Miracle-dz/UniFAR-FTUs huggingface dataset:
Nanomedicines for high‑intensity focused ultrasound cancer treatment and theranostics (Review)

High-intensity focused ultrasound (HIFU) is a promising and representative non-invasive therapeutic method for treating cancer with a high degree of efficacy. This non-invasive method induces tumour cell necrosis by increasing the local temperature and mechanical pressure. However, the clinical application of HIFU is limited given its low penetration depth and the incidence of off-target side effects. With their promising structural adjustability and targeting ability, nanomedicines have been adopted to improve the ablative efficacy of HIFU in the treatment of cancer. By selectively changing the acoustic environment (tissue structure, density and blood supply) of tumour tissue, these nanomedicines may allow for lower HIFU doses and treatment duration, while additionally achieving a higher degree of efficacy. The use of nanomedicines may also enable cancer theranostics of HIFU, allowing for precise cancer therapeutics. The present review aimed to provide an overview of advances in nanomedicines for HIFU cancer treatment and theranostics, stating their current limitations and future perspectives.
Exponential smallness of inertia-gravity-wave generation at small Rossby number

Abstract This paper discusses some of the mechanisms whereby fast inertia–gravity waves can be generated spontaneously by slow, balanced atmospheric and oceanic flows. In the small Rossby number regime relevant to midlatitude dynamics, high-accuracy balanced models, which filter out inertia–gravity waves completely, can in principle describe the evolution of suitably initialized flows up to terms that are exponentially small in the Rossby number e, that is, of the form exp(−α/e) for some α > 0. This suggests that the mechanisms of inertia–gravity wave generation, which are not captured by these balanced models, are also exponentially weak. This has been confirmed by explicit analytical results obtained for a few highly simplified models. These results are reviewed, and some of the exponential-asymptotic techniques that have been used in their derivation are presented. Two types of mechanisms are examined: spontaneous-generation mechanisms, which generate exponentially small waves from perfectly balanced i.
A TRANSITION REGION EXPLOSIVE EVENT OBSERVED IN He ii WITH THE MOSES SOUNDING ROCKET

Transition region explosive events (EEs) have been observed with slit spectrographs since at least 1975, most commonly in lines of C iv (1548 Å, 1550 Å) and Si iv (1393 Å, 1402 Å). We report what we believe to be the first observation of a transition region EE in He ii 304 Å. With the Multi-Order Solar EUV Spectrograph (MOSES) sounding rocket, a novel slitless imaging spectrograph, we are able to see the spatial structure of the event. We observe a bright core expelling two jets that are distinctly non-collinear, in directions that are not anti-parallel. The jets have sky-plane velocities of order 75 km s−1 and line-of-sight velocities of +75 km s−1 (blue) and −30 km s−1 (red). The core is a region of high non-thermal Doppler broadening, characteristic of EEs, with maximal broadening 380 km s−1 FWHM. It is possible to resolve the core broadening into red and blue line-of-sight components of maximum Doppler velocities +160 km s−1 and −220 km s−1. The event lasts more than 150 s. Its properties correspond to the larger, long-lived, and more energetic EEs observed in other wavelengths.
Improving the Accuracy of MODIS Near-Infrared Water Vapor Product Under all Weather Conditions Based on Machine Learning Considering Multiple Dependence Parameters

We developed six machine-learning-based calibration models to improve the all-weather accuracy of precipitable water vapor (PWV) product from near-infrared (NIR) observations of the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument, i.e., MOD05 PWV. The six machine learning approaches are: back propagation neural network (BPNN), gradient boosting decision tree (GBDT), generalized regression neural network (GRNN), K-nearest neighbor (KNN), multilayer perceptron neural network (MLPNN), and extreme gradient boosting (XGBoost). The input of the models included MOD05 PWV, latitude, longitude, elevation, cloud, season, and solar zenith angle, in association with the quality of the MOD05 PWV product. PWV data measured from in situ 453 Global Positioning System (GPS) stations in Australia in 2017 were utilized as the target water vapor data for model training. The validation results in Australia in 2018–2019 indicate that the models can significantly improve the all-weather quality [increased <inline-formula> <tex-math notation="LaTeX">$R^{2}$ </tex-math></inline-formula>, reduced root-mean-square error (RMSE), and reduced mean bias (MB)] of the MOD05 PWV product, exhibiting a reduction in RMSE of 53.33% for BPNN, 55.25% for GBDT, 53.24% for GRNN, 37.81% for KNN, 54.98% for MLPNN, and 55.16% for XGBoost. The <inline-formula> <tex-math notation="LaTeX">$R^{2}$ </tex-math></inline-formula> was 0.58–0.79 and the MB was 0.12–0.72 mm, much better than the MOD05 all-weather PWV product (<inline-formula> <tex-math notation="LaTeX">$R^{2} = 0.26$ </tex-math></inline-formula> and MB = −1.75 mm). Different from previous studies that focused on clear-sky conditions only, this work is the first one to enhance the quality of official MODIS NIR PWV products under all weather conditions, reducing the impact of clouds on PWV products.
Structural and optical properties of InAs–GaAs quantum dots subjected to high temperature annealing

Annealing at higher temperature (700 °C) of structures with two‐dimensional and three‐dimensional arrays in InAs–GaAs quantum dots (QDs) results in an increase in the size and in a corresponding decrease in the indium composition of the QDs. The change in the In composition is monitored by the contrast pattern in the plan‐view transmission electron microscopy (TEM) images viewed under the strong beam imaging conditions. Increase in the size of the QDs is manifested by the plan‐view TEM images taken under [001] zone axis illumination as well as by the cross‐section TEM images. We show that the dots maintain their geometrical shape upon annealing. Luminescence spectra demonstrate a shift of the QD luminescence peak toward higher energies with an increase in the annealing time (10–60 min) in agreement with the decrease in indium composition revealed in TEM studies. The corresponding decrease in the QD localization energy results in an effective evaporation of carriers from QDs at room temperature, and the in.
Semiparametric Inference for the Two‐way Layout Under Order Restrictions

There are many situations in which a researcher would like to analyse data from a two‐way layout. Often, the assumptions of linearity and normality may not hold. To address such situations, we introduce a semiparametric model. The model extends the well‐known density ratio model from the one‐way to the two‐way layout and provides a useful framework for semiparametric analysis of variance type problems under order restrictions. In particular, the likelihood ratio order is emphasized. The model enables highly efficient inference without resorting to fully parametric assumptions or the use of transformations. Estimation and testing procedures under order restrictions are developed and investigated in detail. It is shown that the model is robust to misspecification, and several simulations suggest that it performs well in practice. The methodology is illustrated using two data examples; in the first, the response variable is discrete, whereas in the second, it is continuous.
Stability Analysis of Mixed Traffic Flow Considering Personal Space under the Connected and Automated Environment

A traffic survey using an unmanned aerial vehicle on the Haixia road in Chongqing, China found a significant correlation between the velocity of the vehicle and the distance of the vehicle when moving forward and laterally. To mitigate driving disruptions owing to vehicle intrusion at a desired distance, personal space (PS) is introduced to analyze the car-following behavior of continuous mixed traffic flow formed by human-driven (HD) vehicles and cooperative adaptive cruise control (CACC) vehicles. PS is a virtual boundary that refers to the space where psychological tension is caused by the invasion of others. Further, an intelligent driver model (IDM) was used to establish a mixed traffic car-following PS-IDM. The stability of the disturbance transfer function analytical model in homogeneous and heterogeneous traffic flows was used to calculate the traffic flow stability region under different CACC vehicle permutations. The results show that the PS-IDM-based car-following model effectively improves the stability fitting effect of mixed traffic flow, and the driving comfort is increased by up to 20.7% when compared with that of the single car-following model. In addition, there is a negative correlation between the PS and the unstable velocity range of the traffic flow. Compared with the homogeneous HD traffic flow, the average intrusion rate of homogeneous CACC traffic flow is reduced by 4.6%, and the driving comfort of vehicles is improved by approximately 65%.
Robust analysis of fuzzy logic control systems with uncertainties

In this paper, the robust stability of fuzzy control systems with uncertainties or nonlinearities is studied through the Popov-Lyapunov approach. Since solving an algebraic Riccati equation is the kernel of the proposed algorithm the method is feasible and easy to implement. In additional the proposed method has no fuzzy rule, inference engine, fuzzifier, or defuzzifier limitations. The resultant allowable uncertainty or nonlinearity bounds can help us to estimate the robust stability of a fuzzy control system; then such elements as the appropriate gauges can be chosen so that the stability can be guaranteed.
Hierarchical predictive coding in distributed pain circuits

Predictive coding is a computational theory on describing how the brain perceives and acts, which has been widely adopted in sensory processing and motor control. Nociceptive and pain processing involves a large and distributed network of circuits. However, it is still unknown whether this distributed network is completely decentralized or requires networkwide coordination. Multiple lines of evidence from human and animal studies have suggested that the cingulate cortex and insula cortex (cingulate-insula network) are two major hubs in mediating information from sensory afferents and spinothalamic inputs, whereas subregions of cingulate and insula cortices have distinct projections and functional roles. In this mini-review, we propose an updated hierarchical predictive coding framework for pain perception and discuss its related computational, algorithmic, and implementation issues. We suggest active inference as a generalized predictive coding algorithm, and hierarchically organized traveling waves of independent neural oscillations as a plausible brain mechanism to integrate bottom-up and top-down information across distributed pain circuits.
Antenna Array Diversity Evaluation Under Multipath Environments With Digital Beamforming

This work proposes a methodology for evaluating the antenna array diversity and resultant radiation pattern from digitally-processed-based beamforming systems. Our approach enables to interpret the advanced antenna systems (AAS) coverage and massive multiple-input multiple output (mMIMO) spatial resolution, by the inspection of the array resultant multiple beams. Particularly, the impact on the mMIMO spatial resolution is conducted as a function of the channel correlation, by means of an exclusively radiofrequency (RF) approach, with the advantage of not considering the system-level features, and using a new figure of merit (<inline-formula> <tex-math notation="LaTeX">$\Lambda $ </tex-math></inline-formula> factor). The new figure of merit enables to evaluate the antenna array diversity from two- and three-dimensional (2D and 3D) beamforming, by computing the number of lobes with gain higher than a unique element. In the 3D case, the figure of merit is based on a differential calculation, which enables performing an infinitesimal counting of lobes per antenna element beamwidth. Such parameter is initially applied to a theoretical dipole-based array, with the purpose of quantifying the created multiple beams by the overlapped radiation patterns from mMIMO systems. Furthermore, the <inline-formula> <tex-math notation="LaTeX">$\Lambda $ </tex-math></inline-formula> factor is exploited for analyzing the performance of a 64-element and dual-polarized SICL-based slot antenna array and a 64-element dipole-based antenna prototypes, both previously developed by our research group. Finally, it is demonstrated that the <inline-formula> <tex-math notation="LaTeX">$\Lambda $ </tex-math></inline-formula> factor increases as diversity increases and dipole-based antenna array could be used as an upper limit, attaining 11.46 lobes/rad
Chemical, biological and in silico assessment of date (P. dactylifera L.) fruits grown in Ha’il region

Background: Dates palm (Phoenix dactylifera L.) fruits are among the most widely used fruits in the Middle East and African nations. Numerous researchers confirmed the presence of phytochemicals in P. dactylifera L. fruit and its by-products with broad-ranging biological activities. Objectives: In the present work, phytochemical and biological assessments of two different cultivars of date fruit (Shishi M1 and Majdool M2 grown in the Ha’il region of Saudi Arabia) have been carried out. Methods: Date fruits were extracted and analyzed by gas chromatography-mass spectrometry (GS-MS),liquid chromatography-mass spectrometry (LC-MS) and Fourier-transform infrared spectroscopy (FT-IR)techniques. The lyophilized methanolic extracts were analyzed for their in-vitro antiproliferative andcytotoxicity against colon cancer (HCT116) cell line. To identify the possible constituents responsible for the bioactivity, in-silico molecular docking and molecular dynamics (MD) simulation studies were carried out. Results: Both cultivars exhibited in-vitro anticancer activity (IC50 = 591.3 μg/mL and 449.9 μg/mL for M1 and M2, respectively) against colon cancer HCT-116 cells. The computational analysis results indicated procyanidin B2 and luteolin-7-O-rutinoside as the active constituents. Conclusion: Based on these results, we conclude that these cultivars could be a valuable source for developing health promoter phytochemicals, leading to the development of the Ha’il region, Saudi Arabia.
Exploring Novel Therapeutic Opportunities for Glioblastoma Using Patient-Derived Cell Cultures

Simple Summary Glioblastomas (GBM) are aggressive brain tumors with poor prognosis that need effective treatment. GBMs are characterized by extensive cellular and molecular heterogeneity which are reflected in patient-derived cell cultures, frequently used in testing potential therapeutics. Here, we established GBM-derived cell cultures from fresh tumor specimens and characterized them at the protein and molecular levels. We confirmed the considerable intertumor heterogeneity of GBMs. As the epidermal growth factor receptor (EGFR) is a subject of common oncogenic alterations in GBM, we tested anti-EGFR therapy combined with temozolomide (first-choice medication for GBM) or with doxorubicin (common therapeutic for various solid and blood cancers). We found that GBM-derived cells were more sensitive to a combined therapy than to monotherapy, particularly cells with inactive DNA repair mechanisms. Abstract Glioblastomas (GBM) are the most common, primary brain tumors in adults. Despite advances in neurosurgery and radio- and chemotherapy, the median survival of GBM patients is 15 months. Recent large-scale genomic, transcriptomic and epigenetic analyses have shown the cellular and molecular heterogeneity of GBMs, which hampers the outcomes of standard therapies. We have established 13 GBM-derived cell cultures from fresh tumor specimens and characterized them molecularly using RNA-seq, immunoblotting and immunocytochemistry. Evaluation of proneural (OLIG2, IDH1R132H, TP53 and PDGFRα), classical (EGFR) and mesenchymal markers (CHI3L1/YKL40, CD44 and phospho-STAT3), and the expression of pluripotency (SOX2, OLIG2, NESTIN) and differentiation (GFAP, MAP2, β-Tubulin III) markers revealed the striking intertumor heterogeneity of primary GBM cell cultures. Upregulated expression of VIMENTIN, N-CADHERIN and CD44 at the mRNA/protein levels suggested increased epithelial-to-mesenchymal transition (EMT) in most studied cell cultures. The effects of temozolomide (TMZ) or doxorubicin (DOX) were tested in three GBM-derived cell cultures with different methylation status of the MGMT promoter. Amongst TMZ- or DOX-treated cultures, the strongest accumulation of the apoptotic markers caspase 7 and PARP were found in WG4 cells with methylated MGMT, suggesting that its methylation status predicts vulnerability to both drugs. As many GBM-derived cells showed high EGFR levels, we tested the effects of AG1478, an EGFR inhibitor, on downstream signaling pathways. AG1478 caused decreased levels of phospho-STAT3, and thus inhibition of active STAT3 augmented antitumor effects of DOX and TMZ in cells with methylated and intermediate status of MGMT. Altogether, our findings show that GBM-derived cell cultures mimic the considerable tumor heterogeneity, and that identifying patient-specific signaling vulnerabilities can assist in overcoming therapy resistance, by providing personalized combinatorial treatment recommendations.
Modeling Accounting Profit Behavior Based on Events Theory a Comparative Study of Companies Listed on the Tehran and Istanbul Stock Exchange

Purpose: Th is study aims to evaluate the effect of annual financial events on operating, and net accounting profits in the financial statements of Iranian and Turkish companies. Theoretical framework: The profitability of the company is one of the main factors that determine shareholder and investor returns. This topic has been central to a number of contemporary financial studies discussed in the literature review. Design/methodology/approach: To conduct the research, data related to the financial statements of 121 companies listed on the Tehran Stock Exchange for a period of 10 years from 2010 to 2019 and 151 companies listed on the Istanbul Stock Exchange for a period of 10 years from 2010 to 2019 were used. Findings: According to the results, there was a significant relationship between financial events and operating, and net accounting profits of Iranian and Turkish companies. Moreover, current and previous financial statements affected accounting profit, and no significant difference was observed between the two geographical locations of Iran and Turkey. Research, Practical & Social Implications: Information about companies' financial statements could be utilized by investors and analysts to more suitably analyze companies' current and future profits and returns. Originality/value: Most previous studies have assessed factors inside or outside the organization affecting profit, and the capacity of complete information on the change of the financial situation in different periods and its effect on profit behavior has not been thoroughly analyzed. This matter highlights the significance of our study.
Developing Awareness of Green Human Resource Development Practices in the Hotel Industry

The Problem The hotel industry is a major contributor to the depletion of natural resources (e.g., water and energy) and other practices (e.g., waste management and pollution) that jeopardizes environmental sustainability. The expertise of human resource development (HRD) practitioners is needed to develop the knowledge and skills of industry practitioners towards the development of pro-green knowledge and competencies for automation of workflows for environmental sustainability. The Solution Green human resource development is suggested as a paradigm shift from traditional approaches of HRD to bring awareness of ways that HRD expertise can be applied to green practices. By integrating the expertise, knowledge, and competencies of HRD practitioners with industry practitioners, the hotel industry has the potential to be transformed into a sector with ecofriendly and pro-environmental culture. The Stakeholders Human resource development researchers and practitioners; hotel industry workforce (practitioners, organizational leaders, and all sectors of the workforce).
The growth of Alfvén waves in the resistive current-driven instability

On the basis of a two-fluid, cold-plasma, linear stability calculation with linear friction between electrons and ions, the growth rate of Alfvén waves is derived from the dispersion relation for a uniformly magnetized plasma, in which the plasma resistivity and a uniform electric current carried by an electron beam are both considered. The growth rate is directly proportional to the plasma resistivity, the electric current density and the value of the parameter ωxpe/Ωe (where ωxpe and Ωe are the electron plasma and cyclotron frequency respectively). Moreover, the growth of Alfvén waves is mainly excited in a direction nearly parallel to the ambient magnetic field. The critical value of the velocity of the electron fluid is just equal to the Alfvén velocity. The results of this paper are compared with those for the linear tearing mode.
A Genetic Algorithm Optimized Undersampling Method for Seismic Sparse Acquisition and Reconstruction

The irregular observation region poses challenges to seismic acquisition systems design. The commonly-used parallel-type acquisition system requires that the geophones are located at equally spaced positions and therefore is hard to implement in an irregular observation region. An acquisition system which allows the implementation of sparse and irregular observation (e.g., the node-type geometry) followed by a reconstruction procedure is a solution. It can not only fit in irregular observation regions but also make a significant reduction in seismic acquisition costs. The seismic sparse acquisition can be mathematically modeled as an undersampling operator in the seismic reconstruction problem. A suboptimal undersampling pattern will lead to an inferior reconstruction result. To optimize the seismic sparse acquisition, I propose an undersampling method based on bionic intelligence in this study. In the proposed method, a Shannon entropy maximum model is proposed to improve the observed ergodicity and reduce the undersampling artifacts. To solve the maximum problem, an improved version of the genetic algorithm (GA) is presented. The proposed method is applicable to irregular observation regions and can optimize the subsequent reconstruction performance. I provide a detailed algorithm framework and discuss the undersampling artifacts of different undersampling methods. The application to synthetic and field seismic data validates the effectiveness of the proposed method.