Miracle-dz/UniFAR-FTUs huggingface dataset:
USING SOFT COMPUTING TECHNIQUES TO INTEGRATE MULTIPLE KINDS OF ATTRIBUTES IN DATA MINING

Data mining discouvers interesting information from a data set. Mining incorporates different methods and considers different kinds of information. Granulation is an important task of mining. Mining methods include: association rule discouvery, classification, partitioning, clustering, and sequence discouvery. The data se s can be extremely large with multiple kinds of data in high dimensionality. Most current clustering algorithms deal with either quantitative or qualitative data, but not both. However, many data sets contain a mixture of quantitative and qualitative data. We are considering how to best group records containing multiple k nds of data. It is difficult to do this. Even grouping based on different quantitative metrics has its difficulties. There are many partially successful strategies as well as several different possible differential geometries. Adding in various qualitative elements is exceedingly difficult. We expect to use a mixture of scalar methods, soft computing (rough sets, fuzzy sets), as well as methods using other metrics. To cluster records in a data set, it would be useful to have a similarity measure. Unfortunately, few exist that account meaningfully for any combination of kinds of data. The more meaningful metrics known are restrictive to a particular area or science. The method of combining magnitude difference and simple matching so that it is general enough for mining is a topic that is yet to be reasonably solved. We will present several strategies for integrating multiple metrics.
Real-time approaches to the estimation of local wind velocity for a fixed-wing unmanned air vehicle

Three real-time approaches to estimating local wind velocity for a fixed-wing unmanned air vehicle are presented in this study. All three methods work around the navigation equations with added wind components. The first approach calculates the local wind speed by substituting the ground speed and ascent rate data given by the Global Positioning System (GPS) into the navigation equations. The second and third approaches utilize the extended Kalman filter (EKF) and the unscented Kalman filter (UKF), respectively. The results show that, despite the nonlinearity of the navigation equations, the EKF performance is proven to be on a par with the UKF. A time-varying noise estimation method based on the Wiener filter is also discussed. Results are compared with the average wind speed measured on the ground. All three approaches are proven to be reliable with stated advantages and disadvantages.
Estimation of Intervention Effects with Noncompliance: Alternative Model Specifications

This study examines alternative ways of specifying models in the complier average causal effect (CACE) estimation method, where the major interest is in estimating causal effects of treatments for compliers. A fundamental difficulty involved in the CACE estimation method is in dealing with missing compliance information among study participants. Given that, the assumption of the exclusion restriction plays a critical role in separating the distributions of compliers and non-compliers. If no pretreatment covariates are available, assuming the exclusion restriction is unavoidable to obtain unique ML estimates in CACE models, although the assumption can be often unrealistic. One disadvantage of assuming the exclusion restriction is that the CACE estimate can be biased if the assumption is violated. Another disadvantage is that the assumption limits the flexibility of CACE modeling in practice. However, if pretreatment covariates are available, more modeling options other than strictly forcing the exclusion restriction can be considered to establish identifiability of CACE models. This study explores modeling possibilities of CACE estimation within an ML-EM framework in the presence of covariate information.
Genotoxic Effect of Dicyclopropanated 5-Vinyl-2-Norbornene

Dicyclopropanated 5-vinyl-2-norbornene (dcpVNB) is a strained polycyclic hydrocarbon compound with a high energy content, which makes it promising for the development of propellant components based on it. In this work, the genotoxic properties of dcpVNB were studied using whole-cell lux-biosensors based on Escherichia coli and Bacillus subtilis. It was shown that the addition of dcpVNB to bacterial cells leads to the appearance of DNA damage inducing the SOS response and Dps expression with slight activation of the OxyR-mediated response to oxidative stress. The highest toxic effect of dcpVNB is detected by the following lux-biosensors: E. coli pColD-lux, E. coli pDps, B. subtilis pNK-DinC, and B. subtilis pNK-MrgA, in which the genes of bacterial luciferases are transcriptionally fused to the corresponding promoters: Pcda, Pdps, PdinC, and PmrgA. It was shown that lux-biosensors based on B. subtilis, and E. coli are almost equally sensitive to dcpVNB, which indicates the same permeability to this compound of cell wall of Gram-positive and Gram-negative bacteria. The activation of Pdps after dcpVNB addition maintains even in oxyR mutant E. coli strains, which means that the Pdps induction is only partially determined by the OxyR/S regulon. Comparison of specific stress effects caused by dcpVNB and 2-ethyl(bicyclo[2.2.1]heptane) (EBH), characterized by the absence of cyclopropanated groups, shows that structural changes in hydrocarbons could significantly change the mode of toxicity.
Content-based high-resolution remote sensing image retrieval with local binary patterns

Texture is a very important feature in image analysis including content-based image retrieval (CBIR). A common way of retrieving images is to calculate the similarity of features between a sample images and the other images in a database. This paper applies a novel texture analysis approach, local binary patterns (LBP) operator, to 1m Ikonos images retrieval and presents an improved LBP histogram spatially enhanced LBP (SEL) histogram with spatial information by dividing the LBP labeled images into k*k regions. First different neighborhood P and scale factor R were chosen to scan over the whole images, so that their labeled LBP and local variance (VAR) images were calculated, from which we got the LBP, LBP/VAR, and VAR histograms and SEL histograms. The histograms were used as the features for CBIR and a non-parametric statistical test G-statistic was used for similarity measure. The result showed that LBP/VAR based features got a very high retrieval rate with certain values of P and R, and SEL features that are more robust to illumination changes than LBP/VAR also obtained higher retrieval rate than LBP histograms. The comparison to Gabor filter confirmed the effectiveness of the presented approach in CBIR.
Fabrication of PEG-Plasticized Epoxy Resin-Based Microfluidic Chips by Casting over PMMA Mold for PCR Applications: Influence CO2 Laser-Ablation Parameters of Mold

Despite dimethyl siloxane (PDMS) being one of the most used microfluidics chips, its micromachining techniques are infeasible for the mass production of commercial devices. This study proposed Epoxy Resin (ER) as a promising, cost-effective alternative to PDMS in lab-on-chip applications, including Polymerase Chain Reactions (PCR). Moreover, a novel, rapid and non-photolithographic approach has been developed for micromachining epoxy microfluidic chips. A new method for fabricating epoxy resin and polyethylene glycol (PEG) hybrid (ER-PEG) microchannels was developed by casting replication over PMMA molds. A PMMA piece was engraved with a CO2 laser in the raster mode to produce the mold for the ER-PEG casting first. A positive mold was fabricated from a polymethyl methacrylic acid (PMMA) sheet (6mm) by CO2 laser ablation. The microfluidic chips with the negative pattern were replicated by casting thermoset epoxy resin onto the micro-machined PMMA mold. The entire process, from device design conception to working device, can be completed in minutes. Herein, to enhance the surface roughness (Ra) of the ablated mold surface, different Distances to Focus (DF) were tried. The low Ra in the mold results in a low Ra in the replica. Also, the performance of ER-PEG in PCR was evaluated to verify the compatibility of the chip material to the PCR test.
Two further Ramanujan pairs

Abstract In a recent article, George E. Andrews considers a generalization of the Rogers-Ramanujan identities involving a pair of infinite sequences of positive integers, which he calls a Ramanujan pair. He lists the known Ramanujan pairs and conjectures that there are no more. The object of this note is to establish the existence of two further Ramanujan pairs.
High-Resolution Planetscope Imagery and Machine Learning for Estimating Suspended Particulate Matter in the Ebinur Lake, Xinjiang, China

Ebinur Lake is a shallow lake and vulnerable to strong winds, which can lead to drastic changes in suspended particulate matter (SPM). High spatial and temporal resolution images are therefore urgently needed for SPM monitoring over the Ebinur Lake. Hence, a high-efficiency inversion model of estimating SPM from high-resolution images using machine learning is essential to increase the amount of extracted information through band combinations quadratic optimization. This article aims to evaluate the capability of the PlanetScope images and four machine learning approaches for estimating SPM of the Ebinur Lake. The specific objectives include: to obtain the sensitive bands and band combinations for SPM using correlation analysis; to quadratically optimize the combination pattern of sensitive bands using a linear model; and to compare the accuracy of traditional linear model and machine learning models in estimating SPM. The results of the study confirm that after linear model quadratic optimization, the band combinations of B3*B4, (B2+B3)/ (B2-B3), (B3+B4)*(B3+B4), and (B3-B2)/(B2/B3) have higher accuracy than that of the single band model. By inputting the preferred four-band combinations into the partial least squares, random forest, extreme gradient boosting, gradient boosting decision tree, and categorical boosting (CatBoost) models, the performance of the SPM inversion based on PlanetScope images is better than the traditional linear model. Validation of the inversion maps with observations further indicates that the CatBoost model performed the best.
Nonlinear ultrasound monitoring of fatigue microdamage accumulation in cortical bone

Abstract — Accumulation of bone micro-damage is suspected to lead to severe impairment of mechanical properties with an increase in skeletal fragility and fracture risk. The objective of the study was to evaluate the potential of Nonlinear Resonant Ultrasound Spectroscopy (NRUS) for measuring micro-damage accumulation in cortical bone using four-point bending cycling fatigue. Sixteen human cortical bone specimens were machined as parallelepiped beams. Damage progression was controlled by measuring the linear elastic beam theory modulus ( E LEBT ), known to reflect microdamage accumulation. Before and between each damage step, the nonlinear ultrasonic elastic coefficient was measured by NRUS. At the end of each cycling fatigue, a subset of bone samples was measured by µCT at the European Synchrotron Radiation Facility. Results showing a progressive increase of nonlinear ultrasonic elastic coefficient along fatigue cycling suggest that NRUS measurements are sensitive to micro-damage accumulation. The results mentioned above were validated using synchrotron radiation µCT. The variation of elastic nonlinearity was found to be significantly correlated to the variation of number density of small microcracks which almost doubled in damaged regions. Keywords-component; nonlinear; NRUS; microcracks; bone; fatigue
Oxygen diffusion studies using nuclear reactions

The techniques available for oxygen diffusion measurements are summarized and the usefulness of using nuclear techniques is illustrated. In the present work, the mass-18 isotope of oxygen is used as the diffusing species and its concentration distribution is subsequently explored using the 1? 763 MeV resonance in the 18O(p, ? )15N reaction. The yield from the resonance gives a measure of 18O concentration, and depth is explored by measuring at different energies of the incident protons. Variations in the technique have been used. Various methods of analysing the data have been explored and the preferred one is that which makes allowance for the various spreading factors which contribute to the observed ? -particle spectrum. Measurements are quoted for the 18O self-diffusion coefficient in a TiO2 specimen showing that they have good reproducibility and are consistent with those of other observers.
Classification of thermal face images using radial basis function neural network

In this paper we have investigated an approach to recognize thermal face images for face recognition using line features and Radial Basis Function (RBF) neural network as classifier for them. The proposed method comprises of three steps. In the first step, line features are extracted from thermal polar images and feature vectors are constructed using these line. In the second step feature vectors thus obtained are passed through eigenspace projection for the dimensionality reduction of feature vectors. Finally, the images projected into eigenspace are classified using a Radial Basis Function (RBF) neural network. In the experiments we have used Object Tracking and Classification beyond Visible Spectrum (OTCBVS) database. Experimental results show that the proposed approach significantly improves the verification and identification performance and the maximum success rate is 100% whereas on an average it is 94.44%.
Enhanced Catalytic Effect of Ti2CTx-MXene on Thermal Decomposition Behavior of Ammonium Perchlorate

Transition metal carbonitrides (MXenes) are promising catalysts due to their special structures. Recently, many studies have shown that MXenes have a catalytic effect on the thermal decomposition of ammonium perchlorate (AP). However, the catalytic effects have not been extensively investigated. Therefore, it is important to illustrate the catalytic mechanisms of pure MXene in AP thermal decomposition. Herein, the catalytic properties of Ti2CTx for ammonium perchlorate (AP) thermal decomposition were investigated by numerous catalytic experiments. The results showed that the high-temperature decomposition (HTD) decreased by 83 °C, and the decomposition heat of AP mixed with Ti2CTx increased by 1897.3 J/g. Moreover, the mass spectrum (MS) data showed that the NH3, H2O, O2, N2O, NO, HCl, and NO2 were formed. In addition, according to the X-ray diffraction (XRD), Raman spectrum, high-resolution transmission electron microscopy (HRTEM), selected area electron diffraction (SAED), and X-ray photoelectron spectra (XPS) results, the Ti2CTx nanosheets can adsorb the gaseous products and react with them in-situ, generating anatase-TiO2 and carbon layers. The Ti2CTx, as-resulted anatase-TiO2, and carbon can synergize and further catalyze the thermal decomposition of AP when both electron and proton transfers are accelerated during AP decomposition.
Biofunctionalization of Multiplexed Silicon Photonic Biosensors

Silicon photonic (SiP) sensors offer a promising platform for robust and low-cost decentralized diagnostics due to their high scalability, low limit of detection, and ability to integrate multiple sensors for multiplexed analyte detection. Their CMOS-compatible fabrication enables chip-scale miniaturization, high scalability, and low-cost mass production. Sensitive, specific detection with silicon photonic sensors is afforded through biofunctionalization of the sensor surface; consequently, this functionalization chemistry is inextricably linked to sensor performance. In this review, we first highlight the biofunctionalization needs for SiP biosensors, including sensitivity, specificity, cost, shelf-stability, and replicability and establish a set of performance criteria. We then benchmark biofunctionalization strategies for SiP biosensors against these criteria, organizing the review around three key aspects: bioreceptor selection, immobilization strategies, and patterning techniques. First, we evaluate bioreceptors, including antibodies, aptamers, nucleic acid probes, molecularly imprinted polymers, peptides, glycans, and lectins. We then compare adsorption, bioaffinity, and covalent chemistries for immobilizing bioreceptors on SiP surfaces. Finally, we compare biopatterning techniques for spatially controlling and multiplexing the biofunctionalization of SiP sensors, including microcontact printing, pin- and pipette-based spotting, microfluidic patterning in channels, inkjet printing, and microfluidic probes.
Telehealth for Pediatric Disorders of Gut-Brain Interaction During the COVID-19 Pandemic

A retrospective chart review was completed to examine psychological treatment duration and response among pediatric patients with a disorder of gut-brain interaction including functional abdominal pain and irritable bowel syndrome. Cognitive behavioral therapy (CBT) was delivered via telehealth with a licensed psychologist or supervised psychology trainee embedded in a pediatric gastroenterology clinic. Participants were 22 youth (mean age = 14.36 years) who received CBT via telehealth between February and September of 2021, after completing an initial evaluation between February and July of 2021. Patients completed reliable and valid self-report measures of functional disability and pain during treatment. A unique CBT model was employed with an initial focus on psychoeducation and function regardless of level of severity of functional impairment. Consistent with study hypotheses, nonparametric statistical analyses demonstrated statistically significant reductions in functional disability and pain following implementation of the CBT model via telehealth. Contrary to predictions, there was no relation found between severity of functional impairment and duration of treatment.
Efficacy and Safety of Gum Arabic on Renal Failure Patients: Systematic Review and Meta-analysis

Background: Chronic Renal Failure (CRF) is a long-term disease caused by progressive kidney dysfunction due to many reasons leading to a significant rise in serum levels of creatinine and urea reaching the advanced stage where the patient goes for frequent hemodialysis. This study aims to discuss the evaluation of the efficacy of gum Arabic (GA) supplementation on the serum level of creatinine, urea, sodium, and potassium in CRF patients. Methods: Four databases PubMed, Web of Science, Scopus, and the Cochrane Library were searched for clinical trials assessment of gum Arabic intervention in CRF patients. Animal trials and experimental protocols were excluded. Screening of data and data extraction were done by two reviewers independently of each other. Meta-analysis was conducted on the selected studies using RevMan and the resulting description was summarized through the Forest plot tool on the efficacy of GA on 4 variables, creatinine, urea, sodium, and potassium in CRF patients. Results: From 574 studies searched, only 4 studies were included in this systemic review and meta-analysis. Although one of the studies had proved the objectives of the review but it was removed from the meta-analysis due to the heterogeneity caused by its inclusion. Conclusion: The few studies included in the current review revealed significant efficacy of GA treatment on the serum level of creatinine, urea, and sodium, but not potassium.
3D Shape Similarity Comparison Using Multi-level Spherical Moments

AbstractIn this paper we present a novel method for shape comparison of 3D models that employs multilevel spherical moments analysis approach relying on voxelization and spherical mapping of the 3D models. For an input polygon-soup 3D model, firstly a pose normalization step is done to align the model into a canonical coordinate frame and then to define the shape representation with respect to this orientation. Afterward we rasterize its exterior polygons into a cubical voxel grids, then a series of homocentric sphere with their center superposing the center of the voxel grids cut the grids into several spherical surfaces. Finally moments of each sphere are computed and the moments belong to all spheres constitute the descriptor of the model. Experiments show that this shape similarity comparison method outperforms in retrieval performance many previously proposed ones.
A Simple Derivation of Crooks Relation

The link between properties of a system at equilibrium, in particular free energy difference, to the fluctuations in the work performed during non-equilibrium process is called Crooks relation. This relation, which is a measure of the grade of irreversibility of a process, was elegantly derived based on the equations of motion for a set of particles along with the formal solution of the evolution equation using a distribution function, both solved in a classical and a stochastic way. This technical note, reports on a simple derivation of Crooks formula based on the energy balance and entropy generation in a system undergoing a process in which fluctuations are not neglected.
Innovative Methods Used in Monitoring COVID-19 in Europe: A Multinational Study

Several innovative methods have been deployed worldwide to curb the COVID-19 pandemic. The aim of the study is to investigate which innovative methods are used to monitor COVID-19 health issues in Europe and related legislative and ethical aspects. An online questionnaire was administered to European countries’ representatives of the project Population Health Information Research Infrastructure. Additional information was obtained from websites and documents provided by the respondents; an overview of the literature was also performed. Respondents from 14 countries participated in the study. Digital tools are used to monitor the spread of COVID-19 (13/14 countries) and vaccination coverage (12/14); for research, diagnostics, telehealth (14/14); to fight disinformation (11/14) and forecast the pandemic spread (4/14). The level of implementation of telehealth applications was mostly low/medium. Legislative and ethical issues were encountered in many countries, leading to institutional distrust. The COVID-19 pandemic has highlighted the need for timely and accurate health data for research purposes and policy planning. However, the use of innovative methods for population health monitoring and timely data collection has posed challenges to privacy and online security globally. Adequate regulatory oversight, targeted public health interventions, and fight against disinformation could improve the uptake rate and enhance countries’ emergency preparedness.