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The processing of edible oil mainly involves three stages: oilseed pretreatment, oil extraction, and oil refining. Oilseed pretreatment is the primary step in edible oil production. Thermal pretreatment of oilseeds plays a crucial role in improving oil yield and enhancing product flavor. However, poor thermal treatment conditions can destroy micronutrients and lead to the formation of harmful substances, affecting the nutritional and safety quality of edible oil. This study primarily focused on various thermal pretreatment methods, such as high-temperature roasting, infrared, microwave, and ultrasonic treatment. It summarized the main types of thermal pretreatment and their characteristics in oilseed processing. Additionally, it provided an overview of the effects of different thermal pretreatment methods on oil yield, basic oil quality, nutrient content, and harmful components. This information served as a reference for developing flexible and stable pretreatment technologies for oilseeds, which could achieve precise and moderate oil processing, and improve the nutritional and safety quality of edible oil.

Inducing an anti-inflammatory response before neurogenesis is crucial in effectively addressing peripheral nerve damage. Herein, we developed shell-core-structured nanofilms (Cur/PLCL@BDNF/CNT) using poly-(l-Lactide)-Caprolactone (PLCL) and curcumin (Cur, an anti-inflammatory agent) as the shell layer, and carbon nanotubes (CNT) and brain-derived neurotrophic factor (BDNF, a neurogenic factor) as the core via coaxial electrospinning technology. The resulting Cur/PLCL@BDNF/CNT film exhibited a characteristic fibrous structure with remarkable shell-core architecture, demonstrating unweakened mechanical properties. Notably, it displayed sustained release kinetics with distinct stages: prioritized Cur release within the initial 12 days and delayed BDNF release between 10 to 30 days. Additionally, the Cur/PLCL@BDNF/CNT film demonstrated high biocompatibility with Schwann cells. Subsequent in vitro analysis revealed the potent anti-inflammatory capabilities of the released Cur from the shell layer, while the BDNF released from the core layer effectively induced neurogenic differentiation of Schwann cells. The Cur/PLCL@BDNF/CNT film was rolled into a nerve conduit and then utilized for nerve regeneration in a 10 mm rat sciatic nerve defect model. The staged release of Cur and BDNF facilitated by the Cur/PLCL@BDNF/CNT film established an anti-inflammatory microenvironment before initiating nerve regeneration, resulting in better nerve restoration. This study emphasizes the significance of shell-core-structured nanofilms in temporally regulating anti-inflammation and neurogenesis.

This article focuses on the structural design of a surgical robot for radioactive prostate seed implantation and the position detection algorithm for the puncture needle. A seed implantation robot with the ability to pierce with force and receive image feedback is created to increase the positioning precision and puncture stability of the robot as well as to determine the real-time position of the puncture needle. Compared with existing puncture schemes, we use a statistical model approach for classification and a deep learning-based target detection algorithm. Since different human tissues have different structural properties, we conducted quantitative puncture experiments, and the experimental results demonstrated that this puncture scheme can effectively discriminate the punctured tissue and position the puncture needle tip, significantly improving the success rate of surgical radioactive seed implantation procedures.

Abstract Objective to investigate the association between cartilage lesion-related features observed in knee osteoarthritis (OA) patients’ first MRI examination and incident knee surgery within 5 years. Additionally, to assess the predictive value of these features for the incident knee surgery. Methods We identified patients diagnosed with knee OA and treated at our institution between January 2015 and January 2018, and retrieved their baseline clinical data and first MRI examination films from the information system. Next, we proceeded to determine joint space narrowing grade, cartilage lesion size grade, cartilage full-thickness loss grade and cartilage lesion sum score for the medial and lateral compartments, respectively. Generalized linear regression models examined the association of these features with 5-year incident knee surgery. Positive and negative predictive values (PPVs and NPVs) were determined referring to 5-year incident knee surgery. Results Totally, 878 participants (knees) were found eligible to form the study population. Within the 5 years, surgery was performed on 61 knees. None of the cartilage-related features had been found significantly associated with incident surgery. The results were similar for medial and lateral compartments. The PPVs were low for all the features. Conclusions Among symptomatic clinically diagnosed OA knees, cartilage lesions observed in the first MRI examinations were not found to be associated with the occurrence of joint surgery within a 5-year period. All these cartilage-related features appear to have no additional value in predicting 5-year incident joint surgery.

ObjectiveTo establish a UHPLC-MS/MS quantitative method for the determination of glucuronic acid， tartaric acid， glycolic acid， malic acid， lactic acid， citric acid， DL-2-hydroxybutyric acid sodium， mandelic acid， benzilic acid， hydroxycaprylic acid， lactobionic acid， gluconic acid and N-acetylneuraminic acid in cosmetics.MethodsSamples were prepared by ultrasonic extraction， cleansed by precipitating reagent and followed by high-speed centrifugation of the extraction solution. The supernatant was filtered by 0.22 μm Millipore filter. The continued filtrate was taken for analysis. A reversed phase column， Poroshell 120 EC-C18 （2.7 μm， 4.6 mm×1 000 mm） was used with 0.1% formic acid buffer and acetonitrile as the mobile phase under the condition of gradient elution. The analytes were detected with electrospray ionization source in negative ion mode （ESI-） and multiple reactions monitoring （MRM）， and quantified by external standard curve.ResultsThe method showed a good linearity of glucuronic acid， tartaric acid， malic acid， DL-2-hydroxybutyric acid sodium， benzilic acid， hydroxycaprylic acid and N-acetylneuraminic acid within the concentration range of 50.0‒2 000.0 μg·L-1 （r>0.995）. The method showed a good linearity of glycolic acid， lactic acid， citric acid and mandelic acid within the concentration range of 100.0‒5 000.0 μg·L-1 （r>0.995）. The method showed a good linearity of lactobionic acid and gluconic acid within the concentration range of 50.0‒5 000.0 μg·L-1 （r>0.995）. The recoveries were in the range of 92.3%‒114.1%； the relative standard deviations （RSD） were in the range of 0.9%‒6.0% （n=3）. The detection limits of glucuronic acid， tartaric acid， malic acid， citric acid， DL-2-hydroxybutyric acid sodium， mandelic acid， benzilic acid， hydroxycaprylic acid， lactobionic acid， gluconic acid and N-acetylneuraminic acid were 0.003% while the detection limits of glycolic acid， lactic acid and mandelic acid were 0.006%. In 10 batches of commercially available cosmetics， eight batches showed positive result.ConclusionThe UHPLC-MS/MS method is efficient， sensitive and accurate and is applicable to the determination of 13 α-hydroxy acidic components in cosmetics.

This article focuses on the use of a puncture classification method for prostate cancer seed implantation robots. To address the limitations of seed implantation surgery, different tissues in the human body are punctured and classified to improve the precision and success rate of seed implantation. This paper discusses an information fusion sensing technique that can be used in seed implantation surgery, which senses the real-time state of the puncture needle by fusing force and image modes and dramatically improves puncture accuracy and surgical tolerance. In addition, considering the multiscale feature problem of the image recognition process, this paper improves the YOLOv8 model by adding a global attention mechanism (GAM_Attention) to the backbone of the model, which significantly improves the image recognition success rate. Then, datasets of the puncture force and real-time puncture images were produced through puncture experiments. Preliminary puncture experiments with different models were completed, and the experimental results showed that the classification method improved the classification accuracy. The accuracy of seed implantation is improved by this method, which may provide a new idea for deep learning in seed implantation modality perception.

Auditory Brainstem Response (ABR) is an evoked potential in the brainstem’s neural centers in response to sound stimuli. Clinically, characteristic waves, especially Wave V latency, extracted from ABR can objectively indicate auditory loss and diagnose diseases. Several methods have been developed for the extraction of characteristic waves. To ensure the effectiveness of the method, most of the methods are time-consuming and rely on the heavy workloads of clinicians. To reduce the workload of clinicians, automated extraction methods have been developed. However, the above methods also have limitations. This study introduces a novel deep learning network for automatic extraction of Wave V latency, named ABR-Attention. ABR-Attention model includes a self-attention module, first and second-derivative attention module, and regressor module. Experiments are conducted on the accuracy with 10-fold cross-validation, the effects on different sound pressure levels (SPLs), the effects of different error scales and the effects of ablation. ABR-Attention shows efficacy in extracting Wave V latency of ABR, with an overall accuracy of $96.76~\pm ~0.41$ % and an error scale of 0.1ms, and provides a new solution for objective localization of ABR characteristic waves.

Dual-phase steels have received extensive attention in autobody frame manufacturing due to the resulting characteristics of an interesting combination of ductile ferrite and hard martensite. Moreover, the ductile ferrite and hard martensite lead to heterogeneous deformation in the boundary between the two phases. Then, geometrically necessary dislocations (GNDs) are created to accommodate a lattice mismatch due to the deformation incompatibility of the boundary in straining. In this study, a new empirical GND model is developed, in which the GND density is a function of local plastic deformation; the GND density is distributed in the phase boundary in accordance with an “S” model of material plastic strain. The boundary conditions are applied to define the parameters. The proposed model is verified with DP600 steel. The effects of the GNDs and the width between ferrite and martensite on the strain hardening of DP600 steel are evaluated.

Bulk grain categorized storage, is a modern grain storage technology with the aims to meet the requirements of optimal purchase, storage, and sales, guided by grain usage and quality control. The increase of high-quality grain supply represents the development direction of refined management in grain storage. The determination of the storage capacity of a single warehouse is directly related to the types, grain varieties, uses of grain, and quality control technology in the process of discharging the warehouse. Based on the analysis of the grain storage use, the problems existing in the sales and the acceptance capacity of customers, it is addressed that the size of the grain storage single warehouse for different grain varieties and different uses should be matched with the acceptance capacity of the sales destination. Under the existing technical conditions, the relevant opinions and suggestions were preliminary proposed on the appropriate single warehouse capacity scale, which could match the customer acceptance capacity, the grain storage quality control technology and the research on grain warehouse type.

This paper proposes a novel finger-individuating exoskeleton system with a non-contact leader–follower control strategy that effectively combines motion functionality and individual adaptability. Our solution comprises the following two interactive components: the leader side and the follower side. The leader side processes joint angle information from the healthy hand during motion via a Leap Motion Controller as the system input, providing more flexible and active operations owing to the non-contact manner. Then, as the follower side, the exoskeleton is driven to assist the user’s hand for rehabilitation training according to the input. The exoskeleton mechanism is designed as a universal module that can adapt to various digit sizes and weighs only 40 g. Additionally, the current motion of the exoskeleton is fed back to the system in real time, forming a closed loop to ensure control accuracy. Finally, four experiments validate the design effectiveness and motion performance of the proposed exoskeleton system. The experimental results indicate that our prototype can provide an average force of about 16.5 N for the whole hand during flexing, and the success rate reaches 82.03% in grasping tasks. Importantly, the proposed prototype holds promise for improving rehabilitation outcomes, offering diverse options for different stroke stages or application scenarios.

Objective: This paper discusses the feasibility of using mineral element fingerprinting technology of to identify tobacco producing areas, screens out the effective indicators, and constructs the discrimination model of tobacco producing areas. Methods: The contents of 20 mineral elements in tobacco leaves from 11 producing areas were simultaneously determined by ICP-MS, and the data were analyzed by variance analysis, cluster analysis, principal component analysis and discriminant analysis. Results: The contents of 16 elements were significantly different among producing areas, and principal component analysis resulted in 6 principal components, with the cumulative variance contribution of 89.253%. Using linear discriminant analysis, four elementsmineral, K, Mn, Se and Ba, were screened as the effective indicators to discriminate the geographical origin of tobacco leaves. The established discriminant model could accurately distinguish tobacco leaf samples from different tobacco producing areas. Conclusion: Significant differences were showed in the contents of mineral elements in tobacco leaves from 11 producing areas. Four elements, K, Mn, Se and Ba, are important indicators for distinguishing tobacco producing areas. Mineral element fingerprinting technology can be used for distinguishing tobacco producing areas.

BackgroundExtraction of carbon from water is a crucial preprocessing step for measuring 14C in environmental waters using liquid scintillation spectrometry.PurposeThis study aims to explore the optimal technological conditions for extracting carbon from water using wet oxidation method.MethodsA wet oxidation system combining sodium persulfate and Fenton's reagent, along with phosphoric acid acidification and nitrogen bubbling, were employed for the wet oxidation carbon extraction experiments on two types of water samples with known (deionized water + sucrose) and unknown carbon components, each with a volume of 10 L. Simultaneously, carbon extraction experiments were conducted on the water samples having unknown carbon component, using a combination of wet oxidation and 185 nm ultraviolet (UV) oxidation so as to determine the optimal timing and sequence of reagent addition, as well as the optimized reagent dosage and ratio. Further experiments under optimized conditions were conducted to obtain more results for deep analysis.ResultsUnder the optimized conditions, after a 3-h reaction at 90 °C, the organic carbon extraction rate for the known carbon component (deionized water + sucrose) exceeds 96%. The total carbon extraction rate from the unknown carbon component water is (96.8±0.3)%, with an inorganic carbon extraction rate >98.5%, and an organic carbon extraction rate of (93.4±0.2)%, while the oxidation rate of tannic acid-type organic compounds is only (88±0.2)%. After the combination of wet oxidation and 185 nm UV oxidation, the total carbon extraction rate for the unknown carbon component increases to (98.3±0.5)%, with an inorganic carbon extraction rate ≥99% and an organic carbon extraction rate that can reach (95.6±1.4)%.ConclusionsResults of this study indicate that wet oxidation alone cannot represent the carbon recovery rate in actual water samples using typical organic compound carbon recovery rates. The combination of wet oxidation and 185 nm UV oxidation proves to be a more effective method for carbon extraction from water.

In the design of prosthetic hand fingers, achieving human-like movement while meeting anthropomorphic demands such as appearance, size, and lightweight is quite challenging. Human finger movement involves two distinct motion characters during natural reach-and-grasp tasks: consistency in the reaching stage and adaptability in the grasping stage. The former one enhances grasp stability and reduces control complexity; the latter one promotes the adaptability of finger to various objects. However, conventional tendon-driven prosthetic finger designs typically incorporate bulky actuation modules or complex tendon routes to reconcile the consistency and adaptability. In contrast, we propose a novel friction clutch consisting of a single tendon and slider, which is simple and compact enough to be configurated within the metacarpal bone. Through tactfully exploiting the friction force to balance the gravity effect on each phalanx during finger motion, this design effectively combines both consistency and adaptability. As a result, the prosthetic finger can maintain consistent motion unaffected by any spatial posture during reaching, execute adaptive motion during grasping, and automatically switch between them, resulting in human-like reach-and-grasp movements. Additionally, the proposed finger achieves a highly anthropomorphic design, weighing only 18.9 g and possessing the same size as an adult’s middle finger. Finally, a series of experiments validate the theoretical effectiveness and motion performance of the proposed design. Remarkably, the mechanical principle of the proposed friction clutch is beneficial to achieve highly anthropomorphic design, providing not only a new strategy to prosthetic hand design but also great potential in hand rehabilitation.

With the development of construction industry, the traditional manual inspection has been gradually eliminated due to many shortcomings, such as low efficiency, time-consuming and labor-intensive. Meanwhile, the current helmet detection model on the market does not consider the interference of complex weather, which greatly affects the detection performance. A low-cost helmet detection scheme is proposed in this paper, which can be used in various complex weather environments such as heavy rain, fog and snow. Firstly, the monitoring video of the construction site is sliced as the helmet wearing detection data set, and improved on the basis of Yolo v5s model to make it meet the requirements of helmet detection. Secondly, data augmentation and oversampling are adopted to improve the accuracy for small targets. Finally, K-means++ clustering algorithm is utilized to change the dimension of anchor box for better detection performance, and MSRCR algorithm is used to filter complex weather conditions. Compared to the original Yolo v5s, the mean average precision of the proposed scheme achieves 94.27% under complex weather conditions. For images with a size of 300*300, the detection speed can reach 63 frames per second. Therefore, the scheme can realize a high-precision, real-time and low-cost helmet detection system which can be used in a complex weather environments effectively.

Edible oils and fats are the important dietary nutrients for human body, and play a vital roles in maintaining nutritional health for the hosts. Whereas, the unhealthy oils and fats intake would lead to the increase of the risks of chronic metabolic diseases, which has become a serious public health challenge for the present society. The oilomics, integrating genomics, transcriptomics, proteomics, metabolomics, lipomics as the major analytical methods, have been becoming on important approach to elucidate the host nutritional and metabolic regulation mechanisms, and realize the personalized nutrition of human body based on the functional characteristics of dietary factors. The present review manuscript illustrated the basic concepts of oilomics, and the major research approaches of oilomics in the areas of edible oil nutrition and human health. Moreover, the research progress of oilomics in oil nutrition and host health research were also summarized, primarily, focusing on elaborating the nutrients metabolic regulation, the enteral nutrition and gut homeostasis, as well as the personalized nutrition of the humans. In view of the current research status, the future trends of the development of oilomics were further prospected, at the aim of which is to provide references for expanding the applications of oilomics in lipid nutrition and human health. The overall nutrition level of the nationwide residents will be improved, and the construction of healthy China will be promoted.

Oil is a significant source of fatty acids and various trace functional components, and plays a vital role in regulating human health. The macro- and micro-components in oils are closely related to nutritional health. This paper introduces the future development goals and strategies of healthy oils from two aspects of precise nutrition and moderate processing. Firstly, precise nutrition based on life cycle and physiological state is a priority research area of lipid science. On the other hand, moderate processing will retain nutrients such as vitamin E, phytosterols, and squalene to a greater extent, and avoid the formation of risk factors such as trans fatty acids, 3-chloropropanol esters, and glycidyl esters. Moderate processing not only ensures the safety of oil, but also reduces the loss of healthy and beneficial fat concomitants, which is the development direction of oil engineering research. Therefore, under the dual demands of nutrition and safety, accurate nutrition and moderate processing of oils will help the implementation of "Healthy China" and "Double- Carbon" strategies. Future healthy oils will not only provide basic nutrition and flavor, but also give specific health functions to people with different life cycles, such as infants, children, adolescents, adults and the elderly, and maintain the homeostasis of people with different physiological states including pregnant and lactating women.

As an important national strategy, the security of cereal and oil plays a key role in maintaining social stability, promoting the rural revitalization strategy and keeping a sustained, rapid and sound development of national economy. With rapid increase of global population and continous development of food industry, the more diversified, healthy and low-carbon cereal and oil products have been preferred by consumers. However, in China, the development of cereal and oil industries is constrained by many problems, including limited cereal and oil processing resources, poor green processing technology, lack of moderate processing means, unclear mechanism of nutritional factors, and difficulty in hazard risk control. With the development of life science, information technology and materials technology, future food science and technology of cereal and oil based on food omics, synthetic biology, nutrition and materials science are expected to meet the above challenges from the technical level. This paper outlined the status and role of cereal and oil food industries in the national economy, and summarizedthe development trend and market conditions of cereal and oil industries. In China, the technical challenges faced by cereal and oil in China, grain, oil and food science and technology were also introduced, and the future development trend of grain, oil and food science and technology will also be prospected, including moderate oil processing, green grain production, intelligent safety control, and precise nutrition supply.

ObjectiveAn HPLC method was established for the determination of azelaic acid and potassium azeloycinate diglycinate in cosmetics.MethodsThe samples were extracted with 60 mmol·L-1 sodium hydroxide water solution-methyl alcohol. After centrifugation and filtration， the analysis of azelaic acid and potassium azeloycinate diglycinate was performed with a SVEA C8（250 mm×4.6 mm， 5 μm） column， using 15 mmol‧L-1 potassium dihydrogen phosphate solution （pH=3.0） and acetonitrile for gradient elution at a flow rate of 1.0 mL·min-1. The analytes were detected with UV detector， and quantified by external standard curve.ResultsThe results showed a good linearity in the range of 5‒1 000 μg‧mL-1 with correlation coefficients （r） larger than 0.999. The detection limit of azelaic acid and potassium azeloycinate diglycinate （LOD） was 0.020% and 0.015%， respectively. The spiked recoveries were 87.66% to 108.96% with the relative standard deviation （RSD） of 0.6% to 3.3%.ConclusionThe method is simple， rapid and highly sensitive. It is suitable for the determination of azelaic acid and potassium azeloycinate diglycinate in cosmetics.

As a structured form of human knowledge,knowledge graphs have played a great supportive role in supporting the semantic intercommunication of massive,multi-source,heterogeneous data,and effectively support tasks such as data analysis,attracting the attention of academia and industry.At present,most knowledge graphs are constructed based on non-real-time static data,without considering the temporal characteristics of entities and relationships.However,data in application scenarios such as social network communication,financial trade,and epidemic spreading network are highly dynamic and exhibit complex temporal properties.How to use time series data to build knowledge graphs and effectively model them is a challenging problem.Recently,numerous studies use temporal information in time series data to enrich the characteristics of knowledge graphs,endowing know-ledge graphs with dynamic features,expanding fact triples into quadruple representation(head entity,relationship,tail entity,time).The knowledge graph which utilizes time-related quadruples to represent knowledge are collectively referred to as temporal knowledge graph.This paper summarizes the research work of temporal knowledge graph representation learning by sorting out and analyzing the corresponding literature.Specifically,it first briefly introduce the background and definition of temporal know-ledge graph.Next,it summarizes the advantages of the temporal knowledge graph representation learning method compared with the traditional knowledge graph representation learning method.Then it elaborates on the recent method of temporal knowledge graph representation learning from the perspective of the method modeling facts,introduces the dataset used by the above method and summarizes the main challenges of this technology.Finally,the future research direction is prospected.

Phosphine and sulfuryl fluoride are two kinds of fumigation insecticides allowed for use in China and overseas. Phosphine is the “trump card” fumigation insecticide for stored grain, while Sulfuryl fluoride is mainly used as the phosphine resistance management drug. Therefore, both of them are complementary to a certain extent. In view of the application status, problems, and challenges faced by the prevention and control of stored grain pests in China, this paper investigated and sorted out the basic technical characteristics, main production enterprises, production and sales, application technology, residual problems, disposal methods, and application dominance of global grain fumigation pesticide aluminum phosphide (phosphine). Combined with the domestic and international situation, this paper also summarized the technical characteristics, its relationship with phosphine, demand, application characteristics and existing problems of sulfuryl fluoride fumigation, and put forward the suggestions and necessity of systematically carrying out the research on sulfuryl fluoride fumigation and its impact on the environment, so as to comply with the concept of “green, ecological, economic and efficient” and provide reference for the scientific and technological development of stored grain pest control in China.

Under the guidance of the principle of integrated control, this paper investigated and sorted out several methods of integrated control of stored grain pests (physical, chemical and biological control), the management principles of phosphine resistance, the effect of resistance control, essentials and existing problems of comprehensive prevention and control. Some suggestions on the development of integrated pest control technology in stored grain were put forward. In order to deal with pest resistance effectively, reduce pest occurrence, reduce the use of chemicals and the dependence on chemical fumigations, we should pay attention to the combined application of fumigation, protectant, physical control and biological control methods to improve the integrated pest control technology system for grain post-harvest storage and logistics that is suitable for China, so as to comply with the concept of “green, ecological, economic and efficient” and provide ideas for scientific and technological development of integrated pest control in grain storage in China.

The condition assessment of the entire life cycle of nuclear power equipment has a significant impact on improving the safety and economy of nuclear power plants. In the past, operation and maintenance of systems, equipment, and structures of domestic nuclear power plants, mostly relied on the alarm mechanism of equipments, the simple threshold judgments of parameters, or the empirical judgments of engineers. With the implementation of online monitoring system in nuclear power plants, a large number of equipment operation data have been accumulated, and the use of data-driven technology to assess the health of equipment has become the focus of attention in the industry. In this paper, the current situation of the online monitoring system of nuclear power equipment was introduced and the common malfunction of nuclear power equipment was analyzed. The condition assessment of nuclear power equipment were categorized into three major problems (i.e., anomaly detection, life prediction, and fault diagnosis), the situation of research and application were summarized respectively, and the application potential of deep learning technology in this field was emphasized. Based on this, the challenges and possible solutions to the condition assessment of nuclear power plant equipment were further analyzed.

ObjectiveTo determine bimatoprost， tafluprost ethyl amide， latanoprost， travoprost and tafluprost in eyelash enhancing cosmetics by establishing a LC-MS/MS method.MethodsThe samples were extracted with a 50% acetonitrile water solution. A salt mixture （4 g NaCl， 1 g MgSO4） was added to the solution to induce phase separation. After centrifugation and filtration， the analysis of five prostaglandin analogs was performed with an Agilent Poroshell 120 PFP-C18 （2.7 μm， 2.1 mm×100 mm） column， using 0.02% formic acid containing 5 mmol·L-1 Acetic acid amine and acetonitrile by gradient elution at a flow rate of 0.5 mL·min-1. The analytes were detected with electrospray ionization source in positive ion mode （ESI+） and multiple reaction monitoring （MRM）， and quantified by external standard curve.ResultsThe results showed that it had a good linearity in the range of locatable ambit of concentration with correlation coefficients （r） larger than 0.999. The detection limit of five prostaglandin analogs （LOD） was 0.000 2‒1.5 μg·g-1. The spiked recoveries were 93.2% to 103.5% with a relative standard deviation （RSD） of 1.2% to 3.4%.ConclusionThe method is simple， rapid and highly sensitive. It is suitable for the determination of five prostaglandin analogs in eyelash enhancing cosmetics.

Fe3O4@PVA microcapsule catalyst with dissolution as trigger condition was synthesized by utilizing nano Fe3O4 catalyst as core material and water-soluble polyvinyl alcohol as shell material. The microcapsule catalyst was loaded in poly(lactic-co-glycolic acid)(PLGA) membrane to prepare the freshwater/seawater degradable Fe3O4@PVA/PLGA composite films.Transmission electron microscopy (TEM) and dynamic light scattering (DLS) particle size distribution were used to test the morphology of Fe3O4@PVA. The shell thickness of Fe3O4@PVA core-shell particles is 2-3 nm. The structural characteristics, magnetic and mechanical properties of Fe3O4@PVA core-shell particles and Fe3O4@PVA/PLGA composite membrane were determined by FTIR, XPS, TG, VSM and electronic universal material tests. The degradation properties of Fe3O4@PVA/PLGA composite films in freshwater, seawater, air, darkness and low temperature environments were discussed. The results show that the maximum degradation ratio of Fe3O4@PVA/PLGA composite films is 97.79% at 120 days in seawater and 99.75% at 120 days in freshwater. Fe3O4@PVA/PLGA composite films are degraded in the seawater and the mass average molecular weight decreases from 28440 to 1396.

Objective To investigate the clinical characteristics, neurosurgical strategy and curative effect of intracranial invastive olfactory neuroblastoma. Methods A total of 24 patients with intracranial invasive olfactory neuroblastoma diagnosed and treated in Beijing Tongren Hospital, Capital Medical University from January 2005 to December 2020 were included. All patients underwent bilateral extended transbasal approach combined with endoscopic transnasal approach and skull base reconstruction. Results Among the 24 patients, total resection was performed in 22 cases (91.67%) and nearly total resection in 2 cases (8.33%), all of which were confirmed as olfactory neuroblastoma by postoperative pathological examination. Transient cerebrospinal fluid leakage occurred in 2 cases (8.33%) and intracranial infection occurred in 2 cases (8.33%), which were cured by symptomatic treatment. Visual acuity was aggravated in one case and eye movement disorder in 2 cases. Twenty patients were followed up for an average of 54.60 months, and no long⁃term operation related complications occurred. During the follow⁃up period, 12 patients (60%) had tumor recurrence, and the 5⁃year survival rate was 45% (9/20). Conclusions Surgical resection of intracranial invasive olfactory neuroblastoma via extended transbasal approach combined with endoscopic transnasal approach is safe and effective. The operative surgeon should have both microneurosurgery and neuroendoscopy techniques, which is worthy of clinical promotion.

Sulfuryl fluoride is a broad-spectrum fumigant pesticide.The pesticide was registered for the first time in the United States in the 1950s.However,it has only been used as a food (grain) fumigant for more than a decade internationally.This is mainly because its problems are prominent,and it has been a controversial fumigant from the start.At present,“reducing the dose of pesticides,reducing residues,and reducing emissions” is an inevitable requirement for the development of sulfuryl fluoride fumigation and insecticide technology.The research and development of sulfuryl fluoride efficient fumigation and insecticide technology featuring “low dose,low residue,and low emission” is likely to be a feasible technical approach.

The Mg-9Al-3Si-0.375Sr-0.78Y alloy specimens were compressed at constant isothermal strain rate by Gleeble 3500 thermal-simulation machine. The hot deformation behavior in the range of 250-400℃ and strain rate 0.001-10 s-1were studied. The results show that the peak stress decreases with the decreasing of strain rate and the increasing of temperature, meanwhile, the sensitivity of peak stress to strain rate increases with the decreasing of deformation temperature. In addition, the Arrhenius constitutive equation of hot deformation considering strain is established. The calculated flow stresses are compared with the experimental results, in the range of 300, 350℃ and 0.001-10 s-1, the mean absolute errors of the model are 1.57% and 1.76%, respectively. The average deformation activation energy is about 183.58 kJ/mol, and the average strain rate sensitivity index is 0.1616. The α-Mg phases exhibit dynamic recrystallization characteristics obviously. The size of β-Mg17Al12 phases decreases and its distribution becomes uniform, and the morphology of primary Mg2Si phase changes little. At low temperature (250-300℃), dynamic recrystallization occurs only at the grain boundary. Under high temperature (350-400℃) deformation, the primary α-Mg grains show significant dynamic recrystallization. With the increasing temperature and decreasing strain rate, recrystallization degree increases and recrystallization grain grows gradually.

Large-size TSVs have larger parasitic capacitance, which leads to more resolution challenges. At the same time, due to the opposite fault effect of resistive open fault and leakage fault in the ring oscillator, the coexistence of two types of faults will cause serious test confusion. These problems significantly increase the difficulty in the TSV test. In this paper, a test method using Schmitt trigger as a TSV receiver is presented to enhance test resolution and reduce test confusion when two kinds of faults exist simultaneously. Schmitt trigger that is characterized by two threshold voltages is used to improve the test resolution. By reducing the supply voltage and checking whether the ring oscillator oscillates, we can identify whether there are two kinds of faults coexisting. HSPICE simulation results based on 45nm CMOS technology demonstrate that the proposed method offers better test resolution in terms of large-size TSVs compared with the existing similar methods, and can distinguish the misdiagnosis when there are two kinds of faults existing simultaneously in a TSV.

Timely and effective interventions after tracheal mucosal injury are lack in clinical practices, which elevate the risks of airway infection, tracheal cartilage deterioration, and even asphyxiated death. Herein, we proposed a biomaterial-based strategy for the repair of injured tracheal mucosal based on a copper hydrogen phosphate nanosheets (CuHP NSs) functionalized commercial hydrogel (polyethylene glycol disuccinimidyl succinate-human serum albumin, PH). Such CuHP/PH hydrogel achieved favorable injectability, stable gelation, and excellent adhesiveness within the tracheal lumen. Moreover, CuHP NSs within the CuHP/PH hydrogel effectively stimulate the proliferation and migration of endothelial/epithelial cells, enhancing angiogenesis and demonstrating excellent tissue regenerative potential. Additionally, it exhibited significant inhibitory effects on both bacteria and bacterial biofilms. More importantly, when injected injured site of tracheal mucosa under fiberoptic bronchoscopy guidance, our results demonstrated CuHP/PH hydrogel adhered tightly to the tracheal mucosa. The therapeutic effects of the CuHP/PH hydrogel were further confirmed, which significantly improved survival rates, vascular and mucosal regeneration, reduced occurrences of intraluminal infections, tracheal stenosis, and cartilage damage complications. This research presents an initial proposition outlining a strategy employing biomaterials to mitigate tracheal mucosal injury, offering novel perspectives on the treatment of mucosal injuries and other tracheal diseases.

Deep neural networks capable of representing the density functional theory (DFT) Hamiltonian as a function of material structure hold great promise for revolutionizing future electronic structure calculations. However, a notable limitation of previous neural networks is their compatibility solely with the atomic-orbital (AO) basis, excluding the widely used plane-wave (PW) basis. Here we overcome this critical limitation by proposing an accurate and efficient real-space reconstruction method for directly computing AO Hamiltonian matrices from PW DFT results. The reconstruction method is orders of magnitude faster than traditional projection-based methods to convert PW results to the AO basis, and the reconstructed Hamiltonian matrices can faithfully reproduce the PW electronic structure, thus bridging the longstanding gap between the AO basis deep learning electronic structure approach and PW DFT. Advantages of the PW methods, such as high accuracy, high flexibility and wide applicability, thus can be all integrated into deep learning electronic structure methods without sacrificing these methods inherent benefits. This allows for the construction of large-scale and high-fidelity training datasets with the help of PW DFT results towards the development of precise and broadly applicable deep learning electronic structure models.