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Conventional brute-force attacks can now be detected and identified based on statistical analysis of logs and traffic data. However, they fail to detect low-frequency and distributed brute-force attack behaviors. To address different attack methods, new detection techniques have emerged. This study compares various machine learning algorithms and selects two methods, namely the clustering algorithm k-means and bdscan, as well as the decision tree algorithm for data learning. In one approach, normal user login data is integrated with enterprise email log data. The data is first statistically analyzed and filtered, followed by quantifying data characteristics using information entropy. Subsequently, machine learning algorithms are employed for classification, and the results are visualized for display. In another approach, labeled raw data is used to train a model using the decision tree algorithm. By comparing the two analysis results, a more accurate model can be obtained. These analytical methods can help enterprises strengthen email security and defend against low-frequency and distributed brute-force attacks. [ABSTRACT FROM AUTHOR]

Simple Summary: In recent years, the incidence of cancer has been steadily increasing, necessitating a more urgent and in-depth understanding and exploration of this disease. During the process of literature review, we have discovered that the novel protein-coding gene, cartilage intermediate layer protein 2, has been partially associated with colorectal cancer in several studies. However, its role in other cancers remains elusive. Therefore, this study aims to explore the function and mechanism of cartilage intermediate layer protein 2 in pan-cancer. Our findings will enhance the understanding of the role of cartilage intermediate layer protein 2 in pan-cancer tumorigenesis and progression, especially in pancreatic cancer. This research could potentially establish cartilage intermediate layer protein 2 as a promising prognostic biomarker and immunotherapy target for cancers. The elucidation of its significance in pan-cancer will contribute to the development of more effective therapeutic strategies. Cartilage intermediate layer protein 2 (CILP2) facilitates interactions between matrix components in cartilage and has emerged as a potential prognostic biomarker for cancer. This study aimed to investigate the function and mechanisms of CILP2 in pan-cancer. We evaluated the pan-cancer expression, methylation, and mutation data of CILP2 for its clinical prognostic value. Additionally, we explored the immunological characteristics of CILP2 in pan-cancer and then focused specifically on pancreatic ductal adenocarcinoma (PAAD). The subtype analysis of PAAD identified subtype-specific expression and immunological characteristics. Finally, in vitro and in vivo experiments assessed the impact of CILP2 on pancreatic cancer progression. CILP2 exhibited high expression in most malignancies, with significant heterogeneity in epigenetic modifications across multiple cancer types. The abnormal methylation and copy number variations in CILP2 were correlated with poor prognoses. Upregulated CILP2 was associated with TGFB/TGFBR1 and more malignant subtypes. CILP2 exhibited a negative correlation with immune checkpoints in PAAD, suggesting potential for immunotherapy. CILP2 activated the AKT pathway, and it increased proliferation, invasion, migration, and epithelial–mesenchymal transition (EMT) in pancreatic cancer. We demonstrated that CILP2 significantly contributes to pancreatic cancer progression. It serves as a prognostic biomarker and a potential target for immunotherapy. [ABSTRACT FROM AUTHOR]

Biochar adsorption has emerged as a favorable and environmentally friendly approach for removing metals such as chromium (Cr) from wastewater. However, the use of pristine biochar (PBC) is limited due to its finite adsorptive capacity, selectivity, and potential for secondary pollution. In this study, a novel bifunctionalized magnetic biochar (BMBC) was fabricated by incorporating cystamine as a ligand and glutaraldehyde as a crosslinker into alkali-treated magnetic biochar (MBC). This chemical modification introduced numerous amino groups and disulfide bonds onto the surfaces of BMBC. The biochar adsorbents' surface morphologies, crystal structures, and texture properties were characterized using SEM, XRD, and N2 adsorption-desorption techniques. The specific surface area was determined using the BET method. Furthermore, the surface functional groups and elemental compositions before and after adsorption were analyzed using FTIR and XPS, respectively. The results demonstrated higher Cr(VI) removal efficacy of BMBC (100%) than MBC (72.37%) and PBC (61.42%). Optimal conditions for Cr(VI) removal were observed at a solution pH of 2, a temperature of 50 °C, a reaction time of around 1440 min, and an initial adsorbate concentration of 300 mg/L. The sorption process followed a chemical mechanism and was controlled by monolayer adsorption, with a maximum adsorption capacity of 66.10 mg/g at 50 °C and a pH of 2, as indicated by the larger fitting values of the pseudo–second-order and Langmuir models. The positive ∆Ho and ∆So values and negative ∆G0 values suggested a spontaneous and endothermic Cr(VI) adsorption process with high randomness at the solid/liquid interface. The removal of Cr(VI) was attributed to the reduction of Cr(VI) into Cr(III) facilitated by the introduced amino acids, sulfur, and Fe(II), electrostatic interaction between Cr(VI) in the solution and positive charges on the adsorbent surface, and complexation with functional groups. The presence of co-existing cations such as Cu(II), Cd(II), Mn(II), and K(I) had little effect on Cr(VI) removal efficiency. At the same time, the co-existence of anions of Cl−, NO3−, SO42−, and HPO42− resulted in a 7.58% decrease in the Cr(VI) removal rate. After five consecutive adsorption/desorption cycles, BMBC maintained a high Cr(VI) removal rate of 61.12%. Overall, this novel BMBC derived from rice straw shows great promise as a biosorbent for treating Cr(VI) in wastewater. [ABSTRACT FROM AUTHOR]

The ecological restoration of territorial space emphasizes the synergy between ecology and social development. On this basis, we used landscape index analysis methods to explore the spatiotemporal evolution of landscape patterns in urban areas on a district scale. Then, we used multiple regression analysis to explore the driving factors behind this evolution. The results showed the following: (1) Landscape compositions have changed significantly. The growth rate of construction land in the main districts was about three times that in the urban area. (2) There were differences in the characteristics of landscape pattern evolution. Arable land is becoming more fragmented as construction land expands outward. The shapes of public green spaces, arable land, and woodlands tend to be simple and regular. The degree of both urban sprawl and agglomeration decreased in the urban area and the main districts. Meanwhile, landscape separation first decreased and then increased, and landscape diversity increased. (3) Population growth, industrial development, changes in industrial structure, and real estate development are the main driving factors of landscape pattern evolution. Based on this, this study puts forward some suggestions for landscape pattern optimization, which is significant for ecological restoration planning and promotion. [ABSTRACT FROM AUTHOR]

Hedged public-key encryption (HPKE), introduced by Bellare et al. (ASIACRYPT 2009), provides useful security when the per-message randomness fails to be uniform due to faulty implementations or adversarial actions. The HPKE scheme achieves IND-CPA (chosen plaintext attack) security when the randomness they used is of high quality, but, when the randomness is poor quality, rather than breaking completely, it achieves a weaker but a useful notion of security called IND-CDA (chosen distribution attack) as long as the message and randomness together have sufficient min-entropy. However, little research on HPKE in the presence of key leakage was done. In this paper, we study HPKE featuring key leakage-resilience and formulate appropriate security notion for key leakage-resilient HPKE. We work in the continual key leakage model where the secret key is refreshed periodically and an adversary can learn arbitrary but bounded leakage on the secret key between the updates. We present two generic constructions of continual leakage-resilient HPKE in the standard model by using a continual leakage-resilient all-but-one lossy trapdoor function. Finally, we give an instantiation of leakage-resilient HPKE under the linear assumption in bilinear groups. [ABSTRACT FROM AUTHOR]

Air pollution is one of the major environmental risks threatening human health, diesel exhaust particulate matter (DEPM) is an important source of urban air pollution, and oral ingestion is the primary route of exposure to atmospheric particulate matter. This study examined the bioaccessibility of Cr, Fe, and Zn in DEPM within simulated saliva fluids through in vitro experiments, interactions between the particles and mucins, and the mechanisms underlying the oxidative damage they cause. The results indicated that the interaction between DEPM and mucins altered the dispersibility, surface charge, and wettability of the particles, leading to increased release of heavy metals. Protein adsorption experiments and characterizations revealed that the adsorption of mucin by the particles resulted in a complexation reaction between the metals in the DEPM and the mucins, accompanied by fluorescence quenching of the protein. In addition, free radical assays and correlation analyses revealed that environmentally persistent free radicals generated by DEPM induce the production of reactive oxygen species (O 2 ·- , HOOH, and·OH), which damage the secondary structure of mucins and increase the risk of oral diseases. Our study is the first to reveal the interaction between DEPM and mucins in saliva, elucidating the mechanisms of DEPM-induced oxidative damage. This is significant for understanding the oral health risks posed by the ingestion of atmospheric particulate matter., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)