Miracle-dz/UniFAR-FTUs huggingface dataset:
Phellinus baumii Polyphenol: A Potential Therapeutic Candidate against Lung Cancer Cells

Phellinus baumii, a fungus that grows on mulberry trees and is used in traditional Chinese medicine, exerts therapeutic effects against various diseases, including cancer. Polyphenols, generally considered to be antioxidants, have antitumor and proapoptotic effects. In this study, we identified the composition of Phellinus baumii polyphenol (PBP) and characterized its 17 chemical components by UPLC–ESI–QTOF–MS. Furthermore, to clarify the potential mechanism of PBP against Lung Cancer Cells, network pharmacology and experimental verification were combined. Molecular docking elucidated the binding conformation and mechanism of the primary active components (Osmundacetone and hispidin) to the core targets CASP3, PARP1 and TP53. In addition, potential molecular mechanisms of PBP predicted by network pharmacology analysis were validated in vitro. PBP significantly inhibited the human lung cancer A549 cells and showed typical apoptotic characteristics, without significant cytotoxicity to normal human embryonic kidney (HEK293) cells. Analysis using flow cytometry and western blot indicated that PBP caused apoptosis, cell cycle arrest, reactive oxygen species (ROS) accumulation, and mitochondrial membrane potential (MMP) depression in A549 cells to exercise its antitumor effects. These results reveal that PBP has great potential for use as an active ingredient for antitumor therapy.
Kalman filtering for continuous-time systems with multiple delayed measurements

The paper focuses on the Kalman filtering problem for linear continuous-time systems with multiple delayed measurements. An explicit and simpler solution to the Kalman filtering problem is presented for such systems. The approach applied is the reorganised innovation analysis. The obtained Kalman filter is given in terms of Riccati differential equations. A numerical example is given to demonstrate the proposed approach.
Driver Intent-Based Intersection Autonomous Driving Collision Avoidance Reinforcement Learning Algorithm

With the rapid development of artificial intelligent technology, the deep learning method is widely applied to predict human driving intentions due to its relative accuracy of prediction, which is one of critical links for security guarantee in the distributed, mixed driving scenario. In order to sense the intention of human-driven vehicles and reduce the self-driving collision avoidance rate, an improved intention prediction method for human-driving vehicles based on unsupervised, deep inverse reinforcement learning is proposed. Firstly, a contrast discriminator module was proposed to extract richer features. Then, the residual module was created to overcome the drawbacks of gradient disappearance and network degradation with the increase in network layers. Furthermore, the dropout layer was generated to prevent the over-fitting phenomenon in the whole training process of the GRU network, so as to improve the generalization ability of the network model. Finally, abundant experiments were conducted on datasets to evaluate our proposed method. The pass rate of self-driving vehicles with conservative driver probabilities of p = 0.25, p = 0.4, and p = 0.6 improved by a maximum of 8%, 10%, and 3%, compared with the classical method LSTM and VAE + RNN. It indicates that the prediction results of our proposed method fit more with the basic structure of the given traffic scenario in a long-term prediction range, which verifies the effectiveness of our proposed method.
Experimental determination of the mechanical impedance of atomic force microscopy cantilevers in fluids up to 70 kHz

The high-frequency dynamical response of cantilevers used in atomic force microscopy (AFM) to an external force is important for applications such as dynamic AFM modes and dynamic mechanical measurements on biological tissues. In this paper we present a novel method for experimentally determining the mechanical driving-point impedance of an AFM cantilever up to frequencies of at least 70 kHz. A frequency-independent, point force was achieved by applying an electric field between the cantilever and a sharpened steel electrode positioned near (10 μm) the tip of the cantilever. The velocity of the cantilever in response to the force was measured with a laser interferometer. The method was tested in air and in tetrachloromethane (CCl4), a nonpolar, nondissociating fluid. The results agree with theoretical predictions. In addition, the mechanical impedance of a cantilever near a flat surface was measured.
Pooling optimal combinations of energy thresholds in spectroscopic CT

Photon counting detectors used in spectroscopic CT are often based on small pixels and therefore offer only limited space to include energy discriminators and their associated counters in each pixel cell. For this reason, it is important to make efficient use of the available energy discriminators in order to achieve an optimized material contrast at a radiation dose as low as possible. Unfortunately, the complexity of evaluating every possible combination of energy thresholds, given a fixed number of counters, rapidly increases with the resolution at which this search is performed, and makes brute-force approaches to this problem infeasible. In this work, we introduce methods from machine learning, in particular sparse regression, to perform a feature selection to determine optimal combinations of energy thresholds. We will demonstrate how methods enforcing row-sparsity on a linear regression’s coefficient matrix can be applied to the multiple response problem in spectroscopic CT, i.e. the case in which a single set of energy thresholds is sought to simultaneously retrieve concentrations pertaining to a multitude of materials in an optimal way. These methods are applied to CT images experimentally obtained with a Medipix3RX detector operated in charge summing mode and with a CdTe sensor at a pixel pitch of 110μm. We show that the least absolute shrinkage and selection operator (lasso), generalized to the multiple response case, chooses four out of 20 possible threshold positions that allow discriminating PMMA, iodine and gadolinium in a contrast agent phantom at a higher accuracy than with equally spaced thresholds. Finally, we illustrate why it might be unwise to use a higher number of energy thresholds than absolutely necessary.
Virus-like Particles for TEM Regulation and Antitumor Therapy

Tumor development and metastasis are intimately associated with the tumor microenvironment (TME), and it is difficult for vector-restricted drugs to act on the TME for long-term cancer immunotherapy. Virus-like particles (VLPs) are nanocage structures self-assembled from nucleic acid free viral proteins. Most VLPs range from 20–200 nm in diameter and can naturally drain into lymph nodes to induce robust humoral immunity. As natural nucleic acid nanocarriers, their surfaces can also be genetically or chemically modified to achieve functions such as TME targeting. This review focuses on the design ideas of VLP as nanocarriers and the progress of their research in regulating TME.
In-silico analysis of WRKY Transcription Factors gene family in healthy and malformed stages of mango (Mangifera indica)

WRKY proteins play crucial roles in plant defense regulatory networks, development process and physiological programs including responses to several biotic and abiotic stresses. Evalutionary analysis revealed, WRKY genes were categorized into the four major groups. In developed phylogenetic tree, group-D contain highest number (15) of WRKY genes followed by group-B (10), group-A (7), and group-C (6). Several number of CREâ€™s were identified from mango transcriptome belonging to different categories like light responsiveness, hormone responsive, bioticstress responsive, biotic stress responsive, binding, plant development, transcription and circadian control. Among the10 stable genes observed in transcriptome, nine genes had negative Z-score indicating that these structures identifiedfor the proteins are reliable. Motif analysis indicated that the per cent occurrence of all the five motifs were higher in WRKY genes of malformed tissues compared to WRKY genes of healthy tissues. The uniquely identified CREâ€™s (Healthy stages: AC-II, GCC box, OBP; Malformed stages: Aux-RR-core, AC-I, 3-AF1 binding site, CAT-box, MNF1 and rbcS-CMA7a.), defense and stress responsiveness (TC-rich repeats) and fungal elicitor (Box-W1) related cis-regulatory elements will provide insight to solve the problem of mango malformation. The identified information regarding the WRKY Transcription Factor from mango transcriptome will serve as a valuable information for mango breeding against malformation.
The neutrophil-lymphocyte ratio to predict poor prognosis of critical acute myocardial infarction patients: a retrospective cohort study

Introduction Inflammation is closely related to adverse outcomes of acute myocardial infarction (AMI). This study aimed to evaluate whether neutrophil-lymphocyte ratio (NLR) can predict poor prognosis of critical AMI patients. Materials and methods We designed a retrospective cohort study and extracted AMI patients from the “Medical Information Mart for Intensive Care-III” database. The primary outcome was 1-year all-cause mortality. The secondary outcomes were 90-day and in-hospital all-cause mortalities, and acute kidney injury (AKI) incidence. The optimal cut-offs of NLR were picked by X-tile software according to the 1-year mortality and patient groups were created: low-NLR (< 4.8), high-NLR (4.8 - 21.1), and very high-NLR (> 21.1). Cox and modified Poisson regression models were used to evaluate the effect of NLR on outcomes in critically AMI patients. Results Finally, 782 critical AMI patients were enrolled in this study, and the 1-year mortality was 32% (249/782). The high- and very high-NLR groups had a higher incidence of outcomes than the low-NLR group (P < 0.05). The multivariate regression analyses found that the high- and very high-NLR groups had a higher risk of 1-year mortality (Hazard ratio (HR) = 1.59, 95% CI: 1.12 to 2.24, P = 0.009 and HR = 1.73, 95% CI: 1.09 to 2.73, P = 0.020), 90-day mortality (HR = 1.69, 95% CI: 1.13 to 2.54, P = 0.011 and HR = 1.90, 95% CI: 1.13 to 3.20, P = 0.016), in-hospital mortality (Relative risk (RR) = 1.77, 95% CI: 1.14 to 2.74, P = 0.010 and RR = 2.10, 95% CI: 1.23 to 3.58, P = 0.007), and AKI incidence (RR = 1.44, 95% CI: 1.06 to 1.95, P = 0.018 and RR = 1.34, 95% CI: 0.87 to 2.07, P = 0.180) compared with low-NLR group. NLR retained stable predictive ability in sensitivity analyses. Conclusion Baseline NLR is an independent risk factor for 1-year mortality, 90-day mortality, in-hospital mortality, and AKI incidence in AMI patients.
Potential Effect of DIMBOA (2,4-Dihydroxy-7-methoxy-1,4-benzoxazin-3-one) on Alleviating the Autotoxic Coumarin Stress in Alfalfa (Medicago sativa) Seedlings

The allelopathic theory has garnered considerable attention in the field of agricultural production for its efficient plant protection, rapid crop yield increase, and scientific establishment of the crop rotation system. To study the effects of the main maize allelochemical DIMBOA (2,4-Dihydroxy-7-methoxy-1,4-benzoxazin-3-one) on the growth and development of alfalfa under autotoxic coumarin stress, we treated alfalfa seedlings with DIMBOA under coumarin stress and non-stress conditions in this study. Results show that 0.0342 mM coumarin significantly inhibited alfalfa seed germination percentage(Gp), germination potential(GP), radicle length, germ length, seeding height, and simple viability index (SVI), with decreases of 37.29%, 59.91%, 7.60%, 30.90%, 13.27%, and 45.70%, respectively. An amount of 0.6 mM DIMBOA could promote alfalfa seed Gp, GP, radicle length, germ length, seeding height, dry fresh ratio, and SVI, with increases of 12.38%, 23.91%, 48.69%, 48.65%, 48.68%, 295.12%, and 67.17%, respectively. However, the addition of DIMBOA under conditions of coumarin stress could effectively alleviate coumarin effects on alfalfa seedlings. Coumarin + DIMBOA treatment for 24 h mainly decreased reactive oxygen species (ROSs) and malondialdehyde (MDA) as well as soluble protein and soluble sugar, increasing some antioxidant enzyme activities and antioxidant content to alleviate the oxidative damage of alfalfa caused by coumarin stress. Administration of treatment for 72 h significantly promoted the morphological development of alfalfa seeding roots. Administration of treatment for 96 h significantly enhanced the photosynthetic capacity of alfalfa seedlings. The results of principal component analysis demonstrated that chlorophyll b(Chl b)and net photosynthetic rate(Pn) were the key indicators for coumarin + DIMBOA treatment to promote photosynthesis in alfalfa seedlings. Additionally, root length, mean root diameter, and root volume were the key indicators of root growth and development. Coumarin + DIMBOA treatment primarily increased catalase(CAT), peroxidase (POD), and ascorbate peroxidase (APX) activity and antioxidants(ASA) while reducing MDA and superoxide anion radical(O2•−). This study strongly suggested that DIMBOA can effectively improve the tolerance of alfalfa seedlings to coumarin stress through a combination of effects on root morphology, photosynthesis, and physiological indicators.
Recyclable Nacre‐Like Aramid‐Mica Nanopapers with Enhanced Mechanical and Electrical Insulating Properties

The emerging aramid‐mica nanopapers, composed of aramid nanofibers (ANFs) and mica nanosheets (Mica), exhibit superiority in the field of electrical insulation compared with commercial aramid‐mica micropapers. Unfortunately, their mechanical and electrical insulating properties are still less than ideal due to insufficient control of their microstructures. Herein, it is presented that by integrating ANFs and Mica into nacre‐like aramid‐mica nanopapers with improved structural orderliness, densification, and interlayer interaction, simultaneously improved mechanical and electrical insulating properties are achieved. Their maximum tensile strength and breakdown strength reach ≈292 MPa and ≈176 kV mm−1, respectively, which are superior to those of the state‐of‐the‐art ANFs‐based nanopapers. Particularly, the aramid‐mica nanopapers show high resistance to high‐temperature (250–300 °C) and oil‐bath (100 °C) environments commonly involved in practical applications, and can be recycled many times, demonstrating their great potential as high‐performance sustainable electrical insulating papers to be applied in advanced electrical equipment.
Learning to Sense for Coded Diffraction Imaging

In this paper, we present a framework to learn illumination patterns to improve the quality of signal recovery for coded diffraction imaging. We use an alternating minimization-based phase retrieval method with a fixed number of iterations as the iterative method. We represent the iterative phase retrieval method as an unrolled network with a fixed number of layers where each layer of the network corresponds to a single step of iteration, and we minimize the recovery error by optimizing over the illumination patterns. Since the number of iterations/layers is fixed, the recovery has a fixed computational cost. Extensive experimental results on a variety of datasets demonstrate that our proposed method significantly improves the quality of image reconstruction at a fixed computational cost with illumination patterns learned only using a small number of training images.
Method for Correlating Discharge Coefficients of Film-Cooling Holes

A method for correlating the discharge coefficient of a 30-deg inclined, cylindrical film-cooling hole over a broad range of engine-like conditions is presented. The flow conditions considered are the pressure ratio across the hole (up to 2.25), the crossflow Mach number at the hole entry side (up to 0.6), and the crossflow Mach number at the hole exit side (up to 1.2). The effects of baseline hole flow as well as hole entry and exit crossflows on discharge coefficient were correlated independently of each other. Therefore, the discharge coefficient of any combination of pressure ratio, external Mach number, and internal Mach number flow case can be predicted. A comparison of predicted and measured discharge coefficients reveals the capability of the method proposed
A numerical and theoretical study of the first Hopf bifurcation in a cylinder wake

The first Hopf bifurcation of the infinite cylinder wake is analysed theoretically and by direct simulation. It is shown that a decomposition into a series of harmonics is a convenient theoretical and practical tool for this investigation. Two basic properties of the instability allowing the use and truncation of the series of harmonics are identified: the lock-in of frequencies in the flow and separation of the rapid timescale of the periodicity from the slow timescale of the non-periodic behaviour. The Landau model is investigated under weak assumptions allowing strong nonlinearities and transition to saturation of amplitudes. It is found to be rather well satisfied locally at a fixed position of the flow until saturation. It is shown, however, that no truncated expansion into a series of powers of amplitude can account correctly for this fact. The validity of the local Landau model is found to be related to the variation of the form of the unstable mode substantially slower than its amplification. Physically relevant characteristics of the Hopf bifurcation under the assumption of separation of three timescales – those of the periodicity, amplification and deformation of the mode – are suggested.
Determinants and Consequences of Green Investment in the Saudi Arabian Hotel Industry

Hotels in today’s business environment are no longer solely concerned with profit, but rather with profit, people, and the planet (3Ps). In corporate terms, green investment (GI) is regarded as a strategy that aims for maximum profit with minimal environmental impact. As a result, the current study primarily aims to empirically investigate the impact of internal and external drivers on GI adoption in Saudi Arabian eco-friendly hotels. Additionally, it explores to what extent GI affects eco-friendly hotels’ environmental, economic, and social performance. To achieve these objectives, a web-based questionnaire was developed and addressed to the senior manager/director in charge of environmental management in all four- and five-star eco-friendly hotels in Saudi Arabia. The total number of certified eco-friendly hotels in all regions of Saudi Arabia was 403. Only 298 forms were received and were valid for statistical analysis. A structural equation modeling (SEM) technique with maximum likelihood estimation was employed to test the study hypotheses. The findings of this study illustrate that GI is significantly positively affected by external as well as internal drivers. Adaptation to/mitigation of climate change was the highest perceived driver. Additionally, GI has a significant positive contribution to enhancing hotels’ environmental performance, increasing economic performance, and boosting social performance. Based on the study findings, eco-friendly hotel operators should consider GI in their strategic plans, as a corporate strategy aiming at maximizing profit and enhancing the quality of social life without harming the environment.
Multi‐view side information‐incorporated tensor completion

Tensor completion originates in numerous applications where data utilized are of high dimensions and gathered from multiple sources or views. Existing methods merely incorporate the structure information, ignoring the fact that ubiquitous side information may be beneficial to estimate the missing entries from a partially observed tensor. Inspired by this, we formulate a sparse and low‐rank tensor completion model named SLRMV. The ℓ0$$ {\ell}_0 $$ ‐norm instead of its relaxation is used in the objective function to constrain the sparseness of noise. The CP decomposition is used to decompose the high‐quality tensor, based on which the combination of Schatten p$$ p $$ ‐norm on each latent factor matrix is employed to characterize the low‐rank tensor structure with high computation efficiency. Diverse similarity matrices for the same factor matrix are regarded as multi‐view side information for guiding the tensor completion task. Although SLRMV is a nonconvex and discontinuous problem, the optimality analysis in terms of Karush‐Kuhn‐Tucker (KKT) conditions is accordingly proposed, based on which a hard‐thresholding based alternating direction method of multipliers (HT‐ADMM) is designed. Extensive experiments remarkably demonstrate the efficiency of SLRMV in tensor completion.
A gain modification form for Kalman filtering under state inequality constraints

This paper presents a method for dealing with Kalman filtering under particular classes of nonlinear state model and state inequality constraints. This method is based on a modification of the optimal Kalman gain in order to enforce the state constraints if necessary. The proposed method is applied to a nonlinear hydraulic system in order to highlight the efficiency of this method. Copyright © 2010 John Wiley & Sons, Ltd.
Impact of covid-19 on subspecialty training in obstetrics and gynaecology

Abstract The Covid-19 pandemic brought substantial changes in clinical practice in Obstetrics and Gynaecology (O and G). Redeployment of staff and restrictions in elective services raised training concerns. We sought to assess the impact on subspecialty training, to identify issues to help mitigate the impact. We conducted cross-sectional anonymous electronic surveys of UK subspecialty trainees at three time points: June 2020, February 2021, September 2021. Surveys were analysed by descriptive statistics and thematic analysis of free-text responses. Response rates ranged from 30% to 40%, with higher response rates from urogynaecology trainees. Up to 72% reported an impact on training, most notable in gynaecological subspecialties, and particularly urogynaecology, which persisted over time. More than a third anticipated needing extra time to complete training. This raises serious future workforce and patient care concerns. Clinical recovery should consider training needs as essential when re-establishing services. Subspecialty trainees may need additional time to achieve competencies required of future consultants. IMPACT STATEMENT What is already known on the subject? Covid-19 led to dramatic changes in clinical practice in Obstetrics and Gynaecology. Previous studies on training in O and G during the pandemic in the UK and internationally highlighted issues from redeployment, trainee absence, and changes in service provision, that had potential to severely impact training. What do the results of this study add? Subspecialty training in Obstetrics and Gynaecology has been affected by the pandemic. Urogynaecology was worst affected and continues to be affected over the course of the pandemic. What are the implications of these findings for clinical practice and/or further research? Covid-19 recovery plans need to incorporate training requirements. Extended training due to the pandemic may affect consultant workforce numbers and thus service provision in tertiary care.
Potential Power Management Efficiency Improvements in Desktop 3D Printers

Additive manufacturing, also known as 3D printing, has become a significant part of the market. It has received a lot of growth in the domestic R&D segment. They can be produced by large manufacturers or hand-assembled from available components. The main advantage of desktop 3D printers is their low price. But due to low-quality or improperly selected and tuned components, their main advantage is lost, due to an increase in energy costs. Based on the test data and by analyzing and summarizing data from various publications, measures were proposed to increase efficiency and reduce electricity consumption. As a result, a set of actions has been obtained to potentially increase the energy efficiency of 3D printing.