Selective removal of aqueous Hg2+ by magnetic composites sulfur-containing on the hyper-branched surface: Characterization, performance and mechanism.

The adsorbents with recyclable, large adsorption capacity and selective adsorption can effectively remove the pollution and harm of heavy metal ions in water. Therefore, two magnetic composites containing sulfur (MCP-S4 and MCP-S8) on the hyper-branched surface were prepared, furthermore, their structures were characterized and adsorption performance was analyzed by FTIR, XRD, TGA, BET, SEM, TEM, VSM and ICP. The results showed that both MCP-S4 and MCP-S8 had superparamagnetism with saturation susceptibility of 22.10 and 22.26 emu/g, and owned a specific surface area of 11.394 and 11.235 m2/g, respectively. MCP-S4 and MCP-S8 could selectively adsorb Hg2+ with the exist of Fe3+, Cu2+, Co2+, Ni2+, Mn2+, and Al3+ in solution. The adsorption kinetics accorded with pseudo-second-order model and Boyd film diffusion model, and the adsorption isotherm was fitted better with Langmuir isotherm model and D-R model, furthermore, the adsorption was an entropic-increasing and endothermic process. The removal rate of Hg2+ from simulated sewage by the two materials was more than 91%, and the adsorption retention rate was more than 85% after five adsorption-desorption cycles. The adsorption mechanism was analyzed by comparing the changes of FTIR, EDS and XPS spectra before and after adsorption. It was found that functional groups (C-N, CONH, CS, SH) could form stable chelates with Hg2+, which was the main reason why MCP-S4 and MCP-S8 could adsorb Hg2+ selectively, furthermore, S atoms of CS and -SH played a leading role in the process of adsorption. In addition, DFT calculation was also used as an auxiliary means to verify the adsorption mechanism.

Selective adsorption of heavy metals from water by a hyper-branched magnetic composite material: Characterization, performance, and mechanism.

The development of adsorbents to remove heavy metal ions from water with recyclable, high adsorption capacity, strong selectivity, safe, and economic performances has always been the focus and challenge of current research. A hyper-branched magnetic composite material (Fe3O4@SiO2-S4) was fabricated by a method combining "grafting,", "branching," and "modification,", and the structure was characterized by FTIR, XRD, SEM, TEM, SAED, VSM, TGA, and BET. In addition, the adsorption performance and mechanism for heavy metal ions in water were studied. The as-prepared composite material had excellent selective absorbability for Hg2+, Cd2+, and Ag+ in the presence of Fe3+, Fe2+, Cu2+, Mn2+, CO2+, Zn2+, and Ni2+, and when pH = 6, T = 30 °C, t = 4 h, it reached a saturated adsorption capacity of 2.42, 2.18, and 1.94 mmol/g to Hg2+, Cd2+, and Ag+, respectively. The adsorption isotherm was consistent with the Langmuir isotherm adsorption model, and the Dubinin Redushcke (D-R) model identified that the adsorption was chemical adsorption in nature. The adsorption kinetic followed the pseudo-second-order model and Boyd film diffusion models. The adsorption capacity of as-prepared material remained about 83% after five elutions. The adsorption mechanism and selective adsorption were revealed by FTIR, EDS, XPS, and DFT calculation. N atoms and O atoms of the active functional groups complexed with metal ions to form stable 2 heptachate chelates and 1 tridentate chelate to achieve the effect of adsorption; furthermore, the adsorption was mainly governed by N atoms of Schiff base groups. This work not only explored an innovative method for the construction of adsorbing materials but also provided a promising adsorbent to selectively remove heavy metal ions in water with potential application.

Immobilization properties and adsorption mechanism of nickel(II) in soil by biochar combined with humic acid-wood vinegar.

Biochar (BC) combined with humic acid (HA) and wood vinegar (WV) was designed and prepared as an inexpensive, effective, and environmentally friendly immobilization material (BHW) for metal-polluted soil. The influences of the wood vinegar and humic acid on the immobilization properties and adsorption mechanism of this new material were also investigated. The remediation performance was evaluated using a laboratory-made, nickel-contaminated soil with a Ni2+ concentration of 200 mg per kg surface soil (top 20 cm from agricultural land). The results indicated that the immobilization ratio sequence of nickel (II) in the soil was BC< BH< BHW. The maximum adsorption capacity increased in the same order: BC< BH< BHW. All three adsorption isotherms were better fitted by the Freundlich model, which were consistent with the surface heterogeneity of the remediation materials. The cause of this surface heterogeneous migration may be due to the increase in oxygen-containing groups in the BC introduced by the HA and WV. The WV can increase the number of the oxygen-containing groups in the BC combined with HA, which enhanced the adsorption and immobilization of Ni2+ ions. The results suggested that BHW is recommended for the remediation of metal-contaminated soils, because of its high efficacy, economic feasibility, environmental and food safety.

Regioselective Synthesis of Functionalized Dihydropyrones via the Petasis Reaction.

A novel synthesis methodology for the construction of functionalized dihydropyrones has been developed with amines, glyoxylic acid, and 4-substituted-1,2-oxaborol-2(5H)-ols from the Petasis reaction. Mechanistic investigation indicated the intermolecular SN2 cyclization to provide 3,6-dihydro-2H-pyran-2-ones (3,6-DHP) and 5,6-dihydro-2H-pyran-2-ones (5,6-DHP) in one step with moderate to excellent yields.

A Priori-Based Subarray Selection Algorithm for DOA Estimation.

A finer direction-of-arrival (DOA) estimation result needs a large and dense array; it may, however, encounter the mutual coupling effect, which degrades the performance of DOA estimation. There is a new approach to mitigating this effect by using a nonuniform array to achieve DOA estimation. In this paper, we consider a priori DOA estimation, which is easily obtained from tracking results. The a priori DOA requires us to pay close attention to the high possibility of where the DOA will appear; then, a weight according to the prior probability distribution of DOA is added to each direction, which leads the sensing matrix of DOA estimation to be near low-rank. Thus, according to the low-rank matrix approximation theory, an optimal low-rank approximate matrix is obtained and an algorithm is proposed to select the elements of the original array according to right singular vectors of the approximate matrix. After that, the impacts of different weights are analyzed, and a mixed weight is presented which has flexibility for common use. Finally, a number of numerical simulations are carried out, and the results verify the effectiveness of the proposed methods.

A Multi-Node Detection Algorithm Based on Serial and Threshold in Intelligent Sensor Networks.

With the continuous progress of science and technology, intelligent wireless sensor network (IWSN) communication has become indispensable in its role in production and life because of its convenient network settings and flexible use. However, with the widespread availability of intelligent wireless sensor networks, the use of many wireless sensor nodes constitutes a multi-node wireless communication system, which turns the accuracy and low complexity of multi-node detection in sensor networks into a problem. Although the traditional algorithm has excellent performance, it cannot give consideration to both accuracy and complexity. Therefore, a maximum logarithm message passing algorithm based on serial and threshold (S-T-Max-log-MPA) for multi-mode detection in IWSN is proposed in this paper. In this algorithm, the threshold is used to determine the necessary conditions of sensor node stability first, and then the sensor node information updating is integrated into the resource node information updating, so that the system can maintain good accuracy, performance, and change the situation of poor system accuracy at low threshold. Compared with the traditional algorithm, the proposed algorithm significantly changes the algorithm complexity reduction rate of the system multi-node detection. Simulation results show that the algorithm has a good balance between accuracy and complexity reduction rate.

A Threshold-Based Max-log-MPA Low Complexity Multiuser Detection Algorithm.

Sparse Code Multiple Access (SCMA) technology is a new multiple access scheme based on non-orthogonal spread spectrum technology, which was proposed by Huawei in 2014. In the algorithm application of this technology, the original Message Passing Algorithm (MPA) has slow convergence speed and high algorithm complexity. The threshold-based MPA has a high Bit Error Ratio (BER) when the threshold is low. In the Maximum logarithm Message Passing Algorithm (Max-log-MPA), the approximation method is used, which will cause some messages to be lost and the detection performance to be poor. Therefore, in order to solve the above problems, a Threshold-Based Max-log-MPA (T-Max-log-MPA) low complexity multiuser detection algorithm is proposed in this paper. The Maximum logarithm (Max-log) algorithm is combined with threshold setting, and the stability of user nodes is considered as a necessary condition for decision in the algorithm. Before message updating, the user information nodes are judged whether the necessary conditions for the stability of the user node have been met, and then the threshold is determined. Only users who meet the threshold condition and pass the necessary condition of user node stability can be decoded in advance. In the whole process, the logarithm domain MPA algorithm is used to convert an exp operation and a multiplication operation into a maximum value and addition operation. The simulation results show that the proposed algorithm can effectively reduce the computational complexity while ensuring the BER, and with the increase of signal-to-noise ratio, the effect of the Computational Complexity Reduction Ratio (CCRR) is more obvious.

Joint Resource Optimization in Simultaneous Wireless Information and Power Transfer (SWIPT) Enabled Multi-Relay Internet of Things (IoT) System.

The internet of things (IoT) is becoming more indispensable in modern society as the further development and maturity of information technology progresses. However the exponential growth of IoT devices leads to severe energy consumption. As a technology with broad application prospects, simultaneous wireless information and power transfer (SWIPT) enables IoT devices to harvest energy from receiving radio frequency (RF) signals while ensuring information transmission. In this paper, we investigate the transmission rate optimization problem for a dual-hop multi-relay IoT system, where a decode-and-forward (DF) relay supports the SWIPT technique. We jointly optimize the resource including power and subcarrier allocation, to maximize the system transmission rate. The time-sharing strategy and Lagrange dual method are used to solve this optimization problem. Simulation results reveal that the proposed algorithm has a larger transmission rate than other benchmark algorithms when ensuring each relay has no additional energy supply. Specifically, the proposed algorithm improves the information transmission rate by 2.8%, 3.4% and 43% compared with other algorithms in the case of five relays when the source's power is equal to 0.5 W, respectively.

Multi-Target Joint Detection and Estimation Error Bound for the Sensor with Clutter and Missed Detection.

The error bound is a typical measure of the limiting performance of all filters for the given sensor measurement setting. This is of practical importance in guiding the design and management of sensors to improve target tracking performance. Within the random finite set (RFS) framework, an error bound for joint detection and estimation (JDE) of multiple targets using a single sensor with clutter and missed detection is developed by using multi-Bernoulli or Poisson approximation to multi-target Bayes recursion. Here, JDE refers to jointly estimating the number and states of targets from a sequence of sensor measurements. In order to obtain the results of this paper, all detectors and estimators are restricted to maximum a posteriori (MAP) detectors and unbiased estimators, and the second-order optimal sub-pattern assignment (OSPA) distance is used to measure the error metric between the true and estimated state sets. The simulation results show that clutter density and detection probability have significant impact on the error bound, and the effectiveness of the proposed bound is verified by indicating the performance limitations of the single-sensor probability hypothesis density (PHD) and cardinalized PHD (CPHD) filters for various clutter densities and detection probabilities.

Chromatin composition alterations and the critical role of MeCP2 for epigenetic silencing of progesterone receptor-B gene in endometrial cancers.

OBJECTIVE: To understand the epigenetic mechanism underlying the PR-B gene silencing in endometrial cancer (EC) cells, we compared the chromatin composition between transcriptionally active and silenced PR-B genes in EC cell lines and cancer tissues. METHODS: Chromatin Immunoprecipitation (ChIP) assay was performed to measure MBD occupancy and histone acetylation/methylation in transcriptionally active and silenced PR-B genes. PR-B-positive/-negative, as well as epigenetic inhibitor-treated/-untreated EC cells were used as study models. Real-time polymerase chain reaction (PCR) and Western blot analysis were applied to measure the mRNA and protein levels of PR-B, MBD, and histones. RESULTS: A close association among PR-B methylation, MBD binding and PR-B gene silencing was observed. Treatment with epigenetic inhibitors led to dynamic changes in the PR-B chromatin composition and gene expression. Increased H3/H4 acetylation and H3-K4 methylation, and decreased H3-K9 methylation were found to be associated with re-activation of silenced PR-B genes. MeCP2 knockdown resulted in a decreased MeCP2 binding to PR-B genes and an increased PR-B expression. ChIP analysis of MeCP2 binding to PR-B genes in the PR-B-positive/-negative EC samples confirmed the significant role of MeCP2 in PR-B silencing. CONCLUSION: PR-B gene expression is regulated by a concerted action of epigenetic factors including DNA methylation, MBD binding, and histone modifications. MeCP2 occupancy of PR-B genes plays a critical role in PR-B gene silencing. These findings enriched our knowledge of the epigenetic regulation of PR-B expression in EC, and suggested that the epigenetic re-activation of PR-B could be explored as a potential strategy to sensitize the PR-B-negative endometrial cancers to progestational therapy.

[Study on the inclusion compound of avermectin by infrared spectroscopy].

This study was designed to investigate the formation and effect of inclusion complex of Avermectin-beta-cyclodextrin based on the accommodation property of beta-cyclodextrin's molecular cavity. The inclusion complex of Averrnectin-beta-cyclodextrin was prepared using saturated solution method and high performance liquid chromatography (HPLC) was employed to determine its entraping efficiency. The formation of Avermectin-beta-cyclodextrin inclusion complex was also demonstrated by infrared spectroscopy(IR). The change of chemical structure produced by photocatalysis of Abamectin was analyzed and the effect of inclusion complex to strengthen the photolysis stability of Abamectin's chemical structure was studied. The results show that the entraping efficiency of the inclusion complex was 40. 5%. The IR analysis presents that the intermolecular hydrogen bond was formed in the Avermectin-beta-cyclodextrin inclusion complex, indicating the composition effect was different from physical mixture. The lactones structure of Avermectin Bla can be photodecomposed and disrupted. After decomposition, the infrared stretching vibration peak of C-O-C structure disappeared and the lactone bond was significantly broken. The lactones structure of avermectin Bla was covered by the inclusion molecular loci in beta-cyclodextrin after the formation of avermectin-beta-cyclodextrin inclusion complex, providing a good photophobic protection for C-O-C structure in the macrocyclic lactone structure of avermectin Bla and improving the photostability of avermectin Bla molecule. The innovation of this study is that the structure and the characters of the prepared avermectin-beta-cyclodextrin inclusion complex were analyzed using spectrum methods. This inclusion complex is expected to be the ideal intermediate in the construction of protective controlled release formulation of avermectin.

Source-free active domain adaptation for diabetic retinopathy grading based on ultra-wide-field fundus images.

Domain adaptation (DA) is commonly employed in diabetic retinopathy (DR) grading using unannotated fundus images, allowing knowledge transfer from labeled color fundus images. Existing DAs often struggle with domain disparities, hindering DR grading performance compared to clinical diagnosis. A source-free active domain adaptation method (SFADA), which generates features of color fundus images by noise, selects valuable ultra-wide-field (UWF) fundus images through local representation matching, and adapts models using DR lesion prototypes, is proposed to upgrade DR diagnostic accuracy. Importantly, SFADA enhances data security and patient privacy by excluding source domain data. It reduces image resolution and boosts model training speed by modeling DR grade relationships directly. Experiments show SFADA significantly improves DR grading performance, increasing accuracy by 20.90% and quadratic weighted kappa by 18.63% over baseline, reaching 85.36% and 92.38%, respectively. This suggests SFADA's promise for real clinical applications.

An ensemble deep learning diagnostic system for determining Clinical Activity Scores in thyroid-associated ophthalmopathy: integrating multi-view multimodal images from anterior segment slit-lamp photographs and facial images.

Background: Thyroid-associated ophthalmopathy (TAO) is the most prevalent autoimmune orbital condition, significantly impacting patients' appearance and quality of life. Early and accurate identification of active TAO along with timely treatment can enhance prognosis and reduce the occurrence of severe cases. Although the Clinical Activity Score (CAS) serves as an effective assessment system for TAO, it is susceptible to assessor experience bias. This study aimed to develop an ensemble deep learning system that combines anterior segment slit-lamp photographs of patients with facial images to simulate expert assessment of TAO. Method: The study included 156 patients with TAO who underwent detailed diagnosis and treatment at Shanxi Eye Hospital Affiliated to Shanxi Medical University from May 2020 to September 2023. Anterior segment slit-lamp photographs and facial images were used as different modalities and analyzed from multiple perspectives. Two ophthalmologists with more than 10 years of clinical experience independently determined the reference CAS for each image. An ensemble deep learning model based on the residual network was constructed under supervised learning to predict five key inflammatory signs (redness of the eyelids and conjunctiva, and swelling of the eyelids, conjunctiva, and caruncle or plica) associated with TAO, and to integrate these objective signs with two subjective symptoms (spontaneous retrobulbar pain and pain on attempted upward or downward gaze) in order to assess TAO activity. Results: The proposed model achieved 0.906 accuracy, 0.833 specificity, 0.906 precision, 0.906 recall, and 0.906 F1-score in active TAO diagnosis, demonstrating advanced performance in predicting CAS and TAO activity signs compared to conventional single-view unimodal approaches. The integration of multiple views and modalities, encompassing both anterior segment slit-lamp photographs and facial images, significantly improved the prediction accuracy of the model for TAO activity and CAS. Conclusion: The ensemble multi-view multimodal deep learning system developed in this study can more accurately assess the clinical activity of TAO than traditional methods that solely rely on facial images. This innovative approach is intended to enhance the efficiency of TAO activity assessment, providing a novel means for its comprehensive, early, and precise evaluation.

Relationships between parental responsive feeding and infant appetitive traits: The moderating role of infant temperament.

Introduction: Between the ages of 6 and 12 months is a crucial stage for children to develop appetitive self-regulation. Evidence suggests that a combination of parental responsive feeding and infant temperament (surgency, effortful control, negative affect) shapes infant appetitive traits (food approach, food avoidance). There is a need for research to explore these relationships, in order to provide guidance for the design of an effective intervention to improve appetitive traits. The objective of the current study was to explore the moderating role of infant temperament in the relationship between parental responsive feeding and infant appetitive traits. Methods: A total of 616 questionnaires, measuring parental responsive feeding, infant appetitive traits, and infant temperament, were collected from parents with infants aged 6-12 months. Results: Results revealed that responsive feeding was associated with both food approach and food avoidance. Furthermore, only lower levels of surgency significantly moderated the relationship between responsive feeding and food approach, while responsive feeding was associated with food avoidance irrespective of infant temperament. Discussion: These findings suggest that a strategy embedding responsive feeding interventions should be adopted to reduce infant food avoidance and low-surgent infant food approach, and interventions that are tailored toward food approach for infants with effortful control, negative affect, or higher levels of surgency should be further sought.

Simultaneous removal of aqueous same ionic type heavy metals and dyes by a magnetic chitosan/polyethyleneimine embedded hydrophobic sodium alginate composite: Performance, interaction and mechanism.

Heavy metals and azo dyes caused huge harm to the aqueous system and human health. A magnetic chitosan/polyethyleneimine embedded hydrophobic sodium alginate composite (MCPS) was designed and prepared to simultaneously remove aqueous same ionic type heavy metals and azo dyes. In mono-polluted system, the optimal pH for Cr(VI), MO (methyl orange), Cu(Ⅱ) and MB (methylene blue) were 3, 2, 6 and 12 with a saturated adsorption capacity of 87.53, 66.41, 351.03 and 286.54 mg/g, respectively. Pseudo-second-order was suitable to describe the adsorption kinetics of them and the adsorption isotherms were more consistent with the Langmuir isotherm model being a spontaneous, endothermic, and entropy-increasing process. In binary-polluted system, MCPS possessed simultaneous adsorption for Cr (Ⅵ)-MO and Cu(Ⅱ)-MB pollutants at their optimal pH, in addition, whether in anionic or cationic solution, the removal of heavy metals were promoted with the add of azo dyes but the removal of azo dyes were suppressed with the add of heavy metals. Both Cr (Ⅵ)-MO and Cu(Ⅱ)-MB pollutants could be effectively adsorbed and desorbed from MCPS by changing the pH of the aqueous solution to realize recyclability. Lastly, removal mechanism was revealed in detail by FT-IR, EDS and XPS.

A Microwave Pressure Sensor Loaded with Complementary Split Ring Resonator for High-Temperature Applications.

A passive substrate integrated waveguide (SIW) sensor based on the complementary split ring resonator (CSRR) is presented for pressure detection in high-temperature environments. The sensor pressure sensing mechanism is described through circuit analysis and the electromagnetic coupling principle. The pressure sensor is modeled in high frequency structure simulator (HFSS), designed through parameter optimization. According to the optimized parameters, the sensor was customized and fabricated on a high temperature co-fired ceramic (HTCC) substrate using the three-dimensional co-fired technology and screen-printing technology. The pressure sensor was tested in the high-temperature pressure furnace and can work stably in the ambient environment of 25-500 °C and 10-300 kPa. The pressure sensitivity is 139.77 kHz/kPa at 25 °C, and with increasing temperature, the sensitivity increases to 191.97 kHz/kPa at 500 °C. The temperature compensation algorithm is proposed to achieve accurate acquisition of pressure signals in a high-temperature environment.

Comparative study on comprehensive quality of Xinhui chenpi by two main plant propagation techniques.

Xinhui chenpi (XHCP), the sun-dried peel of the mandarin orange, Citrus reticulata "Chachi," is the most famous crude drug, as well as a traditional seasoning in Chinese cooking. The main cultivation methods of XHCP are cutting and grafting, but it is generally considered that the quality of XHCP after cutting is superior to that obtained from plants propagated by graftings, which had a negative impact on the marketing of the finished product. In our study, a total of 25 samples of XHCP obtained from plants cultivated by either traditional methods (i.e., from cuttings) or by grafting were collected to compare the contents of four types of metabolites (essential oils, flavonoids, synephrine, and total polysaccharides) as well as antioxidant activity. The results revealed that the quality of XHCP did not decline after cutting, and marked individual differences between XHCP samples, even when prepared from plants grown in the same way. In general, grafting had no significant effect on the most essential oils components, total polysaccharides, synephrine, total flavonoids, total polymethoxylated flavones, hesperidin, nobiletin, tangeretin content, and antioxidant activity. Nevertheless, five volatile compounds can be used as potential chemical markers (p < 0.05) to distinguish between cutting XHCP and grafted XHCP, while four volatile compounds showed high content in grafted XHCP. Our study is expected to provide a theoretical basis for XHCP breeding and cultivation, and thereby further standardize the market of XHCP.

Preparation and characterization of Schiff-base modified Fe3O4 hybrid material and its selective adsorption for aqueous Hg2.

A Fe3O4 hybrid material (Fe3O4@SiO2-S2) modified by Schiff-base was prepared by grafting methyl acrylate (MA), ethylenediamine (EDA), and salicylaldehyde (SA) to the prepared magnetic hybrid material (Fe3O4@SiO2-NH2) successively; what's more, the structure was characterized by FTIR, XRD, SEM, TEM, and VSM. The results showed that the Fe3O4@SiO2-S2 has an obvious core-shell structure and a saturation magnetization of 45.9 emu/g. Study on the adsorption of aqueous heavy metal ions showed that Fe3O4@SiO2-S2 posed selective adsorption for Hg2+ with the saturated adsorption capacity of 362 mg/g (1.12 mmol/g), which was superior to Fe3O4@SiO2-NH2, Fe3O4@SiO2-HO-S, and other adsorbents, at the condition of pH = 6, 45℃, the adsorption capacity remained 89% after 5 cycles of adsorption-desorption; what is more, adsorption equilibrium was reached at about 300 min, and the adsorption isotherm conformed to the Langmuir isotherm adsorption model; in addition, pseudo-second-order model could be well described the adsorption kinetic process of Fe3O4@SiO2-S2 to Hg2+. The adsorption mechanism demonstrated that the N atoms of Schiff-base were mainly contributed to the adsorption of Hg2+; what is more, the N atom of tertiary amine and the O atoms of hydroxy and carbonyl also help to the adsorption of Hg2+.

Multi-homed abnormal behavior detection algorithm based on fuzzy particle swarm cluster in user and entity behavior analytics.

User and entity behavior analytics (UEBA) is an anomaly detection technique that identifies potential threat events in the enterprise's internal threat analysis and external intrusion detection. One limitation of existing methods in UEBA is that many algorithms use deterministic algorithms only for one category labeling and only compare with other samples within this category. In order to improve the efficiency of potential threat identification, we propose a model to detect multi-homed abnormal behavior based on fuzzy particle swarm clustering. Using the behavior frequency-inverse entities frequency (BF-IEF) technology, the method of measuring the similarity of entity and user behavior is optimized. To improve the iterative speed of the fuzzy clustering algorithm, the particle swarm is introduced into the search process of the category centroid. The entity's nearest neighbor relative anomaly factor (NNRAF) in multiple fuzzy categories is calculated according to the category membership matrix, and it is combined with boxplot to detect outliers. Our model solves the problem that the sample in UEBA is evaluated only in one certain class, and the characteristics of the particle swarm optimization algorithm can avoid clustering results falling into local optimal. The results show that compared with the traditional UEBA approach, the abnormal behavior detection ability of the new method is significantly improved, which can improve the ability of information systems to resist unknown threats in practical applications. In the experiment, the accuracy rate, accuracy rate, recall rate, and F1 score of the new method reach 0.92, 0.96, 0.90, and 0.93 respectively, which is significantly better than the traditional abnormal detections.

Neuroprotective potential of nuclear factor erythroid 2-related factor 2 (Nrf2)/antioxidant response element signaling modulator cucurbitacin I upon glucose and oxygen deprivation/reperfusion (OGD/RP).

This study aimed to investigate the inhibitory effect and mechanism of Cucurbitacin I (Cu I) on apoptosis, oxidative stress, and mitophagy in PC12 cells with glucose and oxygen deprivation/reperfusion (OGD/RP) injury. OGD/RP cell injury model was established by gas anoxic cell incubator and glucose-free medium. The cells were divided into the control group, OGD/RP group, OGD/RP + Cu I group, and OGD/RP + Cu I + 2 µM nuclear factor erythroid 2-related factor 2 (Nrf2) inhibitor ML385 group. The results showed that apoptotic rate and reactive oxygen species (ROS) production were significantly increased in OGD/RP group, which were reversed by Cu I pretreatment. Meanwhile, western blot analysis proved that Cu I inhibited OGD/RP-induced mitophagy, manifested as the decreased expression of PTEN-induced kinase 1 (PINK1) and parkin RBR E3 ubiquitin-protein ligase (Parkin), and light chain 3 (LC3) Ⅱ∕LC3 I, as well as the increased expression of P62. Furthermore, immunofluorescence (IF) staining showed that Cu I reduced the co-localized puncta of LC3 with TOM20 in OGD/RP-induced PC12 cells. Similarly, transmission electron microscope finding is consistent with the IF results. Mechanically, after Cu I and OGD/RP treatments, nuclear Nrf2 expression and the levels of downstream target genes were significantly upregulated compared with OGD/RP alone treatment. Nrf2 inhibition reversed the protective effects of Cu I on OGD/RP-induced injury in PC12 cells. The present study provides evidence of the neuroprotective effect of Cu I unraveling its potential as a potential therapeutic candidate for the treatment of ischemic stroke.