Miracle-dz/UniFAR-FTUs huggingface dataset:
Analytical Predictions and Lattice Boltzmann Simulations of Intrinsic Permeability for Mass Fractal Porous Media

We derived two new expressions for the intrinsic permeability (k) of fractal porous media. The first approach, the probabilistic capillary connectivity (PCC) model, is based on evaluating the expected value of the cross‐sectional area of pores connected along various flow paths in the direction in which the permeability is sought. The other model is a modified version of Marshall's probabilistic approach (MPA) applied to random cross matching of pores present on two parallel slices through a fractal porous medium. The Menger sponge is a three‐dimensional mass fractal that represents the complicated pore space geometry of soil and rock. Predictions based on the analytical models were compared with estimates of k derived from lattice Boltzmann method (LBM) simulations of saturated flow in virtual representations of Menger sponges. Overall, the analytically predicted k values matched the k values from the LBM simulations with <14% error for the deterministic sponges simulated. While the PCC model can represent variation in permeability due to the randomization process for each realization of the sponge, the MPA approach can capture only the average permeability resulting from all possible random realizations. Theoretical and empirical analyses of the surface fractal dimension (D2) for successive slices through a random Menger sponge show that the mean D2 value 〈D2〉 = D3 − 1, where D3 is the three‐dimensional mass fractal dimension. Incorporating 〈D2〉 into the MPA approach resulted in a k that compared favorably with the modal value of k from LBM simulations performed on 100 random realizations of a random Menger sponge.
Void-and-cluster method for dither array generation

Halftoning to two or more levels by means of ordered dither has always been attractive because of its speed and simplicity. However, the so-called recursive tessellation arrays in wide use suffer from strong periodic structure that imparts an unnatural appearance to resulting images. A new method for generating homogeneous ordered dither arrays is presented. A dither array is built by looking for voids and clusters in the intermediate patterns and relaxing them to optimize isotropy. While the method can be used for strikingly high quality artifact-free dithering with relatively small arrays, it is quite general; with different initial conditions the familiar recursive tessellation arrays can be built. This paper presents the algorithm for generating such arrays. Example images are compared with other ordered dither and error diffusion-based techniques.
Fake Online Reviews: A Unified Detection Model Using Deception Theories

Online reviews influence consumers’ purchasing decisions. However, identifying fake online reviews automatically remains a complex problem, and current detection approaches are inefficient in preventing the spread of fake reviews. The literature on fake reviews detection lacks a comprehensive and interpretable theory-based model with high performance, which enables us to understand the phenomenon from a psychological perspective and analyze reviews based on user-generated content as well as consumer behavior. In this research, we synthesized ten well-founded deception theories from psychology, namely leakage theory, four-factor theory, interpersonal deception theory, self-presentational theory, reality monitoring theory, criteria-based content analysis, scientific content analysis, verifiability approach, truth-default theory, and information manipulation theory, and selected nine relevant constructs to develop a unified model for detecting fake online reviews. These constructs include specificity, quantity, non-immediacy, affect, uncertainty, informality, consistency, source credibility, and deviation in behavior. We characterized the selected constructs using verbal and non-verbal features to validate the proposed model empirically. Subsequently, we extracted features from the Yelp datasets and used them to train four machine learning algorithms, specifically Logistic Regression, Naïve Bayes, Decision Tree, and Random Forest. We demonstrated that quantity, non-immediacy, affect, informality, consistency, source credibility, and deviation in behavior are essential constructs for detecting fake reviews. To our surprise, we discovered that non-verbal features are more important than verbal features and that combining features from both types improves the prediction performance. Our theory-based model outperformed most of the state-of-the-art fake review detection models and yielded high interpretability and low complexity.
Impacts of Digital Transformation Capacity on Task Performance of Public Servant: A Case Study in Vietnam Ministry of Home Affairs

Digital transformation has been effectively applied in the public sector in Vietnam, especially the ministries. This fact has received significant attention from scientists. Therefore, to supplement the evidence of previous studies and enrich the research literature, this study examines the impact of factors of the digital transformation capacity of public servant of Vietnam Ministry of Home Affairs (Moha) on their task performance. This study was conducted through a cross-sectional survey using an intentional sampling technique (n=200). A multivariate linear regression analysis technique was applied to prove the hypotheses. Research results show that all three factors, digital technology capabilities, digital transformation ethics, and digital transformation leadership, have a positive and meaningful impact on the task performance of Moha public servant. Among them, the most substantial impact belongs to digital technology capabilities. Therefore, this study implies that the Vietnamese government and the Moha need to pay attention to formulating policies to improve the digital transformation capacity of public servant in digital transformation.
Effect of annealing on the interfaces of giant‐magnetoresistance spin‐valve structures

Si/Ta/NiFe/Cu/NiFe/FeMn/Ta spin‐valve layered structures were analyzed by x‐ray reflectivity, before and after annealing at 240, 320, and 360 °C. Specularly reflected x‐ray data were collected using a high‐resolution reflectometer and were analyzed by least‐squares refinement. The thicknesses of the individual layers in the NiFe/Cu/NiFe/FeMn magnetic sandwich remained essentially unchanged. With the exception of the FeMn/Ta interface, the widths of the buried interfaces increased rapidly with annealing temperature. The increase in widths at each of the NiFe/Cu and Cu/NiFe interfaces from 6.8 to 22.6 A caused a fivefold increase in the magnetically inactive layer in NiFe and a tenfold decrease in magnetoresistance. An increase in the total film thickness with annealing temperature was found to be caused by the surface oxidation of the Ta capping layer and the growth of a Ta silicide layer between the Ta buffer layer and the Si substrate.
High-Resolution Continuum and BR gamma Imaging Observations of M82

We report high angular resolution (about 0.6 sec), broad-band imaging at 1.2 microns (J band), 1.6 microns (H band), 2.2 microns (K band), and 3.7 microns (L' band) of the central 110 sec x 21 sec (1.65 kpc x 0.32 kpc) of the nearby starburst galaxy M82. We also present spectral imaging with 90 km/s resolution in the Br (gamma) (2.17 microns) hydrogen recombination line covering the central 16 sec x 16 sec (240 pc x 240 pc) of this edge-on, disk galaxy. The broad-band mosaics reveal two plateaus of emission indicative of an inner disk of stars and perhaps a larger bar structure. Color maps reveal an extinction ridge running along the central kiloparsec which is strongest at the nucleus and on the western side. The dust emission is more symmetric, suggesting that a dust lane is in front of the stellar population to the west of the nucleus, and behind the stars to the east; this is again suggestive of a stellar bar with leading dust lanes. Channel maps and a position-velocity image of the Br (gamma) reveal two lobes and are consistent with the interpretation that the ionized gas, and hence, the young massive stars are distributed in a toroid of H II regions surrounding the nucleus.
Nanoporous electroporation needle for localized intracellular delivery in deep tissues

Abstract The exogenous control of intracellular drug delivery has been shown to improve the overall efficacy of therapies by reducing nonspecific off‐target toxicity. However, achieving a precise on‐demand dosage of a drug in deep tissues with minimal damage is still a challenge. In this study, we report an electric‐pulse‐driven nanopore‐electroporation (nEP) system for the localized intracellular delivery of a model agent in deep tissues. Compared with conventional bulk electroporation, in vitro nEP achieved better transfection efficiency (>60%) with a high cell recovery rate (>95%) under a nontoxic low electroporation condition (40 V). Furthermore, in vivo nEP using a nanopore needle electrode with a side drug‐releasing compartment offered better control over the dosage release, time, and location of propidium iodide, which was used as a model agent for intracellular delivery. In a pilot study using experimental animals, the nEP system exhibited two times higher transfection efficiency of propidium iodide in the thigh muscle tissue, while minimizing tissue damage (<20%) compared to that of bulk electroporation. This tissue‐penetrating nEP platform can provide localized, safe, and effective intracellular delivery of diverse therapeutics into deep tissues in a controlled manner.
Exploring the Regulatory Role of ncRNA in NAFLD: A Particular Focus on PPARs

Liver diseases are responsible for global mortality and morbidity and are a significant cause of death worldwide. Consequently, the advancement of new liver disease targets is of great interest. Non-coding RNA (ncRNA), such as microRNA (miRNA) and long ncRNA (lncRNA), has been proven to play a significant role in the pathogenesis of virtually all acute and chronic liver disorders. Recent studies demonstrated the medical applications of miRNA in various phases of hepatic pathology. PPARs play a major role in regulating many signaling pathways involved in various metabolic disorders. Non-alcoholic fatty liver disease (NAFLD) is the most prevalent form of chronic liver disease in the world, encompassing a spectrum spanning from mild steatosis to severe non-alcoholic steatohepatitis (NASH). PPARs were found to be one of the major regulators in the progression of NAFLD. There is no recognized treatment for NAFLD, even though numerous clinical trials are now underway. NAFLD is a major risk factor for developing hepatocellular carcinoma (HCC), and its frequency increases as obesity and diabetes become more prevalent. Reprogramming anti-diabetic and anti-obesity drugs is an effective therapy option for NAFLD and NASH. Several studies have also focused on the role of ncRNAs in the pathophysiology of NAFLD. The regulatory effects of these ncRNAs make them a primary target for treatments and as early biomarkers. In this study, the main focus will be to understand the regulation of PPARs through ncRNAs and their role in NAFLD.
A LEXICAL COHESION ANALYSIS ON OSCAR WILDE’S SHORT STORY THE SELFISH GIANT

This article aims to discuss what lexical cohesive devices are applied to a short story The selfish Giant written y Oscar Wilde. Since the data of this article have been collected by reading some books in the library, it is called the library research. Since the data in this article are lexical cohesive devices found in the short story The Selfish Giant, they are called qualitative data. This article uses descriptive method to analyze the data. Through the analysis and the discussion, it is found that there are many lexical items in the short story The Selfish Giant that can be categorized as lexical cohesive devices. The lexical cohesive devices establish the cohesion and coherence in the short story. Repetition plays an important role in making the text coherent and unified. That is why the lexical cohesive device of repetition is frequently used in The Selfish Giant. This repetition creates the relation of meaning in the clauses, so it can build continuity in the text. The continuity that is demonstrated by the repetition shows that there is cohesion in the text. The synonym is the second type of reiteration that is found in The Selfish Giant. The use of the synonym shows two lexical items or more that are similar in meaning. The use of synonym in the text is very helpful to build cohesion because synonym holds the sentences together and gives cohesive effect to the text. The application of lexical cohesive devices makes the text coherent and unified because it links the sentences and helps the readers understand the text. Moreover, the analysis shows that the lexical cohesive device that is most often used to relate sentences in The Selfish Giant is repetition. Therefore, the repetition is claimed as the simplest way of connecting sentences, and of course the repetition plays an important role in making the text coherent and unified. Keywords : Discourse Analysis, Short Story, Lexical Cohesion.
Design and implementation of building crack detection system based convolutional neural network

Buildings are commonly found as important facilities in today's society. How to detect building cracks safely and effectively is a necessary measure to ensure the safety of people's lives and properties. With the emergence of deep learning algorithms, various target detection methods based on convolutional neural network (CNN) models have gradually replaced conventional manual detection methods. In this paper, we design a crack recognition system based on convolutional neural network model for building images collected by UAVs. The experimental structure shows that the system has a good performance and can be further promoted to be applied in the field of safety assessment in the construction industry.
Statistical analysis of query processing time in cache-based cloud database systems

Abstract With the proliferation of data in cloud-based systems, the performance of the data retrieval process from the database management system is becoming indispensable. Caching is one of the techniques to retrieve the data faster. It reduces the number of database accesses for similar queries, which in turn, reduces the processing time. It also facilitates in reducing the load on database servers, which results in the reduction of the overall response time. This paper is based on our caching framework for NOSQL datastores, which seeks to speed up the processing of many requests. The frequently used queries, which are expensive to reevaluate, are cached by this framework on top of a column-based datastore. In order to speed up query processing, certain queries are cached. In this study, query processing times without the influence of the database or system cache are used to evaluate the framework’s performance.
Removal of methylene blue from aqueous solution by magnetic hydrogel nanocomposite absorbents

Currently reported adsorbents for wastewater purification generally have only limited adsorption capacity and low adsorption rate towards dye contaminants. In this work, KH570-modified magnetic hydrogel nanocomposites (KH570-mHNCs) with semi-IPNs structure were prepared based on poly (acrylamide-co-acrylic acid), polyvinyl pyrrolidone (PVP), and KH570-modified magnetic nanoparticles, and it exhibited high absorption capacity and absorption rate for methylene blue dye. KH570-mHNCs had a rough surface with many porous and gully structures, and FTIR results preliminarily confirmed the target structure of KH570-mHNCs. KH570-mHNCs could rapidly absorb methylene blue by approaching absorption equilibrium at 90 min. Dye absorption of KH570-mHNCs had maximum dye absorption capacity at pH = 8, and methylene blue adsorption capacity was 255.4 mg/g, 326.3 mg/g, and 418.5 mg/g in the condition of initial dye concentrations of 700 mg/L, 900 mg/L, and 1100 mg/L, respectively. Methylene blue adsorption isotherms and kinetics conformed to the Langmuir model and pseudo-second-order kinetic model, respectively. Methylene blue adsorption for KH570-mHNCs was a spontaneous, exothermal, and entropy reduction process. In addition, KH570-mHNCs had good magnetic response, desorption, and reusability, which made it a potential application in the field of methylene blue removal from the aqueous solution.
Visualizing the atomic defects by scanning tunneling microscopy in the type-II Dirac semimetal NiTe2

Nickel ditelluride (NiTe2), a newly discovered type-II Dirac semimetal whose Dirac node lies in proximity to the Fermi level, is expected to exhibit exotic phenomena including the pressure-driven Lifshitz transition and novel superconductivity in the monolayer limit. It is known that defects are commonly seen in transition metal dichalcogenides and have remarkable impacts on their optical and electronic properties. However, the systematic study on defects in NiTe2 remains to be explored. Here, by using high-resolution scanning tunneling microscopy combined with the first-principles calculations, the structure and electronic properties of atomic defects in NiTe2 have been systematically investigated. Specifically, we identified five distinct types of atomic defects, involving the vacancy and the intercalation. Our results indicate that the metal intercalation defect is the predominant one due to its lowest formation energy, which differs substantially from the case in MoS2 and PtSe2. It is further revealed that the topological surface states are surprisingly robust against these atomic defects. Our results demonstrate that the electronic properties of NiTe2, especially its topological surface states, are very robust, which may be important for its future applications in microelectronics.
Faster Adaptive Importance Sampling in Low Dimensions

Abstract Adaptive importance sampling using kernel density estimation techniques was introduced by West. This technique adapts the importance sampling function to the underlying integrand, thus yielding small-variance estimates. One drawback of this approach is that evaluation of the kernel mixture density is slow. We present a linear tensor spline representation of the adaptive importance function using variable bandwidth kernels that retains the small variance properties of West's approach but executes more quickly.
Monitoring Land Use/Land Cover Change in Tha Chin River Basin

Land use/ land cover (LULC) changes influence the whole natural system directly or indirectly, so monitoring these changes is essential to balance the natural environment. This research surveyed changes in LULC in the Tha Chin River Basin. Using Google Earth Engine and ArcGIS, Landsat 5 and Landsat 8 Thematic Mapping satellite photos were utilized to identify LULC classes for the years 2000, 2010 and 2020 for the Tha Chin river basin. Fifty training samples for five classes were collected by supervised classification to analyze land cover types in the Tha Chin basin. Among these five classes, the urban area shows a significant change from 2000 to 2020; the second significant change is the forest area. The monitoring of changes in LULC would provide a crucial basis for the region environmental management and integrity in the Tha Chin River Basin.
Active Learning Based Adversary Evasion Attacks Defense for Malwares in the Internet of Things

In this article, we study adversarial evasion attacks in the context of an active learning environment. To prevent evasion attacks in Internet of Things environments, a feature subset selection method is proposed. To train an independent classification model for a single Android application, the approach extracts application-specific data from that application. We compare and evaluate the performance of Android malware benchmarks using ensemble-based active learning, followed by the use of a collaborative machine learning classifier to protect against adversarial evasion attacks on a dataset of Android malware benchmarks. It was found that the proposed approach generates 0.91 receiver operating characteristic with 14 fabricated input features.
Remote Sensing of Cloud-Top Pressure Using Moderately Resolved Measurements within the Oxygen A Band—A Sensitivity Study

Abstract Reflected solar radiation measured by the Medium Resolution Imaging Spectrometer (MERIS) on the Environmental Satellite (Envisat) is currently used within the European Space Agency’s ground segment for the retrieval of cloud-top pressure. The algorithm is based on the analysis of the gaseous absorption of solar radiation in the oxygen A band at 761 nm. The strength of absorption is directly related to the average photon pathlength, which is mainly determined by the cloud-top pressure. However, it additionally depends on surface and cloud properties, like cloud thickness and microphysics. The interpretation of the measurements is further complicated by the temperature dependence of the absorption line shapes and the sensitivity to the spectral properties of the spectrometer like spectral position and width. This paper is focused on results of sensitivity studies using the Matrix Operator Model (MOMO) radiative transfer model that examine the most important parameters affecting the measurements of .
Luminosity Dependent Changes of Pulse Profiles in the X-ray Binary GX 1+4

Abstract We have reviewed the X-ray pulse profiles from a large number of observations of the accreting binary pulsar GX 1+4 obtained during the last 25 years. The profiles cover various energy ranges between 1 and 100 keV. Using these data we present a coherent picture of present and past pulse profiles and the variations of these pulse profiles with time. The pulse shape is dependent on both the X-ray luminosity and whether the pulsar is spinning up or down. Profiles measured during the GX 1+4 high state in the 1970s are all trailing edge bright. Subsequently the profiles have generally been symmetric or leading edge bright. Rossi X-ray Timing Explorer (RXTE) satellite data taken in July 1996 show that similar pulse shape variations can occur on a timescale of hours. The implications of this new information for accretion models is discussed.
LOW-COST MAPPING OF FOREST UNDER-STOREY VEGETATION USING SPHERICAL PHOTOGRAMMETRY

Abstract. This paper is an attempt to respond to the growing need and demand of 3D data in forestry, especially for 3D mapping. The use of terrestrial laser scanners (TLS) dominates contemporary literature for under-storey vegetation mapping as this technique provides precise and easy-to-use solutions for users. However, TLS requires substantial investments in terms of device acquisition and user training. The search for and development of low-cost alternatives is therefore an interesting field of inquiry. Here, we use low-cost 360° cameras combined with spherical photogrammetric principles for under-storey vegetation mapping. While we fully assume that this low-cost approach will not generate results on par with either TLS or classical close-range photogrammetry, its main aim is to investigate whether this alternative is sufficient to meet the requirements of forest mapping. In this regard, geometric analyses were conducted using both TLS and close-range photogrammetry as comparison points. The diameter at breast height (DBH), a parameter commonly used in forestry, was then computed from the 360° point cloud using three different methods to determine if a similar order of precision to the two reference datasets can be obtained. The results show that 360° cameras were able to generate point clouds with a similar geometric quality as the references despite their low density, albeit with a significantly higher amount of noise. The effect of the noise is also evident in the DBH computation, where it yielded an average error of 3.5 cm compared to both the TLS and close-range photogrammetry.