Miracle-dz/UniFAR-FTUs huggingface dataset:
Identification and Biological Evaluation of a Water-Soluble Fullerene Nanomaterial as BTK Kinase Inhibitor

Introduction Thanks to recent advances in synthetic methodology, water-soluble fullerene nanomaterials that interfere with biomolecules, especially DNA/RNA and selected proteins, have been found with tremendous potential for applications in nanomedicine. Herein, we describe the synthesis and evaluation of a water-soluble glycine-derived [60]fullerene hexakisadduct (HDGF) with Th symmetry, which is a first-in-class BTK protein inhibitor. Methods We synthesized and characterized glycine derived [60]fullerene using NMR, ESI-MS, and ATR-FT-IR. DLS and zeta potential were measured and high-resolution transmission electron microscopy (HRTEM) observations were performed. The chemical composition of the water-soluble fullerene nanomaterial was examined by X-ray photoelectron spectrometry. To observe aggregate formation, the cryo-TEM analysis was carried out. The docking studies and molecular dynamic simulations were performed to determine interactions between HDGF and BTK. The in vitro cytotoxicity was evaluated on RAJI and K562 blood cancer cell lines. Subsequently, we examined the induction of cell death by autophagy and apoptosis by determining the expression levels of crucial genes and caspases. We investigated the direct association of HDGF on inhibition of the BTK signalling pathway by examining changes in the calcium levels in RAJI cells after treatment. The inhibitory potential of HDGF against non-receptor tyrosine kinases was evaluated. Finally, we assessed the effects of HDGF and ibrutinib on the expression of the BTK protein and downstream signal transduction in RAJI cells following anti-IgM stimulation. Results Computational studies revealed that the inhibitory activity of the obtained [60]fullerene derivative is multifaceted: it hampers the BTK active site, interacting directly with the catalytic residues, rendering it inaccessible to phosphorylation, and binds to residues that form the ATP binding pocket. The anticancer activity of produced carbon nanomaterial revealed that it inhibited the BTK protein and its downstream pathways, including PLC and Akt proteins, at the cellular level. The mechanistic studies suggested the formation of autophagosomes (increased gene expression of LC3 and p62) and two caspases (caspase-3 and −9) were responsible for the activation and progression of apoptosis. Conclusion These data illustrate the potential of fullerene-based BTK protein inhibitors as nanotherapeutics for blood cancer and provide helpful information to support the future development of fullerene nanomaterials as a novel class of enzyme inhibitors.
Adaptive fast non-singular terminal sliding mode control for a vehicle steer-by-wire system

Steer-by-wire (SbW) systems in road vehicles require an effective controller to provide accurate and robust steering performance. For this purpose, this study proposes an adaptive fast non-singular terminal sliding mode (AFNTSM) controller for an SbW system by combining an adaptive estimation law with a fast non-singular terminal sliding mode (FNTSM) control scheme. First, the authors present a model to identify the dynamics of the SbW system, in which the self-aligning torque and friction-related forces are treated as external disturbances. Second, the AFNTSM control design is elaborated, which is proved to be able to guarantee high tracking accuracy via effectively estimating the self-aligning torque, fast convergence rate owing to its exponential stability, strong robustness against system and road surface uncertainties, and inherently smooth control inputs. Subsequently, the selection criteria of the control parameters are given in details. Finally, experimental results are shown to demonstrate that the designed AFNTSM controller has great superiority in comparison with an FNTSM controller without adaptation and an adaptive sliding mode controller based on conventional sliding mode.
An Algorithm for Computing Digital Cohomology Groups

: Several recent papers have discussed the digital version of the cohomology group for digital images, and some researchers calculate digital cohomology groups of some special two or three-dimensional digital images. In this paper, we determine the simplicial cohomology groups of some minimal simple closed curves and the digital surface MSS 6 . Also we give a general algorithm for computing digital cohomology groups of ﬁnite dimensional digital images
An algorithm for the mean and variance of the noncentral hypergeometric distribution

The mean and variance of the noncentral hypergeometric distribution are essential for obtaining maximum likelihood estimates for conditional logistic models for 2 x 2 tables. The numerical difficulty in directly computing them using the definition is discussed in detail by Satten and Kupper (1990). They also give an algorithm based on a continued fraction representation for the mean. We present here another algorithm, based on two equations in Harkness (1965):
Investigation of Extragalactic Radio Sources by Cross-Matching of Radio Catalogs

Abstract To search for variable radio sources, we used two well-known radio catalogs NVSS and FIRST, both providing fluxes at 1400 MHz. Cross-correlation enabled us to find 556,282 radio sources present in both catalogs. Using the 3σ criteria we distinguished 6,301 variable radio sources, and with certain limitations specified the 260 strongest radio variables. We cross-correlated these 260 sources with other catalogs at different wavelengths (APM, SDSS DR10, VCV-13, BZCAT, 2MASS, and WISE). As a result we obtained photometric data for optical, NIR, MIR and radio ranges for these 260 variable radio sources to study them in details.
Disparity and Diversity in NSCLC Imaging and Genomics: Evaluation of a Mature, Multicenter Database

Simple Summary Lung cancer remains the leading cancer-related death across North America. As imaging is fundamental for its diagnosis, treatment, and follow-up, the presence of healthcare disparities at this level needs to be identified. Using a multicenter collated database, we aimed to identify the existence of such disparities while describing the composition and behavior of our study population. Our results highlight the relevance of adequate access to imaging while being treated for NSCLC that could help pivot treatments early in both clinical and experimental settings. Abstract Lung cancer remains the leading cancer-related death across North America. Imaging is fundamental. Recently, healthcare disparities came into research focus. Our aim was to explore disparity from an imaging, genetic, and outcome perspective. We utilized the AACR Project GENIE Biopharma Consortium (BPC) dataset v 1.1 to build a collated NSCLC dataset. Descriptive and analytical statistics were applied according to data characteristics. From 1849 patients, mean age was 64.4 y (±10.5), 58% (n = 1065) were female, 23% (n = 419) never smoked, 84% (n = 1545) were of white race, and 57% (n = 1052) were < stage III. No difference (p > 0.05) was found for baseline imaging by race. White race showed higher 3-month surveillance imaging (p = 0.048) and a baseline stage < IV (OR 0.61). KRAS (33.3 vs. 17.9%), STK11 (14.8 vs. 7.3%), and KEAP1 (13.3 vs. 5.3%) mutations were predominant among white patients while EGFR mutation (19.2 vs. 44.1%) was less predominant. Mutations in TP53 or KEAP1 had worse PFS and OS. The latter was also reduced in STK11, KRAS + STK11, and KRAS + KEAP1 mutations. Meanwhile, EGFR mutation had increased OS. Multivariate analysis showed that progression on imaging at 3 or 6 months (HR 1.69 and 1.43, respectively), TP53 (HR 1.37) and KRAS (HR 1.26) had lower OS while EGFR and LRP1B (HR 0.69 and 0.39, respectively) had higher OS. No racial disparity at baseline imaging was observed. Higher initial stages among non-white patients might reflect inequalities in accessing healthcare. However, race wasn’t associated to OS. Finally, progression in imaging at 3 or 6 months showed the higher hazard ratios for death.
Microwave breakdown in air for multi-carrier, modulated or stochastically time varying RF fields

An investigation is made of the threshold for microwave breakdown in air in situations where the microwave power is strongly modulated or stochastically varying in time as, e.g. in communication systems based on multi-carrier operation where interference between the carriers may cause occasional high power peaks in the microwave power. Thresholds are established for the scenario of coherent and co-phased carriers as well as for breakdown in an electric field with a stochastically varying amplitude.
VLF emission stimulated by parallel electric fields

We study the influence of a weak quasi-static parallel electric field on the stability of electromagnetic plasma waves. Using an operator calculus to solve the Boltzmann-Maxwell equations we derive a dispersion relation for the electromagnetic waves. Assuming that the electrons have a loss-cone distribution, the real frequency of waves in the whistler band is not changed by the presence of the electric field. Resonant interaction damps the HF waves for propagation parallel to the electric field. In the case of opposite propagation, a new HF excitation is found at frequencies ω ≲ ωce The width of the excitation region depends on the width of the loss cone, field strength and collision frequency. This result is applied to observations of the splitting of VLF emissions under natural conditions in the magnetosphere. It is found that the observed splitting could have been caused by the presence of the weak parallel electric field of a kinetic (shear) Alfvén wave in the emission region, which is quasi-stationary compared with the growth of the observed VLF emission.
Potential Data Loss Due to Head/Disk Contacts During Dynamic Load/Unload

A functioning IBM drive was converted into a component load/unload tester in order to determine the consequence of full-speed loading and unloading of a slider on top of magnetic data. Tests using this apparatus show that the disk scratch damage produced by load/unload is necessary but not sufficient to result in defects that are detectable by surface analysis test. Comparison of the AFM of the scratch damage sites with the MFM of the surrounding data bits shows that data loss results from the physical damage and that any magnetostriction effect is negligible.
A Joint Design Criterion for the Dual Problem of Model Discrimination and Parameter Estimation

Two objectives of much experimentation in science and engineering are (i) to establish the form of an adequate mathematical model for the system being investigated and (ii) to obtain precise estimates of the model parameters. In the past, statistical design procedures have been proposed for tackling either one of these problems separately. Investigators, however, frequently want to perform experiments which will shed light on both questions simultaneously. In this paper, therefore, we present a design criterion which takes both objectives into account. The basic design strategy is to emphasize model discrimination when there is considerable doubt as to which model is best and gradually shifting the emphasis to parameter estimation as experimentation progresses and discrimination is accomplished. It is assumed that experiments can be performed sequentially. The use of the design criterion is illustrated with an example.
Personalization in Graphically Rich E-Learning Environments for K-6 Mathematics

This report describes a randomized controlled study that compared the personalization of educational content based on neural networks to personalization by human experts. The study was conducted in a graphically rich online learning environment for elementary school mathematics, in which N = 135 fourth- and sixth-grade students learn via mathematical applets. The performance of students who followed the algorithm's recommendations was compared with that of students who followed an a priori sequence constructed by the experts. While the algorithm only considered students' performance on past problems when recommending new problems, the human experts also took into consideration other factors related both to content and to the graphical interface. The findings reveal no significant differences in performance between the two groups, suggesting that the algorithm was as successful in preparing the students as human teachers. Herein, we discuss the different mechanisms used to prepare each of the groups for the learning tasks and highlight the importance of the user interface in that process. Specifically, we find that applets involving supportive interactions, in which students' interactions were intended to help solve the problem but were optional, represented students' preknowledge, while applets entailing required interactions did not. We contribute to the field of personalization in education with new evidence of the advantages of a content sequencing algorithm—based on collaborative filtering ranking and implemented via a neural network—in a graphically rich environment as tested in authentic classrooms.
A new nine node degenerated shell element with enhanced membrane and shear interpolation

A new nine node degenerated shell element is presented in this paper. In the formulation of the new element, an enhanced interpolation of the transverse shear strains in the natural co-ordinate system is used to overcome the shear locking problem, and an enhanced interpolation of the membrane strains in the local Cartesian co-ordinate system is applied to avoid membrane locking behaviour. It is shown that the resulting element has the requisite number of zero eigenvalues and associated rigid body modes. The element does not exhibit membrane or shear locking for large span/thickness ratios. To illustrate the good performance of the new element some examples are presented including comparisons with the behaviour of the selectively integrated Lagrangian degenerated shell elements.
Method for retrieving sequences of images on the basis of motion analysis

This paper describes a method for retrieving sequences of images in a motion image database using motion information as a key. This information is obtained by application of the motion analysis technique. The proposed method has three steps: automatic extraction of motion vectors through frame sequences, motion description using spatio-temporal space, and retrieval of sequences of images. The motion vectors of objects are extracted on the basis of block motion estimation. Block motion estimation tracks each block of a scene throughout a period. This tracking procedure takes account of the traceability of each block and the reliability of its calculated motion vector. Extracted motion vectors are mapped using spatio- temporal space (x-y-t). The motion of each block is represented as one vector in the feature space, and motion vectors in a scene are aggregated into several representative vectors by statistical analysis. The retrieval of sequences of images is divided into two parts: specification of the query conditions, and matching between the query conditions and the motion database. The query conditions are input from a stroke device. The user can interactively manipulate the query conditions, such as the number, period, and starting time of objects. The data are gathered as an x-y series at a given interval, and then normalized. Similarity is defined in spatio-temporal space as the distance between the query conditions and the stored motion index. Candidate sequences of images are ranked in order of distance. An experimental system has been developed for retrieving sequences of images on a workstation.
Study of the Behavior of Self-Sensing Concrete under the Influence of Different Mechanical Loads: A Review

Self-sensing concrete is an intelligent application of scientific knowledge for practical purposes and new concrete structures, which can feel the damage, stress and strain in the body of concrete. It has been widely used because of its possibility of getting efficient cost solution for controlling the structural sustainability of concrete structures, which indicate, that it is very impressive during the design life of the facilities. This review contains universal behavior and global information about different conditions of loading for self-sensing concrete. Also, the definitions and applications of intrinsic and non-intrinsic self-sensing concretes are mentioned. Moreover, a major confirmation is stated on the application of scientific knowledge for practical purposes and new concrete structures. The characteristics of self-sensing concrete provide an ability to reveal small cracks before they begin to become significant. During unchanging compression, firstly, the values of electrical resistivity decrease through an increase in load, subsequently become stable and then increased suddenly. While, during impact loading, the electrical resistivity decreases suddenly, but it regresses then to 0 after loading. However under tensile stress, the electrical resistivity increases as the tensile stress increases. Nevertheless, since the flexural is a component of compression and tension, the comparison between sensitivity for compression part is much smaller than in tension part.
Dimensionally Stable Delignified Bamboo Matrix Phase-Change Composite under Ambient Temperature for Indoor Thermal Regulation

Energy storage materials to modulate indoor microclimates are needed to improve energy efficiency and for human comfort. Of these, phase-change material (PCM) is considered a very useful material because of its excellent latent heat energy storage. For application, some synthetic porous materials for supporting PCM are usually not friendly enough for people and housing environments due to their non-degradation characteristics. Hence, to develop an eco-friendly porous material is needed in order to encapsulate PCM composites that are always expected in indoor applications. In this work, heat-treated bamboo bricks were delignified to provide a delignified bamboo (DB) matrix. A phase-change composite was then fabricated by impregnating DB with polyethylene glycol (PEG) polymer. Impregnation was carried out under wet conditions to ensure the regular arrangement of the DB structure so as to achieve dimensional stability. The final DB/PEG composite was investigated for dimensional stability, load rate, latent heat, and phase-change temperature. Results showed that the DB matrix could be easily impregnated with PEG polymer under wet conditions, and the DB/PEG composite was found to have high enthalpy and a large phase-change temperature interval. Moreover, the composite was found to be a good regulator of indoor temperature and a stable dimension with a snow-white appearance. In summary, this DB/PEG composite is an energy storage material with the potential to modulate ambient indoor temperature and reduce building energy consumption.
Control for bounded pseudo ARMAX stochastic systems via linear B-spline approximations

Following algorithms for the control of the shape of the output probability density function for general dynamic stochastic systems, this short paper presents the modelling and control algorithms for pseudo ARMAX systems, where different from all the existing ARMAX systems the considered system is subjected to any arbitrary bounded random input and the purpose of the control input design is to make the output probability density function of the system output as close as possible to a given distribution function. At first, the relationship between the input noise distribution and the output distribution is established. This is then followed by the description on the control algorithm design.
Display of EEG chaotic dynamics

A method for the visualization of the electroencephalogram (EEG) in phase space is described. The signal is transformed from the time domain to phase space by measuring the correlation dimension of the data and constructing the attractor in the required embedding space, which is normally of dimension 3 to 8. A singular value decomposition is used to obtain a good projection to 3-D. Animation of a series of 2-D rotated projections provides a way to visualize the fine structure of the reconstructed 3-D attractor. Examples and a computer package are briefly described. <<ETX>>
The Effect of Graviola Leaves Extract (Annona muricata L.) on Pharmacokinetic of Metformin in Rats’ Plasma and Pharmacological Activity of their Combination on Breast and Prostate Cancer Cell Lines

Objectives: Metformin is the most widely given medication for type 2 diabetes mellitus (T2DM). Annona muricata L. is a medicinal plant that belongs to the family Annonaceae, popularly known as graviola. Graviola leaves extract was found useful against diabetes, headache, insomnia, cystitis, inflammation, cancer, and other health benefits. The objectives of the current study are to investigate the effect of graviola leaves extract on metformin pharmacokinetics in rat plasma by applying high performance liquid chromatography (HPLC) method as well as its pharmacological effects on breast cancer (MCF-7) cells and prostate cancer (DU-145) cells. Methods: Wistar rats were classified into two groups; the first group (control group) received metformin (20 mg/kg) alone by oral gavage, while the second group, was administered a combination of metformin (20 mg/kg) and graviola leaves extract (20 mg/kg). Blood samples were collected at different time intervals to be analyzed using a validated HPLC method. Plasma profile and pharmacokinetic parameters were determined for each group. In addition, blood glucose levels at 0 hours and after 2 hours of metformin administration were measured in both groups. Breast cancer (MCF-7) cells and prostate cancer (DU-145) cells were used to investigate the anticancer effect of metformin (40 mg/ml), graviola leaves extract (20 mg/ml) and their combination by the standard MTT assay. Results: In the first group, metformin maximum plasma concentration (Cmax) and the area under the curve (AUC0-last) were (1509.25 ng/ml and 8705.59 h*ng/ml) respectively. In the second group, Pre-administration of graviola leaves extract significantly reduced MET (Cmax) and (AUC0-last), (701.88 ng/ml and 3467.72 h*ng/ml), respectively (P ≤0.05). Further, the use of metformin and graviola leaves extract separately showed strong anticancer activity on (MCF-7) cell lines with IC50 values of (10 and 20 mg/ml), respectively as well as on (DU-145) cell lines with IC50 value of (0.3125 and 5 mg/ml), respectively. In addition, the combination of metformin and graviola leaves extract showed a synergistic effect on (MCF-7) cells since the fractional inhibitory concentration value (FIC = 0.375) was less than 0.5, while it showed an additive effect on (DU-145) cells since the fractional inhibitory concentration value (FIC = 1.5) was between (0.5 and 4). Conclusion: In the current study, pre-administration of graviola leaves extract significantly reduced efficacy of metformin In vivo. The combination of metformin and graviola leaves extract showed a synergistic anticancer effect on breast cancer in vitro, while the combination has an additive effect on prostate cancer. The combination could be a potential therapeutic option to help treat breast cancer. The result achieved in this study is very encouraging to be considered for further investigation.
European bee diversity: Taxonomic and phylogenetic patterns

Wild bees still face striking shortfalls in knowledge of biodiversity in key regions of the world. This includes Europe, where despite a long tradition of data gathering, the continental scale distribution patterns of wild bees have not been systematically analysed to date. This study aims to characterise large‐scale biodiversity patterns to: (i) understand spatial–temporal heterogeneity in large‐scale databases, (ii) locate genuine diversity hotspots and their relationship with biogeographical patterns or habitats of interests and (iii) identify understudied species and areas to further design conservation actions for most at risk species in key regions.