioritization, comprehensive sensory evaluation criteria for PSPRSSC were formulated. Verification tests confirmed the efficacy of the proposed evaluation system. This study provides critical data and theoretical support for the sensory quality assessment of PSPRSSC, thereby facilitating its industrialization and enhancing its market viability.

Cropland acidification seriously restricts sustainable agricultural development. The main purpose of this study was to determine whether deeper tilling could alleviate topsoil acidification to improve the quality of arable land. A soil column incubation experiment simulating tillage depths (10 cm, 30 cm and 50 cm) and lime addition was conducted to determine their effects on soil acidification improvement. The changes in soil pH, exchangeable acidity, ammonium nitrogen (NH4+-N), nitrate nitrogen (NO3−-N), available phosphorus (AP), and microbial phospholipid fatty acids (PLFA) were analyzed. Tillage depth, lime application, and their interaction all had significant impacts on soil pH. T50 (simulated tillage depth of 50 cm) and T50+Lime (simulated tillage depth of 50 cm plus lime) treatments significantly increased the topsoil pH from 5.41 to 6.35 and 7.12, respectively. T50 treatment significantly reduced the soil exchangeable acid content compared to the T10 treatment. The nutrient accumulation along soil column indicated that the T50 and T50+Lime treatments significantly increased NO3−-N and AP content in the >30–50 cm soil layer. Compared with T30, NO3−-N accumulation in the >30–50 cm soil layers of T50 and T50+Lime treatments was 6.62 and 7.93 times higher, respectively. The accumulation of AP in the >30–50 cm soil layers of the T50 and T50+Lime treatments was 1.33 and 1.54 times higher than in the T30 treatment, respectively. These findings imply tillage up to 50 cm without exogenous materials could be a potential measure to reduce topsoil acidification and increase nutrition availability of >30–50 cm soil layers. Tillage of up to 30 cm combined with lime application confers greater benefits, which would particularly impact crops with shallow root systems. Subsequent field experiments will be conducted to further investigate the efficacy of these strategies in enhancing crop yield.

The segmentation of fundus tumors is critical for ophthalmic diagnosis and treatment, yet it presents unique challenges due to the variability in lesion size and shape. Our study introduces Fundus Tumor Segmentation Network (FTSNet), a novel segmentation network designed to address these challenges by leveraging classification results and prompt learning. Our key innovation is the multiscale feature extractor and the dynamic prompt head. Multiscale feature extractors are proficient in eliciting a spectrum of feature information from the original image across disparate scales. This proficiency is fundamental for deciphering the subtle details and patterns embedded in the image at multiple levels of granularity. Meanwhile, a dynamic prompt head is engineered to engender bespoke segmentation heads for each image, customizing the segmentation process to align with the distinctive attributes of the image under consideration. We also present the Fundus Tumor Segmentation (FTS) dataset, comprising 254 pairs of fundus images with tumor lesions and reference segmentations. Experiments demonstrate FTSNet’s superior performance over existing methods, achieving a mean Intersection over Union (mIoU) of 0.8254 and mean Dice (mDice) of 0.9042. The results highlight the potential of our approach in advancing the accuracy and efficiency of fundus tumor segmentation.

Daytime dysfunction, including symptoms like sleepiness, poor memory, and reduced responsiveness, is not well researched. It is crucial to develop animal models and study the biological mechanisms involved. We simulated sleep disorders through sleep deprivation, and stressful stimuli were used to establish daytime functional animal models. We used tests like the sodium pentobarbital sleep synergy test and the DSI telemetry system to measure sleep duration and structure. We also used tests like the Morris water maze, open field test, grip test, and baton twirling test to assess mental and physical fatigue. To assess the intrinsic biological mechanisms, we measured sleep–wake-related neurotransmitters and related receptor proteins, circadian rhythm-related proteins and cognition-related proteins in hypothalamus tissue, and oxidative stress, inflammatory factors, S100β, and HPA axis-related indexes in serum. Multi-factor sleep deprivation resulted in the disruption of sleep–wakefulness structure, memory–cognitive function degradation, decreased grip coordination, and other manifestations of decreased energetic and physical strength. The intrinsic biological mechanisms were related to the disturbed expression of sleep–wake, circadian rhythm, memory–cognition-related proteins, as well as the significant elevation of inflammatory factors, oxidative stress, the HPA axis, and other related indicators. Intrinsically related biological mechanisms and reduced sirt1 expression can lead to disruption of circadian rhythms; resulting in disruption of their sleep–wake-related neurotransmitter content and receptor expression. Meanwhile, the reduced expression of sirt1 also resulted in reduced expression of synapse-associated proteins. This study prepared an animal model of daytime dysfunction by means of multi-factor sleep deprivation. With sirt1 as a core target, the relevant biological mechanisms of neurological disorders were modulated.

Airborne aircrafts are dependent on the Global Navigation Satellite System (GNSS), which is susceptible to interference due to the satellite base-station and cooperative communication. Synthetic aperture radar altimeter (SARAL) provides the ability to measure the topographic terrain for matching with Digital Elevation Model (DEM) to achieve positioning without relying on GNSS. However, due to the near-vertical coupling in the delay-Doppler map (DDM), the similarity of DDMs of adjacent apertures is high, and the probability of successful matching is low. To this end, a novel neural network of terrain matching and aircraft positioning is proposed based on the airborne SARAL imagery. The model-driven terrain matching and aircraft positioning network (TMP-Net) is capable of realizing aircraft positioning by utilizing the real-time DDMs to match with the DEM-based DDM references, which are generated by a point-by-point coupling mechanism between the airborne routine and ground terrain DEM. Specifically, the training dataset is established by a numerical simulation method based on a semi-analytical model. Therefore, DEM-based DDM references can be generated by forward deduction when only regional DEM can be obtained. In addition to the model-based DDM generation, feature extraction, and similarity measurement, an aircraft positioning module is added. Three different positioning methods are designed to achieve the aircraft positioning, where three-point weighting exhibits the best performance in terms of positioning accuracy. Due to the fact that both the weighted triplet loss and softmax loss are employed in a cooperative manner, the matching accuracy can be improved and the positioning error can be reduced. Finally, both simulated and measured airborne datasets are used to validate the effectiveness of the proposed algorithm. Quantitative and qualitative evaluations show the superiority.

Metal material processing using femtosecond lasers is a useful technique, and it has been widely employed in many applications including laser microfabrication, laser surgery, and micromachining. The basic mechanisms of metal processing using femtosecond lasers are reviewed in this paper and the characteristics and theory of laser processing are considered. In addition to well-known processes, the recent progress relating to metals processing with femtosecond lasers, including metal material drilling, metal ablation thresholds, micro/nano-surface modification, printed circuit board (PCB) micromachining, and liquid metal (LM) processing using femtosecond lasers, is described in detail. Meanwhile, the application of femtosecond laser technology in different fields is also briefly discussed. This review concludes by highlighting the current challenges and presenting a forward-looking perspective on the future of the metal laser processing field.

(1) Background: Various factors, such as oxidative stress, mitochondrial dysfunction, tumors, inflammation, trauma, immune disorders, and neuronal toxicity, can cause nerve damage. Chemical nerve injury, which results from exposure to toxic chemicals, has garnered increasing research attention. The thioredoxin (Trx) system, comprising Trx, Trx reductase, nicotinamide adenine dinucleotide phosphate, and Trx-interacting protein (TXNIP; endogenous Trx inhibitor), helps maintain redox homeostasis in the central nervous system. The dysregulation of this system can cause dementia, cognitive impairment, nerve conduction disorders, movement disorders, and other neurological disorders. Thus, maintaining Trx system homeostasis is crucial for preventing or treating nerve damage. (2) Objective: In this review study, we explored factors influencing the homeostasis of the Trx system and the involvement of its homeostatic imbalance in chemical nerve injury. In addition, we investigated the therapeutic potential of the Trx system-targeting active substances against chemical nerve injury. (3) Conclusions: Chemicals such as morphine, metals, and methylglyoxal interfere with the activity of TXNIP, Trx, and Trx reductase, disrupting Trx system homeostasis by affecting the phosphatidylinositol-3-kinase/protein kinase B, extracellular signal-regulated kinase, and apoptotic signaling-regulated kinase 1/p38 mitogen-activated protein kinase pathways, thereby leading to neurological disorders. Active substances such as resveratrol and lysergic acid sulfide mitigate the symptoms of chemical nerve injury by regulating the Ras/Raf1/extracellular signal-regulated kinase pathway and the miR-146a-5p/TXNIP axis. This study may guide the development of Trx-targeting modulators for treating neurological disorders and chemical nerve injuries.

The contamination risks of plant-derived foods due to the co-existence of pesticides and veterinary drugs (P&VDs) have not been fully understood. With an increasing number of unexpected P&VDs illegally added to foods, it is essential to develop a non-targeted screening method for P&VDs for their comprehensive risk assessment. In this study, a modified support vector machine (SVM)-assisted metabolomics approach by screening eligible variables to represent marker compounds of 124 multi-class P&VDs in maize was developed based on the results of high-performance liquid chromatography–tandem mass spectrometry. Principal component analysis and orthogonal partial least squares discriminant analysis indicate the existence of variables with obvious inter-group differences, which were further investigated by S-plot plots, permutation tests, and variable importance in projection to obtain eligible variables. Meanwhile, SVM recursive feature elimination under the radial basis function was employed to obtain the weight-squared values of all the variables ranging from large to small for the screening of eligible variables as well. Pairwise t-tests and fold changes of concentration were further employed to confirm these eligible variables to represent marker compounds. The results indicate that 120 out of 124 P&VDs can be identified by the SVM-assisted metabolomics method, while only 109 P&VDs can be found by the metabolomics method alone, implying that SVM can promote the screening accuracy of the metabolomics method. In addition, the method’s practicability was validated by the real contaminated maize samples, which provide a bright application prospect in non-targeted screening of contaminants. The limits of detection for 120 P&VDs in maize samples were calculated to be 0.3~1.5 µg/kg.

Using peanut shells, a sustainable agricultural waste product, as its raw material, the acid group-modified biochar (AMBC) was prepared through phosphoric acid activation, partial carbonization, and concentrated sulfuric acid sulfonation for efficient removal of lead ion from aqueous solutions. Characterization techniques such as N2 isothermal adsorption–desorption, SEM, XRD, FT-IR, TG-DTA, and acid–base titration were utilized to fully understand the properties of the AMBC. It was found that there were high densities of acidic oxygen-containing functional groups (-SO3H, -COOH, Ph-OH) on the surface of the AMBC. The optimal adsorption performance of the AMBC for Pb(II) in water occurred when the initial concentration of Pb(II) was 100 mg/L, the pH was 5, the dosage of the adsorbent was 0.5 g/L, and the contact time was 120 min. Under the optimal conditions, the removal ratio of Pb(II) was 76.0%, with an adsorption capacity of 148.6 mg/g. This performance far surpassed that of its activated carbon precursor, which achieved a removal ratio of 39.7% and an adsorption capacity of 83.1 mg/g. The superior adsorption performance of AMBC can be caused by the high content of acidic oxygen-containing functional groups on its surface. These functional groups facilitate the strong binding between AMBC and Pb(II), enabling effective removal from water solutions.

The application of potassium fertilizer application and straw return are effective agronomic measures for increasing crop productivity; however, information on how straw return—when substituting potassium fertilizer—affects crop yield, efficiency, and quality in dryland remains limited. In this study, an experiment on a dryland summer maize and winter wheat rotation system was initiated in 2007. This study included four treatments: CK (no fertilizer and no straw return), NP (nitrogen and phosphorus fertilizer application without straw return), NPK (nitrogen, phosphorus, and potassium fertilizer application without straw return), and NPS (NP treatment with straw return, substituting potassium fertilizer as used in the NPK treatment). These treatments were employed to assess grain yield and fertilizer agronomic efficiency in 2015–2020. Additionally, we evaluated the content of nitrogen (N), phosphorus (P), and potassium (K), as well as the protein content and protein yield in maize and wheat grains and the protein components in wheat grains in 2019–2020. The results showed that compared to the CK treatment, NP, NPK, and NPS treatments not only significantly increased the yield, protein yield, and fertilizer agronomic efficiency in both maize and wheat but also increased the content of protein and protein components in wheat grains. Compared to the NP treatment, the NPK treatment significantly increased the contents of N, K, globulin, and gluten in wheat grains by 5.11%, 21.59%, 10.06%, and 15.14%. Compared to NPK treatment, NPS treatment significantly increased the average yield of summer maize by 21.33% and 20.91%, respectively, as well as the annual yield by 9.99% and 13.59%, the N fertilizer agronomic efficiency of summer maize by 132.47%, and the annual N and P fertilizer agronomic efficiency by 42.83% and 64.36%, over the five-year period. The NPS treatment also significantly increased the summer maize protein yield and annual protein yield by 10.43% and 23.08%, as well as the content of protein components, the protein content, and P content in wheat grains by 4.93–13.58%, 7.81%, and 28.89%, respectively. In conclusion, NPS treatment can not only enhance crop yield, protein yield, and fertilizer agronomic efficiency in summer maize annually but also has the advantage of promoting wheat quality. NPS is an efficient strategy to improve crop yield, efficiency, and quality in a dryland maize–wheat rotation system.

Due to the low impedance matching caused by the high dielectric permittivity of graphene, the strong absorption of electromagnetic waves by graphene/polymer nanocomposites is challenging. In this paper, an analytical model for microwave absorption based on Maxwell’s equation and the effective medium theory, considering the interface effect, was constructed to explore the effect of the gradient distribution of graphene in the polymer matrix on its microwave absorption performance. The outcome indicated that the impedance of the composites matched well with the air, and its attenuation ability for electromagnetic waves was obviously improved as the graphene concentration was distributed in a gradient form. For instance, when the thickness of the material is 10 mm, based on the optimal concentration of the homogeneous composites being 0.7 wt%, the graphene concentration range of the gradient composites is set to 0.7–0.9 wt% and distributed in three gradient forms of linear, parabolic, and 0.5 power. The results show that the microwave absorption performance is significantly improved compared with the homogeneous composites. Among them, the effective bandwidth on the 0.5 power distribution is 5.2 GHz, 0.5 GHz higher than that of the homogeneous composites. The minimum reflection loss (RL) is as low as −54.7 dB, which is 26.26 dB lower than that of the homogeneous composites. This paper contributes to the design and application of gradient absorbing structures.

Soluble N-ethylmaleimide-sensitive factor attachment protein receptors (SNAREs) are central components of the machinery mediating cell membrane fusion and intracellular vesicular trafficking in eukaryotic cells, and have been well-documented to play critical roles in growth, development, and pathogenesis in the filamentous fungal plant pathogens. However, little is known about the contributions of SNAREs to the physiology and biocontrol potential in entomopathogenic filamentous fungi. Here, a genome-wide analysis of SNARE genes was performed taking advantage of the available whole genome sequence of Beauveria bassiana, a classical entomopathogenic fungus. Based on the compared genomic method, 22 genes encoding putative SNAREs were identified from the whole genome of B. bassiana, and were classified into four groups (7 Qa-, 4 Qb-, 6 Qc-, and 5 R-SNAREs) according to the conserved structural features of their encoding proteins. An R-SNARE encoding gene BbSEC22 was further functionally characterized by gene disruption and complementation. The BbSEC22 null mutant showed a fluffy appearance in mycelial growth and an obvious lag in conidial germination. The null mutant also exhibited significantly increased sensitivity to oxidative stress and cell wall perturbing agents and reduced the yield of conidia production by 43.1% compared with the wild-type strain. Moreover, disruption of BbSEC22 caused a significant decrease in conidial virulence to Spodoptera litura larvae. Overall, our results provide an overview of vesicle trafficking in B. bassiana and revealed that BbSec22 was a multifunctional protein associated with mycelial growth, sporulation, conidial germination, stress tolerance, and insecticidal virulence.

Silicone-modified polyurethane (PUSX) refers to the introduction of a silicone short chain into the polyurethane chain to make it have the dual properties of silicone and polyurethane (PU). It can be used in many fields, such as coatings, films, molding products, adhesives, and so on. The use of organic solvents to achieve the fiberization of silicone-modified polyurethane has been reported. However, it is challenging to achieve the fiberization of silicone-modified polyurethane based on an environmentally friendly water solvent. Herein, we report a simple and powerful strategy to fabricate environmentally friendly waterborne silicone-modified polyurethane nanofiber membranes through the addition of polyethylene glycol (PEG) with different molecular weights using electrospinning technology and in situ doping with three crosslinking agents with different functional groups (a polyoxazoline crosslinking agent, a polycarbodiimide crosslinking agent, and a polyisocyanate crosslinking agent) combined with various heating treatment conditions. The influence of PEG molecular weight on fiber formation was explored. The morphology, structure, water resistance, and mechanical properties were analyzed regarding the effect of the introduction of silicone into PU. The effects of the type and content of crosslinking agent on the morphology and physical properties of PUSX nanofiber membranes are discussed. These results show that the introduction of silicone can improve the water resistance and high temperature resistance of waterborne PU, and the addition of a crosslinking agent can further improve the water resistance of the sample, so that the sample can maintain good morphology after immersion. Crosslinking agents with different functional groups had different effects on the mechanical properties of PUSX nanofiber membranes due to different reactions. Among them, the oxazoline crosslinking agent had a significant effect on improving tensile strength, while the isocyanate crosslinking agent had a significant effect on improving the elongation at break. The PUSX nanofiber membrane prepared in this work did not use organic solvents that were harmful to humans and the environment, and it can be used in outdoor textiles, oil–water separation, medical health, and other fields.

Waterproof and breathable membranes have a huge market demand in areas, such as textiles and medical protection. However, existing fluorinated nanofibrous membranes, while possessing good waterproof and breathable properties, pose health and environmental hazards. Consequently, fabricating fluorine-free, eco-friendly waterborne membranes by integrating outstanding waterproofing, breathability, and robust mechanical performance remains a significant challenge. Herein, we successfully prepared waterborne silicone-modified polyurethane nanofibrous membranes with excellent elasticity, waterproofing, and breathability properties through waterborne electrospinning, using a small quantity of poly(ethylene oxide) as a template polymer and in situ doping of the poly(carbodiimide) crosslinking agent, followed by a simple hot-pressing treatment. The silicone imparted the nanofibrous membrane with high hydrophobicity, and the crosslinking agent enabled its stable porous structure. The hot-pressing treatment (120 °C) further reduced the pore size and improved the water resistance. This environmentally friendly nanofibrous membrane showed a high elongation at break of 428%, an ultra-high elasticity of 67.5% (160 cycles under 400% tensile strain), an air transmission of 13.2 mm s−1, a water vapor transmission rate of 5476 g m−2 d−1, a hydrostatic pressure of 51.5 kPa, and a static water contact angle of 137.9°. The successful fabrication of these environmentally friendly, highly elastic membranes provides an important reference for applications in healthcare, protective textiles, and water purification.

The thickness of the Antarctic ice sheet is a crucial parameter for inferring glacier mass and its evolution process. In the literature, the gravity method has been proven to be one of the effective means for estimating ice sheet thickness. And it is a preferred approach when direct measurements are not available. However, few gravity inversion methods are valid in rugged terrain areas with undulating observation surfaces (UOSs). To solve this problem, this paper proposes an improved high-precision 3D density interface inversion method considering terrain and UOSs simultaneously. The proposed method utilizes airborne gravity data at their flight altitudes, instead of the continued data yield from the unstable downward continuation procedure. In addition, based on the undulating right rectangular prism model, the large reliefs of the terrain are included in the iterative inversion. The proposed method is verified on two synthetic examples and is successfully applied to real data in East Antarctica.

Epilepsy is a common neurological disorder, and its diagnosis mainly relies on the analysis of electroencephalogram (EEG) signals. However, the raw EEG signals contain limited recognizable features, and in order to increase the recognizable features in the input of the network, the differential features of the signals, the amplitude spectrum and the phase spectrum in the frequency domain are extracted to form a two-dimensional feature vector. In order to solve the problem of recognizing multimodal features, a neural network model based on a multimodal dual-stream network is proposed, which uses a mixture of one-dimensional convolution, two-dimensional convolution and LSTM neural networks to extract the spatial features of the EEG two-dimensional vectors and the temporal features of the signals, respectively, and combines the advantages of the two networks, using the hybrid neural network to extract both the temporal and spatial features of the signals at the same time. In addition, a channel attention module was used to focus the model on features related to seizures. Finally, multiple sets of experiments were conducted on the Bonn and New Delhi data sets, and the highest accuracy rates of 99.69% and 97.5% were obtained on the test set, respectively, verifying the superiority of the proposed model in the task of epileptic seizure detection.

In this paper, a new axial-type magnetic gear with an auxiliary flux-enhancing structure (AFS-AMG) is proposed. Compared to conventional AMGs, it has a higher torque density and higher permanent magnet (PM) utilization factor. Firstly, the design rules and operating principles of the proposed AFS-AMG are elaborated. Then, the mapping relation between the radial-type magnetic gears (RMGs) and AMGs are elucidated. Compared to its counterparts in RMGs, the AFS-AMG achieves a small size. Then, the geometrical parameters of the AFS-AMG are optimized to obtain better electromagnetic performance, where the torque density per volume and per PM volume is adopted as the evaluation standard. Finally, three different AMG topologies are constructed in finite element analysis (FEA) software for comparison. It is proven that the AFS-AMG has the largest torque density per volume and per PM volume.

In this work, analytic solutions of initial value problems for fractional Langevin equations involving Hilfer fractional derivatives and variable coefficients are studied. Firstly, the equivalence of an initial value problem to an integral equation is proved. Secondly, the existence and uniqueness of solutions for the above initial value problem are obtained without a contractive assumption. Finally, a formula of explicit solutions for the proposed problem is derived. By using similar arguments, corresponding conclusions for the case involving Riemann–Liouville fractional derivatives and variable coefficients are obtained. Moreover, the nonlinear case is discussed. Two examples are provided to illustrate theoretical results.

The accurate segmentation and quantification of retinal fluid in Optical Coherence Tomography (OCT) images are crucial for the diagnosis and treatment of ophthalmic diseases such as age-related macular degeneration. However, the accurate segmentation of retinal fluid is challenging due to significant variations in the size, position, and shape of fluid, as well as their complex, curved boundaries. To address these challenges, we propose a novel multi-scale feature fusion attention network (FNeXter), based on ConvNeXt and Transformer, for OCT fluid segmentation. In FNeXter, we introduce a novel global multi-scale hybrid encoder module that integrates ConvNeXt, Transformer, and region-aware spatial attention. This module can capture long-range dependencies and non-local similarities while also focusing on local features. Moreover, this module possesses the spatial region-aware capabilities, enabling it to adaptively focus on the lesions regions. Additionally, we propose a novel self-adaptive multi-scale feature fusion attention module to enhance the skip connections between the encoder and the decoder. The inclusion of this module elevates the model’s capacity to learn global features and multi-scale contextual information effectively. Finally, we conduct comprehensive experiments to evaluate the performance of the proposed FNeXter. Experimental results demonstrate that our proposed approach outperforms other state-of-the-art methods in the task of fluid segmentation.

Fusarium sacchari is a causal agent of sugarcane Pokkah boeng, an important fungal disease that causes a considerable reduction in yield and sugar content in susceptible varieties of sugarcane worldwide. Despite its importance, the fungal factors that regulate the virulence of this pathogen remain largely unknown. In our previous study, mapping of an insertional mutant defect in virulence resulted in the identification of a cutinase G-box binding protein gene, designated FsCGBP, that encodes a C2H2-type transcription factor (TF). FsCGBP was shown to localize in the nuclei, and the transcript level of FsCGBP was significantly upregulated during the infection process or in response to abiotic stresses. Deletion or silencing of FsCGBP resulted in a reduction in mycelial growth, conidial production, and virulence and a delay in conidial germination in the F. sacchari. Cutinase genes FsCUT2, FsCUT3, and FsCUT4 and the mitogen-activated protein kinase (MAPK) genes FsHOG1, FsMGV1, and FsGPMK1, which were significantly downregulated in ΔFsCGBP. Except for FsHOG1, all of these genes were found to be transcriptionally activated by FsCGBP using the yeast one-hybrid system in vitro. The deletion of individual cutinase genes did not result in any of the phenotypes exhibited in the ΔFsCGBP mutant, except for cutinase activity. However, disruption of the MAPK pathway upon deletion of FsMGV1 or FsGPMK1 resulted in phenotypes similar to those of the ΔFsCGBP mutant. The above results suggest that FsCGBP functions by regulating the MAPK pathway and cutinase genes, providing new insights into the mechanism of virulence regulation in F. sacchari.

The normalized difference vegetation index (NDVI) can depict the status of vegetation growth and coverage in grasslands, whereas coarse spatial resolution, cloud cover, and vegetation phenology limit its applicability in fine-scale research, especially in areas covering various vegetation or in fragmented landscapes. In this study, a methodology was developed for obtaining the 30 m annual maximum NDVI to overcome these shortcomings. First, the Landsat NDVI was simulated by fusing Landsat and MODIS NDVI by using the enhanced spatial and temporal adaptive reflectance fusion model (ESTARFM), and then a single-peaked symmetric logistic model was employed to fit the Landsat NDVI data and derive the maximum NDVI in a year. The annual maximum NDVI was then used as a season-independent substitute to monitor grassland variation from 2001 to 2022 in a typical area covering the major vegetation types in the Qinghai Lake Basin. The major conclusions are as follows: (1) Our method for reconstructing the NDVI time series yielded higher accuracy than the existing dataset. The root mean square error (RMSE) for 91.8% of the pixels was less than 0.1. (2) The annual maximum NDVI from 2001 to 2022 exhibited spatial distribution characteristics, with higher values in the northern and southern regions and lower values in the central area. In addition, the earlier vegetation growth maximum dates were related to the vegetation type and accompanied by higher NDVI maxima in the study area. (3) The overall interannual variation showed a slight increasing trend from 2001 to 2022, and the degraded area was characterized as patches and was dominated by Alpine kobresia spp., Forb Meadow, whose change resulted from a combination of permafrost degradation, overgrazing, and rodent infestation and should be given more attention in the Qinghai Lake Basin.

The power capacity of reflectarray antennas (RAs) is investigated through full-wave simulations and high-power microwave (HPM) experiments in this paper. In order to illustrate the results in detail, two RA elements are designed. The simulated power handling capacity of two RA elements are 7.17 MW/m2 and 2.3 GW/m2, respectively. To further study the HPM RA, two RA prototypes operating at 2.8 GHz are constructed with the aperture size of 1 m × 1 m. Simulations and experimental measurements are conducted for the two prototypes. The experimental results demonstrate that, even when subjected to 1 GW of power, the radiation beam of the RA with the second elements can still propagate in the intended direction. This research will establish a basis for advancing the practicality of RAs in HPM applications.

In the Earth’s hydrosphere, 96 [...]

H5N1 highly pathogenic avian influenza virus (HPAIV) infections pose a significant threat to human health, with a mortality rate of around 50%. Limited global approval of H5N1 HPAIV vaccines, excluding China, prompted the need to address safety concerns related to MDCK cell tumorigenicity. Our objective was to improve vaccine safety by minimizing residual DNA and host cell protein (HCP). We developed a downstream processing method for the cell-based H5N1 HPAIV vaccine, employing CaptoTM Core 700, a multimodal resin, for polishing. Hydrophobic-interaction chromatography (HIC) with polypropylene glycol as a functional group facilitated the reversible binding of virus particles for capture. Following the two-step chromatographic process, virus recovery reached 68.16%. Additionally, HCP and DNA levels were reduced to 2112.60 ng/mL and 6.4 ng/mL, respectively. Western blot, high–performance liquid chromatography (HPLC), and transmission electron microscopy (TEM) confirmed the presence of the required antigen with a spherical shape and appropriate particle size. Overall, our presented two-step downstream process demonstrates potential as an efficient and cost-effective platform technology for cell-based influenza (H5N1 HPAIV) vaccines.

In this paper, we derive an explicit formula of solutions to Hilfer linear fractional integro-differential equations with a variable coefficient in a weighted space, and obtain the existence and uniqueness of solutions for fractional kinetic equations and fractional integro-differential equations with a generalized Mittag–Leffler function. An example is given to illustrate the result obtained.

This paper introduces a novel single-layer microstrip patch element designed to achieve a wide beamwidth, in order to address the growing demand for wide-angle scanning capabilities in modern phased array systems. The proposed element, comprising a slot-etched circular patch and an array of metallized holes arranged in square rings, offers a unique approach to beam shaping. By carefully adjusting parameters such as the slot structure and feeding position, our element is engineered to simultaneously excite both the TM01 and TM21 modes, a key feature that contributes to its wide beamwidth characteristics. Through the constructive interference of these modes, our element demonstrates a remarkable 3 dB beamwidth of approximately 150° in both principal planes, showcasing its potential for wide-angle scanning applications. To validate the practical performance of this proposed element, two linear phased arrays are manufactured and experimentally evaluated. The simulation results confirm the wide-angle scanning capability of the antennas in both the E-plane and H-plane. Furthermore, the experimental assessment demonstrates that these linear phased arrays can effectively generate scanning beams within a frequency range of 25 GHz to 28 GHz, covering a wide angular range from −60° to 60°, while maintaining a gain loss within 3 dB. This innovative design approach not only offers a promising solution for achieving a wide beamwidth in microstrip patch elements, but also holds significant potential for the development of cost-effective phased arrays with wide-angle scanning capabilities, making it a valuable contribution to the advancement of phased array technology.

We propose a seawater salinity sensor array based on a micro/nanofiber Bragg grating structures, which allows for the simultaneous measurement of temperature and salinity. The proposed sensing structure is fabricated through a process involving optical fiber tapering, femtosecond laser inscription, and chemical etching. The equivalent refractive index (RI) of this sensor structure is influenced by the surrounding RI, resulting in a Bragg characteristic wavelength shift that can be used for salinity sensing. The experimental results show that the salinity sensitivity for two cascaded sensor arrays is 8.39 pm/‰ and 7.71 pm/‰, while the temperature sensitivity is 8.28 pm/°C and 8.03 pm/°C, respectively. This sensor structure is compact, exhibits excellent linearity, and offers good repeatability. It holds great potential for applications in seawater environmental monitoring and quantitative studies of seawater dispersion characteristics.

Due to the lack of accurate labels for the airborne synthetic aperture radar altimeter (SARAL), the use of deep learning methods is limited for estimating the above ground level (AGL) of complicated landforms. In addition, the inherent additive and speckle noise definitely influences the intended delay/Doppler map (DDM); accurate AGL estimation becomes more challenging when using the feature extraction approach. In this paper, a generalized AGL estimation algorithm is proposed, based on a fully supervised altimetry enhancement network (FuSAE-net), where accurate labels are generated by a novel semi-analytical model. In such a case, there is no need to have a fully analytical DDM model, and accurate labels are achieved without additive noises and speckles. Therefore, deep learning supervision is easy and accurate. Next, to further decrease the computational complexity for various landforms on the airborne platform, the network architecture is designed in a lightweight manner. Knowledge distillation has proven to be an effective and intuitive lightweight paradigm. To significantly improve the performance of the compact student network, both the encoder and decoder of the teacher network are utilized during knowledge distillation under the supervision of labels. In the experiments, airborne raw radar altimeter data were applied to examine the performance of the proposed algorithm. Comparisons with conventional methods in terms of both qualitative and quantitative aspects demonstrate the superiority of the proposed algorithm.

Litchi (Litchi chinensis) is an evergreen fruit tree grown in subtropical and tropical countries. China accounts for 71.5% of the total litchi cultivated area in the world. Anthracnose disease caused by Colletotrichum species is one of the most important diseases of litchi in China. In this study, the causal pathogens of litchi anthracnose in Hainan, China, were determined using phylogenetic and morphological analyses. The results identified eight Colletotrichum species from four species complexes, including a proposed new species. These were C. karsti from the C. boninense species complex; C. gigasporum and the proposed new species C. danzhouense from the C. gigasporum species complex; C. arecicola, C. fructicola species complex; C. arecicola, C. fructicola and C. siamense from the C. gloeosporioides species complex; and C. musicola and C. plurivorum from the C. orchidearum species complex. Pathogenicity tests showed that all eight species could infect litchi leaves using a wound inoculation method, although the pathogenicity was different in different species. To the best of our knowledge, the present study is the first report that identifies C. arecicola, C. danzhouense, C. gigasporum and C. musicola as etiological agents of litchi anthracnose.

When ships navigate in polar regions, they may collide with ice masses, which may cause structural damage and endanger the safety of their occupants. Therefore, it is essential to promptly detect sea ice, icebergs, and passing ships. However, individual data sources have limits and should be combined and integrated to obtain more thorough information. A polar multi-target local-scale dataset with five categories was constructed. Sea ice, icebergs, ice melt ponds, icebreakers, and inter-ice channels were identified by a single-shot detector (SSD), with a final mAP value of 70.19%. A remote sensing sea ice dataset with 15,948 labels was constructed. The You Only Look Once (YOLOv5) model was improved with Squeeze-and-Excitation Networks (SE), Funnel Activation (FReLU), Fast Spatial Pyramid Pooling, and Cross Stage Partial Network (SPPCSPC-F). In the detection stage, a slicing operation was performed on remote sensing images to detect small targets. Simulated sea ice data were included to verify the model’s generalization ability. Then, the improved model was trained and evaluated in an ablation experiment. The mAP, recall (R), and precision (P) values of the improved YOLOv5 were 75.3%, 70.3, and 75.4%, with value increases of 3.5%, 3.4%, and 1.9%, respectively, compared to the original model. The improved YOLOv5 was also compared with other models such as YOLOv3, Faster-RCNN, and YOLOv4-tiny. The results indicated that the performance of the proposed model surpassed those of the other conventional models. This study achieved the detection of multiple targets on different scales in a polar region and realized data fusion, avoiding the limitations of using a single data source, and provides a method to support polar ship path planning.

Alzheimer’s disease (AD) is a leading cause of dementia, impacting millions worldwide. However, its complex neuropathologic features and heterogeneous pathophysiology present significant challenges for diagnosis and treatment. To address the urgent need for early AD diagnosis, this review focuses on surface-enhanced Raman scattering (SERS)-based biosensors, leveraging the excellent optical properties of nanomaterials to enhance detection performance. These highly sensitive and noninvasive biosensors offer opportunities for biomarker-driven clinical diagnostics and precision medicine. The review highlights various types of SERS-based biosensors targeting AD biomarkers, discussing their potential applications and contributions to AD diagnosis. Specific details about nanomaterials and targeted AD biomarkers are provided. Furthermore, the future research directions and challenges for improving AD marker detection using SERS sensors are outlined.

Nitrate (NO3) pollution in groundwater, caused by various factors both natural and synthetic, contributes to the decline of human health and well-being. Current techniques used for nitrate detection include spectroscopic, electrochemical, chromatography, and capillary electrophoresis. It is highly desired to develop a simple cost-effective alternative to these complex methods for nitrate detection. Therefore, a real-time poly (3,4-ethylenedioxythiophene) (PEDOT)-based sensor for nitrate ion detection via electrical property change is introduced in this study. Vapor phase polymerization (VPP) is used to create a polymer thin film. Variations in specific parameters during the process are tested and compared to develop new insights into PEDOT sensitivity towards nitrate ions. Through this study, the optimal fabrication parameters that produce a sensor with the highest sensitivity toward nitrate ions are determined. With the optimized parameters, the electrical resistance response of the sensor to 1000 ppm nitrate solution is 41.79%. Furthermore, the sensors can detect nitrate ranging from 1 ppm to 1000 ppm. The proposed sensor demonstrates excellent potential to detect the overabundance of nitrate ions in aqueous solutions in real time.

During the operation of boom sprayers in the field, it is crucial to ensure that the entire boom is maintained at an optimal height relative to the ground or crop canopy. Active suspension is usually used to adjust the height. A control system for double-pendulum active suspension was developed in this paper. The control system consisted of a main control node, two distance measurement nodes, a vehicle inclination detection node, and an execution node. Communication between nodes was carried out using a CAN bus. The hardware was selected, and the interface circuits of the sensors and the actuator were designed. The transfer functions of the active suspension and electric linear actuator were established. In order to enhance the efficiency of the control system, the particle swarm optimization (PSO) algorithm was employed to optimize the initial parameters of the fuzzy PID controller. The simulation results demonstrated that the PSO-based fuzzy PID controller exhibited improvements in terms of reduced overshoot and decreased settling time when compared to conventional PID and fuzzy PID controllers. The experimental results showed that the active suspension system equipped with the control system could effectively isolate high-frequency disturbances and follow low-frequency ground undulations, meeting the operational requirements.

Because the demand for pork is increasing, it is crucial to devise efficient and green methods to improve the quality and quantity of meat. This study investigated the improvement in pork quality after the inclusion of alfalfa meal or alfalfa silage in pig diet. Our results indicated that alfalfa silage improved meat quality more effectively in terms of water-holding capacity, drip loss, and marbling score. Besides, an alfalfa silage diet can affect the level of fatty acids and amino acids in pork. Further, alfalfa silage was found to improve meat quality by remodeling intestinal microbiota and altering the level of SCFAs, providing a viable option for improving meat quality through forage.

Quantitative detection of veterinary drug residues in animal-derived food is of great significance. In this work, a simple and label-free electrochemical aptasensor for the highly sensitive detection of chloramphenicol (CAP) in milk was successfully developed based on a new biosensing method, where the single- or few-layer Ti3C2 MXene nanosheets functionalized via the specific aptamer by self-assembly were used as electrode modifiers for a glassy carbon electrode (aptamer/Ti3C2 MXene/GCE). Differential pulse voltammetry (DPV), electrochemical impedance spectroscopy (EIS), cyclic voltammetry (CV), scanning electron microscopy (SEM), atomic force microscope (AFM), and so on were utilized for electrochemical and morphological characterization. Under the optimized conditions, the constructed aptasensor exhibited excellent performance with a wider linearity to CAP in the range from 10 fM to 1 μM and a low detection limit of 1 fM. Aptamer/Ti3C2 MXene/GCE demonstrated remarkable selectivity over other potentially interfering antibiotics, as well as exceptional reproducibility and stability. In addition, the aptasensor was successfully applied to determine CAP in milk with acceptable recovery values of 96.13% to 108.15% and relative standard deviations below 9%. Therefore, the proposed electrochemical aptasensor is an excellent alternative for determining CAP in food samples.

The ecological compensation standard in transboundary river basins should be determined by the basin countries through negotiation on the basis of the base value of the ecological compensation standard. This paper calculated the base value range of the ecological compensation standard, determining the upper limit based on the spillover value of ecosystem services for the ecosystem-service-consuming country and the lower limit according to the cost of ecological protection for the ecosystem-service-supplying country. The final range was determined by integrating this with the willingness to pay and the actual effort in each basin country. Taking, for example, the Lancang–Mekong River basin, the results indicate that the spillover value of ecosystem services in Laos, China and Myanmar was positive and these three countries were ecosystem-service-supplying countries, while in Cambodia, Vietnam and Thailand it was negative and these three countries were ecosystem-service-consuming countries. Among the ecosystem-service-supplying countries, the cost of ecological protection of them was in descending order of Laos, China and Myanmar, which was related to their own level of economic development. Considering the adjustment coefficient for the payment of ecosystem service value and the cost-sharing coefficient of each basin country, the feasible range for the base value of the ecological compensation standard was determined to be [2.47, 229.67] × 108 $, which provided the basis for the negotiation on the determination of the ECS. In addition, implementation suggestions were proposed from three aspects: establishing a basin-information-sharing mechanism and platform, establishing an integrated management organization for transboundary river basins, and strengthening and improving the coordination and supervision model of ecological compensation.

This paper introduces a scenario evolution model for maritime accidents, wherein Bayesian networks (BNs) were employed to predict the most probable causes of distinct types of maritime incidents. The BN nodes encompass factors such as accident type, life loss contingency, accident severity, quarter and time period of the accident, and type and gross tonnage of the involved ships. An analysis of 5660 global maritime accidents spanning the years 2005 to 2020 was conducted. Using Netica software, a tree augmented network (TAN) model was constructed, thus accounting for interdependencies among risk-influencing factors. To confirm these results, a validation process involving sensitivity analysis and historical accident records was performed. Following this, both forward causal inference and reverse diagnostic inference were carried out on each node variable to scrutinize the accident development trend and evolution process under preset conditions. The findings suggest that the model was competent in effectively predicting the likelihood of various accident scenarios under specific conditions, as well as extrapolating accident consequences. Forward causal reasoning unveiled that general cargo ships with a gross tonnage of 1–18,500 t were most prone to experiencing collision and stranding/grounding accidents in the first quarter. Reverse diagnostic reasoning indicated that, in the early morning hours, container ships, general cargo ships, and chemical ships with a tonnage of 1–18,500 t were less likely to involve life loss in the event of collision accidents.

Bilayer graphene is a contender of interest for functional electronic applications because of its variable band gap due to interlayer interactions. Graphene growth on Cu is self-limiting, thus despite the fact that chemical vapor deposition (CVD) has made substantial strides in the production of monolayer and single-crystal graphene on Cu substrates, the direct synthesizing of high-quality, large-area bilayer graphene remains an enormous challenge. In order to tackle this issue, we present a simple technique using typical CVD graphene growth followed by a repetitive wrinkling-etching-regrowth procedure. The key element of our approach is the rapid cooling process that causes high-density wrinkles to form in the monolayer area rather than the bilayer area. Next, wrinkled sites are selectively etched with hydrogen, exposing a significant portion of the active Cu surface, and leaving the remaining bilayer areas, which enhance the nucleation and growth of the second graphene layer. A fully covered graphene with 78 ± 2.8% bilayer coverage and a bilayer transmittance of 95.6% at room temperature can be achieved by modifying the process settings. Bilayer graphene samples are examined using optical microscopy (OM), scanning electron microscopy (SEM), Raman spectroscopy, and an atomic force microscope (AFM) during this process. The outcomes of our research are beneficial in clarifying the growth processes and future commercial applications of bilayer graphene.

Blood viscosity is the defining health indicator for hyperviscosity syndrome patients. This paper introduces an alternative approach for the real-time monitoring of blood viscosity by employing a surface-horizontal surface acoustic wave (SH-SAW) device at room temperature. A novel bi-layer waveguide is constructed on top of the SAW device. This device enables the SAW sensing of liquid droplets utilizing a bi-layer waveguide, consisting of a zinc oxide (ZnO) enhancement layer and Parlyene C, that facilitates the promotion of the surface horizontal mode. The ZnO piezoelectric thin-film layer enhanced the local particle displacement and dielectric coupling while the Parylene C layer constrained the wave mode at the interface of the piezoelectric material and polymer material. The device was tested with a liquid drop on the SAW delay-line path. Both experimental and finite element analysis results demonstrated the benefits of the bi-layer waveguide. The simulation results confirmed that the displacement field of local particles increased 9 times from 1.261 nm to 11.353 nm with the Parylene C/ZnO bi-layer waveguide structure. The device demonstrated a sensitivity of 3.57 ± 0.3125 kHz shift per centipoise enabling the potential for high precision blood viscosity monitoring.

An innovative optical frequency-domain reflectometry (OFDR)-based distributed temperature sensing method is proposed that utilizes a Rayleigh backscattering enhanced fiber (RBEF) as the sensing medium. The RBEF features randomly high backscattering points; the analysis of the fiber position shift of these points before and after the temperature change along the fiber is achieved using the sliding cross-correlation method. The fiber position and temperature variation can be accurately demodulated by calibrating the mathematical relationship between the high backscattering point position along the RBEF and the temperature variation. Experimental results reveal a linear relationship between temperature variation and the total position displacement of high backscattering points. The temperature sensing sensitivity coefficient is 7.814 μm/(m·°C), with an average relative error temperature measurement of −1.12% and positioning error as low as 0.02 m for the temperature-influenced fiber segment. In the proposed demodulation method, the spatial resolution of temperature sensing is determined by the distribution of high backscattering points. The temperature sensing resolution depends on the spatial resolution of the OFDR system and the length of the temperature-influenced fiber. With an OFDR system spatial resolution of 12.5 μm, the temperature sensing resolution reaches 0.418 °C per meter of RBEF under test.

A series of digital marketing transformations have been carried out at Chinese gas stations. From the perspective of user experience, the article discovers the problems in the digital service system of gas stations. Through semi-structured interviews, we collect consumers’ actual usage of digital equipment and service systems. The research adopts grounded theory to encode qualitative data. The behavioral state and psychological needs of consumers in the driving situation are analyzed. The study clarifies the influence of consumer behavior status, service context process, key task difficulty, and service information visualization on service experience. The discovery of service problems in turn help to further optimize the digital service system. The constructed SITE model clarifies the key factors of user experience in the gas station scenario. The research findings can provide a theoretical reference and practical guidance for gas station business owners, managers, and designers.

Background and objective: Teaching is widely recognized as a highly stressful profession. Job stress leads to emotional exhaustion, which in turn triggers teacher attrition. The cost is estimated as USD 2.2 billion annually for teacher dropouts. It is therefore important to understand the mental state of teachers and the factors that may influence it in order to provide the appropriate early intervention. In the past, more attention has been paid to the mental status of teachers in economically developed cities, but less research has been conducted in remote cities. In this study, we selected primary and secondary school teachers in a typical area to assess their mental health, thereby contributing to the development of effective mental health education programs for teachers in primary and secondary schools. Materials and methods: In this study, 1102 teachers from a typical city in Ningxia Province, characterized by remote mountain areas, minority communities, and a low economic level, participated. The mental status of the teachers was assessed by a Symptom Checklist-90 (SCL-90). The effects of gender, age, level of education, place of work, and marital status on the total SCL-90 score were recorded and compared. The subscale scores of the SCL-90 and the differences among the respondents with various characteristics were analyzed. Results: In total, 1025 data were valid and used for statistical analysis. The effective rate of this study was 93.01%. The analysis showed that 25.17% of the subjects had possible mental problems. There were significant differences in age and marital status (p < 0.001). The score of teachers less than 30 years old was lower than that of other teachers (p = 0.001 vs. 30–39; p < 0.001 vs. 40–49; p < 0.001 vs. ≥50). The no-marriage teachers had the lowest score than the married group or others (p < 0.001 vs. married; p < 0.05 vs. others). Compared to the norm, teachers’ mental status was poor, especially in somatization (p < 0.001), obsessive-compulsive symptoms (p < 0.001), depression (p < 0.001), anxiety (p < 0.001), hostility (p < 0.001), phobic anxiety (p < 0.001), and psychosis (p < 0.001). There were gender differences in obsessive-compulsive symptoms (p < 0.05) and depression (p < 0.05). Conclusions: These data indicate that the mental status of these teachers is not optimistic, and married female teachers aged 40–55 years need to be given more attention. Mental health examinations can be incorporated into daily physical examination items to facilitate the timely detection and early intervention of negative emotions.

Background: UAVs (Unmanned Aerial Vehicles) and SUGVs (Sidewalk Unmanned Ground Vehicles) are two prominent options to revolutionize last mile home delivery. However, there is no literature yet addressing a comprehensive assessment of them. To bridge this research gap, this paper aimed to compare UAVs to SUGVs in the context of urban parcel delivery from a practical, conceptual, technological, commercial, and environmental perspective. Methodology: Based on structured literature and web research, this paper provided a comparative status quo review of these two delivery concepts. We introduced a parameter-based cost calculus model to estimate the costs per shipment for each technology. To detect the key cost drivers, we applied a one-way sensitivity analysis, as well as a “full factorial design of experiment” approach. Results: These key cost drivers for both operations are the “number of vehicles per operator” and the “average beeline service radius”. From today’s commercial point of view, our model indicated better profitability of SUGVs. However, technical and regulatory developments may render different results in the future. As SUGVs emit significantly less noise than UAVs, we assume that SUGVs have an additional advantage for usage in autonomous urban last mile delivery from a resident’s perspective. Conclusions: Both key cost drivers will significantly influence the commercial viability of unmanned home delivery services. Safety and security aspects will determine regulatory rules on “number of vehicles per operator”. To increase the “average beeline service radius”, UAVs could profit from mothership delivery concepts while SUGV delivery may co-use existing public transport infrastructure.

The interface pressure between the cable attachment and the body is crucial for the stable long-term operation of the cable. To solve the issue of interface insulation characteristics’ damage caused by the pressure transducer measurement method, a non-destructive testing method of silicone rubber interface pressure using nonlinear ultrasound is presented. Initially, the study analyzes the propagation characteristics of ultrasonic waves at the interface of cross-linked polyethylene and silicone rubber. The study also establishes the relationship between the nonlinear coefficient and the interface pressure. Subsequently, a nonlinear ultrasonic test platform is constructed using the pulse reflection method to measure the interface pressure of flat silicone rubber and cross-linked polyethylene through nonlinear ultrasonic testing. Theoretical and experimental results indicate that the fundamental amplitude of the frequency domain of the interface reflection wave decreases, and the second harmonic amplitude and nonlinear coefficient both increase as pressure increases. These results demonstrate that the nonlinear ultrasound, non-destructive testing method can accurately evaluate the interfacial pressure state of the cable accessories.

Laser transmission welding (LTW) is an excellent process for joining plastics and is widely used in industry. Numerical simulation is an important method and area for studying LTW. It can effectively shorten the experimental time and reduce research costs, aid in understanding the welding mechanism, and enable the acquisition of ideal process parameters. To enhance understanding of numerical simulation studies on LTW and facilitate research in this area, this paper presents a comprehensive overview of the progress made in numerical simulation of LTW, covering the following aspects: (a) characteristics of the three heat source models for LTW temperature field simulation, including surface heat source model, volumetric heat source model, and hybrid heat source model, along with the methods, results, and applications of temperature field simulation based on these models and experimental validation; (b) numerical simulation of thermal and residual stresses based on the temperature field; (c) numerical simulation of the melt flow field; and (d) predictive simulation of material degradation. The conclusion of the review and the prospects for further research work are eventually addressed.

Antibiotics have been identified as emerging pollutants, and they increasingly threaten the safety of mariculture; thus, effective treatment methods are urgently needed. In this study, Fe(II)-peroxymonosulfate-modified clay (Fe-PMS-MC), an effective mineral complex for harmful algal bloom control, was tested for sulfamethoxazole (SMX) removal from seawater. The results showed that SMX removal efficiency increased gradually from 42.3% to 100% in seawater in 6 h as the Fe-PMS-MC dose increased from 0.1 g/L to 1.0 g/L; this removal was more efficient than that in freshwater. Both an increase in temperature and the addition of inorganic anions such as Cl−, HCO3−, and SO42− improved the SMX removal efficiency; in contrast, there was no noticeable influence of a pH change from 3.0 to 9.0 or of Heterosigma akashiwo biomass addition from 103 cells/mL to 105 cells/mL. Oxidation was the main mechanism for the removal of SMX by Fe-PMS-MC treatment, and the mechanisms included radical oxidation and non-radical oxidation. PMS was the key component in Fe-PMS-MC for the production of radicals, which increased with temperature. Similarly, both radical oxidation and non-radical oxidation increased when PMS was attacked by Cl−, HCO3−, and SO42− in seawater.

Quantum key distribution (QKD) protocols have unique advantages of enabling symmetric key sharing with information-theoretic security (ITS) between remote locations, which ensure the long-term security even in the era of quantum computation. QKD-based quantum secure communication (QSC) enhancing the security of key generation and update rate of keys, which could be integrated with a variety of cryptographic applications and communication protocols, has become one of the important solutions to improve information security. In recent years, the research on QKD has been active and productive, the performance of novel protocol systems has been improved significantly, and the feasibility of satellite-based QKD has been experimentally verified. QKD network construction, application exploration, and standardization have been carried out in China as well as other countries and regions around the world. Although QKD-based QSC applications and industrialization are still in the initial stage, the research and exploration momentum is positive and more achievements could be expected in the future.

With the increasingly serious problem of aminoglycoside antibiotic residues, it is imperative to develop rapid, sensitive and efficient detection methods. This article reviews the detection methods of aminoglycoside antibiotics in animal-derived foods, including enzyme-linked immunosorbent assay, fluorescent immunoassay, chemical immunoassay, affinity sensing assay, lateral flow immunochromatography and molecular imprinted immunoassay. After evaluating the performance of these methods, the advantages and disadvantages were analyzed and compared. Furthermore, development prospects and research trends were proposed and summarized. This review can serve as a basis for further research and provide helpful references and new insights for the analysis of aminoglycoside residues. Accordingly, the in-depth investigation and analysis will certainly make great contributions to food safety, public hygiene and human health.

Over the past several years, resonance energy transfer involving noble metallic nanoparticles has received considerable attention. The aim of this review is to cover advances in resonance energy transfer, widely exploited in biological structures and dynamics. Due to the presence of surface plasmons, strong surface plasmon resonance absorption and local electric field enhancement are generated near noble metallic nanoparticles, and the resulting energy transfer shows potential applications in microlasers, quantum information storage devices and micro-/nanoprocessing. In this review, we present the basic principle of the characteristics of noble metallic nanoparticles, as well as the representative progress in resonance energy transfer involving noble metallic nanoparticles, such as fluorescence resonance energy transfer, nanometal surface energy transfer, plasmon-induced resonance energy transfer, metal-enhanced fluorescence, surface-enhanced Raman scattering and cascade energy transfer. We end this review with an outlook on the development and applications of the transfer process. This will offer theoretical guidance for further optical methods in distance distribution analysis and microscopic detection.

Mesoporous materials, which exhibit great potential in the control of polymorphs and delivery of poorly water-soluble drugs, have obtained considerable attention in the field of pharmaceutical science. The physical properties and release behaviors of amorphous or crystalline drugs may be affected by formulating them into mesoporous drug delivery systems. In the past few decades, an increasing amount of papers have been written about mesoporous drug delivery systems, which play a crucial role in improving the properties of drugs. Herein, mesoporous drug delivery systems are comprehensively reviewed in terms of their physicochemical characteristics, control of polymorphic forms, physical stability, in vitro performance, and in vivo performance. Moreover, the challenges and strategies of developing robust mesoporous drug delivery systems are also discussed.