On the ICPCICPC-property of finite subgroups

Let $G$ be a finite group and $A$ be a subgroup of $G$. Then $A$ is called a $p$-$CAP$-subgroup of $G$, if $A$ covers or avoids every $pd$-chief factor of $G$. A subgroup $H$ of $G$ is said to be an $ICPC$-subgroup of $G$, if $H \cap [H,G] \leq H_{pcG}$, where $H_{pcG}$ is a $p$-$CAP$-subgroup of $G$ contained in $H$. In this paper, we investigate the structure of $G$ under the assumption that certain subgroups are $ICPC$-subgroups of $G$, and characterization of $p$-nilpotency and other results are obtained

Retention forestry amplifies microclimate buffering in boreal forests

Retention forestry is increasingly adopted as an alternative to clearcutting practices and involves retaining structural and compositional complexity (e.g., living and dead trees) from preharvest to postharvest. Past studies have examined the role of retention forestry in supporting various ecosystem functions and biodiversity, whilst its microclimate buffering capacity has been largely neglected. We investigated the microclimates and the underlying mechanisms of retention forests relative to clearcuts and old forests in a boreal forest landscape in central Sweden. We found that both air temperature and vapour pressure deficit (VPD) differed significantly between the forest types. Old forests consistently exhibited the most buffered forest microclimates, followed by retention forests, while clearcuts displayed the lowest. Basal area and canopy cover were identified as the key determinants influencing air temperature and VPD across the forest types. Retention practices can also impact a stand’s microclimates. Specifically, maintaining diverse tree species had the potential to lower the stand’s maximum temperature, given its positive association with canopy cover. Large volumes of lying deadwood were found to be negatively correlated with both basal area and canopy cover, likely contributing to increased maximum temperatures. Furthermore, standing deadwood directly lowered the maximum temperature within forest stands. Finally, edge effects were observed in the retention forests, with south-facing edges experiencing significantly higher maximum temperature and VPD compared to north-facing edges and forest interiors. These south-facing edge effects were positively associated with the difference in lying deadwood volumes between forest edges and interiors. Our findings support the positive influence of retention practices on a stand’s microclimate buffering, achieved through preserving diverse tree species, standing deadwood, and implementing measures to prevent severe wind-induced tree mortality, particularly in south-facing edges (e.g. creating southfacing buffer zones). Forest managers and policy makers can utilize these results to minimize the climate-change impacts on below-canopy biodiversity and functioning

Electronic structure and photoexcitation dynamics of chemisorbed alkali atoms induced resonances

We investigate the electronic structure and photoexcitation dynamics of alkali atoms (Rb and Cs) chemisorbed on Ru(0001) and Cu(111) surfaces by angle and time-resolved multi-photon photoemission (mPP) spectroscopy. Although the electronic structure of alkali atoms on no- ble surfaces has been studied, the development of mPP methods, combined with wavelength tunable femtosecond laser excitation, provides more incisive tools for exploration of alkali chemisorption induced electronic resonances and probing of electron relaxation dynamics. On Ru(0001), three-photon photoemission (3PP) spectroscopic features due to the σ- and π-resonances arising from the ns and np states of free alkali atoms are observed at ∼2 and ∼1 eV below the vacuum level in the zero coverage limit, respectively. As the alkali coverage is increased to 0.02 monolayer, the resonances are stabilized by formation of a surface dipole layer and form dispersive bands with nearly free-electron mass. Density functional theory calculations confirm the band formation through substrate-mediated interaction involving hybridization with the unoccupied d-bands. Time-resolved measurements provide the experimental measurements of phase and population decay in the 3PP process via σ- and π-resonances; simulations by solving the four-energy level optical Bloch equations quantify the phase and population relaxation times. By contrast, on Cu(111) we observe clear signatures of Cs and Rb alkali atom-localized electronic states in 3PP spectra. The angular distributions reflect the non-dispersive σ and π symmetries of the alkali atom localized states. Due to the high dispersion of Shockley surface state (SS) of Cu(111), the resonant two-photon transition is driven from SS to π-resonance under visible light. Time-resolved measurements and corresponding Fourier transforms (FT) with respect to time describe the phase and population relaxation dynamics. In the case of the σ-resonance with hν=1.92 eV, the interferometric measurements contain extra frequency components at fractions of the laser frequency, which we attribute to multielectron (ME) dynamics. Two-dimensional electronic spectroscopy shows that the photoexcitation creates coherent polarization components outside of the excitation laser bandwidth, through Coulomb interaction induced decay of an electron excited from the SS to a two-photon virtual state decaying into one electron in the -resonance and the other excited from SS to the Fermi level

Hydrocarbon accumulation model based on threshold combination control and favorable zone prediction for the lower Enping Formation, Southern Lufeng sag

Deep complex oil and gas reservoirs are the future directions of oil and gas exploration. The exploration potential of Paleocene deposits in the Lufeng sag is enormous. However, due to the greater burial depth and complex oil and gas accumulation conditions of the Paleocene, few large-scale reservoirs have been discovered and the next exploration strategy is unclear. In this study, based on the Paleocene geological data of the Southern Lufeng sag, a model of hydrocarbon accumulation based on functional element control is constructed using geostatistical and numerical simulation techniques. The hydrocarbon accumulation elements, thresholds, boundaries and scopes are clarified, and the favorable zones of hydrocarbon accumulation of the lower Enping Formation are predicted using the model of hydrocarbon accumulation based on threshold combination control. The results indicate that the source rock, reservoir, caprock, and low-potential area are the four functional elements controlling hydrocarbon accumulation. Since there are three types of low-potential zones, a total of six accumulation elements are considered to control hydrocarbon accumulation, and the corresponding hydrocarbon accumulation control thresholds are determined by the model of hydrocarbon accumulation according to the controlling effects of these accumulation elements. The predicted Type I favorable zones are located in the eastern part of Lufeng 13 east sub-sag and the northern and southern parts of Lufeng 7 sub-sag; Type II favorable zones are located in the western part and around the Lufeng 13 east sub-sag; Type III favorable zones are adjacent to Type II favorable zones. The hydrocarbon shows are all located in the overlapping zone of five or more accumulation elements.Cited as: Zhang, L., Pang, X., Pang, H., Huo, X., Ma, K., Huang, S. Hydrocarbon accumulation model based on threshold combination control and favorable zone prediction for the lower Enping Formation, Southern Lufeng sag. Advances in Geo-Energy Research, 2022, 6(5): 438-450. https://doi.org/10.46690/ager.2022.05.0

Research progress of cancer cell membrane coated nanoparticles for the diagnosis and therapy of breast cancer

Nanoparticles (NPs) disguised in the cell membrane are a new type of biomimetic platform. Due to their ability to simulate the unique biological functions of membrane-derived cells, they have become one of the hotspots of research at home and abroad. The tumor-specific antigen antibody carried by breast cancer cell membranes can modify nanoparticles to have homologous tumor targeting. Therefore, nanoparticles wrapped in cancer cell membranes have been widely used in research on the diagnosis and treatment of breast cancer. This article reviews the current situation, prospects, advantages and limitations of nanoparticles modified by cancer cell membranes in the treatment and diagnosis of breast cancer

Attribute-based encryption for cloud computing access control: A survey

National Research Foundation (NRF) Singapore; AXA Research Fun

SIMC 2.0: Improved Secure ML Inference Against Malicious Clients

In this paper, we study the problem of secure ML inference against a malicious client and a semi-trusted server such that the client only learns the inference output while the server learns nothing. This problem is first formulated by Lehmkuhl \textit{et al.} with a solution (MUSE, Usenix Security'21), whose performance is then substantially improved by Chandran et al.'s work (SIMC, USENIX Security'22). However, there still exists a nontrivial gap in these efforts towards practicality, giving the challenges of overhead reduction and secure inference acceleration in an all-round way. We propose SIMC 2.0, which complies with the underlying structure of SIMC, but significantly optimizes both the linear and non-linear layers of the model. Specifically, (1) we design a new coding method for homomorphic parallel computation between matrices and vectors. It is custom-built through the insight into the complementarity between cryptographic primitives in SIMC. As a result, it can minimize the number of rotation operations incurred in the calculation process, which is very computationally expensive compared to other homomorphic operations e.g., addition, multiplication). (2) We reduce the size of the garbled circuit (GC) (used to calculate nonlinear activation functions, e.g., ReLU) in SIMC by about two thirds. Then, we design an alternative lightweight protocol to perform tasks that are originally allocated to the expensive GCs. Compared with SIMC, our experiments show that SIMC 2.0 achieves a significant speedup by up to $17.4\times$ for linear layer computation, and at least $1.3\times$ reduction of both the computation and communication overheads in the implementation of non-linear layers under different data dimensions. Meanwhile, SIMC 2.0 demonstrates an encouraging runtime boost by $2.3\sim 4.3\times$ over SIMC on different state-of-the-art ML models

Establishment of a 7-gene prognostic signature based on oxidative stress genes for predicting chemotherapy resistance in pancreatic cancer

Background: Oxidative stress is involved in regulating various biological processes in human cancers. However, the effect of oxidative stress on pancreatic adenocarcinoma (PAAD) remained unclear.Methods: Pancreatic cancer expression profiles from TCGA were downloaded. Consensus ClusterPlus helped classify molecular subtypes based on PAAD prognosis-associated oxidative stress genes. Limma package filtered differentially expressed genes (DEGs) between subtypes. A multi-gene risk model was developed using Lease absolute shrinkage and selection operator (Lasso)-Cox analysis. A nomogram was built based on risk score and distinct clinical features.Results: Consistent clustering identified 3 stable molecular subtypes (C1, C2, C3) based on oxidative stress-associated genes. Particularly, C3 had the optimal prognosis with the greatest mutation frequency, activate cell cycle pathway in an immunosuppressed status. Lasso and univariate cox regression analysis selected 7 oxidative stress phenotype-associated key genes, based on which we constructed a robust prognostic risk model independent of clinicopathological features with stable predictive performance in independent datasets. High-risk group was found to be more sensitive to small molecule chemotherapeutic drugs including Gemcitabine, Cisplatin, Erlotinib and Dasatinib. The 6 of 7 genes expressions were significantly associated with methylation. Survival prediction and prognostic model was further improved through a decision tree model by combining clinicopathological features with RiskScore.Conclusion: The risk model containing seven oxidative stress-related genes may have a greater potential to assist clinical treatment decision-making and prognosis determination